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Jiang Z, Yang T, Xu L. Head-to-head comparison of prostate-specific membrane antigen positron emission tomography/computed tomography and multiparametric magnetic resonance imaging in the detection of biochemical recurrence of prostate cancer: a systematic review and meta-analysis. Clin Radiol 2024; 79:436-445. [PMID: 38582633 DOI: 10.1016/j.crad.2024.02.008] [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: 09/14/2023] [Revised: 01/30/2024] [Accepted: 02/05/2024] [Indexed: 04/08/2024]
Abstract
AIM Our main goal of this meta-analytical analysis was to evaluate the diagnostic effectiveness of prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/computed tomography (CT) against multiparametric magnetic resonance imaging (mpMRI) in the context of identifying biochemical recurrence in patients with prostate cancer (PCa). MATERIALS AND METHODS A thorough search covering articles published until March 2023 was carried out across major databases such as PubMed, Embase, and Web of Science. Studies examining the direct comparison of PSMA PET/CT and mpMRI in patients with PCa suffering biochemical recurrence were included in the inclusion criteria. Using the renowned Quality Assessment of Diagnostic Performance Studies-2 technique, each study's methodological rigor was assessed. RESULTS We analyzed data from six eligible studies involving 290 patients in total. The combined data showed that for PSMA PET/CT and mpMRI, respectively, the pooled overall detection rates for recurrent PCa after definitive treatment were 0.69 (95% confidence interval [CI]: 0.45-0.89) and 0.70 (95% CI: 0.44-0.91). The detection rates for local recurrence were specifically 0.52 (95% CI: 0.39-0.65) and 0.62 (95% CI: 0.31-0.89), while they were 0.50 (95% CI: 0.26-0.74) and 0.32 (95% CI: 0.18-0.48) for lymph node metastasis. Notably, there was no discernible difference between the two imaging modalities in terms of the overall detection rate (P = 0.95). The detection rates for local recurrence and lymph node metastasis did not differ statistically significantly (P = 0.55, 0.23). CONCLUSION The performance of PSMA PET/CT and mpMRI in identifying biochemical recurrence in PCa appears to be comparable. However, the meta-analysis' findings came from research with modest sample sizes. In this context, more extensive research should be conducted in the future.
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Affiliation(s)
- Z Jiang
- Medical School, Hunan University of Chinese Medicine, Changsha, Hunan, 410208, China.
| | - T Yang
- Medical School, Hunan University of Chinese Medicine, Changsha, Hunan, 410208, China
| | - L Xu
- Medical School, Hunan University of Chinese Medicine, Changsha, Hunan, 410208, China
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2
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Wang Z, Jiang N, Jiang Z, Deng Q, Zhou Q, Hu B. Beyond silence: evolving ultrasound strategies in the battle against cardiovascular thrombotic challenges. J Thromb Thrombolysis 2024:10.1007/s11239-024-02989-w. [PMID: 38689069 DOI: 10.1007/s11239-024-02989-w] [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] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/18/2024] [Indexed: 05/02/2024]
Abstract
Cardiovascular thrombotic events have long been a perplexing factor in clinical settings, influencing patient prognoses significantly. Ultrasound-mediated acoustic therapy, an innovative thrombolytic treatment method known for its high efficiency, non-invasiveness, safety, and convenience, has demonstrated promising potential for clinical applications and has gradually become a focal point in cardiovascular thrombotic disease research. The current challenge lies in the technical complexities of preparing ultrasound-responsive carriers with thrombus-targeting capabilities and high thrombolytic efficiency. Additionally, optimizing the corresponding acoustic treatment mode is crucial to markedly enhance the thrombolytic effectiveness of ultrasound-mediated acoustic therapy. In light of the current status, this article provides a comprehensive review of the research progress in innovative ultrasound-mediated acoustic therapy for cardiovascular thrombotic diseases. It explores the impact of technical methods, therapeutic mechanisms, and influencing factors on the thrombolytic efficiency and clinical potential of ultrasound-mediated acoustic therapy. The review places particular emphasis on identifying solutions and key considerations in addressing the challenges associated with this cutting-edge therapeutic approach.
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Affiliation(s)
- Zhiwen Wang
- Echo Lab, Department of Ultrasound Imaging, Renmin Hospital of Wuhan University, 238# Jiefang Road, Wuhan, 430060, Hubei, People's Republic of China
| | - Nan Jiang
- Echo Lab, Department of Ultrasound Imaging, Renmin Hospital of Wuhan University, 238# Jiefang Road, Wuhan, 430060, Hubei, People's Republic of China
| | - Zhixin Jiang
- Echo Lab, Department of Ultrasound Imaging, Renmin Hospital of Wuhan University, 238# Jiefang Road, Wuhan, 430060, Hubei, People's Republic of China
| | - Qing Deng
- Echo Lab, Department of Ultrasound Imaging, Renmin Hospital of Wuhan University, 238# Jiefang Road, Wuhan, 430060, Hubei, People's Republic of China
| | - Qing Zhou
- Echo Lab, Department of Ultrasound Imaging, Renmin Hospital of Wuhan University, 238# Jiefang Road, Wuhan, 430060, Hubei, People's Republic of China.
| | - Bo Hu
- Echo Lab, Department of Ultrasound Imaging, Renmin Hospital of Wuhan University, 238# Jiefang Road, Wuhan, 430060, Hubei, People's Republic of China.
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Chen S, Chung LH, Chen S, Jiang Z, Li N, Hu J, Liao WM, He J. Efficient Lead Removal by Assembly of Bio-Derived Ellagate Framework, Which Enables Electrocatalytic Reduction of CO 2 to Formate. Small 2024:e2400978. [PMID: 38593307 DOI: 10.1002/smll.202400978] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 03/19/2024] [Indexed: 04/11/2024]
Abstract
Lead (Pb) poisoning and CO2-induced global warming represent two exemplary environmental and energy issues threatening humanity. Various biomass-derived materials are reported to take up Pb and convert CO2 electrochemically into low-valent carbon species, but these works address the problems separately rather than settle the issues simultaneously. In this work, cheap, natural ellagic acid (EA) extracted from common plants is adopted to assemble a stable metal-organic framework (MOF), EA-Pb, by effective capture of Pb2+ ions in an aqueous medium (removal rate close to 99%). EA-Pb represents the first structurally well-defined Pb-based MOF showing selective electrocatalytic CO2-to-HCOO- conversion with Faradaic efficiency (FE) of 95.37% at -1.08 V versus RHE. The catalytic mechanism is studied by 13CO2 labeling, in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and theoretical calculation. The use of EA-Pb as an electrocatalyst for CO2 reduction represents a 2-in-1 solution of converting detrimental wastes (Pb2+) as well as natural resources (EA) into wealth (electrocatalytic EA-Pb) for addressing the global warming issue.
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Affiliation(s)
- Song Chen
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, Guangdong, 510006, P. R. China
| | - Lai-Hon Chung
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, Guangdong, 510006, P. R. China
| | - Shaoru Chen
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, Guangdong, 510006, P. R. China
| | - Zhixin Jiang
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, Guangdong, 510006, P. R. China
| | - Ning Li
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, Guangdong, 510006, P. R. China
| | - Jieying Hu
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, Guangdong, 510006, P. R. China
| | - Wei-Ming Liao
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, Guangdong, 510006, P. R. China
| | - Jun He
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, Guangdong, 510006, P. R. China
- Guangdong Provincial Laboratory of Chemistry and Fine Chemical Engineering Jieyang Center, Jieyang, 515200, P. R. China
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4
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Rosenberg E, Andersen TI, Samajdar R, Petukhov A, Hoke JC, Abanin D, Bengtsson A, Drozdov IK, Erickson C, Klimov PV, Mi X, Morvan A, Neeley M, Neill C, Acharya R, Allen R, Anderson K, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Bilmes A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Campero J, Chang HS, Chen Z, Chiaro B, Chik D, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Debroy DM, Barba ADT, Demura S, Di Paolo A, Dunsworth A, Earle C, Faoro L, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Garcia G, Genois É, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Dau AG, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hill G, Hoffmann MR, Hong S, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lensky YD, Lester BJ, Lill AT, Liu W, Locharla A, Mandrà S, Martin O, Martin S, McClean JR, McEwen M, Meeks S, Miao KC, Mieszala A, Montazeri S, Movassagh R, Mruczkiewicz W, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O'Brien TE, Omonije S, Opremcak A, Potter R, Pryadko LP, Quintana C, Rhodes DM, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Sivak V, Skruzny J, Smith WC, Somma RD, Sterling G, Strain D, Szalay M, Thor D, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Babbush R, Bacon D, Boixo S, Hilton J, Lucero E, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Khemani V, Gopalakrishnan S, Prosen T, Roushan P. Dynamics of magnetization at infinite temperature in a Heisenberg spin chain. Science 2024; 384:48-53. [PMID: 38574139 DOI: 10.1126/science.adi7877] [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] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 03/01/2024] [Indexed: 04/06/2024]
Abstract
Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the one-dimensional Heisenberg model were conjectured as to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we studied the probability distribution of the magnetization transferred across the chain's center, [Formula: see text]. The first two moments of [Formula: see text] show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments ruled out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide insights into universal behavior in quantum systems.
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Affiliation(s)
- E Rosenberg
- Google Research, Mountain View, CA, USA
- Department of Physics, Cornell University, Ithaca, NY, USA
| | | | - R Samajdar
- Department of Physics, Princeton University, Princeton, NJ, USA
- Princeton Center for Theoretical Science, Princeton University, Princeton, NJ, USA
| | | | - J C Hoke
- Department of Physics, Stanford University, Stanford, CA, USA
| | - D Abanin
- Google Research, Mountain View, CA, USA
| | | | - I K Drozdov
- Google Research, Mountain View, CA, USA
- Department of Physics, University of Connecticut, Storrs, CT, USA
| | | | | | - X Mi
- Google Research, Mountain View, CA, USA
| | - A Morvan
- Google Research, Mountain View, CA, USA
| | - M Neeley
- Google Research, Mountain View, CA, USA
| | - C Neill
- Google Research, Mountain View, CA, USA
| | - R Acharya
- Google Research, Mountain View, CA, USA
| | - R Allen
- Google Research, Mountain View, CA, USA
| | | | - M Ansmann
- Google Research, Mountain View, CA, USA
| | - F Arute
- Google Research, Mountain View, CA, USA
| | - K Arya
- Google Research, Mountain View, CA, USA
| | - A Asfaw
- Google Research, Mountain View, CA, USA
| | - J Atalaya
- Google Research, Mountain View, CA, USA
| | - J C Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | - A Bilmes
- Google Research, Mountain View, CA, USA
| | - G Bortoli
- Google Research, Mountain View, CA, USA
| | | | - J Bovaird
- Google Research, Mountain View, CA, USA
| | - L Brill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Buell
- Google Research, Mountain View, CA, USA
| | - T Burger
- Google Research, Mountain View, CA, USA
| | - B Burkett
- Google Research, Mountain View, CA, USA
| | | | - J Campero
- Google Research, Mountain View, CA, USA
| | - H-S Chang
- Google Research, Mountain View, CA, USA
| | - Z Chen
- Google Research, Mountain View, CA, USA
| | - B Chiaro
- Google Research, Mountain View, CA, USA
| | - D Chik
- Google Research, Mountain View, CA, USA
| | - J Cogan
- Google Research, Mountain View, CA, USA
| | - R Collins
- Google Research, Mountain View, CA, USA
| | - P Conner
- Google Research, Mountain View, CA, USA
| | | | - A L Crook
- Google Research, Mountain View, CA, USA
| | - B Curtin
- Google Research, Mountain View, CA, USA
| | | | | | - S Demura
- Google Research, Mountain View, CA, USA
| | | | | | - C Earle
- Google Research, Mountain View, CA, USA
| | - L Faoro
- Google Research, Mountain View, CA, USA
| | - E Farhi
- Google Research, Mountain View, CA, USA
| | - R Fatemi
- Google Research, Mountain View, CA, USA
| | | | | | - E Forati
- Google Research, Mountain View, CA, USA
| | | | - B Foxen
- Google Research, Mountain View, CA, USA
| | - G Garcia
- Google Research, Mountain View, CA, USA
| | - É Genois
- Google Research, Mountain View, CA, USA
| | - W Giang
- Google Research, Mountain View, CA, USA
| | - C Gidney
- Google Research, Mountain View, CA, USA
| | - D Gilboa
- Google Research, Mountain View, CA, USA
| | | | - R Gosula
- Google Research, Mountain View, CA, USA
| | | | - J A Gross
- Google Research, Mountain View, CA, USA
| | | | - M C Hamilton
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
| | - M Hansen
- Google Research, Mountain View, CA, USA
| | | | | | - P Heu
- Google Research, Mountain View, CA, USA
| | - G Hill
- Google Research, Mountain View, CA, USA
| | | | - S Hong
- Google Research, Mountain View, CA, USA
| | - T Huang
- Google Research, Mountain View, CA, USA
| | - A Huff
- Google Research, Mountain View, CA, USA
| | | | - L B Ioffe
- Google Research, Mountain View, CA, USA
| | | | - J Iveland
- Google Research, Mountain View, CA, USA
| | - E Jeffrey
- Google Research, Mountain View, CA, USA
| | - Z Jiang
- Google Research, Mountain View, CA, USA
| | - C Jones
- Google Research, Mountain View, CA, USA
| | - P Juhas
- Google Research, Mountain View, CA, USA
| | - D Kafri
- Google Research, Mountain View, CA, USA
| | - T Khattar
- Google Research, Mountain View, CA, USA
| | - M Khezri
- Google Research, Mountain View, CA, USA
| | - M Kieferová
- Google Research, Mountain View, CA, USA
- QSI, Faculty of Engineering & Information Technology, University of Technology Sydney, Ultimo, NSW, Australia
| | - S Kim
- Google Research, Mountain View, CA, USA
| | - A Kitaev
- Google Research, Mountain View, CA, USA
| | - A R Klots
- Google Research, Mountain View, CA, USA
| | - A N Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P Laptev
- Google Research, Mountain View, CA, USA
| | - K-M Lau
- Google Research, Mountain View, CA, USA
| | - L Laws
- Google Research, Mountain View, CA, USA
| | - J Lee
- Google Research, Mountain View, CA, USA
- Department of Chemistry, Columbia University, New York, NY, USA
| | - K W Lee
- Google Research, Mountain View, CA, USA
| | | | | | - A T Lill
- Google Research, Mountain View, CA, USA
| | - W Liu
- Google Research, Mountain View, CA, USA
| | | | - S Mandrà
- Google Research, Mountain View, CA, USA
| | - O Martin
- Google Research, Mountain View, CA, USA
| | - S Martin
- Google Research, Mountain View, CA, USA
| | | | - M McEwen
- Google Research, Mountain View, CA, USA
| | - S Meeks
- Google Research, Mountain View, CA, USA
| | - K C Miao
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - M Newman
- Google Research, Mountain View, CA, USA
| | - J H Ng
- Google Research, Mountain View, CA, USA
| | - A Nguyen
- Google Research, Mountain View, CA, USA
| | - M Nguyen
- Google Research, Mountain View, CA, USA
| | - M Y Niu
- Google Research, Mountain View, CA, USA
| | | | - S Omonije
- Google Research, Mountain View, CA, USA
| | | | - R Potter
- Google Research, Mountain View, CA, USA
| | - L P Pryadko
- Department of Physics and Astronomy, University of California, Riverside, CA, USA
| | | | | | - C Rocque
- Google Research, Mountain View, CA, USA
| | - N C Rubin
- Google Research, Mountain View, CA, USA
| | - N Saei
- Google Research, Mountain View, CA, USA
| | - D Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - A Shorter
- Google Research, Mountain View, CA, USA
| | - N Shutty
- Google Research, Mountain View, CA, USA
| | - V Shvarts
- Google Research, Mountain View, CA, USA
| | - V Sivak
- Google Research, Mountain View, CA, USA
| | - J Skruzny
- Google Research, Mountain View, CA, USA
| | | | - R D Somma
- Google Research, Mountain View, CA, USA
| | | | - D Strain
- Google Research, Mountain View, CA, USA
| | - M Szalay
- Google Research, Mountain View, CA, USA
| | - D Thor
- Google Research, Mountain View, CA, USA
| | - A Torres
- Google Research, Mountain View, CA, USA
| | - G Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T White
- Google Research, Mountain View, CA, USA
| | - B W K Woo
- Google Research, Mountain View, CA, USA
| | - C Xing
- Google Research, Mountain View, CA, USA
| | | | - P Yeh
- Google Research, Mountain View, CA, USA
| | - J Yoo
- Google Research, Mountain View, CA, USA
| | - G Young
- Google Research, Mountain View, CA, USA
| | - A Zalcman
- Google Research, Mountain View, CA, USA
| | - Y Zhang
- Google Research, Mountain View, CA, USA
| | - N Zhu
- Google Research, Mountain View, CA, USA
| | - N Zobrist
- Google Research, Mountain View, CA, USA
| | - H Neven
- Google Research, Mountain View, CA, USA
| | - R Babbush
- Google Research, Mountain View, CA, USA
| | - D Bacon
- Google Research, Mountain View, CA, USA
| | - S Boixo
- Google Research, Mountain View, CA, USA
| | - J Hilton
- Google Research, Mountain View, CA, USA
| | - E Lucero
- Google Research, Mountain View, CA, USA
| | - A Megrant
- Google Research, Mountain View, CA, USA
| | - J Kelly
- Google Research, Mountain View, CA, USA
| | - Y Chen
- Google Research, Mountain View, CA, USA
| | | | - V Khemani
- Department of Physics, Stanford University, Stanford, CA, USA
| | | | - T Prosen
- Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia
| | - P Roushan
- Google Research, Mountain View, CA, USA
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5
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Fan C, Jiang Z, Teng C, Song X, Li L, Shen W, Jiang Q, Huang D, Lv Y, Du L, Wang G, Hu Y, Man S, Zhang Z, Gao N, Wang F, Shi T, Xin T. Efficacy and safety of intrathecal pemetrexed for TKI-failed leptomeningeal metastases from EGFR+ NSCLC: an expanded, single-arm, phase II clinical trial. ESMO Open 2024; 9:102384. [PMID: 38377785 DOI: 10.1016/j.esmoop.2024.102384] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 01/06/2024] [Accepted: 01/19/2024] [Indexed: 02/22/2024] Open
Abstract
BACKGROUND This study aimed to evaluate the efficacy and safety of intrathecal pemetrexed (IP) for treating patients with leptomeningeal metastases (LM) from non-small-cell lung cancer (NSCLC) who progressed from epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI) treatment in an expanded, prospective, single-arm, phase II clinical study (ChiCTR1800016615). PATIENTS AND METHODS Patients with confirmed NSCLC-LM who progressed from TKI received IP (50 mg, day 1/day 5 for 1 week, then every 3 weeks for four cycles, and then once monthly) until disease progression or intolerance. Objectives were to assess overall survival (OS), response rate, and safety. Measurable lesions were assessed by investigator according to RECIST version 1.1. LM were assessed according to the Response Assessment in Neuro-Oncology (RANO) criteria. RESULTS The study included 132 patients; 68% were female and median age was 52 years (31-74 years). The median OS was 12 months (95% confidence interval 10.4-13.6 months), RANO-assessed response rate was 80.3% (106/132), and the most common adverse event was myelosuppression (n = 42; 31.8%), which reversed after symptomatic treatment. The results of subgroup analysis showed that absence of brain parenchymal metastasis, good Eastern Cooperative Oncology Group score, good response to IP treatment, negative cytology after treatment, and patients without neck/back pain/difficult defecation had longer survival. Gender, age, previous intrathecal methotrexate/cytarabine, and whole-brain radiotherapy had no significant influence on OS. CONCLUSIONS This study further showed that IP is an effective and safe treatment method for the EGFR-TKI-failed NSCLC-LM, and should be recommended for these patients in clinical practice and guidelines.
