AIM: To investigate the influence of pterygium thickness and area on corneal refractive status.METHODS: Prospective longitudinal study. A total of 60 cases(60 eyes)of pterygium patients admitted to our hospital from January 2024 to September 2024 were randomly selected. All patients underwent pterygium excision combined with pedicle conjunctival flap transplantation for treatment. Optical coherence tomography(OCT)was used to measure the preoperative thickness of patient's pterygium, and a digital slit lamp microscope was used to measure the area of pterygium. The corneal refractive status(degree of corneal astigmatism and average curvature)and changes in uncorrected visual acuity of patients before surgery, 1 d, 1, and 3 mo after surgery were compared. The relationship between preoperative thickness and area of pterygium in patients and corneal refractive status indicators at different postoperative time points were analyzed, and Logistic regression was used to analyze the impact of pterygium thickness and area on postoperative visual improvement in patients.RESULTS: All patients completed follow-up after surgery for 3 mo. At 3 mo after surgery, visual acuity improved in 21 eyes(35%). The results of bivariate Pearson correlation analysis showed that the thickness and area of pterygium positively correlated with the degree of corneal astigmatism and uncorrected visual acuity before surgery and 1 d, 1, and 3 mo after surgery(all P<0.05), and negatively correlated with the average corneal curvature before surgery and 1 d, 1, and 3 mo after surgery(all P<0.05). Logistic regression analysis showed that the thickness and area of pterygium before surgery, high degree of corneal astigmatism, and low uncorrected visual acuity(large LogMAR value)were all risk factors for poor postoperative visual improvement in patients(OR>1, P<0.05). The large average corneal curvature before surgery was a protective factor for poor postoperative visual improvement in patients(OR<1, P<0.05).CONCLUSION: The increase in thickness and area of pterygium can, to some extent, improve corneal astigmatism, reduce the average curvature of the cornea, and affect postoperative visual recovery.

ObjectiveTo explore the improving effect of Huangqi Chifengtang（HCT） on atherosclerosis（AS）， and elucidate its mechanism in relation to adenosine monophosphate-activated protein kinase（AMPK）/peroxisome proliferator-activated receptor α（PPARα） signaling pathway and nucleotide-binding oligomerization domain（NOD）-like receptor thermal protein domain associated protein 3（NLRP3） inflammasome. MethodsEight C57BL/6J mice were set as the normal group， and 32 ApoE^-/- mice were randomly divided into the model group， the positive drug group（atorvastatin， 5 mg·kg^-1·d^-1）， HCT low- and high-dose groups（1.95， 3.90 g·kg^-1·d^-1）. ApoE^-/- mice were fed with high-fat and high-cholesterol feed to establish an AS mouse model. After modeling， they were orally administered corresponding dose of drugs for 28 days， while the normal and model groups received an equal volume of physiological saline via oral gavage. Hematoxylin-eosin（HE） staining was used to observe the pathological status of the aorta and liver in mice， Biochemical testing and enzyme-linked immunosorbent assay（ELISA） were used to detect the levels of total cholesterol（TC）， triglycerides（TG）， low-density lipoprotein cholesterol（LDL-C）， alanine aminotransferase（ALT）， aspartate aminotransferase（AST）， C-reactive protein（CRP）， interleukin（IL）-1β， IL-18 in the serum， as well as superoxide dismutase（SOD）， malondialdehyde（MDA）， and reduced glutathione（GSH） in the liver. Real-time fluorescence quantitative polymerase chain reaction（Real-time PCR） was used to measure the mRNA expression levels of NLRP3， apoptosis-associated speck-like protein（ASC）， cysteinyl aspartate specific proteinase-1（Caspase-1）， Toll-like receptor 4（TLR4） in the aorta， and fatty acid synthase（FAS）， stearoyl-CoA desaturase 1（SCD1）， PPARα， and carnitine palmitoyltransferase 1A（CPT1A） in the liver. Immunohistochemistry was used to determine the protein expressions of NLRP3， Caspase-1， and ASC in the aorta， and Western blot was used to measure the protein expressions of AMPK， p-AMPK， sterol regulatory element binding protein-1c（SREBP-1c）， CPT1A， and FAS in the liver. ResultsCompared with the normal group， the model group showed a significant increase in lipid plaque deposition in the aorta and lipid accumulation in the liver， the levels of TC， TG， LDL-C， AST， ALT， IL-1β， IL-18 and CRP in the serum were significantly increased（P<0.01）， and the mRNA and protein expressions of aortic TLR4， NLRP3， Caspase-1 and ASC were significantly upregulated（P<0.01）. The levels of SOD and GSH in the liver were significantly reduced， while the level of MDA was significantly increased（P<0.01）. The mRNA expressions of FAS and SCD1 in the