Objective To investigate the screening results and factors affecting abnormal detection rates among high-risk groups of esophageal cancer and to explore effective intervention measures. Methods We investigated and collected the information on gender, education level, age, marital status, symptoms of reflux esophagitis (heartburn, acid reflux, belching, hiccup, foreign body sensation in the pharynx, and difficulty swallowing), consumption of pickled vegetables, salt use, and esophageal cancer incidence of villagers in a natural village in Wenfeng District, Anyang City, Henan Province. Changes in reflux esophagitis symptoms in the high-incidence area of esophageal cancer before and after 16 years were observed, and the relationship of such changes with esophageal cancer was analyzed. Results In 2008, 711 cases were epidemiologically investigated, including 213 cases with one of the symptoms of reflux esophagitis such as heartburn, acid reflux, belching, hiccups, foreign body sensation in the pharynx, and difficulty swallowing (sorted in accordance with the abovementioned symptoms; if there are multiple symptoms, then the former is taken); 55 cases with at least two related symptoms, among which the most symptom was heartburn in 108 cases (15.1%); followed by acid reflux, belching, etc. In 2024, the same group of people was investigated, and eight people were missing because of relocation. A total of 703 people were successfully investigated, of which 189 cases (26.8%) had one of the symptoms of reflux esophagitis, such as heartburn (sorted in accordance with relevant symptoms, if there are multiple symptoms, then the former will be selected); 167 cases (23.7%) had at least two related symptoms, among which the most symptom was heartburn in 139 cases (19.7%); followed by acid reflux. Over 16 years, among the 703 people investigated, 45 cases had esophageal cancer and they had one or more of the abovementioned symptoms. No significant differences in the reflux esophagitis-like symptoms were found between 2008 and 2024 (P=0.26); no significant differences in the composition of reflux esophagitis-like symptoms were found between 2008 and 2024 (P=0.299). Conclusion The detection rate of reflux esophagitis-related symptoms in the population in a high-risk area of esophageal cancer has not decreased in the past 16 years, and the high-risk factors still exist. Esophageal cancer is closely related to reflux esophagitis, and clinical practice can provide early diagnosis and treatment for high-risk population.

Postmenopausal osteoporosis (PMOP) is a chronic metabolic bone disease caused by a decrease in estrogen levels. With the acceleration of population aging process, the public health burden caused by it is becoming increasingly severe. The prevalence rate of osteoporosis in people over 65 years old in China is as high as 32%, which is especially prominent after menopause, which is about 5 times that of elderly men. About 40% of postmenopausal women are at risk of osteoporotic fractures, with a disability rate of up to 50% and a fatality rate of about 20%. The prevention and treatment of osteoporosis has become a major public health issue of global concern, and it is particularly urgent to develop reasonable and effective prevention and treatment programs and explore their scientific basis. Exercise is an important non-drug means for the prevention and treatment of PMOP, it can improve estrogen levels and the expression of bone formation transcription factors, and inhibit the levels of proinflammatory factors and bone resorption markers, macroscopically manifested by the improvement of bone microstructure and bone density. However, the effectiveness of exercise in improving bone mineral density (BMD) remains controversial. Some studies revealed significant changes of bone to mechanical stimulation, while others showed no significant effect of mechanical training, this heterogeneity in bone adapt to mechanical stimulation is particularly evident in postmenopausal women. Although the evidence that a wide range of exercise programs can improve osteoporosis, the optimal solution to address bone mineral loss remains unclear. The most effective exercise type, dosage and personalized adaptation are still being determined. This study will fully consider the differences in gender and hormone levels, searching and screening randomized controlled trials of PubMed, CNKI and other databases regarding exercise improving bone mineral density in women with PMOP. Strictly following the PRISMA guidelines to reviewed and compared the effects of different types of exercise modalities on BMD at different sites in women with PMOP by network Meta-analysis, to provide theoretical guidance to maintain or improve BMD in women with PMOP.

