Objective: To investigate the correlation between color parameters (L^*, a^*, b^*, Eab^*) and the contents of reducing sugars, total polysaccharides, total oligosaccharides, as well as four saccharides (fructose, glucose, sucrose, and kestose) during the nine cycles of steaming and sun-drying processing of Polygonatum kingianum, and to preliminarily explore the optimal processing duration.
Methods: The color changes were objectively evaluated using a colorimeter. The anthrone-sulfuric acid method was employed to determine total polysaccharides and oligosaccharides. The 3,5-dinitrosalicylic acid (DNS) colorimetric method was used to measure total reducing sugar content. High-performance liquid chromatography coupled with charged aerosol detection (HPLC-CAD) was applied for quantitative analysis of fructose, glucose, sucrose, and kestose. Multivariate statistical analysis was conducted to assess samples from different processing stages.
Results: Significant variations in color and component contents were observed across processing stages. The herbal pieces progressively darkened with increased processing cycles: brightness (L^*) and total color difference (Eab^*) initially decreased then stabilized, while a^* (red-green) and b^* (yellow-blue) values first increased then declined. Total polysaccharides and oligosaccharides showed overall decreasing trends, whereas reducing sugars initially increased before stabilizing. Fructose and glucose levels rose continuously, while sucrose and kestose decreased progressively, becoming undetectable after five cycles.
Conclusion: The chromatic alteration and saccharide composition of P. kingianum showed significant correlation with processing duration. Both total color difference (Eab^*) and reducing sugar content stabilized after four processing cycles (12 hours), suggesting that four cycles of steaming and sun-drying may represent the optimal processing duration.

Objective: To investigate the correlation between the color parameters (L^*, a^*, b^*, Eab^* values) of Polygoni Multiflori Radix Praeparata powder prepared by different processing techniques and the contents of 2,3,5,4’-tetrahydroxystilbene-2-O-β-D-glucopyranoside, emodin, physcion, emodin-8-O-β-D-glucopyranoside, physcion-8-O-β-D-glucopyranoside.
Methods: The L^*, a^*, b^* and Eab^* values of Polygoni Multiflori Radix Praeparata powder prepared by different processing techniques were determined by spectrophotometer, and the contents of the five components were determined by high performance liquid chromatography. Secondly, SPSS 26.0 software and Simca 14.1 software were used to analyze the correlation.
Results: Through the hierarchical cluster analysis (HCA), it was found that the steamed samples and black bean steamed samples could be obviously divided into two categories: raw products and processed products. The processed products could be further divided into 2-8 h and 12-48 h. Pearson correlation analysis showed that the content of stilbene glycoside was significantly positively correlated with L^*, a^* and b^* values (P<0.01). The a^* value was significantly positively correlated with the content of emodin and physcion (P<0.01). Emodin-8-O-β-D-glucoside was positively correlated with L^* value and b^* value, while physcion-8-O-β-D-glucoside was negatively correlated with a^* value. Partial least squares discriminant analysis (PLS) showed that 2,3,5,4’-tetrahydroxystilbene-2-O-β-D-glucoside (VIP=1.69) and emodin-8-O-β-D-glucoside (VIP=1.06) were the key variables affecting chromaticity characteristics (P<0.01).
Conclusion: The three processes of steaming, black bean steaming and black bean stewing are consistent in composition transformation and chromaticity variation, and stilbene glycoside can be used as a specific index component to characterize the processed color. Chromatic parameters can effectively reflect the processing progression and serve as quality monitoring indicators during production.

Objective: The cross sectional study aimed to identify predominant co-occurrence patterns among six common mental health issues in college students, so as to provide empirical basis for designing targeted interventions. Methods: From October 2024, a total of 9 837 students from 4 universities in Xiangtan City, Hunan Province, participated in the current study by multistage random cluster sampling method. Participants completed self report measures, including the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7 item Scale (GAD-7), Young s Internet Addiction Diagnostic Questionnaire, the Adolescent Insomnia Symptom Self rating Scale, the Ottawa Self injury Inventory, and the Brief Community Assessment of Psychic Experiences Questionnaire. Demographic and co-occurrence characteristics were first compared using Chi square or trend Chi-square tests, followed by application of the Apriori algorithm to mine association rules for primary co-occurrence patterns. Results: The detection rate of co-occuring the common mental health issues was 46.44%. The detection rate was significantly higher in female than in male students (50.42%, 43.61%; χ 2=44.46) and in students from rural versus urban areas (47.22%, 44.60%; χ 2=5.67) (both P <0.05). Significant differences were observed among freshmen, sophomores, juniors, and seniors (46.63%, 48.35%, 45.05% , 43.66%, respectively; χ 2=9.22, P <0.05), although no statistically significant trend was detected ( χ 2 trend =3.75, P = 0.05 ). Association rule mining identified “anxiety + depression” “anxiety + psychotic experiences + depression” and “anxiety + sleep disorder + depression” as the combinations with the highest support. In addition, “anxiety+depression+Internet addiction+psychotic experiences =>sleep disorder (>= refered to the occurrence of the latter item under the condition that the former item occurs)” and “anxiety + depression+Internet addiction=>sleep disorder” were combinations with relatively high confidence. Conclusions Co-occurrence of these mental health issues among college students is high and exhibits diverse patterns. Strategies to address this burden should prioritize integrated interventions that target these specific combinations of factors.

