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.

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 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.

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans ; Root Canal Therapy/adverse effects* ; Consensus ; Root Canal Preparation/adverse effects*

177Lu-prostate specific membrane antigen(PSMA)radio-ligand therapy has been approved abroad for advanced prostate cancer and has been in several clinical trials in China.Based on domestic clinical practice and experimental data and referred to international experience and viewpoints,the expert group forms a consensus on the clinical application of 177Lu-PSMA radio-ligand therapy in prostate cancer to guide clinical practice.

Objective To detect the expression changes of interleukin-10(IL-10)and transforming growth factor-β1(TGF-β1)during the development of deep vein thrombosis in mice,and to explore the application value of them in thrombus age estimation.Methods The mice in the experimental group were subjected to ligation of inferior vena cava.The mice were sacrificed by excessive anesthesia at 1 d,3 d,5 d,7 d,10 d,14 d and 21 d after ligation,respectively.The inferior vena cava segment with thrombosis was extracted below the ligation point.The mice in the control group were not ligated,and the inferior vena cava segment at the same position as the experimental group was extracted.The ex-pression changes of IL-10 and TGF-β1 were detected by immunohistochemistry(IHC),Western blot-ting and real-time qPCR.Results IHC results revealed that IL-10 was mainly expressed in monocytes in thrombosis and TGF-β1 was mainly expressed in monocytes and fibroblast-like cells in thrombosis.Western blotting and real-time qPCR showed that the relative expression levels of IL-10 and TGF-β1 in each experimental group were higher than those in the control group.The mRNA and protein levels of IL-10 reached the peak at 7 d and 10 d after ligation,respectively.The mRNA expression level at 7 d after ligation was 4.72±0.15 times that of the control group,and the protein expression level at 10 d after ligation was 7.15±0.28 times that of the control group.The mRNA and protein levels of TGF-β1 reached the peak at 10 d and 14 d after ligation,respectively.The mRNA expression level at 10 d after ligation was 2.58±0.14 times that of the control group,and the protein expression level at 14 d after ligation was 4.34±0.19 times that of the control group.Conclusion The expressions of IL-10 and TGF-β1 during the evolution of deep vein thrombosis present time-dependent sequential changes,and the expression levels of IL-10 and TGF-β1 can provide a reference basis for thrombus age estimation.

This study utilized the CCK-8 assay to examine the effects of various concentrations of CoCl2(0,50,100,200,300,400 μmol/L)and different treatment durations(0,6,12,24,48 h)on the viability of adipocytes,in order to determine the most suitable treatment conditions.Western blot analysis was employed to investigate the impact of different concentrations of CoCl2(0,50,100,200,400 μmol/L)on the expression of hypoxia and its downstream key proteins in adipocytes.The results indicated that higher concentrations of CoCl2 led to lower adipocyte viability,with sig-nificant decreases in cell viability observed in the 300,400 μmol/L treatment groups(P＜0.01),while the 200 μmol/L group exhibited the highest cell viability.Compared to the control group,the 200 μmol/L CoCl2 treatment group showed a significant upregulation in the expression of hypoxia and its downstream signaling pathway key molecules:hypoxia-inducible factor 1-alpha(HIF-1α),glucose transporter type 4(GLUT4),vascular endothelial growth factor receptor 1(FLT-1),prolyl hydroxylase 2(PHD2),and vascular endothelial growth factor(VEGF)(P＜0.01).Addi-tionally,the 200 μmol/L CoCl2 treatment group exhibited higher levels of key lipolytic enzymes,including adipose triglyceride lipase(ATGL),perilipin 1(PLIN1),protein kinase A(PKA),and increased phosphorylation levels of hormone-sensitive lipase(HSL)in the 300 and 400 μmol/L groui ps(P＜0.01).CoCl2-mediated hypoxia in the 200 μmol/L treatment group also in-creased the protein expression of phosphatidylinositol 3-kinase(PI3K)and the phosphorylation level of protein kinase B(Akt).These findings suggest that adding 200 μmol/L CoCl2 can enhance the expression of hypoxia-related proteins,lipolytic enzymes,and insulin-related signaling proteins in primary bovine adipocytes.

Objective:To analyze the genes related to platelet activation in essential thrombocythemia (ET)based on transcriptome sequencing technology (RNA-seq ),and to explore the potential targets related to ET thrombosis. Methods:Blood samples from ET patients and healthy individuals were collected for RNA-seq,and differentially expressed lncRNAs,miRNAs,and mRNAs were selected to construct a lncRNA-miRNA-mRNA regulatory network. Differential mRNAs in the regulatory network were enriched and analyzed using Gene Ontology (GO ) and Kyoto Encyclopedia of Genes and Genomes (KEGG).The real-time PCR method was applied to validate differential mRNAs on crucial signaling pathways.Results:A total of 32 lncRNAs (3 up-regulated,29 down-regulated),16 miRNAs (8 up-regulated,8 down-regulated),and 35 mRNAs (27 up-regulated,8 down-regulated)were identified as differentially expressed.Among them,5 lncRNAs,12 miRNAs,and 19 mRNAs constituted the regulatory network.KEGG enrichment analysis showed that the differential mRNAs were related to the platelet activation signaling pathway,and there were 6 differential mRNAs related to platelet activation,namely F2R,ITGA2B,ITGB1,ITGB3,PTGS1,and GP1 BB,which were all up-regulated in their expression.RT-PCR results showed that the expression of five mRNAs including F2R,ITGA2B,ITGB1,ITGB3,and GP1BB were upregulated in ET patients compared with healthy subjects,and consistent with RNA-seq results,while PTGS1 expression was not significantly different.Conclusion:Differential mRNAs in ET patients are related to the platelet activation pathway,and F2R,ITGA2B,ITGB1,ITGB3,and GP1BB mRNAs may serve as novel targets associated with platelet activation in ET.

Objective:Using cancer care as an example,we apply multi-dimensional data for healthcare region division in Beijing,and apply indicators to compare the results of the divisions.Methods:We use two approaches:the hospital catchments division method based on the hospital service range,and the K-Means clustering algorithm based on the population geographic distribution from the residents'healthcare needs,and established two indicators for comparison.Results:Three regions are divided by hospital service range method and eight regions by population geographic distribution method.The indicators of the number of beds per 100 000 population and the need satisfaction rate are more balanced among the different regions than when divided by administrative district.Conclusions:The distribution of healthcare resource in Beijing is significantly imbalanced.The region division based on hospital service range has extended the range of high-quality medical institutions.The division based on population geographical distribution reflects the actual supply and need of healthcare resources in different regions.Beijing can adopt the regional division method based on hospital service range to expand the service coverage of high-quality hospitals and reduce the imbalance in medical resources between central urban areas and suburban areas.The regional division based on population geographical distribution can provide decision support to achieve balanced allocation of healthcare resources.