Licorice flavonoid ameliorates ethanol-induced gastric ulcer in rats by suppressing apoptosis via PI3K/AKT signaling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Licorice is the dry roots and rhizomes of Glycyrrhiza uralensis Fisch., Glycyrrhiza glabra L. and Glycyrrhiza inflata Bat., which was first recorded in Shengnong's herbal classic. Licorice flavonoid (LF) is the main compound isolated from licorice with an indispensable action in treating gastric ulcer (GU). However, the underlying mechanisms need to be further explored.

AIM OF THE STUDY

This study aimed to investigate and further elucidate the mechanisms of LF against ethanol-induced GU using an integrated approach.

MATERIALS AND METHODS

The anti-GU effects of LF were evaluated in an ethanol-induced gastric injury rat model. Then, the metabolomics approach was applied to explore the specific metabolites and metabolic pathways. Next, the network pharmacology combined with metabolomics strategy was employed to predict the targets and pathways of LF for GU. Finally, these predictions were validated by molecular docking, RT-qPCR, and western blotting.

RESULTS

LF had a positive impact on gastric injury and regulated the expression of GU-related factors. Upon serum metabolomics analysis, 25 metabolic biomarkers of LF in GU treatment were identified, which were primarily involved in amino acid metabolism, carbohydrate metabolism, and other related processes. Subsequently, a "components-targets-metabolites" network was constructed, revealing six key targets (HSP90AA1, AKT1, MAPK1, EGFR, ESR1, PIK3CA) that may be associated with GU treatment. More importantly, KEGG analysis highlighted the importance of the PI3K/AKT pathway including key targets, as a critical route through which LF exerted its anti-GU effects. Molecular docking analyses confirmed that the core components of LF exhibited a strong affinity for key targets. Furthermore, RT-qPCR and western blotting results indicated that LF could reverse the expression of these targets, activate the PI3K/AKT pathway, and ultimately reduce apoptosis.

CONCLUSION

LF exerted a gastroprotective effect against gastric ulcer induced by ethanol, and the therapeutic mechanism may involve improving metabolism and suppressing apoptosis through the PI3K-AKT pathway.

Transcriptome sequencing analysis reveals miR-30c-5p promotes ferroptosis in cervical cancer and inhibits growth and metastasis of cervical cancer xenografts by targeting the METTL3/KRAS axis

Cervical cancer is the most common malignant tumor in the female reproductive system worldwide, and its molecular mechanisms remain complex and poorly understood. Various techniques, including transcriptome sequencing, RT-qPCR, ELISA, immunofluorescence, Western blot, CCK-8 assay, Transwell assay, and xenograft models, were employed to investigate gene/miRNA expression, cellular proliferation, migration, and the interactions between miR-30c-5p, METTL3, and KRAS. Our transcriptome sequencing results demonstrated a significant downregulation of miR-30c-5p in cervical cancer cells. Further investigations using RNA pull-down, dual-luciferase reporter assay, Me-RIP, and PAR-CLIP confirmed METTL3 as one of the downstream targets of miR-30c-5p, while KRAS was identified as an iron-death suppressor gene susceptible to m6A modification. Notably, our Me-RIP analysis demonstrated the involvement of METTL3 in m6A modification of KRAS. In vitro experiments revealed that miR-30c-5p facilitated ferroptosis in cervical cancer cells by inhibiting the METTL3/KRAS axis, thus suppressing proliferation and migration. Additionally, in vivo studies demonstrated that miR-30c-5p repressed the growth and metastasis of cervical cancer xenografts through the inhibition of the METTL3/KRAS axis. Overall, this study highlights the critical role of miR-30c-5p in modulating cervical cancer progression by targeting the METTL3/KRAS axis, providing new insights into the molecular mechanisms underlying cervical cancer growth and metastasis.

A validation of register-derived diagnoses of interstitial lung disease in patients with inflammatory arthritis: data from the NOR-DMARD study

OBJECTIVE

There is a lack of knowledge concerning the validity of the interstitial lung disease (ILD) diagnoses used in epidemiological studies on rheumatic diseases. This paper seeks to verify register-derived ILD diagnoses using chest computed tomography (CT) and medical records as a gold standard.

METHOD

The Norwegian Anti-Rheumatic Drug Register (NOR-DMARD) is a multicentre prospective observational study of patients with inflammatory arthritis who start treatment with disease-modifying anti-rheumatic drugs. NOR-DMARD is linked to the Norwegian Patient Registry (NPR) and Cause of Death Registry. We searched registers for ILD coded by ICD-10 J84 or J99 among patients with rheumatoid arthritis, psoriatic arthritis, or spondyloarthritis. We extracted chest CT reports and medical records from participating hospitals. Two expert thoracic radiologists scored examinations to confirm the ILD diagnosis. We also searched medical records to find justifications for the diagnosis following multidisciplinary evaluations. We calculated the positive predictive values (PPVs) for ILD across subsets.

RESULTS

We identified 71 cases with an ILD diagnosis. CT examinations were available in 65/71 patients (91.5%), of whom ILD was confirmed on CT in 29/65 (44.6%). In a further 10 patients, medical records confirmed the diagnosis, giving a total of 39/71 verified cases. The PPV of a register-derived ILD diagnosis was thus 54.9%. In a subset of patients who had received an ILD code at two or more time-points and had a CT scan taken within a relevant period, the PPV was 72.2%.

CONCLUSION

The validity of register-based diagnoses of ILD must be carefully considered in epidemiological studies.

The mystery of methylmercury-perturbed calcium homeostasis: AMPK-DRP1-dependent mitochondrial fission initiates ER-mitochondria contact formation

Methylmercury (MeHg), as a global environmental pollutant, is of concern globally due to its neurodevelopmental toxicity. Mitochondria-associated membranes (MAMs) are highly dynamic sites of endoplasmic reticulum (ER)-haemocyte contact. MAMs are closely associated with the pathophysiology of neurological disorders due to their role in the transfer of calcium ions (Ca2+) between mitochondria and the ER. However, the molecular mechanisms that control these interactions in MeHg-induced neurotoxicity have not yet been characterized. In the current study, MeHg caused increases in the levels of both cytosolic and mitochondrial Ca2+ in PC12 cells and promoted MAMs formation in both in vivo and in vitro experiments. Of note, MeHg perturbed mitochondrial dynamics, promoting a shift toward a fission phenotype, and this was supported by the dysregulation of fission regulators. Interestingly, the MeHg-induced promotion of MAMs formation and increase in Ca2+ levels were effectively attenuated by the inhibition of mitochondrial fission using Mdivi-1, a DRP1 inhibitor. Furthermore, MeHg triggered the AMPK pathway, and most of the aforementioned changes were significantly rescued by Compound C. Mechanistic investigations revealed a reciprocal relationship between AMPK- and Ca2+-mediated mitochondrial fission. The specific inhibitor of Ca2+ uniporter, ruthenium-red (RuR), effectively abolished the feedback regulation of mitochondrial dynamics and MAMs formation mediated by AMPK in response to MeHg-induced Ca2+ overload. This study reveals a novel role of AMPK-DRP1-mediated mitochondrial fragmentation in the coupling of ER-mitochondrial calcium microdomains in MeHg-induced neurotoxicity. The findings provide valuable insights for the development of strategies to regulate mitochondrial imbalances in neurological diseases.

Claudin 18.2 expression in digestive neuroendocrine neoplasms: a clinicopathological study

BACKGROUND

Claudin 18.2-targeted therapy has shown significant efficacy in treating claudin 18.2-positive cancers. However, limited systematic studies have investigated characteristics of claudin 18.2 expression in neuroendocrine neoplasms (NENs).

METHODS

Data and specimens from 403 cases of digestive NENs were retrospectively collected, and claudin 18.2 expression was detected using immunochemical staining.

RESULTS

Claudin 18.2 was positive in 19.6% (79/403) of the digestive NENs. The highest positive rate of claudin 18.2 was observed in gastric NENs (72/259, 27.8%), accounting for 91.1% (72/79) of all positive cases. The positivity rate was significantly higher in gastric NENs compared to pancreatic (2/78, 2.6%) or colorectal NENs (2/38, 5.3%; p < 0.05). For digestive NENs, claudin 18.2 positivity was significantly higher in neuroendocrine carcinomas (NECs) (37/144, 25.7%) than in neuroendocrine tumours (NETs; 14/160, 8.8%; p < 0.001), but no significant difference was found between gastric NECs (59/213, 27.7%) and gastric NETs (13/46, 28.3%; p > 0.05). The positivity was significantly higher in large-cell NECs (LCNECs; 28/79, 35.4%) and MiNEN (mixed neuroendocrine-non- neuroendocrine neoplasms)-LCNECs (23/66, 34.8%) compared to small-cell NECs (SCNECs; 9/65, 13.8%) and MiNEN-SCNECs (5/33, 15.2%; p < 0.05). Claudin 18.2 expression was more prevalent in gastric NENs than in pancreatic (12.5 ×; p = 0.001) and colorectal NENs (5.9 ×; p = 0.021). Claudin 18.2 staining was a useful method for identify the gastric origins of NETs, with a sensitivity of 28.3% and a specificity of 99.1%.

CONCLUSION

The expression characteristics of claudin 18.2 in NENs were characterized, which may provide a clinicopathological reference for targeted therapies in patients with NENs.

The role of iron-rich hydrosaline liquids in the formation of Kiruna-type iron oxide-apatite deposits

Kiruna-type iron oxide-apatite (IOA) deposits, an important source of iron, show close associations with andesitic subvolcanic intrusions. However, the processes of ore formation and the mechanism controlling iron concentration remain uncertain. Here, we report the widespread presence of high-temperature (>800°C) water-poor multisolid hydrosaline liquid inclusions in pre- and syn-ore minerals from IOA deposits of eastern China. These inclusions consistently homogenize to a liquid phase by vapor disappearance and mostly contain 3 to 10 wt % Fe, signifying a substantial capacity for iron transportation by such hydrosaline liquids. We propose that the hydrosaline liquids were likely immiscible from the dioritic magmas with high Cl/H2O in subvolcanic settings. Subsequent reaction with host rocks and/or decompression and cooling of the hydrosaline liquids is deemed responsible for the simultaneous formation of high-temperature alteration and magnetite ores, thereby providing important insights into the distinctive characteristics of IOA deposits in shallow magmatic-hydrothermal systems.

A pulmonary artery was embolized in a patient with an occluded pulmonary vein to manage massive hemoptysis

BACKGROUND

Stenosis and obliteration of the pulmonary vein can be developed by multiple diseases and might cause hemoptysis. Traditional therapy including surgical procedure and conservative treatments might be inappropriate choices to manage massive hemoptysis.

CASE PRESENTATION

A 64-year-old man, diagnosed with advanced stage IVA lung squamous cell carcinoma, presented with dyspnea and recurrent, massive hemoptysis. An initial contrast-enhanced computed tomography revealed a giant tumor in the left lung hilus and occlusion of the left superior pulmonary vein. Despite immediate selective bronchial artery embolization and simultaneous embolization of an anomalous branch of the internal thoracic artery, the massive hemoptysis continued. Subsequently, embolization of the left superior pulmonary artery was performed, achieving functional pulmonary lobectomy, which successfully treated the hemoptysis without relapse during a six-month follow-up. The patient continues to undergo cancer therapy and remains stable.

CONCLUSIONS

This case successfully managed massive hemoptysis associated with lung cancer invasion into the pulmonary vein through functional pulmonary lobectomy via embolization of the corresponding pulmonary artery.

Efficacy and Safety of Disitamab Vedotin in Patients With Human Epidermal Growth Factor Receptor 2-Positive Locally Advanced or Metastatic Urothelial Carcinoma: A Combined Analysis of Two Phase II Clinical Trials

PURPOSE

To evaluate the efficacy and safety of disitamab vedotin (DV, RC48-ADC), a novel humanized anti-human epidermal growth factor receptor 2 (HER2) antibody conjugated with monomethyl auristatin E, in patients with HER2-positive locally advanced or metastatic urothelial carcinoma (UC) refractory to standard or regular therapies.

PATIENTS AND METHODS

The data analyzed and reported are from two phase II, open-label, multicenter, single-arm studies (RC48-C005 and RC48-C009) in patients with HER2-positive (immunohistochemistry 3+ or 2+) locally advanced or metastatic UC who have progressed on at least one previous line of systemic chemotherapy. Patients received DV treatment (2 mg/kg IV infusion, once every 2 weeks). The primary end point was objective response rate (ORR) assessed by a blinded independent review committee (BIRC). Progression-free survival (PFS), overall survival (OS), and safety were also assessed.

RESULTS

One hundred and seven patients were enrolled in total. The overall confirmed ORR by BIRC was 50.5% (95% CI, 40.6 to 60.3). Consistent results were observed in prespecified subgroups including patients with liver metastasis and patients previously treated with anti-PD-1/L1 therapies. By the cutoff date of May 10, 2022, the median duration of response was 7.3 months (95% CI, 5.7 to 10.8). The median PFS and OS were 5.9 months (95% CI, 4.3 to 7.2) and 14.2 months (95% CI, 9.7 to 18.8), respectively. The most common treatment-related adverse events (TRAEs) were peripheral sensory neuropathy (68.2%), leukopenia (50.5%), AST increased (42.1%), and neutropenia (42.1%). Fifty-eight (54.2%) patients experienced grade ≥3 TRAEs, including peripheral sensory neuropathy (18.7%) and neutropenia (12.1%).