ObjectiveHepatocellular carcinoma (HCC) represents 90% of all primary liver cancers. The main risk factors associated with HCC include viral hepatitis (B and/or C), alcohol abuse, and metabolic dysfunction-associated steatotic liver disease (MASLD), which progressively advance to liver fibrosis, cirrhosis, and ultimately evolve into HCC. Surgical resection represents the most effective treatment for HCC, while recent advances in immunotherapy, including immune checkpoint inhibitors and adoptive cell therapies, have provided improved treatment prospects for patients with unresectable HCC. However, the complex metabolic heterogeneity of HCC limits the therapeutic efficacy. Metabolic intermediates acyl-CoA not only provide energy and substrates for numerous biochemical reactions but also serve as donors for protein lysine acylation, a major class of post-translational modification (PTM). Therefore, a deeper understanding of the molecular mechanisms underlying protein lysine acylation and hepatocarcinogenesis is urgently needed. MethodsThe levels of protein lysine acylation and silence information regulator 5 (SIRT5) expression levels in clinical HCC samples were analyzed by Western blot. Quantitative malonylome and succinylome of HCC samples were analyzed by antibody-based affinity enrichment coupled with tandem mass spectrometry. The proliferation of HCC cells was analyzed with Cell Counting Kit-8 (CCK-8) assays, the apoptosis was quantified by Annexin V-FITC/propidium iodide (PI) staining coupled with flow cytometry, and the ability of cells to migrate was assayed by Transwell assays. The enzymatic activity of glutathione S-transferase Mu 1 (GSTM1) was quantified. Transgenic mice with hepatic overexpression of SIRT5 were constructed using CRISPR-Cas9, and primary hepatocarcinogenesis was induced by administration of diethylnitrosamine. ResultsWestern blot analysis indicated that the expression level of SIRT5 was elevated in clinical samples from HCC patients, and the levels of lysine malonylation, glutarylation, and succinylation were significantly reduced in HCC tissues. Knockout of SIRT5 in MHCC-97H and MHCC-97L hepatoma cells suppressed cell proliferation, and increased the percentage of apoptotic cells significantly. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially malonylome and succinylome of HCC samples revealed significant enrichment in two major classes of biological processes: core energy metabolism (e.g., glycolysis/gluconeogenesis, tricarboxylic acid metabolic process, fatty acid beta oxidation) and detoxification and oxidative stress response (e.g., response to toxic substance, chemical carcinogenesis, reactive oxygen species (ROS)). SIRT5 removes malonylation from lysine residues in GSTM1 and restores its detoxification activity, which is crucial for the survival of hepatocytes under stressed conditions. More importantly, in vivo experiment indicated that hepatic-specific overexpression of SIRT5 in mice accelerated diethylnitrosamine-induced liver fibrosis and hepatocarcinogenesis, indicating the critical role of SIRT5 in HCC progression. ConclusionThis study highlights the previously unrecognized SIRT5-GSTM1 axis as a key regulator in hepatocarcinogenesis, and suggests a potential target for the treatment of patients with HCC.

Objective To explore the incidence and risk factors of sarcopenia in non-dialysis patients with stage 5 chronic kidney disease (CKD). Methods Non-dialysis stage 5 CKD patients in Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences from October 2023 to October 2024 were enrolled and divided into the non-sarcopenia group and the sarcopenia group according to lean tissue index (LTI) and handgrip strength (HGS). Demographic data of patients were collected and biochemical indicators were detected. Serum advanced glycation end products (AGEs) were detected by competitive ELISA. Multivariate logistic regression analysis was conducted to analyze the risk factors of sarcopenia in these patients. The diagnostic efficacy of the risk factors was evaluated by the receiver operating characteristic (ROC) curve. Results A total of 102 non-dialysis stage 5 CKD patients with (68.52±7.39) years, were enrolled, including 61 male (59.8%). Among them, 24 were diagnosed with sarcopenia (23.5%). Compared with patients in non-sarcopenia group, patients in sarcopenia group were older and had higher interleukin-6 (IL-6) and AGEs, lower body mass index (BMI) and lower serum albumin (sAlb; P＜0.05). Multivariate logistic regression showed that advanced age (OR＝1.153, 95%CI 1.045–1.273, P＝0.005), higher IL-6 (OR＝1.165, 95%CI 1.042–1.302, P＝0.007)、lower sAlb (OR＝0.675, 95%CI 0.542–0.840, P＝0.001), and higher serum AGEs (OR＝1.105, 95%CI 1.013–1.206, P＝0.024) were independent risk factors of sarcopenia in non-dialysis CKD 5 patients. The areas under the curve (AUC) for the age, IL-6, sAlb, and serum AGEs were 0.896, 0.643, 0.658, and 0.724, respectively. Conclusions Sarcopenia is common in non-dialysis stage 5 CKD patients, and the risk of sarcopenia is higher in non-dialysis stage 5 CKD patients with advanced age, higher IL-6, lower sAlb, and higher serum AGEs.

