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Zhang CY, Gu T, Xia S, Wang Y, Li J. [Salivary carcinoma showing thymus-like differentiation: clinicopathological analysis of 7 cases]. Zhonghua Kou Qiang Yi Xue Za Zhi 2024; 59:480-486. [PMID: 38637002 DOI: 10.3760/cma.j.cn112144-20231211-00290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/20/2024]
Abstract
Objective: To analyze the clinicopathological features of salivary carcinoma with thymus-like differentiation(CASTLE). Methods: Cases diagnosed with salivary CASTLE from January 2020 to December 2023 were collected and selected from the Department of Oral Pathology, Shanghai Ninth People's Hospital,Shanghai Jiao Tong University School of Medicine. A total of 7 cases of salivary CASTLE were identified. All the cases originated from parotid. There were 3 males and 4 females. The patients' age range was 11-70 years.The clinical, microscopic, immunohistochemical and prognostic features of these cases were analyzed. Results: The duration of disease ranged from 1 month to 1 year, and 1 patient had facial numbness and 1 with swelling sensation occasionally. Radiographically, 4 cases showed malignant signs. Microscopically, 4 cases involved in parotid gland, and all the tumors had different degrees of lymphoid tissue background. The tumor cells arranged in nests, 5 cases with lymphoepithelial carcinoma-like and 2 cases with squamous cell carcinoma morphology. The tumor cells expressed CD5 and CD117 proteins diffusely in lymphoepithelial carcinoma-like cases. However, the tumor cells expressed CD5 diffusely and CD117 focally in cases with squamous cell carcinoma morphology. All the cases had no Epstein-Barr virus infection. Among the 6 patients with follow-up information, all of them underwent postoperative radiotherapy, and none of them had local recurrence and lymph node metastasis. Conclusions: Salivary CASTLE is a rare tumor, it should be distinguished from lymphoepithelial carcinoma and squamous cell carcinoma. The patients often have better prognosis and CD5 protein expression has a valuable role in the differential diagnosis.
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Affiliation(s)
- C Y Zhang
- Department of Oral Pathology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine & College of Stomatology, Shanghai Jiao Tong University & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai 200011, China
| | - T Gu
- Department of Oral Pathology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine & College of Stomatology, Shanghai Jiao Tong University & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai 200011, China
| | - S Xia
- Department of Oral Pathology, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210018, China
| | - Y Wang
- Department of Oral Pathology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine & College of Stomatology, Shanghai Jiao Tong University & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai 200011, China
| | - J Li
- Department of Oral Pathology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine & College of Stomatology, Shanghai Jiao Tong University & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai 200011, China
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Jian T, Yang M, Wu T, Ji X, Xia S, Sun F. Diagnostic value of dynamic contrast enhancement combined with conventional MRI in differentiating benign and malignant lacrimal gland epithelial tumours. Clin Radiol 2024; 79:e345-e352. [PMID: 37953093 DOI: 10.1016/j.crad.2023.10.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 10/13/2023] [Accepted: 10/16/2023] [Indexed: 11/14/2023]
Abstract
AIM To establish the diagnostic value of the quantitative parameters of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) combined with conventional MRI in differentiating of benign and malignant lacrimal gland epithelial tumours. MATERIALS AND METHODS A retrospective analysis of primary lacrimal gland epithelial tumours confirmed by histopathology was conducted. Conventional MRI features and DCE-MRI quantitative parameters were collected and subjected to analysis. The diagnostic value was evaluated using receiver operating characteristic (ROC) curve analysis. RESULTS A total of 53 patients were enrolled of which 29 had malignant, whereas 24 had benign tumours. Conventional MRI revealed statistically significant differences between benign and malignant tumours regarding maximum tumour diameter, posterior margin characteristic, bone destruction, and erosion. The Ktrans and Kep values obtained by DCE-MRI were higher in malignant than in benign tumours, with a statistically significant (p<0.001 and p=0.022). A type I time-signal intensity (TIC) curve was more frequent in benign tumours, whereas a type II TIC curve was prevalent in malignant tumours (p=0.001). ROC analysis showed that Ktrans had the best diagnostic value of the DCE-MRI parameters (area under the ROC curve [AUC] of 0.822, 75.9% sensitivity, and 83.3% specificity, p<0.001). The combination of conventional MRI and DCE-MRI factors had the best diagnostic value and balanced sensitivity and specificity (AUC of 0.948, 93.1% sensitivity, and 91.7% specificity, p<0.001). CONCLUSIONS The present findings indicate that the combination of quantitative parameters of DCE-MRI and image characteristics of conventional MRI have a high diagnostic value for the diagnosis of benign and malignant lacrimal gland epithelial tumours.
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Affiliation(s)
- T Jian
- Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, Tianjin, China
| | - M Yang
- Department of Ophthalmology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Taizhou, China
| | - T Wu
- Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, Tianjin, China
| | - X Ji
- Department of Radiology, Tianjin First Central Hospital, Tianjin, China
| | - S Xia
- Department of Radiology, Tianjin First Central Hospital, Tianjin, China
| | - F Sun
- Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, Tianjin, China.
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Staplin N, Haynes R, Judge PK, Wanner C, Green JB, Emberson J, Preiss D, Mayne KJ, Ng SYA, Sammons E, Zhu D, Hill M, Stevens W, Wallendszus K, Brenner S, Cheung AK, Liu ZH, Li J, Hooi LS, Liu WJ, Kadowaki T, Nangaku M, Levin A, Cherney D, Maggioni AP, Pontremoli R, Deo R, Goto S, Rossello X, Tuttle KR, Steubl D, Petrini M, Seidi S, Landray MJ, Baigent C, Herrington WG, Abat S, Abd Rahman R, Abdul Cader R, Abdul Hafidz MI, Abdul Wahab MZ, Abdullah NK, Abdul-Samad T, Abe M, Abraham N, Acheampong S, Achiri P, Acosta JA, Adeleke A, Adell V, Adewuyi-Dalton R, Adnan N, Africano A, Agharazii M, Aguilar F, Aguilera A, Ahmad M, Ahmad MK, Ahmad NA, Ahmad NH, Ahmad NI, Ahmad Miswan N, Ahmad Rosdi H, Ahmed I, Ahmed S, Ahmed S, Aiello J, Aitken A, AitSadi R, Aker S, Akimoto S, Akinfolarin A, Akram S, Alberici F, Albert C, Aldrich L, Alegata M, Alexander L, Alfaress S, Alhadj Ali M, Ali A, Ali A, Alicic R, Aliu A, Almaraz R, Almasarwah R, Almeida J, Aloisi A, Al-Rabadi L, Alscher D, Alvarez P, Al-Zeer B, Amat M, Ambrose C, Ammar H, An Y, Andriaccio L, Ansu K, Apostolidi A, Arai N, Araki H, Araki S, Arbi A, Arechiga O, Armstrong S, Arnold T, Aronoff S, Arriaga W, Arroyo J, Arteaga D, Asahara S, Asai A, Asai N, Asano S, Asawa M, Asmee MF, Aucella F, Augustin M, Avery A, Awad A, Awang IY, Awazawa M, Axler A, Ayub W, Azhari Z, Baccaro R, Badin C, Bagwell B, Bahlmann-Kroll E, Bahtar AZ, Baigent C, Bains D, Bajaj H, Baker R, Baldini E, Banas B, Banerjee D, Banno S, Bansal S, Barberi S, Barnes S, Barnini C, Barot C, Barrett K, Barrios R, Bartolomei Mecatti B, Barton I, Barton J, Basily W, Bavanandan S, Baxter A, Becker L, Beddhu S, Beige J, Beigh S, Bell S, Benck U, Beneat A, Bennett A, Bennett D, Benyon S, Berdeprado J, Bergler T, Bergner A, Berry M, Bevilacqua M, Bhairoo J, Bhandari S, Bhandary N, Bhatt A, Bhattarai M, Bhavsar M, Bian W, Bianchini F, Bianco S, Bilous R, Bilton J, Bilucaglia D, Bird C, Birudaraju D, Biscoveanu M, Blake C, Bleakley N, Bocchicchia K, Bodine S, Bodington R, Boedecker S, Bolduc M, Bolton S, Bond C, Boreky F, Boren K, Bouchi R, Bough L, Bovan D, Bowler C, Bowman L, Brar N, Braun C, Breach A, Breitenfeldt M, Brenner S, Brettschneider B, Brewer A, Brewer G, Brindle V, Brioni E, Brown C, Brown H, Brown L, Brown R, Brown S, Browne D, Bruce K, Brueckmann M, Brunskill N, Bryant M, Brzoska M, Bu Y, Buckman C, Budoff M, Bullen M, Burke A, Burnette S, Burston C, Busch M, Bushnell J, Butler S, Büttner C, Byrne C, Caamano A, Cadorna J, Cafiero C, Cagle M, Cai J, Calabrese K, Calvi C, Camilleri B, Camp S, Campbell D, Campbell R, Cao H, Capelli I, Caple M, Caplin B, Cardone A, Carle J, Carnall V, Caroppo M, Carr S, Carraro G, Carson M, Casares P, Castillo C, Castro C, Caudill B, Cejka V, Ceseri M, Cham L, Chamberlain A, Chambers J, Chan CBT, Chan JYM, Chan YC, Chang E, Chang E, Chant T, Chavagnon T, Chellamuthu P, Chen F, Chen J, Chen P, Chen TM, Chen Y, Chen Y, Cheng C, Cheng H, Cheng MC, Cherney D, Cheung AK, Ching CH, Chitalia N, Choksi R, Chukwu C, Chung K, Cianciolo G, Cipressa L, Clark S, Clarke H, Clarke R, Clarke S, Cleveland B, Cole E, Coles H, Condurache L, Connor A, Convery K, Cooper A, Cooper N, Cooper Z, Cooperman L, Cosgrove L, Coutts P, Cowley A, Craik R, Cui G, Cummins T, Dahl N, Dai H, Dajani L, D'Amelio A, Damian E, Damianik K, Danel L, Daniels C, Daniels T, Darbeau S, Darius H, Dasgupta T, Davies J, Davies L, Davis A, Davis J, Davis L, Dayanandan R, Dayi S, Dayrell R, De Nicola L, Debnath S, Deeb W, Degenhardt S, DeGoursey K, Delaney M, Deo R, DeRaad R, Derebail V, Dev D, Devaux M, Dhall P, Dhillon G, Dienes J, Dobre M, Doctolero E, Dodds V, Domingo D, Donaldson D, Donaldson P, Donhauser C, Donley V, Dorestin S, Dorey S, Doulton T, Draganova D, Draxlbauer K, Driver F, Du H, Dube F, Duck T, Dugal T, Dugas J, Dukka H, Dumann H, Durham W, Dursch M, Dykas R, Easow R, Eckrich E, Eden G, Edmerson E, Edwards H, Ee LW, Eguchi J, Ehrl Y, Eichstadt K, Eid W, Eilerman B, Ejima Y, Eldon H, Ellam T, Elliott L, Ellison R, Emberson J, Epp R, Er A, Espino-Obrero M, Estcourt S, Estienne L, Evans G, Evans J, Evans S, Fabbri G, Fajardo-Moser M, Falcone C, Fani F, Faria-Shayler P, Farnia F, Farrugia D, Fechter M, Fellowes D, Feng F, Fernandez J, Ferraro P, Field A, Fikry S, Finch J, Finn H, Fioretto P, Fish R, Fleischer A, Fleming-Brown D, Fletcher L, Flora R, Foellinger C, Foligno N, Forest S, Forghani Z, Forsyth K, Fottrell-Gould D, Fox P, Frankel A, Fraser D, Frazier R, Frederick K, Freking N, French H, Froment A, Fuchs B, Fuessl L, Fujii H, Fujimoto A, Fujita A, Fujita K, Fujita Y, Fukagawa M, Fukao Y, Fukasawa A, Fuller T, Funayama T, Fung E, Furukawa M, Furukawa Y, Furusho M, Gabel S, Gaidu J, Gaiser S, Gallo K, Galloway C, Gambaro G, Gan CC, Gangemi C, Gao M, Garcia K, Garcia M, Garofalo C, Garrity M, Garza A, Gasko S, Gavrila M, Gebeyehu B, Geddes A, Gentile G, George A, George J, Gesualdo L, Ghalli F, Ghanem A, Ghate T, Ghavampour S, Ghazi A, Gherman A, Giebeln-Hudnell U, Gill B, Gillham S, Girakossyan I, Girndt M, Giuffrida A, Glenwright M, Glider T, Gloria R, Glowski D, Goh BL, Goh CB, Gohda T, Goldenberg R, Goldfaden R, Goldsmith C, Golson B, Gonce V, Gong Q, Goodenough B, Goodwin N, Goonasekera M, Gordon A, Gordon J, Gore A, Goto H, Goto S, Goto S, Gowen D, Grace A, Graham J, Grandaliano G, Gray M, Green JB, Greene T, Greenwood G, Grewal B, Grifa R, Griffin D, Griffin S, Grimmer P, Grobovaite E, Grotjahn S, Guerini A, Guest C, Gunda S, Guo B, Guo Q, Haack S, Haase M, Haaser K, Habuki K, Hadley A, Hagan S, Hagge S, Haller H, Ham S, Hamal S, Hamamoto Y, Hamano N, Hamm M, Hanburry A, Haneda M, Hanf C, Hanif W, Hansen J, Hanson L, Hantel S, Haraguchi T, Harding E, Harding T, Hardy C, Hartner C, Harun Z, Harvill L, Hasan A, Hase H, Hasegawa F, Hasegawa T, Hashimoto A, Hashimoto C, Hashimoto M, Hashimoto S, Haskett S, Hauske SJ, Hawfield A, Hayami T, Hayashi M, Hayashi S, Haynes R, Hazara A, Healy C, Hecktman J, Heine G, Henderson H, Henschel R, Hepditch A, Herfurth K, Hernandez G, Hernandez Pena A, Hernandez-Cassis C, Herrington WG, Herzog C, Hewins S, Hewitt D, Hichkad L, Higashi S, Higuchi C, Hill C, Hill L, Hill M, Himeno T, Hing A, Hirakawa Y, Hirata K, Hirota Y, Hisatake T, Hitchcock S, Hodakowski A, Hodge W, Hogan R, Hohenstatt U, Hohenstein B, Hooi L, Hope S, Hopley M, Horikawa S, Hosein D, Hosooka T, Hou L, Hou W, Howie L, Howson A, Hozak M, Htet Z, Hu X, Hu Y, Huang J, Huda N, Hudig L, Hudson A, Hugo C, Hull R, Hume L, Hundei W, Hunt N, Hunter A, Hurley S, Hurst A, Hutchinson C, Hyo T, Ibrahim FH, Ibrahim S, Ihana N, Ikeda T, Imai A, Imamine R, Inamori A, Inazawa H, Ingell J, Inomata K, Inukai Y, Ioka M, Irtiza-Ali A, Isakova T, Isari W, Iselt M, Ishiguro A, Ishihara K, Ishikawa T, Ishimoto T, Ishizuka K, Ismail R, Itano S, Ito H, Ito K, Ito M, Ito Y, Iwagaitsu S, Iwaita Y, Iwakura T, Iwamoto M, Iwasa M, Iwasaki H, Iwasaki S, Izumi K, Izumi K, Izumi T, Jaafar SM, Jackson C, Jackson Y, Jafari G, Jahangiriesmaili M, Jain N, Jansson K, Jasim H, Jeffers L, Jenkins A, Jesky M, Jesus-Silva J, Jeyarajah D, Jiang Y, Jiao X, Jimenez G, Jin B, Jin Q, Jochims J, Johns B, Johnson C, Johnson T, Jolly S, Jones L, Jones L, Jones S, Jones T, Jones V, Joseph M, Joshi S, Judge P, Junejo N, Junus S, Kachele M, Kadowaki T, Kadoya H, Kaga H, Kai H, Kajio H, Kaluza-Schilling W, Kamaruzaman L, Kamarzarian A, Kamimura Y, Kamiya H, Kamundi C, Kan T, Kanaguchi Y, Kanazawa A, Kanda E, Kanegae S, Kaneko K, Kaneko K, Kang HY, Kano T, Karim M, Karounos D, Karsan W, Kasagi R, Kashihara N, Katagiri H, Katanosaka A, Katayama A, Katayama