Objective: Blood safety surveillance is a critical measure for the objective assessment of blood quality and enhancing transfusion safety. This study aims to comprehensively understand the current status of blood safety surveillance and management in blood collection and supply institutions in Sichuan Province, systematically analyze existing problems and vulnerabilities, and provide a basis for optimizing management strategies and improving capabilities to ensure blood safety. Methods: The Blood Safety Surveillance questionnaire was designed, covering adverse donor reaction reporting, management of adverse events, and transfusion adverse reaction feedback. An online survey was conducted via Questionnaire Star platform among 21 blood collection and supply institutions in the province, gathering information on management systems, process implementation, and utilization of monitoring data. The collected data were organized and statistically analyzed using Excel. Results: The questionnaire response rate and validity rate were both 100%. Blood collection and supply institutions in Sichuan Province have generally established a blood safety surveillance system and achieved positive outcomes. Regarding adverse events in blood collection and supply, 95.24% (20 institutions) have established reporting procedures, and 66.67% (14) collect information through multiple channels such as internal reports, external reports, and statistical trend feedback. A total of 90.48% (19) institutions regularly summarize and analyze adverse event data, and 85.71% (18) produce reports with improvement recommendations based on this analysis.71.43% (15) institutions implement reward and penalty measures, and 71.43% (15) report underreporting or omission due to accountability or performance concerns. In terms of monitoring adverse blood donation reactions, all blood collection and supply institutions have established full-process management systems.76.19% (16) collect data through multiple approaches, including on-site donation records, voluntary donor reports, and donor follow-ups. Adverse reactions were followed up in 95.24% (20) of institutions with 65% (13) completing follow-ups within 24 hours.80.95% (17) have established investigation procedures, while 66.67% (14) believe underreporting or omission still occurs. All blood collection and supply institutions regularly compile statistics on adverse donation reactions. Of these, 85.71% (18) institutions providing feedback to management departments and 90.48% (19) analyzing the data and making recommendations.76.19% (16) institutions use monitoring data for return donor management and targeted care, and 71.43% (15 stations) incorporate it into management reviews. Regarding adverse transfusion reactions, 95.24% (20) institutions have established and implemented procedures for isolating, recalling, and tracing of problematic blood units. However, only 42.86% (9) have established feedback mechanisms of adverse transfusion reaction with hospitals, and only 19.05% (4) support direct reporting via information systems.47.62% (10) institutions regularly analyze adverse transfusion reaction data, and 19.05% (4) provide feedback and recommendations to relevant hospitals. All blood collection and supply institutions reported challenges in collecting hospital feedback, citing complexities in data collection and reporting processes. Conclusion: Blood safety surveillance systems have been preliminarily established in Sichuan Province. However, further strengthening is still required, including conducting in-depth data analysis and utilization, standardizing the configuration of emergency medications and equipment, and improving feedback mechanisms for adverse transfusion reactions. To improve the overall level of blood safety management, it is recommended to strengthen closed-loop data management, improve feedback mechanisms between blood collection and supply institutions and hospitals, foster a non-punitive reporting culture, and systematically advance the regionalization and standardization of the monitoring system. These efforts will contribute to sustainably improving the overall effectiveness and sustainability of blood safety management.

