OBJECTIVE To form an expert consensus addressing clinical issues regarding the use of parenteral direct thrombin inhibitors （DTIs） in special populations. METHODS Led by the Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital（the Affiliated Hospital of UESTC）， a multidisciplinary working group was formed comprising experts from multiple fields， including clinical pharmacy， cardiac surgery， obstetrics， pediatrics and evidence-based medicine. Through literature review and the Delphi method， clinical questions regarding the efficacy and safety of parenteral DTIs used in special populations were identified. A structured design was adopted using the “Population-Intervention-Comparison-Outcome” （PICO） framework；systematic searches were conducted in CJFD， PubMed， Embase and other databases. Relevant evidence from randomized controlled trials，cohort studies and systematic reviews were included and synthesized. Evidence quality was assessed using the Grading of Recommendations Assessment，Development and Evaluation （GRADE） approach， and recommendations were formulated through three rounds of Delphi surveys and expert consensus meetings. RESULTS &CONCLUSIONS Seven clinical questions were ultimately selected （with a consensus rate exceeding 90%）， resulting in the formulation of seven recommendations on the use of parenteral DTIs in special populations， including children， pregnant women， patients with hepatic or renal impairment， patients with mesenteric venous thrombosis， and individuals with thrombophilia. These recommendations clarify the preferred agents， dosing ranges， monitoring parameters， and safety management strategies for parenteral DTIs in these special populations. This expert consensus， which is formulated based on the best available evidence， provides evidence-based guidance for standardized and individualized use of parenteral DTIs in special populations.

ObjectiveTo develop an assessment tool for apraxia of speech (AOS) of Chinese Putonghua speakers and test its reliability and validity. MethodsThe Chinese Apraxia of Speech Assessment and Diagnostic Tool (CAADT) was developed based on the Apraxia of Speech Rating Scale 3.5, combined with the linguistic characteristics of Chinese and clinical experience. The tool consistsed of eleven items across three sections: articulation, prosody and alternating motion rates. Six experts evaluated the content validity. From November, 2024 to May, 2025, 51 patients with post-stroke AOS (experimental group) and ten patients with post-stroke aphasia without AOS (control group) were recruited from Anhui Wannan Rehabilitation Hospital (the Fifth People's Hospital of Wuhu), and tested with CAADT. Reliability was assessed using Cronbach's α coefficient, Kendall's coefficient of concordance W and Pearson correlation coefficient. Validity was evaluated using the content validity index (CVI) and Spearman correlation coefficient. Discriminative effect was analyzed using the receiver operating characteristic (ROC) curve. ResultsThe Cronbach's α coefficients for the articulation and prosody sections and the total scale were all > 0.9, while it was 0.454 for the alternating motion rates. Inter-rater reliability was good (W ≥ 0.598, P < 0.001). Test-retest reliability showed high positive correlations for the three sections and the total score between the two assessments (r ≥ 0.84, P < 0.001). The scale-level CVI was 0.95, and the item-level CVI ≥ 0.83. The Spearman correlation coefficients among the sections ranged from 0.30 to 0.70. ROC analysis revealed an area under the curve of 0.953, with a cut-off value of 11, yielding a sensitivity of 0.92 and a specificity of 0.90. ConclusionCAADT demonstrates good reliability, validity and discriminative effect, which can be used for clinical assessment and auxiliary diagnosis of Chinese Putonghua speaking patients with post-stroke AOS.

ObjectiveTo systematically explore the current practical status, core predicaments, and optimization paths of effective contract fulfillment by family doctors in Shanghai from the perspective of informatization, and to provide empirical support and policy references for the high-quality development of contracted services. MethodsA mixed research approach was adopted. The connotation of effective contract fulfillment, the current status of informatization support, and the priority of demand were comprehensively analyzed through policy document review, in-depth interviews with key informants, and a questionnaire survey covering 45 community health service centers across all 16 districts of Shanghai. ResultsThe family doctor contract service in Shanghai has formed a dual-core framework of “accurate contracting” and “substantive service delivery”, yet challenges persist in system interoperability, health data integration, and the limited diversity of service outreach tools. The comprehensive utilization rate of the information integration terminal in the 45 surveyed community health service centers was merely 50.74%. Three prioritized demands were identified: horizontal connectivity between the Hospital Information System (HIS) and the public health system for contract status updates, integration of “medical-prevention-management” information, and automated generation of health assessments. Based on these findings, this study proposed a closed-loop fulfillment pathway of “tag generation-task management-service delivery-data return”. ConclusionTo facilitate the high-quality development of contracted services, it is recommended to transform the concept of contracted services and promote the integration of medical care and disease prevention through information system construction from a holistic perspective. Concurrently, municipal top-level design and district-level platform development should be reinforced to refine data governance and application. Furthermore, substantial efforts should be devoted to cultivating interdisciplinary talents bridging clinical practice and information technology, thus strengthening the convergence of clinical and information operations.

