Objective: To establish a rapid, accurate, and decentralized workflow for bacterial whole-genome sequencing (WGS) and risk profiling within the shelf-life of platelet concentrates, and to characterize the species, virulence, antimicrobial resistance (AMR), and immune evasion mechanisms of co-existing bacteria in qualified platelet products, thereby providing a scientific basis for transfusion safety assessment. Methods: Three units of platelet concentrates, which tested negative by routine bacterial screening, were collected from the Chengdu Blood Center between May and June 2025. Samples were enriched at 37℃under six aerobic and nine anaerobic conditions for 7 days. Using a culturomics strategy, aliquots were plated for isolation on days 1, 3, 5, and 7 to obtain cultivable isolates, with negative culture controls included to exclude contamination. High-molecular-weight genomic DNA was extracted via mechanical grinding, purified, and size-selected. Sequencing libraries were constructed and sequenced on the G-seq500 single-molecule nanopore sequencing platform. Genomes were assembled using Flye and polished with NextPolish, with quality evaluated by BUSCO and CheckM. Taxonomic identification was performed using GTDB-Tk. Functional annotation and database comparisons were conducted to analyze virulence factors, AMR genes, and genes related to immune evasion and environmental adaptation. Results: Viable bacteria were successfully isolated from all three qualified platelet units within their shelf life. The isolates were identified as Bacillus albus, Niallia taxi, and Staphylococcus warneri. Nanopore sequencing generated 92 227-109 813 reads (totaling 680-758 Mb) with an N50 of 7 625-8 584 bp and Q20/Q30 scores of 97%/93%, respectively. All three genomes were assembled into complete circular chromosomes with 1-3 plasmids, achieving >93% completeness. Functional analysis revealed that B. albus carried multiple hemolysins, metalloproteases, and multidrug resistance genes, indicating the highest potential pathogenicity and AMR risk. S. warneri exhibited a typical multidrug resistance profile and regulatory network characteristic of coagulase-negative staphylococci, suggesting intermediate virulence. N. taxi harbored few canonical virulence factors and lacked functional AMR determinants, presenting a "low-virulence, low-resistance" profile. Notably, all three strains were enriched in genes encoding antimicrobial peptide resistance systems (e.g., dltABCD, mprF, GraRS, BceAB) and antioxidant enzymes, suggesting a strong capacity to withstand immune stress in the blood environment. Conclusion: Viable bacteria can be recovered from qualified platelet concentrates that test negative by routine screening. Nanopore WGS enables rapid strain-level identification and comprehensive risk profiling of virulence, resistance, and immune adaptation traits. The functional repertoires of these "co-existing" isolates range from environmental adaptation to potential pathogenicity, representing an underappreciated risk for transfusion-transmitted infections in susceptible recipients.

Objective:To investigate the association between estimated cumulative low-density lipoprotein cholesterol (LDL-C) exposure and the severity of coronary artery disease and long-term adverse cardiovascular and cerebrovascular events (MACCE) in patients with acute coronary syndrome (ACS).Methods:The subjects were from the PROMISE study. This study was a prospective cohort study led by Fuwai Hospital, Chinese Academy of Medical Sciences, with participation from eight regional tertiary hospitals as sub-centers, and enrolled 18 701 patients with confirmed coronary heart disease between January 2015 and May 2019. Among them, 8 429 patients with ACS were included in this study. The estimated cumulative LDL-C exposure was calculated by multiplying LDL-C by age. Participants were then divided into four groups based on quartiles. Baseline data and coronary angiography data were collected, and participants were followed for 2 years. The primary endpoint was MACCE, which was composed of all-cause death, cardiac death, myocardial infarction, revascularization, and stroke. Spearman correlation analysis was used to estimate the correlation between cumulative LDL-C exposure and the severity of coronary artery disease. The differences in MACCE among the four groups were compared, and multivariate Cox regression was used to divide the estimated cumulative exposure LDL-C into two groups, three groups, and four groups to analyze its relationship with MACCE.Results:The 8 429 ACS patients included in the study had an age of (60.9±11.4) years, with 1 951(23.1%) females. Spearman correlation analysis revealed that estimated cumulative LDL-C exposure was positively associated with the preoperative SYNTAX score, three-vessel lesions disease, left main disease, and the number of target lesions (correlation coefficients r=0.14, 0.10, 0.04 and 0.03, respectively, with all P<0.05). The 2-year follow-up results indicated that the incidence rates of MACCE, all-cause death, cardiac death, myocardial infarction, and stroke in ACS patients grouped by different levels of estimated cumulative LDL-C exposure were statistically significant (all P<0.05). The results of the Cox multivariate regression analysis showed that when the estimated cumulative LDL-C exposure was treated as a continuous variable and analyzed in two, three, and four groups, with the lowest group as the reference, the risk of MACCE occurrence in the high-value group increased by 21% (95% CI 1.08-1.37, P=0.002), 24% (95% CI 1.07-1.43, P=0.004), and 21% (95% CI 1.02-1.43, P=0.025) respectively. Conclusions:A positive correlation was found between estimated cumulative LDL-C exposure and severity of coronary artery disease. High estimated cumulative LDL-C exposure level is a risk factor for MACCE in ACS patients within 2 years.