ObjectiveTo prepare triptolide-Chuanxiong Rhizoma extract ethanol transfersomes（TP-CX@TESs）， conduct its quality evaluation， and investigate its in vitro anti-inflammatory efficacy and the underlying mechanisms. MethodsTP-CX@TESs was prepared via the ultrasonic injection method. With encapsulation efficiency and particle size as evaluation indicators， Box-Behnken design-response surface methodology（BBD-RSM） was employed to optimize the formulation process. The TP-CX@TESs prepared under the optimal process was characterized and evaluated for in vitro transdermal performance. A lipopolysaccharide（LPS）-induced RAW264.7 cell inflammation model was established. After 24 h of drug intervention， the levels of inflammatory factors such as nitric oxide（NO）， interleukin-6（IL-6）， and tumor necrosis factor-α（TNF-α） in the cell supernatant were detected. Western blot was used to determine the protein expression levels of Janus kinase 2（JAK2）， signal transducer and activator of transcription 3（STAT3）， and α7 nicotinic acetylcholine receptor（α7nAChR）， and real-time fluorescence quantitative polymerase chain reaction（Real-time PCR） was applied to measure the mRNA expression levels of JAK2， STAT3， the encoding gene of α7nAChR（CHRNA7）， and nuclear transcription factor-κB（NF-κB）. ResultsResults of BBD-RSM showed that the optimal formulation for preparing TP-CX@TESs was as follows：egg yolk lecithin content of 2.3%， ethanol volume fraction of 30%， and ratio of polysorbate-80 to egg yolk lecithin of 2∶5. Microscopic characterization revealed that TP-CX@TESs exhibited a spherical-like structure with a particle size of （105.60±3.85） nm， a polydispersity index of 0.19±0.03， and a Zeta potential of （-15.89±0.98） mV. The encapsulation efficiencies of triptolide， ferulic acid， and ligustilide were （76.88±4.40）%， （78.84±4.40）%， and （65.88±0.06）%， respectively. Both in vitro release and transdermal penetration of triptolide， ferulic acid， and ligustilide in TP-CX@TESs all followed the first-order kinetic model， showing a certain sustained-release property. Experimental results in RAW264.7 cells indicated that TP-CX@TESs significantly inhibited the release of NO， TNF-α， and IL-6（P<0.01）， remarkably upregulated the protein expression levels of STAT3 and α7nAChR（P<0.01）， increased the mRNA expression level of CHRNA7， and significantly downregulated the mRNA expression level of NF-κB（P<0.05， P<0.01）. ConclusionThe optimized formulation process of TP-CX@TESs is simple and feasible， along with favorable in vitro release property， good transdermal permeability， and excellent in vitro anti-inflammatory activity， the mechanism is related to the inhibition of NF-κB.

ObjectiveTo prepare triptolide-Chuanxiong Rhizoma extract ethanol transfersomes（TP-CX@TESs）， conduct its quality evaluation， and investigate its in vitro anti-inflammatory efficacy and the underlying mechanisms. MethodsTP-CX@TESs was prepared via the ultrasonic injection method. With encapsulation efficiency and particle size as evaluation indicators， Box-Behnken design-response surface methodology（BBD-RSM） was employed to optimize the formulation process. The TP-CX@TESs prepared under the optimal process was characterized and evaluated for in vitro transdermal performance. A lipopolysaccharide（LPS）-induced RAW264.7 cell inflammation model was established. After 24 h of drug intervention， the levels of inflammatory factors such as nitric oxide（NO）， interleukin-6（IL-6）， and tumor necrosis factor-α（TNF-α） in the cell supernatant were detected. Western blot was used to determine the protein expression levels of Janus kinase 2（JAK2）， signal transducer and activator of transcription 3（STAT3）， and α7 nicotinic acetylcholine receptor（α7nAChR）， and real-time fluorescence quantitative polymerase chain reaction（Real-time PCR） was applied to measure the mRNA expression levels of JAK2， STAT3， the encoding gene of α7nAChR（CHRNA7）， and nuclear transcription factor-κB（NF-κB）. ResultsResults of BBD-RSM showed that the optimal formulation for preparing TP-CX@TESs was as follows：egg yolk lecithin content of 2.3%， ethanol volume fraction of 30%， and ratio of polysorbate-80 to egg yolk lecithin of 2∶5. Microscopic characterization revealed that TP-CX@TESs exhibited a spherical-like structure with a particle size of （105.60±3.85） nm， a polydispersity index of 0.19±0.03， and a Zeta potential of （-15.89±0.98） mV. The encapsulation efficiencies of triptolide， ferulic acid， and ligustilide were （76.88±4.40）%， （78.84±4.40）%， and （65.88±0.06）%， respectively. Both in vitro release and transdermal penetration of triptolide， ferulic acid， and ligustilide in TP-CX@TESs all followed the first-order kinetic model， showing a certain sustained-release property. Experimental results in RAW264.7 cells indicated that TP-CX@TESs significantly inhibited the release of NO， TNF-α， and IL-6（P<0.01）， remarkably upregulated the protein expression levels of STAT3 and α7nAChR（P<0.01）， increased the mRNA expression level of CHRNA7， and significantly downregulated the mRNA expression level of NF-κB（P<0.05， P<0.01）. ConclusionThe optimized formulation process of TP-CX@TESs is simple and feasible， along with favorable in vitro release property， good transdermal permeability， and excellent in vitro anti-inflammatory activity， the mechanism is related to the inhibition of NF-κB.