CONCLUSION

DV demonstrated a promising efficacy with a manageable safety profile in patients with HER2-positive locally advanced or metastatic UC who had progressed on at least one line of systemic chemotherapy.

Progress of Angiogenesis Signal Pathway and Antiangiogenic Drugs in Nasopharyngeal Carcinoma

Nasopharyngeal cancer is a rare cancer with unique ethnic and geographic distribution. Since nasopharyngeal cancer often originates from the pharyngeal crypt, early symptoms are not obvious. They are difficult to detect in time, and the disease is usually diagnosed and treated only when it has progressed to an advanced-stage. Since angiogenesis is essential for the growth and invasion of solid tumors, antiangiogenic therapy has become a common treatment strategy for many solid tumors, and it has also achieved remarkable results in the treatment of nasopharyngeal carcinoma, which is prone to recurrence and distant metastasis. In this paper, we review the latest research progress of antiangiogenic drugs for nasopharyngeal carcinoma and their antiangiogenic mechanism of action and further propose some promising antiangiogenic therapeutic targets.

[Epidemiological investigation of iron deficiency among preschool children in 10 provinces, autonomous regions, or municipalities in China]

Objective: To understand the current status of anemia, iron deficiency, and iron-deficiency anemia among preschool children in China. Methods: A cross-sectional study was conducted with a multi-stage stratified sampling method to select 150 streets or townships from 10 Chinese provinces, autonomous regions, or municipalities (East: Jiangsu, Zhejiang, Shandong, and Hainan; Central: Henan; West: Chongqing, Shaanxi, Guizhou, and Xinjiang; Northeast: Liaoning). From May 2022 to April 2023, a total of 21 470 children, including community-based children aged 0.5 to<3.0 years receiving child health care and kindergarten-based children aged 3.0 to<7.0 years, were surveyed. They were divided into 3 age groups: infants (0.5 to<1.0 year), toddlers (1.0 to<3.0 years), and preschoolers (3.0 to<7.0 years). Basic information such as sex and date of birth of the children was collected, and peripheral blood samples were obtained for routine blood tests and serum ferritin measurement. The prevalence rates of anemia, iron deficiency, and iron-deficiency anemia were analyzed, and the prevalence rate differences were compared among different ages, sex, urban and rural areas, and regions using the chi-square test. Results: A total of 21 460 valid responses were collected, including 10 780 boys (50.2%). The number of infants, toddlers, and preschoolers were 2 645 (12.3%), 6 244 (29.1%), and 12 571 (58.6%), respectively. The hemoglobin level was (126.7±14.8) g/L, and the serum ferritin level was 32.3 (18.5, 50.1) μg/L. The overall rates of anemia, iron deficiency, and iron-deficiency anemia were 10.4% (2 230/21 460), 28.3% (6 070/21 460), and 3.9% (845/21 460), respectively. The prevalence rate of anemia was higher for boys than for girls (10.9% (1 173/10 780) vs. 9.9% (1 057/10 680), χ2=5.58, P=0.018), with statistically significant differences in the rates for infants, toddlers and preschoolers (18.0% (475/2 645), 10.6% (662/6 244), and 8.7% (1 093/12 571), respectively, χ2=201.81, P<0.01), and the rate was significantly higher for children in rural than that in urban area (11.8% (1 516/12 883) vs. 8.3% (714/8 577), χ2=65.54, P<0.01), with statistically significant differences in the rates by region (χ2=126.60, P<0.01), with the highest rate of 15.8% (343/2 173) for children in Central region, and the lowest rate of 5.3% (108/2 053) in Northeastern region. The prevalence rates of iron deficiency were 33.8% (895/2 645), 32.2% (2 011/6 244), and 25.2% (3 164/12 571) in infants, toddlers, and preschoolers, respectively, and 30.0% (3 229/10 780) in boys vs. 26.6% (2 841/10 680) in girls, 21.7% (1 913/8 821), 40.0% (870/2 173), 27.1% (2 283/8 413), 48.9% (1 004/2 053) in Eastern, Central, Western, and Northeastern regions, respectively, and each between-group showed a significant statistical difference (χ2=147.71, 29.73, 773.02, all P<0.01). The prevalence rate of iron-deficiency anemia showed a significant statistical difference between urban and rural areas, 2.9% (251/8 577) vs. 4.6% (594/12 883) (χ2=38.62, P<0.01), while the difference in iron deficiency prevalence was not significant (χ2=0.51, P=0.476). Conclusions: There has been a notable improvement in iron deficiency and iron-deficiency anemia among preschool children in China, but the situation remains concerning. Particular attention should be paid to the prevention and control of iron deficiency and iron-deficiency anemia, especially among infants and children in the Central, Western, and Northeastern regions of China.

Characterisation of the mitochondrial genome and phylogenetic analysis of Toxocara apodemi (Nematoda: Ascarididae)

We first sequenced and characterised the complete mitochondrial genome of Toxocara apodeme, then studied the evolutionary relationship of the species within Toxocaridae. The complete mitochondrial genome was amplified using PCR with 14 specific primers. The mitogenome length was 14303 bp in size, including 12 PCGs (encoding 3,423 amino acids), 22 tRNAs, 2 rRNAs, and 2 NCRs, with 68.38% A+T contents. The mt genomes of T. apodemi had relatively compact structures with 11 intergenic spacers and 5 overlaps. Comparative analyses of the nucleotide sequences of complete mt genomes showed that T. apodemi had higher identities with T. canis than other congeners. A sliding window analysis of 12 PCGs among 5 Toxocara species indicated that nad4 had the highest sequence divergence, and cox1 was the least variable gene. Relative synonymous codon usage showed that UUG, ACU, CCU, CGU, and UCU most frequently occurred in the complete genomes of T. apodemi. The Ka/Ks ratio showed that all Toxocara mt genes were subject to purification selection. The largest genetic distance between T. apodemi and the other 4 congeneric species was found in nad2, and the smallest was found in cox2. Phylogenetic analyses based on the concatenated amino acid sequences of 12 PCGs demonstrated that T. apodemi formed a distinct branch and was always a sister taxon to other congeneric species. The present study determined the complete mt genome sequences of T. apodemi, which provide novel genetic markers for further studies of the taxonomy, population genetics, and systematics of the Toxocaridae nematodes.

Copper Ion-Inspired Dual Controllable Drug Release Hydrogels for Wound Management: Driven by Hydrogen Bonds

Bacterial infections and inflammation progression yield huge trouble for the management of serious skin wounds and burns. However, some hydrogel dressing exhibit poor wound-healing capabilities. Additionally, little information is given on the molecular theory of hydrogel gelation mechanisms and drug release performance from drug-polymer network in the water environment. Herein, cationic guar gum (CG) is first mixed with dipotassium glycyrrhizinate (DG), and then crosslinked Cu2+ to strengthen the mechanical strength followed by encapsulating mussel adhesive protein (MAP) as composite dressings. Intriguingly, CG-Cu2+ 0.5-DG10 possessed proper rheological properties and mechanical strength predominantly driven by strong CG-H2O-Cu2+ and Cu2+-CG hydrogen bonding interaction. Weak DG-CG hydrogen bonding only controlled DG release in the initial 4 h, while strong hydrogen bonding is the main force regulating the sustained release of Cu2+ within 48 h. The incorporation of MAP further loosened the tight crosslinking of CG-Cu2+ 0.5-DG10. The screened CG-Cu2+ 0.5-DG10/MAP possessed excellent self-healing, injectability, antibacterial, anti-inflammatory, cell proliferation-promotion activities with high biocompatibility. Therefore, CG-Cu2+ 0.5-DG10/MAP hydrogel expedited wound closure on S. aureus-infected full-thickness skin wound model and lowered necrosis progression to the unburned interspaces on a rat burn model. The results highlight the promising translational potential of Cu2+-inspired hydrogels for the management of burns and infected wounds.

Study of the f_{0}(980) and f_{0}(500) Scalar Mesons through the Decay D_{s}^{+}→π^{+}π^{-}e^{+}ν_{e}

Using e^{+}e^{-} collision data corresponding to an integrated luminosity of 7.33  fb^{-1} recorded by the BESIII detector at center-of-mass energies between 4.128 and 4.226 GeV, we present an analysis of the decay D_{s}^{+}→π^{+}π^{-}e^{+}ν_{e}, where the D_{s}^{+} is produced via the process e^{+}e^{-}→D_{s}^{*±}D_{s}^{∓}. We observe the f_{0}(980) in the π^{+}π^{-} system and the branching fraction of the decay D_{s}^{+}→f_{0}(980)e^{+}ν_{e} with f_{0}(980)→π^{+}π^{-} measured to be (1.72±0.13_{stat}±0.10_{syst})×10^{-3}, where the uncertainties are statistical and systematic, respectively. The dynamics of the D_{s}^{+}→f_{0}(980)e^{+}ν_{e} decay are studied with the simple pole parametrization of the hadronic form factor and the Flatté formula describing the f_{0}(980) in the differential decay rate, and the product of the form factor f_{+}^{f_{0}}(0) and the c→s Cabibbo-Kobayashi-Maskawa matrix element |V_{cs}| is determined for the first time to be f_{+}^{f_{0}}(0)|V_{cs}|=0.504±0.017_{stat}±0.035_{syst}. Furthermore, the decay D_{s}^{+}→f_{0}(500)e^{+}ν_{e} is searched for the first time but no signal is found. The upper limit on the branching fraction of D_{s}^{+}→f_{0}(500)e^{+}ν_{e}, f_{0}(500)→π^{+}π^{-} decay is set to be 3.3×10^{-4} at 90% confidence level.

Prognosis of immune checkpoint inhibitor-induced myasthenia gravis: a single center experience and systematic review

Background

Immune checkpoint inhibitors (ICI)-induced myasthenia gravis (MG) is an uncommon but potentially fatal neurotoxicity. We aim to help physicians familiarize themselves with the clinical characteristics of ICI-induced MG, facilitating early diagnosis and prompt intervention.

Methods

We searched the Chinese People's Liberation Army General Hospital medical record system from January 2017 to August 2023 for patients diagnosed with ICI-induced MG. We systematically reviewed the literature until August 2023 to identify all similar patients. We collected clinical information on these patients.

Results

110 patients were identified, 9 from our institution and 101 from case reports. In our institution, Median age was 66 years (range: 49-79 years). 6 were males. The most common was lung cancer (n = 4). All patients had no previous history of MG and received PD-1 or PD-L1 inhibitors. The median time from ICI initiation to first MG symptoms was 4 weeks (range: 2-15 weeks). ICIs were discontinued in all patients. Most patients initially received high-dose corticosteroids, and their symptoms improved. Some patients are discharged with corticosteroids maintenance therapy. In addition, 55 patients (50%) with concomitant myositis and/or myocarditis and MG-induced mortality were more common in the myositis and/or myocarditis group (10.9% vs. 34.5%, p = 0.016). Overlap of myositis with MG (OR = 3.148, p = 0.009) and anti-AChR antibody positivity (OR = 3.364, p = 0.005) were both significantly associated with poor outcomes.

Conclusion

Our study reveals the prognosis of ICI-induced MG and suggests that myositis and/or myocarditis are severe comorbidities of ICI-induced MG, emphasizing the importance of early diagnosis and clinical intervention.

The functional role of circRNA CHRC through miR-431-5p/KLF15 signaling axis in the progression of heart failure

Pathological myocardial hypertrophy is a common early clinical manifestation of heart failure, with non-coding RNAs exerting regulatory influence. However, the molecular function of circular RNAs (circRNAs) in the progression from cardiac hypertrophy to heart failure remains unclear. To uncover functional circRNAs and identify the core circRNA signaling pathway in heart failure, we construct a global triple network (microRNA, circRNA, and mRNA) based on the competitive endogenous RNA (ceRNA) theory. We observe that circRNA CHRC, within the ceRNA network, is down-regulated in both transverse aortic constriction (TAC) mice and Ang-II-treated primary mouse cardiomyocytes. Silencing circRNA CHRC increases cross-sectional cell area, atrial natriuretic peptide, and β-myosin heavy chain levels in primary mouse cardiomyocytes. Further screening reveals that circRNA CHRC targets the miR-431-5p/KLF15 axis implicated in heart failure progression in vivo and in vitro. Immunoprecipitation with anti-Ago2-RNA confirms the interaction between circRNA CHRC and miR-431-5p, while miR-431-5p mimics reverse Klf15 activation caused by circRNA CHRC over-expression. In summary, circRNA CHRC attenuates cardiac hypertrophy via sponging miR-431-5p to maintain the normal level of Klf15 expression.

The relationship between alcohol consumption and chronic kidney disease in patients with nonalcoholic fatty liver disease

Objective: To examine the impact of moderate alcohol consumption on the progression of chronic kidney disease (CKD) in individuals diagnosed with non-alcoholic fatty liver disease (NAFLD), as NAFLD has been identified as an autonomous risk factor for CKD and previous research has demonstrated a reduction in overall mortality in NAFLD patients who consume alcohol in moderation.Methods: This study included participants from ten consecutive rounds of the National Health and Nutrition Examination Survey (NHANES:1998-2018). Multivariate logistic regression models were employed to assess the impact of moderate alcohol consumption on chronic kidney disease (CKD) in both male and female populations. Subgroup analysis was conducted by categorizing patients with non-alcoholic fatty liver disease (NAFLD) based on the Fibrosis-4 (FIB-4) index.Results: 17040 participants were eligible to be included in the study. The logistic regression analysis model showed that moderate alcohol consumption was a protective factor for CKD in male NAFLD patients, with an unadjusted OR: 0.37 (0.22,0.65), and p < 0.001. After further adjustment, the association persisted. However, the association was not significant in female patients with NAFLD. Among men with low risk of liver fibrosis group, moderate alcohol consumption remained a protective factor for CKD (OR = 0.32, 95% CI 0.12-0.84, p = 0.02), but the association was not significant in the high risk of liver fibrosis group. In female patients, both moderate alcohol consumption and excessive alcohol consumption were not significantly associated with CKD in either the low-risk group or the high-risk group.Conclusion: Moderate alcohol consumption is associated with a lower prevalence of CKD in men with NAFLD.