liver were significantly downregulated， while the mRNA expressions of PPARα and CPT1A were significantly upregulated. The protein expressions of p-AMPK/AMPK and CPT1A in the liver were significantly reduced， while the expressions of SREBP-1c and FAS proteins were significantly increased（P<0.01）. Compared with the model group， the low- and high-dose HCT groups showed significant improvements in aortic plaques and hepatic lipid deposition. The levels of TC， LDL-C， AST， IL-1β and IL-18 in the serum of the low-dose HCT group， as well as TC， TG， LDL-C， AST， ALT， IL-1β， IL-18 and CRP in the serum of the high-dose HCT group， were significantly reduced（P<0.01）. The mRNA expressions of TLR4， NLRP3 and Caspase-1 in the aorta of the low-dose HCT group， as well as TLR4， NLRP3， Caspase-1 and ASC in the aorta of the high-dose HCT group， were significantly downregulated（P<0.01）. The protein expressions of Caspase-1 and ASC in the aorta of the low-dose HCT group， as well as NLRP3， Caspase-1 and ASC in the high-dose HCT group， were significantly downregulated（P<0.01）. The levels of SOD and GSH in the liver of the low- and high-dose HCT groups were significantly increased， while the level of MDA in the high-dose HCT group was significantly decreased（P<0.05， P<0.01）. In the HCT-treated group， the mRNA expressions of FAS and SCD1 in the liver were significantly upregulated， while the mRNA expressions of PPARα and CPT1A were significantly downregulated， the protein expressions of p-AMPK/AMPK and CPT1A in the liver were significantly increased， while the protein expressions of SREBP-1c and FAS were significantly decreased（P<0.05， P<0.01）. ConclusionHCT can improve lipid metabolism by activating the AMPK/PPARα pathway and inhibit NLRP3 inflammasome-mediated inflammatory responses， thereby reducing hepatic lipid deposition and AS plaque formation.

[Objective] To study on the genotyping of a sample with inconsistent forward and reverse serological tests, and to conduct a pedigree investigation and molecular biological mechanism study. [Methods] The ABO blood group of the proband and his family members were identified using blood group serological method. The ABO gene exon 1-7 of samples of the proband and his family were sequenced by Sanger and single molecule real-time sequencing (SMRT). DeepTMHMM was used to predict and analyze the transmembrane region of proteins before and after mutation. [Results] The proband and his mother have the Bw phenotype, while his maternal grandfather has ABw phenotype. The blood group results of forward and reverse typing of other family members were consistent. ABO gene sequencing results showed that there was B new mutation of c.3 G>C in exon 1 of ABO gene in the proband, his mother and grandfather, leading to a shift in translation start site. DeepTMHMM analysis indicated that the shift in the translation start site altered the protein topology. [Conclusion] The c.3G>C mutation in the first exon of the ABO gene leads to a shift in the translation start site, altering the protein topology from an α-transmembrane region to a spherical signaling peptide, reducing enzyme activity and resulting in the Bw serological phenotype.

Laboratory animals are essential in scientific research and experimental teaching in colleges and universities. Disciplines such as life sciences, medicine, pharmacy, chemistry, and biomedical engineering heavily rely on animal experiments. The standardized barrier environmental facility for laboratory animals provides a fundamental platform for stable, scientific, and reliable animal experiment results. Rigorous access management for such facilities is a vital safeguard for maintaining standardized operations of facilities, controlling the quality and stability of laboratory animals, mitigating pathogen contamination risks among animals and laboratory staff, and preventing biosecurity incidents such as zoonotic disease outbreaks. Taking the small-scale barrier facilities for laboratory rats and mice at Nanjing University's Xianlin Campus, operational since 2019, as an example, this study focuses on the safety access management system of these facilities. Based on five years of operational data and accumulated experience in studying and optimizing the access management system, this study, from the perspectives of management system development and the formulation and implementation of standard operating procedures, reviews five aspects of access management: personnel access, animals access, material access, equipment access, and air circulation control. Furthermore, these aspects are systematically analyzed and summarized to serve as a reference for the construction and management of the laboratory animal facilities in universities, while also contributing to scientific research, public health security, and the well-being of experimental personnel.