Objective To investigate the effects of Aconite decoction （AD） on the viability and polarization of murine RAW264.7 macrophages induced by lipopolysaccharide （LPS） or interleukin-4 （IL-4）. Methods Cytotoxicity of AD was assessed by the CCK-8 assay. RAW264.7 cells were polarized toward M1 phenotype by LPS or M2 phenotype by IL-4, followed by treatment with varying concentrations of AD. Macrophage polarization was analyzed by flow cytometry. Quantitative PCR was performed to measure mRNA expression of polarization-associated markers （IL-6, iNOS, Arg1, and Ym1）. ELISA was used to quantify secreted cytokines （TNF-α and IL-10）in the supernatant. Results At non-toxic concentrations, IL-6 and iNOS mRNA levels in LPS-stimulated cells were significantly upregulated while Arg1 and Ym1 expression in IL-4-treated groups were downregulated by AD. Concurrently, TNF-α secretion in LPS-induced M1 polarization was enhanced but IL-10 production in IL-4-induced M2 polarization was suppressed by AD. Conclusion AD could promote macrophage proliferation and viability, augments LPS-driven M1 polarization, and inhibit IL-4-mediated M2 polarization, which provided experimental evidence for the potential application of AD in tumor immunotherapy.

Accumulating evidence has demonstrated that nucleic acid-based therapies are promising for atherosclerosis. However, nearly all nucleic acid delivery systems developed for atherosclerosis necessitate injection, which results in rapid elimination and poor patient compliance. Consequently, oral delivery strategies capable of targeting atherosclerotic plaques are imperative for nucleic acid therapeutics. Herein we report the development of yeast-derived capsules (YCs) packaging an antisense oligonucleotide (AM33) targeting microRNA-33 (miR-33) for the oral treatment of atherosclerosis. YCs provide stability for AM33, preventing its premature release in the gastrointestinal tract. AM33-containing YCs, defined as YAM33, showed high transfection in macrophages, thus promoting cholesterol efflux and inhibiting foam cell formation by regulating the target genes/proteins of miR-33. Orally delivered YAM33 effectively accumulated within atherosclerotic plaques in ApoE ^-/- mice, primarily by transepithelial absorption via M cells in Peyer's patches and subsequent translocation via macrophages through the lymphatic system. Inhibition of miR-33 by oral YAM33 significantly delayed the progression of atherosclerosis. Moreover, oral treatment with YCs co-delivering AM33 and atorvastatin afforded significantly enhanced anti-atherosclerotic effects. Our findings suggest that yeast-based microcapsules represent an effective carrier for oral delivery of nucleic acids, either alone or in combination with existing drugs, offering a promising approach for precision therapy of atherosclerotic diseases.

Objective To observe the value of machine learning(ML)models based on ultrasound radiomics for preoperatively distinguishing atypical parathyroid tumor(APT)/parathyroid carcinoma(PC)and parathyroid adenoma(PA).Methods Totally 330 primary hyperparathyroidism patients who underwent surgical treatments were retrospectively enrolled and categorized into APT/PC group(n=78)and PA group(n=252)according to surgical pathology and clinical follow-up results,also divided into training set(n=231)and test set(n=99)at the ratio of 7∶3.Based on preoperative ultrasound,545 radiomics features were extracted,and recursive feature elimination(RFE),Kruskal-Wallis or analysis of variance methods were used to screen the features,respectively.Support vector machine(SVM),linear discriminant analysis(LDA),least absolute shrinkage and selection operator logistic regression(LRLASSO),also random forest(RF)and decision tree(DT)algorithms were adopted to construct ML models for differentiating APT/PC and PA,respectively.Then the models were trained in training set,their performance were verified in test set,and a 5-fold cross-validation was adopted to screen out the better combinations.Results Compared with Kruskal-Wallis and analysis of variance methods,the distinguishing efficacy of SVM,LDA,LRLASSO,RF and DT models constructed based on features screened out using RFE method in training set(area under the curve[AUC]=0.870,0.878,0.850,0.847,1.000)and test set(AUC=0.856,0.842,0.827,0.847 and 0.704)were all relatively higher.In test set,the AUC of SVM,LDA,LRLASSO and RF models constructed based on the features screened out using RFE method(included 25,23,17 and 23 features)were all higher than that of DT model(8 features)(all P＜0.001).No significant difference of AUC was found between SVM,LRLASSO or RF models and LDA model(all P＞0.05).The AUC of SVM and RF models were higher than that of LRLASSO model(both P＜0.05),while of SVM and RF models were not significantly different(P＞0.05),indicating that SVM,LDA and RF models were better ones.Conclusion SVM,LDA,LRLASSO,RF and DT models based on ultrasound radiomics could effectively distinguish APT/PC and PA preoperatively,among which SVM,LDA and RF models had better diagnostic efficacy.

