Objective: To characterize perioperative dynamic changes in immune-cell phenotypes and inflammatory cytokines in patients undergoing CPB (cardiopulmonary bypass) cardiac surgery, and to explore their associations with postoperative outcomes. Methods: In this prospective cohort study, 120 adult patients who underwent elective cardiac surgery under CPB at West China Hospital from May 2022 to March 2023 were enrolled. Perioperative immune-cell phenotypes and concentrations of 40 inflammation-related cytokines were measured. The primary outcomes were the sequential organ failure assessment (SOFA) score at 24 h after surgery and ΔSOFA (the peak SOFA score within 48 h after surgery minus the preoperative SOFA score). Secondary outcomes included major adverse cardiovascular events (MACE), acute kidney injury (AKI), respiratory failure, severe liver injury, and infection. Results: The mean age of enrolled patients was 57±10 years. Of these, 52% (62/120) were male and 90% (108/120) underwent valve surgery. During the rewarming to the end of CPB, neutrophil counts rapidly increased (7.39×10 /L vs preoperative 3.07×10 /L, P<0.001), with significant upregulation of CD11b (7.30×10 /L vs preoperative 3.05×10 /L, P<0.001) and CD54 (7.15×10 /L vs preoperative 2.99×10 /L, P<0.001). Lymphocyte counts increased at the end of CPB (1.75×10 /L vs preoperative 1.12×10 /L, P<0.001) but decreased significantly at 24 h after surgery (0.59×10 /L vs preoperative 1.12×10 /L, P<0.001). Plasma analysis showed that multiple pro-inflammatory cytokines increased during CPB and remained elevated up to 24 h after surgery; five chemokines and the anti-inflammatory cytokine IL-10 peaked at the end of CPB. The SOFA score increased from 1 (1, 2) preoperatively to 7 (5, 10) at 24 h after surgery, with a ΔSOFA of 6 (4, 8). Within 30 days after surgery, 48 patients (40.0%) developed AKI, 17 (14.2%) developed infection, 4 (3.3%) developed severe liver injury, 3 (2.5%) developed respiratory failure, and 3 (2.5%) experienced MACE. During the 2-year follow-up, 8 patients (6.7%) experienced MACE and 5 (4.2%) died. Conclusion: Multi-organ dysfunction is common after cardiac surgery under CPB (median ΔSOFA, 6), accompanied by perioperative activation of multiple immune-cell subsets and upregulation of pro-inflammatory, anti-inflammatory, and chemotactic mediators. This study provides data-driven evidence and research clues for further investigation of the associations between CPB-related immune perturbations and postoperative organ dysfunction and clinical outcomes.

ObjectiveTo explore the effects of Jingui Shenqiwan （JSW） and Liuwei Dihuangwan （LDW） on the reproductive ability and brain function of normal mice and compare the actions of the two medications. MethodsSeven groups of female and male mice were divided at a ratio of 2∶1. Except for the control group， the other six groups were as follows： a group of both males and females receiving JSW （3.0 g·kg^-1）， a group of both males and females receiving LDW （4.5 g·kg^-1）， a group of males receiving water and females receiving JSW， a group of males receiving water while females receiving LDW， a group of females receiving water while males receiving JSW， and a group of females receiving water while males receiving LDW. Each group was administered the drug for 14 days and then caged together at a 2∶1 （female∶male） ratio to detect the number of pregnant mice and calculate the pregnancy rate. Pregnant mice continued receiving the drug until they naturally gave birth， which was followed by the observation of newborn mice， calculation of their average number， and the measurement of the offspring's preference for sugar water and neonatal recognition index. At the end of the experiment， the weights of the thymus and spleen were measured to calculate the organ coefficients， and mRNA or protein expression was analyzed in the brain and testes or ovaries. A 1% sucrose solution was used to examine the euphoria of their brain reward systems， while novel object recognition test （NOR） was applied to assess their memory capabilities. mRNA expression was detected using real-time quantitative polymerase chain reaction （Real-time PCR） assay， and protein expression was analyzed with Western blot. ResultsCompared with the control group， oral administration of JSW to both male and female mice for 14 days significantly increased the pregnancy rate of female mice on day 2 after being caged together （P<0.05）， while LDW showed a trend but no statistical significance. Additionally， compared with the control group， JSW could upregulate the gene expression of gonadotropin-releasing hormone （GnRH） in the thalamus， as well as reproductive stem cell factor （SCF） and tyrosine kinase receptor （c-Kit） in the testes and reproductive stem cell marker mouse vasa homologue （MVH） in the ovaries， upregulate the expression of proteins influencing neuronal functional activity， such as brain-derived neurotrophic factor （BDNF）， in hippocampal neurons （P<0.05）， and enhance sucrose preference in male mice （P<0.05）. Compared with the control group， JSW significantly increased sucrose preference and novel object recognition index in offspring mice （P<0.05）， which was related to the upregulation of hippocampal dopamine D1 receptor （D1R） and N-methyl-D-aspartate receptor （Nmdar） gene expression. Compared with the control group， both JSW and LDW could upregulate the protein expression of glucocorticoid receptor （GR）， BDNF， and tyrosine kinase receptor B （TrkB） in the hippocampus of offspring mice （P<0.05）. ConclusionJSW significantly enhances the reproductive ability of normal mice， which is not only related to the release of gonadotropin but also associated with its regulation of brain function. Additionally， JSW has a certain regulatory effect on the brain function of the offspring mice.