M, Katiman E, Kato K, Kato M, Kato N, Kato S, Kato T, Kato Y, Katsuda Y, Katsuno T, Kaufeld J, Kavak Y, Kawai I, Kawai M, Kawai M, Kawase A, Kawashima S, Kazory A, Kearney J, Keith B, Kellett J, Kelley S, Kershaw M, Ketteler M, Khai Q, Khairullah Q, Khandwala H, Khoo KKL, Khwaja A, Kidokoro K, Kielstein J, Kihara M, Kimber C, Kimura S, Kinashi H, Kingston H, Kinomura M, Kinsella-Perks E, Kitagawa M, Kitajima M, Kitamura S, Kiyosue A, Kiyota M, Klauser F, Klausmann G, Kmietschak W, Knapp K, Knight C, Knoppe A, Knott C, Kobayashi M, Kobayashi R, Kobayashi T, Koch M, Kodama S, Kodani N, Kogure E, Koizumi M, Kojima H, Kojo T, Kolhe N, Komaba H, Komiya T, Komori H, Kon SP, Kondo M, Kondo M, Kong W, Konishi M, Kono K, Koshino M, Kosugi T, Kothapalli B, Kozlowski T, Kraemer B, Kraemer-Guth A, Krappe J, Kraus D, Kriatselis C, Krieger C, Krish P, Kruger B, Ku Md Razi KR, Kuan Y, Kubota S, Kuhn S, Kumar P, Kume S, Kummer I, Kumuji R, Küpper A, Kuramae T, Kurian L, Kuribayashi C, Kurien R, Kuroda E, Kurose T, Kutschat A, Kuwabara N, Kuwata H, La Manna G, Lacey M, Lafferty K, LaFleur P, Lai V, Laity E, Lambert A, Landray MJ, Langlois M, Latif F, Latore E, Laundy E, Laurienti D, Lawson A, Lay M, Leal I, Leal I, Lee AK, Lee J, Lee KQ, Lee R, Lee SA, Lee YY, Lee-Barkey Y, Leonard N, Leoncini G, Leong CM, Lerario S, Leslie A, Levin A, Lewington A, Li J, Li N, Li X, Li Y, Liberti L, Liberti ME, Liew A, Liew YF, Lilavivat U, Lim SK, Lim YS, Limon E, Lin H, Lioudaki E, Liu H, Liu J, Liu L, Liu Q, Liu WJ, Liu X, Liu Z, Loader D, Lochhead H, Loh CL, Lorimer A, Loudermilk L, Loutan J, Low CK, Low CL, Low YM, Lozon Z, Lu Y, Lucci D, Ludwig U, Luker N, Lund D, Lustig R, Lyle S, Macdonald C, MacDougall I, Machicado R, MacLean D, Macleod P, Madera A, Madore F, Maeda K, Maegawa H, Maeno S, Mafham M, Magee J, Maggioni AP, Mah DY, Mahabadi V, Maiguma M, Makita Y, Makos G, Manco L, Mangiacapra R, Manley J, Mann P, Mano S, Marcotte G, Maris J, Mark P, Markau S, Markovic M, Marshall C, Martin M, Martinez C, Martinez S, Martins G, Maruyama K, Maruyama S, Marx K, Maselli A, Masengu A, Maskill A, Masumoto S, Masutani K, Matsumoto M, Matsunaga T, Matsuoka N, Matsushita M, Matthews M, Matthias S, Matvienko E, Maurer M, Maxwell P, Mayne KJ, Mazlan N, Mazlan SA, Mbuyisa A, McCafferty K, McCarroll F, McCarthy T, McClary-Wright C, McCray K, McDermott P, McDonald C, McDougall R, McHaffie E, McIntosh K, McKinley T, McLaughlin S, McLean N, McNeil L, Measor A, Meek J, Mehta A, Mehta R, Melandri M, Mené P, Meng T, Menne J, Merritt K, Merscher S, Meshykhi C, Messa P, Messinger L, Miftari N, Miller R, Miller Y, Miller-Hodges E, Minatoguchi M, Miners M, Minutolo R, Mita T, Miura Y, Miyaji M, Miyamoto S, Miyatsuka T, Miyazaki M, Miyazawa I, Mizumachi R, Mizuno M, Moffat S, Mohamad Nor FS, Mohamad Zaini SN, Mohamed Affandi FA, Mohandas C, Mohd R, Mohd Fauzi NA, Mohd Sharif NH, Mohd Yusoff Y, Moist L, Moncada A, Montasser M, Moon A, Moran C, Morgan N, Moriarty J, Morig G, Morinaga H, Morino K, Morisaki T, Morishita Y, Morlok S, Morris A, Morris F, Mostafa S, Mostefai Y, Motegi M, Motherwell N, Motta D, Mottl A, Moys R, Mozaffari S, Muir J, Mulhern J, Mulligan S, Munakata Y, Murakami C, Murakoshi M, Murawska A, Murphy K, Murphy L, Murray S, Murtagh H, Musa MA, Mushahar L, Mustafa R, Mustafar R, Muto M, Nadar E, Nagano R, Nagasawa T, Nagashima E, Nagasu H, Nagelberg S, Nair H, Nakagawa Y, Nakahara M, Nakamura J, Nakamura R, Nakamura T, Nakaoka M, Nakashima E, Nakata J, Nakata M, Nakatani S, Nakatsuka A, Nakayama Y, Nakhoul G, Nangaku M, Naverrete G, Navivala A, Nazeer I, Negrea L, Nethaji C, Newman E, Ng SYA, Ng TJ, Ngu LLS, Nimbkar T, Nishi H, Nishi M, Nishi S, Nishida Y, Nishiyama A, Niu J, Niu P, Nobili G, Nohara N, Nojima I, Nolan J, Nosseir H, Nozawa M, Nunn M, Nunokawa S, Oda M, Oe M, Oe Y, Ogane K, Ogawa W, Ogihara T, Oguchi G, Ohsugi M, Oishi K, Okada Y, Okajyo J, Okamoto S, Okamura K, Olufuwa O, Oluyombo R, Omata A, Omori Y, Ong LM, Ong YC, Onyema J, Oomatia A, Oommen A, Oremus R, Orimo Y, Ortalda V, Osaki Y, Osawa Y, Osmond Foster J, O'Sullivan A, Otani T, Othman N, Otomo S, O'Toole J, Owen L, Ozawa T, Padiyar A, Page N, Pajak S, Paliege A, Pandey A, Pandey R, Pariani H, Park J, Parrigon M, Passauer J, Patecki M, Patel M, Patel R, Patel T, Patel Z, Paul R, Paul R, Paulsen L, Pavone L, Peixoto A, Peji J, Peng BC, Peng K, Pennino L, Pereira E, Perez E, Pergola P, Pesce F, Pessolano G, Petchey W, Petr EJ, Pfab T, Phelan P, Phillips R, Phillips T, Phipps M, Piccinni G, Pickett T, Pickworth S, Piemontese M, Pinto D, Piper J, Plummer-Morgan J, Poehler D, Polese L, Poma V, Pontremoli R, Postal A, Pötz C, Power A, Pradhan N, Pradhan R, Preiss D, Preiss E, Preston K, Prib N, Price L, Provenzano C, Pugay C, Pulido R, Putz F, Qiao Y, Quartagno R, Quashie-Akponeware M, Rabara R, Rabasa-Lhoret R, Radhakrishnan D, Radley M, Raff R, Raguwaran S, Rahbari-Oskoui F, Rahman M, Rahmat K, Ramadoss S, Ramanaidu S, Ramasamy S, Ramli R, Ramli S, Ramsey T, Rankin A, Rashidi A, Raymond L, Razali WAFA, Read K, Reiner H, Reisler A, Reith C, Renner J, Rettenmaier B, Richmond L, Rijos D, Rivera R, Rivers V, Robinson H, Rocco M, Rodriguez-Bachiller I, Rodriquez R, Roesch C, Roesch J, Rogers J, Rohnstock M, Rolfsmeier S, Roman M, Romo A, Rosati A, Rosenberg S, Ross T, Rossello X, Roura M, Roussel M, Rovner S, Roy S, Rucker S, Rump L, Ruocco M, Ruse S, Russo F, Russo M, Ryder M, Sabarai A, Saccà C, Sachson R, Sadler E, Safiee NS, Sahani M, Saillant A, Saini J, Saito C, Saito S, Sakaguchi K, Sakai M, Salim H, Salviani C, Sammons E, Sampson A, Samson F, Sandercock P, Sanguila S, Santorelli G, Santoro D, Sarabu N, Saram T, Sardell R, Sasajima H, Sasaki T, Satko S, Sato A, Sato D, Sato H, Sato H, Sato J, Sato T, Sato Y, Satoh M, Sawada K, Schanz M, Scheidemantel F, Schemmelmann M, Schettler E, Schettler V, Schlieper GR, Schmidt C, Schmidt G, Schmidt U, Schmidt-Gurtler H, Schmude M, Schneider A, Schneider I, Schneider-Danwitz C, Schomig M, Schramm T, Schreiber A, Schricker S, Schroppel B, Schulte-Kemna L, Schulz E, Schumacher B, Schuster A, Schwab A, Scolari F, Scott A, Seeger W, Seeger W, Segal M, Seifert L, Seifert M, Sekiya M, Sellars R, Seman MR, Shah S, Shah S, Shainberg L, Shanmuganathan M, Shao F, Sharma K, Sharpe C, Sheikh-Ali M, Sheldon J, Shenton C, Shepherd A, Shepperd M, Sheridan R, Sheriff Z, Shibata Y, Shigehara T, Shikata K, Shimamura K, Shimano H, Shimizu Y, Shimoda H, Shin K, Shivashankar G, Shojima N, Silva R, Sim CSB, Simmons K, Sinha S, Sitter T, Sivanandam S, Skipper M, Sloan K, Sloan L, Smith R, Smyth J, Sobande T, Sobata M, Somalanka S, Song X, Sonntag F, Sood B, Sor SY, Soufer J, Sparks H, Spatoliatore G, Spinola T, Squyres S, Srivastava A, Stanfield J, Staplin N, Staylor K, Steele A, Steen O, Steffl D, Stegbauer J, Stellbrink C, Stellbrink E, Stevens W, Stevenson A, Stewart-Ray V, Stickley J, Stoffler D, Stratmann B, Streitenberger S, Strutz F, Stubbs J, Stumpf J, Suazo N, Suchinda P, Suckling R, Sudin A, Sugamori K, Sugawara H, Sugawara K, Sugimoto D, Sugiyama H, Sugiyama H, Sugiyama T, Sullivan M, Sumi M, Suresh N, Sutton D, Suzuki H, Suzuki R, Suzuki Y, Suzuki Y, Suzuki Y, Swanson E, Swift P, Syed S, Szerlip H, Taal M, Taddeo M, Tailor C, Tajima K, Takagi M, Takahashi K, Takahashi K, Takahashi M, Takahashi T, Takahira E, Takai T, Takaoka M, Takeoka J, Takesada A, Takezawa M, Talbot M, Taliercio J, Talsania T, Tamori Y, Tamura R, Tamura Y, Tan CHH, Tan EZZ, Tanabe A, Tanabe K, Tanaka A, Tanaka A, Tanaka N, Tang S, Tang Z, Tanigaki K, Tarlac M, Tatsuzawa A, Tay JF, Tay LL, Taylor J, Taylor K, Taylor K, Te A, Tenbusch L, Teng KS, Terakawa A, Terry J, Tham ZD, Tholl S, Thomas G, Thong KM, Tietjen D, Timadjer A, Tindall H, Tipper S, Tobin K, Toda N, Tokuyama A, Tolibas M, Tomita A, Tomita T, Tomlinson J, Tonks L, Topf J, Topping S, Torp A, Torres A, Totaro F, Toth P, Toyonaga Y, Tripodi F, Trivedi K, Tropman E, Tschope D, Tse J, Tsuji K, Tsunekawa S, Tsunoda R, Tucky B, Tufail S, Tuffaha A, Turan E, Turner H, Turner J, Turner M, Tuttle KR, Tye YL, Tyler A, Tyler J, Uchi H, Uchida H, Uchida T, Uchida T, Udagawa T, Ueda S, Ueda Y, Ueki K, Ugni S, Ugwu E, Umeno R, Unekawa C, Uozumi K, Urquia K, Valleteau A, Valletta C, van Erp R, Vanhoy C, Varad V, Varma R, Varughese A, Vasquez P, Vasseur A, Veelken R, Velagapudi C, Verdel K, Vettoretti S, Vezzoli G, Vielhauer V, Viera R, Vilar E, Villaruel S, Vinall L, Vinathan J, Visnjic M, Voigt E, von-Eynatten M, Vourvou M, Wada J, Wada J, Wada T, Wada Y, Wakayama K, Wakita Y, Wallendszus K, Walters T, Wan Mohamad WH, Wang L, Wang W, Wang X, Wang X, Wang Y, Wanner C, Wanninayake S, Watada H, Watanabe K, Watanabe K, Watanabe M, Waterfall H, Watkins D, Watson S, Weaving L, Weber B, Webley Y, Webster A, Webster M, Weetman M, Wei W, Weihprecht H, Weiland L, Weinmann-Menke J, Weinreich T, Wendt R, Weng Y, Whalen M, Whalley G, Wheatley R, Wheeler A, Wheeler J, Whelton P, White K, Whitmore B, Whittaker S, Wiebel J, Wiley J, Wilkinson L, Willett M, Williams A, Williams E, Williams K, Williams T, Wilson A, Wilson P, Wincott L, Wines E, Winkelmann B, Winkler M, Winter-Goodwin B, Witczak J, Wittes J, Wittmann M, Wolf G, Wolf L, Wolfling R, Wong C, Wong E, Wong HS, Wong LW, Wong YH, Wonnacott A, Wood A, Wood L, Woodhouse H, Wooding N, Woodman A, Wren K, Wu J, Wu P, Xia S, Xiao H, Xiao X, Xie Y, Xu C, Xu Y, Xue H, Yahaya H, Yalamanchili H, Yamada A, Yamada N, Yamagata K, Yamaguchi M, Yamaji Y, Yamamoto A, Yamamoto S, Yamamoto S, Yamamoto T, Yamanaka A, Yamano T, Yamanouchi Y, Yamasaki N, Yamasaki Y, Yamasaki Y, Yamashita C, Yamauchi T, Yan Q, Yanagisawa E, Yang F, Yang L, Yano S, Yao S, Yao Y, Yarlagadda S, Yasuda Y, Yiu V, Yokoyama T, Yoshida S, Yoshidome E, Yoshikawa H, Young A, Young T, Yousif V, Yu H, Yu Y, Yuasa K, Yusof N, Zalunardo N, Zander B, Zani R, Zappulo F, Zayed M, Zemann B, Zettergren P, Zhang H, Zhang L, Zhang L, Zhang N, Zhang X, Zhao J, Zhao L, Zhao S, Zhao Z, Zhong H, Zhou N, Zhou S, Zhu D, Zhu L, Zhu S, Zietz M, Zippo M, Zirino F, Zulkipli FH. Effects of empagliflozin on progression of chronic kidney disease: a prespecified secondary analysis from the empa-kidney trial. Lancet Diabetes Endocrinol 2024; 12:39-50. [PMID: 38061371 PMCID: PMC7615591 DOI: 10.1016/s2213-8587(23)00321-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 10/24/2023] [Accepted: 10/25/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND Sodium-glucose co-transporter-2 (SGLT2) inhibitors reduce progression of chronic kidney disease and the risk of cardiovascular morbidity and mortality in a wide range of patients. However, their effects on kidney disease progression in some patients with chronic kidney disease are unclear because few clinical kidney outcomes occurred among such patients in the completed trials. In particular, some guidelines stratify their level of recommendation about who should be treated with SGLT2 inhibitors based on diabetes status and albuminuria. We aimed to assess the effects of empagliflozin on progression of chronic kidney disease both overall and among specific types of participants in the EMPA-KIDNEY trial. METHODS EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA), and included individuals aged 18 years or older with an estimated glomerular filtration rate (eGFR) of 20 to less than 45 mL/min per 1·73 m2, or with an eGFR of 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher. We explored the effects of 10 mg oral empagliflozin once daily versus placebo on the annualised rate of change in estimated glomerular filtration rate (eGFR slope), a tertiary outcome. We studied the acute slope (from randomisation to 2 months) and chronic slope (from 2 months onwards) separately, using shared parameter models to estimate the latter. Analyses were done in all randomly assigned participants by intention to treat. EMPA-KIDNEY is registered at ClinicalTrials.gov, NCT03594110. FINDINGS Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and then followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroups of eGFR included 2282 (34·5%) participants with an eGFR of less than 30 mL/min per 1·73 m2, 2928 (44·3%) with an eGFR of 30 to less than 45 mL/min per 1·73 m2, and 1399 (21·2%) with an eGFR 45 mL/min per 1·73 m2 or higher. Prespecified subgroups of uACR included 1328 (20·1%) with a uACR of less than 30 mg/g, 1864 (28·2%) with a uACR of 30 to 300 mg/g, and 3417 (51·7%) with a uACR of more than 300 mg/g. Overall, allocation to empagliflozin caused an acute 2·12 mL/min per 1·73 m2 (95% CI 1·83-2·41) reduction in eGFR, equivalent to a 6% (5-6) dip in the first 2 months. After this, it halved the chronic slope from -2·75 to -1·37 mL/min per 1·73 m2 per year (relative difference 50%, 95% CI 42-58). The absolute and relative benefits of empagliflozin on the magnitude of the chronic slope varied significantly depending on diabetes status and baseline levels of eGFR and uACR. In particular, the absolute difference in chronic slopes was lower in patients with lower baseline uACR, but because this group progressed more slowly than those with higher uACR, this translated to a larger relative difference in chronic slopes in this group (86% [36-136] reduction in the chronic slope among those with baseline uACR <30 mg/g compared with a 29% [19-38] reduction for those with baseline uACR ≥2000 mg/g; ptrend<0·0001). INTERPRETATION Empagliflozin slowed the rate of progression of chronic kidney disease among all types of participant in the EMPA-KIDNEY trial, including those with little albuminuria. Albuminuria alone should not be used to determine whether to treat with an SGLT2 inhibitor. FUNDING Boehringer Ingelheim and Eli Lilly.