Updated overall survival and circulating tumor DNA analysis of ensartinib for crizotinib-refractory ALK-positive NSCLC from a phase II study

BACKGROUND

The initial phase II stuty (NCT03215693) demonstrated that ensartinib has shown clinical activity in patients with advanced crizotinib-refractory, anaplastic lymphoma kinase (ALK)-positive non-small cell lung cancer (NSCLC). Herein, we reported the updated data on overall survival (OS) and molecular profiling from the initial phase II study.

METHODS

In this study, 180 patients received 225 mg of ensartinib orally once daily until disease progression, death or withdrawal. OS was estimated by Kaplan‒Meier methods with two-sided 95% confidence intervals (CIs). Next-generation sequencing was employed to explore prognostic biomarkers based on plasma samples collected at baseline and after initiating ensartinib. Circulating tumor DNA (ctDNA) was detected to dynamically monitor the genomic alternations during treatment and indicate the existence of molecular residual disease, facilitating improvement of clinical management.

RESULTS

At the data cut-off date (August 31, 2022), with a median follow-up time of 53.2 months, 97 of 180 (53.9%) patients had died. The median OS was 42.8 months (95% CI: 29.3-53.2 months). A total of 333 plasma samples from 168 patients were included for ctDNA analysis. An inferior OS correlated significantly with baseline ALK or tumor protein 53 (TP53) mutation. In addition, patients with concurrent TP53 mutations had shorter OS than those without concurrent TP53 mutations. High ctDNA levels evaluated by variant allele frequency (VAF) and haploid genome equivalents per milliliter of plasma (hGE/mL) at baseline were associated with poor OS. Additionally, patients with ctDNA clearance at 6 weeks and slow ascent growth had dramatically longer OS than those with ctDNA residual and fast ascent growth, respectively. Furthermore, patients who had a lower tumor burden, as evaluated by the diameter of target lesions, had a longer OS. Multivariate Cox regression analysis further uncovered the independent prognostic values of bone metastases, higher hGE, and elevated ALK mutation abundance at 6 weeks.

CONCLUSION

Ensartinib led to a favorable OS in patients with advanced, crizotinib-resistant, and ALK-positive NSCLC. Quantification of ctDNA levels also provided valuable prognostic information for risk stratification.

Quality change in Bombay duck (Harpadon nehereus) surimi during frozen storage using different freezing methods

To inhibit the quality deterioration caused by the frozen storage of surimi products, this work investigated the effect of freezing methods, including raw-freezing-setting-heating, raw-setting-freezing-heating, and raw-setting-heating-freezing, on quality changes in surimi gel. The moisture loss, physical-chemical properties, and protein structure conformation of surimi gel derived from Bombay duck (BD) were assessed following frozen storage periods of 20, 40, and 60 days. The findings suggest that the raw-setting-heating-freezing method yielded optimal surimi gel properties with extended frozen storage time. Employing this approach led to a reduction in thawing loss, while cooking loss remained constant. After 60 days of frozen storage, the hardness exhibited an initial increase followed by a subsequent decrease, and water-holding capacity increased to 68.2%. Notably, the impact on surimi gel during the late stage of frozen storage was more pronounced throughout the formation of ice crystals, resulting in decreased disulfide bond content. Scanning hematoxylin-eosin (HE) staining slices of samples following thawing and heating demonstrated that the raw-setting-heating-freezing method could better resist the effect of ice crystals in frozen storage period on surimi tissue, while the gel on setting process could delay the erosion imposed on by ice crystals during frozen storage. This study provides a scientific foundation for the industrialization on frozen BD surimi products.

TRIM34 suppresses non-small-cell lung carcinoma via inducing mTORC1-dependent glucose utilization and promoting cellular death

Non-small-cell lung carcinoma (NSCLC) is a type of pernicious tumor, which owns high morbidity and mortality. TRIM34 has a stimulative role in cell apoptosis and a suppressive role in inflammation. However, no studies were focused on the regulatory impacts of TRIM34 in NSCLC. This study aimed to examine the underlying regulatory effects of TRIM34 in NSCLC. TRIM34 exhibited lower expression in NSCLC. TRIM34 facilitated mitochondrial damage and apoptosis in NSCLC. TRIM34 induced the increased activity of mTORC1 and accelerated glycolysis in NSCLC. Enhanced mitochondrial damage induced by TRIM34 overexpression was reversed after rapamycin (mTORC1 inhibitor) treatment in NSCLC. The strengthened cell apoptosis stimulated by TRIM34 overexpression was rescued after rapamycin treatment. TRIM34 activated mTORC1 to suppress NSCLC progression in vivo. TRIM34 suppressed NSCLC via inducing mTORC1-dependent glucose utilization and promoting cellular death. The results suggest that TRIM34 can be a useful therapeutic biomarker for NSCLC patients.

Menopausal age and cardiovascular disease risk in American women: evidence from the National Health and Nutrition Examination Survey

OBJECTIVE

Cardiovascular disease (CVD) is a significant contributor to the deaths of females, and premature menopause adds to the risk of CVD in females. Therefore, our study aimed to investigate the age of menopause and CVD incidence in American females using data from the National Health and Nutrition Examination Survey (NHANES).

METHOD

We analyzed data from 6347 females to investigate the association between menopausal age and the risk of CVD using multivariate logistic regression analysis.

RESULTS

The study found that a later menopausal age reduces the risk of developing CVD (odds ratio [OR] = 0.74, 95% confidence interval [CI] = 0.63 - 0.88, p < 0.001). Moreover, females with early-onset CVD had an increased risk of premature menopause before the age of 40 years (OR = 2.44, 95% CI = 1.60 - 3.72, p < 0.001).

CONCLUSION

Menopausal age is associated with the risk of developing CVD in American females. Specifically, if menopause occurs earlier, there is an increased risk of CVD. Additionally, early-onset CVD significantly raises the risk of premature menopause, which in turn has important implications for female reproductive health.

Changes in lipid profile and glucose metabolism following administration of bupropion alone or in combination with naltrexone: A systematic review and meta-regression analysis

BACKGROUND

Considering the conflicting effects of bupropion on parameters related to metabolic syndrome including glucose metabolism and lipid profile, in this meta-analysis study, we investigated the effects of this drug alone or in combination with naltrexone on glucose metabolism and lipid profile.

METHODS

Scopus, PubMed/Medline, Web of Science and Embase databases were searched using standard keywords to identify all controlled trials investigating effects of bupropion alone and combined with naltrexone on the glucose and lipid profile. Pooled weighted mean difference and 95% confidence intervals were achieved by random-effects model.

RESULTS

Twelve studies with 5152 participants' were included in this article. The pooled findings showed that bupropion alone or in combination with naltrexone would significantly reduce glucose (weighted mean difference (WMD): -2.25 mg/dL, 95% confidence interval (CI): -4.10, -0.40), insulin (WMD: -4.06 μU/mL, 95% CI: -6.09, -2.03), homeostatic model assessment for insulin resistance (HOMA-IR) (WMD: -0.58, 95% CI: -0.98, -0.19), triglyceride (TG) (WMD: -11.78 mg/dL, 95% CI: -14.48 to -9.08) and increase high-density lipoprotein (HDL) (WMD: 2.68 mg/dL, 95% CI: 2.13 to 3.24). A Greater reduction in glucose levels was observed with duration >26 weeks. Dose of bupropion intake ≤360 mg and intervention for more than 26 weeks decreased insulin level significantly. With regard to lipid profile, reduction of triglycerides is more significant with dose of bupropion greater than 360 mg and a shorter intervention length equal to 26 weeks.

CONCLUSIONS

The addition of combination therapies such as bupropion and naltrexone to lifestyle modification can significantly improve glucose metabolism and some lipid parameters.

Ionic liquid modification reshapes the substrate pockets of lipase to boost its stability and activity in vitamin E succinate synthesis

BACKGROUND

The relative low stability, reusability and activity of enzymes made the industrial production of vitamin E succinate (VES) can only be performed with complex processes and high cost using chemical methods. To address these issues, in the present study, an ionic liquids (ILs) modification strategy was developed to improve the activity and stability of lipases in VES synthesis.

RESULTS

The results showed that the [1-butyl-3-methyl imidazole] [N-acetyl-l-proline] ILs modified Candida rugosa lipase (CRL) has the highest modification degree (48.28%), activity (774 U g-1 ), thermostability and solvent tolerance in three selected modifiers. Additionally, after reaction condition optimization, the highest yield of VES can be improved to 95.18% at 45 °C for 15 h, which was significantly improved compared to some previous studies.

CONCLUSION

In the present study, a high-efficiency VES synthesis strategy was successfully developed via modification of lipase. Moreover, the mechanism by which ILs modification can enhance the activity and stability of lipase was investigated via both experimental and computational-aided methods. Molecular dynamics simulation suggested that ILs modification changed the geometry of Phe344 from flat to upright, which significantly reshaped and enhanced the size of substrate binding pocket of CRL. It is also agreement with our circular dichroism and fluorescence spectroscopy results, which suggested that the modification changed the secondary structure of CRL to a certain extent. The larger pocket also endowed the suitable binding pose of succinate, which made the hydrogen bonds between succinate and active site Ser209 become stronger, and thus improving the yield of VES. © 2023 Society of Chemical Industry.

Observation of D^{+}→K_{S}^{0}a_{0}(980)^{+} in the Amplitude Analysis of D^{+}→K_{S}^{0}π^{+}η

We perform for the first time an amplitude analysis of the decay D^{+}→K_{S}^{0}π^{+}η and report the observation of the decay D^{+}→K_{S}^{0}a_{0}(980)^{+} using 2.93  fb^{-1} of e^{+}e^{-} collision data taken at a center-of-mass energy of 3.773 GeV with the BESIII detector. As the only W-annihilation-free decay among D to a_{0}(980) pseudoscalar, D^{+}→K_{S}^{0}a_{0}(980)^{+} is the ideal decay in extracting the contributions of the W-emission amplitudes involving a_{0}(980) and to study the final-state interactions. The absolute branching fraction of D^{+}→K_{S}^{0}π^{+}η is measured to be (1.27±0.04_{stat}±0.03_{syst})%. The branching fractions of intermediate processes D^{+}→K_{S}^{0}a_{0}(980)^{+} with a_{0}(980)^{+}→π^{+}η and D^{+}→π^{+}K[over ¯]_{0}^{*}(1430)^{0} with K[over ¯]_{0}^{*}(1430)^{0}→K_{S}^{0}η are measured to be (1.33±0.05_{stat}±0.04_{syst})% and (0.14±0.03_{stat}±0.01_{syst})%, respectively.

Observation of Significant Flavor-SU(3) Breaking in the Kaon Wave Function at 12<Q^{2}<25 GeV^{2} and Discovery of the Charmless Decay ψ(3770)→K_{S}^{0}K_{L}^{0}

We present cross sections for the reaction e^{+}e^{-}→K_{S}^{0}K_{L}^{0} at center-of-mass energies ranging from 3.51 to 4.95 GeV using data samples collected in the BESIII experiment, corresponding to a total integrated luminosity of 26.5  fb^{-1}. The ratio of neutral-to-charged kaon form factors at large momentum transfers (12 Collapse

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Affiliation(s)