Objective To explore the effectiveness of the cumulative sum (CUSUM) and the exponentially weighted moving average (EWMA) for early warning of influenza epidemic using two datasets of reported influenza cases and influenza-like illness (ILI) cases. Methods Using the reported cases of influenza and ILI in Daxing District, Beijing, from week 23 of 2018 to week 22 of 2024 as data sets, the CUSUM and EWMA models were established, respectively. The positive rate of influenza etiology was used as the ^“gold standard^”, and the Youden index was used as the evaluation index to compare the early warning effect of the two models under different data sets and different parameters. Results In CUSUM, the optimal Youden indices of the reported influenza cases set and the ILI cases set were 0.751 and 0.635, respectively. In EWMA, the optimal Youden indices of the reported influenza cases set and the ILI cases set were 0.544 and 0.464, respectively. The optimal EWMA and CUSUM models could both issue early warning signals in advance of the ^“gold standard^”. Conclusion In the influenza epidemic early warning in Daxing District, Beijing, the CUSUM model established with the reported cases of influenza can achieve good early warning effects, but the model parameters need to be dynamically adjusted according to the local epidemic characteristics.

ObjectiveTo develop a standardized classification model for traditional Chinese medicine （TCM） syndrome patterns of mixed hemorrhoids using multi-center real-world data， and unveil their distribution patterns and core risk factors， thereby providing evidence-based support for standardizing TCM syndrome differentiation and implementing precision interventions. MethodsA multi-center cross-sectional study was conducted， enrolling 13 283 mixed hemorrhoid patients from eight hospitals in Jiangsu Province between September 1st， 2023 and December 31st， 2024. DeepSeek-R1-Distill-Qwen-7B and LLaMA-3.3 large language models （LLM） were integrated with latent class analysis （LCA） to perform unsupervised learning and latent class modeling of TCM symptomatology. Potential risk factors were screened via univariate analysis， followed by logistic regression to identify independent risk factors for each syndrome pattern. ResultsThe model's performance indicators were stable and reliable across different clinical data types，i.e. in the outpatient records， past medical history （F1=99.7%）， current medical history （F1=94.9%）， and specialist examination （F1=90.7%）； in inpatient records， past medical history （F1=98.2%）， current medical history （F1=91.2%）， specialist examination （F1=90.3%）， and discharge status （F1=90.6%）. Latent class mode-ling identified four core TCM syndrome patterns including spleen deficiency and qi sinking syndrome （915 cases， 6.89%）， damp-heat pouring downward syndrome （10 820 cases， 81.46%）， qi stagnation and blood stasis syndrome （1252 cases， 9.43%）， and wind injuring intestinal collaterals syndrome （296 cases， 2.22%）， with respective latent class probabilities of 0.069， 0.815， 0.094， and 0.022. Logistic regression demonstrated that gender， age， disease duration， hypertension， diabetes， hyperlipidemia， constipation， smoking history， and alcohol consumption were independent risk factors for pattern differentiation （P＜0.05）. The efficacy validation evaluation revealed that the cure rates for patients with spleen deficiency and qi sinking syndrome and qi stagnation and blood stasis syndrome were higher than those for patients with damp-heat pouring downward syndrome （adjusted P＜0.05）， with no statistically significant differences among other syndrome patterns. ConclusionDamp-heat pouring downward syndrome is the predominant syndrome in mixed hemorrhoids. Gender， age， disease duration， hypertension， diabetes， hyperlipi-demia， constipation， smoking history， and alcohol consumption are independent risk factors for the differentiation of syndrome types.

This paper has constructed a traditional Chinese medicine （TCM） specialized disease dataset platform for mixed hemorrhoids based on a multimodal large model， and the preliminary application has been validated. The platform uses StarRocks to establish a four-level data warehouse system， enabling the aggregation， cleaning， and standardization of multi-source heterogeneous data. Using DeepSeek-R1-Distill-Qwen-7B as the base model， domain fine-tuning is performed through low-rank adaptation （LoRA） technology. Combined with LLaMA-3.3 natural language processing and reasoning chain techniques， the platform enables intelligent parsing and structured extraction of unstructured TCM medical records. It accurately identifies six major categories and 28 subcategories of entities， including symptoms and syndromes， with a fine-tuned model F1 score of 93.8%. The platform has established a high-quality specialized disease dataset containing more than 50,000 medical records and has been applied in a real-world study involving 17,831 patients， preliminarily verifying the efficacy of TCM heritage surgery.