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Affiliation(s)
- C Fan
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - Z Jiang
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - C Teng
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - X Song
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - L Li
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - W Shen
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - Q Jiang
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - D Huang
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - Y Lv
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - L Du
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - G Wang
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - Y Hu
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - S Man
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - Z Zhang
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin
| | - N Gao
- Department of Oncology, Heilongjiang Sengong General Hospital, Harbin, People's Republic of China
| | - F Wang
- Department of Oncology, Heilongjiang Sengong General Hospital, Harbin, People's Republic of China
| | - T Shi
- Department of Oncology, Heilongjiang Sengong General Hospital, Harbin, People's Republic of China
| | - T Xin
- Department of Oncology, Second Affiliated Hospital of Harbin Medical University, Harbin.
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6
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Mi X, Michailidis AA, Shabani S, Miao KC, Klimov PV, Lloyd J, Rosenberg E, Acharya R, Aleiner I, Andersen TI, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Bengtsson A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Chik D, Chou C, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Dau AG, Debroy DM, Del Toro Barba A, Demura S, Di Paolo A, Drozdov IK, Dunsworth A, Erickson C, Faoro L, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Genois É, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hoffmann MR, Hong S, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Kechedzhi K, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lensky YD, Lester BJ, Lill AT, Liu W, Locharla A, Malone FD, Martin O, McClean JR, McEwen M, Mieszala A, Montazeri S, Morvan A, Movassagh R, Mruczkiewicz W, Neeley M, Neill C, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O'Brien TE, Opremcak A, Petukhov A, Potter R, Pryadko LP, Quintana C, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Skruzny J, Smith WC, Somma R, Sterling G, Strain D, Szalay M, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Babbush R, Bacon D, Boixo S, Hilton J, Lucero E, Megrant A, Kelly J, Chen Y, Roushan P, Smelyanskiy V, Abanin DA. Stable quantum-correlated many-body states through engineered dissipation. Science 2024; 383:1332-1337. [PMID: 38513021 DOI: 10.1126/science.adh9932] [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] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 02/13/2024] [Indexed: 03/23/2024]
Abstract
Engineered dissipative reservoirs have the potential to steer many-body quantum systems toward correlated steady states useful for quantum simulation of high-temperature superconductivity or quantum magnetism. Using up to 49 superconducting qubits, we prepared low-energy states of the transverse-field Ising model through coupling to dissipative auxiliary qubits. In one dimension, we observed long-range quantum correlations and a ground-state fidelity of 0.86 for 18 qubits at the critical point. In two dimensions, we found mutual information that extends beyond nearest neighbors. Lastly, by coupling the system to auxiliaries emulating reservoirs with different chemical potentials, we explored transport in the quantum Heisenberg model. Our results establish engineered dissipation as a scalable alternative to unitary evolution for preparing entangled many-body states on noisy quantum processors.
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Affiliation(s)
- X Mi
- Google Research, Mountain View, CA, USA
| | - A A Michailidis
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - S Shabani
- Google Research, Mountain View, CA, USA
| | - K C Miao
- Google Research, Mountain View, CA, USA
| | | | - J Lloyd
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | | | - R Acharya
- Google Research, Mountain View, CA, USA
| | - I Aleiner
- Google Research, Mountain View, CA, USA
| | | | - M Ansmann
- Google Research, Mountain View, CA, USA
| | - F Arute
- Google Research, Mountain View, CA, USA
| | - K Arya
- Google Research, Mountain View, CA, USA
| | - A Asfaw
- Google Research, Mountain View, CA, USA
| | - J Atalaya
- Google Research, Mountain View, CA, USA
| | - J C Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | | | - G Bortoli
- Google Research, Mountain View, CA, USA
| | | | - J Bovaird
- Google Research, Mountain View, CA, USA
| | - L Brill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Buell
- Google Research, Mountain View, CA, USA
| | - T Burger
- Google Research, Mountain View, CA, USA
| | - B Burkett
- Google Research, Mountain View, CA, USA
| | | | - Z Chen
- Google Research, Mountain View, CA, USA
| | - B Chiaro
- Google Research, Mountain View, CA, USA
| | - D Chik
- Google Research, Mountain View, CA, USA
| | - C Chou
- Google Research, Mountain View, CA, USA
| | - J Cogan
- Google Research, Mountain View, CA, USA
| | - R Collins
- Google Research, Mountain View, CA, USA
| | - P Conner
- Google Research, Mountain View, CA, USA
| | | | - A L Crook
- Google Research, Mountain View, CA, USA
| | - B Curtin
- Google Research, Mountain View, CA, USA
| | - A G Dau
- Google Research, Mountain View, CA, USA
| | | | | | - S Demura
- Google Research, Mountain View, CA, USA
| | | | | | | | | | - L Faoro
- Google Research, Mountain View, CA, USA
| | - E Farhi
- Google Research, Mountain View, CA, USA
| | - R Fatemi
- Google Research, Mountain View, CA, USA
| | | | | | - E Forati
- Google Research, Mountain View, CA, USA
| | | | - B Foxen
- Google Research, Mountain View, CA, USA
| | - É Genois
- Google Research, Mountain View, CA, USA
| | - W Giang
- Google Research, Mountain View, CA, USA
| | - C Gidney
- Google Research, Mountain View, CA, USA
| | - D Gilboa
- Google Research, Mountain View, CA, USA
| | | | - R Gosula
- Google Research, Mountain View, CA, USA
| | - J A Gross
- Google Research, Mountain View, CA, USA
| | | | - M C Hamilton
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
| | - M Hansen
- Google Research, Mountain View, CA, USA
| | | | | | - P Heu
- Google Research, Mountain View, CA, USA
| | | | - S Hong
- Google Research, Mountain View, CA, USA
| | - T Huang
- Google Research, Mountain View, CA, USA
| | - A Huff
- Google Research, Mountain View, CA, USA
| | | | - L B Ioffe
- Google Research, Mountain View, CA, USA
| | | | - J Iveland
- Google Research, Mountain View, CA, USA
| | - E Jeffrey
- Google Research, Mountain View, CA, USA
| | - Z Jiang
- Google Research, Mountain View, CA, USA
| | - C Jones
- Google Research, Mountain View, CA, USA
| | - P Juhas
- Google Research, Mountain View, CA, USA
| | - D Kafri
- Google Research, Mountain View, CA, USA
| | | | - T Khattar
- Google Research, Mountain View, CA, USA
| | - M Khezri
- Google Research, Mountain View, CA, USA
| | - M Kieferová
- Google Research, Mountain View, CA, USA
- Centre for Quantum Software and Information (QSI), Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, Australia
| | - S Kim
- Google Research, Mountain View, CA, USA
| | - A Kitaev
- Google Research, Mountain View, CA, USA
| | - A R Klots
- Google Research, Mountain View, CA, USA
| | - A N Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P Laptev
- Google Research, Mountain View, CA, USA
| | - K-M Lau
- Google Research, Mountain View, CA, USA
| | - L Laws
- Google Research, Mountain View, CA, USA
| | - J Lee
- Google Research, Mountain View, CA, USA
- Department of Chemistry, Columbia University, New York, NY, USA
| | - K W Lee
- Google Research, Mountain View, CA, USA
| | | | | | - A T Lill
- Google Research, Mountain View, CA, USA
| | - W Liu
- Google Research, Mountain View, CA, USA
| | | | | | - O Martin
- Google Research, Mountain View, CA, USA
| | | | - M McEwen
- Google Research, Mountain View, CA, USA
| | | | | | - A Morvan
- Google Research, Mountain View, CA, USA
| | | | | | - M Neeley
- Google Research, Mountain View, CA, USA
| | - C Neill
- Google Research, Mountain View, CA, USA
| | | | - M Newman
- Google Research, Mountain View, CA, USA
| | - J H Ng
- Google Research, Mountain View, CA, USA
| | - A Nguyen
- Google Research, Mountain View, CA, USA
| | - M Nguyen
- Google Research, Mountain View, CA, USA
| | - M Y Niu
- Google Research, Mountain View, CA, USA
| | | | | | | | - R Potter
- Google Research, Mountain View, CA, USA
| | - L P Pryadko
- Google Research, Mountain View, CA, USA
- Department of Physics and Astronomy, University of California, Riverside, CA, USA
| | | | - C Rocque
- Google Research, Mountain View, CA, USA
| | - N C Rubin
- Google Research, Mountain View, CA, USA
| | - N Saei
- Google Research, Mountain View, CA, USA
| | - D Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - A Shorter
- Google Research, Mountain View, CA, USA
| | - N Shutty
- Google Research, Mountain View, CA, USA
| | - V Shvarts
- Google Research, Mountain View, CA, USA
| | - J Skruzny
- Google Research, Mountain View, CA, USA
| | - W C Smith
- Google Research, Mountain View, CA, USA
| | - R Somma
- Google Research, Mountain View, CA, USA
| | | | - D Strain
- Google Research, Mountain View, CA, USA
| | - M Szalay
- Google Research, Mountain View, CA, USA
| | - A Torres
- Google Research, Mountain View, CA, USA
| | - G Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T White
- Google Research, Mountain View, CA, USA
| | - B W K Woo
- Google Research, Mountain View, CA, USA
| | - C Xing
- Google Research, Mountain View, CA, USA
| | - Z J Yao
- Google Research, Mountain View, CA, USA
| | - P Yeh
- Google Research, Mountain View, CA, USA
| | - J Yoo
- Google Research, Mountain View, CA, USA
| | - G Young
- Google Research, Mountain View, CA, USA
| | - A Zalcman
- Google Research, Mountain View, CA, USA
| | - Y Zhang
- Google Research, Mountain View, CA, USA
| | - N Zhu
- Google Research, Mountain View, CA, USA
| | - N Zobrist
- Google Research, Mountain View, CA, USA
| | - H Neven
- Google Research, Mountain View, CA, USA
| | - R Babbush
- Google Research, Mountain View, CA, USA
| | - D Bacon
- Google Research, Mountain View, CA, USA
| | - S Boixo
- Google Research, Mountain View, CA, USA
| | - J Hilton
- Google Research, Mountain View, CA, USA
| | - E Lucero
- Google Research, Mountain View, CA, USA
| | - A Megrant
- Google Research, Mountain View, CA, USA
| | - J Kelly
- Google Research, Mountain View, CA, USA
| | - Y Chen
- Google Research, Mountain View, CA, USA
| | - P Roushan
- Google Research, Mountain View, CA, USA
| | | | - D A Abanin
- Google Research, Mountain View, CA, USA
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
- Department of Physics, Princeton University, Princeton, NJ, USA
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7
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Su H, Xu Z, Bao MDL, Luo S, Liang JW, Pei W, Guan X, Liu Z, Jiang Z, Zhang MG, Zhao ZX, Jin WS, Zhou HT. [The clinical significance of lateral pelvic sentinel lymph node biopsy using indocyanine green fluorescence navigation in laparoscopic lateral pelvic lymph node dissection]. Zhonghua Zhong Liu Za Zhi 2024; 46:140-145. [PMID: 38418188 DOI: 10.3760/cma.j.cn112152-20231026-00265] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/01/2024]
Abstract
Objectives: This study aims to explore the clinical significance of lateral pelvic sentinel lymph node biopsy (SLNB) using indocyanine green (ICG) fluorescence navigation in laparoscopic lateral pelvic lymph node dissection (LLND) and evaluate the accuracy and feasibility of this technique to predict the status of lateral pelvic lymph nodes (LPLNs). Methods: The clinical and pathological characteristics, surgical outcomes, lymph node findings and perioperative complications of 16 rectal cancer patients who underwent SLNB using ICG fluorescence navigation in laparoscopic LLND in the Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College during April 2017 and October 2022 were retrospectively collected and analyzed. The patients did not receive preoperative neoadjuvant radiotherapy and presented with LPLNs but without LPLN enlargement (MRI showed the maximum short axes of the LPLNs were ≥5 mm and <10 mm at first visit). Results: All 16 patients were successfully performed SLNB using ICG fluorescence navigation in laparoscopic LLND. Three patients underwent bilateral LLND and 13 patients underwent unilateral LLND. The lateral pelvic sentinel lymph nodes (SLNs) were clearly fluorescent before dissection in 14 patients and the detection rate of SLNs for these patients was 87.5%. Lateral pelvic SLN metastasis was diagnosed in 2 patients and negative results were found in 12 patients by frozen pathological examinations. Among the 14 patients in whom lateral pelvic SLNs were detected, the dissected lateral pelvic non-SLNs were all negative. All dissected LPLNs were negative in two patients without fluorescent lateral pelvic SLNs. The specificity, sensitivity, negative predictive value, and accuracy was 85.7%, 100%, 100%, and 100%, respectively. Conclusions: This study indicates that lateral pelvic SLNB using ICG fluorescence navigation shows promise as a safe and feasible procedure with good accuracy. This technique may replace preventive LLND for locally advanced lower rectal cancer.
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Affiliation(s)
- H Su
- Department of Gastrointestinal Surgery, Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Z Xu
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - M D L Bao
- Department of Pancreatic and Gastric Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - S Luo
- Department of Gastrointestinal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - J W Liang
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - W Pei
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - X Guan
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - Z Liu
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - Z Jiang
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - M G Zhang
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - Z X Zhao
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
| | - W S Jin
- Department of Anorectal Diseases, Third Medical Center of Chinese PLA General Hospital, Beijing 100039, China
| | - H T Zhou
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China
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Chen C, Xu J, Jiang Z, Wu GH, Zhang YQ, Zhao Y, Wu ZY. [Association between CD4 +T lymphocyte and body composition with physical frailty among elderly HIV-infected patients in Chongqing City]. Zhonghua Yu Fang Yi Xue Za Zhi 2024; 58:235-240. [PMID: 38387956 DOI: 10.3760/cma.j.cn112150-20230822-00115] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Abstract
Objective: To identify the association between CD4+T lymphocyte (CD4) counts and physical frailty among HIV-infected people aged 65 years and older, and evaluate whether this association will be modified by the indicators of body composition. Methods: From May to October 2022, 485 elderly HIV-infected patients receiving antiretroviral therapy (ART) were recruited from 7 antiviral treatment sites in Jiangjin District Center for Disease Control and Prevention, Chongqing. The data of basic characteristics (age and gender), living habits (smoking and drinking) and disease history (metabolic diseases, cardiovascular and cerebrovascular diseases, respiratory disease and malignant tumors) were collected through the face-to-face investigation with self-made questionnaires. Fried Frailty Scale was used to evaluate the status of physical frailty. Physical fitness (walking speed, grip strength, height, and weight) and body composition (skeletal muscle mass, body fat mass, and basal metabolic rate) were measured. The antiretroviral treatment data were obtained from the China AIDS Integrated Prevention and Treatment Data information management system. The prevalence of physical frailty was calculated among the HIV-infected patients. The potential effects of CD4 counts on physical frailty were explored by using multivariate logistic regression. Subgroup analyses were repeated in the logistic regression with muscle mass, body fat mass, and other indicators of body composition as subgroup variables to determine whether the association might be modified by body composition. Results: The age of 485 patients were (72±5) years old, of which 48.2% (234 cases) were>70 years old and 70.9% (344 cases) were male, and all of whom had initiated the ART treatment. The prevalence of physical frailty among these patients was 7.4% (36/485). Multivariate logistic regression showed that after adjusting for age, sex, smoking, drinking, body composition index, ART duration, viral load and the number of comorbidities, increased CD4 cell level was associated with decreased prevalent risk of physical frailty among elderly HIV-infected patients. For every increase of 5.0×107 CD4 cells/L, the prevalent risk of physical frailty decreased by 12% [OR (95%CI): 0.88 (0.76-1.01)]. Compared with the low CD4 cell level group, the risk of physical frailty in those with normal CD4 cell level decreased by 69% [OR (95%CI): 0.31 (0.10-0.92)]. Subgroup analysis of body composition indicators showed that the protective effect of normal CD4 cell level on physical frailty was more pronounced in the high skeletal muscle mass and high basal metabolic rate group (Pinteraction<0.05). Conclusion: The prevalence of physical frailty among elderly HIV-infected patients is relatively lower in Chongqing, and the CD4 cell level, skeletal muscle mass and basal metabolic rate are related to physical frailty.
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Affiliation(s)
- C Chen
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - J Xu
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Z Jiang
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - G H Wu
- Chongqing Center for Disease Control and Prevention, Chongqing 400042, China
| | - Y Q Zhang
- Department of AIDS/STD Control and Prevention, Chongqing Jiangjin District Center for Disease Control and Prevention, Chongqing 402260, China
| | - Y Zhao
- Department of Treatment and Care, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Z Y Wu
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
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Jiang Z, Shao F, Hu J, Zhuang Q, Cooray PLRK, Chen K, Wu Z, Chen T, Li C. Time-weighted blood pressure with cardiovascular risk among patients with or without diabetes. Clin Cardiol 2024; 47:e24213. [PMID: 38269631 PMCID: PMC10790318 DOI: 10.1002/clc.24213] [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] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 12/25/2023] [Accepted: 12/28/2023] [Indexed: 01/26/2024] Open
Abstract
BACKGROUND Usual measures of blood pressure (BP) do not account for both the magnitude and duration of exposure to elevated BP over time. We aimed to demonstrate the effect of a novel time-weighted BP on cardiovascular outcomes using a post hoc analysis of two published randomized trials. HYPOTHESIS Time-weighted blood pressure is associated with cardiovascular risk among patients with or without diabetes. METHODS The limited-access ACCORD and SPRINT data sets were used for the current study. Time-weighted BP is obtained by dividing cumulative BP by the total follow-up time. Time-weighted BP burden above a threshold is also determined after deriving the time-weighted BP by re-zeroing the interpolated pressure values at two different hypertension thresholds (>140/90 and >130/80 mmHg). RESULTS Eighteen thousand five hundred forty-one patients from the two clinical trials were enrolled in this study. A J-curve relation was observed between time-weighted BP and major cardiovascular events (MACE). The systolic blood pressure (SBP) burden independently predicted MACE across the two trials at different thresholds (ACCORD: SBP > 130 mmHg, HR = 1.05 [1.03-1.06]; SBP > 140 mmHg, HR = 1.06 [1.04-1.08]; SPRINT: SBP > 130 mmHg, HR = 1.04 [1.03-1.05]; SBP > 140 mmHg, HR = 1.05 [1.04-1.07]). Consistent results were found for diastolic blood pressure (DBP) burden (ACCORD: DBP > 80 mmHg, HR = 1.10 [1.06-1.15]; DBP > 90 mmHg, HR = 1.20 [1.11-1.30]. SPRINT DBP > 80 mmHg, HR = 1.06 [1.02-1.09]; DBP > 90 mmHg, HR = 1.12 [1.06-1.18]). Significant associations were also observed for stroke, myocardial infarction, cardiovascular death, and all-cause mortality. CONCLUSION Both time-weighted SBP and DBP independently influenced the risk of adverse cardiovascular events among patients with and without diabetes, regardless of the definition of hypertension (130/80 or <140/90 mmHg).
