Objective To explore scientific and accurate prediction methods for the incidence of hand, foot, and mouth disease in the post-pandemic era, and to address modeling challenges caused by abnormal fluctuations in case numbers from 2020 to 2023. Methods The seasonal index was used to pre-process the data. The traditional seasonal autoregressive integrated moving average (SARIMA) model, singular spectrum analysis (SSA)-ARIMA model, ARIMA-Long short-term memory (LSTM) model, and SSA-ARIMA-LSTM model were used to fit the incidence from 2013 to 2023, and the incidence of hand, foot and mouth disease in 2024 was predicted. The real data collected in 2024 were used as the test set to compare the prediction performance of the models. Results The fitting performance of the constructed models was as follows: the ARIMA model had MAE=107.50 and RMSE=144.53, the SSA-ARIMA model showed MAE=2.84 and RMSE=4.33, the ARIMA-LSTM model achieved MAE=99.46 and RMSE=131.59, and the SSA-ARIMA-LSTM model had MAE=96.35 and RMSE=132.13. In terms of prediction performance, the ARIMA model resulted in MAE=151.64 and RMSE=146.70, the SSA-ARIMA model demonstrated MAE=41.22 and RMSE=57.01, the ARIMA-LSTM model yielded MAE=220.75 and RMSE=257.89, and the SSA-ARIMA-LSTM model recorded MAE=58.83 and RMSE=72.06. Conclusion The SSA-ARIMA model has the best fitting degree and the highest prediction accuracy, and is suitable for predicting the incidence trend of hand, foot and mouth disease.

Objective To explore the prevalence of Helicobacter pylori (Hp) infection and its association with dietary and lifestyle habits among the adult physical examination population in Xuzhou area. Methods Retrospectively selected the physical examination population who underwent HP testing at our hospital's physical examination center from May 2021 to December 2023 as the research object. The prevalence of Hp infection in the population was analyzed based on the physical examination results. A questionnaire survey was used to collect information on the eating and living habits of all study subjects. Logistic regression was used to analyze the relationship between eating and living habits and Hp infection. Results A total of 1 354 physical examination people were included in the study, and the Hp infection rate was 37.30% (505/1354). The difference in Hp infection rates among people of different age groups is statistically significant (P<0.05), with the middle-aged population (41-59 years old) having the highest Hp positive infection rate (45.38%).High salt (41.11%), hot diet (40.56%), history of smoking (45.23%) and drinking (43.80%), less consumption of fruits and vegetables (43.73%), irregular exercise (41.29%), irregular diet People who frequently eat out (43.56%) and eat out frequently (42.57%) have a higher Hp infection rate (P<0.05).After adjusting for demographic factors such as gender, age, place of residence and education level, multivariate Logistic regression results showed that high-salt diet (OR=3.975, 95%CI: 2.670-5.917) and hot diet (OR=3.357, 95%CI: 2.291-4.919), smoking (OR=1.458, 95%CI: 1.082-1.964), drinking alcohol (OR=1.654, 95%CI: 1.279-2.138), eating fruits and vegetables (OR=1.759, 95%CI: 1.345-2.301), regular exercise (OR=1.822, 95%CI: 1.371-2.421), regular diet (OR=1.893, 95%CI: 1.391-2.575), eating out (OR=1.690, 95%CI: 1.277-2.237) were associated with the risk of Hp infection (P<0.05). Conclusion The positive infection rate of Hp among the physical examination population in Xuzhou is slightly lower than the average epidemic level in China. Cultivating healthy eating and living habits can effectively reduce the risk of Hp infection.

Despite breakthroughs in immunotherapy for solid tumors, significant variations in treatment efficacy persist. Up to 80% of cancer patients suffer from malnutrition, which leads to: lymphoid atrophy and reduced T-cell reserves; deficiency of substrates required for T-cell activation and expansion; concurrent inflammation hindering T-cell infiltration into tumors; and cachexia accelerating PD-1 antibody clearance. Clinical studies confirm that severe malnutrition significantly impairs immune responses and increases the risk of treatment toxicity. Therefore, implementing standardized nutritional therapy is crucial for optimizing the reserve, activation, expansion, and infiltration capacity of immune cells, thereby providing a sound immune system foundation for immunotherapy. Immunonutrition therapy, by enhancing immunonutrients such as arginine, omega-3 polyunsaturated fatty acids, and nucleotides, reduces the secretion of pro-inflammatory mediators and promotes T-cell activation and proliferation. This enhances anti-tumor immune responses, prolongs survival, and advances cancer treatment towards multimodal combination and precision approaches.