Objective : To investigate the diagnostic value of plasma calprotectin in childern with refractory mycoplasma pneumoniae pneumonia(RMPP). Methods : A multicenter, prospective cohort study was conducted, enrolling 228 children with mycoplasma pneumoniae pneumonia(MPP). Among these, 177 cases were diagnosed with general mycoplasma pneumoniae pneumonia(GMPP), while the remaining 51 cases were RMPP. Plasma was collected at the time of admission of the children in both groups, and calprotectin levels were measured. A one-way difference analysis was performed on the blood test indexes of the children in the two groups, and the difference variables withP<0.05 between the two groups were included in a multifactorial logistic regression to analyze the risk factors for the progression of GMPP to RMPP. The differential diagnostic value of plasma calprotectin for GMPP and RMPP was analyzed by the receiver operating characteristic(ROC) curves. Results : Univariate analysis showed that plasma calprotectin levels were significantly higher in the RMPP group than those in the GMPP group, and the difference was statistically significant(P<0.05). Logistic regression analysis showed that plasma calprotectin was an independent risk factor for RMPP(OR=1.323,P<0.001), ROC curve analysis showed that plasma calprotectin had a higher diagnostic value for the differential diagnosis of GMPP and RMPP(AUC =0.839), and its combination with C-reactive protein and albumin could significantly improve the diagnostic efficiency. Conclusion Plasma calprotectin has good clinical value for the diagnosis of RMPP.

Objective:To develop a treatment-related quality of life scale for Chinese patients with multiple myeloma (MM) and to test its reliability and validity.Methods:The initial scale was constructed through a literature search, Delphi expert correspondence, and cognitive testing. This study conducted a preliminary survey of 379 patients with MM and a formal survey of 865 patients from the hematology departments of 155 hospitals nationwide from February 2024 to March 2024. The final scale was obtained after conducting item analysis and reliability and validity tests on the initial scale.Results:The constructed scale contains 36 items covering six domains: physiological, psychological, social, treatment side effects, general health, and others. In the preliminary survey, the Cronbach’s alpha coefficient of each item ranged from 0.597 to 0.939, and the test-retest reliability was 0.747 ( P<0.001). Exploratory factor analysis extracted eight common factors with a cumulative variance contribution of 60.058%. In the formal survey, the Cronbach’s alpha coefficient of each item ranged from 0.484 to 0.930, and the test-retest reliability was 0.835 ( P<0.001). Confirmatory factor analysis revealed a comparative fit index of 0.750, a root-mean-square error of approximation of 0.090, and a root-mean-square residual of 0.067. Conclusion:The treatment-related quality of life scale for Chinese patients with MM designed in this study exhibited good reliability and validity, reflecting the impact of treatment on the quality of life of patients. This scale can provide a reference to clinicians for assessing the disease status of patients.