BACKGROUND:Osteosarcoma has a complex pathogenesis and a poor prognosis.While advancements in medical technology have led to some improvements in the 5-year survival rate,substantial progress in its treatment has not yet been achieved. OBJECTIVE:To screen key molecular markers in osteosarcoma,analyze their relationship with osteosarcoma treatment drugs,and explore the potential disease mechanisms of osteosarcoma at the molecular level. METHODS:GSE99671 and GSE284259(miRNA)datasets were obtained from the Gene Expression Omnibus database.Differential gene expression analysis and Weighted Gene Co-expression Network Analysis(WGCNA)on GSE99671 were performed.Functional enrichment analysis was conducted using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes separately for the differentially expressed genes and the module genes with the highest positive correlation to the disease.The intersection of these module genes and differentially expressed genes was taken as key genes.A Protein-Protein Interaction network was constructed,and correlation analysis on the key genes was performed using CytoScape software,and hub genes were identified.Hub genes were externally validated using the GSE28425 dataset and text validation was conducted.The drug sensitivity of hub genes was analyzed using the CellMiner database,with a threshold of absolute value of correlation coefficient|R|>0.3 and P<0.05. RESULTS AND CONCLUSION:(1)Differential gene expression analysis identified 529 differentially expressed genes,comprising 177 upregulated and 352 downregulated genes.WGCNA analysis yielded a total of 592 genes with the highest correlation to osteosarcoma.(2)Gene Ontology enrichment results indicated that the development of osteosarcoma may be associated with extracellular matrix,bone cell differentiation and development,human immune regulation,and collagen synthesis and degradation.Kyoto Encyclopedia of Genes and Genomes enrichment results showed the involvement of pathways such as PI3K-Akt signaling pathway,focal adhesion signaling pathway,and immune response in the onset of osteosarcoma.(3)The intersection analysis revealed a total of 59 key genes.Through Protein-Protein Interaction network analysis,8 hub genes were selected,which were LUM,PLOD1,PLOD2,MMP14,COL11A1,THBS2,LEPRE1,and TGFB1,all of which were upregulated.(4)External validation revealed significantly downregulated miRNAs that regulate the hub genes,with hsa-miR-144-3p and hsa-miR-150-5p showing the most significant downregulation.Text validation results demonstrated that the expression of hub genes was consistent with previous research.(5)Drug sensitivity analysis indicated a negative correlation between the activity of methotrexate,6-mercaptopurine,and pazopanib with the mRNA expression of PLOD1,PLOD2,and MMP14.Moreover,zoledronic acid and lapatinib showed a positive correlation with the mRNA expression of PLOD1,LUM,MMP14,PLOD2,and TGFB1.This suggests that zoledronic acid and lapatinib may be potential therapeutic drugs for osteosarcoma,but further validation is required through additional basic experiments and clinical studies.

Tumor drug resistance is an important problem in the failure of chemotherapy and targeted drug therapy, which is a complex process involving chromatin remodeling. SWI/SNF is one of the most studied ATP-dependent chromatin remodeling complexes in tumorigenesis, which plays an important role in the coordination of chromatin structural stability, gene expression, and post-translation modification. However, its mechanism in tumor drug resistance has not been systematically combed. SWI/SNF can be divided into 3 types according to its subunit composition: BAF, PBAF, and ncBAF. These 3 subtypes all contain two mutually exclusive ATPase catalytic subunits (SMARCA2 or SMARCA4), core subunits (SMARCC1 and SMARCD1), and regulatory subunits (ARID1A, PBRM1, and ACTB, etc.), which can control gene expression by regulating chromatin structure. The change of SWI/SNF complex subunits is one of the important factors of tumor drug resistance and progress. SMARCA4 and ARID1A are the most widely studied subunits in tumor drug resistance. Low expression of SMARCA4 can lead to the deletion of the transcription inhibitor of the BCL2L1 gene in mantle cell lymphoma, which will result in transcription up-regulation and significant resistance to the combination therapy of ibrutinib and venetoclax. Low expression of SMARCA4 and high expression of SMARCA2 can activate the FGFR1-pERK1/2 signaling pathway in ovarian high-grade serous carcinoma cells, which induces the overexpression of anti-apoptosis gene BCL2 and results in carboplatin