ObjectiveTo investigate the metabolic mechanisms of Limosilactobacillus reuteri （L. reuteri） in alleviating chemotherapy-induced intestinal mucosal injury （CIMI）. MethodsC57BL/6 mice were randomly divided into the Control group， Model group， and L. reuteri treatment group （n=8 per group）. Mice in the L. reuteri group were intragastrically administered L. reuteri （1 × 10⁹ CFU/mL） for 10 consecutive days. From day 5， mice in the Model and L. reuteri groups were intraperitoneally injected with 5-FU （65 mg/kg） for 6 consecutive days to establish a CIMI model. Body weight changes， colon length， and related indicators were recorded. Intestinal histopathological injury was assessed by HE staining with measurement of villus height and crypt depth. The expression levels of zonula occludens-1 （ZO-1）， Occludin， Claudin-4， Muc1， and Muc2 in ileal tissues were determined by RT-qPCR and immunohistochemistry to evaluate intestinal barrier function. In addition， untargeted metabolomics was performed on cecal contents from each group to analyze metabolic profiles and enrichment of differential metabolic pathways. ResultsL. reuteri intervention significantly alleviated body weight loss （P<0.001） and colon shortening （P<0.05） in CIMI mice， effectively reducing ileal tissue pathological damage， and upregulating the expression of ZO-1， Occludin， Claudin4， Muc1， and Muc2 （P<0.05）. Untargeted metabolomics analysis showed that L. reuteri treatment reversed the abnormal metabolic profile in the cecal contents of CIMI mice， bringing it closer to normal. Various differential metabolites， such as acylcarnitines and polyunsaturated fatty acids， might play an important role in L. reuteri-mediated alleviation of CIMI. These differential metabolites were primarily enriched in key pathways such as linoleic acid metabolism， tryptophan metabolism， and unsaturated fatty acid biosynthesis. ConclusionThis study reveals that L. reuteri improves intestinal barrier function and alleviates CIMI by regulating the intestinal metabolic profile， particularly lipid and amino acid metabolism. It provides a novel potential strategy for the prevention and treatment of CIMI.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

Enhancer of zeste homolog 2(EZH2)is a histone methyltransferase It mediates trimethylation of lysine 27 on histone H3,thereby facilitating the epigenetic silencing of downstream genes.In conjunc-tion with SUZ12,EED,and other components,it constitutes the polycomb repressive complex 2(PRC2)complex.While EZH2 is intricately involved in cellular proliferation and cardiac development,the chan-ges in its expression during cardiac terminal differentiation remain elusive.In this study,we employed differential gene expression analysis of embryonic and adult myocardial cells using the GEO database,and found that EZH2 is highly expressed in embryonic myocardium,but is present at very low levels in adult myocardium(P＜0.0001).Conversely,the expression changes of PRC2 members SUZ12 and EED are not as pronounced.Online analysis through the Tabula Muris database indicates that under physiological conditions,various cell subpopulations in the adult mouse heart exhibit negligible expression of EZH2.Immunohistochemical staining of mouse cardiac tissues shows that EZH2 is highly expressed in embryonic and neonatal myocardium but declines progressively from the first day after birth(P＜0.0001),becoming almost undetectable by the third day.Western blotting further confirms the rapid disappearance of EZH2 expression post-birth(P＜0.05),with EZH1 compensating for the downregulation of EZH2 to maintain H3K27me3 modification levels.Additionally,using the P19 teratocarcinoma stem cell model for cardio-myocyte differentiation,it is observed that EZH2 is significantly upregulated during the transition from cardiac progenitor cells to spontaneously beating cardiomyocytes,correlating with the expression of the cardiomyocyte transcription factor Gata4(P＜0.01).Targeted degradation of EZH2 using the small mole-cule drug MS1943 significantly inhibits the proliferation of induced cardiomyocytes,as evidenced by 5-e-thynyl-2'-deoxyuridine(EdU)incorporation assays(P＜0.01),and RT-qPCR reveals a marked in-crease in the expression of the proliferation inhibitor CDKN1A(P＜0.01).In summary,the high expres-sion of EZH2 in embryonic myocardial cells is associated with enhanced cell proliferation.The rapid loss of EZH2 expression postnatally correlates with the loss of proliferative capacity in cardiomyocytes,mark-ing it as a key indicator of cardiac terminal differentiation.