OBJECTIVE To investigate the intervention effect and its potential mechanism of Yifei xuanfei jiangzhuo formula by inhibiting mitochondrial fission in a vascular dementia （VaD） model rats. METHODS VaD rat model was established by bilateral common carotid artery ligation. The experimental animals were randomly divided into sham operation group （SHAM）， model group （MOD），Yifei xuanfei jiangzhuo formula low-dose group （YFXF-L）， Yifei xuanfei jiangzhuo formula high-dose group （YFXF-H）， and Donepezil hydrochloride group （positive control）， with 9 animals in each group. After 30 days of intervention， the spatial learning memory ability was assessed by Morris water maze experiment； HE staining was used to observe histopathological changes in CA1 area of hippocampus； ELISA was used to detect the levels of serum inflammatory factors [interleukin-1β （IL-1β） and IL-4]； Western blot was used to detect the expressions of heat shock protein 90 （HSP90）/mixed lineage kinase domain-like protein （MLKL）/dynamin-related protein 1 （Drp1） pathway-related proteins， mitochondrial fusion proteins （MFN1， MFN2）， and adenosine triphosphate synthase 5A （ATP5A） in hippocampal tissues. The immunohistochemistry was used to detect the level of phosphorylated MLKL （p-MLKL）； real-time fluorescence quantitative PCR was adopted to detect mRNA expressions ofHSP90， MFN1， MFN2 and ATP5A. RESULTS Compared with SHAM group， the escape latency of rats in the MOD group was significantly prolonged， the number of crossing the platform was significantly reduced， and the hippocampal tissues showed typical neuronal damage characteristics， the positive expression level of p-MLKL and the serum level of IL-1β significantly increased， while the serum level of IL-4 significantly decreased， the protein and mRNA expression of HSP90， as well as the protein expressions of p-MLKL/MLKL and p-Drp1（Ser616）/Drp1 were all significantly increased in hippocampal tissue， the protein and mRNA expressions of MFN1， MFN2 and ATP5A， and protein expression of p-Drp1（Ser637）/Drp1 were all significantly decreased （P＜0.05）. After the intervention of Yifei xuanfei jiangzhuo formula， above indicators in each treatment group were all significantly reversed （P＜0.05）. CONCLUSIONS Yifei xuanfei jiangzhuo formula may alleviate neuronal damage and neuroinflammatory responses in VaD rats by regulating the HSP90/MLKL/Drp1 signaling pathway， inhibiting mitochondrial fission， thereby maintaining mitochondrial dynamic balance and improving mitochondrial function.

ObjectiveAutoimmune thyroiditis （AIT） is a complex and immune-mediated disorder， with no established treatment protocol. Both Western and traditional Chinese medicine （TCM） focus on the pathogenesis and treatment of AIT. This study evaluated the clinical consistency of existing AIT animal models based on the diagnostic criteria of both Western and TCM， using a novel evaluation method. Additionally， it proposed recommendations and future prospects for improving these models. MethodsA comprehensive literature review was conducted on existing AIT animal models， using databases and the diagnostic criteria of both Western and TCM. Core and accompanying symptoms of these models were scored based on the diagnostic criteria of both Western and TCM， and clinical consistency was assessed. ResultsMice are the primary experimental animals used in AIT modeling. Modeling methods include vaccine immunization， iodine induction， heterologous thyroid antigen immunization， and a combination of high iodine water and antigen immunization. The average consistency of clinical syndromes based on TCM and Western medicine is 40%， 60%， 54%， and 63%， with the highest consistency observed in the combined high iodine water and antigen immunization model. Pathological models based on TCM are less common， with the liver-stagnation-spleen-deficiency rat model showing high clinical consistency. While most models are designed according to Western medical theory， meeting the surface and structural effectiveness criteria of Western medicine. However， there is a lack of fine-tuning and clear differentiation of TCM syndromes. ConclusionCurrent AIT syndrome-disease combination animal models primarily reflect the pathological features of Western medicine， with limited integration of TCM syndromes. Future research should aim to combine the syndrome characteristics of TCM with the pathological features of Western medicine， creating multi-factor and dynamic syndrome-disease models. Such models would better facilitate an experimental platform that conforms to the theories of TCM， providing more comprehensive support and guidance for the pathogenesis and treatment strategies of AIT.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