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Affiliation(s)
- Zhixin Jiang
- Department of CardiologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| | - Fang Shao
- Department of BiostatisticsNanjing Medical University School of Public HealthNanjingJiangsuChina
| | - Jingwen Hu
- Department of CardiologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| | - Qinyuan Zhuang
- Department of CardiologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| | | | - Kangyu Chen
- Department of CardiologyDivision of Life Sciences and Medicine, The First Affiliated Hospital of USTCUniversity of Science and Technology of ChinaHefeiChina
| | - Zhenqiang Wu
- Department of Geriatric MedicineThe University of AucklandAucklandNew Zealand
| | - Tao Chen
- Centre for Health EconomicsUniversity of YorkYorkUK
- Department of Clinical SciencesLiverpool School of Tropical MedicineLiverpoolUK
| | - Chao Li
- Department of Epidemiology and Health StatisticsSchool of Public Health, Xi'an Jiaotong University Health Science CentreXi'anChina
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Wu L, Ying J, Jiang Z, Zhang L, Cai Y, Zhou C, Xu Y, Lei S. Risk factors in ICU patients with initial acquisition of carbapenemase-resistant Klebsiella Pneumoniae. Int J Tuberc Lung Dis 2023; 27:899-905. [PMID: 38042974 DOI: 10.5588/ijtld.23.0043] [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] [Indexed: 12/04/2023] Open
Abstract
OBJECTIVE: To identify the risk factors associated with antimicrobial use on the initial acquisition of carbapenem-resistant Klebsiella pneumoniae (CRKP) in elderly intensive care unit (ICU) patients.METHODS: Respiratory secretion, blood, urine, anal swab and peritoneal drainage samples from all elderly patients with non-colonised CRKP who had been hospitalised from January 2021 to December 2022 were collected, and screened for CRKP colonisation using surveillance culture at the time of the first ICU admission and weekly thereafter in Zhejiang Provincial Hospital of Chinese Medicine, Zhejiang, China. Cumulative antibiotic variables included duration of antibiotic use, total amount of antimicrobials received in grams, total antibiotic consumption (defined daily dose) and the types of antimicrobial exposure. A time-dependent model based on Cox regression analysis was used to investigate the effect of each variable on the initial acquisition of CRKP infection or colonisation.RESULTS: Of 214 patients, 44 were infected or had CRKP colonies and death rate was 34.1%. males were the risk factor for acquiring CRKP in culture (HR 2.12, 95% CI 1.06-4.21; P = 0.033). It is notable that the hazard of acquiring CRKP increased by 9% with every single-point increase in the APACHE II score (HR 1.09, 95% CI 1.01-1.18; P = 0.025). The hazard of acquiring CRKP doubled when carbapenems were administered (HR 1.81, 95% CI 1.42-2.30; P < 0.001), In contrast, exposure to quinolone antimicrobials had a smaller effect on acquiring CRKP (HR 1.07; 95% CI 1.01-1.14; P = 0.024).CONCLUSION: This study found that male sex, APACHE II score and exposure to quinolones and carbapenems were independent risk factors for acquiring CRKP.
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Affiliation(s)
- L Wu
- Departments of Respiratory and Critical Care Medicine, and
| | - J Ying
- Departments of Obstetrics and Gynecology, The Affiliated Cangnan Hospital of Wenzhou Medical University, Cangnan, Zhejiang
| | - Z Jiang
- Department of Emergency Medicine, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou, Zhejiang
| | - L Zhang
- Departments of Respiratory and Critical Care Medicine, and
| | - Y Cai
- Departments of Respiratory and Critical Care Medicine, and
| | - C Zhou
- Departments of Respiratory and Critical Care Medicine, and
| | - Y Xu
- Department of Cardiology, Hangzhou Ninth People's Hospital, Hangzhou, Zhejiang
| | - S Lei
- Intensive Care Unit, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
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11
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Jiang Z, Shi C, Han H, Fu M, Zhu H, Han T, Fei J, Huang Y, Jin Z, He J, Wang Y, Chen X, Shen H. Autologous non-invasively derived stem cells mitochondria transfer shows therapeutic advantages in human embryo quality rescue. Biol Res 2023; 56:60. [PMID: 37978575 PMCID: PMC10657142 DOI: 10.1186/s40659-023-00470-1] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 10/26/2023] [Indexed: 11/19/2023] Open
Abstract
BACKGROUND The decline in the quantity and quality of mitochondria are closely associated with infertility, particularly in advanced maternal age. Transferring autologous mitochondria into the oocytes of infertile females represents an innovative and viable strategy for treating infertility, with no concerns regarding ethical considerations. As the donor cells of mitochondria, stem cells have biological advantages but research and evidence in this area are quite scarce. METHODS To screen out suitable human autologous ooplasmic mitochondrial donor cells, we performed comprehensive assessment of mitochondrial physiology, function and metabolic capacity on a varity of autologous adipose, marrow, and urine-derived mesenchymal stromal cells (ADSC, BMSC and USC) and ovarian germline granulosa cells (GC). Further, to explore the biosafety, effect and mechanism of stem cell-derived mitochondria transfer on human early embryo development, randomized in-vitro basic studies were performed in both of the young and aged oocytes from infertile females. RESULTS Compared with other types of mesenchymal stromal cells, USC demonstrated a non-fused spherical mitochondrial morphology and low oxidative stress status which resembled the oocyte stage. Moreover, USC mitochondrial content, activity and function were all higher than other cell types and less affected by age, and it also exhibited a biphasic metabolic pattern similar to the pre-implantation stage of embryonic development. After the biosafety identification of the USC mitochondrial genome, early embryos after USC mitochondrial transfer showed improvements in mitochondrial content, activity, and cytoplasmic Ca2+ levels. Further, aging embryos also showed improvements in embryonic morphological indicators, euploidy rates, and oxidative stress status. CONCLUSION Autologous non-invasively derived USC mitochondria transfer may be an effective strategy to improve embryonic development and metabolism, especially in infertile females with advanced age or repeated pregnancy failure. It provides evidence and possibility for the autologous treatment of infertile females without invasive and ethical concerns.
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Affiliation(s)
- Zhixin Jiang
- Reproductive Medical Center, Peking University People's Hospital, Peking University, Beijing, 100044, China
- Center for Reproductive Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200135, China
- Shanghai Key Laboratory for Assisted Reproduction and Reproductive Genetics, Shanghai, 200135, China
| | - Cheng Shi
- Reproductive Medical Center, Peking University People's Hospital, Peking University, Beijing, 100044, China
| | - Hongjing Han
- Reproductive Medical Center, Peking University People's Hospital, Peking University, Beijing, 100044, China
| | - Min Fu
- Reproductive Medical Center, Peking University People's Hospital, Peking University, Beijing, 100044, China
| | - Honglan Zhu
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Peking University, Beijing, 100044, China
| | - Tingting Han
- Peking University Institute of Hematology, National Clinical Research Center for Hematologic Disease, Beijing Key Laboratory of Hematopoietic Stem Cell Transplantation, Collaborative Innovation Center of Hematology, Peking University People's Hospital, Peking University, Beijing, 100044, China
| | - Jia Fei
- Peking Jabrehoo Med Tech Co., Ltd, Beijing, 102629, China
| | - Yining Huang
- Peking Jabrehoo Med Tech Co., Ltd, Beijing, 102629, China
| | - Zhiping Jin
- Peking Jabrehoo Med Tech Co., Ltd, Beijing, 102629, China
| | - Jianan He
- Peking Jabrehoo Med Tech Co., Ltd, Beijing, 102629, China
| | - Yanbin Wang
- Reproductive Medical Center, Peking University People's Hospital, Peking University, Beijing, 100044, China.
| | - Xi Chen
- Reproductive Medical Center, Peking University People's Hospital, Peking University, Beijing, 100044, China.
| | - Huan Shen
- Reproductive Medical Center, Peking University People's Hospital, Peking University, Beijing, 100044, China.
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12
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Kuai YX, Li M, Jiang Z, Chen J, Bai ZJ, Li XZ, Lu GP, Li YH. [Comparison of diagnostic criteria for acute kidney injury in critically ill children]. Zhonghua Er Ke Za Zhi 2023; 61:1011-1017. [PMID: 37899340 DOI: 10.3760/cma.j.cn112140-20230623-00418] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/31/2023]
Abstract
Objective: The kidney disease: improving global outcome (KDIGO) and pediatric reference change value optimized for acute kidney injury (pROCK) criteria were used to evaluate the incidence, stages and mortality of acute kidney injury (AKI). The differences between the 2 criteria were compared for exploring the value of pROCK criteria in diagnosing pediatric AKI and predicting adverse outcomes. Methods: In the multicenter prospective clinical cohort study, we collected general data and clinical data such as serum creatinine values from 1 120 children admitted to 4 PICUs of Children's Hospital of Soochow University, Children's Hospital of Fudan University, Anhui Provincial Children's Hospital, and Xuzhou Children's Hospital from September 2019 to February 2021. AKI was defined and staged according to the KDIGO and pROCK criteria. The incidence of AKI, the consistency of AKI definite diagnosis and stages, and the mortality in PICU were compared between the 2 groups. The chi-square test or Fisher's exact test was applied for comparison between 2 groups. The Cohen's Kappa and Weighted Kappa analyses were used for evaluating diagnostic consistency. The Cox regression analysis was used to evaluate the correlation between AKI and mortality. Results: A total of 1 120 critically ill children were included, with an age of 33 (10, 84) months. There are 668 boys and 452 girls. The incidence of AKI defined by the KDIGO guideline was higher than that defined by pROCK criteria (27.2%(305/1 120), 14.7%(165/1 120), χ2=52.78, P<0.001). The concordance rates of the 2 criteria for the diagnosis of AKI and AKI staging were 87.0% (κ=0.62) and 79.7% (κ=0.58), respectively. Totally 63 infants with AKI stage 1 defined by the KDIGO guideline were redefined as non-AKI by following the pROCK criteria. The PICU mortality rate of these infants was similar to patients without AKI defined by KDIGO guideline(P=0.761). After adjusting for confounders, AKI defined by KDIGO or pROCK criteria was an independent risk factor of death in PICU (AHR=2.04, 2.73,95%CI 1.27-3.29, 1.74-4.28, both P<0.01), and the risk of death was higher when using the pROCK compared with the KDIGO criteria. As for the KDIGO criteria, mild AKI was not associated with the mortality in PICU (P=0.702), while severe AKI was associated with increased mortality (P<0.001). As for the pROCK criteria, both mild and severe AKI were risk factors of PICU death in children (HR=3.51, 6.70, 95%CI 1.94-6.34, 4.30-10.44, both P<0.001). In addition, The AKI severity was positively associated with the mortality. Conclusions: The AKI incidence and staging varied depending on the used diagnostic criteria. The KDIGO definition is more sensitive, while the pROCK-defined AKI is more strongly associated with high mortality rate.
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Affiliation(s)
- Y X Kuai
- Department of Nephrology and Immunology, Children's Hospital of Soochow University, Suzhou 215000, China
| | - M Li
- Pediatric Intensive Care Unit, Anhui Provincial Children's Hospital, Hefei 230002, China
| | - Z Jiang
- Pediatric Intensive Care Unit, Xuzhou Children's Hospital, Xuzhou 221002, China
| | - J Chen
- Pediatric Intensive Care Unit, Children's Hospital of Soochow University, Suzhou 215000, China
| | - Z J Bai
- Pediatric Intensive Care Unit, Children's Hospital of Soochow University, Suzhou 215000, China
| | - X Z Li
- Department of Nephrology and Immunology, Children's Hospital of Soochow University, Suzhou 215000, China
| | - G P Lu
- Pediatric Intensive Care Unit, Children's Hospital of Fudan University, Shanghai 201102, China
| | - Y H Li
- Department of Nephrology and Immunology, Children's Hospital of Soochow University, Suzhou 215000, China
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Jiang Z, Xu XL, Zhuang PY. [Frontier technology and research progress in the diagnostics and therapeutics of voice diseases: report from the Voice Foundation 52nd Anniversary Symposium]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2023; 58:1024-1028. [PMID: 37840170 DOI: 10.3760/cma.j.cn115330-20230619-00289] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/17/2023]
Affiliation(s)
- Z Jiang
- Department of Voice Medicine, Zhongshan Hospital, Xiamen University; Key Laboratory of Voice of Xiamen City, Xiamen 361004, China
| | - X L Xu
- Department of Voice Medicine, Zhongshan Hospital, Xiamen University; Key Laboratory of Voice of Xiamen City, Xiamen 361004, China
| | - P Y Zhuang
- Department of Voice Medicine, Zhongshan Hospital, Xiamen University; Key Laboratory of Voice of Xiamen City, Xiamen 361004, China
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Hoke JC, Ippoliti M, Rosenberg E, Abanin D, Acharya R, Andersen TI, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Bengtsson A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Chik D, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Dau AG, Debroy DM, Del Toro Barba A, Demura S, Di Paolo A, Drozdov IK, Dunsworth A, Eppens D, Erickson C, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hoffmann MR, Hong S, Huang T, Huff A, Huggins WJ, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Kechedzhi K, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klimov PV, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lensky YD, Lester BJ, Lill AT, Liu W, Locharla A, Martin O, McClean JR, McEwen M, Miao KC, Mieszala A, Montazeri S, Morvan A, Movassagh R, Mruczkiewicz W, Neeley M, Neill C, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O’Brien TE, Omonije S, Opremcak A, Petukhov A, Potter R, Pryadko LP, Quintana C, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Skruzny J, Smith WC, Somma R, Sterling G, Strain D, Szalay M, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Babbush R, Bacon D, Boixo S, Hilton J, Lucero E, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Mi X, Khemani V, Roushan P. Measurement-induced entanglement and teleportation on a noisy quantum processor. Nature 2023; 622:481-486. [PMID: 37853150 PMCID: PMC10584681 DOI: 10.1038/s41586-023-06505-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 08/01/2023] [Indexed: 10/20/2023]
Abstract
Measurement has a special role in quantum theory1: by collapsing the wavefunction, it can enable phenomena such as teleportation2 and thereby alter the 'arrow of time' that constrains unitary evolution. When integrated in many-body dynamics, measurements can lead to emergent patterns of quantum information in space-time3-10 that go beyond the established paradigms for characterizing phases, either in or out of equilibrium11-13. For present-day noisy intermediate-scale quantum (NISQ) processors14, the experimental realization of such physics can be problematic because of hardware limitations and the stochastic nature of quantum measurement. Here we address these experimental challenges and study measurement-induced quantum information phases on up to 70 superconducting qubits. By leveraging the interchangeability of space and time, we use a duality mapping9,15-17 to avoid mid-circuit measurement and access different manifestations of the underlying phases, from entanglement scaling3,4 to measurement-induced teleportation18. We obtain finite-sized signatures of a phase transition with a decoding protocol that correlates the experimental measurement with classical simulation data. The phases display remarkably different sensitivity to noise, and we use this disparity to turn an inherent hardware limitation into a useful diagnostic. Our work demonstrates an approach to realizing measurement-induced physics at scales that are at the limits of current NISQ processors.
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Li Y, Zhang J, Cai W, Wang C, Yu Z, Jiang Z, Lai K, Wang Y, Yang G. CREB3L2 Regulates Hemidesmosome Formation during Epithelial Sealing. J Dent Res 2023; 102:1199-1209. [PMID: 37555472 DOI: 10.1177/00220345231176520] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/10/2023] Open
Abstract
The long-term success rate of dental implants can be improved by establishing a favorable biological sealing with a high-quality epithelial attachment. The application of mesenchymal stem cells (MSCs) holds promise for facilitating the soft tissue integration around implants, but the molecular mechanism is still unclear and the general application of MSC sheet for soft tissue integration is also relatively unexplored. We found that gingival tissue-derived MSC (GMSC) sheet treatment significantly promoted the expression of hemidesmosome (HD)-related genes and proteins in gingival epithelial cells (GECs). The formation of HDs played a key role in strengthening peri-implant epithelium (PIE) sealing. Further, high-throughput transcriptome sequencing showed that GMSC sheet significantly upregulated the PI3K/AKT pathway, confirming that cell adhesion and HD expression in GECs were regulated by GMSC sheet. We observed that the expression of transcription factor CREB3L2 in GECs was downregulated. After treatment with PI3K pathway inhibitor LY294002, CREB3L2 messenger RNA and protein expression levels were upregulated. Further experiments showed that overexpression or knockdown of CREB3L2 could significantly inhibit or promote HD-related genes and proteins, respectively. We confirmed that CREB3L2 was a transcription factor downstream of the PI3K/AKT pathway and participated in the formation of HDs regulated by GMSC sheet. Finally, through the establishment of early implant placement model in rats, we clarified the molecular function of CREB3L2 in PIE sealing as a mechanical transmission molecule in GECs. The application of GMSC sheet-implant complex could enhance the formation of HDs at the implant-PIE interface and decrease the penetration distance of horseradish peroxidase between the implant and PIE. Meanwhile, GMSC sheet reduced the length of CREB3L2 protein expression on PIE. These findings elucidate the potential function and molecular mechanism of MSC sheet regulating the epithelial sealing around implants, providing new insights and ideas for the application of stem cell therapy in regenerative medicine.
