Objective To explore the application effect of multi-disciplinary team(MDT)model in hospital antimi-crobial management.Methods Relevant data on antimicrobial use in hospitalized patients in a hospital from January 2021 to December 2022 were analyzed retrospectively,January-December 2021 adopted conventional management mode and was as the control group,January-December 2022 adopted MDT management model and was as the inter-vention group.Antimicrobial therapy relevant indicators between two groups of patients were compared.Results After adopting the MDT management model,pathogen detection rate before the therapeutic antimicrobial use in the intervention group(73.62％)was higher than that in the control group(70.56％),difference was statistically sig-nificant(P＜0.001).Pathogen detection rate related to healthcare-associated infection diagnosis was 87.98％in the control group and 88.89％in the intervention group,with no statistically significant difference between two groups(P＞0.05).Pathogen detection rate before combined use of key antimicrobial agents in the intervention group(93.94％)was higher than that in the control group(92.00％),difference was statistically significant(P＜0.05).Antimicro-bial use rate in hospitalized patients and use rate of prophylactic antimicrobial agents in class Ⅰ incision surgery de-creased from 38.03％and 21.03％to 32.78％and 10.30％,respectively,with statistically significant differences(both P＜0.05).The amount and intensity of antimicrobial use in hospitalized patients in the intervention group de-creased.The implementation rate of bundled prevention and control measures for multidrug-resistant organism(MDRO)after intervention was significantly higher than that of the control group,with statistically significant differences(all P＜0.05).MDRO detection rate decreased from 34.70％to 32.37％,difference was statistically significant(P=0.027).there was no significant change in the MDRO case infection rate.Conclusion The MDT model can effectively improve the standardized management of antimicrobial agents,promote the rational use of anti-microbial agents in clinical practice,and prevent bacterial resistance.

Mammals exhibit limited heart regeneration ability, which can lead to heart failure after myocardial infarction. In contrast, zebrafish exhibit remarkable cardiac regeneration capacity. Several cell types and signaling pathways have been reported to participate in this process. However, a comprehensive analysis of how different cells and signals interact and coordinate to regulate cardiac regeneration is unavailable. We collected major cardiac cell types from zebrafish and performed high-precision single-cell transcriptome analyses during both development and post-injury regeneration. We revealed the cellular heterogeneity as well as the molecular progress of cardiomyocytes during these processes, and identified a subtype of atrial cardiomyocyte exhibiting a stem-like state which may transdifferentiate into ventricular cardiomyocytes during regeneration. Furthermore, we identified a regeneration-induced cell (RIC) population in the epicardium-derived cells (EPDC), and demonstrated Angiopoietin 4 (Angpt4) as a specific regulator of heart regeneration. angpt4 expression is specifically and transiently activated in RIC, which initiates a signaling cascade from EPDC to endocardium through the Tie2-MAPK pathway, and further induces activation of cathepsin K in cardiomyocytes through RA signaling. Loss of angpt4 leads to defects in scar tissue resolution and cardiomyocyte proliferation, while overexpression of angpt4 accelerates regeneration. Furthermore, we found that ANGPT4 could enhance proliferation of neonatal rat cardiomyocytes, and promote cardiac repair in mice after myocardial infarction, indicating that the function of Angpt4 is conserved in mammals. Our study provides a mechanistic understanding of heart regeneration at single-cell precision, identifies Angpt4 as a key regulator of cardiomyocyte proliferation and regeneration, and offers a novel therapeutic target for improved recovery after human heart injuries.
Humans ; Mice ; Rats ; Cell Proliferation ; Heart/physiology* ; Mammals ; Myocardial Infarction/metabolism* ; Myocytes, Cardiac/metabolism* ; Pericardium/metabolism* ; Single-Cell Analysis ; Zebrafish/metabolism*

