Objective To investigate the impact of red blood cell suspension infusion across various perioperative periods on patients with valvular heart disease. Methods The patients with valvular heart disease admitted to Tianjin Chest Hospital from 2018 to 2020 were selected. Based on the timing of perioperative red cell suspension infusion, patients were categorized into three groups: a group 1 receiving intraoperative red cell suspension infusion, a group 2 receiving red cell suspension infusion within 24 hours after entering the ICU, and a group 3 receiving red cell suspension infusion at both time points. The laboratory results, perioperative blood component infusion volume, and other relevant parameters were retrospectively analyzed. After propensity score matching, the differences in different variables among the three groups were compared. Results After propensity score matching, 102 patients were enrolled, including 52 males and 50 females, with an average age of (61.74±10.58) years. There were 34 patients in each group. The preoperative hemoglobin (Hb) value of the group 2 was significantly higher than that of the group 1 and the group 3, and the amount of red cell suspension and autoblood transfusion was the lowest (P<0.05). Group 1 had the highest postoperative Hb, as well as the highest Hb and hematocrit (HCT) levels within 24 hours post-surgery (P<0.05). The group 1 had the lowest plasma, platelet and cryoprecipitate infusion volumes, and the shortest cardiopulmonary bypass time, aortic occlusion time, postoperative ICU stay and hospital stay, and the least blood loss and total drainage volume (P<0.05). The difference between postoperative and preoperative Hb (△Hb1) was highest in group 1 (P<0.05). Conclusion For patients with valvular heart disease, intraoperative-only infusion of red blood cell suspension is associated with a better prognosis at discharge and during follow-up.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

ObjectiveTo evaluate the impact of stroke on diaphragmatic function by ultrasound. MethodsFrom April, 2024 to June, 2025, 40 stroke patients (stroke group) were recruited in Xuanwu Hospital Capital Medical University. Additionally, 40 sex- and age-matched healthy subjects (control group) were recruited without directional selection. Diaphragmatic excursion and diaphragmatic thickness during quiet breathing and deep breathing were assessed using ultrasound in both groups, and the diaphragmatic thickening fraction was calculated. The stroke group was further divided into two subgroups according to disease course: ≤ 30 days group and > 30 days group, for subgroup analysis. ResultsDuring both quiet and deep breathing, diaphragmatic excursion on the affected side in the stroke group was smaller than that on the unaffected side and in the control group (P < 0.05). During quiet breathing, diaphragmatic thickening fraction on the affected side in the stroke group was smaller than that on the unaffected side and in the control group (P < 0.05), while the diaphragmatic thickening fraction on the unaffected side was significantly smaller than that in the control group (P < 0.01). During deep breathing, the bilateral diaphragmatic thickening fraction in the stroke group was significantly smaller than that in the control group (P < 0.001), and the bilateral end-inspiratory diaphragmatic thickness was significantly smaller than that in the control group (P < 0.001). During quiet breathing, diaphragmatic excursion in both the ≤ 30 d group and the > 30 d group was smaller than that in the control group (P < 0.05); during deep breathing, diaphragmatic excursion in the ≤ 30 d group was smaller than that in the control group (P < 0.05). In both quiet breathing and deep breathing, the diaphragmatic thickening fraction in the ≤ 30 d group and the >30 d group were lower than those in the control group (P < 0.05). During deep breathing, end-inspiratory diaphragmatic thickness in both the ≤ 30 d group and the > 30 d group was significantly smaller than that in the control group (P < 0.01). ConclusionUltrasound can effectively identify the impact of stroke on patients' diaphragmatic function. In stroke patients, both diaphragmatic excursion and contractile performance are reduced on the affected side, while contractile performance is also reduced on the unaffected side.