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Affiliation(s)
- Y Li
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
| | - J Zhang
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
| | - W Cai
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
| | - C Wang
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
| | - Z Yu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
| | - Z Jiang
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
| | - K Lai
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
| | - Y Wang
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
| | - G Yang
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center of Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, China
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Zhu F, Wang G, Zhao C, Malhotra S, Zhao M, He Z, Shi J, Jiang Z, Zhou W. Automatic reorientation by deep learning to generate short-axis SPECT myocardial perfusion images. J Nucl Cardiol 2023; 30:1825-1835. [PMID: 36859594 DOI: 10.1007/s12350-023-03226-2] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Accepted: 01/30/2023] [Indexed: 03/03/2023]
Abstract
BACKGROUND Single photon emission computed tomography (SPECT) myocardial perfusion images (MPI) can be displayed both in traditional short-axis (SA) cardiac planes and polar maps for interpretation and quantification. It is essential to reorient the reconstructed transaxial SPECT MPI into standard SA slices. This study is aimed to develop a deep-learning-based approach for automatic reorientation of MPI. METHODS A total of 254 patients were enrolled, including 226 stress SPECT MPIs and 247 rest SPECT MPIs. Fivefold cross-validation with 180 stress and 201 rest MPIs was used for training and internal validation; the remaining images were used for testing. The rigid transformation parameters (translation and rotation) from manual reorientation were annotated by an experienced nuclear cardiologist and used as the reference standard. A convolutional neural network (CNN) was designed to predict the transformation parameters. Then, the derived transform was applied to the grid generator and sampler in spatial transformer network (STN) to generate the reoriented image. A loss function containing mean absolute errors for translation and mean square errors for rotation was employed. A three-stage optimization strategy was adopted for model optimization: (1) optimize the translation parameters while fixing the rotation parameters; (2) optimize rotation parameters while fixing the translation parameters; (3) optimize both translation and rotation parameters together. RESULTS In the test set, the Spearman determination coefficients of the translation distances and rotation angles between the model prediction and the reference standard were 0.993 in X axis, 0.992 in Y axis, 0.994 in Z axis, 0.987 along X axis, 0.990 along Y axis and 0.996 along Z axis, respectively. For the 46 stress MPIs in the test set, the Spearman determination coefficients were 0.858 in percentage of profusion defect (PPD) and 0.858 in summed stress score (SSS); for the 46 rest MPIs in the test set, the Spearman determination coefficients were 0.9 in PPD and 0.9 in summed rest score (SRS). CONCLUSIONS Our deep learning-based LV reorientation method is able to accurately generate the SA images. Technical validations and subsequent evaluations of measured clinical parameters show that it has great promise for clinical use.
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Affiliation(s)
- Fubao Zhu
- School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450000, Henan, China
| | - Guojie Wang
- School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450000, Henan, China
| | - Chen Zhao
- Department of Applied Computing, Michigan Technological University, Houghton, MI, 49931, USA
| | - Saurabh Malhotra
- Division of Cardiology, Cook County Health and Hospitals System, Chicago, IL, 60612, USA
- Division of Cardiology, Rush Medical College, Chicago, IL, 60612, USA
| | - Min Zhao
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Zhuo He
- Department of Applied Computing, Michigan Technological University, Houghton, MI, 49931, USA
| | - Jianzhou Shi
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Guangzhou Road 300, Nanjing, 210029, Jiangsu, China
| | - Zhixin Jiang
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Guangzhou Road 300, Nanjing, 210029, Jiangsu, China.
| | - Weihua Zhou
- Department of Applied Computing, Michigan Technological University, Houghton, MI, 49931, USA.
- Center for Biocomputing and Digital Health, Institute of Computing and Cybersystems, and Health Research Institute, Michigan Technological University, 1400 Townsend Drive, Houghton, MI, 49931, USA.
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Lang Y, Jiang Z, Sun L, Xiang L, Ren L. Hybrid-Supervised Deep Learning for Proton-Acoustic Reconstruction for 3D In Vivo Proton Dose Verification. Int J Radiat Oncol Biol Phys 2023; 117:e682-e683. [PMID: 37786007 DOI: 10.1016/j.ijrobp.2023.06.2145] [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] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Proton-acoustic (PA) image has shown great potential to provide real-time 3D dose verification of proton therapy. However, the PA image quality suffers from severe limited view artifacts, which significantly impairs its accuracy for dose verification. In this study, we developed a hybrid-supervised deep learning method for PA reconstruction to address the limited-view issues. MATERIALS/METHODS Our method consists of two stages. In the first stage, a transformer-based network was proposed to reconstruct initial pressure maps from protoacoustic signals. The network was first trained using supervision by the iteratively reconstructed pressure map and then fine-tuned using transfer learning and self-supervision based on the data fidelity constraint. In the second stage, the PA image was further enhanced by a 3D U-net. The final PA images were converted to dose maps using conversion coefficients derived from CT images. Data from 126 prostate cancer patients treated by proton therapy were collected under an IRB protocol and were split into 86 and 40 patients for model training and testing, respectively. Data of each patient contains the planning CT scan, the corresponding clinical treatment plan, and the dose map calculated by commercial software. The radiofrequency signals were generated by performing proton acoustic simulation based on CT images and the ground truth pressure map derived from the treatment plan. An ultrasound detector matrix with 64 × 64 size and 500kHz central frequency was simulated under the perineum to acquire the signals in the prostate area. In the testing results, the method's accuracy was evaluated using Root-mean-squared-error (RMSE) and structural-similarity-index-measure (SSIM) between the reconstructed and ground truth pressure map and dose distribution. RESULTS Testing results showed that the reconstructed pressure map achieved an average RMSE/SSIM of 0.0292/0.96, demonstrating excellent 3D information with details. Dose maps derived from the pressure map achieved an average RMSE/SSIM of 0.018/0.99 with a gamma index of 94.7% and 95.7% for 1%/3 mm and 1%/5 mm criteria compared to the ground truth dose maps. The reconstruction time was 6s, which can be further reduced using GPU. CONCLUSION Our study achieves start-of-the-art performance in the challenging task of direct reconstruction from limited-view radiofrequency signals, demonstrating the great promise of PA imaging as a highly efficient and accurate tool for in-vivo 3D proton dose verification. Such high-precision 3D online dose verification can substantially reduce the range uncertainties of proton therapy to significantly improve its precision and outcomes.
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Affiliation(s)
- Y Lang
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD
| | | | - L Sun
- University of California, Irvine, CA
| | - L Xiang
- University of California, Irvine, CA
| | - L Ren
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD
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Zhang G, Jiang Z, Wang L. A Radiotherapy Positioning Method for Both Coarse Guidance and Precise Verification Based on Integration of AR and Optical Surface Imaging. Int J Radiat Oncol Biol Phys 2023; 117:e743-e744. [PMID: 37786156 DOI: 10.1016/j.ijrobp.2023.06.2280] [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] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Traditional methods of radiotherapy positioning have shortcomings such as fragile skin-markers, additional doses and lack of information integration. Emerging technologies may provide alternatives for the relevant clinical practice. We proposed a noninvasive radiotherapy positioning method integrating augmented reality (AR) and optical surface, and evaluated its feasibility in clinical workflow. MATERIALS/METHODS AR and structured light-based surface were integrated to implement the coarse-to-precise positioning through two coherent steps, i) the AR-based coarse guidance. To implement quality assurance, recognition of face and pattern was used for patient authentication, case association and accessory validation in AR scenes. The holographic images reconstructed from simulation computed tomography (CT) images, guided the initial posture correction by virtual-real alignment. ii) optical surface-based precise verification. The point clouds were fused, with the calibration and pose estimation of structured light cameras, and segmented according to the preset regions of interest (ROIs). The global-to-local registration for cross-source point clouds was achieved to calculate couch shifts in 6 degrees-of-freedom (DoF), which were ultimately transmitted to AR scenes. The evaluation based on phantom and human-body (4 volunteers) included, i) quality assurance workflow, ii) errors of both steps and correlation analysis, and iii) receiver operating characteristic (ROC). RESULTS The maximum errors in phantom evaluation were 3.4±2.5 mm in Vrt and 1.4±1.0° in Pitch for the coarse guidance step, while 1.6±0.9 mm in Vrt and 0.6±0.4° in Pitch for the precise verification step. The Pearson correlation coefficients between precise verification and cone beam CT (CBCT) results were distributed in the interval [0.81, 0.85]. In ROC analysis, the areas under the curve (AUC) were 0.87 and 0.89 for translation and rotation respectively. In human body-based evaluation, the errors of thorax and abdomen (T&A) were significantly greater than those of head and neck (H&N) in Vrt (2.6±1.3 vs. 1.7±1.1, p<0.01), Lng (2.4±1.3 vs. 1.4±0.1, p<0.01) and Rtn (0.8±0.5 vs. 0.6±0.4, p = 0.03) while relatively similar in Lat (1.7±1.0 vs. 1.9±1.1, p = 0.13). CONCLUSION The combination of AR and optical surface has utility and feasibility for patient positioning, in terms of both safety and accuracy.
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Affiliation(s)
- G Zhang
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Ji'nan, China
| | - Z Jiang
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Ji'nan, China
| | - L Wang
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
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Han R, Gao J, Wang L, Hao P, Chen X, Wang Y, Jiang Z, Jiang L, Wang T, Zhu L, Li X. MicroRNA-146a negatively regulates inflammation via the IRAK1/TRAF6/NF-κB signaling pathway in dry eye. Sci Rep 2023; 13:11192. [PMID: 37433841 DOI: 10.1038/s41598-023-38367-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 07/07/2023] [Indexed: 07/13/2023] Open
Abstract
Inflammation is a key factor in the pathogenesis of dry eye disease (DED). We aimed to investigate the role of microRNA-146a (miR-146a) in regulating corneal inflammation in a mouse model of benzalkonium chloride (BAC)-induced dry eye and the TNF-α-induced NF-κB signaling pathway in human corneal epithelial cells (HCECs). A mouse model of dry eye was established by administering with BAC to BALB/c mice, and the expression of TNF-α, IL-1β, IL-6, IL-8, cyclooxygenase 2 (COX2), interleukin-1 receptor-associated kinase 1 (IRAK1) and TNF receptor-associated factor 6 (TRAF6) in the corneas of dry eye model mice was significantly increased; this was accompanied by the upregulation of miR-146a and activation of the NF-κB pathway. In vitro, TNF-α induced miR-146a expression in HCECs, while the NF-κB inhibitor SC-514 reduced the expression of miR-146a. Overexpression of miR-146a decreased the expression of IRAK1 and TRAF6, which have been identified as targets of miR-146a. Furthermore, overexpression of miR-146a suppressed NF-κB p65 translocation from the cytoplasm to the nucleus. Moreover, overexpression of miR-146a attenuated the TNF-α-induced expression of IL-6, IL-8, COX2 and intercellular adhesion molecule 1 (ICAM1), while inhibition of miR-146a exerted the opposite effect. Our results suggest that miR-146a mediates the inflammatory response in DED. MiR-146a negatively regulates inflammation in HCECs through the IRAK1/TRAF6/NF-κB pathway, and this may serve as a potential therapeutic approach for the treatment of DED.
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Affiliation(s)
- Ruifang Han
- Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin Eye Hospital, Tianjin Eye Institute, Nankai University Affiliated Eye Hospital, Clinical College of Ophthalmology of Tianjin Medical University, No.4 Gansu Road, Heping District, Tianjin, 300020, China
| | - Juan Gao
- Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin Eye Hospital, Tianjin Eye Institute, Nankai University Affiliated Eye Hospital, Clinical College of Ophthalmology of Tianjin Medical University, No.4 Gansu Road, Heping District, Tianjin, 300020, China
| | - Liming Wang
- Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin Eye Hospital, Tianjin Eye Institute, Nankai University Affiliated Eye Hospital, Clinical College of Ophthalmology of Tianjin Medical University, No.4 Gansu Road, Heping District, Tianjin, 300020, China
| | - Peng Hao
- Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin Eye Hospital, Tianjin Eye Institute, Nankai University Affiliated Eye Hospital, Clinical College of Ophthalmology of Tianjin Medical University, No.4 Gansu Road, Heping District, Tianjin, 300020, China
| | - Xi Chen
- Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin Eye Hospital, Tianjin Eye Institute, Nankai University Affiliated Eye Hospital, Clinical College of Ophthalmology of Tianjin Medical University, No.4 Gansu Road, Heping District, Tianjin, 300020, China
| | - Yuchuan Wang
- Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin Eye Hospital, Tianjin Eye Institute, Nankai University Affiliated Eye Hospital, Clinical College of Ophthalmology of Tianjin Medical University, No.4 Gansu Road, Heping District, Tianjin, 300020, China
| | - Zhixin Jiang
- Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin Eye Hospital, Tianjin Eye Institute, Nankai University Affiliated Eye Hospital, Clinical College of Ophthalmology of Tianjin Medical University, No.4 Gansu Road, Heping District, Tianjin, 300020, China
| | - Li Jiang
- Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin Eye Hospital, Tianjin Eye Institute, Nankai University Affiliated Eye Hospital, Clinical College of Ophthalmology of Tianjin Medical University, No.4 Gansu Road, Heping District, Tianjin, 300020, China
| | - Ting Wang
- Clinical College of Ophthalmology, Tianjin Medical University, Tianjin, China
| | - Lin Zhu
- Clinical College of Ophthalmology, Tianjin Medical University, Tianjin, China
| | - Xuan Li
- Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin Eye Hospital, Tianjin Eye Institute, Nankai University Affiliated Eye Hospital, Clinical College of Ophthalmology of Tianjin Medical University, No.4 Gansu Road, Heping District, Tianjin, 300020, China.
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Yang FL, Chen X, Zheng F, Liu XX, Sun N, Li RQ, Jiang Z, Han J, Yang J. [Targeting microRNA-125b inhibited the metastasis of Alisertib resistance cells through mediating p53 pathway]. Zhonghua Zhong Liu Za Zhi 2023; 45:499-507. [PMID: 37355468 DOI: 10.3760/cma.j.cn112152-20200511-00438] [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: 06/26/2023]
Abstract
Objective: To clarify the mechanisms involvement in Alisertib-resistant colorectal cells and explore a potential target to overcome Alisertib-resistance. Methods: Drug-resistant colon cancer cell line (named as HCT-8-7T cells) was established and transplanted into immunodeficient mice. The metastasis in vivo were observed. Proliferation and migration of HCT-8-7T cells and their parental cells were assessed by colony formation and Transwell assay, respectively. Glycolytic capacity and glutamine metabolism of cells were analyzed by metabolism assays. The protein and mRNA levels of critical factors which are involved in mediating glycolysis and epithelial-mesenchymal transition (EMT) were examined by western blot and reverse transcription-quantitative real-time polymerase chain reaction(RT-qPCR), respectively. Results: In comparison with the mice transplanted with HCT-8 cells, which were survival with limited metastatic tumor cells in organs, aggressive metastases were observed in liver, lung, kidney and ovary of HCT-8-7T transplanted mice (P<0.05). The levels of ATP [(0.10±0.01) mmol/L], glycolysis [(81.77±8.21) mpH/min] and the capacity of glycolysis [(55.50±3.48) mpH/min] in HCT-8-7T cells were higher than those of HCT-8 cells [(0.04±0.01) mmol/L, (27.77±2.55) mpH/min and(14.00±1.19) mpH/min, respectively, P<0.05]. Meanwhile, the levels of p53 protein and mRNA in HCT-8-7T cells were potently decreased as compared to that in HCT-8 cells (P<0.05). However, the level of miRNA-125b (2.21±0.12) in HCT-8-7T cells was significantly elevated as compared to that in HCT-8 cells (1.00±0.00, P<0.001). In HCT-8-7T cells, forced-expression of p53 reduced the colon number (162.00±24.00) and the migration [(18.53±5.67)%] as compared with those in cells transfected with control vector [274.70±40.50 and (100.00±29.06)%, P<0.05, respectively]. Similarly, miR-125b mimic decreased the glycolysis [(25.28±9.51) mpH/min] in HCT-8-7T cells as compared with that [(54.38±12.70)mpH/min, P=0.003] in HCT-8-7T cells transfected with control. Meanwhile, in comparison with control transfected HCT-8-7T cells, miR-125b mimic also significantly led to an increase in the levels of p53 and β-catenin, in parallel with a decrease in the levels of PFK1 and HK1 in HCT-8-7T cells (P<0.05). Conclusions: Silencing of p53 by miR-125b could be one of the mechanisms that contributes to Alisertib resistance. Targeting miR-125b could be a strategy to overcome Alisertib resistance.
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Affiliation(s)
- F L Yang
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Xuzhou 221000, China
| | - X Chen
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Jiangsu International Joint Laboratory for Immunology and Metabolism, Xuzhou 221000, China
| | - F Zheng
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Xuzhou 221000, China
| | - X X Liu
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Jiangsu International Joint Laboratory for Immunology and Metabolism, Xuzhou 221000, China
| | - N Sun
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Jiangsu International Joint Laboratory for Immunology and Metabolism, Xuzhou 221000, China
| | - R Q Li
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Jiangsu International Joint Laboratory for Immunology and Metabolism, Xuzhou 221000, China
| | - Z Jiang
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Xuzhou 221000, China
| | - J Han
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Jiangsu International Joint Laboratory for Immunology and Metabolism, Xuzhou 221000, China
| | - J Yang
- Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu Province Key Laboratory of Immunity and Metabolism, National Experimental Teaching Demonstration Center of Basic Medicine, Xuzhou Medical University, Jiangsu International Joint Laboratory for Immunology and Metabolism, Xuzhou 221000, China
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Andersen TI, Lensky YD, Kechedzhi K, Drozdov IK, Bengtsson A, Hong S, Morvan A, Mi X, Opremcak A, Acharya R, Allen R, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Babbush R, Bacon D, Bardin JC, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Chik D, Chou C, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Debroy DM, Del Toro Barba A, Demura S, Dunsworth A, Eppens D, Erickson C, Faoro L, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Dau AG, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hilton J, Hoffmann MR, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klimov PV, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lester BJ, Lill AT, Liu W, Locharla A, Lucero E, Malone FD, Martin O, McClean JR, McCourt T, McEwen M, Miao KC, Mieszala A, Mohseni M, Montazeri S, Mount E, Movassagh R, Mruczkiewicz W, Naaman O, Neeley M, Neill C, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O’Brien TE, Omonije S, Petukhov A, Potter R, Pryadko LP, Quintana C, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Skruzny J, Smith WC, Somma R, Sterling G, Strain D, Szalay M, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Boixo S, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Kim EA, Aleiner I, Roushan P. Non-Abelian braiding of graph vertices in a superconducting processor. Nature 2023; 618:264-269. [PMID: 37169834 DOI: 10.1038/s41586-023-05954-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 03/14/2023] [Indexed: 06/09/2023]
Abstract
Indistinguishability of particles is a fundamental principle of quantum mechanics1. For all elementary and quasiparticles observed to date-including fermions, bosons and Abelian anyons-this principle guarantees that the braiding of identical particles leaves the system unchanged2,3. However, in two spatial dimensions, an intriguing possibility exists: braiding of non-Abelian anyons causes rotations in a space of topologically degenerate wavefunctions4-8. Hence, it can change the observables of the system without violating the principle of indistinguishability. Despite the well-developed mathematical description of non-Abelian anyons and numerous theoretical proposals9-22, the experimental observation of their exchange statistics has remained elusive for decades. Controllable many-body quantum states generated on quantum processors offer another path for exploring these fundamental phenomena. Whereas efforts on conventional solid-state platforms typically involve Hamiltonian dynamics of quasiparticles, superconducting quantum processors allow for directly manipulating the many-body wavefunction by means of unitary gates. Building on predictions that stabilizer codes can host projective non-Abelian Ising anyons9,10, we implement a generalized stabilizer code and unitary protocol23 to create and braid them. This allows us to experimentally verify the fusion rules of the anyons and braid them to realize their statistics. We then study the prospect of using the anyons for quantum computation and use braiding to create an entangled state of anyons encoding three logical qubits. Our work provides new insights about non-Abelian braiding and, through the future inclusion of error correction to achieve topological protection, could open a path towards fault-tolerant quantum computing.