Objective: To analyze and compare therapy responses, outcomes, and incidence of severe hematologic adverse events of flumatinib and imatinib in patients newly diagnosed with chronic phase chronic myeloid leukemia (CML) . Methods: Data of patients with chronic phase CML diagnosed between January 2006 and November 2022 from 76 centers, aged ≥18 years, and received initial flumatinib or imatinib therapy within 6 months after diagnosis in China were retrospectively interrogated. Propensity score matching (PSM) analysis was performed to reduce the bias of the initial TKI selection, and the therapy responses and outcomes of patients receiving initial flumatinib or imatinib therapy were compared. Results: A total of 4 833 adult patients with CML receiving initial imatinib (n=4 380) or flumatinib (n=453) therapy were included in the study. In the imatinib cohort, the median follow-up time was 54 [interquartile range (IQR), 31-85] months, and the 7-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.2%, 88.4%, 78.3%, and 63.0%, respectively. The 7-year FFS, PFS, and OS rates were 71.8%, 93.0%, and 96.9%, respectively. With the median follow-up of 18 (IQR, 13-25) months in the flumatinib cohort, the 2-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.4%, 86.5%, 58.4%, and 46.6%, respectively. The 2-year FFS, PFS, and OS rates were 80.1%, 95.0%, and 99.5%, respectively. The PSM analysis indicated that patients receiving initial flumatinib therapy had significantly higher cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) and higher probabilities of FFS than those receiving the initial imatinib therapy (all P<0.001), whereas the PFS (P=0.230) and OS (P=0.268) were comparable between the two cohorts. The incidence of severe hematologic adverse events (grade≥Ⅲ) was comparable in the two cohorts. Conclusion: Patients receiving initial flumatinib therapy had higher cumulative incidences of therapy responses and higher probability of FFS than those receiving initial imatinib therapy, whereas the incidence of severe hematologic adverse events was comparable between the two cohorts.
Adult ; Humans ; Adolescent ; Imatinib Mesylate/adverse effects* ; Incidence ; Antineoplastic Agents/adverse effects* ; Retrospective Studies ; Pyrimidines/adverse effects* ; Leukemia, Myelogenous, Chronic, BCR-ABL Positive/drug therapy* ; Treatment Outcome ; Benzamides/adverse effects* ; Leukemia, Myeloid, Chronic-Phase/drug therapy* ; Aminopyridines/therapeutic use* ; Protein Kinase Inhibitors/therapeutic use*

Objective Bioinformatics techniques were used to analyze the key genes that affect the survival of patients with breast cancer,so as to provide theoretical basis for the prognosis evaluation and targeted therapy of breast cancer.Methods The dif-ferentially expressed genes between breast cancer samples and normal breast samples were screened by TCGA database,enriched and analyzed by gene ontology(GO)and Kyoto Encyclopedia of Gene and Genome(KEGG).The protein-protein interaction network was constructed and the key genes were screened.The Kaplan-Meier method was used to find and verify the genes that might be used as potential prognostic biomarkers for breast cancer,and to explore the correlation between prognostic target genes and molecular typing and staging.The Timer database was used to analyze the correlation between prognosis-related target genes and immune cell infiltra-tion.Results A total of 1,285 differentially expressed genes were screened,including 318 up-regulated genes and 967 down-regu-lated genes(|log2FC| ≥ 1,P＜0.05).Differentially expressed genes were mainly enriched in cytokine-cytokine receptor interac-tions,PI3K-AKT signaling pathway,cAMP signaling pathway,and so on.A total of 10 key genes(AURKB,CDC20,CCNA2,NCAPG,BUB1,TOP2A,BUB1B,CCNB1,CDK1,and KIF11)were screened from the protein interaction network.Among them,the ex-pression of CCNA2,NCAPG and BUB1 in breast cancer tissues were higher than those in normal tissues.Their high expression was as-sociated with the poor prognosis of patient's overall survival(P＜0.05),and was significantly associated with the molecular typing and staging of breast cancer.The results of immune infiltration showed a significant correlation between the expression of CCNA2,NCAPG,BUB1 and the infiltration of immune cells such as B lymphocytes,CD8+T lymphocytes,neutrophils,dendritic cells and other immune cells.Conclusion CCNA2,NCAPG and BUB1 may be key genes in the occurrence and development of breast cancer,and their high expression is related to poor prognosis of breast cancer patients,which can be used as potential biomarkers for the prognosis of breast cancer.