Objective: To analyze the structural changes in whole blood and apheresis platelet donations in Chinese Society of Blood Transfusion (CSBT) sentinel units from 2021 to 2025, and to provide evidence for donor recruitment and blood service management. Methods: Aggregated data reported by sentinel sites were collected and stratified according to six indicators: age, sex, donation history, donation volume, donation site, and organization mode. Pearson χ test, Cramer′V coefficient, Cochran-Armitage trend test and simple linear regression were adopted for analysis. Results: A total of 16 256 973 whole blood donations and 1 576 546 apheresis platelet donations were included. Among whole-blood donations, the proportion of donors aged 18-22 years decreased from 27.30% to 10.60%. The proportion of male donors increased from 58.81% to 63.13%; the proportion of people aged 30 and above increased from 58.40% to 75.30%; the proportion of fixed locations rose from 28.37% to 36.57%; the proportion of social groups increased from 21.69% to 39.69%. The 400-mL donations decreased from 62.12% to 53.46%, while individually initiated voluntary donations remained above 50%. Apheresis platelet donations were predominantly from males, individuals aged 30-39 years, and repeat donors; 2-treatment-unit apheresis platelet donations increased from 67.19% to 74.93%, and individually initiated donations accounted for 92.97%-96.02%. Statistically significant overall annual compositional differences were observed for all six indicators (all P<0.001), whereas linear trends for some sub-categories were not statistically significant. Conclusion: In the participating CSBT sentinel units, among whole blood donations, the proportions of donors aged 18-22 years, university-organized group donations, and donations at blood mobiles decreased, whereas the proportions of organizational group donations and donations at fixed venues increased. The apheresis platelet donation cohort is relatively mature and is evolving toward a high-efficiency donation model. Individual voluntary donation remains the primary organization mode for both donation types. Strategies such as youth donor recruitment, optimized layout of fixed donation sites, and retention of repeat donors should be strengthened to improve the resilience of blood supply.

Abstract To clarify the service targets, service contents, and safeguard mechanisms of the basic public service program for student vision health management, the study grounded in the current status of child and adolescent myopia prevention and control in China and integrated with the practical experience and innovative practices of Wuhan National Demonstration Area for Student Vision Health Management, takes education as the main thread and schools as the base, consolidating resources from multiple stakeholders including education administrative departments, schools, families, and professional technical service institutions. Centering on four core components—vision health education, monitoring and record keeping, risk prevention and control, and dynamic management, the study constructs a multi tiered basic public service system for vision health management of primary and secondary school students. It further proposes the use of an intelligent management platform and a "three tier color coded early warning" mechanism (red, yellow, blue) to prevent and control student myopia at the source, providing schools with replicable and operable implementation pathways to enhance the level of student vision health management.