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22
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Liu L, Zhu M, Wang Y, Wan B, Jiang Z. [Molecular pathological mechanism of liver metabolic disorder in mice with severe spinal muscular atrophy]. Nan Fang Yi Ke Da Xue Xue Bao 2023; 43:852-858. [PMID: 37313828 DOI: 10.12122/j.issn.1673-4254.2023.05.22] [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: 06/15/2023]
Abstract
OBJECTIVE To explore the molecular pathological mechanism of liver metabolic disorder in severe spinal muscular atrophy (SMA). METHODS The transgenic mice with type Ⅰ SMA (Smn-/- SMN20tg/2tg) and littermate control mice (Smn+/- SMN20tg/2tg) were observed for milk suckling behavior and body weight changes after birth. The mice with type Ⅰ SMA mice were given an intraperitoneal injection of 20% glucose solution or saline (15 μL/12 h), and their survival time was recorded. GO enrichment analysis was performed using the RNA-Seq data of the liver of type Ⅰ SMA and littermate control mice, and the results were verified using quantitative real-time PCR. Bisulfite sequencing was performed to examine CpG island methylation level in Fasn gene promoter region in the liver of the neonatal mice. RESULTS The neonatal mice with type Ⅰ SMA showed normal milk suckling behavior but had lower body weight than the littermate control mice on the second day after birth. Intraperitoneal injection of glucose solution every 12 h significantly improved the median survival time of type Ⅰ SMA mice from 9±1.3 to 11± 1.5 days (P < 0.05). Analysis of the RNA-Seq data of the liver showed that the expression of the target genes of PPARα related to lipid metabolism and mitochondrial β oxidation were down-regulated in the liver of type Ⅰ SMA mice. Type Ⅰ SMA mice had higher methylation level of the Fasn promoter region in the liver than the littermate control mice (76.44% vs 58.67%). In primary cultures of hepatocytes from type Ⅰ SMA mice, treatment with 5-AzaC significantly up-regulated the expressions of the genes related to lipid metabolism by over 1 fold (P < 0.01). CONCLUSION Type Ⅰ SMA mice have liver metabolic disorder, and the down-regulation of the target genes of PPARα related to lipid and glucose metabolism due to persistent DNA methylation contributes to the progression of SMA.
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Affiliation(s)
- L Liu
- Suzhou Medical College of Soochow University, Suzhou 215000, China
| | - M Zhu
- Suzhou Medical College of Soochow University, Suzhou 215000, China
| | - Y Wang
- Suzhou Medical College of Soochow University, Suzhou 215000, China
| | - B Wan
- Suzhou Medical College of Soochow University, Suzhou 215000, China
| | - Z Jiang
- Suzhou Medical College of Soochow University, Suzhou 215000, China
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Nie XY, Xue Y, Li L, Jiang Z, Qin B, Wang Y, Wang S. A functional intact SUMOylation machinery in Aspergillus flavus contributes to fungal and aflatoxin contamination of food. Int J Food Microbiol 2023; 398:110241. [PMID: 37167787 DOI: 10.1016/j.ijfoodmicro.2023.110241] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 04/08/2023] [Accepted: 05/01/2023] [Indexed: 05/13/2023]
Abstract
SUMO adducts occur in Aspergillus flavus, and are implicated in fungal biology, while the underlying mechanism and the SUMOylation apparatus components in this saprophytic food spoilage mould, remain undefined. Herein, genes encoding SUMOylation cascade enzymes in A. flavus, including two heterodimeric SUMO E1 activating enzymes, a unique SUMO E2 conjugating enzyme, and one of SUMO E3 ligases, were identified and functionally analyzed. Global SUMO adducts immunoassay, multiple morphological comparison, aflatoxin attributes test, fungal infection and transcriptomic analyses collectively revealed that: E1 and E2 were essential for intracellular SUMOylation, and contributed to both stress response and fungal virulence-related events, including sporulation, colonization, aflatoxins biosynthesis; the primary E3 in this fungus, AfSizA, might serve as the molecular linkage of SUMOylation pathway to fungal virulence rather than SUMOylation-mediated stress adaptation. These findings demonstrated that SUMOylation machinery in A. flavus was functionally intact and contributed to multiple pathobiological processes, hence offering ideas and targets to control food contamination by this mycotoxigenic fungus.
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Affiliation(s)
- Xin-Yi Nie
- Key Laboratory of Pathogenic Fungi and Mycotoxins of Fujian Province, School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
| | - Yang Xue
- Key Laboratory of Pathogenic Fungi and Mycotoxins of Fujian Province, School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Ling Li
- Key Laboratory of Pathogenic Fungi and Mycotoxins of Fujian Province, School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Zhixin Jiang
- Key Laboratory of Pathogenic Fungi and Mycotoxins of Fujian Province, School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Bei Qin
- Key Laboratory of Pathogenic Fungi and Mycotoxins of Fujian Province, School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Yu Wang
- Key Laboratory of Pathogenic Fungi and Mycotoxins of Fujian Province, School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Shihua Wang
- Key Laboratory of Pathogenic Fungi and Mycotoxins of Fujian Province, School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
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Gao G, Li X, Jiang Z, Osorio L, Tang YL, Yu X, Jin G, Zhou Z. Isthmin-1 (Ism1) modulates renal branching morphogenesis and mesenchyme condensation during early kidney development. Nat Commun 2023; 14:2378. [PMID: 37185772 PMCID: PMC10130008 DOI: 10.1038/s41467-023-37992-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 04/06/2023] [Indexed: 05/17/2023] Open
Abstract
The outgrowth of epithelial bud followed by reiterated bifurcations during renal development is driven by the ligand-receptor interactions between the epithelium and the surrounding mesenchyme. Here, by exploring ligand-receptor interactions in E10.5 and E11.5 kidneys by single cell RNA-seq, we find that Isthmin1 (Ism1), a secreted protein, resembles Gdnf expression and modulates kidney branching morphogenesis. Mice deficient for Ism1 exhibit defective ureteric bud bifurcation and impaired metanephric mesenchyme condensation in E11.5 embryos, attributable to the compromised Gdnf/Ret signaling, ultimately leading to renal agenesis and hypoplasia/dysplasia. By HRP-induced proximity labelling, we further identify integrin α8β1 as a receptor of Ism1 in E11.5 kidney and demonstrate that Ism1 promoted cell-cell adhesion through interacting with Integrin α8β1, the receptor whose activation is responsible for Gdnf expression and mesenchyme condensation. Taken together, our work reveals Ism1 as a critical regulator of cell-cell interaction that modulates Gdnf/Ret signaling during early kidney development.
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Affiliation(s)
- Ge Gao
- Guangdong Cardiovascular Institute, Medical Research Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China
- School of Biomedical Sciences, LKS Faculty of medicine, The University of Hong Kong, Hong Kong, China
| | - Xiaoping Li
- Department of Hepatic Surgery and Liver Transplantation Center of the Third Affiliated Hospital, Organ Transplantation Institute, Sun Yat-sen University, Guangzhou, 510630, Guangdong, China
| | - Zhixin Jiang
- School of Biomedical Sciences, LKS Faculty of medicine, The University of Hong Kong, Hong Kong, China
| | - Liliana Osorio
- School of Biomedical Sciences, LKS Faculty of medicine, The University of Hong Kong, Hong Kong, China
| | - Ying Lam Tang
- School of Biomedical Sciences, LKS Faculty of medicine, The University of Hong Kong, Hong Kong, China
| | - Xueqing Yu
- Guangdong Cardiovascular Institute, Medical Research Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China
| | - Guoxiang Jin
- Guangdong Cardiovascular Institute, Medical Research Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China
| | - Zhongjun Zhou
- Guangdong Cardiovascular Institute, Medical Research Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China.
- School of Biomedical Sciences, LKS Faculty of medicine, The University of Hong Kong, Hong Kong, China.
- Reproductive Medical Center, The University of Hong Kong - Shenzhen Hospital, Shenzhen, China.
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Zhu F, Li L, Zhao J, Zhao C, Tang S, Nan J, Li Y, Zhao Z, Shi J, Chen Z, Han C, Jiang Z, Zhou W. A new method incorporating deep learning with shape priors for left ventricular segmentation in myocardial perfusion SPECT images. Comput Biol Med 2023; 160:106954. [PMID: 37130501 DOI: 10.1016/j.compbiomed.2023.106954] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 04/09/2023] [Accepted: 04/15/2023] [Indexed: 05/04/2023]
Abstract
Accurate segmentation of the left ventricle (LV) is crucial for evaluating myocardial perfusion SPECT (MPS) and assessing LV functions. In this study, a novel method combining deep learning with shape priors was developed and validated to extract the LV myocardium and automatically measure LV functional parameters. The method integrates a three-dimensional (3D) V-Net with a shape deformation module that incorporates shape priors generated by a dynamic programming (DP) algorithm to guide its output during training. A retrospective analysis was performed on an MPS dataset comprising 31 subjects without or with mild ischemia, 32 subjects with moderate ischemia, and 12 subjects with severe ischemia. Myocardial contours were manually annotated as the ground truth. A 5-fold stratified cross-validation was used to train and validate the models. The clinical performance was evaluated by measuring LV end-systolic volume (ESV), end-diastolic volume (EDV), left ventricular ejection fraction (LVEF), and scar burden from the extracted myocardial contours. There were excellent agreements between segmentation results by our proposed model and those from the ground truth, with a Dice similarity coefficient (DSC) of 0.9573 ± 0.0244, 0.9821 ± 0.0137, and 0.9903 ± 0.0041, as well as Hausdorff distances (HD) of 6.7529 ± 2.7334 mm, 7.2507 ± 3.1952 mm, and 7.6121 ± 3.0134 mm in extracting the LV endocardium, myocardium, and epicardium, respectively. Furthermore, the correlation coefficients between LVEF, ESV, EDV, stress scar burden, and rest scar burden measured from our model results and the ground truth were 0.92, 0.958, 0.952, 0.972, and 0.958, respectively. The proposed method achieved a high accuracy in extracting LV myocardial contours and assessing LV functions.
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Affiliation(s)
- Fubao Zhu
- School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450001, China
| | - Longxi Li
- School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450001, China
| | - Jinyu Zhao
- School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450001, China
| | - Chen Zhao
- Department of Applied Computing, Michigan Technological University, Houghton, MI, 49931, USA
| | - Shaojie Tang
- School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi, 710121, China
| | - Jiaofen Nan
- School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450001, China
| | - Yanting Li
- School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450001, China
| | - Zhongqiang Zhao
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Provincial Hospital), Nanjing, 210029, China
| | - Jianzhou Shi
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Provincial Hospital), Nanjing, 210029, China
| | - Zenghong Chen
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Provincial Hospital), Nanjing, 210029, China
| | - Chuang Han
- School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450001, China
| | - Zhixin Jiang
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Provincial Hospital), Nanjing, 210029, China.
| | - Weihua Zhou
- Department of Applied Computing, Michigan Technological University, Houghton, MI, 49931, USA; Center for Biocomputing and Digital Health, Institute of Computing and Cybersystems, Health Research Institute, Michigan Technological University, Houghton, MI, 49931, USA.
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Zhong H, Chen S, Jiang Z, Hu J, Dong J, Chung LH, Lin QC, Ou W, Yu L, He J. Utilizing Metal-Thiocatecholate Functionalized UiO-66 Framework for Photocatalytic Hydrogen Evolution Reaction. Small 2023; 19:e2207266. [PMID: 36693790 DOI: 10.1002/smll.202207266] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 01/07/2023] [Indexed: 06/17/2023]
Abstract
Exploiting clean energy is essential for sustainable development and sunlight-driven photocatalytic water splitting represents one of the most promising approaches toward this goal. Metal-organic frameworks (MOFs) are competent photocatalysts owing to their tailorable functionality, well-defined structure, and high porosity. Yet, the introduction of the unambiguous metal-centered active site into MOFs is still challenging since framework motifs capable of anchoring metal ions firmly are lacking. Herein, the assembly using 1,4-dicarboxylbenzene-2,3-dithiol (H2 dcbdt) and Zr-Oxo clusters to give a thiol-functionalized UiO-66 type framework, UiO-66-dcbdt, is reported. The thiocatechols on the struts are allowed to capture transition metal (TM) ions to generate UiO-66-dcbdt-M (M = Fe, Ni, Cu) with unambiguous metal-thiocatecholate moieties for photocatalytic hydrogen evolution reaction (HER). UiO-66-dcbdt-Cu is found the best catalyst exhibiting an HER rate of 4.18 mmol g-1 h-1 upon irradiation with photosensitizing Ru-polypyridyl complex. To skip the use of the external sensitizer, UiO-66-dcbdt-Cu is heterojunctioned with titanium dioxide (TiO2 ) and achieves an HER rate of 12.63 mmol g-1 h-1 (32.3 times that of primitive TiO2 ). This work represents the first example of MOF assembly employing H2 dcbdt as the mere linker followed by chelation with TM ions and undoubtedly fuels the rational design of MOF photocatalysts bearing well-defined active sites.
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Affiliation(s)
- Hao Zhong
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, 510006, P. R. China
| | - Song Chen
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, 510006, P. R. China
| | - Zhixin Jiang
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, 510006, P. R. China
| | - Jieying Hu
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, 510006, P. R. China
| | - Jiale Dong
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, 510006, P. R. China
| | - Lai-Hon Chung
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, 510006, P. R. China
| | - Qia-Chun Lin
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, 510006, P. R. China
| | - Weihui Ou
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, 510006, P. R. China
| | - Lin Yu
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, 510006, P. R. China
| | - Jun He
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou, 510006, P. R. China
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Luo QR, Hu J, Jiang Z, Chen S, Ye X, Li J, Chung LH, Yu L, He J. Ni(II)-Pyrazolate Framework Bearing a Metalated Schiff-Base Moiety for Electrocatalytic Hydrogen Evolution. Inorg Chem 2023; 62:5229-5236. [PMID: 36960995 DOI: 10.1021/acs.inorgchem.3c00239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/25/2023]
Abstract
A robust and porous Ni-based metal-organic framework (MOF), NiL1, was assembled from Ni(II) ions and a dipyrazolate linker (L12-). A Ni(II)-anchored MOF catalyst Ni@NiL1-Sal has been successfully prepared by post-synthetic modification (PSM) condensation between NiL1 with salicylaldehyde, followed by chelation of Ni(II) ions by salicylaldimine as a secondary active site. Ni@NiL1-Sal with carbon black was found to exhibit enhanced electrocatalytic hydrogen evolution reaction (HER) performance (the smallest overpotential, 384 mV, and Tafel slope, 87 mV dec-1) when compared with primitive NiL1 and NiL1-Sal. Such improvement in HER highlights the creation of unambiguous secondary active sites as an avenue to the rational design of a functional MOF-based electrocatalyst.
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Affiliation(s)
- Qian-Ru Luo
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou 510006, Guangdong, China
| | - Jieying Hu
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou 510006, Guangdong, China
| | - Zhixin Jiang
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou 510006, Guangdong, China
| | - Shaoru Chen
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou 510006, Guangdong, China
| | - Xinhe Ye
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou 510006, Guangdong, China
| | - Jianrong Li
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou 510006, Guangdong, China
| | - Lai-Hon Chung
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou 510006, Guangdong, China
| | - Lin Yu
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou 510006, Guangdong, China
| | - Jun He
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou 510006, Guangdong, China
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Yang W, Wu T, Wu Y, Xu J, Jiang Z, Zhou X, Shan Q. Left Bundle Branch Pacing for Bradycardia in Non-obstructive Hypertrophic Cardiomyopathy Patients: Feasibility, Safety, and Effect. Cardiovasc Drugs Ther 2023:10.1007/s10557-023-07440-5. [PMID: 36847900 DOI: 10.1007/s10557-023-07440-5] [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] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/02/2023] [Indexed: 03/01/2023]
Abstract
PURPOSE Left bundle branch pacing (LBBP) is as an innovative physiological pacing approach. The research on LBBP in non-obstructive hypertrophic cardiomyopathy (NOHCM) patients is scarce. This study aimed to assess the feasibility, safety, and effect of LBBP in bradycardia NOHCM patients with permanent pacemaker (PPM) implantation indication. METHODS Thirteen consecutive patients with NOHCM who received LBBP were retrospectively enrolled as a hypertrophic cardiomyopathy (HCM) group. Following 1:3 matching, 39 patients without HCM were randomly matched as a control group. Echocardiographic index and pacing parameters were collected. RESULTS The successful LBBP was achieved in 96.2% of all cases (50/52), and the success rate of the HCM group was 92.3% (12/13). In the HCM group, the paced QRS duration (from the pacing stimulus to QRS end) was 145.6±20.8 ms. The stimulus to left ventricular activation time (s-LVAT) was 87.4±15.2 ms. In the control group, the paced QRS duration was 139.4±17.2 ms, and the s-LVAT was 79.9±14.1 ms. During the implantation, R-wave sensing and the pacing threshold of the HCM group were significantly higher than the control group (20.2±10.5 vs 12.5±5.9 mV, P < 0.05; 0.8±0.3 vs 0.6±0.2V/0.4 ms, P < 0.05). In addition, the fluoroscopic duration and procedural duration were longer in the HCM group (14.8±8.3 vs 10.3±6.6min, P = 0.07; 131.8±50.5 vs 101.4±41.6 min, P < 0.05). The lead insertion depth was 15±2 mm in the HCM group, and no procedure-related complications occurred. During the 12-month follow-up, pacing parameters remained stable and were of no significance in the two groups. The cardiac function did not deteriorate, and the left ventricular outflow tract gradient (LVOTG) did not increase in the follow-up. CONCLUSION LBBP might be feasible and safe for NOHCM patients with conventional bradycardia pacing indication, and there is no deterioration in cardiac function and LVOTG of patients with NOHCM.
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Affiliation(s)
- Wen Yang
- Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), 300, Guangzhou Road, Nanjing, 210029, China
| | - Tian Wu
- Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), 300, Guangzhou Road, Nanjing, 210029, China
| | - Yixian Wu
- Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), 300, Guangzhou Road, Nanjing, 210029, China
| | - Jiayi Xu
- Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), 300, Guangzhou Road, Nanjing, 210029, China
| | - Zhixin Jiang
- Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), 300, Guangzhou Road, Nanjing, 210029, China
| | - Xiujuan Zhou
- Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), 300, Guangzhou Road, Nanjing, 210029, China.
| | - Qijun Shan
- Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), 300, Guangzhou Road, Nanjing, 210029, China.