OBJECTIVE: This study aimed to determine the HIV-1 subtype distribution and HIV drug resistance (HIVDR) in patients with ART failure from 2014 to 2020 in Hainan, China. METHODS: A 7-year cross-sectional study was conducted among HIV/AIDS patients with ART failure in Hainan. We used online subtyping tools and the maximum likelihood phylogenetic tree to confirm the HIV subtypes with pol sequences. Drug resistance mutations (DRMs) were analyzed using the Stanford University HIV Drug Resistance Database. RESULTS: A total of 307 HIV-infected patients with ART failure were included, and 241 available pol sequences were obtained. Among 241 patients, CRF01_AE accounted for 68.88%, followed by CRF07_BC (17.00%) and eight other subtypes (14.12%). The overall prevalence of HIVDR was 61.41%, and the HIVDR against non-nucleoside reverse transcriptase inhibitors (NNRTIs), nucleotide reverse transcriptase inhibitors (NRTIs), and protease inhibitors (PIs) were 59.75%, 45.64%, and 2.49%, respectively. Unemployed patients, hypoimmunity or opportunistic infections in individuals, and samples from 2017 to 2020 increased the odd ratios of HIVDR. Also, HIVDR was less likely to affect female patients. The common DRMs to NNRTIs were K103N (21.99%) and Y181C (20.33%), and M184V (28.21%) and K65R (19.09%) were the main DRMs against NRTIs. CONCLUSION The present study highlights the HIV-1 subtype diversity in Hainan and the importance of HIVDR surveillance over a long period.
Humans ; Reverse Transcriptase Inhibitors/therapeutic use* ; HIV-1/genetics* ; Cross-Sectional Studies ; Phylogeny ; Anti-HIV Agents/therapeutic use* ; Drug Resistance, Viral/genetics* ; HIV Infections/epidemiology* ; Mutation ; China/epidemiology* ; Prevalence ; Genotype

The pathogenesis of Sjögren's syndrome （SS） was considered to involve external dryness， internal injured essence and blood， yin-deficiency endowment， and abnormal emotion and spirit， and it was believed that SS has the characteristics of dryness and impassability， and the pathogenesis of deficiency-excess in complexity. According to the theory “upper dryness treats qi， and lower dryness treats blood” in YE Gui's monograph “Medical Records for Clinical Guidance”， the dryness was divided into upper dryness and lower dryness syndromes to be differentiated and treated. When treating dryness syndrome， the patient should follow the characteristics of the five zang organs， using soft and cool medicines， avoiding warm and dry medicines， and valuing the animal products. The upper dryness could be treated with Sangxiang Decoction （桑杏汤） to clear the qi and moisten the dryness， Qiaohe Decoction （翘荷汤） to clear the upper with pungent-cool， and Shashen Maidong Decoction （沙参麦冬汤） to nourish yin and promote the production of body fluid. The lower dryness could be treated with Fumai Decoction （复脉汤） to enrich and nourish the five kinds of fluid. Liuwei Dihuang Pill （六味地黄丸） to nourish the kidneys and supplement essence， and Wuren Pill （五仁丸） to moisten the dryness and nourish the blood， which provided a new way of thinking for differentiation of the dryness syndrome.