ObjectiveTo address the key challenges in breast electrical impedance tomography (EIT) reconstruction including the severe ill‑posedness of the inverse problem, limited measurement information from the electrodes, low contrast of small lesions, as well as the common drawbacks of traditional reconstruction methods such as boundary blurring, low spatial resolution, and weak small-target detection capability, and to overcome the limitations of existing deep learning approaches namely low training efficiency, insufficient physical consistency, and substantial information loss during the low‑to‑high dimensional mapping process, this study proposes a multi‑scale attention and dynamic sparse mask fusion network (MADS‑Net). The proposed method aims to enhance high‑resolution reconstruction accuracy, small-lesion detectability, noise robustness, and computational efficiency in breast‑screening-oriented EIT, thereby providing a feasible solution for the application of EIT in breast functional imaging. MethodsThe proposed network adopts a strategy of “locate first, reconstruct later”. It realizes adaptive allocation of computational resources through a dynamic mask module, alleviates information loss in the low-to-high dimensional mapping process via a multi-scale attention mechanism, and embeds physical constraints to improve the physical rationality of reconstruction results. The performance of the proposed method was validated through systematic numerical simulations, agar phantom experiments, and porcine tissue experiments. Comparisons were made with mainstream methods including the Gauss-Newton algorithm, convolutional neural networks, U-Net, and Deep D-Bar. The image correlation coefficient (ICC), root mean square error (RMSE), and peak signal-to-noise ratio (PSNR) were adopted as quantitative evaluation metrics. Furthermore, lesion‑level evaluation metrics were introduced to assess the capability of different methods in reconstructing abnormal target boundaries and small‑sized target regions. ResultsExperimental results demonstrate that MADS-Net outperforms all comparison methods across all test scenarios. In numerical simulations, it achieves higher accuracy in target morphology and spatial location recovery as well as better background suppression. In agar phantom experiments, its detection and imaging reliability for small targets is significantly superior to the comparison methods. In porcine tissue experiments, the model maintains good generalization performance and can adapt to complex biological tissue imaging scenarios. Quantitative results show that MADS-Net achieves an average ICC of 0.917 6±0.048 8, an RMSE as low as0.060 6±0.031 6, and a PSNR of (23.893 9±2.685 3) dB. It successfully detects tiny targets as small as 5 mm within a 100 mm diameter sensing field, reduces the total training duration by 23.5% compared with the baseline method, and maintains stable reconstruction performance even under strong noise interference. ConclusionThe results demonstrate that MADS-Net achieves favorable EIT reconstruction performance in numerical simulations, agar phantom experiments, and porcine tissue experiments, even under common practical imaging challenges including low signal-to-noise ratio and blurred tissue boundaries. This study provides a methodological reference for further research on EIT in breast-screening-related scenarios and other medical functional imaging tasks, and also offers a low-cost, radiation-free alternative for breast lesion screening that aligns with the clinical demand for non-invasive diagnostic tools. It should be noted that real clinical breast data have not yet been used for validation in this study, and the clinical applicability of the proposed method requires further investigation. Future work will prioritize collecting multi-center real clinical breast datasets, and further optimize the model’s generalization ability to adapt to individual differences in breast tissue composition to promote its clinical application.

OBJECTIVE To establish the an optimal prediction model for carbapenem-resistant Acinetobacter bau-mannii(CRAB)infection in ICU patients based on machine learning(ML)so as to help clinicians to diagnose and make decisions.METHODS The clinical data were collected from the patients who were hospitalized in ICUs of a three-A hospital from Jan.1,2017 to Dec.31,2024 and were randomly divided into the training set and the test set in a 7∶3 ratio.The characteristic variables were selected by means of LASSO regression analysis in combina-tion with multivariate logistic regression analysis.Five types of M L classification models were integrated,the opti-mal model was analyzed and identified.The performance of the prediction model for CRAB infection in the ICU patients was evaluated with the use of sensitivity,specificity,accuracy,areas under receiver operating characteris-tic curves(AUCs),calibration curves,Hosmer-Lemeshow test and decision curve analysis(DCA).The outputs of the ML models were interpreted by Shapley additive explanations(SHAP)and permutation importance.RESULTS A total of 2 904 patients were enrolled in the study,695(23.93％)of whom had CRAB infection.The AUC of XGBoost model was highest in the training set and the test set,respectively(0.994 and 0.907).The result of Hosmer-Lemeshow test showed that the calibration curves of the XGBoost model indicated that the predicated risk was highly con-sistent with the observed risk(x2=7.323 and 4.609,P=0.513 and 0.764,respectively).The DCA curves showed that the XGBoost model performed best within the whole range of threshold,with the highest net profit.The length of ICU stay,use of tigecycline,central venous catheterization,use of carbapenems and use of ventilator were determined as the major predictive factors by means of SHAP.CONCLUSIONS The XGBoost model is established and interpreted by SHAP.It provides bases for screening of the ICU patients at high risk of CRAB infection.

Organophosphorus nerve agents are the most threatening chemical warfare agents and terrorist agents.The number of nerve agents and their related chemicals involved in the verification of Chemical Weapon Convention(CWC)exceeds ten million,with the majority being isomers.Accurate structural identification of these chemicals has always been one of the challenges in CWC related verification analysis.In this work,a total of 17 kinds of alkyl phosphonate isomers and structural analogs from 5 groups were designed and synthesized,and then analyzed by gas chromatography-mass spectrometry(GC-MS)and gas chromatography-infrared spectroscopy(GC-FTIR).The spectra of isomers or structural analogs obtained from two techniques as well as the structural information provided therein were compared and analyzed.The results showed that for isomers or structural analogs with similar MS spectra,FTIR spectra could provided more structural fingerprint information of compounds and had advantages in confirming structures.Combined with the excellent separation ability of GC,GC-FTIR can be used to assist GC-MS in the structural confirmation of alkyl phosphates,achieving rapid and accurate identification of isomers or structural analogues.