M Ablikim Institute of High Energy Physics, Beijing 100049, People's Republic of China
M N Achasov Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
P Adlarson Uppsala University, Box 516, SE-75120 Uppsala, Sweden
X C Ai Zhengzhou University, Zhengzhou 450001, People's Republic of China
R Aliberti Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
A Amoroso University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
M R An Liaoning Normal University, Dalian 116029, People's Republic of China
Q An State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Y Bai Southeast University, Nanjing 211100, People's Republic of China
O Bakina Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
I Balossino INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
Y Ban Peking University, Beijing 100871, People's Republic of China
H-R Bao University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
V Batozskaya Institute of High Energy Physics, Beijing 100049, People's Republic of China National Centre for Nuclear Research, Warsaw 02-093, Poland
K Begzsuren Institute of Physics and Technology, Peace Avenue 54B, Ulaanbaatar 13330, Mongolia
N Berger Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
M Berlowski National Centre for Nuclear Research, Warsaw 02-093, Poland
M Bertani INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
D Bettoni INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
F Bianchi University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
E Bianco University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
A Bortone University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
I Boyko Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
R A Briere Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
A Brueggemann University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
H Cai Wuhan University, Wuhan 430072, People's Republic of China
X Cai Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
A Calcaterra INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
G F Cao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
N Cao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S A Cetin Turkish Accelerator Center Particle Factory Group, Istinye University, 34010 Istanbul, Turkey
J F Chang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
T T Chang Xinyang Normal University, Xinyang 464000, People's Republic of China
W L Chang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
G R Che Nankai University, Tianjin 300071, People's Republic of China
G Chelkov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
C Chen Nankai University, Tianjin 300071, People's Republic of China
Chao Chen Soochow University, Suzhou 215006, People's Republic of China
G Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China
H S Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
M L Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S J Chen Nanjing University, Nanjing 210093, People's Republic of China
S L Chen North China Electric Power University, Beijing 102206, People's Republic of China
S M Chen Tsinghua University, Beijing 100084, People's Republic of China
T Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X R Chen Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X T Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y B Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y Q Chen Jilin University, Changchun 130012, People's Republic of China
Z J Chen Hunan University, Changsha 410082, People's Republic of China
S K Choi Chung-Ang University, Seoul, 06974, Republic of Korea
X Chu Nankai University, Tianjin 300071, People's Republic of China
G Cibinetto INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
S C Coen Bochum Ruhr-University, D-44780 Bochum, Germany
F Cossio INFN, I-10125, Turin, Italy
J J Cui Shandong University, Jinan 250100, People's Republic of China
H L Dai Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
J P Dai Yunnan University, Kunming 650500, People's Republic of China
A Dbeyssi Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
R E de Boer Bochum Ruhr-University, D-44780 Bochum, Germany
D Dedovich Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
Z Y Deng Institute of High Energy Physics, Beijing 100049, People's Republic of China
A Denig Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
I Denysenko Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
M Destefanis University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
F De Mori University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
B Ding Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Jinan, Jinan 250022, People's Republic of China
X X Ding Peking University, Beijing 100871, People's Republic of China
Y Ding Liaoning University, Shenyang 110036, People's Republic of China
Y Ding Jilin University, Changchun 130012, People's Republic of China
J Dong Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
L Y Dong Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
M Y Dong Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Dong Wuhan University, Wuhan 430072, People's Republic of China
M C Du Institute of High Energy Physics, Beijing 100049, People's Republic of China
S X Du Zhengzhou University, Zhengzhou 450001, People's Republic of China
Z H Duan Nanjing University, Nanjing 210093, People's Republic of China
P Egorov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
Y H Fan North China Electric Power University, Beijing 102206, People's Republic of China
J Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
S S Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
W X Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Q Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
R Farinelli INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
L Fava University of Eastern Piedmont, I-15121 Alessandria, Italy INFN, I-10125, Turin, Italy
F Feldbauer Bochum Ruhr-University, D-44780 Bochum, Germany
G Felici INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
C Q Feng State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J H Feng Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
K Fischer University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
M Fritsch Bochum Ruhr-University, D-44780 Bochum, Germany
C D Fu Institute of High Energy Physics, Beijing 100049, People's Republic of China
J L Fu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y W Fu Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Gao University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y N Gao Peking University, Beijing 100871, People's Republic of China
Yang Gao State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
S Garbolino INFN, I-10125, Turin, Italy
I Garzia INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy University of Ferrara, I-44122 Ferrara, Italy
P T Ge Wuhan University, Wuhan 430072, People's Republic of China
Z W Ge Nanjing University, Nanjing 210093, People's Republic of China
C Geng Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
E M Gersabeck University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
A Gilman University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
K Goetzen GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
L Gong Liaoning University, Shenyang 110036, People's Republic of China
W X Gong Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
W Gradl Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
S Gramigna INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy University of Ferrara, I-44122 Ferrara, Italy
M Greco University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
M H Gu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y T Gu Guangxi University, Nanning 530004, People's Republic of China
C Y Guan Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z L Guan Henan University of Technology, Zhengzhou 450001, People's Republic of China
A Q Guo Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L B Guo Nanjing Normal University, Nanjing 210023, People's Republic of China
M J Guo Shandong University, Jinan 250100, People's Republic of China
R P Guo Shandong Normal University, Jinan 250014, People's Republic of China
Y P Guo Fudan University, Shanghai 200433, People's Republic of China
A Guskov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
J Gutierrez Indiana University, Bloomington, Indiana 47405, USA
T T Han Institute of High Energy Physics, Beijing 100049, People's Republic of China
W Y Han Liaoning Normal University, Dalian 116029, People's Republic of China
X Q Hao Henan Normal University, Xinxiang 453007, People's Republic of China
F A Harris University of Hawaii, Honolulu, Hawaii 96822, USA
K K He Soochow University, Suzhou 215006, People's Republic of China
K L He Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
F H H Heinsius Bochum Ruhr-University, D-44780 Bochum, Germany
C H Heinz Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
Y K Heng Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C Herold Suranaree University of Technology, University Avenue 111, Nakhon Ratchasima 30000, Thailand
T Holtmann Bochum Ruhr-University, D-44780 Bochum, Germany
P C Hong Fudan University, Shanghai 200433, People's Republic of China
G Y Hou Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X T Hou Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y R Hou University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z L Hou Institute of High Energy Physics, Beijing 100049, People's Republic of China
B Y Hu Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
H M Hu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J F Hu South China Normal University, Guangzhou 510006, People's Republic of China
T Hu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y Hu Institute of High Energy Physics, Beijing 100049, People's Republic of China
G S Huang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
K X Huang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
L Q Huang Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X T Huang Shandong University, Jinan 250100, People's Republic of China
Y P Huang Institute of High Energy Physics, Beijing 100049, People's Republic of China
T Hussain University of the Punjab, Lahore-54590, Pakistan
N Hüsken Indiana University, Bloomington, Indiana 47405, USA Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
N In der Wiesche University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
M Irshad State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J Jackson Indiana University, Bloomington, Indiana 47405, USA
S Jaeger Bochum Ruhr-University, D-44780 Bochum, Germany
S Janchiv Institute of Physics and Technology, Peace Avenue 54B, Ulaanbaatar 13330, Mongolia
J H Jeong Chung-Ang University, Seoul, 06974, Republic of Korea
Q Ji Institute of High Energy Physics, Beijing 100049, People's Republic of China
Q P Ji Henan Normal University, Xinxiang 453007, People's Republic of China
X B Ji Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X L Ji Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y Y Ji Shandong University, Jinan 250100, People's Republic of China
X Q Jia Shandong University, Jinan 250100, People's Republic of China
Z K Jia State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
H J Jiang Wuhan University, Wuhan 430072, People's Republic of China
P C Jiang Peking University, Beijing 100871, People's Republic of China
S S Jiang Liaoning Normal University, Dalian 116029, People's Republic of China
T J Jiang Hangzhou Normal University, Hangzhou 310036, People's Republic of China
X S Jiang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y Jiang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J B Jiao Shandong University, Jinan 250100, People's Republic of China
Z Jiao Huangshan College, Huangshan 245000, People's Republic of China
S Jin Nanjing University, Nanjing 210093, People's Republic of China
Y Jin University of Jinan, Jinan 250022, People's Republic of China
M Q Jing Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X M Jing University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
T Johansson Uppsala University, Box 516, SE-75120 Uppsala, Sweden
X Kui Institute of High Energy Physics, Beijing 100049, People's Republic of China
S Kabana Instituto de Alta Investigación, Universidad de Tarapacá, Casilla 7D, Arica 1000000, Chile
N Kalantar-Nayestanaki University of Groningen, NL-9747 AA Groningen, The Netherlands
X L Kang China University of Geosciences, Wuhan 430074, People's Republic of China
X S Kang Liaoning University, Shenyang 110036, People's Republic of China
M Kavatsyuk University of Groningen, NL-9747 AA Groningen, The Netherlands
B C Ke Zhengzhou University, Zhengzhou 450001, People's Republic of China
V Khachatryan Indiana University, Bloomington, Indiana 47405, USA
A Khoukaz University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
R Kiuchi Institute of High Energy Physics, Beijing 100049, People's Republic of China
R Kliemt GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
O B Kolcu Turkish Accelerator Center Particle Factory Group, Istinye University, 34010 Istanbul, Turkey
B Kopf Bochum Ruhr-University, D-44780 Bochum, Germany
M Kuessner Bochum Ruhr-University, D-44780 Bochum, Germany
A Kupsc National Centre for Nuclear Research, Warsaw 02-093, Poland Uppsala University, Box 516, SE-75120 Uppsala, Sweden
W Kühn Justus-Liebig-Universitaet Giessen, II. Physikalisches Institut, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
J J Lane University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
P Larin Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
A Lavania Indian Institute of Technology Madras, Chennai 600036, India
L Lavezzi University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
T T Lei State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Z H Lei State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
H Leithoff Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
M Lellmann Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
T Lenz Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
C Li Qufu Normal University, Qufu 273165, People's Republic of China
C Li Nankai University, Tianjin 300071, People's Republic of China
C H Li Liaoning Normal University, Dalian 116029, People's Republic of China
Cheng Li State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
D M Li Zhengzhou University, Zhengzhou 450001, People's Republic of China
F Li Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
G Li Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Li State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
H B Li Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H J Li Henan Normal University, Xinxiang 453007, People's Republic of China
H N Li South China Normal University, Guangzhou 510006, People's Republic of China
Hui Li Nankai University, Tianjin 300071, People's Republic of China
J R Li Tsinghua University, Beijing 100084, People's Republic of China
J S Li Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
J W Li Shandong University, Jinan 250100, People's Republic of China
Ke Li Institute of High Energy Physics, Beijing 100049, People's Republic of China
L J Li Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L K Li Institute of High Energy Physics, Beijing 100049, People's Republic of China
Lei Li Renmin University of China, Beijing 100872, People's Republic of China
M H Li Nankai University, Tianjin 300071, People's Republic of China
P R Li Lanzhou University, Lanzhou 730000, People's Republic of China
Q X Li Shandong University, Jinan 250100, People's Republic of China
S X Li Fudan University, Shanghai 200433, People's Republic of China
T Li Shandong University, Jinan 250100, People's Republic of China
W D Li Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
W G Li Institute of High Energy Physics, Beijing 100049, People's Republic of China
X H Li State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X L Li Shandong University, Jinan 250100, People's Republic of China
Xiaoyu Li Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y G Li Peking University, Beijing 100871, People's Republic of China
Z J Li Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
Z X Li Guangxi University, Nanning 530004, People's Republic of China
C Liang Nanjing University, Nanjing 210093, People's Republic of China
H Liang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H Liang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Y F Liang Sichuan University, Chengdu 610064, People's Republic of China
Y T Liang Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
G R Liao Guangxi Normal University, Guilin 541004, People's Republic of China
L Z Liao Shandong University, Jinan 250100, People's Republic of China
Y P Liao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J Libby Indian Institute of Technology Madras, Chennai 600036, India
A Limphirat Suranaree University of Technology, University Avenue 111, Nakhon Ratchasima 30000, Thailand
D X Lin Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
T Lin Institute of High Energy Physics, Beijing 100049, People's Republic of China
B J Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
B X Liu Wuhan University, Wuhan 430072, People's Republic of China
C Liu Jilin University, Changchun 130012, People's Republic of China
C X Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
F H Liu Shanxi University, Taiyuan 030006, People's Republic of China
Fang Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
Feng Liu Central China Normal University, Wuhan 430079, People's Republic of China
G M Liu South China Normal University, Guangzhou 510006, People's Republic of China
H Liu Lanzhou University, Lanzhou 730000, People's Republic of China
H B Liu Guangxi University, Nanning 530004, People's Republic of China
H M Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Huanhuan Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
Huihui Liu Henan University of Science and Technology, Luoyang 471003, People's Republic of China
J B Liu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J Y Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
K Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
K Y Liu Liaoning University, Shenyang 110036, People's Republic of China
Ke Liu Henan University of Technology, Zhengzhou 450001, People's Republic of China
L Liu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
L C Liu Nankai University, Tianjin 300071, People's Republic of China
Lu Liu Nankai University, Tianjin 300071, People's Republic of China
M H Liu Fudan University, Shanghai 200433, People's Republic of China
P L Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
Q Liu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S B Liu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
T Liu Fudan University, Shanghai 200433, People's Republic of China
W K Liu Nankai University, Tianjin 300071, People's Republic of China
W M Liu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X Liu Lanzhou University, Lanzhou 730000, People's Republic of China
Y Liu Lanzhou University, Lanzhou 730000, People's Republic of China
Y Liu Zhengzhou University, Zhengzhou 450001, People's Republic of China
Y B Liu Nankai University, Tianjin 300071, People's Republic of China
Z A Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z Q Liu Shandong University, Jinan 250100, People's Republic of China
X C Lou Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
F X Lu Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
H J Lu Huangshan College, Huangshan 245000, People's Republic of China
J G Lu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
X L Lu Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Lu Central South University, Changsha 410083, People's Republic of China
Y P Lu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Z H Lu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C L Luo Nanjing Normal University, Nanjing 210023, People's Republic of China
M X Luo Zhejiang University, Hangzhou 310027, People's Republic of China
T Luo Fudan University, Shanghai 200433, People's Republic of China
X L Luo Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
X R Lyu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y F Lyu Nankai University, Tianjin 300071, People's Republic of China
F C Ma Liaoning University, Shenyang 110036, People's Republic of China
H Ma Yunnan University, Kunming 650500, People's Republic of China
H L Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China
J L Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L L Ma Shandong University, Jinan 250100, People's Republic of China
M M Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Q M Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China
R Q Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Y Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y Ma Peking University, Beijing 100871, People's Republic of China
Y M Ma Institute of Modern Physics, Lanzhou 730000, People's Republic of China
F E Maas Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
M Maggiora University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
S Malde University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
Q A Malik University of the Punjab, Lahore-54590, Pakistan
A Mangoni INFN Sezione di Perugia, I-06100 Perugia, Italy
Y J Mao Peking University, Beijing 100871, People's Republic of China
Z P Mao Institute of High Energy Physics, Beijing 100049, People's Republic of China
S Marcello University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
Z X Meng University of Jinan, Jinan 250022, People's Republic of China
J G Messchendorp GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany University of Groningen, NL-9747 AA Groningen, The Netherlands
G Mezzadri INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
H Miao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