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Judge PK, Staplin N, Mayne KJ, Wanner C, Green JB, Hauske SJ, Emberson JR, Preiss D, Ng SYA, Roddick AJ, Sammons E, Zhu D, Hill M, Stevens W, Wallendszus K, Brenner S, Cheung AK, Liu ZH, Li J, Hooi LS, Liu WJ, Kadowaki T, Nangaku M, Levin A, Cherney D, Maggioni AP, Pontremoli R, Deo R, Goto S, Rossello X, Tuttle KR, Steubl D, Massey D, Landray MJ, Baigent C, Haynes R, Herrington WG, Abat S, Abd Rahman R, Abdul Cader R, Abdul Hafidz MI, Abdul Wahab MZ, Abdullah NK, Abdul-Samad T, Abe M, Abraham N, Acheampong S, Achiri P, Acosta JA, Adeleke A, Adell V, Adewuyi-Dalton R, Adnan N, Africano A, Agharazii M, Aguilar F, Aguilera A, Ahmad M, Ahmad MK, Ahmad NA, Ahmad NH, Ahmad NI, Ahmad Miswan N, Ahmad Rosdi H, Ahmed I, Ahmed S, Ahmed S, Aiello J, Aitken A, AitSadi R, Aker S, Akimoto S, Akinfolarin A, Akram S, Alberici F, Albert C, Aldrich L, Alegata M, Alexander L, Alfaress S, Alhadj Ali M, Ali A, Ali A, Alicic R, Aliu A, Almaraz R, Almasarwah R, Almeida J, Aloisi A, Al-Rabadi L, Alscher D, Alvarez P, Al-Zeer B, Amat M, Ambrose C, Ammar H, An Y, Andriaccio L, Ansu K, Apostolidi A, Arai N, Araki H, Araki S, Arbi A, Arechiga O, Armstrong S, Arnold T, Aronoff S, Arriaga W, Arroyo J, Arteaga D, Asahara S, Asai A, Asai N, Asano S, Asawa M, Asmee MF, Aucella F, Augustin M, Avery A, Awad A, Awang IY, Awazawa M, Axler A, Ayub W, Azhari Z, Baccaro R, Badin C, Bagwell B, Bahlmann-Kroll E, Bahtar AZ, Baigent C, Bains D, Bajaj H, Baker R, Baldini E, Banas B, Banerjee D, Banno S, Bansal S, Barberi S, Barnes S, Barnini C, Barot C, Barrett K, Barrios R, Bartolomei Mecatti B, Barton I, Barton J, Basily W, Bavanandan S, Baxter A, Becker L, Beddhu S, Beige J, Beigh S, Bell S, Benck U, Beneat A, Bennett A, Bennett D, Benyon S, Berdeprado J, Bergler T, Bergner A, Berry M, Bevilacqua M, Bhairoo J, Bhandari S, Bhandary N, Bhatt A, Bhattarai M, Bhavsar M, Bian W, Bianchini F, Bianco S, Bilous R, Bilton J, Bilucaglia D, Bird C, Birudaraju D, Biscoveanu M, Blake C, Bleakley N, Bocchicchia K, Bodine S, Bodington R, Boedecker S, Bolduc M, Bolton S, Bond C, Boreky F, Boren K, Bouchi R, Bough L, Bovan D, Bowler C, Bowman L, Brar N, Braun C, Breach A, Breitenfeldt M, Brenner S, Brettschneider B, Brewer A, Brewer G, Brindle V, Brioni E, Brown C, Brown H, Brown L, Brown R, Brown S, Browne D, Bruce K, Brueckmann M, Brunskill N, Bryant M, Brzoska M, Bu Y, Buckman C, Budoff M, Bullen M, Burke A, Burnette S, Burston C, Busch M, Bushnell J, Butler S, Büttner C, Byrne C, Caamano A, Cadorna J, Cafiero C, Cagle M, Cai J, Calabrese K, Calvi C, Camilleri B, Camp S, Campbell D, Campbell R, Cao H, Capelli I, Caple M, Caplin B, Cardone A, Carle J, Carnall V, Caroppo M, Carr S, Carraro G, Carson M, Casares P, Castillo C, Castro C, Caudill B, Cejka V, Ceseri M, Cham L, Chamberlain A, Chambers J, Chan CBT, Chan JYM, Chan YC, Chang E, Chang E, Chant T, Chavagnon T, Chellamuthu P, Chen F, Chen J, Chen P, Chen TM, Chen Y, Chen Y, Cheng C, Cheng H, Cheng MC, Cherney D, Cheung AK, Ching CH, Chitalia N, Choksi R, Chukwu C, Chung K, Cianciolo G, Cipressa L, Clark S, Clarke H, Clarke R, Clarke S, Cleveland B, Cole E, Coles H, Condurache L, Connor A, Convery K, Cooper A, Cooper N, Cooper Z, Cooperman L, Cosgrove L, Coutts P, Cowley A, Craik R, Cui G, Cummins T, Dahl N, Dai H, Dajani L, D'Amelio A, Damian E, Damianik K, Danel L, Daniels C, Daniels T, Darbeau S, Darius H, Dasgupta T, Davies J, Davies L, Davis A, Davis J, Davis L, Dayanandan R, Dayi S, Dayrell R, De Nicola L, Debnath S, Deeb W, Degenhardt S, DeGoursey K, Delaney M, Deo R, DeRaad R, Derebail V, Dev D, Devaux M, Dhall P, Dhillon G, Dienes J, Dobre M, Doctolero E, Dodds V, Domingo D, Donaldson D, Donaldson P, Donhauser C, Donley V, Dorestin S, Dorey S, Doulton T, Draganova D, Draxlbauer K, Driver F, Du H, Dube F, Duck T, Dugal T, Dugas J, Dukka H, Dumann H, Durham W, Dursch M, Dykas R, Easow R, Eckrich E, Eden G, Edmerson E, Edwards H, Ee LW, Eguchi J, Ehrl Y, Eichstadt K, Eid W, Eilerman B, Ejima Y, Eldon H, Ellam T, Elliott L, Ellison R, Emberson J, Epp R, Er A, Espino-Obrero M, Estcourt S, Estienne L, Evans G, Evans J, Evans S, Fabbri G, Fajardo-Moser M, Falcone C, Fani F, Faria-Shayler P, Farnia F, Farrugia D, Fechter M, Fellowes D, Feng F, Fernandez J, Ferraro P, Field A, Fikry S, Finch J, Finn H, Fioretto P, Fish R, Fleischer A, Fleming-Brown D, Fletcher L, Flora R, Foellinger C, Foligno N, Forest S, Forghani Z, Forsyth K, Fottrell-Gould D, Fox P, Frankel A, Fraser D, Frazier R, Frederick K, Freking N, French H, Froment A, Fuchs B, Fuessl L, Fujii H, Fujimoto A, Fujita A, Fujita K, Fujita Y, Fukagawa M, Fukao Y, Fukasawa A, Fuller T, Funayama T, Fung E, Furukawa M, Furukawa Y, Furusho M, Gabel S, Gaidu J, Gaiser S, Gallo K, Galloway C, Gambaro G, Gan CC, Gangemi C, Gao M, Garcia K, Garcia M, Garofalo C, Garrity M, Garza A, Gasko S, Gavrila M, Gebeyehu B, Geddes A, Gentile G, George A, George J, Gesualdo L, Ghalli F, Ghanem A, Ghate T, Ghavampour S, Ghazi A, Gherman A, Giebeln-Hudnell U, Gill B, Gillham S, Girakossyan I, Girndt M, Giuffrida A, Glenwright M, Glider T, Gloria R, Glowski D, Goh BL, Goh CB, Gohda T, Goldenberg R, Goldfaden R, Goldsmith C, Golson B, Gonce V, Gong Q, Goodenough B, Goodwin N, Goonasekera M, Gordon A, Gordon J, Gore A, Goto H, Goto S, Goto S, Gowen D, Grace A, Graham J, Grandaliano G, Gray M, Green JB, Greene T, Greenwood G, Grewal B, Grifa R, Griffin D, Griffin S, Grimmer P, Grobovaite E, Grotjahn S, Guerini A, Guest C, Gunda S, Guo B, Guo Q, Haack S, Haase M, Haaser K, Habuki K, Hadley A, Hagan S, Hagge S, Haller H, Ham S, Hamal S, Hamamoto Y, Hamano N, Hamm M, Hanburry A, Haneda M, Hanf C, Hanif W, Hansen J, Hanson L, Hantel S, Haraguchi T, Harding E, Harding T, Hardy C, Hartner C, Harun Z, Harvill L, Hasan A, Hase H, Hasegawa F, Hasegawa T, Hashimoto A, Hashimoto C, Hashimoto M, Hashimoto S, Haskett S, Hauske SJ, Hawfield A, Hayami T, Hayashi M, Hayashi S, Haynes R, Hazara A, Healy C, Hecktman J, Heine G, Henderson H, Henschel R, Hepditch A, Herfurth K, Hernandez G, Hernandez Pena A, Hernandez-Cassis C, Herrington WG, Herzog C, Hewins S, Hewitt D, Hichkad L, Higashi S, Higuchi C, Hill C, Hill L, Hill M, Himeno T, Hing A, Hirakawa Y, Hirata K, Hirota Y, Hisatake T, Hitchcock S, Hodakowski A, Hodge W, Hogan R, Hohenstatt U, Hohenstein B, Hooi L, Hope S, Hopley M, Horikawa S, Hosein D, Hosooka T, Hou L, Hou W, Howie L, Howson A, Hozak M, Htet Z, Hu X, Hu Y, Huang J, Huda N, Hudig L, Hudson A, Hugo C, Hull R, Hume L, Hundei W, Hunt N, Hunter A, Hurley S, Hurst A, Hutchinson C, Hyo T, Ibrahim FH, Ibrahim S, Ihana N, Ikeda T, Imai A, Imamine R, Inamori A, Inazawa H, Ingell J, Inomata K, Inukai Y, Ioka M, Irtiza-Ali A, Isakova T, Isari W, Iselt M, Ishiguro A, Ishihara K, Ishikawa T, Ishimoto T, Ishizuka K, Ismail R, Itano S, Ito H, Ito K, Ito M, Ito Y, Iwagaitsu S, Iwaita Y, Iwakura T, Iwamoto M, Iwasa M, Iwasaki H, Iwasaki S, Izumi K, Izumi K, Izumi T, Jaafar SM, Jackson C, Jackson Y, Jafari G, Jahangiriesmaili M, Jain N, Jansson K, Jasim H, Jeffers L, Jenkins A, Jesky M, Jesus-Silva J, Jeyarajah D, Jiang Y, Jiao X, Jimenez G, Jin B, Jin Q, Jochims J, Johns B, Johnson C, Johnson T, Jolly S, Jones L, Jones L, Jones S, Jones T, Jones V, Joseph M, Joshi S, Judge P, Junejo N, Junus S, Kachele M, Kadowaki T, Kadoya H, Kaga H, Kai H, Kajio H, Kaluza-Schilling W, Kamaruzaman L, Kamarzarian A, Kamimura Y, Kamiya H, Kamundi C, Kan T, Kanaguchi Y, Kanazawa A, Kanda E, Kanegae S, Kaneko K, Kaneko K, Kang HY, Kano T, Karim M, Karounos D, Karsan W, Kasagi R, Kashihara N, Katagiri H, Katanosaka A, Katayama A, Katayama M, Katiman E, Kato K, Kato M, Kato N, Kato S, Kato T, Kato Y, Katsuda Y, Katsuno T, Kaufeld J, Kavak Y, Kawai I, Kawai M, Kawai M, Kawase A, Kawashima S, Kazory A, Kearney J, Keith B, Kellett J, Kelley S, Kershaw M, Ketteler M, Khai Q, Khairullah Q, Khandwala H, Khoo KKL, Khwaja A, Kidokoro K, Kielstein J, Kihara M, Kimber C, Kimura S, Kinashi H, Kingston H, Kinomura M, Kinsella-Perks E, Kitagawa M, Kitajima M, Kitamura S, Kiyosue A, Kiyota M, Klauser F, Klausmann G, Kmietschak W, Knapp K, Knight C, Knoppe A, Knott C, Kobayashi M, Kobayashi R, Kobayashi T, Koch M, Kodama S, Kodani N, Kogure E, Koizumi M, Kojima H, Kojo T, Kolhe N, Komaba H, Komiya T, Komori H, Kon SP, Kondo M, Kondo M, Kong W, Konishi M, Kono K, Koshino M, Kosugi T, Kothapalli B, Kozlowski T, Kraemer B, Kraemer-Guth A, Krappe J, Kraus D, Kriatselis C, Krieger C, Krish P, Kruger B, Ku Md Razi KR, Kuan Y, Kubota S, Kuhn S, Kumar P, Kume S, Kummer I, Kumuji R, Küpper A, Kuramae T, Kurian L, Kuribayashi C, Kurien R, Kuroda E, Kurose T, Kutschat A, Kuwabara N, Kuwata H, La Manna G, Lacey M, Lafferty K, LaFleur P, Lai V, Laity E, Lambert A, Landray MJ, Langlois M, Latif F, Latore E, Laundy E, Laurienti D, Lawson A, Lay M, Leal I, Leal I, Lee AK, Lee J, Lee KQ, Lee R, Lee SA, Lee YY, Lee-Barkey Y, Leonard N, Leoncini G, Leong CM, Lerario S, Leslie A, Levin A, Lewington A, Li J, Li N, Li X, Li Y, Liberti L, Liberti ME, Liew A, Liew YF, Lilavivat U, Lim SK, Lim YS, Limon E, Lin H, Lioudaki E, Liu H, Liu J, Liu L, Liu Q, Liu WJ, Liu X, Liu Z, Loader D, Lochhead H, Loh CL, Lorimer A, Loudermilk L, Loutan J, Low CK, Low CL, Low YM, Lozon Z, Lu Y, Lucci D, Ludwig U, Luker N, Lund D, Lustig R, Lyle S, Macdonald C, MacDougall I, Machicado R, MacLean D, Macleod P, Madera A, Madore F, Maeda K, Maegawa H, Maeno S, Mafham M, Magee J, Maggioni AP, Mah DY, Mahabadi V, Maiguma M, Makita Y, Makos G, Manco L, Mangiacapra R, Manley J, Mann P, Mano S, Marcotte G, Maris J, Mark P, Markau S, Markovic M, Marshall C, Martin M, Martinez C, Martinez S, Martins G, Maruyama K, Maruyama S, Marx K, Maselli A, Masengu A, Maskill A, Masumoto S, Masutani K, Matsumoto M, Matsunaga T, Matsuoka N, Matsushita M, Matthews M, Matthias S, Matvienko E, Maurer M, Maxwell P, Mayne KJ, Mazlan N, Mazlan SA, Mbuyisa A, McCafferty K, McCarroll F, McCarthy T, McClary-Wright C, McCray K, McDermott P, McDonald C, McDougall R, McHaffie E, McIntosh K, McKinley T, McLaughlin S, McLean N, McNeil L, Measor A, Meek J, Mehta A, Mehta R, Melandri M, Mené P, Meng T, Menne J, Merritt K, Merscher S, Meshykhi C, Messa P, Messinger L, Miftari N, Miller R, Miller Y, Miller-Hodges E, Minatoguchi M, Miners M, Minutolo R, Mita T, Miura Y, Miyaji M, Miyamoto S, Miyatsuka T, Miyazaki M, Miyazawa I, Mizumachi R, Mizuno M, Moffat S, Mohamad Nor FS, Mohamad Zaini SN, Mohamed Affandi FA, Mohandas C, Mohd R, Mohd Fauzi NA, Mohd Sharif NH, Mohd Yusoff Y, Moist L, Moncada A, Montasser M, Moon A, Moran C, Morgan N, Moriarty J, Morig G, Morinaga H, Morino K, Morisaki T, Morishita Y, Morlok S, Morris A, Morris F, Mostafa S, Mostefai Y, Motegi M, Motherwell N, Motta D, Mottl A, Moys R, Mozaffari S, Muir J, Mulhern J, Mulligan S, Munakata Y, Murakami C, Murakoshi M, Murawska A, Murphy K, Murphy L, Murray S, Murtagh H, Musa MA, Mushahar L, Mustafa R, Mustafar R, Muto M, Nadar E, Nagano R, Nagasawa T, Nagashima E, Nagasu H, Nagelberg S, Nair H, Nakagawa Y, Nakahara M, Nakamura J, Nakamura R, Nakamura T, Nakaoka M, Nakashima E, Nakata J, Nakata M, Nakatani S, Nakatsuka A, Nakayama Y, Nakhoul G, Nangaku M, Naverrete G, Navivala A, Nazeer I, Negrea L, Nethaji C, Newman E, Ng SYA, Ng TJ, Ngu LLS, Nimbkar T, Nishi H, Nishi M, Nishi S, Nishida Y, Nishiyama A, Niu J, Niu P, Nobili G, Nohara N, Nojima I, Nolan J, Nosseir H, Nozawa M, Nunn M, Nunokawa S, Oda M, Oe M, Oe Y, Ogane K, Ogawa W, Ogihara T, Oguchi G, Ohsugi M, Oishi K, Okada Y, Okajyo J, Okamoto S, Okamura K, Olufuwa O, Oluyombo R, Omata A, Omori Y, Ong LM, Ong YC, Onyema J, Oomatia A, Oommen A, Oremus R, Orimo Y, Ortalda V, Osaki Y, Osawa Y, Osmond Foster J, O'Sullivan A, Otani T, Othman N, Otomo S, O'Toole J, Owen L, Ozawa T, Padiyar A, Page N, Pajak S, Paliege A, Pandey A, Pandey R, Pariani H, Park J, Parrigon M, Passauer J, Patecki M, Patel M, Patel R, Patel T, Patel Z, Paul R, Paul R, Paulsen L, Pavone L, Peixoto A, Peji J, Peng BC, Peng K, Pennino L, Pereira E, Perez E, Pergola P, Pesce F, Pessolano G, Petchey W, Petr EJ, Pfab T, Phelan P, Phillips R, Phillips T, Phipps M, Piccinni G, Pickett T, Pickworth S, Piemontese M, Pinto D, Piper J, Plummer-Morgan J, Poehler D, Polese L, Poma V, Pontremoli R, Postal A, Pötz C, Power A, Pradhan N, Pradhan R, Preiss D, Preiss E, Preston K, Prib N, Price L, Provenzano C, Pugay C, Pulido R, Putz F, Qiao Y, Quartagno R, Quashie-Akponeware M, Rabara R, Rabasa-Lhoret R, Radhakrishnan D, Radley M, Raff R, Raguwaran S, Rahbari-Oskoui F, Rahman M, Rahmat K, Ramadoss S, Ramanaidu S, Ramasamy S, Ramli R, Ramli S, Ramsey T, Rankin A, Rashidi A, Raymond L, Razali WAFA, Read K, Reiner H, Reisler A, Reith C, Renner J, Rettenmaier B, Richmond L, Rijos D, Rivera R, Rivers V, Robinson H, Rocco M, Rodriguez-Bachiller I, Rodriquez R, Roesch C, Roesch J, Rogers J, Rohnstock M, Rolfsmeier S, Roman M, Romo A, Rosati A, Rosenberg S, Ross T, Rossello X, Roura M, Roussel M, Rovner S, Roy S, Rucker S, Rump L, Ruocco M, Ruse S, Russo F, Russo M, Ryder M, Sabarai A, Saccà C, Sachson R, Sadler E, Safiee NS, Sahani M, Saillant A, Saini J, Saito C, Saito S, Sakaguchi K, Sakai M, Salim H, Salviani C, Sammons E, Sampson A, Samson F, Sandercock P, Sanguila S, Santorelli G, Santoro D, Sarabu N, Saram T, Sardell R, Sasajima H, Sasaki T, Satko S, Sato A, Sato D, Sato H, Sato H, Sato J, Sato T, Sato Y, Satoh M, Sawada K, Schanz M, Scheidemantel F, Schemmelmann M, Schettler E, Schettler V, Schlieper GR, Schmidt C, Schmidt G, Schmidt U, Schmidt-Gurtler H, Schmude M, Schneider A, Schneider I, Schneider-Danwitz C, Schomig M, Schramm T, Schreiber A, Schricker S, Schroppel B, Schulte-Kemna L, Schulz E, Schumacher B, Schuster A, Schwab A, Scolari F, Scott A, Seeger W, Seeger W, Segal M, Seifert L, Seifert M, Sekiya M, Sellars R, Seman MR, Shah S, Shah S, Shainberg L, Shanmuganathan M, Shao F, Sharma K, Sharpe C, Sheikh-Ali M, Sheldon J, Shenton C, Shepherd A, Shepperd M, Sheridan R, Sheriff Z, Shibata Y, Shigehara T, Shikata K, Shimamura K, Shimano H, Shimizu Y, Shimoda H, Shin K, Shivashankar G, Shojima N, Silva R, Sim CSB, Simmons K, Sinha S, Sitter T, Sivanandam S, Skipper M, Sloan K, Sloan L, Smith R, Smyth J, Sobande T, Sobata M, Somalanka S, Song X, Sonntag F, Sood B, Sor SY, Soufer J, Sparks H, Spatoliatore G, Spinola T, Squyres S, Srivastava A, Stanfield J, Staplin N, Staylor K, Steele A, Steen O, Steffl D, Stegbauer J, Stellbrink C, Stellbrink E, Stevens W, Stevenson A, Stewart-Ray V, Stickley J, Stoffler D, Stratmann B, Streitenberger S, Strutz F, Stubbs J, Stumpf J, Suazo N, Suchinda P, Suckling R, Sudin A, Sugamori K, Sugawara H, Sugawara K, Sugimoto D, Sugiyama H, Sugiyama H, Sugiyama T, Sullivan M, Sumi M, Suresh N, Sutton D, Suzuki H, Suzuki R, Suzuki Y, Suzuki Y, Suzuki Y, Swanson E, Swift P, Syed S, Szerlip H, Taal M, Taddeo M, Tailor C, Tajima K, Takagi M, Takahashi K, Takahashi K, Takahashi M, Takahashi T, Takahira E, Takai T, Takaoka M, Takeoka J, Takesada A, Takezawa M, Talbot M, Taliercio J, Talsania T, Tamori Y, Tamura R, Tamura Y, Tan CHH, Tan EZZ, Tanabe A, Tanabe K, Tanaka A, Tanaka A, Tanaka N, Tang S, Tang Z, Tanigaki K, Tarlac M, Tatsuzawa A, Tay JF, Tay LL, Taylor J, Taylor K, Taylor K, Te A, Tenbusch L, Teng KS, Terakawa A, Terry J, Tham ZD, Tholl S, Thomas G, Thong KM, Tietjen D, Timadjer A, Tindall H, Tipper S, Tobin K, Toda N, Tokuyama A, Tolibas M, Tomita A, Tomita T, Tomlinson J, Tonks L, Topf J, Topping S, Torp A, Torres A, Totaro F, Toth P, Toyonaga Y, Tripodi F, Trivedi K, Tropman E, Tschope D, Tse J, Tsuji K, Tsunekawa S, Tsunoda R, Tucky B, Tufail S, Tuffaha A, Turan E, Turner H, Turner J, Turner M, Tuttle KR, Tye YL, Tyler A, Tyler J, Uchi H, Uchida H, Uchida T, Uchida T, Udagawa T, Ueda S, Ueda Y, Ueki K, Ugni S, Ugwu E, Umeno R, Unekawa C, Uozumi K, Urquia K, Valleteau A, Valletta C, van Erp R, Vanhoy C, Varad V, Varma R, Varughese A, Vasquez P, Vasseur A, Veelken R, Velagapudi C, Verdel K, Vettoretti S, Vezzoli G, Vielhauer V, Viera R, Vilar E, Villaruel S, Vinall L, Vinathan J, Visnjic M, Voigt E, von-Eynatten M, Vourvou M, Wada J, Wada J, Wada T, Wada Y, Wakayama K, Wakita Y, Wallendszus K, Walters T, Wan Mohamad WH, Wang L, Wang W, Wang X, Wang X, Wang Y, Wanner C, Wanninayake S, Watada H, Watanabe K, Watanabe K, Watanabe M, Waterfall H, Watkins D, Watson S, Weaving L, Weber B, Webley Y, Webster A, Webster M, Weetman M, Wei W, Weihprecht H, Weiland L, Weinmann-Menke J, Weinreich T, Wendt R, Weng Y, Whalen M, Whalley G, Wheatley R, Wheeler A, Wheeler J, Whelton P, White K, Whitmore B, Whittaker S, Wiebel J, Wiley J, Wilkinson L, Willett M, Williams A, Williams E, Williams K, Williams T, Wilson A, Wilson P, Wincott L, Wines E, Winkelmann B, Winkler M, Winter-Goodwin B, Witczak J, Wittes J, Wittmann M, Wolf G, Wolf L, Wolfling R, Wong C, Wong E, Wong HS, Wong LW, Wong YH, Wonnacott A, Wood A, Wood L, Woodhouse H, Wooding N, Woodman A, Wren K, Wu J, Wu P, Xia S, Xiao H, Xiao X, Xie Y, Xu C, Xu Y, Xue H, Yahaya H, Yalamanchili H, Yamada A, Yamada N, Yamagata K, Yamaguchi M, Yamaji Y, Yamamoto A, Yamamoto S, Yamamoto S, Yamamoto T, Yamanaka A, Yamano T, Yamanouchi Y, Yamasaki N, Yamasaki Y, Yamasaki Y, Yamashita C, Yamauchi T, Yan Q, Yanagisawa E, Yang F, Yang L, Yano S, Yao S, Yao Y, Yarlagadda S, Yasuda Y, Yiu V, Yokoyama T, Yoshida S, Yoshidome E, Yoshikawa H, Young A, Young T, Yousif V, Yu H, Yu Y, Yuasa K, Yusof N, Zalunardo N, Zander B, Zani R, Zappulo F, Zayed M, Zemann B, Zettergren P, Zhang H, Zhang L, Zhang L, Zhang N, Zhang X, Zhao J, Zhao L, Zhao S, Zhao Z, Zhong H, Zhou N, Zhou S, Zhu D, Zhu L, Zhu S, Zietz M, Zippo M, Zirino F, Zulkipli FH. Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial. Lancet Diabetes Endocrinol 2024; 12:51-60. [PMID: 38061372 DOI: 10.1016/s2213-8587(23)00322-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 10/24/2023] [Accepted: 10/25/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND The EMPA-KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population. METHODS EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110. FINDINGS Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62-0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16-1·59), representing a 50% (42-58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1). INTERPRETATION In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease. FUNDING Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council.