ObjectiveTo systematically compare the differential regulation of the maternal-fetal interface cell lineages and communication networks in the CBA/J×DBA/2 mouse model of recurrent pregnancy loss （RPL） by the two classic therapeutic methods-tonifying the kidney to stabilize the fetus and invigorating the spleen to stabilize the fetus （Shoutai Wan， Juyuan Jian）-of traditional Chinese medicine （TCM） at the single-cell resolution and clarify their modern scientific connotations. MethodsFemale non-pregnant CBA/J mice were caged with male BALB/c （blank group） and DBA/2 （modeling group） mice separately. Pregnant mice in the modeling group were randomly grouped as follows： high/low-dose Shoutai Wan， high/low-dose Juyuan Jian， model （RPL）， and positive control （dydrogesterone）， with 10 mice in each group. Starting from the day after the detection of the vaginal plug， mice were administrated with drugs or an equal volume of normal saline by gavage for 10 consecutive days. After the intervention， the following indicators were measured. ① Macroscopic evaluation： general conditions， uterine wet weight， embryo loss rate， four coagulation parameters ［prothrombin time （PT）， activated partial thromboplastin time （APTT）， fibrinogen （FIB）， and thrombin time （TT）］， and peripheral blood estradiol （E₂） and progesterone （Pg） levels. The decidua with embryos was stained with hematoxylin-eosin （HE） and evaluated by transmission electron microscopy （TEM）. The expression of B-cell lymphoma-2 （Bcl-2）， vascular endothelial growth factor （VEGF）， angiotensin Ⅱ （AngⅡ）， matrix metalloproteinase-2 （MMP-2）， interleukin-6 （IL-6）， leukemia inhibitory factor （LIF）， CXC chemokine ligand 12 （CXCL12）， and microtubule-associated protein 1 light chain 3 homolog （LC3）Ⅰ/Ⅱ was quantified by Western blot. ② Mechanism analysis at the single-cell level： The decidua with embryos from the blank， model， high-dose Shoutai Wan， and high-dose Juyuan Jian groups （6 mice per group， with 3 single-cell samples per group， totaling 24 mice） were analyzed by the BD Rhapsody™ platform， and the whole-cell atlas was drawn by uniform manifold approximation and projection （UMAP） dimensionality reduction clustering combined with the single-cell mouse cell atlas （scMCA）. The differentially expressed genes （DEGs） and cell interaction networks were analyzed via Gene Ontology （GO）， Kyoto Encyclopedia of Genes and Genomes （KEGG）， and CellChat， and the protein-protein interaction （PPI） map of subtype cells was constructed. The CytoTRACE pseudo-temporal analysis was performed to explore the developmental trajectories of core immune cells （natural killer cells， NK cells） from maternal and fetal sources. Results① Pathological and Western blot results indicated that compared with the blank group， the RPL group showed an increase in the embryo loss rate （P<0.01）， down-regulated expression of Bcl-2， LIF， MMP-2， and Vegf in the decidua with embryos （P<0.05）， up-regulated protein levels of CXCL-12， AngⅡ， and IL-6 （P<0.05）， blocked angiogenesis， apoptosis-inflammation imbalance， and coagulation dysfunction. Both prescriptions dose-dependently reduced the abortion rate and restored the angiogenesis-inflammation balance， and Shoutai pill showed superior performance in restoring the E₂ level to the Pg level （P<0.05）. ② Single-cell transcriptome analysis indicated that compared with the blank group， the RPL group showed differences in multiple key cell populations such as decidual cells， trophoblast cells， endothelial cells， erythroblasts， NK cells， and macrophages at the maternal-fetal interface. Immunity and angiogenesis were the key links in RPL. Compared with the RPL group， high-dose Shoutai Wan reversed the changes of NK cells in the embryonic layer （upregulating the mRNA levels of 17 genes and downregulating the mRNA levels of 29 genes） and macrophages （upregulating the mRNA levels of 117 genes and downregulating the mRNA levels of 53 genes） through the regulation of gene expression. High-dose Shoutai pill regulated the immune cells to affect unfolded proteins， cell adhesion， and programmed cell death， thereby promoting decidualization and angiogenesis and modulating embryo-membrane development. High-dose Juyuan Jian regulated the key subgroups of NK cells （up-regulating the mRNA levels of 9 genes and down-regulating the mRNA levels of 17 genes） and macrophages （up-regulating the mRNA levels of 110 genes and down-regulating the mRNA levels of 81 genes）， which affected decidual inflammation and apoptosis and intervened in glycolysis. ③ The pseudo-temporal analysis and communication network indicated that the communication frequency of the RPL group decreased. High-dose Shoutai Wan restored maternal-fetal tolerance through pathways such as NKG2D， CDH5， GDF， and FASLG. High-dose Juyuan Jian enhanced the IL-6/LIFR/JAK/signal transducer and activator of transcription 3 （STAT3） and desmosome/SEMA6/tumor necrosis factor-like weak inducer of apoptosis （TWEAK） signaling to improve endometrial receptivity. The RPL group showed an increased proportion of toxic dNK7， a decreased proportion of reparative dNK4， and blocked embryo fNK1. High-dose Shoutai Wan down-regulated dNK7 and up-regulated dNK4. High-dose Juyuan Jian inhibited the terminal differentiation of dNK7 and up-regulated LILRB1， thus restoring the balance of cytotoxicity and repair. ConclusionBoth the kidney-tonifying and spleen-invigorating methods are effective in treating RPL. NK and macrophages are the key immune cells in the interaction between the embryo and the membrane. The kidney-tonifying method （Shoutai Wan） has an advantage in regulating the phenotypes of unfolded protein， cell adhesion， and programmed cell death， and shows expression characteristics closer to the physiological state in the regulation of NKG2D and CDH5 signals. The spleen-invigorating method （Juyuan Jian） has an advantage in regulating epithelial-mesenchymal transition （EMT）， angiogenesis， and glycolysis and shows higher communication intensity in the IL-6 and LIFR pathways.