Objective:To estimate the economic burden of 14 chronic diseases among middle-aged and elderly people in China.Methods:This cross-sectional study was based on longitudinal data from five waves (2011 to 2020) of the China Health and Retirement Longitudinal Study (CHARLS). Participants aged 45 and over who had been diagnosed with exactly one target chronic disease were included in the study. The 14 chronic diseases included: hypertension, dyslipidemia, diabetes or elevated blood glucose, malignant tumors, chronic pulmonary diseases, liver diseases, heart diseases, stroke, kidney diseases, digestive system diseases, emotional and mental diseases, memory-related diseases, arthritis or rheumatic diseases, and asthma. The economic burden of disease was measured in terms of both direct and indirect economic burden, with the results adjusted using a healthcare-specific Consumer Price Index (CPI). The direct economic burden included direct medical and non-medical burden. The human capital method was employed to calculate the indirect economic burden. A generalized linear mixed model (GLMM) was conducted to compare the differences in the economic burden between urban and rural areas, with provinces and prefecture-level cities set as random effects and residence (urban or rural areas) as fixed effects to control for the effects of geographic hierarchical structure. Gender, age and educational attainment were also included as covariates to control for confounding factors. The model′s robustness was assessed by comparing the significance of urban-rural differences before and after adding the covariates.Results:The median annual economic burden of the 14 chronic diseases among the middle-aged and elderly population in China ranged from 7 565 to 17 174 CNY, of which the direct economic burden ranged from 6 909 to 16 565 CNY, and the indirect burden ranged from 284 to 1 276 CNY. The direct economic burden was primarily driven by direct medical burden (83.67% to 95.01% of direct economic burden). Out-of-pocket expenses for outpatient medical burden ranged from 50% to 100%, while those for inpatient ranged from 36.30% to 61.29%. GLMM analysis revealed no statistically significant difference in the overall economic burden between urban and rural areas across diseases. However, the burden of inpatient medical burden for arthritis or rheumatism was higher in urban areas than in rural areas (5 338 vs. 3 898 CNY; LR=6.04, P=0.014). Similarly, the burden of self-treatment for hypertension was also higher in urban areas than in rural areas (324 vs. 238 CNY; LR=8.30, P=0.004). The outpatient non-medical burden for diabetes or elevated blood glucose (59 vs. 149 CNY; LR=5.99, P=0.014), stroke (0 vs. 307 CNY; LR=4.55, P=0.033), and digestive system diseases (45 vs. 107 CNY; LR=9.58, P=0.002) was lower in urban areas than rural. Conclusions:Chronic diseases cause heavy economic burden on middle-aged and elderly people in both urban and rural areas of China, with direct economic burden accounting for the majority of expenditure. The outpatient medical burden accounts for a higher proportion of out-of-pocket expenses than the inpatient.

Objective To investigate the epidemiological trends,temporal and spatial distribution characteristics of pulmonary tuberculosis in Lanping County.Methods Based on tuberculosis management data and basic information systems from the"China Disease Prevention and Control Information System,"pulmonary tuberculosis data from Lanping County for 2018-2023 were obtained.Descriptive epidemiology,concentration method,circular distribution method,and spatial autocorrelation analysis were used to conduct epidemiological and spatial analyses of the pulmonary tuberculosis data.Results A total of 2836 TB cases were reported in Lanping County from 2018 to 2023,with an average annual incidence rate of 233.26 per 100000,showing a declining trend.The male-to-female ratio was 1.95∶1,with the highest incidence among individuals aged 60 and above(932 cases,32.86%).Cases were predominantly among farmers(91.01%)and the Lisu ethnic group(52.68%).TB incidence showed weak seasonality with a bimodal distribution,with primary peak occurring from October to March and secondary peak from June to August.Tu'e Township(324.74 per 100,000),Shideng Township(307.42 per 100000),and Jinding Town(260.98 per 100,000)had the highest incidence rates,accounting for 1,284 cases or 45.28%of the county's total cases.In 2020,the incidence of pulmonary tuberculosis in Lanping County showed a spatial clustering distribution(global Morans's I value<0,P value<0.05),with Shideng Township consistently showing high-low aggregation characteristics.Conclusion Between 2018-2023,while the tuberculosis incidence rate in Lanping County has declined,it still falls short of Yunnan Province's tuberculosis prevention and control targets,and the prevention and control work continues to face significant challenges.Strengthening screening of high-risk populations and providing medical support to remote areas will be key measures for future prevention and treatment.