Objective To understand the disease spectrum of a natural village in an area with high incidence of esophageal cancer to provide a reference for precise prevention and control. Methods From 2008 to 2024, 711 asymptomatic people over the age of 35 years in a natural village with high incidence of esophageal cancer in China were surveyed, and 171 of them were subjected to gastroscopy, biopsy, and pathological examination. All participants were followed up for a long time, and their disease history was recorded. Results A total of 16 years of follow-up were performed, and 703 people were effectively followed up. In 2008, 171 people underwent gastroscopy, and 160 people had biopsy and pathological results in endoscopic screening. By 2024, 76 people had been diagnosed with malignant tumors of 12 different types, and among these people, 45 had esophageal cancer. Conclusion Esophageal cancer remains a significant cause of morbidity and mortality from malignant tumors in this region. Biopsy and pathological examination should be strengthened during gastroscopy, and follow-ups and regular check-ups should be given high importance to reduce the incidence and mortality rates of esophageal cancer.

OBJECTIVE To summarize the implementation experiences of the China Hospital Association’s Clinical Pharmacist Instructor Training Program Reform， and to evaluate the effectiveness of the reform， thus continuously enhancing the quality and standards of clinical pharmacist instructor training. METHODS The study drew on project evaluation methodologies to summarize the main characteristics of the comprehensive system and new model for clinical pharmacist instructor training established through the reform by literature review. The “learning assessment” and “reaction assessment” were conducted by using Kirkpatrick’s four-level model of evaluation in order to evaluate the effectiveness of the clinical pharmacist instructor training reform through statistically processing and analyzing the performance data and teaching evaluation data of the instructor participants. Based on problem and trend analysis， the future development directions were anticipated for the reform of clinical pharmacist instructor training. RESULTS & CONCLUSIONS The latest round of clinical pharmacist instructor training reform initiated by the Chinese Hospital Association had initially established a four-pronged training system encompassing “recruitment， training， assessment， and management”. It had also forged a training 。 model “oriented towards enhancing clinical teaching competency， with practical learning and skill-based assessment conducted on clinical teaching sites as its core”. Following a period of over three years of gradual reform， the new training system and model became increasingly mature. In both 2023 and 2024， the participants achieved relatively high average total scores in their initial completion assessments [with scores of （84.05± 5.83） and （85.82±4.35） points， respectively]. They also reported a strong sense of gain from the training reform [with self- perceived gain scores of （4.80±0.44） and （4.85±0.39） points， respectively]. The operation and implementation effects of the reform were generally satisfactory. In the future， clinical pharmacist instructor training reforms should continue to address the issues remaining from the current phase， while aligning with global trends in pharmacy education and industry development. Additionally， sustained exploration and practice will be carried out around the core objective of “enhancing clinical teaching competence”.

The innate immune system serves as the body’s first line of defense against pathogens and plays a central role in inflammation regulation, immune homeostasis, and tumor immunosurveillance. In recent years, with the growing recognition of the concept “exercise is medicine”, increasing attention has been paid to the immunoregulatory effects of physical activity. Accumulating evidence suggests that regular, moderate-intensity exercise significantly enhances innate immunity by strengthening the skin-mucosal barrier, increasing levels of secretory immunoglobulin A (sIgA), and improving the functional capacity of key immune cells such as natural killer (NK) cells, neutrophils, macrophages, and dendritic cells. It also modulates the complement system and various inflammatory mediators. This review comprehensively summarizes the effects of exercise on each component of the innate immune system and highlights the underlying molecular mechanisms, including activation of AMP-activated protein kinase (AMPK), inhibition of nuclear factor-kappa B (NF-κB), enhancement of mitochondrial function via the PGC-1α/TFAM axis, and initiation of autophagy through the ULK1/mTOR pathway. Emerging mechanisms are also discussed, such as exercise-induced epigenetic modifications (e.g., histone acetylation and miRNA regulation), modulation of the gut microbiota, and metabolite-mediated immune programming (e.g., short-chain fatty acids (SCFAs), β‑hydroxybutyrate). The effects of exercise on innate immunity vary considerably among individuals, depending on factors such as age, sex, and comorbidities. For example, adolescents exhibit enhanced NK cell mobilization, whereas older adults benefit from reduced chronic inflammation and immune aging. Sex hormones and metabolic conditions (e.g., obesity, diabetes, chronic obstructive pulmonary disease, cancer) further modulate the immune response to exercise. Based on these insights, we propose a personalized approach to exercise prescription guided by the FITT (frequency, intensity, time, and type) principle, aiming to optimize immune outcomes across diverse populations. Importantly, given the dual role of exercise in immune activation and regulation, caution is warranted: while moderate exercise enhances immune defense, excessive or high-intensity activity may induce transient immunosuppression. In pathological contexts such as infection, autoimmune diseases, or tissue injury, exercise intensity and timing must be carefully adjusted. This review provides practical guidelines for exercise-based immune modulation and underscores the need for dose-response studies and advancements in precision exercise medicine. In conclusion, exercise represents a safe and effective strategy for enhancing innate immune function and mitigating chronic inflammatory diseases.