Childhood simple obesity has become a significant public health issue in China. Modern medicine primarily relies on lifestyle interventions and often suffers from poor long-term compliance， while pharmacological options are limited and associated with potential adverse effects. Traditional Chinese Medicine （TCM） has a long history in the prevention and management of this condition， demonstrating eight distinct advantages， including systematic theoretical foundation， diversified therapeutic approaches， definite therapeutic efficacy， high safety profile， good patient compliance， comprehensive intervention strategies， emphasis on prevention， and stepwise treatment protocols. Additionally， TCM is characterized by six distinctive features： the use of natural medicinal substances， non-invasive external therapies， integration of medicinal dietetics， simple exercise regimens， precise syndrome differentiation， and diverse dosage forms. By combining internal and external treatments， TCM facilitates individualized regimen adjustment and holistic regulation， demonstrating remarkable effects in improving obesity-related metabolic indicators， regulating constitutional imbalance， and promoting healthy behaviors. However， challenges remain， such as inconsistent operational standards， insufficient high-quality clinical evidence， and a gap between basic research and clinical application. Future efforts should focus on accelerating the standardization of TCM diagnosis and treatment， conducting multicenter randomized controlled trials， and fostering interdisciplinary integration， so as to enhance the scientific validity and international recognition of TCM in the prevention and treatment of childhood obesity.

ObjectiveTo establish a new noninvasive， simple， and convenient clinical predictive model by identifying independent predictive factors for rebleeding after endoscopic therapy in cirrhotic patients with esophagogastric variceal bleeding （EGVB）， and to provide a basis for individualized risk assessment and development of clinical intervention strategies. MethodsCirrhotic patients with EGVB who were diagnosed and treated in The First Affiliated Hospital of Xi’an Medical University from September 2018 to October 2023 were enrolled as subjects， and according to whether the patient experienced rebleeding within 1 year after endoscopic therapy， they were divided into rebleeding group with 93 patients and non-rebleeding group with 84 patients. Clinical data were collected and analyzed. The independent samples t-test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. A Logistic model was established based on the results of the univariate and multivariate analyses， and the receiver operating characteristic （ROC） curve and the area under the ROC curve （AUC） were used to assess the accuracy of the model. R software was used to visualize the model by plotting a nomogram， and the Bootstrap method was used for internal validation of the model. ResultsThe multivariate analysis showed that red blood cell count （RBC）， cholinesterase （ChE）， alkaline phosphatase （ALP）， albumin （Alb）， thrombin time （TT）， portal vein trunk diameter， sequential therapy， and primary prevention were independent predictive factors for rebleeding. Based on the results of the multivariate analysis， a logistic model was established as logit（P）=-0.805-1.978×（RBC）+0.001×（ChE）-0.020×（ALP）-0.314×（Alb）+0.567×（TT）+0.428×（portal vein trunk diameter）-2.303×［sequential therapy （yes=1， no=0）］-2.368×［primary prevention （yes=1， no=0）］. The logistic model （AUC=0.928， 95% confidence interval ［CI］： 0.893—0.964， P<0.001） had a better performance in predicting rebleeding than MELD score （AUC=0.603， 95%CI： 0.520—0.687， P=0.003）， Child-Pugh class （AUC=0.650， 95%CI： 0.578—0.722， P=0.001）， and FIB-4 index （AUC=0.587， 95%CI： 0.503—0.671， P=0.045）. The model had an optimal cut-off value of 0.607， a sensitivity of 0.817， and a specificity of 0.817. Internal validation confirmed that the model had good predictive performance and accuracy. ConclusionSequential therapy， implementation of primary prevention， an increase in RBC， and an increase in Alb are protective factors against rebleeding， while prolonged TT and widened main portal vein diameter are risk factors. The logistic model based on these independent predictive factors can predict rebleeding and thus holds promise for clinical application.