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Chen A, Sun Y, Lei Y, Li C, Liao S, Meng J, Bai Y, Liu Z, Liang Z, Zhu Z, Yuan N, Yang H, Wu Z, Lin F, Wang K, Li M, Zhang S, Yang M, Fei T, Zhuang Z, Huang Y, Zhang Y, Xu Y, Cui L, Zhang R, Han L, Sun X, Chen B, Li W, Huangfu B, Ma K, Ma J, Li Z, Lin Y, Wang H, Zhong Y, Zhang H, Yu Q, Wang Y, Liu X, Peng J, Liu C, Chen W, Pan W, An Y, Xia S, Lu Y, Wang M, Song X, Liu S, Wang Z, Gong C, Huang X, Yuan Y, Zhao Y, Chai Q, Tan X, Liu J, Zheng M, Li S, Huang Y, Hong Y, Huang Z, Li M, Jin M, Li Y, Zhang H, Sun S, Gao L, Bai Y, Cheng M, Hu G, Liu S, Wang B, Xiang B, Li S, Li H, Chen M, Wang S, Li M, Liu W, Liu X, Zhao Q, Lisby M, Wang J, Fang J, Lin Y, Xie Q, Liu Z, He J, Xu H, Huang W, Mulder J, Yang H, Sun Y, Uhlen M, Poo M, Wang J, Yao J, Wei W, Li Y, Shen Z, Liu L, Liu Z, Xu X, Li C. Single-cell spatial transcriptome reveals cell-type organization in the macaque cortex. Cell 2023; 186:3726-3743.e24. [PMID: 37442136 DOI: 10.1016/j.cell.2023.06.009] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 02/24/2023] [Accepted: 06/14/2023] [Indexed: 07/15/2023]
Abstract
Elucidating the cellular organization of the cerebral cortex is critical for understanding brain structure and function. Using large-scale single-nucleus RNA sequencing and spatial transcriptomic analysis of 143 macaque cortical regions, we obtained a comprehensive atlas of 264 transcriptome-defined cortical cell types and mapped their spatial distribution across the entire cortex. We characterized the cortical layer and region preferences of glutamatergic, GABAergic, and non-neuronal cell types, as well as regional differences in cell-type composition and neighborhood complexity. Notably, we discovered a relationship between the regional distribution of various cell types and the region's hierarchical level in the visual and somatosensory systems. Cross-species comparison of transcriptomic data from human, macaque, and mouse cortices further revealed primate-specific cell types that are enriched in layer 4, with their marker genes expressed in a region-dependent manner. Our data provide a cellular and molecular basis for understanding the evolution, development, aging, and pathogenesis of the primate brain.
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Affiliation(s)
- Ao Chen
- BGI-Shenzhen, Shenzhen 518103, China; Department of Biology, University of Copenhagen, Copenhagen 2200, Denmark; BGI Research-Southwest, BGI, Chongqing 401329, China; JFL-BGI STOmics Center, Jinfeng Laboratory, Chongqing 401329, China
| | - Yidi Sun
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
| | - Ying Lei
- BGI-Shenzhen, Shenzhen 518103, China; BGI-Hangzhou, Hangzhou 310012, China
| | - Chao Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Sha Liao
- BGI-Shenzhen, Shenzhen 518103, China; BGI Research-Southwest, BGI, Chongqing 401329, China; JFL-BGI STOmics Center, Jinfeng Laboratory, Chongqing 401329, China
| | - Juan Meng
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yiqin Bai
- Lingang Laboratory, Shanghai 200031, China
| | - Zhen Liu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zhifeng Liang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | - Nini Yuan
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Hao Yang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zihan Wu
- Tencent AI Lab, Shenzhen 518057, China
| | - Feng Lin
- BGI-Shenzhen, Shenzhen 518103, China
| | - Kexin Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Mei Li
- BGI-Shenzhen, Shenzhen 518103, China
| | - Shuzhen Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | - Tianyi Fei
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zhenkun Zhuang
- BGI-Shenzhen, Shenzhen 518103, China; School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
| | - Yiming Huang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yong Zhang
- BGI-Shenzhen, Shenzhen 518103, China; School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
| | - Yuanfang Xu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Luman Cui
- BGI-Shenzhen, Shenzhen 518103, China
| | - Ruiyi Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Lei Han
- BGI-Shenzhen, Shenzhen 518103, China
| | - Xing Sun
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | | | - Baoqian Huangfu
- BGI-Shenzhen, Shenzhen 518103, China; School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
| | | | - Jianyun Ma
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zhao Li
- BGI-Shenzhen, Shenzhen 518103, China
| | - Yikun Lin
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - He Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yanqing Zhong
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Huifang Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Qian Yu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yaqian Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xing Liu
- BGI-Shenzhen, Shenzhen 518103, China
| | - Jian Peng
- BGI-Shenzhen, Shenzhen 518103, China
| | | | - Wei Chen
- BGI-Shenzhen, Shenzhen 518103, China
| | | | - Yingjie An
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shihui Xia
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yanbing Lu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Mingli Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xinxiang Song
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shuai Liu
- BGI-Shenzhen, Shenzhen 518103, China
| | | | - Chun Gong
- BGI-Shenzhen, Shenzhen 518103, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Xin Huang
- BGI-Shenzhen, Shenzhen 518103, China
| | - Yue Yuan
- BGI-Shenzhen, Shenzhen 518103, China
| | - Yun Zhao
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Qinwen Chai
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xing Tan
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Jianfeng Liu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Mingyuan Zheng
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shengkang Li
- BGI-Shenzhen, Shenzhen 518103, China; Guangdong Bigdata Engineering Technology Research Center for Life Sciences, Shenzhen 518083, China
| | | | - Yan Hong
- BGI-Shenzhen, Shenzhen 518103, China
| | | | - Min Li
- BGI-Shenzhen, Shenzhen 518103, China
| | - Mengmeng Jin
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yan Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Hui Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Suhong Sun
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Li Gao
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yinqi Bai
- BGI-Shenzhen, Shenzhen 518103, China
| | | | - Guohai Hu
- China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Shiping Liu
- BGI-Shenzhen, Shenzhen 518103, China; BGI-Hangzhou, Hangzhou 310012, China
| | - Bo Wang
- China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Bin Xiang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shuting Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Huanhuan Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Mengni Chen
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shiwen Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Minglong Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | - Xin Liu
- BGI-Shenzhen, Shenzhen 518103, China
| | - Qian Zhao
- BGI-Shenzhen, Shenzhen 518103, China
| | - Michael Lisby
- Department of Biology, University of Copenhagen, Copenhagen 2200, Denmark
| | - Jing Wang
- BGI-Shenzhen, Shenzhen 518103, China
| | - Jiao Fang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yun Lin
- BGI-Shenzhen, Shenzhen 518103, China
| | - Qing Xie
- BGI-Shenzhen, Shenzhen 518103, China
| | - Zhen Liu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China
| | - Jie He
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Huatai Xu
- Lingang Laboratory, Shanghai 200031, China
| | - Wei Huang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Jan Mulder
- Department of Protein Science, Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm 17121, Sweden; Department of Neuroscience, Karolinska Institute, Stockholm 17177, Sweden
| | | | - Yangang Sun
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Mathias Uhlen
- Department of Protein Science, Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm 17121, Sweden; Department of Neuroscience, Karolinska Institute, Stockholm 17177, Sweden
| | - Muming Poo
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China
| | - Jian Wang
- BGI-Shenzhen, Shenzhen 518103, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | | | - Wu Wei
- Lingang Laboratory, Shanghai 200031, China; CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
| | - Yuxiang Li
- BGI-Shenzhen, Shenzhen 518103, China; BGI Research-Wuhan, BGI, Wuhan 430074, China.
| | - Zhiming Shen
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China.
| | - Longqi Liu
- BGI-Shenzhen, Shenzhen 518103, China; BGI-Hangzhou, Hangzhou 310012, China.
| | - Zhiyong Liu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China.
| | - Xun Xu
- BGI-Shenzhen, Shenzhen 518103, China; Guangdong Provincial Key Laboratory of Genome Read and Write, Shenzhen 518120, China.
| | - Chengyu Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China; School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, China.
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Chen S, Duan L, Li S, Zhou J, Zhou Y, Yang Y, Liu M, Wang Y, Xia S, Xu J, Lü S. [Preliminary study on the mechanism underlying the ecological isolation of Oncomelania hupensis populations in Changde City]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2023; 35:147-154. [PMID: 37253563 DOI: 10.16250/j.32.1374.2022276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
OBJECTIVE To investigate ecological isolation between Oncomelania hupensis snail populations in hilly regions and marshland and lake regions in Yuanjiang valley, Changde City, Hunan Province, and to unravel its underlying mechanisms. METHODS Taoyuan County, Shimen County, Linli County and Lixian County in Changde City were selected as snail sampling sites in hilly regions, and Lixian County, Jinshi City, West Lake Administration District, Hanshou County and Dingcheng District were selected as snail sampling sites in marshland and lake areas. Cytochrome C oxidase 1 (cox 1) gene was amplified in snail samples and sequenced. The genetic sequences of O. hupensis snails were aligned using the software MEGA 11, and the haplotypes of O. hupensis snails were determined using the software DNASP 5.10.01. The phylogenetic tree was generated using Bayesian inference with the software MrBayes 3.2, and analysis of molecular variance (AMOVA) was performed to analyze the source of genetic divergence and estimate the genetic divergence index (FST) among snail populations with the software Arlequin 3.5.2.2. The genetic barrier among 11 O. hupensis snail populations was estimated using the Monmonier algorithm of adegenet toolkit in R package. The settings with "land in winter and water in summer" in the Yuanjian River section were divided into two categories according to the upstream and downstream, and the areas with "land in winter and water in summer" in the upstream and downstream were transformed into raster data, and then loaded into the software Fragstats 4 for analysis of landscape indicators. The trends in changes of digital elevation were extracted from the Yuanjiang River section based on the digital elevation model, and made three-dimensional visualization using the R package. RESULTS The mitochondrial cox 1 gene were amplified in 165 O. hupensis snais from 11 sampling sites and sequenced, and a total of 152 valid gene sequences were obtained, with 46 haplotypes or 9 populations determined. No haplotype was shared in snails between Taoyuan County and Dingcheng District and Hanshou County along the downstream of the Yuanjiang River. The total area of settings with "land in winter and water in summer" was 617.66 hm2 in the upsteram of the Yuanjiang River, which consisted of 473 patches, with each patch measuring 1.31 hm2, the largest area index of 0.735 2, the landscape division index of 0.999 9, and the landscape shape index of 45.293 7. The total area of settings with "land in winter and water in summer" was 9 956.92 hm2 in the downstream of the Yuanjiang River, which consisted of 771 patches, with each patch measuring 12.91 hm2, the largest area index of 97.839 9, the landscape division index of 0.042 7, and the landscape shape index of 7.249 6. The area of settings with "land in winter and water in summer" was much larger in the downstream than that in the upstream of the Yuanjiang River, and the stronger landscape connectivity and non-remarkable alteration of riverbed elevation provided suitable habitats for snail breeding. CONCLUSIONS The hydrological and environmental characteristics of the upstream of the Yuanjiang River restrain the breeding and spread of O. hupensis, resulting in ecological isolation between Oncomelania hupensis in Taoyuan County and those in the downstream of Yuanjiang River.
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Affiliation(s)
- S Chen
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), Key Laboratory of National Health Commission on Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai 200025, China
| | - L Duan
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), Key Laboratory of National Health Commission on Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai 200025, China
| | - S Li
- Hunan Institute of Schistosomiasis Control, China
| | - J Zhou
- Hunan Institute of Schistosomiasis Control, China
| | - Y Zhou
- Changde Center for Disease Control and Prevention, Hunan Province, China
| | - Y Yang
- Health Bureau of Taoyuan County, Changde City, Hunan Province, China
| | - M Liu
- Health Bureau of Hanshou County, Hunan Province, China
| | - Y Wang
- Health Department of Dingcheng District, Changde City, Hunan Province, China
| | - S Xia
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), Key Laboratory of National Health Commission on Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai 200025, China
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - J Xu
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), Key Laboratory of National Health Commission on Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai 200025, China
| | - S Lü
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), Key Laboratory of National Health Commission on Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai 200025, China
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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Li H, Zheng J, Qian Y, Lü S, Xia S, Zhou X. [Comparison of the disease burden of schistosomiasis globally and in China and Zimbabwe]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2023; 35:128-136. [PMID: 37253561 DOI: 10.16250/j.32.1374.2022263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
OBJECTIVE To investigate the trends in the disease burden of schistosomiasis worldwide and in China, and Zimbabwe from 1990 to 2019, so as to provide insights into the formulation of the schistosomiasis control strategy in Zimbabwe. METHODS Based on Global Burden of Disease Study 2019 (GBD 2019) data sources, the age-standardized prevalence, mortality, disability-adjusted life year (DALY) rate of schistosomiasis were compared in the world, China, and Zimbabwe and the trends in the disease burden of schistosomiasis from 1990 to 2019 were investigated using Joinpoint regression analysis. In addition, the associations between the burden of schistosomiasis worldwide and in China and Zimbabwe from 1990 to 2019 and socio-demographic index (SDI) were examined using Pearson correlation analysis. RESULTS The age-standardized prevalence, mortality, and DALY rate of schistosomiasis were 1 804.95/105, 0.14/105 and 20.92/105 in the world, 707.09/105, 0.02/105 and 5.06/105 in China, and 2 218.90/105, 2.39/105 and 90.09/105 in Zimbabwe in 2019, respectively. The global prevalence, mortality, and DALY rate of schistosomiasis appeared a tendency towards a rise followed by a decline with age in 2019, while the prevalence and DALY rate of schistosomiasis appeared a tendency towards a sharp rise followed by a fluctuating decline in both China and Zimbabwe, and the mortality of schistosomiasis appeared a tendency towards a rise. The age-standardized prevalence [average annual percent change (AAPC) = -1.31%, -2.22% and -6.12%; t = -20.07, -83.38 and -53.06; all P values < 0.05)] and DALY rate of schistosomiasis (AAPC = -1.91%,-4.17% and -2.08%; t = -31.89, -138.70 and -16.45; all P values < 0.05) appeared a tendency towards a decline in the world, China and Zimbabwe from 1990 to 2019, and the age-standardized mortality of schistosomiasis appeared a tendency towards a decline in the world and China (AAPC = -3.46% and -8.10%, t = -41.03 and -61.74; both P values < 0.05), and towards a rise followed by a decline in Zimbabwe (AAPC = 1.35%, t = 4.88, P < 0.05). In addition, Pearson correlation analysis showed that the age-standardized prevalence (r = -0.75, P < 0.05), mortality (r = -0.73, P < 0.05), and DALY rate of schistosomiasis (r = -0.77, P < 0.05) correlated negatively with SDI in the world, China and Zimbabwe from 1990 to 2019. CONCLUSIONS The disease burden of schistosomiasis appeared a remarkable decline in China from 1990 to 2019, and the prevalence of schistosomiasis showed a tendency towards a decline in Zimbabwe from 1990 to 2019; however, the mortality and DALY rate of schistosomiasis in Zimbabwe topped in the world. A schistosomiasis control strategy with adaptations to local epidemiology and control needs of schistosomiasis is needed to facilitate the elimination of schistosomiasis in Zimbabwe.
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Affiliation(s)
- H Li
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); National Health Commission Key Laboratory of Parasite and Vector Biology; WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai 200025, China
| | - J Zheng
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); National Health Commission Key Laboratory of Parasite and Vector Biology; WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai 200025, China
| | - Y Qian
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); National Health Commission Key Laboratory of Parasite and Vector Biology; WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai 200025, China
| | - S Lü
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); National Health Commission Key Laboratory of Parasite and Vector Biology; WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai 200025, China
| | - S Xia
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); National Health Commission Key Laboratory of Parasite and Vector Biology; WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai 200025, China
| | - X Zhou
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); National Health Commission Key Laboratory of Parasite and Vector Biology; WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai 200025, China
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Xue J, Xia S, Li Z, Wang X, Huang L, He R, Li S. [Intelligent identification of livestock, a source of Schistosoma japonicum infection, based on deep learning of unmanned aerial vehicle images]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2023; 35:121-127. [PMID: 37253560 DOI: 10.16250/j.32.1374.2022273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
OBJECTIVE To develop an intelligent recognition model based on deep learning algorithms of unmanned aerial vehicle (UAV) images, and to preliminarily explore the value of this model for remote identification, monitoring and management of cattle, a source of Schistosoma japonicum infection. METHODS Oncomelania hupensis snail-infested marshlands around the Poyang Lake area were selected as the study area. Image datasets of the study area were captured by aerial photography with UAV and subjected to augmentation. Cattle in the sample database were annotated with the annotation software VGG Image Annotator to create the morphological recognition labels for cattle. A model was created for intelligent recognition of livestock based on deep learning-based Mask R-convolutional neural network (CNN) algorithms. The performance of the model for cattle recognition was evaluated with accuracy, precision, recall, F1 score and mean precision. RESULTS A total of 200 original UAV images were obtained, and 410 images were yielded following data augmentation. A total of 2 860 training samples of cattle recognition were labeled. The created deep learning-based Mask R-CNN model converged following 200 iterations, with an accuracy of 88.01%, precision of 92.33%, recall of 94.06%, F1 score of 93.19%, and mean precision of 92.27%, and the model was effective to detect and segment the morphological features of cattle. CONCLUSIONS The deep learning-based Mask R-CNN model is highly accurate for recognition of cattle based on UAV images, which is feasible for remote intelligent recognition, monitoring, and management of the source of S. japonicum infection.
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Affiliation(s)
- J Xue
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), National Health Commission Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China
- School of Global Health, Shanghai Jiao Tong University School of Medicine and Chinese Center for Tropical Diseases Research, Shanghai 200025, China
| | - S Xia
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), National Health Commission Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China
- School of Global Health, Shanghai Jiao Tong University School of Medicine and Chinese Center for Tropical Diseases Research, Shanghai 200025, China
| | - Z Li
- Jiangxi Provincial Institute of Parasitic Diseases Control, Jiangxi Provincial Key Laboratory of Schistosomiasis Prevention and Control, China
| | - X Wang
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), National Health Commission Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - L Huang
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), National Health Commission Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - R He
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), National Health Commission Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - S Li
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), National Health Commission Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China
- School of Global Health, Shanghai Jiao Tong University School of Medicine and Chinese Center for Tropical Diseases Research, Shanghai 200025, China
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Li HL, Zhang L, Xia S, Chen S, Yang Y, Ye CJ, Huang XF. [Clinical pathologic analysis and review of literature on 11 cases of calcifying epithelial odontogenic tumor]. Zhonghua Kou Qiang Yi Xue Za Zhi 2022; 57:1119-1127. [PMID: 36379890 DOI: 10.3760/cma.j.cn112144-20220730-00422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Objective: To improve the understanding of histological variants of calcifying epithelial odontogenic tumor (CEOT). Methods: In this retrospective study, 11 cases of CEOT diagnosed from January 2008 to March 2022 were enrolled in the Department of Oral Pathology of Nanjing Stomatological Hospital, Medical School of Nanjing University. Among them, 10 were male and 1 was female. The patients were 19 to 58 years old [(43.0±11.9) years] and the course of disease was 2 weeks to 5 years. The clinicopathological characteristics were analyzed and the follow-up of patients ranged from 1 to 8 years, including 8 cases with follow-up data and 3 cases lost to follow-up. Furthermore, the related domestic and international literature was reviewed. Results: Eleven cases of CEOT included 6 cases of classic CEOT, 2 cases of clear cell CEOT, 2 cases of Langerhans cell-rich variant of CEOT and 1 case of non-calcified CEOT. In 6 cases of classic CEOT, the ratio of occurrence in mandible to maxilla was 2∶1, the ratio in central parts to peripheral parts was 5∶1, 2 cases were associated with unerupted teeth and 3 cases showed local aggressiveness. Histopathologically, classic CEOT showed eosinophilic epithelial cells, amyloid and calcification with Ki-67 value<5%. Among 4 cases with follow-up information, 1 case recurred after 1 year and 3 cases did not recur for 3 to 8 years. In 2 cases of clear cell CEOT, they both occurred in the periphery of mandible, pathologically showing a mix of lamellar balloon-like clear cells and typical CEOT, positive for CK5/6 and p63 in the area where the epithelial cells and clear cells were located, scattered positive for periodic acid-Schiff (PAS) in clear cells, which indicated the presence of glycogen. The maximum Ki-67 value was 5% in this type. One case lost to follow-up and the other case did not recur for 1 year follow-up after surgery. In 2 cases of Langerhans cell-rich variant of CEOT, they were cystic solid lesions and both occurred in the anterior maxilla. Langerhans cells were scattered in the epithelium and non-calcified amyloid glomeruli were present. Two cases were followed up for 1 year and 2 years without recurrence after surgery. One case of non-calcified CEOT that occurs within the jan showed invasion of surrounding soft tissues and the highest of Ki-67 value at 8% in all 11 cases without recurrence at 1 year follow-up. Conclusions: The histological pattern of classic CEOT is unique, and it is necessary to prompt the understanding of several histological variants derived from it.