Objective: To analyze differences in the expression levels of lipid metabolism-related proteins in adi- pose tissue exosomes between obese mice and wild-type mice using proteomic techniques . Methods: Wild-type (WT) and obese (ob/ob) model mice of the same age were selected , with 8 mice per group . Adipose tissue from both groups was minced and cultured for 48 hours . Conditioned media was collected , and exosomes were isolated u- sing differential centrifugation . Liquid chromatography-tandem mass spectrometry ( LC-MS/MS) was utilized for proteomic analysis to screen differentially expressed proteins ( DEPs) . Gene ontology ( GO) enrichment analysis and kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis were performed on the DEPs . Heatmaps were generated to visualize DEPs expression patterns , and Western blot was employed to validate DEPs expression levels . Results: Exosomes were successfully extracted from the culture supernatant of adipose tissues from mice in the WT group and the ob/ob group . Mass spectrometry analysis identified a total of 25 629 peptides and 3 376 proteins . Compared with the WT group , there were 699 proteins with high expression and 632 proteins with low expression in the exosomes derived from adipose tissues of ob/ob mice . Both GO and KEGG analyses showed that DEPs were mainly enriched in metabolic pathways . Heatmap analysis visualized the expression patterns of metabolism-related DEPs , and the expression levels of lipid metabolism-related proteins such as acyl-CoA syn- thetase long-chain family member 1 (ACSL1) , apolipoprotein E (ApoE) , and albumin (Alb) changed significant- ly in the obese state (P < 0. 05) . Western blot verification results showed that the expression of ApoE and Alb pro- teins in the adipose tissue-derived exosomes of ob/ob mice decreased ( P < 0. 01) . Conclusion In the obese state , the expression levels of lipid metabolism-related proteins in mouse adipose tissue exosomes are significantly altered . These differentially expressed proteins may thus serve as potential molecular targets for treating obesity and its associated metabolic complications .

Objective To develop and compare the predictive performance of five machine learning models for adverse postoperative outcomes in cardiac surgery patients, and to identify key decision factors through SHapley Additive exPlanations (SHAP) interpretability analysis. Methods A retrospective collection of perioperative data (including demographic information, preoperative, intraoperative, and postoperative indicators) with 88 variables was conducted from adult cardiac surgery patients at the First Affiliated Hospital of Xinjiang Medical University in 2023. Adverse postoperative outcomes were defined as the occurrence of acute kidney injury and/or in-hospital mortality during the postoperative hospitalization period following cardiac surgery. Patients were divided into an adverse outcome group and a favorable outcome group based on the presence of adverse postoperative outcomes. After screening feature variables using the least absolute shrinkage and selection operator (LASSO) regression method, five machine learning models were constructed: eXtreme gradient boosting (XGBoost), random forest (RF), gradient boosting machine (GBM), light gradient boosting machine (LightGBM), and generalized linear model (GLM). The dataset was randomly divided into a training set and a test set at a 7 : 3 ratio using stratified sampling, with postoperative outcome as the stratification factor. Model performance was evaluated using receiver operating characteristic curves, decision curve analysis, and F1 Score. The SHAP method was applied to analyze feature contribution. Results A total of 639 patients were included, comprising 395 males and 244 females, with a median age of 62 (55, 69) years. The adverse outcome group consisted of 191 patients, while the favorable outcome group included 448 patients, resulting in an adverse postoperative outcome incidence of 29.9%. Univariate analysis showed no significant differences between the two groups for any variables (P>0.05). Using LASSO regression, 16 feature variables were selected (including cardiopulmonary bypass support time, blood glucose on postoperative day 3, creatine kinase-MB isoenzyme, systemic inflammatory response index, etc.), and five machine learning models (GLM, RF, GBM, LightGBM, XGBoost) were constructed. Evaluation results demonstrated that the XGBoost model exhibited the best predictive performance on both the training set (n=447) and test set (n=192), with area under the curve values of 0.761 [95%CI (0.719, 0.800) ] and 0.759 [95%CI (0.692, 0.818) ], respectively. It also significantly outperformed other models in positive predictive value, and balanced accuracy in the test set. Decision curve analysis further confirmed its clinical utility across various risk thresholds. SHAP analysis indicated that variables such as cardiopulmonary bypass support time, blood glucose on postoperative day 3, creatine kinase-MB isoenzyme, and inflammatory markers (SIRI, NLR, CAR) had high contributions to the prediction. Conclusion The XGBoost model effectively predicts adverse postoperative outcomes in cardiac surgery patients. Clinically, attention should be focused on cardiopulmonary bypass support time, postoperative blood glucose control, and monitoring of inflammatory levels to improve patient prognosis.