The research and development of innovative drug have progressed remarkably, but the long development circle and high failure rate have become the bottleneck. Drug repurposing, discovering new indications of approved drugs, is a strategy to overcome these obstacles. By exploring new indications for approved drugs, rapid progress has been made in basic research and clinical translation in recent years. Rich resources of drugs, proven security, efficient development workflow and reduced cost are core advantages of this strategy, making the strategy a crucial direction of optimizing the pipeline of drug research and development. This review systematically summarizes drug repurposing cases that have received clinical approval over the past five years, and proposes core strategies for drug repurposing, including approaches based on targets, pathways, drug similarity, post-treatment phenotypes, and clinical side effects, aiming to provide some strategic guidance for drug repurposing efforts.

ObjectiveTo compare the differences in fungal community composition between lesional and non-lesional scalp areas in patients suffering from severe alopecia areata （AA）， and compare these with healthy scalp areas in control subjects. Additionally， to preliminarily explore the changes in scalp fungal communities in severe AA patients and their potential underlying immunological mechanisms. MethodsA total of 20 severe AA patients and 18 healthy controls were enrolled. Skin swab samples were collected from lesional and non-lesional scalp areas of severe AA patients， as well as from the normal scalp of healthy controls. The fungal internal transcribed spacer （ITS） region was amplified and analyzed using high-throughput sequencing. ResultsThe lesional scalp areas of severe AA patients exhibited higher α-diversity and species richness in fungal communities. Notably， the relative abundance of Ascomycota， along with genera such as Mycosphaerella， Aspergillus， Penicillium， and Wallemia， significantly increased in the bald regions. In contrast， Acremonium and Schizophyllum were more predominant in the non-lesional areas of severe AA patients. ConclusionDistinct region-specific differences in scalp fungal microbiota in severe AA patients suggests that fungal dysbiosis may play a potential role in the pathogenesis of alopecia areata. These findings provide new insights into the disease characteristics of severe AA from the perspective of scalp microecology.

Systemic inflammatory response (SIR) evoked by cardiopulmonary bypass (CPB) is still one of the major causes of postoperative multiple organs injuries. Since the concentrations of circulating inflammatory factors are positively associated with postoperative adverse events, removal or inhibition of inflammatory factors are considered as effective treatments to improve outcomes. After more than 20 years of research, however, the results are disappointed as neither neutralization nor removal of circulating inflammatory factors could reduce adverse events. Therefore, the role of circulating inflammatory factors in CPB-related organs injuries should be reconsidered in order to find effective therapies. Here we reviewed the association between circulating inflammatory factors and the outcomes, as well as the current therapies, including antibody and hemadsorption. Most importantly, the role of circulating inflammatory factors in SIR was reviewed, which may be helpful to develop new measures to prevent and treat CPB-related organs injuries.

Hepatic encephalopathy （HE） is a common complication of severe liver disease in the end stage， and it is urgently needed to improve the rate of effective treatment and clarify the pathogenesis of HE. The liver is a crucial hub for immune regulation， and disruption of immune homeostasis is a key factor in the pathological mechanisms of HE. As the main metabolites of intestinal flora， short-chain fatty acids （SCFAs） play a vital role in the biological processes of both innate and adaptive immunity and can regulate the proliferation and differentiation of immune cells maintain the homeostasis of intestinal microenvironment and the integrity of barrier function. Studies have shown that SCFAs participate in bidirectional and dynamic interactions with the liver-gut-brain axis through immunomodulatory pathways， thereby playing an important role in the diagnosis， treatment， and prognostic evaluation of HE. Starting from the immunoregulatory effect of SCFAs， this article summarizes and analyzes the crosstalk relationship between SCFAs and the liver-gut-brain axis and the significance of SCFAs in the diagnosis and treatment of HE， in order to provide new ideas for optimizing clinical prevention and treatment strategies.

Background::Computer-aided detection (CAD) software has been introduced to automatically interpret digital chest X-rays. This study aimed to evaluate the performance of CAD software (JF CXR-1 v3.0, which was developed by a domestic Hi-tech enterprise) in tuberculosis (TB) case finding in China.Methods::In 2019, we conducted an internal evaluation of the performance of JF CXR-1 v3.0 by reading standard images annotated by a panel of experts. In 2020, using the reading results of chest X-rays by a panel of experts as the reference standard, we conducted an on-site prospective study to evaluate the performance of JF CXR-1 v3.0 and local radiologists in TB case finding in 13 township health centers in Zhongmu County, Henan Province.Results::Internal assessment results based on 277 standard images showed that JF CXR-1 v3.0 had a sensitivity of 85.94% (95% confidence interval [CI]: 77.42%, 94.45%) and a specificity of 74.65% (95% CI: 68.81%, 80.49%) to distinguish active TB from other imaging conditions. In the on-site evaluation phase, images from 3705 outpatients who underwent chest X-ray detection were read by JF CXR-1 v3.0 and local radiologists in parallel. The imaging diagnosis of local radiologists for active TB had a sensitivity of 32.89% (95% CI: 22.33%, 43.46%) and a specificity of 99.28% (95% CI: 99.01%, 99.56%), while JF CXR-1 v3.0 showed a significantly higher sensitivity of 92.11% (95% CI: 86.04%, 98.17%) ( p < 0.05) and maintained high specificity at 94.54% (95% CI: 93.81%, 95.28%). Conclusions::CAD software could play a positive role in improving the TB case finding capability of township health centers.