Objective To investigate the effect of lifestyle on cognitive decline in rural people aged 40 years and older in Xi'an.Methods This was a prospective cohort study.People aged 40 years and older in two villages in Huyi District were selected as the study population.They completed the baseline survey from October 2014 to March 2015 as well as two follow-up visits in 2016 and 2018,respectively.A comprehensive score of lifestyle was calculated based on factors including smoking,drinking,exercise,and diet collected at the baseline.The Mini-Mental State Examination(MMSE)was used to evaluate global cognitive function at both baseline and follow-up;a≥4-point decrease in MMSE score from the baseline was defined as marked cognitive decline.Multivariable Logistic regression,propensity score correction,and propensity score matching were used to investigate the relationship between lifestyle and cognitive decline.Results A total of 1 348 participants were ultimately enrolled and 56(4.2％)of them met the criteria for marked cognitive decline(△MMSE≥4-points).Among them,386(28.6％)people had smoking history,184(13.6％)were drinkers,214(15.9％)lacked physical activity,and 400(29.7％)ate a diet high in oil and salt.Generally,304(22.6％)met the definition of the unhealthy lifestyle(comprehensive score＜6),which means more than one of the four subscales was unhealthy or more than two were relatively unhealthy.Multivariable Logistic regression analysis showed that unhealthy lifestyle was positively associated with marked cognitive decline(OR=2.838,95％CI:1.302-5.525,P=0.005).Propensity-score adjusted model yielded very similar results(OR=2.786,95％CI:1.371-5.661,P=0.005).Propensity score matching was performed to further balance the differences in covariates between the two groups.Multivariate Logistic regression analysis conducted in the matched population revealed that the risk of marked cognitive decline was still higher in those with unhealthy lifestyle(OR=3.994,95％CI:1.582-12.176,P=0.006).Conclusion Unhealthy lifestyle is associated with an increased risk of cognitive decline in cognitively normal people aged 40 years and older.

Objective To establish a forensic age inference method based on age-related changes in maxillofacial CBCT imaging of Han population in North China.Methods CBCT imaging data of Han people aged 7～50 years were collected from September 2021 to September 2023.Mimics 17.0 software was used to perform 3D reconstruction on 480 cases that met the inclusion criteria(420 cases in the experimental group,60 cases in the blind test group,with a 50%male-to-female ratio)and obtain measured values for 16 indicators.The data were then statistically analyzed using SPSS 27.0 to identify age-related significant indicators and establish regression equations.Results Regression equations based on age-related significant indicators were established for different genders and age intervals.The accuracy of the equations decreased as the age interval increased.The blind test accuracy rates of regression equations for males across different age groups ranged between 62.6%and 80.6%,while for females,they ranged between 55.3%and 76.6%.Conclusion This study enriches maxillofacial skeletal data for Chinese population and establishes multivariate age inference regression equations based on significant indicators of age-related changes in maxillofacial CBCT,providing a new reference basis and inference method for forensic age assessment.

Objective:To understand the status of bone health literacy in middle-aged and older female breast cancer patients undergoing chemotherapy and analyze its influencing factors using structural equation modeling.Methods:A convenience sampling method was used to select 250 middle-aged and older breast cancer patients undergoing chemotherapy in two tertiary hospitals in Xi'an from May to October 2024. Patients were surveyed using a general information questionnaire, the Bone Health Literacy Scale for Middle-Aged and Older Women, the Perceived Social Support Scale, and the General Self-Efficacy Scale. Pearson correlation analysis was used to examine the correlations among bone health literacy, perceived social support, and self-efficacy.Results:A total of 250 questionnaires were distributed, and 239 valid questionnaires were recovered, yielding an effective response rate of 95.6% (239/250). The mean score of the Bone Health Literacy Scale among the 239 patients was (39.71±8.16). Bone health literacy was positively correlated with perceived social support and self-efficacy ( P<0.01). Perceived social support directly affected bone health literacy and could also indirectly influence it through general self-efficacy, with an indirect effect value of 0.367, accounting for 45.2% of the total effect (0.367/0.812) . Conclusions:Healthcare professionals should implement effective interventions to enhance patients' perceived social support and strengthen their self-efficacy, thereby improving bone health literacy.