Objective:To systematically review the progress in the method development and application of distributed learning in the estimation of epidemiological effect and provide methodological reference for multi-center studies.Methods:We conducted a literature retrieval for English papers published up to December 31, 2023 by using keywords of "health/medical big data" and "distributed/federated learning". After consulting experts, we set criteria of paper inclusion and exclusion and created a framework for data extraction. We collected information about basic study details, including method, application, and evaluation. Two researchers independently screened the papers and extracted information. We used EndNote 20 for the management of literatures and EpiData for the management of data.Results:A total of 3 444 papers were collected, and 29 papers were included in the final analysis. Most of the papers (25, 86.2%) were published in or after 2019, and the papers were mainly from the United States (21/29, 72.4%). For the estimation of epidemiological effects, 22 distributed learning methods had been developed, including methods for logistic regression (8), Cox regression (8), Poisson regression (2), and generalized linear mixed model (GLMM) (4), as well as three platforms for distributed analysis (VLP, Vantage6, AusCAT). The 29 papers described 45 applications, with 20 (44.4%) focusing on the establishment of prediction model and 25 (55.6%) on association analysis. Importantly, except for GLMM, current distributed learning methods can estimate effects with little bias in 1-3 rounds of communication. These methods show less bias compared with meta-analysis, especially in the address of data heterogeneity and rare outcomes. However, less studies examined how differences in data structure and sparse data affect results, an area that requires further research.Conclusion:While distributed learning shows promise in epidemiological effect estimation, it is still in early development, requiring further research on data heterogeneity handling and communication efficiency improvement.

Objective:To investigate the prevalence,related factors,and career implications of occupational burnout among resident physicians during standardized training in Inner Mongolia.Methods:This cross-sectional study used convenience sampling to enroll 2 891 resident physicians,assessing them with a self-developed general information questionnaire,socio-psychological scales,and a universal burnout inventory.Latent profile analysis clas-sified participants based on burnout dimensions,while logistic regression models examined the factors influencing burnout and their relationship with career choices.Results:Resident physicians were divided into low(59.0％),moderate(28.9％),and high(12.1％)burnout subgroups.Logistic regression showed that,compared to the low burnout group,significant risk factors included professional master's students(OR=0.44),working＞70 hours weekly(OR=0.63),＞4 night shifts monthly(OR=0.66),anxiety(mild OR=0.49;moderate OR=0.26;se-vere OR=0.14),depression(mild OR=0.38;moderate OR=0.24;severe OR=0.11),insomnia(mild OR=0.51;moderate OR=0.44;severe OR=0.38),low social support(OR=0.23),and low happiness index(OR=0.42).Male residents(OR=1.25)were less likely to experience burnout.High burnout residents were 5.11 times more likely to quit the medical profession.Conclusion:Training intensity and socio-psychological factors signifi-cantly contribute resident physicians' burnout levels,with severe burnout increase career attrition.

Nipah virus (NiV) and related viruses form a distinct henipavirus genus within the Paramyxoviridae family. NiV continues to spillover into the humans causing deadly outbreaks with increasing human-bat interaction. NiV encodes the large protein (L) and phosphoprotein (P) to form the viral RNA polymerase machinery. Their sequences show limited homologies to those of non-henipavirus paramyxoviruses. We report two cryo-electron microscopy (cryo-EM) structures of the Nipah virus (NiV) polymerase L-P complex, expressed and purified in either its full-length or truncated form. The structures resolve the RNA-dependent RNA polymerase (RdRp) and polyribonucleotidyl transferase (PRNTase) domains of the L protein, as well as a tetrameric P protein bundle bound to the L-RdRp domain. L-protein C-terminal regions are unresolved, indicating flexibility. Two PRNTase domain zinc-binding sites, conserved in most Mononegavirales, are confirmed essential for NiV polymerase activity. The structures further reveal anchoring of the P protein bundle and P protein X domain (XD) linkers on L, via an interaction pattern distinct among Paramyxoviridae. These interactions facilitate binding of a P protein XD linker in the nucleotide entry channel and distinct positioning of other XD linkers. We show that the disruption of the L-P interactions reduces NiV polymerase activity. The reported structures should facilitate rational antiviral-drug discovery and provide a guide for the functional study of NiV polymerase.
Nipah Virus/chemistry* ; Cryoelectron Microscopy ; Viral Proteins/genetics* ; RNA-Dependent RNA Polymerase/genetics* ; Phosphoproteins/genetics* ; Humans ; Models, Molecular ; Protein Binding