Creutzfeldt-Jakob disease(CJD)is a rare neurodegenerative disorder characterized by abnor-malities in the prion protein(PrP),the most common form of human prion disease.Although Genome-Wide Association Studies(GWAS)have identified numerous risk genes for CJD,the mechanisms under-lying these risk loci remain poorly understood.This study aims to elucidate novel genetically prioritized candidate proteins associated with CJD in the human brain through an integrative analytical pipeline.Uti-lizing datasets from Protein Quantitative Trait Loci(pQTL)(NpQTL1=152,NpQTL2=376),expres-sion QTL(eQTL)(N=452),and the CJD GWAS(NCJD=4 110,NControls=13 569),we imple-mented a systematic analytical pipeline.This pipeline included Proteome-Wide Association Study(PWAS),Mendelian randomization(MR),Bayesian colocalization,and Transcriptome-Wide Associa-tion Study(TWAS)to identify novel genetically prioritized candidate proteins implicated in CJD patho-genesis within the brain.Through PWAS,we identified that the altered abundance of six brain proteins was significantly associated with CJD.Two genes,STX6 and PDIA4,were established as lead causal genes for CJD,supported by robust evidence(False Discovery Rate＜0.05 in MR analysis;PP4/(PP3+PP4)≥0.75 in Bayesian colocalization).Specifically,elevated levels of STX6 and PDIA4 were asso-ciated with an increased risk of CJD.Additionally,TWAS demonstrated that STX6 and PDIA4 were asso-ciated with CJD at the transcriptional level.

OBJECTIVE: To retrospectively analyze the characteristics and influencing factors of COVID-19 infection in patients with multiple myeloma (MM) who underwent autologous hematopoietic stem cell transplantation (AHSCT). METHODS: The clinical data of MM patients who underwent AHSCT in Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from May 26, 2021 to December 26, 2022 were collected. The onset of COVID-19 infection, corresponding symptoms and laboratory tests were followed up in outpatient or by the means of telephone contact and online questionnaires. Related analysis was then performed. RESULTS: This study included 96 patients, and 72 cases among them were infected with COVID-19 while 24 cases were uninfected. Logistic regression analysis showed that vaccination did not significantly reduce the risk of COVID-19 infection, but patients who received two doses of the vaccine had a lower risk of developing moderate and severe disease than those who did not receive or received one dose (OR =0.06, P =0.029). Patients who received daratumumab before had a higher risk of COVID-19 infection (OR =5.78, P =0.039), while those with a history of immunomodulatory drugs (IMiDs) had the opposite effect (OR =0.31, P =0.028). The use of both drugs did not affect the severity of COVID-19 infection. CONCLUSION For MM patients undergoing AHSCT as first-line chemotherapy, COVID-19 vaccination does not significantly reduce the infection rate, but it plays a role in preventing moderate and severe cases. The application of antineoplastic drugs with different mechanisms has a certain impact on the susceptibility to the COVID-19, which should be considered comprehensively when creating treatment plans.
Humans ; Multiple Myeloma/complications* ; COVID-19/epidemiology* ; Hematopoietic Stem Cell Transplantation ; Transplantation, Autologous ; Retrospective Studies ; Risk Assessment ; Risk Factors ; Male ; Female ; Middle Aged ; SARS-CoV-2 ; Adult ; Antibodies, Monoclonal

BACKGROUND: Depression among older adults is an important public health issue, and air and noise pollution have been found to contribute to exacerbation of depressive symptoms. This study examined the association of exposure to air and noise pollutants with clinically-newly-diagnosed depressive disorder. The mediating role of individual pro-inflammatory markers was explored. METHODS: We linked National Health Insurance claim data with 2998 healthy community-dwellers aged 55 and above who participated in the Healthy Aging Longitudinal Study between 2009 and 2013. Newly diagnosed depressive disorder was identified using diagnostic codes from the medical claim data. Pollutants were estimated using nationwide land use regression, including PM_2.5 and PM₁₀, carbon monoxide, ozone, nitrogen dioxide, sulfur dioxide, and road traffic noise. Cox proportional hazard models were employed to examine the association between pollutants and newly developed depressive disorders. The mediating effect of serum pro-inflammatory biomarkers on the relationship was examined. RESULTS: Among the 2998 participants, 209 had newly diagnosed depressive disorders. In adjusted Cox proportional hazard models, one interquartile range increase in PM_2.5 (8.53 µg/m³) was associated with a 17.5% increased hazard of developing depressive disorders. Other air pollutants and road traffic noise were not linearly associated with depressive disorder incidence. Levels of serum tumor necrosis factor receptor 1 mediated the relationship between PM_2.5 and survival time to newly onset depressive disorder. CONCLUSION PM_2.5 is related to an increased risk of newly developed depressive disorder among middle-aged and older adults, and the association is partially mediated by the pro-inflammatory marker TNF-R1.
Humans ; Particulate Matter/analysis* ; Male ; Female ; Middle Aged ; Longitudinal Studies ; Aged ; Incidence ; Air Pollutants/analysis* ; Environmental Exposure/adverse effects* ; Taiwan/epidemiology* ; Receptors, Tumor Necrosis Factor, Type I/blood* ; Proportional Hazards Models ; Biomarkers/blood* ; Depression/epidemiology* ; Aged, 80 and over ; Depressive Disorder/chemically induced* ; Risk Factors ; Air Pollution/adverse effects*