Objective To systematically evaluate the research progress of risk prediction models for periprosthetic joint infection(PJI)after total joint arthroplasty(TJA),analyze the limitations of current researches,and propose optimized suggestions.Methods Chinese and English databases such as PubMed,Embase,Web of Science,Co-chrane Library,SinoMed,Wanfang Database,VIP Database,and CNKI were retrieved systematically.The re-trieved period was from the establishment of each database to August 31,2024.Two researchers independently screened literatures and extracted data according to the CHARMS checklist,and the risk of bias in the included studies was evaluated by the PROBAST tool.Results A total of 14 studies were included in this study,involving 17 prediction models.The most common predictors included history of diabetes mellitus,obesity(body mass index[BMI]≥30 kg/m2),advanced age(≥65 years old),history of traumatic fracture,and prolonged operation time(≥2 hours).All of the included studies had high risks of bias,mainly study subject selection bias(such as single-center sample)and statistical analysis bias(such as unadjusted confounding factors).Conclusion Most of the cur-rently published risk prediction models for PJA after TJA have good predictive performance,however,there are sig-nificant limitations in the research design,especially in the insufficient control of bias risk.Future research needs to focus on improving methodological design,including adoption of prospective multi-center studies,definition of standardized predictive variables,and sufficient adjustment of confounding factors.

Purpose This study aims to analyze genetic mutations in patients with BCR ∷ABL negative myelopro-liferative neoplasms(MPN)and to explore their relationship with clinical features.Methods We retrospectively ana-lyzed the clinical data of 208 patients diagnosed with BCR ∷ABL negative MPN,which included 34 patients with poly-cythemia vera(PV),33 with essential thrombocytopenia(ET),and 141 with primary myelofibrosis(PMF).Mutations in driver genes were assessed in all patients.A total of 72 patients underwent next-generation sequencing(NGS)with 69-gene panel,and the relationship between gene mutations and clinical features were analyzed.Results Among the 208 MPN patients,at least one driver gene mutation(JAK2,CALR,MPL)was detected in 96.15％(200/208)of the patients.Only 0.48％(1/208)of the patients exhibited both JAK2 and CALR driver mutations.We analyzed the clinical data of 136 patients with only driver gene mutations to compare the relationship between the most common JAK2 mutations(identified in 110 patients)and clinical outcomes.The JAK2 mutation group demonstrated higher white blood cell(WBC)counts and lower platelet(PLT)counts compared to the group without JAK2 mutations.173 muta-tions in 40 genes were detected in 72 patients,per capita carried(2.40±1.40)mutations.TET2,ASXL1,and TP53 are the most prevalent non-driver gene mutations,with 44.4％(32/72)of patients exhibiting at least one mutation in these three genes.In comparison to patients without detected mutations in TET2,ASXL1,and TP53,those with muta-tions in these genes demonstrated lower hemoglobin(HGB)levels,a higher incidence of splenomegaly,and more se-vere bone marrow fibrosis.High-molecular risk category(HMR)mutations were detected in 22.22％(16/72)of the patients,and patients with HMR exhibited lower hemoglobin(HGB)levels,lower PLT counts,a higher likelihood of peripheral blood primitive cell percentage ≥ 1％,a greater incidence of splenomegaly,and more severe myelofibrosis.Mutations in the ASXL1 gene were exclusively observed in patients with PMF.Among the PMF patients with ASXL1 mutations(12 patients),there was a higher likelihood of having a peripheral blood primitive cell percentage of ≥1％,as well as a more severe degree of myelofibrosis.Conclusion Approximately 97％of patients with myeloproliferative neoplasms(MPN)exhibit positivity for driver genes,with a notably high mutation rate of the JAK2 gene.Each sub-group of MPN is characterized by distinct gene mutation patterns.Notably,ASXL1 mutations are exclusive to patients with primary myelofibrosis(PMF).Furthermore,PMF patients harboring ASXL1 mutations tend to demonstrate more pronounced bone marrow fibrosis and a greater proportion of blast cells in peripheral blood.