With the development of society and changes in people's lifestyles, diabetes mellitus (DM) has become a major risk factor threatening human health, with its incidence rate increasing year by year. Based on the theory of "excessive fire consumes qi while mild fire generates qi", combined with the pathological mechanism and symptom characteristics of DM complicated with heart failure (HF), it is considered that deficiency and insufficiency of "less fire" and excessive "strong fire" consume qi are the fundamental pathogenesis of the occurrence and development of the two diseases. Phlegm, dampness, blood stasis and water are all from this, which further aggravates the disease. The basic treatment principle of "tonifying qi, activating yang, supporting Shao fire, clearing heat, detoxifying and strengthening fire" was proposed. Combined with the different emphasis of patients' syndromes, the treatment methods of promoting blood circulation and removing blood stasis, diuresis and phlegm were supplemented, in order to improve the clinical symptoms of patients and improve the survival rate.

Objective:To systematically review the progress in the method development and application of distributed learning in the estimation of epidemiological effect and provide methodological reference for multi-center studies.Methods:We conducted a literature retrieval for English papers published up to December 31, 2023 by using keywords of "health/medical big data" and "distributed/federated learning". After consulting experts, we set criteria of paper inclusion and exclusion and created a framework for data extraction. We collected information about basic study details, including method, application, and evaluation. Two researchers independently screened the papers and extracted information. We used EndNote 20 for the management of literatures and EpiData for the management of data.Results:A total of 3 444 papers were collected, and 29 papers were included in the final analysis. Most of the papers (25, 86.2%) were published in or after 2019, and the papers were mainly from the United States (21/29, 72.4%). For the estimation of epidemiological effects, 22 distributed learning methods had been developed, including methods for logistic regression (8), Cox regression (8), Poisson regression (2), and generalized linear mixed model (GLMM) (4), as well as three platforms for distributed analysis (VLP, Vantage6, AusCAT). The 29 papers described 45 applications, with 20 (44.4%) focusing on the establishment of prediction model and 25 (55.6%) on association analysis. Importantly, except for GLMM, current distributed learning methods can estimate effects with little bias in 1-3 rounds of communication. These methods show less bias compared with meta-analysis, especially in the address of data heterogeneity and rare outcomes. However, less studies examined how differences in data structure and sparse data affect results, an area that requires further research.Conclusion:While distributed learning shows promise in epidemiological effect estimation, it is still in early development, requiring further research on data heterogeneity handling and communication efficiency improvement.

Objective:To investigate the prevalence,related factors,and career implications of occupational burnout among resident physicians during standardized training in Inner Mongolia.Methods:This cross-sectional study used convenience sampling to enroll 2 891 resident physicians,assessing them with a self-developed general information questionnaire,socio-psychological scales,and a universal burnout inventory.Latent profile analysis clas-sified participants based on burnout dimensions,while logistic regression models examined the factors influencing burnout and their relationship with career choices.Results:Resident physicians were divided into low(59.0％),moderate(28.9％),and high(12.1％)burnout subgroups.Logistic regression showed that,compared to the low burnout group,significant risk factors included professional master's students(OR=0.44),working＞70 hours weekly(OR=0.63),＞4 night shifts monthly(OR=0.66),anxiety(mild OR=0.49;moderate OR=0.26;se-vere OR=0.14),depression(mild OR=0.38;moderate OR=0.24;severe OR=0.11),insomnia(mild OR=0.51;moderate OR=0.44;severe OR=0.38),low social support(OR=0.23),and low happiness index(OR=0.42).Male residents(OR=1.25)were less likely to experience burnout.High burnout residents were 5.11 times more likely to quit the medical profession.Conclusion:Training intensity and socio-psychological factors signifi-cantly contribute resident physicians' burnout levels,with severe burnout increase career attrition.