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Affiliation(s)
- H L Li
- Department of Oral Pathology, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing 210008, China
| | - L Zhang
- Department of Oral Pathology, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing 210008, China
| | - S Xia
- Department of Oral Pathology, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing 210008, China
| | - S Chen
- Department of Oral Pathology, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing 210008, China
| | - Y Yang
- Department of Oral Pathology, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing 210008, China
| | - C J Ye
- Department of Oral Pathology, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing 210008, China
| | - X F Huang
- Department of Oral Pathology, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing 210008, China
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Xia S, Zhu H, Zhang X, Shi Y, Li X, Sun Y. An End-to-End Auto-Prediction Model Response to Neoadjuvant Chemoradiotherapy for Rectal Cancer Based on Multimodal Segmentation and Multipath Lightweight Convolution. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Qiu WD, Xiao XJ, Xia S, Gao ZP, Li LW. [Predictive value of plasma TMAO combined with NT-proBNP on the prognosis and length of hospitalization of patients with ischemic heart failure]. Zhonghua Xin Xue Guan Bing Za Zhi 2022; 50:684-689. [PMID: 35856225 DOI: 10.3760/cma.j.cn112148-20210920-00807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To explore the value of the assessment of plasma trimethylamine N-oxide (TMAO) combined with N-terminal pro-B-type natriuretic peptide (NT-proBNP) on predicting the all-cause mortality, length of hospitalization, and hospital cost in ischemic heart failure (IHF) patients. Methods: This prospective cohort study included 189 patients (157 males, mean age (64.0±10.5) years) with a left ventricular ejection fraction<45% caused by coronary artery disease, who hospitalized in our department from March 2016 to December 2020. Baseline data, including demographics, comorbid conditions and laboratory examination, were analyzed. The cumulative rate of all-cause mortality was evaluated using the Kaplan-Meier method and compared between the groups according to the log-rank test. Relative risks were reported as hazard ratios (HR) and 95% confidence interval (95%CI) calculated using the Cox proportional-hazards analysis, with stepwise adjustment for covariables. Spearman correlation analysis was then performed to determine the relationship between TMAO combined with NT-proBNP and length of hospitalization and hospital cost. Results: There were 50 patients in the low TMAO+low NT-proBNP group, 89 patients in high TMAO or high NT-proBNP group, 50 patients in high TMAO+high NT-proBNP group. The mean follow-up period was 3.0 years. Death occurred in 70 patients (37.0%), 27 patients (54.0%) in high TMAO+high NT-proBNP group, 29 patients (32.6%) in high TMAO or high NT-proBNP group and 14 patients (28.0%) in low TMAO+low NT-proBNP group. TMAO, in combination with NT-proBNP, improved all-cause mortality prediction in IHF patients when stratified as none, one or both biomarker(s) elevation, with the highest risk of all-cause mortality in high TMAO+high NT-proBNP group (HR=3.62, 95%CI 1.89-6.96, P<0.001). ROC curve analysis further confirmed that TMAO combined with NT-proBNP strengthened the prediction performance on the risk of all-cause death (AUC=0.727(95%CI 0.640-0.813), sensitivity 55.0%, characteristic 83.1%). Spearman correlation analysis showed that IHF patients with high TMAO and high NT-proBNP were positively associated with longer duration of hospitalization (r=0.191,P=0.009), but not associated with higher hospital cost (r=0.030, P=0.686). Conclusions: TMAO combined with NT-proBNP are valuable prediction tool on risk stratification of patients with IHF, and those with two biomarkers elevation face the highest risk of mortality during follow-up period, and are associated with the longer hospital stay.
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Affiliation(s)
- W D Qiu
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China Second School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China
| | - X J Xiao
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China Second School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China
| | - S Xia
- Second School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China
| | - Z P Gao
- Concord Medical Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - L W Li
- Second School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China
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Gong YF, Luo ZW, Feng JX, Xue JB, Guo ZY, Jin YJ, Yu Q, Xia S, Lü S, Xu J, Li SZ. [Prediction of trends for fine-scale spread of Oncomelania hupensis in Shanghai Municipality based on supervised machine learning models]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2022; 34:241-251. [PMID: 35896487 DOI: 10.16250/j.32.1374.2021247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
OBJECTIVE To predict the trends for fine-scale spread of Oncomelania hupensis based on supervised machine learning models in Shanghai Municipality, so as to provide insights into precision O. hupensis snail control. METHODS Based on 2016 O. hupensis snail survey data in Shanghai Municipality and climatic, geographical, vegetation and socioeconomic data relating to O. hupensis snail distribution, seven supervised machine learning models were created to predict the risk of snail spread in Shanghai, including decision tree, random forest, generalized boosted model, support vector machine, naive Bayes, k-nearest neighbor and C5.0. The performance of seven models for predicting snail spread was evaluated with the area under the receiver operating characteristic curve (AUC), F1-score and accuracy, and optimal models were selected to identify the environmental variables affecting snail spread and predict the areas at risk of snail spread in Shanghai Municipality. RESULTS Seven supervised machine learning models were successfully created to predict the risk of snail spread in Shanghai Municipality, and random forest (AUC = 0.901, F1-score = 0.840, ACC = 0.797) and generalized boosted model (AUC= 0.889, F1-score = 0.869, ACC = 0.835) showed higher predictive performance than other models. Random forest analysis showed that the three most important climatic variables contributing to snail spread in Shanghai included aridity (11.87%), ≥ 0 °C annual accumulated temperature (10.19%), moisture index (10.18%) and average annual precipitation (9.86%), the two most important vegetation variables included the vegetation index of the first quarter (8.30%) and vegetation index of the second quarter (7.69%). Snails were more likely to spread at aridity of < 0.87, ≥ 0 °C annual accumulated temperature of 5 550 to 5 675 °C, moisture index of > 39% and average annual precipitation of > 1 180 mm, and with the vegetation index of the first quarter of > 0.4 and the vegetation index of the first quarter of > 0.6. According to the water resource developments and township administrative maps, the areas at risk of snail spread were mainly predicted in 10 townships/subdistricts, covering the Xipian, Dongpian and Tainan sections of southern Shanghai. CONCLUSIONS Supervised machine learning models are effective to predict the risk of fine-scale O. hupensis snail spread and identify the environmental determinants relating to snail spread. The areas at risk of O. hupensis snail spread are mainly located in southwestern Songjiang District, northwestern Jinshan District and southeastern Qingpu District of Shanghai Municipality.
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Affiliation(s)
- Y F Gong
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), National Health Commission Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - Z W Luo
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), National Health Commission Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - J X Feng
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), National Health Commission Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - J B Xue
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), National Health Commission Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - Z Y Guo
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), National Health Commission Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - Y J Jin
- Shanghai Municipal Center for Disease Control and Prevention, China
| | - Q Yu
- Shanghai Municipal Center for Disease Control and Prevention, China
| | - S Xia
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), National Health Commission Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - S Lü
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), National Health Commission Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - J Xu
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), National Health Commission Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - S Z Li
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), National Health Commission Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Shanghai 200025, China
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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Wu G, Wang H, Zhao C, Cao C, Chai C, Huang L, Guo Y, Gong Z, Tirschwell D, Zhu C, Xia S. Large Culprit Plaque and More Intracranial Plaques Are Associated with Recurrent Stroke: A Case-Control Study Using Vessel Wall Imaging. AJNR Am J Neuroradiol 2022; 43:207-215. [PMID: 35058299 PMCID: PMC8985671 DOI: 10.3174/ajnr.a7402] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 11/02/2021] [Indexed: 02/03/2023]
Abstract
BACKGROUND AND PURPOSE Intracranial atherosclerotic plaque features are potential factors associated with recurrent stroke, but previous studies only focused on a single lesion, and few studies investigated them with perfusion impairment. This study aimed to investigate the association among whole-brain plaque features, perfusion deficit, and stroke recurrence. MATERIALS AND METHODS Patients with ischemic stroke due to intracranial atherosclerosis were retrospectively collected and categorized into first-time and recurrent-stroke groups. Patients underwent high-resolution vessel wall imaging and DSC-PWI. Intracranial plaque number, culprit plaque features (such as plaque volume/burden, degree of stenosis, enhancement ratio), and perfusion deficit variables were recorded. Logistic regression analyses were performed to determine the independent factors associated with recurrent stroke. RESULTS One hundred seventy-five patients (mean age, 59 [SD, 12] years; 115 men) were included. Compared with the first-time stroke group (n = 100), the recurrent-stroke group (n = 75) had a larger culprit volume (P = .006) and showed more intracranial plaques (P < .001) and more enhanced plaques (P = .003). After we adjusted for other factors, culprit plaque volume (OR, 1.16 per 10-mm3 increase; 95% CI, 1.03-1.30; P = .015) and total plaque number (OR, 1.31; 95% CI, 1.13-1.52; P < .001) were independently associated with recurrent stroke. Combining these factors increased the area under the curve to 0.71. CONCLUSIONS Large culprit plaque and more intracranial plaques were independently associated with recurrent stroke. Performing whole-brain vessel wall imaging may help identify patients with a higher risk of recurrent stroke.
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Affiliation(s)
- G. Wu
- From The School of Medicine (G.W., H.W.), Nankai University, Tianjin, China
| | - H. Wang
- From The School of Medicine (G.W., H.W.), Nankai University, Tianjin, China
| | - C. Zhao
- Department of Radiology (C. Zhao), First Central Clinical College, Tianjin Medical University, Tianjin, China
| | - C. Cao
- Department of Radiology (C. Cao), Tianjin Huanhu Hospital, Tianjin, China
| | - C. Chai
- Department of Radiology (C. Chai, L.H., Y.G., S.X.)
| | - L. Huang
- Department of Radiology (C. Chai, L.H., Y.G., S.X.)
| | - Y. Guo
- Department of Radiology (C. Chai, L.H., Y.G., S.X.)
| | - Z. Gong
- Neurology (Z.G.), Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | | | - C. Zhu
- Radiology (C. Zhu), University of Washington, Seattle, Washington
| | - S. Xia
- Department of Radiology (C. Chai, L.H., Y.G., S.X.)
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14
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Xia S, Zhang Z. Circular RNA hsa_circ_0000317 inhibits non-small cell lung cancer progression through regulating microRNA-494-3p/phosphatase and tensin homolog deleted on chromosome 10 axis. Clinics (Sao Paulo) 2022; 77:100086. [PMID: 35917658 PMCID: PMC9344349 DOI: 10.1016/j.clinsp.2022.100086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 12/07/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Circular RNA (circRNA), a group of non-coding RNA, is pivotal in the progression of various cancers, including Non-Small Cell Lung Cancer (NSCLC). Some circRNAs have been reported to be implicated in the progression of NSCLC, however, the function and molecular mechanism of hsa_circ_0000317 (circ_0000317) in NSCLC have not been fully understood. METHODS The significantly differentially expressed circRNA in NSCLC tissues, circ_0000317, was screened out by microarray. Circ_0000317, microRNA(miR)-494-3p and Phosphatase and Tensin Homolog Deleted on Chromosome 10 (PTEN) expressions in NSCLC tissues were respectively probed by quantitative real-time polymerase chain reaction and western blot assay. MTT and Transwell assays were adopted to examine the growth, migration, and invasion of NSCLC cells. Bioinformatics, luciferase reporter gene assay, RNA immunoprecipitation, and RNA pull-down assay were conducted to probe the relationships among circ_0000317, miR-494-3p, and PTEN. RESULTS Circ_0000317 expression level was reduced in NSCLC tissues and cell lines. Circ_0000317 expression in NSCLC patients was associated with TNM stage and lymphatic metastasis. Circ_0000317 overexpression restrained the proliferation, migration, and invasion of NSCLC cells, but co-transfection of miR-494-3p mimics partially reversed this effect. In addition, circ_0000317, was identified as a competitive endogenous RNA, which could sponge miR-494-3p to increase PTEN expression and activate PI3K/AKT pathway. CONCLUSION Circ_0000317, inhibits NSCLC progression via modulating miR-494-3p/PTEN/PI3K/AKT pathway.
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Affiliation(s)
- Shihui Xia
- Department of Cardiothoracic Surgery, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Hubei, China
| | - Zengwang Zhang
- Department of Cardiothoracic Surgery, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Hubei, China.
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15
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Tsimikas S, Karwatowska-Prokopczuk E, Clouet-Foraison N, Xia S, Viney N, Witztum J, Marcovina S. Prevalence and influence of LPA gene variants and isoform size on the Lp(a)-lowering effect of antisense oligonucleotides. Atherosclerosis 2021. [DOI: 10.1016/j.atherosclerosis.2021.06.337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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16
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Xin JF, Sun YG, Xia S, Chang K, Zhu Y, Liu X, An R, Su WC, Shen WB. [Clinical features of primary isolated chylopericardium: a retrospective review study]. Zhonghua Wai Ke Za Zhi 2021; 59:507-512. [PMID: 34102736 DOI: 10.3760/cma.j.cn112139-20200724-00577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To examine the clinical characteristics and abnormal reflux branches of primary isolated chylopericardium. Methods: Totally 43 patients with primary isolated chylopericardium at Department of Lymphatic Surgery, Affiliated Beijing Shijitan Hospital,Capital Medical University from June 2007 to January 2018 were recruited in this study. There were 21 males and 22 females, aging (23.0±15.9) years (range: 2 to 57 years). The levels of triglyceride, total cholesterol, total protein and albumin in pericardial effusion and blood were compared by paired-t test, and the characteristics of lymphatic system in direct lymphangiography and postoperative CT were analyzed. Results: Pericardial effusion was mainly milky white and monocytes, and 95.3%(41/43) were positive for Rivalta test. The level of triglyceride in pericardial effusion was significantly higher than that of blood ((9.67±5.11) mmol/L vs. (1.28±0.89) mmol/L, t=10.557, P<0.01), and the levels of total cholesterol ((2.19±0.52) mmol/L vs. (4.12±1.06) mmol/L, t=-3.732, P<0.01), total protein ((61.25±16.17) g/L vs. (68.26±8.30) g/L, t=-2.958, P=0.005) and albumin ((36.63±7.06) g/L vs. (42.32±4.73) g/L, t=-5.747, P<0.01) were significantly lower than that of blood. In the direct lymphangiography, the imaging of iliac and retroperitoneal lymphatics showed dilated or tortuous in 90.7% (39/43), the thoracoabdominal segment of thoracic duct showed dilation in 46.5% (20/43), and cervical thoracic duct imaging showed dilation in 44.2% (19/43) and stenosis in 55.8% (24/43). The image of lipiodol flowing into the vein showed obstruction at the venous angle. There were 60.5%(26/43) of the patients with lipiodol reflux through the bronchomediastinal trunk (type Ⅰ), 11.6%(5/43) with lipiodol diffusion to the pericardium through the abnormal pathway from the thoracic segment of the thoracic duct (type Ⅱ), while no communication pathway between the thoracic duct and the pericardial cavity (type Ⅲ) found in 27.9%(12/43). CT images obtained after the direct lymphangiography showed 34.9%(15/43) had abnormal distribution of lipiodol in pericardium, mediastinal lymph nodes and lung hilar lymph nodes, 46.5%(20/43) in mediastinal lymph nodes and lung hilar lymph nodes, 14.0%(6/43) only mediastinal lymph nodes, 4.6%(2/43) had no lipiodol in the above areas. Conclusions: Pericardial effusion compared with same period blood, has higher triglyceride, lower total cholesterol, total protein and albumin. The obstruction of the cervical segment of the thoracic duct and the formation of abnormal reflux branches would be corelative to primary isolated chylopericardium.
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Affiliation(s)
- J F Xin
- Department of Lymphatic Surgery, Affiliated Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - Y G Sun
- Department of Lymphatic Surgery, Affiliated Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - S Xia
- Department of Lymphatic Surgery, Affiliated Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - K Chang
- Department of Lymphatic Surgery, Affiliated Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - Y Zhu
- Department of Lymphatic Surgery, Affiliated Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - X Liu
- Department of Lymphatic Surgery, Affiliated Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - R An
- Department of Lymphatic Surgery, Affiliated Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - W C Su
- Department of Lymphatic Surgery, Affiliated Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - W B Shen
- Department of Lymphatic Surgery, Affiliated Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
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Liu Y, Yu J, Liu J, Wu B, Cui Q, Shen W, Xia S. Prognostic value of late gadolinium enhancement in arrhythmogenic right ventricular cardiomyopathy: a meta-analysis. Clin Radiol 2021; 76:628.e9-628.e15. [PMID: 34024635 DOI: 10.1016/j.crad.2021.04.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 04/14/2021] [Indexed: 01/11/2023]
Abstract
AIM To assess systematically the prognostic value of cardiac magnetic resonance imaging (CMRI) in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC). MATERIALS AND METHODS The full text of studies of the clinical efficacy of late gadolinium enhancement (LGE) in ARVC was retrieved in multiple databases. Stata 14 was adopted for meta-analysis and bias analysis. Heterogeneity was assessed with the I2 statistic. RESULTS After exclusions, 561 patients were included in five studies, and the eligibility criteria were met. The meta-analysis suggested that there was a significant difference between LGE positive and negative patients with ARVC in all-cause mortality (relative risk [RR] = 4.78, 95% confidence interval [CI] = 1.41, 16.23, p=0.012; p for heterogeneity = 0.692, I2 = 0%); major adverse cardiovascular events (MACE) (RR=2.48, 95% CI = 1.24, 4.96, p=0.010; p for heterogeneity = 0.596, I2 = 0%); ventricular tachycardia (RR=3.13, 95% CI = 1.69, 5.78, p<0.001; p for heterogeneity = 0.825, I2 = 0%); implanted cardiac defibrillators (RR=3.15, 95% CI = 1.69, 5.87], p<0.001; p for heterogeneity = 0.353, I2 = 9.4%). CONCLUSION LGE in ARVC patients is a predictor of all-cause mortality and MACE.
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Affiliation(s)
- Y Liu
- Department of Radiology, Tianjin First Central Hospital, No. 24, Fukang Road, Nankai District, Tianjin, 300000, China
| | - J Yu
- Department of Radiology, Tianjin First Central Hospital, No. 24, Fukang Road, Nankai District, Tianjin, 300000, China
| | - J Liu
- Outpatient Department, Tianjin Third Central Hospital, No. 83, Jintang Road, Hedong District, Tianjin, 300000, China
| | - B Wu
- Department of Radiology, Tianjin First Central Hospital, No. 24, Fukang Road, Nankai District, Tianjin, 300000, China
| | - Q Cui
- Department of Radiology, Tianjin First Central Hospital, No. 24, Fukang Road, Nankai District, Tianjin, 300000, China
| | - W Shen
- Department of Radiology, Tianjin First Central Hospital, No. 24, Fukang Road, Nankai District, Tianjin, 300000, China.
| | - S Xia
- Department of Radiology, Tianjin First Central Hospital, No. 24, Fukang Road, Nankai District, Tianjin, 300000, China.