Objective To design an intelligent airborne soldier physical training system based on human body composition analysis to solve the problems in diversity of training mode,targeted training plan and high incidence of military training-related injuries.Methods The intelligent airborne military physical training system was designed with B/S architecture and developed with Python language,which was composed of four functional modules for airborne soldier information acquisition,trainee physical fitness state assessment,physical fitness training program recommendation and airborne soldier physical fitness training program evaluation.The airborne soldier information acquisition module collected and analyzed the trainee physiological parameter information with a human body composition analyzer,clarified the parameter characteristics related to physical training with considerations on military physical training requirements and constructed a trainee physical fitness assessment parameter model;the trainee physical fitness state assessment module established an evaluation model based on machine learning to realize stage-by-stage physical fitness evaluation for airborne soldiers;the physical fitness training program recommendation module was constructed based on the physical training feature similarity algorithm and graph embedding theory to provide decision making assistance for program development of airborne military physical training;the airborne soldier physical fitness training program evaluation module compared the physical fitness and evaluation results before and after training by means of list and chart,and updated the training program based on the evaluation results by calling the physical training program recommendation module.Results The intelligent airborne soldier physical training system contributed to forming an individualized physical fitness training recommendation mechanism after trainee body evaluation,modifying training program based on comparison and feedback for stage-by-stage training evaluation,so as to decrease the incidence of military training-related injuries while increasing the training efficiency.Conclusion The system developed improves airborne soldier physical training in rationality and reliability,and provides references for intelligent military training of the PLA.[Chinese Medical Equipment Journal,2025,46(2):16-23]

Objective To analyze differentially expressed proteins(DEPs)in the hippocampal tissue of an amyloid-beta 1-42(Aβ1-42)-induced Alzheimer's disease(AD)rat model using Tandem mass tag(TMT)-based quantitative proteomics,followed by bioinformatic analysis to explore potential AD mechanisms.Methods Twelve male Sprague-Dawley(SD)rats were randomly assigned to a control group(n=6)and a model group(n=6).The AD model was established by bilateral hippocampal injection of Aβ1-42 in the model group,while the control group received an equivalent volume of saline.Cognitive function was assessed using the novel object recognition test,and hippocampal Aβ deposition was detected by immunofluorescence.DEPs were identified using TMT-based proteomics and subsequently analyzed via Gene Ontology(GO)annotation,Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment,and protein-protein interaction(PPI)network analysis.Key DEPs were validated using parallel reaction monitoring(PRM)technology.Results The model group exhibited a significantly lower novel object recognition index(P<0.01)and significantly increased hippocampal Aβ deposition(P<0.01)compared to the control group.Proteomic analysis identified 183 DEPs(87 upregulated,96 downregulated).GO analysis revealed that DEPs were primarily enriched in processes such as amyloid-beta binding and ion transmembrane transport.KEGG analysis indicated significant enrichment in 42 pathways,including dopaminergic synapse,glutamatergic synapse,cholinergic synapse,and long-term potentiation.Ten core DEPs were identified from the PPI network,and PRM validation confirmed expression trends consistent with the TMT results.Conclusion Aβ1-42-induced AD involves the synergistic action of multiple targets,biological processes,and pathways.The activation of glutamatergic and dopaminergic synaptic signaling pathways,mediated by core DEPs(e.g.,Th、D1、VGLUT2、GluN2A、GluA1、GluA3、Shank1、DARPP-32、PKC-δ、PKC-α、PKA C-β、CaMKⅡα、PTK2B),likely represents a key molecular mechanism in this AD model,providing a basis for identifying potential therapeutic targets.