resistance. SMARCA4 deletion can up-regulate epithelial-mesenchymal transition (EMT) by activating YAP1 gene expression in triple-negative breast cancer. It can also reduce the expression of Ca²⁺ channel IP3R3 in ovarian and lung cancer, resulting in the transfer of Ca²⁺ needed to induce apoptosis from endoplasmic reticulum to mitochondria damage. Thus, these two tumors are resistant to cisplatin. It has been found that verteporfin can overcome the drug resistance induced by SMARCA4 deletion. However, this inhibitor has not been applied in clinical practice. Therefore, it is a promising research direction to develop SWI/SNF ATPase targeted drugs with high oral bioavailability to treat patients with tumor resistance induced by low expression or deletion of SMARCA4. ARID1A deletion can activate the expression of ANXA1 protein in HER2+ breast cancer cells or down-regulate the expression of progesterone receptor B protein in endometrial cancer cells. The drug resistance of these two tumor cells to trastuzumab or progesterone is induced by activating AKT pathway. ARID1A deletion in ovarian cancer can increase the expression of MRP2 protein and make it resistant to carboplatin and paclitaxel. ARID1A deletion also can up-regulate the phosphorylation levels of EGFR, ErbB2, and RAF1 oncogene proteins.The ErbB and VEGF pathway are activated and EMT is increased. As a result, lung adenocarcinoma is resistant to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). Although great progress has been made in the research on the mechanism of SWI/SNF complex inducing tumor drug resistance, most of the research is still at the protein level. It is necessary to comprehensively and deeply explore the detailed mechanism of drug resistance from gene, transcription, protein, and metabolite levels by using multi-omics techniques, which can provide sufficient theoretical basis for the diagnosis and treatment of poor tumor prognosis caused by mutation or abnormal expression of SWI/SNF subunits in clinical practice.

OBJECTIVE To investigate the effects and mechanism of asperuloside （Asp） on the pyroptosis of intestinal epithelial cells in rats with ulcerative colitis （UC）. METHODS The male SD rats were randomly divided into Control group， model group （UC group）， ASP low-dose and high-dose groups [Asp-L， Asp-H groups， Asp 35， 70 mg/（kg·d）]， ASP high-dose group+AMPK inhibitor Compound C group [Asp-H+Compound C group， Asp 70 mg/（kg·d）+Compound C 0.2 mg/（kg·d）]， with 12 rats in each group. Except for Control group， the other groups were injected with 50% ethanol （0.25 mL）+5% 2，4， 6- trinitrobenzene sulfonic acid solution （2 mL/kg） into the intestinal cavity to construct UC model. After modeling， the rats in each drug group were given corresponding drug solution by gavage or （and） tail vein injection， once a day， for 14 consecutive days. After the last administration， the weight of rats in each group was measured， and the length of their colons was measured； disease activity index （DAI） score and colonic mucosal damage index （CMDI） score were performed， and the serum levels of inflammatory factors （interleukin-18， -1β， -6） were detected. The pathological changes of the colon tissue were observed. The expressions of pyroptosis-related proteins [caspase-1， gasdermin D （GSDMD）] in colon tissue， and pathway-related proteins such as adenosine monophosphate-activated protein kinase （AMPK）， thioredoxin-interacting protein （TXNIP）， NOD-like receptor protein 3 （NLRP3） and apoptosis-associated speck-like protein containing a CARD （ASC） were all detected. RESULTS Compared with Control group， the colon tissue structure of rats in UC group was damaged， with obvious infiltration of inflammatory cells and edema. Their body weight， colon length and phosphorylation level of AMPK protein were significantly reduced or shortened； DAI and CMDI scores， serum levels of inflammatory factors， and the protein expressions of caspase-1， GSDMD， TXNIP， NLRP3 and ASC in colon tissue were increased or upregulated significantly （P＜0.05）. Compared with UC group， the pathological damage of colon tissue in rats was relieved in Asp-L and Asp-H groups， and all quantitative indicators were significantly improved （P＜0.05）； the improvement effect of Asp-H group was more significant （P＜0.05）. Compound C could significantly reverse the improvement effect of high-dose of Asp on the above indicators in UC rats （P＜0.05）. CONCLUSIONS Asp can improve inflammatory damage in colon tissue and inhibit pyroptosis of intestinal epithelial cells in UC rats， which is associated with the activation of AMPK and inhibition of TXNIP/NLRP3 signaling pathway.