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18
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Zheng JX, Xia S, Lü S, Zhang Y, Zhou XN. [Construction of a forecast system for prediction of schistosomiasis risk in China based on the flood information]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2021; 33:133-137. [PMID: 34008359 DOI: 10.16250/j.32.1374.2020253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
OBJECTIVE To create a model based on meteorological data to predict the regions at risk of schistosomiasis during the flood season, so as to provide insights into the surveillance and forecast of schistosomiasis. METHODS An interactive schistosomiasis forecast system was created using the open-access R software. The schistosomiasis risk index was used as a basic parameter, and the species distribution model of Oncomelania hupensis snails was generated according to the cumulative rainfall and temperature to predict the probability of O. hupensis snail distribution, so as to identify the regions at risk of schistosomiasis transmission during the flood season. RESULTS The framework of the web page was built using the Shiny package in the R program, and an interactive and visualization system was successfully created to predict the distribution of O. hupensis snails, containing O. hupensis snail surveillance site database, meteorological and environmental data. In this system, the snail distribution area may be displayed and the regions at risk of schistosomiasis transmission may be predicted using the species distribution model. This predictive system may rapidly generate the schistosomiasis transmission risk map, which is simple and easy to perform. In addition, the regions at risk of schistosomiasis transmission were predicted to be concentrated in the middle and lower reaches of the Yangtze River during the flood period. CONCLUSIONS A schistosomiasis forecast system is successfully created, which is accurate and rapid to utilize meteorological data to predict the regions at risk of schistosomiasis transmission during the flood period.
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Affiliation(s)
- J X Zheng
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); NHC Key Laboratory of Parasite and Vector Biology; WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - S Xia
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); NHC Key Laboratory of Parasite and Vector Biology; WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - S Lü
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); NHC Key Laboratory of Parasite and Vector Biology; WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - Y Zhang
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); NHC Key Laboratory of Parasite and Vector Biology; WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - X N Zhou
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); NHC Key Laboratory of Parasite and Vector Biology; WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Shanghai 200025, China
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19
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Shi Z, Chen GZ, Mao L, Li XL, Zhou CS, Xia S, Zhang YX, Zhang B, Hu B, Lu GM, Zhang LJ. Machine Learning-Based Prediction of Small Intracranial Aneurysm Rupture Status Using CTA-Derived Hemodynamics: A Multicenter Study. AJNR Am J Neuroradiol 2021; 42:648-654. [PMID: 33664115 PMCID: PMC8041003 DOI: 10.3174/ajnr.a7034] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Accepted: 11/09/2020] [Indexed: 01/08/2023]
Abstract
BACKGROUND AND PURPOSE Small intracranial aneurysms are being increasingly detected while the rupture risk is not well-understood. We aimed to develop rupture-risk models of small aneurysms by combining clinical, morphologic, and hemodynamic information based on machine learning techniques and to test the models in external validation datasets. MATERIALS AND METHODS From January 2010 to December 2016, five hundred four consecutive patients with only small aneurysms (<5 mm) detected by CTA and invasive cerebral angiography (or surgery) were retrospectively enrolled and randomly split into training (81%) and internal validation (19%) sets to derive and validate the proposed machine learning models (support vector machine, random forest, logistic regression, and multilayer perceptron). Hemodynamic parameters were obtained using computational fluid dynamics simulation. External validation was performed in other hospitals to test the models. RESULTS The support vector machine performed the best with areas under the curve of 0.88 (95% CI, 0.85-0.92) and 0.91 (95% CI, 0.74-0.98) in the training and internal validation datasets, respectively. Feature ranks suggested hemodynamic parameters, including stable flow pattern, concentrated inflow streams, and a small (<50%) flow-impingement zone, and the oscillatory shear index coefficient of variation, were the best predictors of aneurysm rupture. The support vector machine showed an area under the curve of 0.82 (95% CI, 0.69-0.94) in the external validation dataset, and no significant difference was found for the areas under the curve between internal and external validation datasets (P = .21). CONCLUSIONS This study revealed that machine learning had a good performance in predicting the rupture status of small aneurysms in both internal and external datasets. Aneurysm hemodynamic parameters were regarded as the most important predictors.
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Affiliation(s)
- Z Shi
- From the Department of Diagnostic Radiology (Z.S., C.S.Z., B.H., G.M.L., L.J.Z.), Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - G Z Chen
- Department of Medical Imaging (G.Z.C.), Nanjing First Hospital, Nanjing, Jiangsu, China
| | - L Mao
- Deepwise AI Lab (L.M., X.L.L.), Beijing, China
| | - X L Li
- Deepwise AI Lab (L.M., X.L.L.), Beijing, China
| | - C S Zhou
- From the Department of Diagnostic Radiology (Z.S., C.S.Z., B.H., G.M.L., L.J.Z.), Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - S Xia
- Department of Radiology (S.X.), Tianjin First Central Hospital, Tianjin, China
| | - Y X Zhang
- Laboratory of Image Science and Technology (Y.X.Z.), School of Computer Science and Engineering, Southeast University, Nanjing, China
| | - B Zhang
- Department of Radiology (B.Z.), Taizhou People's Hospital, Taizhou, Jiangsu, China
| | - B Hu
- From the Department of Diagnostic Radiology (Z.S., C.S.Z., B.H., G.M.L., L.J.Z.), Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - G M Lu
- From the Department of Diagnostic Radiology (Z.S., C.S.Z., B.H., G.M.L., L.J.Z.), Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - L J Zhang
- From the Department of Diagnostic Radiology (Z.S., C.S.Z., B.H., G.M.L., L.J.Z.), Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
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Xu L, Xia S, Li LW. [Cardiovascular oncology: opportunities and challenges of interdisciplinarity]. Zhonghua Xin Xue Guan Bing Za Zhi 2021; 49:198-204. [PMID: 33611911 DOI: 10.3760/cma.j.cn112148-20200706-00536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Affiliation(s)
- L Xu
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - S Xia
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - L W Li
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
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Yu Q, Han S, Xue JB, Xia S. [Epidemiological profiles of echinococcosis cases reported in the National Notifiable Disease Report System in non-endemic areas of China from 2004 to 2016]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2021; 33:48-53. [PMID: 33660474 DOI: 10.16250/j.32.1374.2020019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
OBJECTIVE To investigate the epidemiological profiles of echinococcosis cases reported in non-endemic areas of China in the National Notifiable Disease Report System from 2004 to 2016, so as to provide insights into the development of effective surveillance and response measures. METHODS The data pertaining to the echinococcosis cases reported in the National Notifiable Disease Report System in 22 non-endemic provinces of China from 2004 to 2016 were collected, and the epidemiological profiles of the reported echinococcosis cases were descriptively analyzed. RESULTS A total of 462 echinococcosis cases were reported in the 22 non-endemic provinces of China from 2004 to 2016, and the number of reported cases increased with time (χ2 = 4.516, P = 0.034). During the 13-year period from 2004 to 2016, the highest number of echinococcosis cases was reported in central and eastern China (56.49%), followed by in northern and northeastern China (30.30%), and the highest number of echinococcosis cases was reported in Henan Province (99 cases). Among the 462 echinococcosis cases reported, there were 234 men and 228 women, and the mean age was (41.42 ± 16.03) years (range, 4 to 86 years), with the highest number of echinococcosis cases reported at ages of 20 to 50 years (63.20%). The highest proportion of occupations was farmers and herdsmen (36.15%), and the greatest source was from echinococcosis-endemic provinces (50.43%); in addition, 97.40% of the echinococcosis cases were reported by hospitals. CONCLUSIONS Echinococcosis cases were reported in all 22 non-endemic provinces of China in the National Notifiable Disease Report System from 2004 to 2016, and the number of reported cases appeared an overall tendency for sporadicity and local increase with time. Screening of echinococcosis is recommended among famers and herdsmen at ages of 20 to 50 years from endemic regions by medical institutions in non-endemic regions for timely identification and treatment of echinococcosis cases.
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Affiliation(s)
- Q Yu
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Key Laboratory of Parasite and Vector Biology, National Health Commission, Shanghai 200025, China.,Shanghai Municipal Center for Disease Control and Prevention, China
| | - S Han
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Key Laboratory of Parasite and Vector Biology, National Health Commission, Shanghai 200025, China
| | - J B Xue
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Key Laboratory of Parasite and Vector Biology, National Health Commission, Shanghai 200025, China
| | - S Xia
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Key Laboratory of Parasite and Vector Biology, National Health Commission, Shanghai 200025, China
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He B, Xia S, Zhang Z. NudCD1 Promotes the Proliferation and Metastasis of Non-Small Cell Lung Cancer Cells through the Activation of IGF1R-ERK1/2. Pathobiology 2020; 87:244-253. [PMID: 32634806 DOI: 10.1159/000505159] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2019] [Accepted: 11/30/2019] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND NudC domain containing 1 (NudCD1) is an oncoprotein related to diverse cancers. This study aims to investigate the expression, role, and regulatory mechanism of NudCD1 in non-small cell lung cancer (NSCLC). METHODS qRT-PCR, Western blot, and immunohistochemistry were performed to detect the expressions of NudCD1 in NSCLC tissues and cell lines. The correlation between NudCD1 expression and clinical features was determined by the χ2 test. Besides, shRNA was used to construct the NudCD1 low expression model of NCI-H1299 and NCI-H460 cells, and CCK-8 and transwell assay were conducted to monitor the changes of proliferation, migration, and invasion of cancer cells. The expression levels of epithelial-mesenchymal transition markers and IGF1R-ERK1/2 signaling pathway proteins were detected by Western blot. RESULTS The expression of NudCD1 in NSCLC was higher than that in normal tissues, and the increased expression of NudCD1 was significantly correlated with increased T stage and lymph node metastasis. Moreover, patients with high expression of NudCD1 had worse prognosis. NudCD1 knockdown was proven to impede the proliferation but facilitate the migration and invasion of cancer cells. Furthermore, knockdown of NudCD1 resulted in an increase in the expression of E-cadherin and a decrease in the expression of vimentin. We also observed that NudCD1 overexpression promoted the phosphorylation of IGF1R and ERK1/2 proteins. CONCLUSION NudCD1 promotes the proliferation and metastasis of NSCLC cells via activation of IGF1R-ERK1/2, which indicates that NudCD1 may be a potential therapy target of NSCLC.
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Affiliation(s)
- Bin He
- Centre for Cardiothoracic Surgery, Xiangyang Central Hospital, Hospital Affiliated to Hubei University of Arts and Science, Xiangyang, China
| | - Shihui Xia
- Centre for Cardiothoracic Surgery, Xiangyang Central Hospital, Hospital Affiliated to Hubei University of Arts and Science, Xiangyang, China
| | - Zengwang Zhang
- Centre for Cardiothoracic Surgery, Xiangyang Central Hospital, Hospital Affiliated to Hubei University of Arts and Science, Xiangyang, China,
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Bagel J, Blauvelt A, Nia J, Hashim P, Patekar M, de Vera A, Ahmad K, Paguet B, Xia S, Muscianisi E, Lebwohl M. Secukinumab maintains superiority over ustekinumab in clearing skin and improving quality of life in patients with moderate to severe plaque psoriasis: 52-week results from a double-blind phase 3b trial (CLARITY). J Eur Acad Dermatol Venereol 2020; 35:135-142. [PMID: 32365251 PMCID: PMC7818402 DOI: 10.1111/jdv.16558] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 04/21/2020] [Indexed: 01/01/2023]
Abstract
Background Secukinumab demonstrated superior efficacy over ustekinumab in the treatment of moderate to severe plaque psoriasis over 16 weeks in the CLARITY study and over 52 weeks in the CLEAR study. Objective To compare the efficacy and safety of secukinumab vs. ustekinumab over 52 weeks in CLARITY. Methods Analysis of 52‐week data from CLARITY (NCT02826603), a phase 3b study in which patients were randomized to receive secukinumab 300 mg (n = 550) or ustekinumab 45/90 mg (n = 552) per label. Results At week 52, secukinumab was superior to ustekinumab in the proportion of patients who achieved ≥ 90% improvement in Psoriasis Area and Severity Index (73.2% vs. 59.8%; odds ratio [OR], 1.84 [95% CI, 1.41–2.41]; P < 0.0001), Investigator’s Global Assessment modified 2011 responses of clear (0) or almost clear (1) skin (76.0% vs. 60.2%; OR, 2.12 [95% CI, 1.61–2.79]; P < 0.0001) and Dermatology Life Quality Index response of no effect (0/1) (69.9% vs. 61.2%; P = 0.0028). Proportions of patients with any adverse events were comparable between treatment arms. Conclusions This second head‐to‐head study confirmed the superior efficacy of secukinumab over ustekinumab in skin clearance and quality of life through 52 weeks, with safety comparable to that reported in previous trials. Clinicaltrials.gov identifier: NCT02826603.
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Affiliation(s)
- J Bagel
- Psoriasis Treatment Center of Central New Jersey, East Windsor, NJ, USA
| | - A Blauvelt
- Oregon Medical Research Center, Portland, OR, USA
| | - J Nia
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - P Hashim
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - M Patekar
- Novartis Pharma AG, Basel, Switzerland
| | - A de Vera
- Novartis Pharma AG, Basel, Switzerland
| | - K Ahmad
- Novartis Healthcare Pvt Ltd, Hyderabad, India
| | - B Paguet
- Novartis Pharma AG, Basel, Switzerland
| | - S Xia
- Beijing Novartis Pharma Co, Ltd, Shanghai, China
| | - E Muscianisi
- Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA
| | - M Lebwohl
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
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24
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Chai S, Sheng Z, Xie W, Wang C, Liu S, Tang R, Cao C, Xin W, Guo Z, Chang B, Yang X, Zhu J, Xia S. Assessment of Apparent Internal Carotid Tandem Occlusion on High-Resolution Vessel Wall Imaging: Comparison with Digital Subtraction Angiography. AJNR Am J Neuroradiol 2020; 41:693-699. [PMID: 32115423 DOI: 10.3174/ajnr.a6452] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Accepted: 01/15/2020] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Not all tandem occlusions diagnosed on traditional vascular imaging modalities, such as MRA, represent actual complete ICA occlusion. This study aimed to explore the utility of high-resolution vessel wall imaging in identifying true ICA tandem occlusions and screening patients for their suitability for endovascular recanalization. MATERIALS AND METHODS Patients with no signal in the ICA on MRA were retrospectively reviewed. Two neuroradiologists independently reviewed their high-resolution vessel wall images to assess whether there were true tandem occlusions and categorized all cases into intracranial ICA occlusion, extracranial ICA occlusion, tandem occlusion, or near-occlusion. DSA classified patient images into the same 4 categories, which were used as the comparison with high-resolution vessel wall imaging. The suitability for recanalization of occluded vessels was evaluated on high-resolution vessel wall imaging compared with DSA. RESULTS Forty-five patients with no ICA signal on MRA who had available high-resolution vessel wall imaging and DSA images were included. Among the 34 patients (34/45, 75.6%) with tandem occlusions on DSA, 18 cases also showed tandem occlusions on high-resolution vessel wall imaging. The remaining 16 patients, intracranial ICA, extracranial ICA occlusions and near-occlusions were found in 2, 6, and 8 patients, respectively, on the basis of high-resolution vessel wall imaging. A total of 20 cases (20/45, 44.4%) were considered suitable for recanalization on the basis of both DSA and high-resolution vessel wall imaging. Among the 25 patients deemed unsuitable for recanalization by DSA, 11 were deemed suitable for recanalization by high-resolution vessel wall imaging. CONCLUSIONS High-resolution vessel wall imaging could allow identification of true ICA tandem occlusion in patients with an absence of signal on MRA. Findings on high-resolution vessel wall imaging can be used to screen more suitable candidates for recanalization therapy.
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Affiliation(s)
- S Chai
- From the Department of Radiology (S.C., W. Xie, S.L., R.T., S.X.), First Central Clinical College, Tianjin Medical University, Tianjin, China.,Departments of Radiology and (S.C., W. Xie, S.L., R.T., S.X.), Tianjin First Central Hospital, Tianjin, China
| | - Z Sheng
- Neurosurgery (Z.S., C.W., B.C.), Tianjin First Central Hospital, Tianjin, China
| | - W Xie
- From the Department of Radiology (S.C., W. Xie, S.L., R.T., S.X.), First Central Clinical College, Tianjin Medical University, Tianjin, China.,Departments of Radiology and (S.C., W. Xie, S.L., R.T., S.X.), Tianjin First Central Hospital, Tianjin, China
| | - C Wang
- Neurosurgery (Z.S., C.W., B.C.), Tianjin First Central Hospital, Tianjin, China
| | - S Liu
- From the Department of Radiology (S.C., W. Xie, S.L., R.T., S.X.), First Central Clinical College, Tianjin Medical University, Tianjin, China.,Departments of Radiology and (S.C., W. Xie, S.L., R.T., S.X.), Tianjin First Central Hospital, Tianjin, China
| | - R Tang
- From the Department of Radiology (S.C., W. Xie, S.L., R.T., S.X.), First Central Clinical College, Tianjin Medical University, Tianjin, China.,Departments of Radiology and (S.C., W. Xie, S.L., R.T., S.X.), Tianjin First Central Hospital, Tianjin, China
| | - C Cao
- Department of Radiology (C.C.), Tianjin Huanhu Hospital, Tianjin, China
| | - W Xin
- Department of Neurosurgery (W. Xin, X.Y.), Tianjin Medical University General Hospital, Tianjin, China
| | - Z Guo
- Department of Neurosurgery (Z.G.), Tianjin TEDA Hospital, Tianjin, China
| | - B Chang
- Neurosurgery (Z.S., C.W., B.C.), Tianjin First Central Hospital, Tianjin, China
| | - X Yang
- Department of Neurosurgery (W. Xin, X.Y.), Tianjin Medical University General Hospital, Tianjin, China
| | - J Zhu
- MR Collaboration (J.Z.), Siemens Healthcare Ltd., Beijing, China
| | - S Xia
- From the Department of Radiology (S.C., W. Xie, S.L., R.T., S.X.), First Central Clinical College, Tianjin Medical University, Tianjin, China .,Departments of Radiology and (S.C., W. Xie, S.L., R.T., S.X.), Tianjin First Central Hospital, Tianjin, China
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Xia S, Laselva O, Bear CE, Jones N. A115 MODELING CYSTIC FIBROSIS (CF) INTESTINAL DISEASE USING PATIENT DERIVED TISSUES. J Can Assoc Gastroenterol 2020. [DOI: 10.1093/jcag/gwz047.114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Cystic Fibrosis is caused by mutations in the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) gene, which encodes for a chloride/bicarbonate anion channel expressed on the apical membrane of most epithelial tissues, such as the lungs, liver, pancreas, small and large intestines, and reproductive tissues. CFTR is responsible for the transport of chloride and bicarbonate ions to maintain tissue surface hydration and pH balance of epithelial tissues. Historically, recurrent lung infections have been the most common cause of mortality in CF patients. With advances in clinical care and therapeutics, the current mean survival age of Canadian patients has increased to 52.3 years. However, this increase in survival has also been associated with an elevated risk of developing gastrointestinal cancers in CF adults. Compared to the general public, CF patients are 10 times more likely to develop cancer. This risk is increased to 25-20 times in patients that have undergone organ transplantations. Although the exact molecular mechanism regarding increased cancer risk in CF remains unclear, chronic intestinal inflammation has been known to contribute to elevated cancer development.
Aims
CF patients display an increased baseline inflammatory status that is exacerbated with microbiome exposure leading to possible increased risk for inflammation-mediated cancer development.
Methods
To reduce inter-patient heterogeneity, we have differentiated human intestinal organoids using induced pluripotent stem cells from homozygous F508del CF patients and gene edited isogenic non-CF (Wt-CFTR) controls. We conducted gene expression studies using RT-qPCR to determine baseline differences in gene expression prior to environmental exposures and following exposure to LPS and flagellin.
