Objective To evaluate the predictive value of different machine learning models constructed in a multicenter environment for potential organ donors and verify their clinical application feasibility. Methods The study included 2 000 inpatients admitted to five domestic tertiary hospitals from January 2020 to December 2023, who met the criteria for potential organ donation assessment. They were randomly divided into a training set and an internal validation set (7∶3). Another 300 similar patients admitted to the First Affiliated Hospital of Harbin Medical University from January 2024 to April 2025 were included as an external validation set. The area under the curve (AUC), sensitivity, specificity, accuracy and F1-score of three models were compared, and the consistency of the potential organ donor determination process was tested. Multivariate logistic regression analysis was used to identify predictive factors of potential organ donors. Decision curve analysis (DCA) was employed to verify the resource efficiency of each model, and the threshold interval and intervention balance point were assessed. Results Apart from age, there were no significant differences in other basic characteristics among the centers (all P>0.05). The consistency of the potential organ donor determination process among researchers in each center was good [all 95% confidence interval (CI) lower limits >0]. In the internal validation set, the XGBoost model had the best predictive performance (AUC=0.92, 95% CI 0.89-0.94) and the best calibration (P=0.441, Brier score 0.099). In the external validation set, the XGBoost model also had the best predictive performance (AUC=0.91, 95% CI 0.88-0.94), outperforming logistic regression and random forest models. Multivariate logistic regression showed that mechanical ventilation had the greatest impact (odds ratio=2.06, 95% CI 1.54-2.76, P<0.001). DCA indicated that the XGBoost model had the highest net benefit in the threshold interval of 0.2-0.6. The “treat all” strategy only had a slight advantage at extremely low thresholds. The recommended threshold interval, which balances intervention costs and clinical benefits, considers ≥50% positive predictive value (PPV) and ≤50 referrals per 100 high-risk patients. Conclusions The XGBoost model established in a multicenter environment is accurate and well-calibrated in predicting potential organ donors. Combined with DCA, it may effectively guide the timing of clinical interventions and resource allocation, providing new ideas for the assessment and management of organ donation after brain death.

Blood products are biological products derived from human plasma for use in clinical treatment.As such,they inherently carry the risk of blood-bome viral contamination,which has garnered significant attention from regulatory agencies worldwide regarding the viral safety of these products.This article compares and discusses the differences in domestic and international regulations on viral safety for blood products,focusing on aspects such as raw material selection and viral testing.Additionally,the article explores further impactful measures for viral safety control,namely,viral reduction during the manufacturing process and strategies to prevent cross-contamination.Moreover,we propose corresponding recommendations for China's regulatory framework to further enhance the viral safety of blood products in the country.

Objective To analyze the medication rules of traditional Chinese medicine in treating breast cancer based on real-world data mining.Methods Inpatients with breast cancer who received traditional Chinese medicine treatment at the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine from January 2017 to December 2021 were selected.Python 3.10 software was used to mine traditional Chinese medicine prescription data;SPSS 23.0 software was applied for descriptive analysis,and systematic cluster analysis was performed on high-frequency drugs.Results A total of 3026 consultation records of inpatients with breast cancer were collected.The main traditional Chinese medicine syndrome diagnosis of"predominantly liver depression and Qi stagnation"accounted for 60.94％of the total consultations.A total of 240 kinds of traditional Chinese medicine were used,with a cumulative frequency of 35 462 times.Among them,29 kinds of traditional Chinese medicine such as Danggui,Fuling,Baizhu,Chaihu had a cumulative usage frequency exceeding 300 times.Regarding the four natures of drugs,cold-natured(43.55％),warm-natured(30.05％),and neutral-natured(23.34％)drugs were predominant;In terms of five flavors,sweet(46.12％),bitter(30.91％),and pungent(20.02％)were the main ones.The most frequently used drugs were tonifying herbs(32.77％),followed by heat-clearing herbs(15.96％)and phlegm-resolving herbs(14.71％).Systematic cluster analysis yielded 7 groups of drug combinations.Conclusion In real-world clinical practice,traditional Chinese medicine for breast cancer mainly uses tonifying herbs,reflecting the traditional Chinese medicine principle of"strengthening healthy Qi and cultivating the root"in treating tumors.The four natures and five flavors of drugs follow syndrome differentiation and the combination of cold and heat.The clustered drug combinations have extensive therapeutic effects,covering various syndromes of breast cancer at different stages,which can provide a reference for clinical medication.

Cancer stands as a significant global public health challenge,and cancer screening serves as a pivotal strategy for reducing its mortality.Presently,only a limited number of cancer types have appropriate screening methods available.Traditional single-cancer screen-ing approaches are fraught with limitations,including invasiveness,low accuracy,and poor patient compliance.Multi-cancer early detection(MCED)leveraging liquid biopsy technology enables non-invasive and efficient early detection of multiple cancers by analyzing biomarkers such as cell-free DNA,cell-free RNA,proteins,and metabolites in blood and other bodily fluids.This innovative approach substantially broadens the spectrum of detectable cancers and enhances population coverage,showcasing immense potential for improving existing can-cer screening strategies.This expert consensus comprehensively reviews the progress of liquid biopsy-based MCED,biomarker selection and detection technologies,the criteria for cancer type selection,research design and clinical utility evaluation,as well as implementation path-ways.The overarching goal of this consensus is to offer scientific guidance for further research and the widespread adoption of MCED,thereby facilitating the continuous optimization of cancer screening strategies.