OBJECTIVE To investigate the effects and mechanism of asperuloside （Asp） on the pyroptosis of intestinal epithelial cells in rats with ulcerative colitis （UC）. METHODS The male SD rats were randomly divided into Control group， model group （UC group）， ASP low-dose and high-dose groups [Asp-L， Asp-H groups， Asp 35， 70 mg/（kg·d）]， ASP high-dose group+AMPK inhibitor Compound C group [Asp-H+Compound C group， Asp 70 mg/（kg·d）+Compound C 0.2 mg/（kg·d）]， with 12 rats in each group. Except for Control group， the other groups were injected with 50% ethanol （0.25 mL）+5% 2，4， 6- trinitrobenzene sulfonic acid solution （2 mL/kg） into the intestinal cavity to construct UC model. After modeling， the rats in each drug group were given corresponding drug solution by gavage or （and） tail vein injection， once a day， for 14 consecutive days. After the last administration， the weight of rats in each group was measured， and the length of their colons was measured； disease activity index （DAI） score and colonic mucosal damage index （CMDI） score were performed， and the serum levels of inflammatory factors （interleukin-18， -1β， -6） were detected. The pathological changes of the colon tissue were observed. The expressions of pyroptosis-related proteins [caspase-1， gasdermin D （GSDMD）] in colon tissue， and pathway-related proteins such as adenosine monophosphate-activated protein kinase （AMPK）， thioredoxin-interacting protein （TXNIP）， NOD-like receptor protein 3 （NLRP3） and apoptosis-associated speck-like protein containing a CARD （ASC） were all detected. RESULTS Compared with Control group， the colon tissue structure of rats in UC group was damaged， with obvious infiltration of inflammatory cells and edema. Their body weight， colon length and phosphorylation level of AMPK protein were significantly reduced or shortened； DAI and CMDI scores， serum levels of inflammatory factors， and the protein expressions of caspase-1， GSDMD， TXNIP， NLRP3 and ASC in colon tissue were increased or upregulated significantly （P＜0.05）. Compared with UC group， the pathological damage of colon tissue in rats was relieved in Asp-L and Asp-H groups， and all quantitative indicators were significantly improved （P＜0.05）； the improvement effect of Asp-H group was more significant （P＜0.05）. Compound C could significantly reverse the improvement effect of high-dose of Asp on the above indicators in UC rats （P＜0.05）. CONCLUSIONS Asp can improve inflammatory damage in colon tissue and inhibit pyroptosis of intestinal epithelial cells in UC rats， which is associated with the activation of AMPK and inhibition of TXNIP/NLRP3 signaling pathway.

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 innovatively apply the pre-intelligent precision dosing and verification system （hereinafter referred to as “the system”）， and to provide a reference for the high-level “intelligent” transformation of inpatient pharmacy. METHODS The limitations of the triple-serial dispensing mode， which comprised the automatic medicine packaging machine （ATC）， intelligent tablet dispensing table （ITDT） and medication detection machine （MDM）， were analyzed. The application of the system and the adoption of the barcode scanning verification method optimized the pre-dosing management， whole-tablet drug dispensing process and ATC temporary dosing management. The comparative analysis was conducted to assess dosing time， labor cost and packaging error of the eight-month period， before and after the system application. RESULTS The triple-serial dispensing mode had a weak ability to avoid error risks in the manual dosing stage， and also had errors in the verification stage. Through the innovative application system， the pre-dosing management had been upgraded， the whole-tablet drug dispensing process had been optimized， and the ATC temporary dosing management had been improved. The average time required for each drug for pre-dosing， whole-tablet drug dispensing and ATC temporary dosing was significantly shortened after the application of the system， compared with before the application of the system （P＜0.001）. The number of pharmacists was reduced from two to one. The error rate of ATC decreased significantly from 0.220‰ to 0.029‰ （P＜0.001）. Specifically， the rate of pharmacist-related errors （pre-dosing error， ITDT dosing error， and ATC temporary dosing error） decreased from 0.116‰ to 0.001‰ （P＜0.001）， and machine-related errors decreased from 0.096‰ to 0.023‰ （P＜0.001）. CONCLUSIONS This innovative integration mode greatly improves the working efficiency and quality of inpatient pharmacy. It enhances refined management of drug expiration and inventory， saves time and labor costs， improves the accuracy of drug dispensing， and ensures patient medication safety.