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Zhan K, Zhang X, Wang B, Jiang Z, Fang X, Yang S, Jia H, Li L, Cao G, Zhang K, Ma X. Response to: COVID-19 and diabetes-double whammy. QJM 2023; 116:144-145. [PMID: 35178559 DOI: 10.1093/qjmed/hcac048] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 02/10/2022] [Indexed: 12/24/2022] Open
Affiliation(s)
- K Zhan
- College of Public Health, Southwest Medical University, Luzhou, Sichuan, China
- Department of Epidemiology, College of Preventive Medicine, Third Military Medical University (Army Medical University), Chongqing, China
| | - X Zhang
- Department of General Surgery, Daping Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - B Wang
- Pulmonary and Critical Care Medicine Center, Chinese PLA Respiratory Disease Institute, Xinqiao Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Z Jiang
- Yidu Cloud Technology Co. Ltd, Beijing, China
| | - X Fang
- College of Public Health, Southwest Medical University, Luzhou, Sichuan, China
- Department of Epidemiology, College of Preventive Medicine, Third Military Medical University (Army Medical University), Chongqing, China
| | - S Yang
- Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing 400038, China
| | - H Jia
- College of Public Health, Southwest Medical University, Luzhou, Sichuan, China
| | - L Li
- Department of Respiratory Medicine, Daping Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - G Cao
- Department of Respiratory Medicine, Daping Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - K Zhang
- Department of Outpatients, Daping Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - X Ma
- Department of Epidemiology, College of Preventive Medicine, Third Military Medical University (Army Medical University), Chongqing, China
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Zhan K, Zhang X, Wang B, Jiang Z, Fang X, Yang S, Jia H, Li L, Cao G, Zhang K, Ma X. Response to: Glycemic control and COVID-19 outcomes: the missing metabolic players. QJM 2023; 116:91-92. [PMID: 35166838 PMCID: PMC9383446 DOI: 10.1093/qjmed/hcac044] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Accepted: 02/07/2022] [Indexed: 12/24/2022] Open
Affiliation(s)
- K Zhan
- From the College of Public Health, Southwest Medical University, Xianglin street 1, Luzhou, Sichuan 646000, China
- Department of Epidemiology, College of Preventive Medicine, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
| | - X Zhang
- Department of General Surgery, Daping Hospital, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
| | - B Wang
- Pulmonary and Critical Care Medicine Center, Chinese PLA Respiratory Disease Institute, Xinqiao Hospital, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
| | - Z Jiang
- Yidu Cloud Technology Co. Ltd, North Huayuan Road 35, Beijing 100071, China
| | - X Fang
- From the College of Public Health, Southwest Medical University, Xianglin street 1, Luzhou, Sichuan 646000, China
- Department of Epidemiology, College of Preventive Medicine, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
| | - S Yang
- Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
| | - H Jia
- From the College of Public Health, Southwest Medical University, Xianglin street 1, Luzhou, Sichuan 646000, China
| | - L Li
- Department of Respiratory Medicine, Daping Hospital, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
| | - G Cao
- Department of Respiratory Medicine, Daping Hospital, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
| | - K Zhang
- Department of Outpatients, Daping Hospital, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
| | - X Ma
- Department of Epidemiology, College of Preventive Medicine, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China
- Address correspondence to X. Ma, Department of General Surgery, Daping Hospital, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China. ,
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Wang LL, Hong H, Zhang YR, Shi HB, Chen L, Jiang HB, Jiang Z, Wu Z. [Cost-effectiveness prediction of AIDS interventions among men who have sex with men in Ningbo]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:2008-2014. [PMID: 36572477 DOI: 10.3760/cma.j.cn112338-20220410-00275] [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: 12/29/2022]
Abstract
Objective: To provide information reference for resource allocation and decision-making in related fields, the cost-effectiveness of HIV input among men who have sex with men (MSM) in Ningbo. Different intervention coverages were compared. Methods: Taking MSM as the target population, data were collected and modeled by Optima HIV for the corresponding HIV health output and the budget under different intervention coverages. Results: According to the estimated size of the MSM population, which was 19 584 in Ningbo in 2020, if the coverage of 2020 baseline intervention is maintained in the next ten years, the number of HIV cases, new HIV infections, and HIV-related deaths among this population will show an upward trend. It is estimated that from 2021 to 2030, 7.9% of new infections and 1.7% of deaths can be avoided and the relevant funding investment comed to 2.4 time the baseline if the intervention coverage rate expanded to 3.0 times the 2020 baseline. After the coverage rate of intervention expanded to 3 times the baseline, it continued to grow, the health effect did not increase. Conclusions: At present, expanding the baseline coverage of HIV-related intervention projects among MSM in Ningbo and increasing capital investment will still reverse HIV-related death and reduce new infections. Moreover, there is a saturation point of the intervention effect. Researchers and policymakers must explore more effective interventions/combinations to obtain more significant health outcomes.
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Affiliation(s)
- L L Wang
- School of Health Management, Anhui Medical University, Hefei 230032, China
| | - H Hong
- Ningbo municipal Center for Disease Control and Prevention, Ningbo 315010, China
| | - Y R Zhang
- School of Health Management, Anhui Medical University, Hefei 230032, China
| | - H B Shi
- Ningbo municipal Center for Disease Control and Prevention, Ningbo 315010, China
| | - L Chen
- Department of HIV/AIDS and STDS Control and Prevention, Zhejiang Center for Disease Control and Prevention, Hangzhou 310000, China
| | - H B Jiang
- Ningbo municipal Center for Disease Control and Prevention, Ningbo 315010, China
| | - Z Jiang
- Division of Health Education and Behavioral Intervention, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Zunyou Wu
- Division of Health Education and Behavioral Intervention, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
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32
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Pinzón-Arteaga C, Wang Y, Wei Y, Scatolin G, Liu L, Yu L, Jiang Z, Wu J. 234 Bovine blastocyst-like structures derived from pluripotent stem cell cultures. Reprod Fertil Dev 2022. [DOI: 10.1071/rdv35n2ab234] [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: 12/09/2022] Open
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33
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Scatolin G, Wang Y, Zhu L, Gutierrez-Castillo E, Jiang Z. 92 A single cell atlas of bovine peri-implantation embryo development. Reprod Fertil Dev 2022. [DOI: 10.1071/rdv35n2ab92] [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: 12/12/2022] Open
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34
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Liu L, Jiang Z, Li F, Wei Y, Ming J, Yang Y, Liu S, Shi L, Chen Y. Were economic evaluations well reported for the newly listed oncology drugs in China's national reimbursement drug list. BMC Health Serv Res 2022; 22:1475. [PMID: 36463141 PMCID: PMC9719239 DOI: 10.1186/s12913-022-08858-7] [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] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Accepted: 11/18/2022] [Indexed: 12/05/2022] Open
Abstract
PURPOSE To assess the reporting quality of published economic evaluations of the negotiated oncology drugs listed for China's 2020 National Reimbursement Drug List (NRDL). METHODS A comprehensive search was conducted to identify economic evaluation studies of negotiated oncology drugs listed in China's 2020 NRDL using the PubMed/MEDLINE, Embase, Web of Science, CNKI, SinoMed, and WanFang Database up to March 31, 2021. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist scored the reporting quality between 0 and 100. A linear regression analysis was employed to examine the influence of various characteristics on the reporting quality scores. RESULTS Eighty papers were included in the study, with the majority published during the past decade. Furthermore, more than half of the articles (57.5%, or 46 out of 80) were written in English. The average CHEERS score was 74.63 ± 12.75 and ranged from 43.48 to 93.75. The most inadequately reported items included choice of model, characterization of heterogeneity, and discussion, as well as currency, price date and conversion. Higher scores were associated with articles published from 2019 to 2021 and English publications. CONCLUSION The economic evaluation studies of negotiated oncology drugs listed in 2020 NRDL had moderate reporting quality. The Chinese economic evaluation publications could improve the reporting quality if the CHEERS checklist is consistently implemented. Also, the Chinese journals maybe explore introducing a reporting standard for economic evaluations.
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Affiliation(s)
- Liu Liu
- grid.8547.e0000 0001 0125 2443School of Public Health, Fudan University, Shanghai, China ,grid.8547.e0000 0001 0125 2443NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai, China
| | - Zhixin Jiang
- grid.8547.e0000 0001 0125 2443School of Public Health, Fudan University, Shanghai, China ,grid.8547.e0000 0001 0125 2443NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai, China
| | - Fuming Li
- grid.8547.e0000 0001 0125 2443School of Public Health, Fudan University, Shanghai, China ,grid.8547.e0000 0001 0125 2443NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai, China
| | - Yan Wei
- grid.8547.e0000 0001 0125 2443School of Public Health, Fudan University, Shanghai, China ,grid.8547.e0000 0001 0125 2443NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai, China
| | - Jian Ming
- grid.8547.e0000 0001 0125 2443School of Public Health, Fudan University, Shanghai, China ,grid.8547.e0000 0001 0125 2443NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai, China ,Real World Solutions, IQVIA China, Shanghai, China
| | - Yi Yang
- grid.8547.e0000 0001 0125 2443School of Public Health, Fudan University, Shanghai, China ,grid.8547.e0000 0001 0125 2443NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai, China
| | - Shimeng Liu
- grid.8547.e0000 0001 0125 2443School of Public Health, Fudan University, Shanghai, China ,grid.8547.e0000 0001 0125 2443NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai, China
| | - Lizheng Shi
- grid.265219.b0000 0001 2217 8588School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA USA
| | - Yingyao Chen
- grid.8547.e0000 0001 0125 2443School of Public Health, Fudan University, Shanghai, China ,grid.8547.e0000 0001 0125 2443NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai, China
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35
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Morvan A, Andersen TI, Mi X, Neill C, Petukhov A, Kechedzhi K, Abanin DA, Michailidis A, Acharya R, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Basso J, Bengtsson A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Debroy DM, Del Toro Barba A, Demura S, Dunsworth A, Eppens D, Erickson C, Faoro L, Farhi E, Fatemi R, Flores Burgos L, Forati E, Fowler AG, Foxen B, Giang W, Gidney C, Gilboa D, Giustina M, Grajales Dau A, Gross JA, Habegger S, Hamilton MC, Harrigan MP, Harrington SD, Hoffmann M, Hong S, Huang T, Huff A, Huggins WJ, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev AY, Klimov PV, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lester BJ, Lill AT, Liu W, Locharla A, Malone F, Martin O, McClean JR, McEwen M, Meurer Costa B, Miao KC, Mohseni M, Montazeri S, Mount E, Mruczkiewicz W, Naaman O, Neeley M, Nersisyan A, Newman M, Nguyen A, Nguyen M, Niu MY, O'Brien TE, Olenewa R, Opremcak A, Potter R, Quintana C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shvarts V, Skruzny J, Smith WC, Strain D, Sterling G, Su Y, Szalay M, Torres A, Vidal G, Villalonga B, Vollgraff-Heidweiller C, White T, Xing C, Yao Z, Yeh P, Yoo J, Zalcman A, Zhang Y, Zhu N, Neven H, Bacon D, Hilton J, Lucero E, Babbush R, Boixo S, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Aleiner I, Ioffe LB, Roushan P. Formation of robust bound states of interacting microwave photons. Nature 2022; 612:240-245. [PMID: 36477133 PMCID: PMC9729104 DOI: 10.1038/s41586-022-05348-y] [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] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 09/14/2022] [Indexed: 12/12/2022]
Abstract
Systems of correlated particles appear in many fields of modern science and represent some of the most intractable computational problems in nature. The computational challenge in these systems arises when interactions become comparable to other energy scales, which makes the state of each particle depend on all other particles1. The lack of general solutions for the three-body problem and acceptable theory for strongly correlated electrons shows that our understanding of correlated systems fades when the particle number or the interaction strength increases. One of the hallmarks of interacting systems is the formation of multiparticle bound states2-9. Here we develop a high-fidelity parameterizable fSim gate and implement the periodic quantum circuit of the spin-½ XXZ model in a ring of 24 superconducting qubits. We study the propagation of these excitations and observe their bound nature for up to five photons. We devise a phase-sensitive method for constructing the few-body spectrum of the bound states and extract their pseudo-charge by introducing a synthetic flux. By introducing interactions between the ring and additional qubits, we observe an unexpected resilience of the bound states to integrability breaking. This finding goes against the idea that bound states in non-integrable systems are unstable when their energies overlap with the continuum spectrum. Our work provides experimental evidence for bound states of interacting photons and discovers their stability beyond the integrability limit.
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Affiliation(s)
- A Morvan
- Google Research, Mountain View, CA, USA
| | | | - X Mi
- Google Research, Mountain View, CA, USA
| | - C Neill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Abanin
- Google Research, Mountain View, CA, USA
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - A Michailidis
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - R Acharya
- Google Research, Mountain View, CA, USA
| | - F Arute
- Google Research, Mountain View, CA, USA
| | - K Arya
- Google Research, Mountain View, CA, USA
| | - A Asfaw
- Google Research, Mountain View, CA, USA
| | - J Atalaya
- Google Research, Mountain View, CA, USA
| | - J C Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | - J Basso
- Google Research, Mountain View, CA, USA
| | | | - G Bortoli
- Google Research, Mountain View, CA, USA
| | | | - J Bovaird
- Google Research, Mountain View, CA, USA
| | - L Brill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Buell
- Google Research, Mountain View, CA, USA
| | - T Burger
- Google Research, Mountain View, CA, USA
| | - B Burkett
- Google Research, Mountain View, CA, USA
| | | | - Z Chen
- Google Research, Mountain View, CA, USA
| | - B Chiaro
- Google Research, Mountain View, CA, USA
| | - R Collins
- Google Research, Mountain View, CA, USA
| | - P Conner
- Google Research, Mountain View, CA, USA
| | | | - A L Crook
- Google Research, Mountain View, CA, USA
| | - B Curtin
- Google Research, Mountain View, CA, USA
| | | | | | - S Demura
- Google Research, Mountain View, CA, USA
| | | | - D Eppens
- Google Research, Mountain View, CA, USA
| | | | - L Faoro
- Google Research, Mountain View, CA, USA
| | - E Farhi
- Google Research, Mountain View, CA, USA
| | - R Fatemi
- Google Research, Mountain View, CA, USA
| | | | - E Forati
- Google Research, Mountain View, CA, USA
| | | | - B Foxen
- Google Research, Mountain View, CA, USA
| | - W Giang
- Google Research, Mountain View, CA, USA
| | - C Gidney
- Google Research, Mountain View, CA, USA
| | - D Gilboa
- Google Research, Mountain View, CA, USA
| | | | | | - J A Gross
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - S Hong
- Google Research, Mountain View, CA, USA
| | - T Huang
- Google Research, Mountain View, CA, USA
| | - A Huff
- Google Research, Mountain View, CA, USA
| | | | | | - J Iveland
- Google Research, Mountain View, CA, USA
| | - E Jeffrey
- Google Research, Mountain View, CA, USA
| | - Z Jiang
- Google Research, Mountain View, CA, USA
| | - C Jones
- Google Research, Mountain View, CA, USA
| | - P Juhas
- Google Research, Mountain View, CA, USA
| | - D Kafri
- Google Research, Mountain View, CA, USA
| | - T Khattar
- Google Research, Mountain View, CA, USA
| | - M Khezri
- Google Research, Mountain View, CA, USA
| | - M Kieferová
- Google Research, Mountain View, CA, USA
- Centre for Quantum Computation and Communication Technology, Centre for Quantum Software and Information, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, New South Wales, Australia
| | - S Kim
- Google Research, Mountain View, CA, USA
| | - A Y Kitaev
- Google Research, Mountain View, CA, USA
- Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, CA, USA
| | | | - A R Klots
- Google Research, Mountain View, CA, USA
| | - A N Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P Laptev
- Google Research, Mountain View, CA, USA
| | - K-M Lau
- Google Research, Mountain View, CA, USA
| | - L Laws
- Google Research, Mountain View, CA, USA
| | - J Lee
- Google Research, Mountain View, CA, USA
| | - K W Lee
- Google Research, Mountain View, CA, USA
| | | | - A T Lill
- Google Research, Mountain View, CA, USA
| | - W Liu
- Google Research, Mountain View, CA, USA
| | | | - F Malone
- Google Research, Mountain View, CA, USA
| | - O Martin
- Google Research, Mountain View, CA, USA
| | | | - M McEwen
- Google Research, Mountain View, CA, USA
- Department of Physics, University of California, Santa Barbara, CA, USA
| | | | - K C Miao
- Google Research, Mountain View, CA, USA
| | - M Mohseni
- Google Research, Mountain View, CA, USA
| | | | - E Mount
- Google Research, Mountain View, CA, USA
| | | | - O Naaman
- Google Research, Mountain View, CA, USA
| | - M Neeley
- Google Research, Mountain View, CA, USA
| | | | - M Newman
- Google Research, Mountain View, CA, USA
| | - A Nguyen
- Google Research, Mountain View, CA, USA
| | - M Nguyen
- Google Research, Mountain View, CA, USA
| | - M Y Niu
- Google Research, Mountain View, CA, USA
| | | | - R Olenewa
- Google Research, Mountain View, CA, USA
| | | | - R Potter
- Google Research, Mountain View, CA, USA
| | | | - N C Rubin
- Google Research, Mountain View, CA, USA
| | - N Saei
- Google Research, Mountain View, CA, USA
| | - D Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - A Shorter
- Google Research, Mountain View, CA, USA
| | - V Shvarts
- Google Research, Mountain View, CA, USA
| | - J Skruzny
- Google Research, Mountain View, CA, USA
| | - W C Smith
- Google Research, Mountain View, CA, USA
| | - D Strain
- Google Research, Mountain View, CA, USA
| | | | - Y Su
- Google Research, Mountain View, CA, USA
| | - M Szalay
- Google Research, Mountain View, CA, USA
| | - A Torres
- Google Research, Mountain View, CA, USA
| | - G Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T White
- Google Research, Mountain View, CA, USA
| | - C Xing
- Google Research, Mountain View, CA, USA
| | - Z Yao
- Google Research, Mountain View, CA, USA
| | - P Yeh
- Google Research, Mountain View, CA, USA
| | - J Yoo
- Google Research, Mountain View, CA, USA
| | - A Zalcman
- Google Research, Mountain View, CA, USA
| | - Y Zhang
- Google Research, Mountain View, CA, USA
| | - N Zhu
- Google Research, Mountain View, CA, USA
| | - H Neven
- Google Research, Mountain View, CA, USA
| | - D Bacon
- Google Research, Mountain View, CA, USA
| | - J Hilton
- Google Research, Mountain View, CA, USA
| | - E Lucero
- Google Research, Mountain View, CA, USA
| | - R Babbush
- Google Research, Mountain View, CA, USA
| | - S Boixo
- Google Research, Mountain View, CA, USA
| | - A Megrant
- Google Research, Mountain View, CA, USA
| | - J Kelly
- Google Research, Mountain View, CA, USA
| | - Y Chen
- Google Research, Mountain View, CA, USA
| | | | - I Aleiner
- Google Research, Mountain View, CA, USA.
| | - L B Ioffe
- Google Research, Mountain View, CA, USA.
| | - P Roushan
- Google Research, Mountain View, CA, USA.