Results
We determined the expression levels of stem cell, intestinal epithelial cell, innate immunity genes and differentiation markers and found expression of such genes were not significantly different between 3D CF and gene-edited non-CF organoids. We are currently conducting RNA sequencing to survey expression pattern of all genes to definitively determine possible fundamental changes in the CF intestinal epithelium and determining the effect of LPS and flagellin treatment to determine if there is an altered response to inflammatory stimuli.
Conclusions
iPSC derived HIOs is a novel, patient based, and renewable model that can be used to dissect the primary intestinal pathologies in CF. Transcriptomic data of CF HIOs at steady state will provide insights to possible developmental defects. Complex interactions between the host intestinal epithelia and the commensal microbiome can also be investigated using this model.
Funding Agencies
CAG
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Affiliation(s)
- S Xia
- Cell Biology, Hospital For Sick Children, Toronto, ON, Canada
| | - O Laselva
- Cell Biology, Hospital For Sick Children, Toronto, ON, Canada
| | - C E Bear
- Cell Biology, Hospital For Sick Children, Toronto, ON, Canada
| | - N Jones
- The Hospital for Sick Children, Toronto, ON, Canada
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Chen Y, Peng P, Chen Y, Xia S. P2.11-44 A Preliminary Study Investigating the Impact of Platelet on Circulating Tumor Cell Enumeration. J Thorac Oncol 2019. [DOI: 10.1016/j.jtho.2019.08.1744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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27
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Peng P, Chen Y, Han G, Meng R, Zhang S, Liao Z, Zhang Y, Gong J, Xiao C, Liu X, Zhang P, Zhang L, Xia S, Chu Q, Chen Y, Zhang L. MA01.09 Concomitant SBRT and EGFR-TKI Versus EGFR-TKI Alone for Oligometastatic NSCLC: A Multicenter, Randomized Phase II Study. J Thorac Oncol 2019. [DOI: 10.1016/j.jtho.2019.08.499] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Azgahdi S, Candas D, Xie B, Zhang L, Zhang Y, Fan M, Liu L, Sweeney C, Pan C, Ozpiskin O, Vaughan A, Wang J, Xia S, Monjazeb A, Woloschak G, Grdina D, Murphy W, Sun L, Chen H, Lam K, Weichselbaum R, Li J. Dual Blockade of CD47 and HER2 Re-sensitizes Resistant Breast Cancer Cells to Radiation Therapy. Int J Radiat Oncol Biol Phys 2019. [DOI: 10.1016/j.ijrobp.2019.06.705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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29
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Hao B, Chen Z, Zeng G, Huang L, Luan C, Xie Z, Chen J, Bao M, Tian X, Xu B, Wang Y, Wu J, Xia S, Yuan L, Huang J. Efficacy, safety and immunogenicity of live attenuated varicella vaccine in healthy children in China: double-blind, randomized, placebo-controlled clinical trial. Clin Microbiol Infect 2019; 25:1026-1031. [DOI: 10.1016/j.cmi.2018.12.033] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Revised: 12/18/2018] [Accepted: 12/22/2018] [Indexed: 10/27/2022]
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30
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Boffa M, Marar T, Borrelli M, Yeang C, Viney N, Xia S, Witztum J, Koschinsky M, Tsimikas S. Reduction Of Plasma Lipoprotein(A) With Antisense Oligonucleotides In Human Subjects Does Not Affect Fibrinolysis. Atherosclerosis 2019. [DOI: 10.1016/j.atherosclerosis.2019.06.167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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31
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Liu R, Zhou J, Xia S, Li T. The impact of PTEN deletion and ERG rearrangement on recurrence after treatment for prostate cancer: a systematic review and meta-analysis. Clin Transl Oncol 2019; 22:694-702. [DOI: 10.1007/s12094-019-02170-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2019] [Accepted: 06/28/2019] [Indexed: 11/28/2022]
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32
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Habinshuti I, Chen X, Yu J, Mukeshimana O, Duhoranimana E, Karangwa E, Muhoza B, Zhang M, Xia S, Zhang X. Antimicrobial, antioxidant and sensory properties of Maillard reaction products (MRPs) derived from sunflower, soybean and corn meal hydrolysates. Lebensm Wiss Technol 2019. [DOI: 10.1016/j.lwt.2018.11.083] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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Qian G, Xu X, Chen L, Xia S, Wang A, Chuai Y, Jiang W. The effect of maternal low flow oxygen administration during the second stage of labour on umbilical cord artery pH: a randomised controlled trial. BJOG 2018; 124:678-685. [PMID: 28224745 DOI: 10.1111/1471-0528.14418] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/28/2016] [Indexed: 11/29/2022]
Abstract
OBJECTIVE To assess the effect of maternal low flow oxygen administration during the second stage of labour on umbilical cord artery pH. DESIGN A randomised controlled trial. SETTING A tertiary teaching hospital in China. POPULATION Women in the second stage of labour with no complications. METHODS About 443 women were randomly allocated to receive either supplemental oxygen at a flow rate of 2 l/min or a sham supplementation by nasal cannula. Healthcare providers, women and outcome assessors were blinded to allocation. MAIN OUTCOME MEASURES Umbilical cord artery pH and fetal heart rate (FHR) pattern. RESULTS Baseline characteristics were similar between the two groups. There were no significant differences between the two groups in the umbilical cord artery pH [median 7.261, interquartile range (IQR) 7.228-7.295 versus 7.266 (IQR 7.232-7.297), P = 0.64], the proportion with pH less than 7.2 [30/219 versus 34/224, P = 0.66, RR (relative risk) 0.9, 95% CI 0.57-1.42], and the proportion with normal FHR pattern (147/219 versus 153/224, P = 0.79, RR 0.98, 95% CI 0.86-1.12). Maternal partial pressure of dissolved oxygen was significantly higher in the oxygen group than in the sham group [median 150.0 mmHg (IQR 142.6-156.7) versus 112.0 (IQR 104.8-118.3), P < 0.001], whereas carbon dioxide was significantly lower in the oxygen group than in the sham group (mean difference -1.1, 95% CI -2.1 to -0.1, P = 0.03). CONCLUSION The use of 2 l/min maternal oxygen during the second stage of labour did not adversely affect either the umbilical artery pH or the FHR pattern distribution. TWEETABLE ABSTRACT No difference in abnormal fetal acid base or normal heart rate if maternal O2 given, randomised trial finds.
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Affiliation(s)
- G Qian
- Department of Obstetrics and Gynaecology, Navy General Hospital, Beijing, China
| | - X Xu
- Department of Anaesthesia, Navy General Hospital, Beijing, China.,Department of Anaesthesia, Chaoyang Chinese Traditional and Western Medicine Emergency Medical Center, Beijing, China
| | - L Chen
- Department of Obstetrics and Gynaecology, Navy General Hospital, Beijing, China
| | - S Xia
- Department of Obstetrics and Gynaecology, Navy General Hospital, Beijing, China
| | - A Wang
- Department of Obstetrics and Gynaecology, Navy General Hospital, Beijing, China
| | - Y Chuai
- Department of Obstetrics and Gynaecology, Navy General Hospital, Beijing, China
| | - W Jiang
- Department of Obstetrics and Gynaecology, Navy General Hospital, Beijing, China
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Xia S, Chuai S, Chen Y, Huang L, Deng W, Zhang H, Zhang Y, Xu F, Ren X, Chen Y. P2.03-36 DNA Methylation: A More Sensitive Marker for Treatment Monitoring? J Thorac Oncol 2018. [DOI: 10.1016/j.jtho.2018.08.1223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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35
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Myles N, Myles H, Xia S, Large M, Kisely S, Galletly C, Bird R, Siskind D. Meta-analysis examining the epidemiology of clozapine-associated neutropenia. Acta Psychiatr Scand 2018; 138:101-109. [PMID: 29786829 DOI: 10.1111/acps.12898] [Citation(s) in RCA: 111] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/20/2018] [Indexed: 12/19/2022]
Abstract
BACKGROUND Clozapine is associated with life-threatening neutropenia. There are no previous meta-analyses of the epidemiology of clozapine-associated neutropenia. OBJECTIVES To determine the cumulative incidence of mild, moderate and severe neutropenia, incidence of death related to severe neutropenia, case fatality rate of neutropenia and the longitudinal incidence of neutropenia following exposure to clozapine. DATA SOURCES A systematic search of Medline, EMBASE and PsycINFO using search terms [clozapine OR clopine OR zaponex OR clozaril] AND [neutropenia OR agranulocytosis]. METHODS Random effects meta-analysis to determine event rates and longitudinal incidence of events per 100 person-years of exposure. RESULTS A total of 108 studies were included. The incidence of clozapine-associated neutropenia was 3.8% (95% CI: 2.7-5.2%) and severe neutropenia 0.9% (95% CI: 0.7-1.1%). The incidence of death related to neutropenia following prescription of clozapine was 0.013% (95% CI: 0.01-0.017%). The case fatality rate of severe neutropenia was 2.1% (95% CI: 1.6-2.8%). The peak incidence of severe neutropenia occurred at one month of exposure and declined to negligible levels after one year of treatment. CONCLUSION Severe neutropenia associated with clozapine is a rare event and occurs early with a substantial decline in risk after one year of exposure. Death from clozapine-associated neutropenia is extremely rare. Implications for haematological monitoring are discussed.
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Affiliation(s)
- N Myles
- Haematology Directorate, SA Pathology, Adelaide, SA, Australia.,School of Medicine, University of Queensland, St Lucia, Qld, Australia
| | - H Myles
- Country Health, Glenside, SA, Australia.,Discipline of Psychiatry, University of Adelaide, Adelaide, SA, Australia
| | - S Xia
- Prince of Wales Hospital, Randwick, NSW, Australia
| | - M Large
- Prince of Wales Hospital, Randwick, NSW, Australia.,School of Psychiatry, University of New South Wales, Randwick, NSW, Australia
| | - S Kisely
- School of Medicine, University of Queensland, St Lucia, Qld, Australia.,Departments of Psychiatry, Community Health and Epidemiology, Dalhousie University, Halifax, NS, Canada
| | - C Galletly
- Discipline of Psychiatry, University of Adelaide, Adelaide, SA, Australia.,Northern Adelaide Local Health Network, Adelaide, SA, Australia.,Mental Health, Ramsey Healthcare, Gilberton, SA, Australia
| | - R Bird
- Division of Cancer Services, Princess Alexandra Hospital, Woolloongabba, Qld, Australia.,School of Medicine, Griffith University, Parkwood, Qld, Australia
| | - D Siskind
- School of Medicine, University of Queensland, St Lucia, Qld, Australia.,Metro South Addiction and Mental Health Service, Woolloongabba, Qld, Australia
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Begoyan VV, Weseliński ŁJ, Xia S, Fedie J, Kannan S, Ferrier A, Rao S, Tanasova M. Multicolor GLUT5-permeable fluorescent probes for fructose transport analysis. Chem Commun (Camb) 2018; 54:3855-3858. [PMID: 29594264 DOI: 10.1039/c7cc09809j] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The specificity of carbohydrate transporters towards their substrates poses a significant challenge for the development of molecular probes to monitor sugar uptake in cells for biochemical and biomedical applications. Herein we report a new set of coumarin-based fluorescent sugar conjugates applicable for the analysis of fructose uptake due to their free passage through the fructose-specific transporter GLUT5. The reported probes cover a broad range of the fluorescence spectrum providing essential tools for the evaluation of fructose transport capacity in live cells.
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Affiliation(s)
- V V Begoyan
- Department of Chemistry, Michigan Technological University, 1400 Townsend Drive, Houghton, Michigan 49331, USA.
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Ge J, Cui X, Shi Y, Zhao L, Wei C, Wen S, Xia S, Chen H. Correction to: Development and application of an indirect enzyme-linked immunosorbent assay based on recombinant capsid protein for the detection of mink circovirus infection. BMC Vet Res 2018; 14:128. [PMID: 29636037 PMCID: PMC5894238 DOI: 10.1186/s12917-018-1449-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Accepted: 03/27/2018] [Indexed: 11/13/2022] Open
Affiliation(s)
- J Ge
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, 150030, China. .,Northeastern Science Inspection Station, China Ministry of Agriculture Key Laboratory of Animal Pathogen Biology, Harbin, 150030, China.
| | - X Cui
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, 150030, China
| | - Y Shi
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, 150030, China
| | - L Zhao
- Laboratory Animal and Comparative Medicine Unit, Harbin Veterinary Research Institute, The Chinese Academy of Agricultural Sciences, No. 678 Haping Rd, Harbin, 150069, China
| | - C Wei
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, 150030, China
| | - S Wen
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, 150030, China
| | - S Xia
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, 150030, China
| | - H Chen
- Laboratory Animal and Comparative Medicine Unit, Harbin Veterinary Research Institute, The Chinese Academy of Agricultural Sciences, No. 678 Haping Rd, Harbin, 150069, China
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Bissonnette R, Luger T, Thaçi D, Toth D, Lacombe A, Xia S, Mazur R, Patekar M, Charef P, Milutinovic M, Leonardi C, Mrowietz U. Secukinumab demonstrates high sustained efficacy and a favourable safety profile in patients with moderate-to-severe psoriasis through 5 years of treatment (SCULPTURE Extension Study). J Eur Acad Dermatol Venereol 2018; 32:1507-1514. [PMID: 29444376 PMCID: PMC6175198 DOI: 10.1111/jdv.14878] [Citation(s) in RCA: 141] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2017] [Accepted: 01/29/2018] [Indexed: 12/14/2022]
Abstract
BACKGROUND Secukinumab, a fully human monoclonal antibody that selectively neutralizes IL-17A, has been shown to have significant efficacy and a favourable safety profile in the treatment of moderate-to-severe psoriasis and psoriatic arthritis. OBJECTIVE To assess the efficacy and safety of secukinumab through 5 years of treatment in moderate-to-severe psoriasis. METHODS In the core SCULPTURE study, Psoriasis Area and Severity Index (PASI) 75 responders at Week 12 continued receiving subcutaneous secukinumab until Year 1. Thereafter, patients entered the extension phase and continued treatment as per the core trial. Treatment was double-blinded until the end of Year 3 and open-label from Year 4. Here, we focus on the 300 mg fixed-interval (every 4 weeks) treatment, the recommended per label dose. Efficacy data are primarily reported as observed, but multiple imputation (MI) and last observation carried forward (LOCF) techniques were also undertaken as supportive analyses. RESULTS At Year 1, 168 patients entered the extension study and at the end of Year 5, 126 patients completed 300 mg (every 4 weeks) treatment. PASI 75/90/100 responses at Year 1 (88.9%, 68.5% and 43.8%, respectively) were sustained to Year 5 (88.5%, 66.4% and 41%). PASI responses were consistent regardless of the analysis undertaken (as observed, MI, or LOCF). The average improvement in mean PASI was approximately 90% through 5 years compared with core study baseline. DLQI (dermatology life quality index) 0/1 response also sustained through 5 years (72.7% at Year 1 and 65.5% at Year 5). The safety profile of secukinumab remained favourable, with no cumulative or unexpected safety concerns identified. CONCLUSION Secukinumab 300 mg treatment delivered high and sustained levels of skin clearance and improved quality of life through 5 years in patients with moderate-to-severe psoriasis. Favourable safety established in the secukinumab phase 2/3 programme was maintained through 5 years.
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Affiliation(s)
| | - T Luger
- Department of Dermatology, University of Münster, Münster, Germany
| | - D Thaçi
- Comprehensive Center for Inflammation Medicine, University Hospital Schleswig-Holstein, Lübeck, Germany
| | - D Toth
- Department of Geriatric and Environmental Dermatology, Probity Medical Research Windsor and XLR8 Medical Research, Windsor, ON, Canada
| | - A Lacombe
- Novartis Pharma AG, Basel, Switzerland
| | - S Xia
- Beijing Novartis Pharma Co. Ltd., Shanghai, China
| | - R Mazur
- Novartis Pharma AG, Basel, Switzerland
| | - M Patekar
- Novartis Pharma AG, Basel, Switzerland
| | - P Charef
- Novartis Pharma AG, Basel, Switzerland
| | | | - C Leonardi
- Department of Dermatology, Saint Louis University Health Science Center, St Louis, MO, USA
| | - U Mrowietz
- Department of Dermatology, Psoriasis-Center, University Medical Center Schleswig-Holstein, Kiel, Germany
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Nie J, Patrocinio AOT, Hamid S, Sieland F, Sann J, Xia S, Bahnemann DW, Schneider J. New insights into the plasmonic enhancement for photocatalytic H2 production by Cu–TiO2 upon visible light illumination. Phys Chem Chem Phys 2018; 20:5264-5273. [DOI: 10.1039/c7cp07762a] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Cu nanoparticles were deposited on the surface of commercial TiO2 nanoparticles (Cu–TiO2) using different methods aiming at the production of highly efficient visible light photocatalysts.
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Affiliation(s)
- J. Nie
- Key Laboratory of Marine Chemistry Theory and Technology
- Ministry of Education
- College of Chemistry and Chemical Engineering
- Ocean University of China
- 266100 Qingdao
| | - A. O. T. Patrocinio
- Institut für Technische Chemie
- Leibniz Universität Hannover
- D-30167 Hannover
- Germany
- Laboratory of Photochemistry and Materials Science
| | - S. Hamid
- Institut für Technische Chemie
- Leibniz Universität Hannover
- D-30167 Hannover
- Germany
| | - F. Sieland
- Institut für Technische Chemie
- Leibniz Universität Hannover
- D-30167 Hannover
- Germany
| | - J. Sann
- Justus-Liebig-University Giessen
- Institute of Physical Chemistry
- 35392 Giessen
- Germany
| | - S. Xia
- Key Laboratory of Marine Chemistry Theory and Technology
- Ministry of Education
- College of Chemistry and Chemical Engineering
- Ocean University of China
- 266100 Qingdao
| | - D. W. Bahnemann
- Institut für Technische Chemie
- Leibniz Universität Hannover
- D-30167 Hannover
- Germany
- Laboratory “Photoactive Nanocomposite Materials”
| | - J. Schneider
- Institut für Technische Chemie
- Leibniz Universität Hannover
- D-30167 Hannover
- Germany
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40
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Bissonnette R, Luger T, Thaçi D, Toth D, Konstantinou MP, Lacour JP, Joly P, Goujon C, Becherel PA, Letzelter K, Xia S, Mazur R, Milutinovic M, Martin L, Leonardi C. Sécukinumab : efficacité et tolérance à 4 ans dans le psoriasis modéré à sévère (extension de l’étude SCUPTURE). Ann Dermatol Venereol 2017. [DOI: 10.1016/j.annder.2017.09.430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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41
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Jing Y, Nguyen MM, Wang D, Pascal LE, Guo W, Xu Y, Ai J, Deng FM, Masoodi KZ, Yu X, Zhang J, Nelson JB, Xia S, Wang Z. DHX15 promotes prostate cancer progression by stimulating Siah2-mediated ubiquitination of androgen receptor. Oncogene 2017; 37:638-650. [PMID: 28991234 PMCID: PMC5794523 DOI: 10.1038/onc.2017.371] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2017] [Revised: 08/03/2017] [Accepted: 08/25/2017] [Indexed: 11/24/2022]
Abstract
Androgen receptor (AR) activation is critical for prostate cancer development and progression, including castration-resistance. The nuclear export signal of AR (NESAR) plays an important role in AR intracellular trafficking and proteasome-dependent degradation. Here, we identified the RNA helicase DHX15 as a novel AR co-activator using a yeast mutagenesis screen and revealed that DHX15 regulates AR activity by modulating E3 ligase Siah2-mediated AR ubiquitination independent of its ATPase activity. DHX15 and Siah2 form a complex with AR, through NESAR. DHX15 stabilized Siah2 and enhanced its E3 ubiquitin ligase activity, resulting in AR activation. Importantly, DHX15 was upregulated in prostate cancer specimens and its expression was correlated with Gleason scores and PSA recurrence. Furthermore, DHX15 immunostaining correlated with Siah2. Finally, DHX15 knockdown inhibited the growth of C4-2 prostate tumor xenografts in mice. Collectively, our data argue that DHX15 enhances AR transcriptional activity and contributes to prostate cancer progression through Siah2.