This study identified the types and pathogen carrying status of fleas on the surface of sheep in some areas of southern Xinjiang,and analyzed the genetic evolution differences with respect to related pathogens.The aim was to provide a reference for the local prevention and control of fleas and insect borne infectious diseases.A total of 1 586 fleas were collected from agricultural and pas-toral areas of Tumushuke City and Hotan Prefecture.Flea species were identified on the basis of morphology and the Pulex irritans mi-tochondrial COII gene.Flea DNA was extracted,and PCR was conducted to amplify the Bartonella gltA gene;Arsenophonus,Ana-plasma,Ehrlichia,and Wolbachia 16S rRNA genes;RickettsiaOmpA,17kDa,16S rRNA genes,and Yersinia pestis 16S rDNA gene.The amplified products were sequenced,and the homology of the genes of the three detected pathogens(gltA gene of Bartonella,16S rRNA gene of Wolbachia,and Anaplasma phagocytophilum)with respect to known corresponding genes of the same pathogen in Gen-Bank was analyzed.Phylogenetic trees were constructed with the adjacency method in MEGA 11.0.According to morphological and mo-lecular biology identification results,all fleas collected in this study were Pulex irritans.PCR indicated that the target gene fragments had been added to the mitochondrial COII,BartonellagltA,Wolbachia,and autophagosomal 16S rRNA genes of human fleas,all of which were consistent with the expected fragment sizes.Target bands were not amplified from Ehrlichia,Arsenophonus,spotted fever group Rickettsia,and Yersinia pestis.According to homology and genetic evolution analysis of human flea mitochondrial COII and the corresponding genes of the above-described pathogens,the COX2 gene(ON455234.1)of human fleas in Tumushuke city and Iran ob-tained in this study showed the highest homology(99.84%).The COII gene(NC_063709.1)of human fleas in Hetan City and Hunan region showed the highest homology(100%).Our findings further confirmed that the flea species was Pulex irritans.The PCR amplifi-cation results indicated that the collected Pulex irritans carried multiple pathogens,among which Bartonella and Wolbachia had the highest infection rates,and the infection rate with Anaplasma phagocytophilum was relatively low.This study is the first to discover flea species on the surface of sheep in some areas of southern Xinjiang.Our findings preliminarily confirmed that Bartonella,Wolba-chia,and Anaplasma phagocytophilum are the main Pulex irritans pathogens.

Blood products are biological products derived from human plasma for use in clinical treatment.As such,they inherently carry the risk of blood-bome viral contamination,which has garnered significant attention from regulatory agencies worldwide regarding the viral safety of these products.This article compares and discusses the differences in domestic and international regulations on viral safety for blood products,focusing on aspects such as raw material selection and viral testing.Additionally,the article explores further impactful measures for viral safety control,namely,viral reduction during the manufacturing process and strategies to prevent cross-contamination.Moreover,we propose corresponding recommendations for China's regulatory framework to further enhance the viral safety of blood products in the country.

Objective To investigate the predictive capacity of the Triglyceride-Glucose(TyG)index and the Triglyceride-Glucose-Body Mass Index(TyG-BMI)for the development of hyperuricemia(HUA)in a health examination population,and to identify suitable indicators as risk assessment tools for HUA.Methods This study ultimately included 12 004 participants from a health examination cohort.According to SUA levels,the partici-pants were categorized into a normal group(n=9 952)and a hyperuricemia(HUA)group(n=2 052).The TyG index and TyG-BMI index were calculated,and participants were further stratified into four groups(Q1—Q4)based on the quartiles of these indices.Binary logistic regression analysis was performed to assess the association between TyG,TyG-BMI,and HUA.The predictive value of TyG,TyG-BMI,and their combination for HUA was evaluated using Receiver Operating Characteristic(ROC)curves and the Area Under the Curve(AUC).Subgroup analyses were carried out by gender and age.Results The TyG and TyG-BMI indices were significantly elevated in the HUA group compared to the normal group.The prevalence of HUA was markedly higher in the TyG-Q4 and TyG-BMI-Q4 groups than in the other three corresponding quartile groups.Binary logistic regression analysis revealed a positive association between TyG,TyG-BMI levels,and the risk of HUA.The AUC values for predicting HUA using TyG,TyG-BMI,and their combination were 0.700,0.747,and 0.822,respectively.Specifically,for males,the AUC values were 0.641,0.674,and 0.709,respectively,whereas for females,they were 0.742,0.776,and 0.829,respectively.Among individuals younger than 60 years old,the AUC values were 0.716,0.759,and 0.835,respectively,while for those aged 60 years or older,the values were 0.614,0.645,and 0.731,respectively.Conclusions TyG and TyG-BMI are significantly associated with the risk of HUA.Specifically,TyG-BMI demon-strates superior predictive performance compared to TyG alone.Moreover,the combination of TyG and TyG-BMI further improves predictive accuracy,particularly among female and middle-aged or younger populations.