Environmental pollution is a significant public health challenge worldwide, and investigating the causal relationship between environmental exposure and population health outcomes is a key objective of environmental epidemiology research. In recent years, the complexity of environmental exposures has increasingly come to the forefront, making it challenging for observational studies that dominate environmental epidemiology to accurately estimate causal effects. Causal inference methods are particularly advantageous in controlling for confounding factors, thus holding great potential in environmental epidemiology research. Researchers can use appropriate causal inference methods to simulate the process of randomization, providing strong support for revealing the causal relationship between environmental exposure and health outcomes. However, there is a lack of reviews on the application of causal inference methods in environmental epidemiology studies in China. Therefore, this study introduced the basic principles of common causal inference statistical methods in environmental epidemiology, summarized the applicable conditions, advantages and disadvantages of various methods, and provided R software implementation codes for these methods, aiming to offer guidance for optimizing research design and practicing causal inference statistical methods.

Objective: To develop a depression recognition model by integrating the spirit-expression diagnostic framework of traditional Chinese medicine (TCM) with machine learning algorithms. The proposed model seeks to establish a TCM-informed tool for early depression screening, thereby bridging traditional diagnostic principles with modern computational approaches. Methods: The study included patients with depression who visited the Shanghai Pudong New Area Mental Health Center from October 1, 2022 to October 1, 2023, as well as students and teachers from Shanghai University of Traditional Chinese Medicine during the same period as the healthy control group. Videos of 3 – 10 s were captured using a Xiaomi Pad 5, and the TCM spirit and expressions were determined by TCM experts (at least 3 out of 5 experts agreed to determine the category of TCM spirit and expressions). Basic information, facial images, and interview information were collected through a portable TCM intelligent analysis and diagnosis device, and facial diagnosis features were extracted using the Open CV computer vision library technology. Statistical analysis methods such as parametric and non-parametric tests were used to analyze the baseline data, TCM spirit and expression features, and facial diagnosis feature parameters of the two groups, to compare the differences in TCM spirit and expression and facial features. Five machine learning algorithms, including extreme gradient boosting (XGBoost), decision tree (DT), Bernoulli naive Bayes (BernoulliNB), support vector machine (SVM), and k-nearest neighbor (KNN) classification, were used to construct a depression recognition model based on the fusion of TCM spirit and expression features. The performance of the model was evaluated using metrics such as accuracy, precision, and the area under the receiver operating characteristic (ROC) curve (AUC). The model results were explained using the Shapley Additive exPlanations (SHAP). Results: A total of 93 depression patients and 87 healthy individuals were ultimately included in this study. There was no statistically significant difference in the baseline characteristics between the two groups (P > 0.05). The differences in the characteristics of the spirit and expressions in TCM and facial features between the two groups were shown as follows. (i) Quantispirit facial analysis revealed that depression patients exhibited significantly reduced facial spirit and luminance compared with healthy controls (P < 0.05), with characteristic features such as sad expressions, facial erythema, and changes in the lip color ranging from erythematous to cyanotic. (ii) Depressed patients exhibited significantly lower values in facial complexion L, lip L, and a values, and gloss index, but higher values in facial complexion a and b, lip b, low gloss index, and matte index (all P < 0.05). (iii) The results of multiple models show that the XGBoost-based depression recognition model, integrating the TCM “spirit-expression” diagnostic framework, achieved an accuracy of 98.61% and significantly outperformed four benchmark algorithms—DT, BernoulliNB, SVM, and KNN (P < 0.01). (iv) The SHAP visualization results show that in the recognition model constructed by the XGBoost algorithm, the complexion b value, categories of facial spirit, high gloss index, low gloss index, categories of facial expression and texture features have significant contribution to the model. Conclusion This study demonstrates that integrating TCM spirit-expression diagnostic features with machine learning enables the construction of a high-precision depression detection model, offering a novel paradigm for objective depression diagnosis.