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Affiliation(s)
- Y Jing
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.,Department of Urology, University of Pittsburgh Cancer Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - M M Nguyen
- Department of Urology, University of Pittsburgh Cancer Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - D Wang
- Department of Urology, University of Pittsburgh Cancer Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - L E Pascal
- Department of Urology, University of Pittsburgh Cancer Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - W Guo
- Department of Urology, University of Pittsburgh Cancer Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.,Department of Pathology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Y Xu
- Department of Urology, University of Pittsburgh Cancer Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.,Department of Urology, The Second Xiangya Hospital of Central South University, Hunan, China.,The third Xiangya Hospital of Central South University, Changsha, China
| | - J Ai
- Department of Urology, University of Pittsburgh Cancer Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - F-M Deng
- Department of Pathology, NYU School of Medicine, New York, NY, USA
| | - K Z Masoodi
- Department of Urology, University of Pittsburgh Cancer Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.,Transcriptomics Lab, Division of Plant Biotechnology, SKUAST-K, Shalimar, Srinagar, J&K, India
| | - X Yu
- Department of Geriatrics, Guangzhou General Hospital of Guangzhou Military Command; Guangdong Provincial Key Laboratory of Geriatric Infection and Organ Function Support; Guangzhou Key Laboratory of Geriatric Infection and Organ Function Support; Guangzhou, Guangdong, China.,Cancer Center, Traditional Chinese Medicine-Integrated Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - J Zhang
- Center for Translational Medicine, Guangxi Medical University, Nanning, Guangxi, China, University of Pittsburgh Cancer Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - J B Nelson
- Department of Urology, University of Pittsburgh Cancer Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.,Department of Molecular Pharmacology and Chemical Biology, University of Pittsburgh Cancer Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - S Xia
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Z Wang
- Department of Urology, University of Pittsburgh Cancer Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.,Department of Molecular Pharmacology and Chemical Biology, University of Pittsburgh Cancer Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.,Department of Pathology, University of Pittsburgh Cancer Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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42
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Chang K, Xia S, Sun YG, Xin JF, Shen WB. [Liposuction combined with lymphatico-venous anastomosis for treatment of secondary lymphedema of the lower limbs: a report of 49 cases]. Zhonghua Wai Ke Za Zhi 2017; 55:274-278. [PMID: 28355765 DOI: 10.3760/cma.j.issn.0529-5815.2017.04.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To study the clinical effects of liposuction combined with lymphatico-venous anastomosis for treatment of secondary lymphedema of the lower limbs. Methods: A retrospective analysis was performed for 49 patients who had undergone liposuction combined with lymphatico-venous anastomosis to treat secondary lymphedema of the lower limbs at Department of Lymph Surgery, Beijing Shijitan Hospital from November 2013 to February 2015.All patients were female aging from 31 to 70 years with median age of (52±10)years.All patients had history of pelvic surgery.There were 32 cases with cervical carcinoma, 11 cases with endometrial cancer, 1 case with ovarian cancer who accepted radical hysterectomy, 2 cases with benign tumor who accepted resection, 2 cases accepted inguinal lymph node dissection, 1 case with rectal cancer accepted radical resection.There were 30 cases with history of radiation therapy and 23 cases with history of erysipelas recurrent((2.1±3.9)/year). The limb swelling degree in preoperative and postoperative patients was explored using one-way analysis of variance with replicate measures and paired sample t-test. Meanwhile the incidence of lymphogenous infection was used as an evaluation of operation efficacy. Results: The mean lower limb circumference difference at 7 days, 6 months and 12 months was (0.17±1.36)cm, (1.25±1.62)cm and(1.58±1.56)cm, respectively, which was significantly decreased compared with preoperative((4.92±2.16)cm) (t=-5.712, -5.777, -5.765; all P<0.01). The mean lower limb volume difference at 7 days, 6 months and 12 months was (522±799)ml, (726±973)ml and (889±895)ml, respectively, which was significantly decreased compared with preoperative((2 729±1 335) ml)(t=-5.905, -6.093, -5.777; all P<0.01). The incidence of erysipelas was 0.0(0.0, 0.0)/6 months within 6 months after operation and 0.0(0.0, 0.0)/6 months within 6-12 months after operation, which was significantly lower than that before operation(0.0(0.0, 2.0)/year). The feeling of tightness and heaviness of the limb was significantly improved compared with preoperative. Conclusion: Liposuction combined with lymphatico-venous anastomosis is an effective method for the treatment of secondary lymphedema of the lower limbs.
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Affiliation(s)
- K Chang
- Department of Lymph Surgery, Beijing Shijitan Hospital, Beijing 100038, China
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43
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Zhou L, Qi S, Yan C, Jin HM, Xu J, Ma L, Guan J, Xia S. [Myeloid-derived suppressor cells in peripheral blood of multiple myeloma]. Zhonghua Xue Ye Xue Za Zhi 2017; 38:545-547. [PMID: 28655102 PMCID: PMC7342972 DOI: 10.3760/cma.j.issn.0253-2727.2017.06.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
| | | | | | | | | | | | | | - S Xia
- Department of Immunology, Institute of Clinic Laboratory Diagnosis, School of Medicine, Jiangsu University, Zhengjiang 212013, China
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44
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Qiang Y, Xu J, Yan C, Jin H, Xiao T, Yan N, Zhou L, An H, Zhou X, Shao Q, Xia S. Butyrate and retinoic acid imprint mucosal-like dendritic cell development synergistically from bone marrow cells. Clin Exp Immunol 2017; 189:290-297. [PMID: 28542882 DOI: 10.1111/cei.12990] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/16/2017] [Indexed: 12/27/2022] Open
Abstract
Accumulating data show that the phenotypes and functions of distinctive mucosal dendritic cells (DCs) in the gut are regulated by retinoic acid (RA). Unfortunately, the exact role of butyrate in RA-mediated mucosal DC differentiation has not been elucidated thoroughly to date. Mucosal-like dendritic cell differentiation was completed in vitro by culturing bone marrow cells with growth factors [granulocyte-macrophage colony-stimulating factor (GM-CSF/interleukin (IL)-4], RA and/or butyrate. The phenotypes, cytokine secretion, immune functions and levels of retinal dehydrogenase of different DCs were detected using quantitative polymerase chain reaction (qPCR), enzyme-linked immunosorbent assay (ELISA) and flow cytometry, respectively. The results showed that RA-induced DCs (RA-DCs) showed mucosal DC properties, including expression of CD103 and gut homing receptor α4 β7 , low proinflammatory cytokine secretion and low priming capability to antigen-specific CD4+ T cells. Butyrate-treated RA-DCs (Bu-RA-DCs) decreased CD11c, but increased CD103 and α4 β7 expression. Moreover, the CD4+ T priming capability and the levels of retinal dehydrogenase of RA-DCs were suppressed significantly by butyrate. Thus, butyrate and retinoic acid have different but synergistic regulatory functions on mucosal DC differentiation, indicating that immune homeostasis in the gut depends largely upon RA and butyrate to imprint different mucosal DC subsets, both individually and collectively.
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Affiliation(s)
- Y Qiang
- Department of Immunology, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China.,Institute of Clinic Laboratory Diagnosis, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China.,Department of Clinical Laboratory, the Second People's Hospital of Changzhou Affiliated to Nanjing Medical University, Changzhou, Jiangsu, China
| | - J Xu
- Department of Immunology, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China.,Institute of Clinic Laboratory Diagnosis, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China
| | - C Yan
- Department of Immunology, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China.,Institute of Clinic Laboratory Diagnosis, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China
| | - H Jin
- Department of Immunology, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China.,Institute of Clinic Laboratory Diagnosis, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China
| | - T Xiao
- Department of Immunology, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China.,Institute of Clinic Laboratory Diagnosis, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China
| | - N Yan
- Department of Immunology, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China.,Institute of Clinic Laboratory Diagnosis, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China
| | - L Zhou
- Institute of Clinic Laboratory Diagnosis, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China
| | - H An
- Cancer Institute, Institute of Translational Medicine, Second Military Medical University, Shanghai, China
| | - X Zhou
- Department of Pathology, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China
| | - Q Shao
- Department of Immunology, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China.,Institute of Clinic Laboratory Diagnosis, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China
| | - S Xia
- Department of Immunology, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China.,Institute of Clinic Laboratory Diagnosis, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China
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Wu T, Tang DR, Wang F, Xia S, Sun FY. [The value of DCE-MRI in assessing the course of thyroid associated ophthalmopathy]. Zhonghua Yan Ke Za Zhi 2017; 53:430-435. [PMID: 28606264 DOI: 10.3760/cma.j.issn.0412-4081.2017.06.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To explore the feasibility of the semi-quantitative rectus extraocular muscle (EOM) parameters of dynamic contrast-enhanced magetic resonance imaging (DCE-MRI) in assessing the clinical course of thyroid associated ophthalmopathy (TAO). Methods: It was a retrospective case series study. A total of 136 cases of TAO were recruited from March 2011 to October 2012 in the Tianjin the first center hospital including 63 males and 72 females, aged 24.0-65.0 years, with an average age of (40.5±10.9) years. Forty healthy volunteers were recruited as control group (CG). According to clinical activity score (CAS), all TAO patients were divided into 2 groups, activity group (AG) and inactivity group (IAG). MRI and DCE-MRI orbit scan were performed in each subject. Drew time-intensity curves (TIC) by Siemens 3.0 MR (syngo) post-processing workstation. The semi-quantitative parameters of DCE-MRI were calculated. The semi-quantitative paramters based on TIC include early enhancement coefficient (EEC), maximum enhancement coefficient (Emax) and wash-out coefficient (WC(5min)). Kruskal-Wallis H rank test was used for comparing signal intensity among 3 groups, and Nemenyi test for pairwise comparison between groups. The DCE-MRI parameters (EEC, Emax, WC(5 min)) among groups were compared by one-way ANOVA, and Bonferroni t test is for pairwise comparison between groups. The diagnostic value of mean EEC, mean Emax, WC(5min) for assessment of the clinical course in TAO was analyzed by ROC curve. Results: There were significant difference in signal intensity (SI) of rectus EOM on T(2)WI among CG, AG and IAG, which is significantly different in 88 cases of AG including 45 cases of high intensity 51.1%, 23 cases of moderate intensity 26.1%, and 20 cases of low intensity 22.7%,compared with CG and IAG. EEC (P<0.05), Emax and WC5min values of rectus EOM of TAO group were significantly lower than those of CG(P<0.05), which values of rectus EOM of TAO active group of EEC are 0.63±0.06、0.61±0.05、0.56±0.09、0.57±0.09, and values of rectus EOM of TAO inactive group of EEC are 0.49±0.05、0.50±0.08、0.57±0.10、0.55±0.09. The values of rectus EOM of TAO active group of Emax are 1.35±0.09、1.28±0.09、1.21±0.17、1.25±0.10, and the values of rectus EOM of TAO inactive group of Emax are 1.04±0.06、1.05±0.10、1.20±0.19、1.16±0.11. The values of rectus EOM of TAO active group of WC(5 min) are 0.13±0.03、0.13±0.03、0.13±0.06、0.13±0.03 and the values of rectus EOM of TAO inactive group of WC5min are 0.08±0.02、0.79±0.03、0.11±0.06、0.09± 0.03. EEC (χ(2)=9.20, P<0.05), Emax and WC(5min) values of rectus EOM of TAO group were significantly lower than those of CG (P<0.05). EEC, Emax and WC(5min) values of medial rectus and inferior rectus EOM of IAG were significantly lower than those of AG(P<0.05). WC(5min) values of superior rectus EOM of IAG were significantly lower than those of AG (P<0.05). There were no differences in EEC and Emax values of lateral rectus and superior rectus EOM between IAG and AG (P>0.05). There were no differences in WC(5min) values of lateral rectus EOM between IAG and AG (P>0.05). The area under the curve (AUC) were 0.771, 0.879, 0.898 for mean EEC, mean Emax, and mean WC(5min), respectively. Conclusion: The semi-quantitative paramters of DCE-MRI can show the clinical activity of TAO patients and can be considered as the quantitative index of TAO activity staging. (Chin J Ophthalmol, 2017, 53: 430-435).
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Affiliation(s)
- T Wu
- Department of Ophthalmology, Tianjin First Center Hospital, Tianjin 300192, China
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Zhang M, Zhao X, Fang Z, Niu Y, Lou J, Wu Y, Zou S, Xia S, Sun M, Du F. Fabrication of HA/PEI-functionalized carbon dots for tumor targeting, intracellular imaging and gene delivery. RSC Adv 2017. [DOI: 10.1039/c6ra26048a] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Carbon quantum dots (CDs) as emerging carbon nano-materials have attracted tremendous attention in biomedical fields due to unique properties.
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Affiliation(s)
- M. Zhang
- School of Medicine
- Jiangsu University
- Zhenjiang
- P. R. China
| | - X. Zhao
- School of Medicine
- Jiangsu University
- Zhenjiang
- P. R. China
| | - Z. Fang
- School of Medicine
- Jiangsu University
- Zhenjiang
- P. R. China
| | - Y. Niu
- School of Medicine
- Jiangsu University
- Zhenjiang
- P. R. China
| | - J. Lou
- School of Medicine
- Jiangsu University
- Zhenjiang
- P. R. China
| | - Y. Wu
- School of Medicine
- Jiangsu University
- Zhenjiang
- P. R. China
| | - S. Zou
- Department of Hepatosis
- The Third Hospital of Zhenjiang Affiliated to Jiangsu University
- Zhenjiang
- P. R. China
| | - S. Xia
- School of Medicine
- Jiangsu University
- Zhenjiang
- P. R. China
| | - M. Sun
- Department of Clinical Laboratory
- Affiliated Yancheng Hospital
- School of Medicine
- Southeast University
- Yancheng
| | - F. Du
- School of Medicine
- Jiangsu University
- Zhenjiang
- P. R. China
- Department of Hepatosis
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Stroes E, van der Valk F, Gaudet D, Gouni-Berthold I, Riksen N, Steinhagen-Thiessen E, Isermann B, Nordestgaard B, Viney N, Marcovina S, Hughes S, Tami J, Xia S, Witztum J, Tsimikas S. Prevalence of LPA single nucleotide polymorphisms and isoforms in patients enrolled in a phase 2 IONIS-APO(a) Rx clinical trial. Atherosclerosis 2016. [DOI: 10.1016/j.atherosclerosis.2016.07.646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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48
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Viney N, Marcovina S, Tami J, Xia S, Witztum J, Tsimikas S. Natural temporal variability in Lp(a) levels in patients enrolled in the placebo arms of IONIS-APO(a) Rx antisense oligonucleotide clinical trials. Atherosclerosis 2016. [DOI: 10.1016/j.atherosclerosis.2016.07.647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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49
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Elf S, Lin R, Xia S, Pan Y, Shan C, Wu S, Lonial S, Gaddh M, Arellano ML, Khoury HJ, Khuri FR, Lee BH, Boggon TJ, Fan J, Chen J. Targeting 6-phosphogluconate dehydrogenase in the oxidative PPP sensitizes leukemia cells to antimalarial agent dihydroartemisinin. Oncogene 2016; 36:254-262. [PMID: 27270429 PMCID: PMC5464402 DOI: 10.1038/onc.2016.196] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2015] [Revised: 04/19/2016] [Accepted: 04/24/2016] [Indexed: 12/13/2022]
Abstract
The oxidative pentose phosphate pathway (PPP) is crucial for cancer cell metabolism and tumor growth. We recently reported that targeting a key oxidative PPP enzyme, 6-phosphogluconate dehydrogenase (6PGD), using our novel small molecule 6PGD inhibitors Physcion and its derivative S3, shows anti-cancer effects. Notably, humans with genetic deficiency of either 6PGD or another oxidative PPP enzyme, glucose-6-phosphate dehydrogenase (G6PD), exhibit non-immune hemolytic anemia upon exposure to aspirin and various anti-malarial drugs. Inspired by these clinical observations, we examined the anti-cancer potential of combined treatment with 6PGD inhibitors and anti-malarial drugs. We found that stable knockdown of 6PGD sensitizes leukemia cells to anti-malarial agent dihydroartemisinin (DHA). Combined treatment with DHA and Physcion activates AMP-activated protein kinase, leading to synergistic inhibition of human leukemia cell viability. Moreover, our combined therapy synergistically attenuates tumor growth in xenograft nude mice injected with human K562 leukemia cells and cell viability of primary leukemia cells from human patients, but shows minimal toxicity to normal hematopoietic cells in mice as well as red blood cells and mononucleocytes from healthy human donors. Our findings reveal the potential for combined therapy using optimized doses of Physcion and DHA as a novel anti-leukemia treatment without inducing hemolysis.
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Affiliation(s)
- S Elf
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory, Emory University School of Medicine, Atlanta, GA, USA
| | - R Lin
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory, Emory University School of Medicine, Atlanta, GA, USA
| | - S Xia
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory, Emory University School of Medicine, Atlanta, GA, USA
| | - Y Pan
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory, Emory University School of Medicine, Atlanta, GA, USA
| | - C Shan
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory, Emory University School of Medicine, Atlanta, GA, USA
| | - S Wu
- Department of Chemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - S Lonial
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory, Emory University School of Medicine, Atlanta, GA, USA
| | - M Gaddh
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory, Emory University School of Medicine, Atlanta, GA, USA
| | - M L Arellano
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory, Emory University School of Medicine, Atlanta, GA, USA
| | - H J Khoury
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory, Emory University School of Medicine, Atlanta, GA, USA
| | - F R Khuri
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory, Emory University School of Medicine, Atlanta, GA, USA
| | - B H Lee
- Novartis Institutes for BioMedical Research, Cambridge, MA, USA
| | - T J Boggon
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, USA
| | - J Fan
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory, Emory University School of Medicine, Atlanta, GA, USA
| | - J Chen
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory, Emory University School of Medicine, Atlanta, GA, USA
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Feng Y, Liu L, Xia S, Xu JF, Bergquist R, Yang GJ. Reaching the Surveillance-Response Stage of Schistosomiasis Control in The People's Republic of China: A Modelling Approach. Adv Parasitol 2016; 92:165-96. [PMID: 27137447 DOI: 10.1016/bs.apar.2016.02.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
With the goal set to eliminate schistosomiasis nationwide by 2020, The People's Republic of China has initiated the surveillance-response stage to identify remaining sources of infection and potential pockets from where the disease could reemerge. Shifting the focus from classical monitoring and evaluation to rapid detection and immediate response, this approach requires modelling to bridge the surveillance and response components. We review here studies relevant to schistosomiasis modelling in a Chinese surveillance-response system with the expectation to achieve a practically useful understanding of the current situation and potential future study directions. We also present useful experience that could tentatively be applied in other endemic regions in the world. Modelling is discussed at length as it plays an essential role, both with regard to the intermediate snail host and in the definitive, mammal hosts. Research gaps with respect to snail infection, animal hosts and sectoral research cooperation are identified and examined against the prevailing background of ecosystem and socioeconomic changes with a focus on coexisting challenges and opportunities in a situation with increasing financial constraints.
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Affiliation(s)
- Y Feng
- Key Laboratory of National Health and Family Planning Commission on Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Wuxi, The People's Republic of China; Jiangsu Institute of Parasitic Diseases, Wuxi, Jiangsu Province, The People's Republic of China; Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, The People's Republic of China; Public Health Research Center, Jiangnan University, Wuxi, Jiangsu Province, The People's Republic of China
| | - L Liu
- Key Laboratory of National Health and Family Planning Commission on Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Wuxi, The People's Republic of China; Jiangsu Institute of Parasitic Diseases, Wuxi, Jiangsu Province, The People's Republic of China; Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, The People's Republic of China; Public Health Research Center, Jiangnan University, Wuxi, Jiangsu Province, The People's Republic of China
| | - S Xia
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, The People's Republic of China; Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, The People's Republic of China; WHO Collaborating Center for Tropical Diseases, Shanghai, The People's Republic of China
| | - J-F Xu
- Hubei University for Nationalities, The People's Republic of China
| | - R Bergquist
- Geospatial Health, University of Naples Federico II, Naples, Italy
| | - G-J Yang
- Key Laboratory of National Health and Family Planning Commission on Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Wuxi, The People's Republic of China; Jiangsu Institute of Parasitic Diseases, Wuxi, Jiangsu Province, The People's Republic of China; Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, The People's Republic of China; Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
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