Objective: To investigate the effects of Zuogui Jiangtang Jieyu Formula (ZGJTJYF) on histone H3 lysine 18 lactylation (H3K18la) in the hippocampus of rats with diabetes mellitus complicated with depression (DD) and predict the regulatory genes of H3K18la. Methods: Male Sprague-Dawley rats were divided into control, model, and positive drug (metformin [0.18 g/kg] and fluoxetine [1.8 mg/kg]) groups, and the three groups were treated with high, medium, and low ZGJTJYF doses (20.52, 10.26, and 5.13 g/kg, respectively), with 10 rats per group. After treatment, the forced swimming and water maze tests were performed to assess depressive-like behaviors and cognitive function. An enzyme-linked immunosorbent assay was used to measure blood insulin, glycosylated hemoglobin, lactate levels, and lactate content in the hippocampus. Western blotting was used to detect H3K18la expression in the hippocampus. Cleavage Under Targets and lagmentation(CUT&Tag) experiments targeted hippocampal H3K18la epigenetic modification regions to analyze the transcription factors bound by H3K18la. Kyoto Encyclopedia of Genes and Genomes and Protein-Protein Interaction networks were constructed to identify key pathways and target genes regulated by H3K18la. Results: Compared with the normal group, the model group rats showed prolonged immobility time in the forced swim test, increased escape latency in the water maze experiment, decreased target quadrant distance ratio (P<0.01), increased serum lactate content, and decreased lactate content in hippocampal homogenate (P<0.01), as well as decreased H3K18la protein expression in the hippocampus (P<0.01). Compared with the model group, ZGJTJYF reduced the immobility time in the forced swim test and the escape latency in the water maze test (P<0.01), while the distance ratio in the target quadrant increased (P<0.01) in model rats. Lowered fasting blood glucose, insulin, and glycosylated hemoglobin levels (P<0.05, P<0.01) were also observed. ZGJTJYF also increased the lactate content and H3K18la protein expression in hippocampal homogenate (P<0.05, P<0.01). The DNA sequences bound by H3K18la were predominantly enriched at the transcription start sites. ZGJTJYF modulated H3K18la-associated pathways, including cell adhesion junctions, tumor growth factor-beta (TGF-β) signaling, stem cell pluripotency regulation, mitogen-activated protein kinase(MAPK) signaling pathway, and insulin resistance, leading to the identification of 12 target genes. Conclusion ZGJTJYF enhances hippocampal lactate levels and H3K18la modification in DD rats, which may regulate neural cell interactions, neurogenic stem cell function, TGF-β signaling, MAPK signaling, and insulin resistance pathways.

Virus-related lymphoma exhibits a dual nature as both a hematologic malignancy and a viral infectious disease， making it more resistant to treatment and associated with poorer prognosis. This paper analyzes the understanding and therapeutic advantages of traditional Chinese medicine （TCM） in virus-related lymphoma. It proposes a TCM-based approach centered around syndrome differentiation， using standardized measurements of the overall TCM condition， multi-omics research of hematologic tumors， and artificial intelligence technologies to identify the "pre-condition" of virus-related lymphoma. A risk warning model will be established to early identify high-risk populations with viral infections that may develop into malignant lymphoma， thereby establishing a risk warning system for virus-related lymphoma. At the same time， a TCM health management approach will be applied to manage and regulate virus-related lymphoma， interrupting its progression and forming a human-centered， comprehensive， continuous health service model. Based on this， a standardized， integrated clinical prevention and treatment decision-making model for virus-related lymphoma， recognized by both Chinese and western medicine， will be established to provide TCM solutions for primary prevention of major malignant tumors.