Objective To explore the correlation between kinesiophobia and disease uncertainty, personal mastery, cardiac discomfort symptoms in patients with acute myocardial infarction (AMI) during recovery period. Methods A total of 320 patients with AMI admitted to the hospital were enrolled between January 2020 and January 2024. According to the results of Tampa Scale for Kinesiophobia Heart (TSK-H), they were divided into AMI kinesiophobia group (n=166) and simple AMI group (n=154). The disease uncertainty was evaluated by Mishel Uncertainty in Illness Scale for Adults (MUIS-A), personal mastery was evaluated by Personal Mastery Scale (PMS), and cardiac discomfort symptoms were evaluated by cardiac discomfort symptom scale. The correlation between kinesiophobia and disease uncertainty, personal mastery, cardiac discomfort symptoms in AMI patients was analyzed by Pearson correlation analysis. Results The scores of MUIS-A and cardiac discomfort symptoms in AMI kinesiophobia group were higher than those in simple AMI group (P<0.05), and PMS scores were lower than those in simple AMI group (P<0.05). The score of kinesiophobia was significantly positively correlated with scores of disease uncertainty and cardiac discomfort symptoms (r=0.628, 0.689, P<0.05), while significantly negatively correlated with the score of personal mastery (r=-0.526, P<0.05). Conclusion Kinesiophobia is related to disease uncertainty, personal mastery and cardiac discomfort symptoms in AMI patients during recovery period. Clinical medical staffs should focus on patients with the above characteristics. The targeted intervention measures can improve kinesiophobia and promote recovery of patients.

ObjectiveTo investigate the T lymphocyte subset levels and viral loads in newly human immunodeficiency virus (HIV) antibody-confirmed positive cases in Suzhou (2021‒2024), and to analyze potential influencing factors by integrating their demographic characteristics, immune status, and viral replication patterns, thereby providing evidence for HIV/acquired immune deficiency syndrome (AIDS) prevention and control. MethodsPeripheral whole blood samples were collected from newly confirmed HIV-positive cases in Suzhou from 2021 to 2024. T lymphocyte subset analysis and viral load testing were performed, and influencing factors were identified in combination with demographic characteristics. Logistic regression models were employed to identify factors associated with CD4⁺T lymphocyte counts ≤350 cells·μL^-1, and Spearman’s rank correlation test was used to analyze the correlation between logarithmic value of viral load and CD4⁺/CD8⁺ ratio. ResultsAmong the 3 022 confirmed HIV-positive samples, the median CD4⁺T lymphocyte count was 298.00 cells·μL^-1, with 882 cases (29.19%) showing CD4⁺ T lymphocyte counts <200 cells·μL^-1. The median CD8⁺T lymphocyte count was 1 011.00 cells·μL^-1. The median CD4⁺/CD8⁺ ratio was 0.28, with 32.46% of cases exhibiting CD4⁺/CD8⁺ ratios <0.20, and there were statistically significant differences in CD4⁺/CD8⁺ ratio among different genders, age groups, marital status, and sample sources (all P<0.05). Multivariate logistic regression analyses indicated that individuals aged ≥20 years, those who were divorced or widowed, and cases identified through medical institutions had a significantly higher proportion of CD4⁺T lymphocyte counts ≤350 cells·µL⁻¹ compared to those aged <20 years, unmarried individuals, and cases sourced from voluntary counseling and testing (VCT) clinics, respectively. The mean logarithmic value of viral load was (4.29±1.15) copies·mL^-1. The logarithmic value of viral load demonstrated a significantly negative correlation with both CD4⁺/CD8⁺ ratio (r=-0.43, P<0.001) and CD4⁺T lymphocyte count (r=-0.37, P<0.001). ConclusionA substantial proportion of newly diagnosed HIV/AIDS cases in Suzhou are late presenters with high viral load levels. Targeted interventions should prioritize high-risk populations through enhanced active surveillance and the implementation of combined T lymphocyte subsets analysis and viral load testing, which can enable earlier case-finding and timely antiretroviral therapy initiation.