Objective To investigate the impact of the dominant deafness point mutation p.D179N on the oli-gomeric equilibrium state of Connexin 26(Cx26).Methods The wild-type Cx26 fusion protein(Cx26-WT-GFP)and mutant fusion proteins(Cx26-D179N-GFP,Cx26-D179C-GFP)were expressed in HEK293F cells.By using Fluorescence-detection size-exclusion chromatography(FSEC)and size-exclusion chromatography(SEC)to analysis the oligomeric state of the target protein based on malecular weight under the condition of solubilization and purifica-tion respectively.Cryo-electron microscopy(Cryo-EM)single particle analysis(SPA)was conducted to analysis the target protein's oligomeric states based on the 2D classification morphology of the protein particles.Results In vitro,the wild-type Cx26 protein(Cx26-WT)is almost exclusively dodecameric.The deafness mutation p.D179N protein(Cx26-D179N)exists as both dodecamers and hexamers,whereas the artificial mutation p.D179C protein(Cx26-D179C)does not form dodecamers.Conclusion The dominant deafness mutation GJB2 p.D179N could weaken the ability of docking between hexameric proteins,which could affect the balance between hexamers and do-decamers.

This study aims to describe the population and regional distribution characteristics of smoking behavior among adult twins in the China Twin Registry (CNTR), as well as the concordance rates for smoking behavior in monozygotic and dizygotic twins, and estimate the heritability. The study population included adult twins in CNTR who had smoking questionnaire data. A random-effects regression model was used to describe the distribution of smoking behavior among different subgroups based on various characteristics. The concordance of smoking behavior between different zygosity groups was calculated, and heritability was estimated. A total of 28 444 twin pairs were included in this study, with an average age of (36.6±12.0) years. Among male twins, 41.2% were current smokers, while only 1.2% of females smoked. Higher smoking rates were observed among male smokers in the 50-59 age group ( z=23.0, P<0.001), northern regions ( z=2.9, P<0.01), rural areas ( z=-5.2, P<0.001), those who were divorced/widowed ( z=3.8, P<0.001), and first-born twins ( z=-4.3, P<0.001), while lower smoking rates were found in those with higher education ( z=-16.1, P<0.001) and unmarried individuals ( z=-16.0, P<0.001). The smoking concordance rate for male monozygotic twins was 69.6%, significantly higher than the 57.3% concordance rate for dizygotic twins ( χ 2=105.0, P<0.05). The heritability of smoking behavior in male twins was estimated at 28.9% (95% CI: 24.3%-33.4%). Stratified analyses showed differences in heritability across regions and age groups: the heritability in northern regions was 32.6% (95% CI: 27.3%-38.0%), higher than the 21.0% (95% CI: 12.4%-29.5%) observed in southern regions; the highest heritability of 35.1% (95% CI: 26.3%-43.9%) was found in the 18-29 age group, with heritability decreasing with age. In conclusion, the smoking rate and influencing factors in the twin population are similar to those in the general population, with unique characteristics, such as higher smoking rates in first-born twins. Genetic factors have a significant impact on smoking behavior.

Objective To investigate the predictive capacity of the Triglyceride-Glucose(TyG)index and the Triglyceride-Glucose-Body Mass Index(TyG-BMI)for the development of hyperuricemia(HUA)in a health examination population,and to identify suitable indicators as risk assessment tools for HUA.Methods This study ultimately included 12 004 participants from a health examination cohort.According to SUA levels,the partici-pants were categorized into a normal group(n=9 952)and a hyperuricemia(HUA)group(n=2 052).The TyG index and TyG-BMI index were calculated,and participants were further stratified into four groups(Q1—Q4)based on the quartiles of these indices.Binary logistic regression analysis was performed to assess the association between TyG,TyG-BMI,and HUA.The predictive value of TyG,TyG-BMI,and their combination for HUA was evaluated using Receiver Operating Characteristic(ROC)curves and the Area Under the Curve(AUC).Subgroup analyses were carried out by gender and age.Results The TyG and TyG-BMI indices were significantly elevated in the HUA group compared to the normal group.The prevalence of HUA was markedly higher in the TyG-Q4 and TyG-BMI-Q4 groups than in the other three corresponding quartile groups.Binary logistic regression analysis revealed a positive association between TyG,TyG-BMI levels,and the risk of HUA.The AUC values for predicting HUA using TyG,TyG-BMI,and their combination were 0.700,0.747,and 0.822,respectively.Specifically,for males,the AUC values were 0.641,0.674,and 0.709,respectively,whereas for females,they were 0.742,0.776,and 0.829,respectively.Among individuals younger than 60 years old,the AUC values were 0.716,0.759,and 0.835,respectively,while for those aged 60 years or older,the values were 0.614,0.645,and 0.731,respectively.Conclusions TyG and TyG-BMI are significantly associated with the risk of HUA.Specifically,TyG-BMI demon-strates superior predictive performance compared to TyG alone.Moreover,the combination of TyG and TyG-BMI further improves predictive accuracy,particularly among female and middle-aged or younger populations.