Objective:To establish a predictive model for preoperative diagnosis of benign and malignant phyllodes tumor of the breast(PTB). Methods:The clinicopathological data of 69 patients with benign PTB and 41 patients with malignant PTB(24 borderline and 17 malignant)who underwent multiple(≥2)preoperative ultrasound follow-ups in the Cancer Hospital of Harbin Medical University from January 2011 to December 2018 were retrospectively analyzed.The preoperative prediction models of benign and malignant PTB were constructed by using the influencing factors determined by multivariate logistic regression analysis.The receiver operating characteristic(ROC)curve was used to evaluate the efficiency of the prediction model.In addition,the clinicopathological data of 22 patients of benign PTB and 19 patients of malignant PTB(12 borderline and 7 malignant)admitted to the hospital from January 2019 to April 2022 were selected for external verification. Results:Logistic regression analysis showed that growth rate of tumor>2 mm/month and ultrasound BI-RADS category≥4b were independent predictors for the diagnosis of malignant PTB(OR:4.476,95％CI:1.673～11.975;OR:9.448,95％CI:3.149～28.345;P<0.01).The logistic regression equation:Logit(P)=-1.868+1.499×growth rate of tumor+2.246×ultrasound BI-RADS category.The AUC for the training cohort was 0.795(95％CI:0.699～0.890),the best cut-off value was 0.421,the corresponding sensitivity was 0.732,the specificity was 0.826,and the Jorden index was 0.558,P<0.001.The AUC for the the validation cohort was 0.772(95％CI:0.624～0.919),with the sensitivity of 0.526 and the specificity of 0.773,positive predictive value was 0.667 and negative predictive value was 0.654,P = 0.003.The AUC of the training cohort and the validation cohort were both>0.75,indicating that the model has certain predictive ability. Conclusion:The predictive model constructed by clinicopathological parameters can be used for preoperative diagnosis of benign PTB and malignant PTB,and provide a certain reference value for clinicians to select the appropriate surgical resection scope.

A fungal strain WXF1904, was isolated from a starfish sample corrected in the South China Sea. According to its internal transcribed spacer (ITS) analysis, the strain was identified as a member of the genus Aspergillus and designated as Aspergillus sp. WXF1904. One new isocoumarin containing halogennamed 6-chloro-5,7-dihydroxy-3,8-dimethylisocoumarin (1), along with six known compounds pilobolusate (2), p-hydroxybenzaldehyde (3), methyl orsellinate (4), catechol (5), vanillic acid (6), and wasabidienone E (7), were isolated from the cultures of Aspergillus sp. WXF1904 by silica gel column chromatography, ODS gel column chromatography, and high performance liquid chromatography (HPLC). Their structures were elucidated by high resolution mass spectrometry (HR-MS), nuclear magnetic resonance (NMR) as well as literature comparison. The new compound 5-chloro-6,7-dihydroxy-3,8-dimethylisocoumarin and compound 2 showed weak acetylcholinesterase inhibitory activity.

Taking the Chinese city of Xiamen as an example, simulation and quantitative analysis were performed on the transmissions of the Coronavirus Disease 2019 (COVID-19) and the influence of intervention combinations to assist policymakers in the preparation of targeted response measures. A machine learning model was built to estimate the effectiveness of interventions and simulate transmission in different scenarios. The comparison was conducted between simulated and real cases in Xiamen. A web interface with adjustable parameters, including choice of intervention measures, intervention weights, vaccination, and viral variants, was designed for users to run the simulation. The total case number was set as the outcome. The cumulative number was 4,614,641 without restrictions and 78 under the strictest intervention set. Simulation with the parameters closest to the real situation of the Xiamen outbreak was performed to verify the accuracy and reliability of the model. The simulation model generated a duration of 52 days before the daily cases dropped to zero and the final cumulative case number of 200, which were 25 more days and 36 fewer cases than the real situation, respectively. Targeted interventions could benefit the prevention and control of COVID-19 outbreak while safeguarding public health and mitigating impacts on people's livelihood.
COVID-19/prevention & control* ; China/epidemiology* ; Humans ; Machine Learning ; Pandemics/prevention & control* ; Policy ; Reproducibility of Results ; SARS-CoV-2

Cystine/glutamate antiporter [system Xc(-)] is a sodium independent amino acid transporter, which is a heterodimer composed of light chain subunit xCT and heavy chain subunit 4F2hc (CD98) through covalent disulfide bond. System Xc(-) typically mediates cystine uptake and glutamate output, helps to maintain the balance of glutamate, cystine and cysteine inside and outside the cell, regulates the level of glutamate inside and outside the membrane and the synthesis of intracellular glutathione, thus affecting oxidative stress and glutamate neurotoxicity. This review expounds the structure and function of system Xc(-), analyzes the role of the transporter in physiology and pathology, discusses the role and mechanism in different diseases, and discusses the specific research progress of system Xc(-) as a drug target. This review summarizes the research status of system Xc(-) and provides theoretical guidance for further research on system Xc(-) and drug discovery.