T J Min Nanjing University, Nanjing 210093, People's Republic of China
R E Mitchell Indiana University, Bloomington, Indiana 47405, USA
X H Mo Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B Moses Indiana University, Bloomington, Indiana 47405, USA
N Yu Muchnoi Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
J Muskalla Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
Y Nefedov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
F Nerling Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
I B Nikolaev Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
Z Ning Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
S Nisar COMSATS University Islamabad, Lahore Campus, Defence Road, Off Raiwind Road, 54000 Lahore, Pakistan
Q L Niu Lanzhou University, Lanzhou 730000, People's Republic of China
W D Niu Soochow University, Suzhou 215006, People's Republic of China
Y Niu Shandong University, Jinan 250100, People's Republic of China
S L Olsen University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Q Ouyang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S Pacetti INFN Sezione di Perugia, I-06100 Perugia, Italy University of Perugia, I-06100 Perugia, Italy
X Pan Soochow University, Suzhou 215006, People's Republic of China
Y Pan Southeast University, Nanjing 211100, People's Republic of China
A Pathak Jilin University, Changchun 130012, People's Republic of China
P Patteri INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
Y P Pei State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
M Pelizaeus Bochum Ruhr-University, D-44780 Bochum, Germany
H P Peng State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Y Y Peng Lanzhou University, Lanzhou 730000, People's Republic of China
K Peters GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
J L Ping Nanjing Normal University, Nanjing 210023, People's Republic of China
R G Ping Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S Plura Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
V Prasad Instituto de Alta Investigación, Universidad de Tarapacá, Casilla 7D, Arica 1000000, Chile
F Z Qi Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Qi State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
H R Qi Tsinghua University, Beijing 100084, People's Republic of China
M Qi Nanjing University, Nanjing 210093, People's Republic of China
T Y Qi Fudan University, Shanghai 200433, People's Republic of China
S Qian Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
W B Qian University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C F Qiao University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J J Qin University of South China, Hengyang 421001, People's Republic of China
L Q Qin Guangxi Normal University, Guilin 541004, People's Republic of China
X S Qin Shandong University, Jinan 250100, People's Republic of China
Z H Qin Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
J F Qiu Institute of High Energy Physics, Beijing 100049, People's Republic of China
S Q Qu Tsinghua University, Beijing 100084, People's Republic of China
C F Redmer Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
K J Ren Liaoning Normal University, Dalian 116029, People's Republic of China
A Rivetti INFN, I-10125, Turin, Italy
M Rolo INFN, I-10125, Turin, Italy
G Rong Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Ch Rosner Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
S N Ruan Nankai University, Tianjin 300071, People's Republic of China
N Salone National Centre for Nuclear Research, Warsaw 02-093, Poland
A Sarantsev Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
Y Schelhaas Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
K Schoenning Uppsala University, Box 516, SE-75120 Uppsala, Sweden
M Scodeggio INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy University of Ferrara, I-44122 Ferrara, Italy
K Y Shan Fudan University, Shanghai 200433, People's Republic of China
W Shan Hunan Normal University, Changsha 410081, People's Republic of China
X Y Shan State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J F Shangguan Soochow University, Suzhou 215006, People's Republic of China
L G Shao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
M Shao State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
C P Shen Fudan University, Shanghai 200433, People's Republic of China
H F Shen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
W H Shen University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Y Shen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B A Shi University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H C Shi State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J L Shi Fudan University, Shanghai 200433, People's Republic of China
J Y Shi Institute of High Energy Physics, Beijing 100049, People's Republic of China
Q Q Shi Soochow University, Suzhou 215006, People's Republic of China
R S Shi Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Shi Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
J J Song Henan Normal University, Xinxiang 453007, People's Republic of China
T Z Song Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
W M Song Institute of High Energy Physics, Beijing 100049, People's Republic of China Jilin University, Changchun 130012, People's Republic of China
Y J Song Fudan University, Shanghai 200433, People's Republic of China
Y X Song Peking University, Beijing 100871, People's Republic of China
S Sosio University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
S Spataro University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
F Stieler Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
Y J Su University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
G B Sun Wuhan University, Wuhan 430072, People's Republic of China
G X Sun Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Sun University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H K Sun Institute of High Energy Physics, Beijing 100049, People's Republic of China
J F Sun Henan Normal University, Xinxiang 453007, People's Republic of China
K Sun Tsinghua University, Beijing 100084, People's Republic of China
L Sun Wuhan University, Wuhan 430072, People's Republic of China
S S Sun Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
T Sun Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China
W Y Sun Jilin University, Changchun 130012, People's Republic of China
Y Sun China University of Geosciences, Wuhan 430074, People's Republic of China
Y J Sun State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Y Z Sun Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z T Sun Shandong University, Jinan 250100, People's Republic of China
Y X Tan State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
C J Tang Sichuan University, Chengdu 610064, People's Republic of China
G Y Tang Institute of High Energy Physics, Beijing 100049, People's Republic of China
J Tang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
Y A Tang Wuhan University, Wuhan 430072, People's Republic of China
L Y Tao University of South China, Hengyang 421001, People's Republic of China
Q T Tao Hunan University, Changsha 410082, People's Republic of China
M Tat University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
J X Teng State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
V Thoren Uppsala University, Box 516, SE-75120 Uppsala, Sweden
W H Tian Shanxi Normal University, Linfen 041004, People's Republic of China
W H Tian Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
Y Tian Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z F Tian Wuhan University, Wuhan 430072, People's Republic of China
I Uman Near East University, Nicosia, North Cyprus, 99138, Mersin 10, Turkey
Y Wan Soochow University, Suzhou 215006, People's Republic of China
S J Wang Shandong University, Jinan 250100, People's Republic of China
B Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China
B L Wang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Bo Wang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
C W Wang Nanjing University, Nanjing 210093, People's Republic of China
D Y Wang Peking University, Beijing 100871, People's Republic of China
F Wang University of South China, Hengyang 421001, People's Republic of China
H J Wang Lanzhou University, Lanzhou 730000, People's Republic of China
J P Wang Shandong University, Jinan 250100, People's Republic of China
K Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
L L Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China
M Wang Shandong University, Jinan 250100, People's Republic of China
Meng Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
N Y Wang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S Wang Fudan University, Shanghai 200433, People's Republic of China
S Wang Lanzhou University, Lanzhou 730000, People's Republic of China
T Wang Fudan University, Shanghai 200433, People's Republic of China
T J Wang Nankai University, Tianjin 300071, People's Republic of China
W Wang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
W Wang University of South China, Hengyang 421001, People's Republic of China
W P Wang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X Wang Peking University, Beijing 100871, People's Republic of China
X F Wang Lanzhou University, Lanzhou 730000, People's Republic of China
X J Wang Liaoning Normal University, Dalian 116029, People's Republic of China
X L Wang Fudan University, Shanghai 200433, People's Republic of China
Y Wang Tsinghua University, Beijing 100084, People's Republic of China
Y D Wang North China Electric Power University, Beijing 102206, People's Republic of China
Y F Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y L Wang Henan Normal University, Xinxiang 453007, People's Republic of China
Y N Wang North China Electric Power University, Beijing 102206, People's Republic of China
Y Q Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Yaqian Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China Hebei University, Baoding 071002, People's Republic of China
Yi Wang Tsinghua University, Beijing 100084, People's Republic of China
Z Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Z L Wang University of South China, Hengyang 421001, People's Republic of China
Z Y Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Ziyi Wang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
D Wei University of Science and Technology Liaoning, Anshan 114051, People's Republic of China
D H Wei Guangxi Normal University, Guilin 541004, People's Republic of China
F Weidner University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
S P Wen Institute of High Energy Physics, Beijing 100049, People's Republic of China
C W Wenzel Bochum Ruhr-University, D-44780 Bochum, Germany
U Wiedner Bochum Ruhr-University, D-44780 Bochum, Germany
G Wilkinson University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
M Wolke Uppsala University, Box 516, SE-75120 Uppsala, Sweden
L Wollenberg Bochum Ruhr-University, D-44780 Bochum, Germany
C Wu Liaoning Normal University, Dalian 116029, People's Republic of China
J F Wu Institute of High Energy Physics, Beijing 100049, People's Republic of China China Center of Advanced Science and Technology, Beijing 100190, People's Republic of China
L H Wu Institute of High Energy Physics, Beijing 100049, People's Republic of China
L J Wu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Wu Fudan University, Shanghai 200433, People's Republic of China
X H Wu Jilin University, Changchun 130012, People's Republic of China
Y Wu University of Science and Technology of China, Hefei 230026, People's Republic of China
Y H Wu Soochow University, Suzhou 215006, People's Republic of China
Y J Wu Institute of Modern Physics, Lanzhou 730000, People's Republic of China
Z Wu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
L Xia State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X M Xian Liaoning Normal University, Dalian 116029, People's Republic of China
T Xiang Peking University, Beijing 100871, People's Republic of China
D Xiao Lanzhou University, Lanzhou 730000, People's Republic of China
G Y Xiao Nanjing University, Nanjing 210093, People's Republic of China
S Y Xiao Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y L Xiao Fudan University, Shanghai 200433, People's Republic of China
Z J Xiao Nanjing Normal University, Nanjing 210023, People's Republic of China
C Xie Nanjing University, Nanjing 210093, People's Republic of China
X H Xie Peking University, Beijing 100871, People's Republic of China
Y Xie Shandong University, Jinan 250100, People's Republic of China
Y G Xie Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y H Xie Central China Normal University, Wuhan 430079, People's Republic of China
Z P Xie State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
T Y Xing Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C F Xu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C J Xu Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
G F Xu Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Y Xu University of Jinan, Jinan 250022, People's Republic of China
Q J Xu Hangzhou Normal University, Hangzhou 310036, People's Republic of China
Q N Xu Inner Mongolia University, Hohhot 010021, People's Republic of China
W Xu Institute of High Energy Physics, Beijing 100049, People's Republic of China
W L Xu University of Jinan, Jinan 250022, People's Republic of China
X P Xu Soochow University, Suzhou 215006, People's Republic of China
Y C Xu Yantai University, Yantai 264005, People's Republic of China
Z P Xu Nanjing University, Nanjing 210093, People's Republic of China
Z S Xu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
F Yan Fudan University, Shanghai 200433, People's Republic of China
L Yan Fudan University, Shanghai 200433, People's Republic of China
W B Yan State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
W C Yan Zhengzhou University, Zhengzhou 450001, People's Republic of China
X Q Yan Institute of High Energy Physics, Beijing 100049, People's Republic of China
H J Yang Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China
H L Yang Jilin University, Changchun 130012, People's Republic of China
H X Yang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Tao Yang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Yang Fudan University, Shanghai 200433, People's Republic of China
Y F Yang Nankai University, Tianjin 300071, People's Republic of China
Y X Yang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Yifan Yang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z W Yang Lanzhou University, Lanzhou 730000, People's Republic of China
Z P Yao Shandong University, Jinan 250100, People's Republic of China
M Ye Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
M H Ye China Center of Advanced Science and Technology, Beijing 100190, People's Republic of China
J H Yin Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z Y You Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
B X Yu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C X Yu Nankai University, Tianjin 300071, People's Republic of China
G Yu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J S Yu Hunan University, Changsha 410082, People's Republic of China
T Yu University of South China, Hengyang 421001, People's Republic of China
X D Yu Peking University, Beijing 100871, People's Republic of China
C Z Yuan Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L Yuan Beihang University, Beijing 100191, People's Republic of China
S C Yuan Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Yuan Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z Y Yuan Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
C X Yue Liaoning Normal University, Dalian 116029, People's Republic of China
A A Zafar University of the Punjab, Lahore-54590, Pakistan
F R Zeng Shandong University, Jinan 250100, People's Republic of China
S H Zeng University of South China, Hengyang 421001, People's Republic of China
X Zeng Fudan University, Shanghai 200433, People's Republic of China
Y Zeng Hunan University, Changsha 410082, People's Republic of China
Y J Zeng Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Y Zhai Jilin University, Changchun 130012, People's Republic of China
Y C Zhai Shandong University, Jinan 250100, People's Republic of China
Y H Zhan Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
A Q Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B L Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B X Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
D H Zhang Nankai University, Tianjin 300071, People's Republic of China
G Y Zhang Henan Normal University, Xinxiang 453007, People's Republic of China
H Zhang University of Science and Technology of China, Hefei 230026, People's Republic of China
H C Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H H Zhang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
H H Zhang Jilin University, Changchun 130012, People's Republic of China
H Q Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H Y Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
J Zhang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
J Zhang Zhengzhou University, Zhengzhou 450001, People's Republic of China
J J Zhang Shanxi Normal University, Linfen 041004, People's Republic of China
J L Zhang Henan University, Kaifeng 475004, People's Republic of China
J Q Zhang Nanjing Normal University, Nanjing 210023, People's Republic of China
J W Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J X Zhang Lanzhou University, Lanzhou 730000, People's Republic of China
J Y Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
J Z Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Jianyu Zhang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L M Zhang Tsinghua University, Beijing 100084, People's Republic of China
L Q Zhang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
Lei Zhang Nanjing University, Nanjing 210093, People's Republic of China
P Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Q Y Zhang Liaoning Normal University, Dalian 116029, People's Republic of China Zhengzhou University, Zhengzhou 450001, People's Republic of China
Shuihan Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Shulei Zhang Hunan University, Changsha 410082, People's Republic of China
X D Zhang North China Electric Power University, Beijing 102206, People's Republic of China
X M Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
X Y Zhang Shandong University, Jinan 250100, People's Republic of China
Y Zhang University of South China, Hengyang 421001, People's Republic of China
Y Zhang University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
Y T Zhang Zhengzhou University, Zhengzhou 450001, People's Republic of China
Y H Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Yan Zhang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Yao Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z D Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z H Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z L Zhang Jilin University, Changchun 130012, People's Republic of China
Z Y Zhang Nankai University, Tianjin 300071, People's Republic of China
Z Y Zhang Wuhan University, Wuhan 430072, People's Republic of China
G Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China
J Y Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J Z Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Lei Zhao State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Ling Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China
M G Zhao Nankai University, Tianjin 300071, People's Republic of China
R P Zhao University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S J Zhao Zhengzhou University, Zhengzhou 450001, People's Republic of China
Y B Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y X Zhao Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z G Zhao State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
A Zhemchugov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
B Zheng University of South China, Hengyang 421001, People's Republic of China
J P Zheng Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
W J Zheng Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y H Zheng University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B Zhong Nanjing Normal University, Nanjing 210023, People's Republic of China
X Zhong Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
H Zhou Shandong University, Jinan 250100, People's Republic of China
L P Zhou Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Zhou Wuhan University, Wuhan 430072, People's Republic of China
X K Zhou Central China Normal University, Wuhan 430079, People's Republic of China
X R Zhou State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X Y Zhou Liaoning Normal University, Dalian 116029, People's Republic of China
Y Z Zhou Fudan University, Shanghai 200433, People's Republic of China
J Zhu Nankai University, Tianjin 300071, People's Republic of China
K Zhu Institute of High Energy Physics, Beijing 100049, People's Republic of China
K J Zhu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L Zhu Jilin University, Changchun 130012, People's Republic of China
L X Zhu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S H Zhu University of Science and Technology Liaoning, Anshan 114051, People's Republic of China
S Q Zhu Nanjing University, Nanjing 210093, People's Republic of China
T J Zhu Fudan University, Shanghai 200433, People's Republic of China
W J Zhu Fudan University, Shanghai 200433, People's Republic of China
Y C Zhu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Z A Zhu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J H Zou Institute of High Energy Physics, Beijing 100049, People's Republic of China
J Zu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China