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36
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Mi X, Sonner M, Niu MY, Lee KW, Foxen B, Acharya R, Aleiner I, Andersen TI, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Basso J, Bengtsson A, Bortoli G, Bourassa A, Brill L, Broughton M, Buckley BB, Buell DA, Burkett B, Bushnell N, Chen Z, Chiaro B, Collins R, Conner P, Courtney W, Crook AL, Debroy DM, Demura S, Dunsworth A, Eppens D, Erickson C, Faoro L, Farhi E, Fatemi R, Flores L, Forati E, Fowler AG, Giang W, Gidney C, Gilboa D, Giustina M, Dau AG, Gross JA, Habegger S, Harrigan MP, Hoffmann M, Hong S, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Kafri D, Kechedzhi K, Khattar T, Kim S, Kitaev AY, Klimov PV, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Lee J, Laws L, Liu W, Locharla A, Martin O, McClean JR, McEwen M, Meurer Costa B, Miao KC, Mohseni M, Montazeri S, Morvan A, Mount E, Mruczkiewicz W, Naaman O, Neeley M, Neill C, Newman M, O’Brien TE, Opremcak A, Petukhov A, Potter R, Quintana C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schuster C, Shearn MJ, Shvarts V, Strain D, Su Y, Szalay M, Vidal G, Villalonga B, Vollgraff-Heidweiller C, White T, Yao Z, Yeh P, Yoo J, Zalcman A, Zhang Y, Zhu N, Neven H, Bacon D, Hilton J, Lucero E, Babbush R, Boixo S, Megrant A, Chen Y, Kelly J, Smelyanskiy V, Abanin DA, Roushan P. Noise-resilient edge modes on a chain of superconducting qubits. Science 2022; 378:785-790. [DOI: 10.1126/science.abq5769] [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] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Inherent symmetry of a quantum system may protect its otherwise fragile states. Leveraging such protection requires testing its robustness against uncontrolled environmental interactions. Using 47 superconducting qubits, we implement the one-dimensional kicked Ising model, which exhibits nonlocal Majorana edge modes (MEMs) with
ℤ
2
parity symmetry. We find that any multiqubit Pauli operator overlapping with the MEMs exhibits a uniform late-time decay rate comparable to single-qubit relaxation rates, irrespective of its size or composition. This characteristic allows us to accurately reconstruct the exponentially localized spatial profiles of the MEMs. Furthermore, the MEMs are found to be resilient against certain symmetry-breaking noise owing to a prethermalization mechanism. Our work elucidates the complex interplay between noise and symmetry-protected edge modes in a solid-state environment.
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Affiliation(s)
- X. Mi
- Google Research, Mountain View, CA, USA
| | - M. Sonner
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - M. Y. Niu
- Google Research, Mountain View, CA, USA
| | - K. W. Lee
- Google Research, Mountain View, CA, USA
| | - B. Foxen
- Google Research, Mountain View, CA, USA
| | | | | | | | - F. Arute
- Google Research, Mountain View, CA, USA
| | - K. Arya
- Google Research, Mountain View, CA, USA
| | - A. Asfaw
- Google Research, Mountain View, CA, USA
| | | | - J. C. Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | - J. Basso
- Google Research, Mountain View, CA, USA
| | | | | | | | - L. Brill
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - Z. Chen
- Google Research, Mountain View, CA, USA
| | - B. Chiaro
- Google Research, Mountain View, CA, USA
| | | | - P. Conner
- Google Research, Mountain View, CA, USA
| | | | | | | | - S. Demura
- Google Research, Mountain View, CA, USA
| | | | - D. Eppens
- Google Research, Mountain View, CA, USA
| | | | - L. Faoro
- Google Research, Mountain View, CA, USA
| | - E. Farhi
- Google Research, Mountain View, CA, USA
| | - R. Fatemi
- Google Research, Mountain View, CA, USA
| | - L. Flores
- Google Research, Mountain View, CA, USA
| | - E. Forati
- Google Research, Mountain View, CA, USA
| | | | - W. Giang
- Google Research, Mountain View, CA, USA
| | - C. Gidney
- Google Research, Mountain View, CA, USA
| | - D. Gilboa
- Google Research, Mountain View, CA, USA
| | | | - A. G. Dau
- Google Research, Mountain View, CA, USA
| | | | | | | | | | - S. Hong
- Google Research, Mountain View, CA, USA
| | - T. Huang
- Google Research, Mountain View, CA, USA
| | - A. Huff
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - Z. Jiang
- Google Research, Mountain View, CA, USA
| | - C. Jones
- Google Research, Mountain View, CA, USA
| | - D. Kafri
- Google Research, Mountain View, CA, USA
| | | | | | - S. Kim
- Google Research, Mountain View, CA, USA
| | - A. Y. Kitaev
- Google Research, Mountain View, CA, USA
- Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, CA, USA
| | | | | | - A. N. Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P. Laptev
- Google Research, Mountain View, CA, USA
| | - K.-M. Lau
- Google Research, Mountain View, CA, USA
| | - J. Lee
- Google Research, Mountain View, CA, USA
| | - L. Laws
- Google Research, Mountain View, CA, USA
| | - W. Liu
- Google Research, Mountain View, CA, USA
| | | | - O. Martin
- Google Research, Mountain View, CA, USA
| | | | - M. McEwen
- Google Research, Mountain View, CA, USA
- Department of Physics, University of California, Santa Barbara, CA, USA
| | | | | | | | | | - A. Morvan
- Google Research, Mountain View, CA, USA
| | - E. Mount
- Google Research, Mountain View, CA, USA
| | | | - O. Naaman
- Google Research, Mountain View, CA, USA
| | - M. Neeley
- Google Research, Mountain View, CA, USA
| | - C. Neill
- Google Research, Mountain View, CA, USA
| | - M. Newman
- Google Research, Mountain View, CA, USA
| | | | | | | | - R. Potter
- Google Research, Mountain View, CA, USA
| | | | | | - N. Saei
- Google Research, Mountain View, CA, USA
| | - D. Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - D. Strain
- Google Research, Mountain View, CA, USA
| | - Y. Su
- Google Research, Mountain View, CA, USA
| | - M. Szalay
- Google Research, Mountain View, CA, USA
| | - G. Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T. White
- Google Research, Mountain View, CA, USA
| | - Z. Yao
- Google Research, Mountain View, CA, USA
| | - P. Yeh
- Google Research, Mountain View, CA, USA
| | - J. Yoo
- Google Research, Mountain View, CA, USA
| | | | - Y. Zhang
- Google Research, Mountain View, CA, USA
| | - N. Zhu
- Google Research, Mountain View, CA, USA
| | - H. Neven
- Google Research, Mountain View, CA, USA
| | - D. Bacon
- Google Research, Mountain View, CA, USA
| | - J. Hilton
- Google Research, Mountain View, CA, USA
| | - E. Lucero
- Google Research, Mountain View, CA, USA
| | | | - S. Boixo
- Google Research, Mountain View, CA, USA
| | | | - Y. Chen
- Google Research, Mountain View, CA, USA
| | - J. Kelly
- Google Research, Mountain View, CA, USA
| | | | - D. A. Abanin
- Google Research, Mountain View, CA, USA
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
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37
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Feng K, Liu J, Zhao M, Jiang Z, Liu P, Wei P, Dou W, He L. The dynamic changes of genes revealed that persistently overexpressed genes drive the evolution of cyflumetofen resistance in Tetranychus cinnabarinus. Insect Sci 2022. [PMID: 36380571 DOI: 10.1111/1744-7917.13151] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 11/02/2022] [Accepted: 11/07/2022] [Indexed: 06/16/2023]
Abstract
Changes in gene expression are associated with the evolution of pesticide resistance in arthropods. In this study, transcriptome sequencing was performed in 3 different resistance levels (low, L; medium, M; and high, H) of cyflumetofen-resistant strain (YN-CyR). A total of 1 685 genes, including 97 detoxification enzyme genes, were upregulated in all 3 stages, of which 192 genes, including 11 detoxification enzyme genes, showed a continuous increase in expression level with resistance development (L to H). RNA interference experiments showed that overexpression of 7 genes (CYP392A1, TcGSTd05, CCE06, CYP389A1, TcGSTz01, CCE59, and CYP389C2) is involved in the development of cyflumetofen resistance in Tetranychus cinnabarinus. The recombinant CYP392A1 can effectively metabolize cyflumetofen, while CCE06 can bind and sequester cyflumetofen in vitro. We compared 2 methods for rapid screening of resistance molecular markers, including short-term induction and 1-time high-dose selection. Two detoxification enzyme genes were upregulated in the field susceptible strain (YN-S) by induction with 20% lethal concentration (LC20 ) of cyflumetofen. However, 16 detoxification enzyme genes were upregulated by 1-time selection with LC80 of cyflumetofen. Interestingly, the 16 genes were overexpressed in all 3 resistance stages. These results indicated that 1 685 genes that were upregulated at the L stage constituted the basis of cyflumetofen resistance, of which 192 genes in which upregulation continued to increase were the main driving force for the development of resistance. Moreover, the 1-time high-dose selection is an efficient way to rapidly obtain the resistance-related genes that can aid in the development of resistance markers and resistance management in mites.
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Affiliation(s)
- Kaiyang Feng
- Key Laboratory of Entomology and Pest Control Engineering, College of Plant Protection, Southwest University, Chongqing, China
- Academy of Agricultural Sciences, Southwest University, Chongqing, China
- State Cultivation Base of Crop Stress Biology for Southern Mountainous Land of Southwest University, Southwest University, Chongqing, China
| | - Jialu Liu
- Key Scientific Research Base of Pest and Mold Control of Heritage Collection (Chongqing China Three Gorges Museum), State Administration of Cultural Heritage, Chongqing, China
| | - Mingyu Zhao
- Key Laboratory of Entomology and Pest Control Engineering, College of Plant Protection, Southwest University, Chongqing, China
- Academy of Agricultural Sciences, Southwest University, Chongqing, China
- State Cultivation Base of Crop Stress Biology for Southern Mountainous Land of Southwest University, Southwest University, Chongqing, China
- Key Scientific Research Base of Pest and Mold Control of Heritage Collection (Chongqing China Three Gorges Museum), State Administration of Cultural Heritage, Chongqing, China
| | - Zhixin Jiang
- Key Laboratory of Entomology and Pest Control Engineering, College of Plant Protection, Southwest University, Chongqing, China
- Academy of Agricultural Sciences, Southwest University, Chongqing, China
- State Cultivation Base of Crop Stress Biology for Southern Mountainous Land of Southwest University, Southwest University, Chongqing, China
| | - Peilin Liu
- Key Laboratory of Entomology and Pest Control Engineering, College of Plant Protection, Southwest University, Chongqing, China
- Academy of Agricultural Sciences, Southwest University, Chongqing, China
- State Cultivation Base of Crop Stress Biology for Southern Mountainous Land of Southwest University, Southwest University, Chongqing, China
| | - Peng Wei
- Key Laboratory of Entomology and Pest Control Engineering, College of Plant Protection, Southwest University, Chongqing, China
- Academy of Agricultural Sciences, Southwest University, Chongqing, China
- State Cultivation Base of Crop Stress Biology for Southern Mountainous Land of Southwest University, Southwest University, Chongqing, China
| | - Wei Dou
- Key Laboratory of Entomology and Pest Control Engineering, College of Plant Protection, Southwest University, Chongqing, China
- Academy of Agricultural Sciences, Southwest University, Chongqing, China
- State Cultivation Base of Crop Stress Biology for Southern Mountainous Land of Southwest University, Southwest University, Chongqing, China
| | - Lin He
- Key Laboratory of Entomology and Pest Control Engineering, College of Plant Protection, Southwest University, Chongqing, China
- Academy of Agricultural Sciences, Southwest University, Chongqing, China
- State Cultivation Base of Crop Stress Biology for Southern Mountainous Land of Southwest University, Southwest University, Chongqing, China
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38
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Yue JL, Jiang Z, Sun RJ, Fu B, Zhang HD, Pan XL, Liu DY. [Giant esophageal tumor presenting as pharyngeal mass: a report of three cases]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2022; 57:1341-1343. [PMID: 36404662 DOI: 10.3760/cma.j.cn115330-20220321-00124] [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: 06/16/2023]
Affiliation(s)
- J L Yue
- Department of Otorhinolaryngology Head and Neck Surgery, Qilu Hospital of Shandong University (Qingdao), Qingdao 266035, China National Health Commission Key Laboratory of Otorhinolaryngology(Shandong University), Jinan 250012, China
| | - Z Jiang
- Department of Otorhinolaryngology Head and Neck Surgery, Qilu Hospital of Shandong University (Qingdao), Qingdao 266035, China National Health Commission Key Laboratory of Otorhinolaryngology(Shandong University), Jinan 250012, China
| | - R J Sun
- Department of Otorhinolaryngology Head and Neck Surgery, Qilu Hospital of Shandong University (Qingdao), Qingdao 266035, China
| | - B Fu
- Department of Otorhinolaryngology Head and Neck Surgery, Qilu Hospital of Shandong University (Qingdao), Qingdao 266035, China National Health Commission Key Laboratory of Otorhinolaryngology(Shandong University), Jinan 250012, China
| | - H D Zhang
- Department of Otorhinolaryngology Head and Neck Surgery, Qilu Hospital of Shandong University (Qingdao), Qingdao 266035, China
| | - X L Pan
- Department of Otorhinolaryngology Head and Neck Surgery, Qilu Hospital of Shandong University (Qingdao), Qingdao 266035, China National Health Commission Key Laboratory of Otorhinolaryngology(Shandong University), Jinan 250012, China
| | - D Y Liu
- Department of Otorhinolaryngology Head and Neck Surgery, Qilu Hospital of Shandong University (Qingdao), Qingdao 266035, China National Health Commission Key Laboratory of Otorhinolaryngology(Shandong University), Jinan 250012, China
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Jiang Z, Liang Y, Wang X, Zhuang M, Feng M, Kuang Y. A Radiomics-Based Light Gradient Boosting Machine to Predict Radiation-Induced Toxicities in Nasopharynx Cancer Patients Receiving Chemoradiotherapy. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.933] [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: 10/31/2022]
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40
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Geng J, Jiang Z, Zhang S, Zhou X, Chen Y, Chen M, Chen C, Shan Q. Reversible T-wave inversions during left bundle branch area pacing. Kardiol Pol 2022; 80:1002-1009. [DOI: 10.33963/kp.a2022.0167] [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] [Received: 07/12/2022] [Accepted: 07/12/2022] [Indexed: 11/15/2022]
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41
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Li J, Li X, Jiang Z, Hu C, Liu J, Huo J, Liu B. Predicting the probability of malignant pathological type of kidney cancer based on mass size: A retrospective study. Prog Urol 2022; 32:849-855. [PMID: 36068150 DOI: 10.1016/j.purol.2022.08.007] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 07/30/2022] [Accepted: 08/11/2022] [Indexed: 11/19/2022]
Abstract
BACKGROUND Different degrees of malignancy of renal cell carcinoma (RCC) correspond to dissimilar therapies, and the prediction of malignancy of kidney cancer based on tumor size is still not fully studied. METHODS We evaluated a total of 50,776 patients with T1-T2, N0, M0 RCC diagnosed between 2004 to 2015 based on the Surveillance, Epidemiology, and End Results database. Three and four fuhrman grade clear cell RCC, three and four fuhrman grade papillary RCC, collecting duct RCC, sarcomatoid differentiation RCC and unclassified RCC were classified as aggressive RCC. The other RCC was classified as indolent RCC. The probability of aggressive and indolent was estimated according to tumor size using a logistic regression model. Differences in survival between subgroups were assessed using the Kaplan-Meier method. RESULTS There were 38,003 cases of indolent tumor and 12,773 cases of aggressive tumor totally. As tumor size increases, the predicted probability of an aggressive tumor also increases. Concretely, kidney cancers of 2cm, 3cm and 4cm were estimated to be 19.6%, 21.6% and 23.7% more likely to be aggressive. And for the same tumor size, clear cell RCC in men is more likely to be invasive relative to women and other kidney cancer pathology types. In addition, both the overall and tumor-specific survival are longer for indolent tumors than for aggressive tumors. CONCLUSION We evaluated the degree of malignancy of different sizes RCC in a retrospective study. This result may be helpful in the choice of initial therapy strategies for kidney cancer patients.
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Affiliation(s)
- J Li
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China; Jiangsu Province Academy of Traditional Chinese Medicine, Jiangsu, China
| | - X Li
- Kunshan Hospital of Traditional Chinese Medicine, Kunshan, Jiangsu, China
| | - Z Jiang
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China; Jiangsu Province Academy of Traditional Chinese Medicine, Jiangsu, China
| | - C Hu
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China; Jiangsu Province Academy of Traditional Chinese Medicine, Jiangsu, China
| | - J Liu
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China; Jiangsu Province Academy of Traditional Chinese Medicine, Jiangsu, China
| | - J Huo
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China; Jiangsu Province Academy of Traditional Chinese Medicine, Jiangsu, China
| | - B Liu
- The Comprehensive Cancer Centre of Nanjing Drum Tower Hospital, 321, zhongshan Road, 210008 Nanjing, China.