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Bioinformatic validation and machine learning-based exploration of purine metabolism-related gene signatures in the context of immunotherapeutic strategies for nonspecific orbital inflammation

Background

Nonspecific orbital inflammation (NSOI) represents a perplexing and persistent proliferative inflammatory disorder of idiopathic nature, characterized by a heterogeneous lymphoid infiltration within the orbital region. This condition, marked by the aberrant metabolic activities of its cellular constituents, starkly contrasts with the metabolic equilibrium found in healthy cells. Among the myriad pathways integral to cellular metabolism, purine metabolism emerges as a critical player, providing the building blocks for nucleic acid synthesis, such as DNA and RNA. Despite its significance, the contribution of Purine Metabolism Genes (PMGs) to the pathophysiological landscape of NSOI remains a mystery, highlighting a critical gap in our understanding of the disease's molecular underpinnings.

Methods

To bridge this knowledge gap, our study embarked on an exploratory journey to identify and validate PMGs implicated in NSOI, employing a comprehensive bioinformatics strategy. By intersecting differential gene expression analyses with a curated list of 92 known PMGs, we aimed to pinpoint those with potential roles in NSOI. Advanced methodologies, including Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA), facilitated a deep dive into the biological functions and pathways associated with these PMGs. Further refinement through Lasso regression and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) enabled the identification of key hub genes and the evaluation of their diagnostic prowess for NSOI. Additionally, the relationship between these hub PMGs and relevant clinical parameters was thoroughly investigated. To corroborate our findings, we analyzed expression data from datasets GSE58331 and GSE105149, focusing on the seven PMGs identified as potentially crucial to NSOI pathology.

Results

Our investigation unveiled seven PMGs (ENTPD1, POLR2K, NPR2, PDE6D, PDE6H, PDE4B, and ALLC) as intimately connected to NSOI. Functional analyses shed light on their involvement in processes such as peroxisome targeting sequence binding, seminiferous tubule development, and ciliary transition zone organization. Importantly, the diagnostic capabilities of these PMGs demonstrated promising efficacy in distinguishing NSOI from non-affected states.

Conclusions

Through rigorous bioinformatics analyses, this study unveils seven PMGs as novel biomarker candidates for NSOI, elucidating their potential roles in the disease's pathogenesis. These discoveries not only enhance our understanding of NSOI at the molecular level but also pave the way for innovative approaches to monitor and study its progression, offering a beacon of hope for individuals afflicted by this enigmatic condition.

A stable and flexible Au@Ag NPs/PVA SERS platform for thiram residue detection on rough surface

Flexible and transparent surface-enhanced Raman scattering (SERS) substrates have gained great attention in analysis field as they offer a fast, non-destructive, and highly sensitive platform for in-situ detection. In this work, we present a facile one-pot strategy for synthesizing gold-cored silver shell nanoparticles (Au@Ag NPs) in the polyvinyl alcohol (PVA) colloid. With no other reducing agents, PVA can serve as both reducing and stabilizing agents for forming Au@Ag NPs. Besides, PVA acts as a scaffold to maintain SERS "hot-spots" by preventing nanoparticle aggregation. By using this flexible Au@Ag NPs/PVA colloid, the analytes can be extracted from rough surfaces for SERS measurements with excellent sensitivity, repeatability and stability. The SERS activity of the Au@Ag NPs/PVA remained at 89.8% even after 120 days of storage at room temperature in sealed air atmosphere. The selective detection of thiram residues on the surface of fruits and vegetables was successfully achieved. The limits of detection for thiram residues on apple and tomato surfaces were measured to be 0.58 and 0.56 ng cm-2, respectively, with recovery rate ranging from 91% to 107%. This work demonstrates the immense application potential of SERS colloid platform in the fields of food safety and environmental analysis.

Deficiency of lncRNA MERRICAL abrogates macrophage chemotaxis and diabetes-associated atherosclerosis

Diabetes-associated atherosclerosis involves excessive immune cell recruitment and plaque formation. However, the mechanisms remain poorly understood. Transcriptomic analysis of the aortic intima in Ldlr-/- mice on a high-fat, high-sucrose-containing (HFSC) diet identifies a macrophage-enriched nuclear long noncoding RNA (lncRNA), MERRICAL (macrophage-enriched lncRNA regulates inflammation, chemotaxis, and atherosclerosis). MERRICAL expression increases by 249% in intimal lesions during progression. lncRNA-mRNA pair genomic mapping reveals that MERRICAL positively correlates with the chemokines Ccl3 and Ccl4. MERRICAL-deficient macrophages exhibit lower Ccl3 and Ccl4 expression, chemotaxis, and inflammatory responses. Mechanistically, MERRICAL guides the WDR5-MLL1 complex to activate CCL3 and CCL4 transcription via H3K4me3 modification. MERRICAL deficiency in HFSC diet-fed Ldlr-/- mice reduces lesion formation by 74% in the aortic sinus and 86% in the descending aorta by inhibiting leukocyte recruitment into the aortic wall and pro-inflammatory responses. These findings unveil a regulatory mechanism whereby a macrophage-enriched lncRNA potently inhibits chemotactic responses, alleviating lesion progression in diabetes.

Bioinformatics-based screening and analysis of the key genes involved in the influence of antiangiogenesis on myeloid-derived suppressor cells and their effects on the immune microenvironment

This study aimed to screen differentially expressed genes (DEGs) involved in the influence of antiangiogenic therapy on myeloid-derived suppressor cell (MDSC) infiltration and investigate their mechanisms of action. Data on DEGs after the action of antiangiogenic drugs in a pan-cancer context were obtained from the Gene Expression Omnibus (GEO) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the clusterProfiler package in R software. Single-sample gene set enrichment analysis was performed using the gene set variation analysis package to evaluate the levels of immune cells and the activity of immune-related pathways. The relationships of DEGs with the infiltration levels of MDSCs and specific immune cell subpopulations were investigated via gene module analysis. The top 10 key genes were subsequently obtained from PPI network analysis using the cytoHubba plugin of the Cytoscape platform. When the DEGs of the four datasets were intersected, a DEG in the intersection of three datasets and 12 DEGs in the intersection of two datasets were upregulated, and 28 DEGs in the intersection of two datasets were downregulated. GO and KEGG pathway enrichment analyses revealed that the DEGs were associated with multiple important signaling pathways closely related to tumor onset and development, including cell differentiation, cell proliferation, the cell cycle, and immune responses. Most downregulated genes in lung adenocarcinoma (LUAD) were positively correlated with MDSC expression. Only MGP was negatively correlated; the correlation between CACNG6 and MDSC expression was statistically insignificant. In lung squamous cell carcinoma (LUSC), the relationships of PMEPA1, PCDH7, NEURL1B, and CACNG6 with MDSC expression were statistically insignificant; MGP was negatively correlated with MDSC expression. The top 10 key genes with the highest degree scores obtained using the cytoHubba plugin of Cytoscape were AURKB, RRM2, BUB1, NUSAP1, PRC1, TOP2A, NCAPH, CENPA, KIF2C, and CCNA2. Most of these genes were upregulated in LUAD and associated with immune cell infiltration and prognosis in tumors. An analysis of the relationships between DEGs and infiltration by other specific immune cells revealed the presence of consistent patterns in the downregulated genes, which exhibited positive correlations with the levels of Th2 cells, γδ T cells, and CD56dim NK cells, and negative correlations with other infiltrating immune cells. Antiangiogenic therapy may regulate MDSC infiltration through multiple important signaling pathways closely associated with tumor onset and development, such as cell differentiation, cell proliferation, the cell cycle, and immune responses. Antiangiogenic drugs may exert effects by affecting various types of infiltrating cells associated with immune suppression.

Accuracy of MRI-Based Radiomics in Diagnosis of Placenta Accreta Spectrum: A PRISMA Systematic Review and Meta-Analysis

BACKGROUND Placenta accreta syndrome (PAS) can lead to severe obstetric bleeding, and can be life-threatening. This study aimed to assess the precision of radiomics features derived from magnetic resonance imaging (MRI) for diagnosing PAS. MATERIAL AND METHODS A comprehensive search was conducted in the databases PubMed, Embase, Web of Science, and the Cochrane library from inception to October 2023. We included diagnostic accuracy studies utilizing radiomics-MRI in PAS patients, with histopathology serving as the reference standard. The overall diagnostic odds ratio (DOR), sensitivity, specificity, and area under the curve (AUC) were computed to gauge the diagnostic accuracy of MRI-based radiomic features in PAS patients. Quality assessment was performed using the Quality Assessment of Diagnostic Accuracy Studies 2. Statistical analyses were carried out using Stata 14.2, MetaDiSc 1.4, and Review Manager 5.3 software. RESULTS Seven studies involving 672 patients were incorporated. The aggregated DOR, sensitivity, specificity, and AUC for radiomics in detecting PAS were 78% (confidence interval32, 191), 87% (76%, 93%), 92% (89%, 94%), and 0.93 (0.91-0.95), respectively. The meta-analysis revealed notable heterogeneity among the included studies, with no evidence of a threshold effect. Subgroup analysis demonstrated that, in comparison to manual segmentation and validation groups with ≤100 cases and internal validation datasets, automated segmentation, validation groups with >100 cases, and external validation datasets exhibited superior diagnostic performance . CONCLUSIONS Our findings indicate that MRI-based radiomic features perform well in assessing the diagnostic risk of PAS during prenatal diagnosis. This noninvasive and convenient tool may prove valuable in facilitating the identification of PAS.

Unraveling trends in schistosomiasis: deep learning insights into national control programs in China

Objectives

To achieve the ambitious goal of eliminating schistosome infections, the Chinese government has implemented diverse control strategies. This study explored the progress of the 2 most recent national schistosomiasis control programs in an endemic area along the Yangtze River in China.

Methods

We obtained village-level parasitological data from cross-sectional surveys combined with environmental data in Anhui Province, China from 1997 to 2015. A convolutional neural network (CNN) based on a hierarchical integro-difference equation (IDE) framework (i.e., CNN-IDE) was used to model spatio-temporal variations in schistosomiasis. Two traditional models were also constructed for comparison with 2 evaluation indicators: the mean-squared prediction error (MSPE) and continuous ranked probability score (CRPS).

Results

The CNN-IDE model was the optimal model, with the lowest overall average MSPE of 0.04 and the CRPS of 0.19. From 1997 to 2011, the prevalence exhibited a notable trend: it increased steadily until peaking at 1.6 per 1000 in 2005, then gradually declined, stabilizing at a lower rate of approximately 0.6 per 1000 in 2006, and approaching zero by 2011. During this period, noticeable geographic disparities in schistosomiasis prevalence were observed; high-risk areas were initially dispersed, followed by contraction. Predictions for the period 2012 to 2015 demonstrated a consistent and uniform decrease.

Conclusion

The proposed CNN-IDE model captured the intricate and evolving dynamics of schistosomiasis prevalence, offering a promising alternative for future risk modeling of the disease. The comprehensive strategy is expected to help diminish schistosomiasis infection, emphasizing the necessity to continue implementing this strategy.

Chiral nanoparticle separation and discrimination using radially polarized circular Airy vortex beams with orbital-induced spin angular momentum

We report orbit-induced localized spin angular momentum associated with optical spin-orbit interactions in tightly focused radially polarized circular Airy vortex beams and demonstrate their potential for separation and discrimination of chiral nanoparticles. We find that variations in spin angular momentum density endow these beams with positive and negative annular optical chirality density. Utilizing these extraordinary distributions, particles having different chirality parameters can be separated and discriminated by using two degrees of freedom, i.e., radial trapping position and azimuthal rotation. We also discuss the impacts of longitudinal optical force and topological charge on manipulating chiral particles. Additionally, we conduct a comparative analysis of the optical trapping of a non-chiral particle. Our work is expected to deepen the understanding of spin-orbit interactions and provide valuable insight into vortex beam interactions with chiral particles.

[Application of interventional respiratory techniques in the treatment of pulmonary bullae:an update]

Pulmonary bullae is a common complication of chronic obstructive pulmonary disease(COPD), causing the deterioration in lung function, leading to aggravated dyspnea and poor quality of life for patients. The traditional therapeutic approach for pulmonary bullae is bullectomy using surgical thoracoscopy. The disadvantage of this approach is the postoperative complications and high risk of recurrence in many patients. In addition, for some patients, due to the patient's physical conditions, such as poor lung function and other diseases, bullectomy could not be used. Therefore, new alternative approaches were urgently needed. In recent years, interventional respiratory technology has been trialed to treat pulmonary bulla all around the world and has achieved great success. In this paper, we reviewed the relevant clinical research progress of interventional respiratory medicine techniques in the treatment of pulmonary bullae.

Investigation of the ΔI=1/2 Rule and Test of CP Symmetry through the Measurement of Decay Asymmetry Parameters in Ξ^{-} Decays

Using (10087±44)×10^{6}  J/ψ events collected with the BESIII detector, numerous Ξ^{-} and Λ decay asymmetry parameters are simultaneously determined from the process J/ψ→Ξ^{-}Ξ[over ¯]^{+}→Λ(pπ^{-})π^{-}Λ[over ¯](n[over ¯]π^{0})π^{+} and its charge-conjugate channel. The precisions of α_{Λ0} for Λ→nπ^{0} and α[over ¯]_{Λ0} for Λ[over ¯]→n[over ¯]π^{0} compared to world averages are improved by factors of 4 and 1.7, respectively. The ratio of decay asymmetry parameters of Λ→nπ^{0} to that of Λ→pπ^{-}, ⟨α_{Λ0}⟩/⟨α_{Λ-}⟩, is determined to be 0.873±0.012_{-0.010}^{+0.011}, where the first and the second uncertainties are statistical and systematic, respectively. The ratio is smaller than unity more than 5σ, which signifies the existence of the ΔI=3/2 transition in Λ for the first time. Besides, we test for CP symmetry in Ξ^{-}→Λπ^{-} and in Λ→nπ^{0} with the best precision to date.

Overlooked uneven progress across sustainable development goals at the global scale: Challenges and opportunities

Differences in progress across sustainable development goals (SDGs) are widespread globally; meanwhile, the rising call for prioritizing specific SDGs may exacerbate such gaps. Nevertheless, how these progress differences would influence global sustainable development has been long neglected. Here, we present the first quantitative assessment of SDGs' progress differences globally by adopting the SDGs progress evenness index. Our results highlight that the uneven progress across SDGs has been a hindrance to sustainable development because (1) it is strongly associated with many public health risks (e.g., air pollution), social inequalities (e.g., gender inequality, modern slavery, wealth gap), and a reduction in life expectancy; (2) it is also associated with deforestation and habitat loss in terrestrial and marine ecosystems, increasing the challenges related to biodiversity conservation; (3) most countries with low average SDGs performance show lower progress evenness, which further hinders their fulfillment of SDGs; and (4) many countries with high average SDGs performance also showcase stagnation or even retrogression in progress evenness, which is partly ascribed to the antagonism between climate actions and other goals. These findings highlight that while setting SDGs priorities may be more realistic under the constraints of multiple global stressors, caution must be exercised to avoid new problems from intensifying uneven progress across goals. Moreover, our study reveals that the urgent needs regarding SDGs of different regions seem complementary, emphasizing that regional collaborations (e.g., demand-oriented carbon trading between SDGs poorly performed and well-performed countries) may promote sustainable development achievements at the global scale.

Metal-Organic Framework Based Mucoadhesive Nanodrugs for Multifunction Helicobacter Pylori Targeted Eradication, Inflammation Regulation and Gut Flora Protection

The prevalence of drug-resistant bacteria presents a significant challenge to the antibiotic treatment of Helicobacter pylori (H. pylori), while traditional antimicrobial agents often suffer from shortcomings such as poor gastric retention, inadequate alleviation of inflammation, and significant adverse effects on the gut microbiota. Here, a selenized chitosan (CS-Se) modified bismuth-based metal-organic framework (Bi-MOF@CS-Se) nanodrug is reported that can target mucin through the charge interaction of the outer CS-Se layer to achieve mucosal adhesion and gastric retention. Additionally, the Bi-MOF@CS-Se can respond to gastric acid and pepsin degradation, and the exposed Bi-MOF exhibits excellent antibacterial properties against standard H. pylori as well as clinical antibiotic-resistant strains. Remarkably, the Bi-MOF@CS-Se effectively alleviates inflammation and excessive oxidative stress by regulating the expression of inflammatory factors and the production of reactive oxygen species (ROS), thereby exerting therapeutic effects against H. pylori infection. Importantly, this Bi-MOF@CS-Se nanodrug does not affect the homeostasis of gut microbiota, providing a promising strategy for efficient and safe treatment of H. pylori infection.

Deep Learning For Automatic Gross Tumor Volumes Contouring in Esophageal Cancer Based on Contrast-Enhanced Computed Tomography Images: A Multi-Institutional Study

PURPOSE

To develop and externally validate an automatic artificial intelligence (AI) tool for delineating gross tumor volume (GTV) in patients with esophageal squamous cell carcinoma (ESCC), which can assist in neo-adjuvant or radical radiation therapy treatment planning.

METHODS AND MATERIALS

In this multi-institutional study, contrast-enhanced CT images from 580 eligible ESCC patients were retrospectively collected. The GTV contours delineated by 2 experts via consensus were used as ground truth. A 3-dimensional deep learning model was developed for GTV contouring in the training cohort and internally and externally validated in 3 validation cohorts. The AI tool was compared against 12 board-certified experts in 25 patients randomly selected from the external validation cohort to evaluate its assistance in improving contouring performance and reducing variation. Contouring performance was measured using dice similarity coefficient (DSC) and average surface distance. Additionally, our previously established radiomics model for predicting pathologic complete response was used to compare AI-generated and ground truth contours, to assess the potential of the AI contouring tool in radiomics analysis.

RESULTS

The AI tool demonstrated good GTV contouring performance in multicenter validation cohorts, with median DSC values of 0.865, 0.876, and 0.866 and median average surface distance values of 0.939, 0.789, and 0.875 mm, respectively. Furthermore, the AI tool significantly improved contouring performance for half of 12 board-certified experts (DSC values, 0.794-0.835 vs 0.856-0.881, P = .003-0.048), reduced the intra- and interobserver variations by 37.4% and 55.2%, respectively, and saved contouring time by 77.6%. In the radiomics analysis, 88.7% of radiomic features from ground truth and AI-generated contours demonstrated stable reproducibility, and similar pathologic complete response prediction performance for these contours (P = .430) was observed.

CONCLUSIONS

Our AI contouring tool can improve GTV contouring performance and facilitate radiomics analysis in ESCC patients, which indicates its potential for GTV contouring during radiation therapy treatment planning and radiomics studies.

[Respiratory virus infection and its influence on outcome in children with septic shock]

Objective: To investigate respiratory virus infection in children with septic shock in pediatric care units (PICU) in China and its influence on clinical outcomes. Methods: The clinical data of children with septic shock in children's PICU from January 2018 to December 2019 in 10 Chinese hospitals were retrospectively collected. They were divided into the pre-COVID-19 and post-COVID-19 groups according to the onset of disease, and the characteristics and composition of respiratory virus in the 2 groups were compared. Matching age, malignant underlying diseases, bacteria, fungi and other viruses, a new database was generated using 1∶1 propensity score matching method. The children were divided into the respiratory virus group and non-respiratory virus group according to the presence or absence of respiratory virus infection; their clinical characteristics, diagnosis, and treatment were compared by t-test, rank sum test and Chi-square test. The correlation between respiratory virus infection and the clinical outcomes was analyzed by logistic regression. Results: A total of 1 247 children with septic shock were included in the study, of them 748 were male; the age was 37 (11, 105) months. In the pre-and post-COVID-19 groups, there were 530 and 717 cases of septic shock, respectively; the positive rate of respiratory virus was 14.9% (79 cases) and 9.8% (70 cases); the seasonal distribution of septic shock was 28.9% (153/530) and 25.9% (185/717) in autumn, and 30.3% (161/530) and 28.3% (203/717) in winter, respectively, and the corresponding positive rates of respiratory viruses were 19.6% (30/153) and 15.7% (29/185) in autumn, and 21.1% (34/161) and 15.3% (31/203) in winter, respectively. The positive rates of influenza virus and adenovirus in the post-COVID-19 group were lower than those in the pre-COVID-19 group (2.1% (15/717) vs. 7.5% (40/530), and 0.7% (5/717) vs. 3.2% (17/530), χ2=21.51 and 11.08, respectively; all P<0.05). Rhinovirus virus were higher than those in the pre-Covid-19 group (1.7% (12/717) vs. 0.2% (1/530), χ2=6.51, P=0.011). After propensity score matching, there were 147 cases in both the respiratory virus group and the non-respiratory virus group. Rate of respiratory failure, acute respiratory distress, rate of disseminated coagulation dysfunction, and immunoglobulin usage of the respiratory virus group were higher than those of non-respiratory virus group (77.6% (114/147) vs. 59.2% (87/147), 17.7% (26/147) vs. 4.1% (6/147), 15.6% (25/147) vs. 4.1% (7/147), and 35.4% (52/147) vs. 21.4% (32/147); χ2=11.07, 14.02, 11.06 and 6.67, all P<0.05); and PICU hospitalization of the former was longer than that of the later (7 (3, 16) vs. 3 (1, 7)d, Z=5.01, P<0.001). Univariate logistic regression analysis showed that the presence of respiratory viral infection was associated with respiratory failure, disseminated coagulation dysfunction, the use of mechanical ventilation, and the use of immunoglobulin and anti-respiratory viral drugs (OR=2.42, 0.22, 0.25, 0.56 and 1.12, all P<0.05). Conclusions: The composition of respiratory virus infection in children with septic shock is different between pre and post-COVID-19. Respiratory viral infection is associated with organ dysfunction in children with septic shock. Decreasing respiratory viral infection through respiratory protection may improve the clinical outcome of these children.

[Retracted] 14‑3‑3β exerts glioma‑promoting effects and is associated with malignant progression and poor prognosis in patients with glioma

[This retracts the article DOI: 10.3892/etm.2017.5664.].

Second-line antituberculosis drug exposure thresholds predictive of adverse events in multidrug-resistant tuberculosis treatment

OBJECTIVES

This study aimed to investigate the association between drug exposure and adverse events (AEs) during the standardized multidrug-resistant tuberculosis (MDR-TB) treatment, as well as to identify predictive drug exposure thresholds.

METHODS

We conducted a prospective, observational multicenter study among participants receiving standardized MDR-TB treatment between 2016 and 2019 in China. AEs were monitored throughout the treatment and their relationships to drug exposure (e.g., the area under the drug concentration-time curve from 0 to 24 h, AUC0-24 h) were analyzed. The thresholds of pharmacokinetic predictors of observed AEs were identified by boosted classification and regression tree (CART) and further evaluated by external validation.

RESULTS

Of 197 study participants, 124 (62.9%) had at least one AE, and 15 (7.6%) experienced serious AEs. The association between drug exposure and AEs was observed including bedaquiline, its metabolite M2, moxifloxacin and QTcF prolongation (QTcF >450 ms), linezolid and mitochondrial toxicity, cycloserine and psychiatric AEs. The CART-derived thresholds of AUC0-24 h predictive of the respective AEs were 3.2 mg·h/l (bedaquiline M2); 49.3 mg·h/l (moxifloxacin); 119.3 mg·h/l (linezolid); 718.7 mg·h/l (cycloserine).

CONCLUSIONS

This study demonstrated the drug exposure thresholds predictive of AEs for key drugs against MDR-TB treatment. Using the derived thresholds will provide the knowledge base for further randomized clinical trials of dose adjustment to minimize the risk of AEs.

Observation of D_{s}^{+}→η^{'}μ^{+}ν_{μ}, Precision Test of Lepton Flavor Universality with D_{s}^{+}→η^{(')}l^{+}ν_{l}, and First Measurements of D_{s}^{+}→η^{(')}μ^{+}ν_{μ} Decay Dynamics

By analyzing 7.33  fb^{-1} of e^{+}e^{-} annihilation data collected at center-of-mass energies between 4.128 and 4.226 GeV with the BESIII detector, we report the observation of the semileptonic decay D_{s}^{+}→η^{'}μ^{+}ν_{μ}, with a statistical significance larger than 10σ, and the measurements of the D_{s}^{+}→ημ^{+}ν_{μ} and D_{s}^{+}→η^{'}μ^{+}ν_{μ} decay dynamics for the first time. The branching fractions of D_{s}^{+}→ημ^{+}ν_{μ} and D_{s}^{+}→η^{'}μ^{+}ν_{μ} are determined to be (2.235±0.051_{stat}±0.052_{syst})% and (0.801±0.055_{stat}±0.028_{syst})%, respectively, with precision improved by factors of 6.0 and 6.6 compared to the previous best measurements. Combined with the results for the decays D_{s}^{+}→ηe^{+}ν_{e} and D_{s}^{+}→η^{'}e^{+}ν_{e}, the ratios of the decay widths are examined both inclusively and in several ℓ^{+}ν_{ℓ} four-momentum transfer ranges. No evidence for lepton flavor universality violation is found within the current statistics. The products of the hadronic form factors f_{+,0}^{η^{(')}}(0) and the c→s Cabibbo-Kobayashi-Maskawa matrix element |V_{cs}| are determined. The results based on the two-parameter series expansion are f_{+,0}^{η}(0)|V_{cs}|=0.452±0.010_{stat}±0.007_{syst} and f_{+,0}^{η^{'}}(0)|V_{cs}|=0.504±0.037_{stat}±0.012_{syst}, which help to constrain present models on f_{+,0}^{η^{(')}}(0). The forward-backward asymmetries are determined to be ⟨A_{FB}^{η}⟩=-0.059±0.031_{stat}±0.005_{syst} and ⟨A_{FB}^{η^{'}}⟩=-0.064±0.079_{stat}±0.006_{syst} for the first time, which are consistent with the theoretical calculation.