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42
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Zhu X, Chen S, Ma K, Chen Z, Chen C, Jiang Z. AInterventricular septum angle obtained from cardiac computed tomography for origin differentiation of outflow tract ventricular arrhythmia between left and right. Pacing Clin Electrophysiol 2022; 45:1279-1287. [DOI: 10.1111/pace.14593] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 09/07/2022] [Accepted: 09/09/2022] [Indexed: 11/26/2022]
Affiliation(s)
- Xiaomei Zhu
- Department of Radiology the First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital) Nanjing China
| | - Shumin Chen
- Department of Cardiology the First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital) Nanjing China
| | - Kefan Ma
- Department of Radiology the First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital) Nanjing China
| | - Zenghong Chen
- Department of Cardiology the First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital) Nanjing China
| | - Chun Chen
- Department of Cardiology the First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital) Nanjing China
| | - Zhixin Jiang
- Department of Cardiology the First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital) Nanjing China
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43
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Subramanian J, Gregg J, Berktas M, Jiang Z, Li J, Taylor A, Leighl N. EP08.02-080 EGFR Testing Practices, Treatment Choice and Clinical Outcomes in Advanced NSCLC in a Real-World Setting. J Thorac Oncol 2022. [DOI: 10.1016/j.jtho.2022.07.762] [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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Zhan K, Zhang X, Wang B, Jiang Z, Fang X, Yang S, Jia H, Li L, Cao G, Zhang K, Ma X. Response to: Comment on short- and long-term prognosis of glycemic control in COVID-19 patients with type 2 diabetes. QJM 2022; 115:569-570. [PMID: 35789280 PMCID: PMC9384456 DOI: 10.1093/qjmed/hcac162] [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] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Indexed: 12/03/2022] Open
Affiliation(s)
| | | | | | - Z Jiang
- Yidu Cloud Technology Co. Ltd., Beijing, China
| | - X Fang
- Department of Epidemiology, College of Preventive Medicine, Third Military Medical University (Army Medical University), Chongqing, China
| | - S Yang
- Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing 400038, China
| | - H Jia
- From the College of Public Health, Southwest Medical University, Luzhou, Sichuan, China
| | - L Li
- Department of Respiratory Medicine, Daping Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - G Cao
- Department of Respiratory Medicine, Daping Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - K Zhang
- Department of Outpatients, Daping Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - X Ma
- Address correspondence to X. Ma, Department of Epidemiology, College of Preventive Medicine, Third Military Medical University (Army Medical University), Gaotanyan Street 30, Shapingba District, Chongqing 400038, China. ,
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Han YC, Sun PC, Jiang Z, Fan ZM, Wang HB. [The surgical management of benign tumors of the lateral skull base with intracranial invasion: experience from a single centre over ten years]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2022; 57:810-818. [PMID: 35866273 DOI: 10.3760/cma.j.cn115330-20210630-00406] [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 investigate the clinical features, pathological types, imaging features, and surgical strategies of lateral skull base benign tumors with intracranial invasion. Methods: From January 2011 to March 2021, 36 patients of lateral skull base benign tumors with intracranial invasion were included in this retrospective study. Among the 36 patients, 14 cases were male, 22 cases were female, the aged range from 20-67, with the median age of 48. The clinical manifestations, characteristic imaging findings, pathological types, surgical approach selection, and prognosis were analyzed. Results: 36 cases of lateral skull base tumors with intracranial invasion were all accepted surgeries. 23 cases were neurogenic tumors, facial nerve tumors (n=8), neurogenic tumors in jugular foramen with unknown origin(n=6), hypoglossal schwannoma (n=3), transotic intralabyrinthine schwannoma (n=3), vestibular schwannoma involving the middle ear(n=2), vagal nerve schwannoma(n=1). Other types of tumors included meningioma (n=10) and paraganglioma (Di 1 or 2,n=3). Different pathological types of tumors had different clinical manifestations and imaging manifestations. Sixteen cases were subjected to primary resection, while, other 20 cases underwent staged operation. Among the patients with staged operation, 10 patients had completed the second stage operation, five patients were waiting for the second stage operation, the other five patient's residual intracranial tumor were significantly reduced and the space between tumor and brain tissues widened after the first stage operation, so, the following up with "wait and scan"policy was suggested. The total resection rate of tumors was related to the pathological nature, in which neurogenic tumors were 15/17, and meningiomas were 5/8. The main postoperative complications were cerebrospinal fluid leakage and infection in the operation area. There were two cases of postoperative intracranial infection, and three cases of cerebrospinal fluid leakage occurred in non staged operation cases. Conclusions: Lateral skull base tumors with intracranial invasion are rare. The most common pathological type is schwannoma, followed by meningioma and paraganglioma. For this type of tumor, if there is infection in the operation area and neck invasion is large, it is suggested to choose staged surgery, which can reduce the risk of intracranial infection and the incidence of cerebrospinal fluid leakage. Staged surgery strategy can also reduce the difficulty of second stage surgery, so the operation is much safer than non staged surgery.
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Affiliation(s)
- Y C Han
- Department of Neurotology and Lateral Skull Base Surgery, Shandong Provincial ENT Hospital, Shandong Institute of Otorhinolaryngology, Jinan 250022, China
| | - P C Sun
- Department of Neurotology and Lateral Skull Base Surgery, Shandong Provincial ENT Hospital, Shandong Institute of Otorhinolaryngology, Jinan 250022, China
| | - Z Jiang
- Department of Neurotology and Lateral Skull Base Surgery, Shandong Provincial ENT Hospital, Shandong Institute of Otorhinolaryngology, Jinan 250022, China
| | - Z M Fan
- Department of Neurotology and Lateral Skull Base Surgery, Shandong Provincial ENT Hospital, Shandong Institute of Otorhinolaryngology, Jinan 250022, China
| | - H B Wang
- Department of Neurotology and Lateral Skull Base Surgery, Shandong Provincial ENT Hospital, Shandong Institute of Otorhinolaryngology, Jinan 250022, China
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Chen Y, Dong B, Jiang Z, Cai Q, Huang L, Huang H. SuperSonic shear imaging for the differentiation between benign and malignant thyroid nodules: a meta-analysis. J Endocrinol Invest 2022; 45:1327-1339. [PMID: 35229278 DOI: 10.1007/s40618-022-01765-y] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 02/09/2022] [Indexed: 12/07/2022]
Abstract
PURPOSE To assess the diagnostic value of SuperSonic shear imaging (SSI) for the differentiation between benign and malignant thyroid nodules through meta-analysis. METHODS Online database searches were performed on PubMed, EMBASE, the Cochrane Library, and the Web of Science until 31 July 2021. The Quality Assessment of Diagnostic Accuracy Studies-2 tool was used to assess the quality of the included studies. Three measures of diagnostic test performance were used to examine the value of SSI, including the summary area under the receiver operating characteristic curve (AUROC), the summary diagnostic odds ratio (DOR), and the summary sensitivity and specificity. Heterogeneity was explored using meta-regression and subgroup analyses. RESULTS Finally, 21 studies with 3376 patients were included in this study. There were a total of 4296 thyroid nodules, in which 1806 malignant nodules and 2490 benign ones were involved. Thyroid nodules exhibited a malignancy rate of 42.0% (range 5.6-79.8%), 95.1% of which were of papillary variant. SSI showed a summary sensitivity of 74% [95% confidence interval (CI) 67-79%], specificity of 82% (95% CI 77-87%) and AUROC of 0.85 (95% CI 0.82-0.88) for the differentiation between benign and malignant thyroid nodules. The summary positive likelihood ratio (LR), negative LR, and DOR were 4.2 (95% CI 3.3-5.3), 0.32 (95% CI 0.26-0.40), and 13 (95% CI 9-18), respectively. CONCLUSIONS SSI showed high accuracy in the diagnostic differentiation between benign and malignant thyroid nodules and can be served as a noninvasive and important adjunct for thyroid nodule evaluation.
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Affiliation(s)
- Y Chen
- Department of Endocrinology, The Second Affiliated Hospital of Fujian Medical University, No. 34 North Zhongshan Road, Quanzhou, 362000, Fujian, China
| | - B Dong
- Department of Ultrasound, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China
| | - Z Jiang
- Department of Endocrinology, The Second Affiliated Hospital of Fujian Medical University, No. 34 North Zhongshan Road, Quanzhou, 362000, Fujian, China
| | - Q Cai
- Department of Endocrinology, The Second Affiliated Hospital of Fujian Medical University, No. 34 North Zhongshan Road, Quanzhou, 362000, Fujian, China
| | - L Huang
- Department of Endocrinology, The Second Affiliated Hospital of Fujian Medical University, No. 34 North Zhongshan Road, Quanzhou, 362000, Fujian, China
| | - H Huang
- Department of Endocrinology, The Second Affiliated Hospital of Fujian Medical University, No. 34 North Zhongshan Road, Quanzhou, 362000, Fujian, China.
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Guo X, Asthana P, Gurung S, Zhang S, Wong SKK, Fallah S, Chow CFW, Che S, Zhai L, Wang Z, Ge X, Jiang Z, Wu J, Zhang Y, Wu X, Xu K, Lin CY, Kwan HY, Lyu A, Zhou Z, Bian ZX, Wong HLX. Regulation of age-associated insulin resistance by MT1-MMP-mediated cleavage of insulin receptor. Nat Commun 2022; 13:3749. [PMID: 35768470 PMCID: PMC9242991 DOI: 10.1038/s41467-022-31563-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 06/22/2022] [Indexed: 12/24/2022] Open
Abstract
Insulin sensitivity progressively declines with age. Currently, the mechanism underlying age-associated insulin resistance remains unknown. Here, we identify membrane-bound matrix metalloproteinase 14 (MT1-MMP/MMP14) as a central regulator of insulin sensitivity during ageing. Ageing promotes MMP14 activation in insulin-sensitive tissues, which cleaves Insulin Receptor to suppress insulin signaling. MT1-MMP inhibition restores Insulin Receptor expression, improving insulin sensitivity in aged mice. The cleavage of Insulin Receptor by MT1-MMP also contributes to obesity-induced insulin resistance and inhibition of MT1-MMP activities normalizes metabolic dysfunctions in diabetic mouse models. Conversely, overexpression of MT1-MMP in the liver reduces the level of Insulin Receptor, impairing hepatic insulin sensitivity in young mice. The soluble Insulin Receptor and circulating MT1-MMP are positively correlated in plasma from aged human subjects and non-human primates. Our findings provide mechanistic insights into regulation of insulin sensitivity during physiological ageing and highlight MT1-MMP as a promising target for therapeutic avenue against diabetes.
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Affiliation(s)
- Xuanming Guo
- grid.221309.b0000 0004 1764 5980School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China
| | - Pallavi Asthana
- grid.221309.b0000 0004 1764 5980School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China
| | - Susma Gurung
- grid.221309.b0000 0004 1764 5980School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China
| | - Shuo Zhang
- grid.194645.b0000000121742757School of Biomedical Sciences, The University of Hong Kong, Hong Kong SAR, China
| | - Sheung Kin Ken Wong
- grid.194645.b0000000121742757School of Biomedical Sciences, The University of Hong Kong, Hong Kong SAR, China
| | - Samane Fallah
- grid.221309.b0000 0004 1764 5980School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China
| | - Chi Fung Willis Chow
- grid.221309.b0000 0004 1764 5980School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China ,grid.419537.d0000 0001 2113 4567Centre for Systems Biology Dresden, Max Planck Institute for Molecular Cell and Biology, Dresden, Germany
| | - Sijia Che
- grid.221309.b0000 0004 1764 5980School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China
| | - Lixiang Zhai
- grid.221309.b0000 0004 1764 5980School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China
| | - Zening Wang
- grid.267308.80000 0000 9206 2401Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX USA
| | - Xin Ge
- grid.267308.80000 0000 9206 2401Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX USA
| | - Zhixin Jiang
- grid.194645.b0000000121742757School of Biomedical Sciences, The University of Hong Kong, Hong Kong SAR, China
| | - Jiayan Wu
- grid.221309.b0000 0004 1764 5980School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China
| | - Yijing Zhang
- grid.221309.b0000 0004 1764 5980School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China
| | - Xiaoyu Wu
- grid.470187.dRespiratory Department, Jinhua Guangfu hospital, Jinhua, China
| | - Keyang Xu
- grid.221309.b0000 0004 1764 5980School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China
| | - Cheng Yuan Lin
- grid.221309.b0000 0004 1764 5980School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China ,grid.221309.b0000 0004 1764 5980Centre for Chinese Herbal Medicine Drug Development Limited, Hong Kong Baptist University, Hong Kong SAR, China
| | - Hiu Yee Kwan
- grid.221309.b0000 0004 1764 5980School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China
| | - Aiping Lyu
- grid.221309.b0000 0004 1764 5980School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China
| | - Zhongjun Zhou
- grid.194645.b0000000121742757School of Biomedical Sciences, The University of Hong Kong, Hong Kong SAR, China
| | - Zhao-Xiang Bian
- grid.221309.b0000 0004 1764 5980School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China ,grid.221309.b0000 0004 1764 5980Centre for Chinese Herbal Medicine Drug Development Limited, Hong Kong Baptist University, Hong Kong SAR, China
| | - Hoi Leong Xavier Wong
- grid.221309.b0000 0004 1764 5980School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China
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Qu W, Jiang Z, Liu Z, Zhu L, Chen X, Liu B, Zhao Y, Li S, Yan H, Qu X, Zang A, Sun Y, Zhou A. P-246 Real-world outcomes in metastatic colorectal patients receiving regorafenib treatment in China. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.04.336] [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: 11/01/2022] Open
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Chen K, Li C, Cornelius V, Yu D, Wang Q, Shi R, Wu Z, Su H, Yan J, Chen T, Jiang Z. Prognostic Value of Time in Blood Pressure Target Range Among Patients With Heart Failure. JACC Heart Fail 2022; 10:369-379. [PMID: 35654521 DOI: 10.1016/j.jchf.2022.01.010] [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] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 01/12/2022] [Accepted: 01/13/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Blood pressure (BP) is a continuous and dynamic measure. However, standard BP control metrics may not reflect the variability in BP over time. OBJECTIVES This study assessed the prognostic value of time in BP target range among hypertensive patients with heart failure (HF). METHODS The authors performed a post hoc analysis of data from the TOPCAT (Treatment of Preserved Cardiac Function HF with an Aldosterone Antagonist) trial and the BEST (Beta-Blocker Evaluation of Survival Trial). Time in target range (TTR) for each patient was calculated using linear interpolation across the study period with the target range of systolic BP between 120 and 130 mm Hg. RESULTS A total of 4,789 hypertensive patients (n = 1,654 from BEST and n = 3,135 from TOPCAT) were included. The cumulative incidences of primary endpoint (ie, cardiovascular death or HF hospitalization) were highest among the top quartile of TTR with a dose-dependent manner across quartiles (Ptrend <0.005). The top quartile of TTR was significantly associated with a lower risk of primary outcome using adjusted Cox regression model (HR: 0.71; 95% CI: 0.60-0.82), cardiovascular mortality (HR: 0.68; 95% CI: 0.55-0.84), HF hospitalization (HR: 0.70; 95% CI: 0.58-0.85), all-cause mortality (HR: 0.69; 95% CI: 0.58-0.83), and any hospitalization (HR: 0.76; 95% CI: 0.67-0.85). Further analyses using restricted cubic spline indicated a linear relationship between TTR and primary outcome. Similar patterns were observed in the individual trial. Sensitivity analyses generated consistent results while redefining target range as 110 to 130 mm Hg for systolic BP or 70 to 80 mm Hg for diastolic BP. CONCLUSIONS TTR could independently predict major adverse cardiovascular events in hypertensive patients with HF.
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Affiliation(s)
- Kangyu Chen
- Department of Cardiology, Department of Cardiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Chao Li
- Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University Health Science Centre, Xi'an, China
| | - Victoria Cornelius
- Imperial Clinical Trials Unit, School of Public Health, Imperial College London, London, United Kingdom
| | - Dahai Yu
- Primary Care Centre Versus Arthritis, School of Medicine, Keele University, Keele, United Kingdom
| | - Qi Wang
- Department of Cardiology, Department of Cardiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Rui Shi
- Heart Rhythm Centre, The Royal Brompton and Harefield National Health Service Foundation Trust, National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Zhenqiang Wu
- Department of Geriatric Medicine, The University of Auckland, Auckland, New Zealand
| | - Hao Su
- Department of Cardiology, Department of Cardiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Ji Yan
- Department of Cardiology, Department of Cardiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
| | - Tao Chen
- Department of Public Health, Policy & Systems, Institute of Population Health, Whelan Building, Quadrangle, The University of Liverpool, Liverpool, United Kingdom.
| | - Zhixin Jiang
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, China.
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Chen T, Shao F, Chen K, Wang Y, Wu Z, Wang Y, Gao Y, Cornelius V, Li C, Jiang Z. Time to Clinical Benefit of Intensive Blood Pressure Lowering in Patients 60 Years and Older With Hypertension: A Secondary Analysis of Randomized Clinical Trials. JAMA Intern Med 2022; 182:660-667. [PMID: 35532917 PMCID: PMC9086939 DOI: 10.1001/jamainternmed.2022.1657] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 03/26/2022] [Indexed: 11/14/2022]
Abstract
Importance Recent guidelines recommend a systolic blood pressure (BP) goal of less than 150 mm Hg or even 130 mm Hg for adults aged 60 years or older. However, harms from intensive BP treatments occur immediately (eg, syncope, fall), and benefits for cardiovascular event reduction emerge over time. Therefore, harms with low chance of benefit need to be clearer, particularly for those with limited life expectancy. Objective To estimate the time needed to potentially derive clinical benefit from intensive BP treatment in patients 60 years and older. Design, Setting, and Participants This secondary analysis included individual patient data from published randomized clinical trials with 27 414 patients 60 years or older with hypertension. Patient-level survival data were reconstructed when the original data were not available. Published trials were identified by searching PubMed until October 15, 2021. Exposures Intensive BP lowering vs standard BP lowering with the treat-to-target design. Main Outcomes and Measures Major adverse cardiovascular event (MACE) defined by each trial, which was broadly similar with all trials including myocardial infarction, stroke, and cardiovascular mortality. Results Six trials (original data from 2 trials and reconstructed data from 4 trials) with 27 414 participants (mean age, 70 years; 56.3% were women) were included in the analysis. Intensive BP treatment with a systolic BP target below 140 mm Hg was significantly associated with a 21% reduction in MACE (hazard ratio, 0.79; 95% CI, 0.71-0.88; P < .001). On average, 9.1 (95% CI, 4.0-20.6) months were needed to prevent 1 MACE per 500 patients with the intensive BP treatment (absolute risk reduction [ARR], 0.002). Likewise, 19.1 (95% CI, 10.9-34.2) and 34.4 (95% CI, 22.7-59.8) months were estimated to avoid 1 MACE per 200 (ARR, 0.005) and 100 (ARR, 0.01) patients, respectively. Conclusions and Relevance In this analysis, findings suggest that for patients 60 years and older with hypertension, intensive BP treatment may be appropriate for some adults with a life expectancy of greater than 3 years but may not be suitable for those with less than 1 year.
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Affiliation(s)
- Tao Chen
- Department of Public Health, Policy and Systems, Institute of Population Health, The University of Liverpool, Liverpool, United Kingdom
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Fang Shao
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Jiangsu, Nanjing, China
| | - Kangyu Chen
- Department of Cardiology, The First Affiliated Hospital of USTC, Hefei, China
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Yang Wang
- Medical Research and Biometrics Center, Fuwai Hospital, National Center for Cardiovascular Disease, Peking Union Medical College and Chinese Academy of Medical Sciences, Mentougou District, Beijing, China
| | - Zhenqiang Wu
- Department of Geriatric Medicine, The University of Auckland, Auckland, New Zealand
| | - Yongjuan Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an, China
| | - Yanpei Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an, China
| | - Victoria Cornelius
- Imperial Clinical Trials Unit, School of Public Health, Imperial College London, London, United Kingdom
| | - Chao Li
- Department of Epidemiology and Health Statistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an, China
| | - Zhixin Jiang
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, China
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