High-throughput detection allied with machine learning for precise monitoring of significant serum metabolic changes in Helicobacter pylori infection

High-throughput detection of large-scale samples is the foundation for rapidly accessing massive metabolic data in precision medicine. Machine learning is a powerful tool for uncovering valuable information hidden within massive data. In this work, we achieved the extraction of a single fingerprinting of 1 μL serum within 5 s through a high-throughput detection platform based on functionalized nanoparticles. We quickly obtained over a thousand serum metabolic fingerprintings (SMFs) including those of individuals with Helicobacter pylori (HP) infection. Combining four classical machine learning models and enrichment analysis, we attempted to extract and confirm useful information behind these SMFs. Based on all fingerprint signals, all four models achieved area under the curve (AUC) values of 0.983-1. In particular, orthogonal partial least squares discriminant analysis (OPLS-DA) model obtained value of 1 in both the discovery and validation sets. Fortunately, we identified six significant metabolic features, all of which can greatly contribute to the monitoring of HP infection, with AUC values ranging from 0.906 to 0.985. The combination of these six significant metabolic features can enable the precise monitoring of HP infection in serum, with over 95 % of accuracy, specificity and sensitivity. The OPLS-DA model displayed optimal performance and the corresponding scatter plot visualized the clear distinction between HP and HC. Interestingly, they exhibit a consistent reduction trend compared to healthy controls, prompting us to explore the possible metabolic pathways and potential mechanism. This work demonstrates the potential alliance between high-throughput detection and machine learning, advancing their application in precision medicine.

Extracellular Vesicles: The Invisible Heroes and Villains of COVID-19 Central Neuropathology

Acknowledging the neurological symptoms of COVID-19 and the long-lasting neurological damage even after the epidemic ends are common, necessitating ongoing vigilance. Initial investigations suggest that extracellular vesicles (EVs), which assist in the evasion of the host's immune response and achieve immune evasion in SARS-CoV-2 systemic spreading, contribute to the virus's attack on the central nervous system (CNS). The pro-inflammatory, pro-coagulant, and immunomodulatory properties of EVs contents may directly drive neuroinflammation and cerebral thrombosis in COVID-19. Additionally, EVs have attracted attention as potential candidates for targeted therapy in COVID-19 due to their innate homing properties, low immunogenicity, and ability to cross the blood-brain barrier (BBB) freely. Mesenchymal stromal/stem cell (MSCs) secreted EVs are widely applied and evaluated in patients with COVID-19 for their therapeutic effect, considering the limited antiviral treatment. This review summarizes the involvement of EVs in COVID-19 neuropathology as carriers of SARS-CoV-2 or other pathogenic contents, as predictors of COVID-19 neuropathology by transporting brain-derived substances, and as therapeutic agents by delivering biotherapeutic substances or drugs. Understanding the diverse roles of EVs in the neuropathological aspects of COVID-19 provides a comprehensive framework for developing, treating, and preventing central neuropathology and the severe consequences associated with the disease.

Octadecyl and sulfonyl modification of diatomite synergistically improved the immobilization efficiency of lipase and its application in the synthesis of pine sterol esters

Phytosterols usually have to be esterified to various phytosterol esters to avoid their disadvantages of unsatisfactory solubility and low bioavailability. The enzymatic synthesis of phytosterol esters in a solvent-free system has advantages in terms of environmental friendliness, sustainability, and selectivity. However, the limitation of the low stability and recyclability of the lipase in the solvent-free system, which often requires a relatively high temperature to induce the viscosity, also increased the industrial production cost. In this context, a low-cost material, namely diatomite, was employed as the support in the immobilization of Candida rugosa lipase (CRL) due to its multiple modification sites. The Fe3 O4 was also then introduced to this system for quick and simple separation via the magnetic field. Moreover, to further enhance the immobilization efficiency of diatomite, a modification strategy which involved the octadecyl and sulfonyl group for regulating the hydrophobicity and interaction between the support and lipase was successfully developed. The optimization of the ratio of the modifiers suggested that the -SO3 H/C18 (1:1.5) performed best with an enzyme loading and enzyme activity of 84.8 mg·g-1 and 54 U·g-1 , respectively. Compared with free CRL, the thermal and storage stability of CRL@OSMD was significantly improved, which lays the foundation for the catalytic synthesis of phytosterol esters in solvent-free systems. Fortunately, a yield of 95.0% was achieved after optimizing the reaction conditions, and a yield of 70.0% can still be maintained after six cycles.

Novel exosomal circEGFR facilitates triple negative breast cancer autophagy via promoting TFEB nuclear trafficking and modulating miR-224-5p/ATG13/ULK1 feedback loop

Triple-negative breast cancer (TNBC) cells are in a more hypoxic and starved state than non-TNBC cells, which makes TNBC cells always maintain high autophagy levels. Emerging evidence has demonstrated that circular RNAs (circRNAs) are involved in the progress of tumorigenesis. However, the regulation and functions of autophagy-induced circRNAs in TNBC remain unclear. In our study, autophagy-responsive circRNA candidates in TNBC cells under amino acid starved were identified by RNA sequencing. The results showed that circEGFR expression was significantly upregulated in autophagic cells. Knockdown of circEGFR inhibited autophagy in TNBC cells, and circEGFR derived from exosomes induced autophagy in recipient cells in the tumor microenvironment. In vitro and in vivo functional assays identified circEGFR as an oncogenic circRNA in TNBC. Clinically, circEGFR was significantly upregulated in TNBC and was positively associated with lymph node metastasis. CircEGFR in plasma-derived exosomes was upregulated in breast cancer patients compared with healthy people. Mechanistically, circEGFR facilitated the translocation of Annexin A2 (ANXA2) toward the plasma membrane in TNBC cells, which led to the release of Transcription Factor EB (a transcription factor of autophagy-related proteins, TFEB) from ANXA2-TFEB complex, causing nuclear translocation of TFEB, thereby promoting autophagy in TNBC cells. Meanwhile, circEGFR acted as ceRNA by directly binding to miR-224-5p and inhibited the expression of miR-224-5p, which weakened the suppressive role of miR-224-5p/ATG13/ULK1 axis on autophagy. Overall, our study demonstrates the key role of circEGFR in autophagy, malignant progression, and metastasis of TNBC. These indicate circEGFR is a potential diagnosis biomarker and therapeutic target for TNBC.

Analysis of the effectiveness of PDT with 5-aminolevulinic acid in comparison to blue/red light combined with intralesional triamcinolone injection in treatment of severe inflammatory acne: A retrospective study

OBJECTIVE

In this study, the therapeutic effect of 5-aminolevulinic acid photodynamic therapy (ALA-PDT) in comparison to blue/red light combined with intralesional triamcinolone injection for severe inflammatory acne was evaluated and analyzed.

METHODS

One hundred and four cases of severe inflammatory acne were analyzed in this study. They were divided into two groups as control and observation groups, 52 cases in each group. The control group (group A) received red and blue light combined with triamcinolone injection and lidocaine injection (1:4), while the observation group (Group B) was treated with ALA-PDT. Finally, the therapeutic effect and the occurrence of adverse reactions were compared between the two groups.

RESULTS

After 2, 4 and 6 weeks, the effectiveness rates of group B was 28.85%, 75.00%, and 86.54%, respectively while it was 9.62%, 51.92%, and 69.23%, respectively in group A. The difference between A and B was statistically remarkable (χ2 = 6.1905, 5.9713, 4.5217, p = 0.0128, 0.0145, 0.0335 at p < 0.05). In addition, the incidence of adverse reactions in B was 5.77%, lower than A (32.69%). This difference between A and B was statistically remarkable (χ2  = 12.1333, p = 0.0005). After 2, 4, and 6 weeks of treatment, the number of residual lesions in the group B group was remarkably lower than group A (p < 0.01). There was remarkable difference in the incidence of pain, burning sensation, pigmentation and erythema between the two groups.

CONCLUSIONS

The therapeutic effect of ALA-PDT in the treatment of severe acne is better than red blue light combined with triamcinolone injection and lidocaine injection. In addition, ALA-PDT has an ideal effect in the treatment of severe acne.

Immunotherapy for advanced non-small cell lung cancer with negative programmed death-ligand 1 expression: a literature review

Background and Objective

Lung cancer, mainly non-small cell lung cancer (NSCLC), is a serious threat to human life. In particular, the prognosis for advanced patients is poor, with the 5-year survival rate being exceedingly low. In recent years, immune checkpoint inhibition has changed the pattern of the treatment of a variety of cancers, including lung cancer; however, not all patients can benefit from immunotherapy, and thus finding the right biomarkers is particularly important for guiding precise treatment. Programmed death-ligand 1 (PD-L1) expression is one of the most valuable biomarkers for predicting the efficacy of lung cancer immunotherapy. Several studies have confirmed that patients with high PD-L1 expression are more likely to benefit from immunotherapy, but there is a high proportion of people with negative PD-L1 expression constituting a patient population that cannot be ignored. This article reviews the distribution of PD-L1 expression, the methods for evaluating PD-L1, and the effectiveness of immunotherapy for advanced NSCLC with negative PD-L1 expression.

Methods

We performed a literature review to identify relevant data published until September 2022. In order to organize related information, we searched for literature in PubMed; abstracts and reports published in the American Society of Clinical Oncology (ASCO), the European Society for Medical Oncology (ESMO), the World Conference on Lung Cancer (WCLC), and other congresses; and clinical trial information registered on ClinicalTrials.gov. Information on the distribution of PD-L1 expression, detection of PD-L1, and immunotherapy efficacy for NSCLC with negative PD-L1 expression was collated and reviewed.

Key Content and Findings

The incidence of PD-L1 expression in patients with stage IIIB/IV NSCLC is similar in all regions of the world, but PD-L1 expression level is associated with certain clinicopathological features. The expression of PD-L1 can be evaluated by various detecting methods. Some immunotherapy regimens have better efficacy than traditional chemotherapy in patients with negative PD-L1 expression.

Conclusions

Patients with NSCLC and negative PD-L1 expression can receive better survival benefits under some immunotherapy types, and these may represent a better treatment option for this relatively small patient population.

Elevated risk of multimorbidity post-COVID-19 infection: protective effect of vaccination

BACKGROUND

It is unclear how the coronavirus disease 2019 (Covid-19) pandemic has affected multimorbidity incidence among those with one pre-existing chronic condition, as well as how vaccination could modify this association.

AIM

To examine the association of Covid-19 infection with multimorbidity incidence among people with one pre-existing chronic condition, including those with prior vaccination.

DESIGN

Nested case-control study.

METHODS

We conducted a territory-wide nested case-control study with incidence density sampling using Hong Kong electronic health records from public healthcare facilities and mandatory Covid-19 reports. People with one listed chronic condition (based on a list of 30) who developed multimorbidity during 1 January 2020-15 November 2022 were selected as case participants and randomly matched with up to 10 people of the same age, sex and with the same first chronic condition without having developed multimorbidity at that point. Conditional logistic regression was used to estimate adjusted odds ratios (aORs) of multimorbidity.

RESULTS

In total, 127 744 case participants were matched with 1 230 636 control participants. Adjusted analysis showed that there were 28%-increased odds of multimorbidity following Covid-19 [confidence interval (CI) 22% to 36%] but only 3% (non-significant) with prior full vaccination with BNT162b2 or CoronaVac (95% CI -2% to 7%). Similar associations were observed in men, women, older people aged 65 or more, and people aged 64 or younger.

CONCLUSIONS

We found a significantly elevated risk of multimorbidity following a Covid-19 episode among people with one pre-existing chronic condition. Full vaccination significantly reduced this risk increase.

Determination of the Σ^{+} Timelike Electromagnetic Form Factors

Based on data samples collected with the BESIII detector at the BEPCII collider, the process e^{+}e^{-}→Σ^{+}Σ[over ¯]^{-} is studied at center-of-mass energies sqrt[s]=2.3960, 2.6454, and 2.9000 GeV. Using a fully differential angular description of the final state particles, both the relative magnitude and phase information of the Σ^{+} electromagnetic form factors in the timelike region are extracted. The relative phase between the electric and magnetic form factors is determined to be sinΔΦ=-0.67±0.29(stat)±0.18(syst) at sqrt[s]=2.3960  GeV, ΔΦ=55°±19°(stat)±14°(syst) at sqrt[s]=2.6454  GeV, and 78°±22°(stat)±9°(syst) at sqrt[s]=2.9000  GeV. For the first time, the phase of the hyperon electromagnetic form factors is explored in a wide range of four-momentum transfer. The evolution of the phase along with four-momentum transfer is an important input for understanding its asymptotic behavior and the dynamics of baryons.