The Type III Secretion System (T3SS) serves as a pivotal virulence apparatus for numerous Gram-negative bacterial pathogens, enabling them to infect both animal and plant hosts. Functioning as a molecular syringe, the T3SS directly translocates bacterial effector proteins from the bacterial cytoplasm into the interior of eukaryotic host cells. These effectors are central weapons that precisely manipulate a wide spectrum of host cellular physiological processes, ranging from cytoskeletal dynamics to immune signaling, to establish a favorable niche for bacterial survival and proliferation. Among the diverse arsenal of T3SS effectors, the YopJ family constitutes a critical group of virulence factors. Members of this family are characterized by a conserved catalytic triad structure—a hallmark of the CE clan of cysteine proteases that has been evolutionarily repurposed to confer acetyltransferase activity. A defining and intriguing feature of these enzymes is their stringent dependence on a host-derived eukaryotic cofactor, inositol hexakisphosphate (IP₆), for allosteric activation. This requirement acts as a sophisticated molecular safeguard, ensuring enzymatic activity only within the appropriate host environment, thereby preventing detrimental effects on the bacterium itself. While seminal studies on individual members such as Yersinia’s YopJ and Salmonella’s AvrA have provided deep mechanistic insights, a systematic and integrative understanding of the structure-function relationships across the entire family remains fragmented. Key questions persist regarding how a conserved catalytic core has diverged to recognize distinct host substrates in different kingdoms of life. To address this gap, this article provides a systematic review of the YopJ family, focusing on three interconnected aspects: their structural features, their catalytic mechanism, and their divergent immunosuppressive strategies in animal versus plant hosts. By conducting a comparative analysis of the sequences and resolved three-dimensional structures of three representative members (e.g., HopZ1a, PopP2, AvrA), we elucidate regions of significant variation embedded within the conserved core catalytic architecture. These variable regions, often involving surface loops and substrate-binding interfaces, are crucial determinants of target specificity and functional specialization. The functional divergence of this effector family is most apparent when comparing their modes of action in different hosts. In animal hosts, YopJ-family effectors primarily sabotage innate immune signaling pathways. They achieve this by acetylating key serine and threonine residues within the activation loops of critical kinases in the MAPK and NF‑κB pathways. This post-translational modification blocks the phosphorylation and subsequent activation of these kinases, leading to potent suppression of inflammatory cytokine production. Conversely, in plant hosts, the strategy broadens to dismantle the two-tiered plant immune system. YopJ homologs target a more diverse set of substrates, including immune-associated receptor-like cytoplasmic kinases (RLCKs), microtubule networks via tubulin acetylation (which disrupts cellular trafficking and signaling), and transcription factors central to defense gene regulation. This multi-target approach effectively suppresses both Pattern-Triggered Immunity (PTI) and Effector-Triggered Immunity (ETI). In conclusion, this synthesis aims to deepen the mechanistic understanding of YopJ family-mediated pathogenesis by integrating structural biology with cellular function across host kingdoms. Elucidating the precise molecular basis for substrate selection—how conserved platforms achieve target diversity—is a major frontier. Furthermore, this knowledge provides a vital theoretical foundation for developing novel anti-virulence strategies. Targeting the conserved IP₆-binding pocket or the catalytic acetyltransferase activity itself represents a promising avenue for designing broad-spectrum inhibitors that could disarm this critical family of bacterial effectors, potentially offering new therapeutic approaches against a range of pathogenic bacteria.

ObjectiveTo explore an centralized clinical practice teaching model delivered via a summer short-term semester, and to examine its effectiveness on empathy and communication efficacy among undergraduate students majoring in rehabilitation therapy through a mixed-methods design. MethodsFrom June to July, 2025, forty second-year rehabilitation therapy undergraduates from Nanchang Medical College participated in a one-week immersive clinical practice during the summer short-term semester. An action research framework integrating a one-group pre-post experimental design and qualitative research methods were adopted. Quantitative data were collected using the Chinese-Adapted Jefferson Scale of Empathy-Medical Student Version (JSE-HP) to assess changes in empathy. Qualitative data were obtained through semi-structured focus group interviews and structured reflective journals to investigate students' experiences and transformations in empathic cognition, emotional integration and professional identity. ResultsAfter the teaching intervention, students demonstrated significant improvements in the total score of JSE-HP and all subdimensions (perspective taking, compassionate care and standing in the patient's shoes) (t < -3.69, P < 0.01). Qualitative analysis yielded three core themes: reconstruction of clinical reasoning paradigms, emotional-cognitive integration and elevation of professional identity. ConclusionSummer short-term semester clinical practice model, structured around “clinical immersion, narrative reflection, interprofessional collaboration and formative assessment”, effectively facilitates embodied cultivation of empathy. This model not only bridges the gap between theory and clinical practice, but also serves as an educational catalyst for students' transformation from technical performers to humanistic caregivers. It aligns with the core concepts of the World Health Organization rehabilitation competency framework, offering a replicable and scalable approach to advancing systematic reform in medical humanities education.

OBJECTIVE To investigate the effects and potential mechanism of Panax notoginseng saponins （PNS） on gastric mucosal injury and inflammatory response in rats with chronic atrophic gastritis （CAG） via the stem cell factor（SCF）/cellular tyrosine kinase receptor（c-kit） signaling pathway. METHODS Male SD rats were used to establish a CAG rat model through intragastric administration of N -methyl- N ′-nitro- N -nitrosoguanidine combined with an irregular diet. Successfully modeled rats were randomly divided into a model group， positive control-vitacoenzyme group （Positive group， 250 mg/kg）， PNS low- and high-dose groups （PNS-L and PNS-H groups， 9， 18 mg/kg）， and high-dose PNS+SCF/c-kit inhibitor group （PNS-H+ISCK03 group， 18 mg/kg+47 mg/kg）， with 8 rats in each group. Additionally， 8 healthy rats were selected as a control group. After the final administration， the activities of serum gastrin （GAS）， motilin （MTL） and pancreatic polypeptide （PP）， as well as the levels of tumor necrosis factor-α （TNF-α）， interleukin-10 （IL-10）， and IL-8 in gastric mucosal tissues， were measured in each group. Pathological changes of the gastric mucosal and ultrastructure of the epithelial cells were observed， and gastric mucosal atrophy was scored. Cell apoptosis in gastric mucosal tissues and the expressions of proliferating cell nuclear antigen （PCNA）， nuclear factor-κB p65 （NF-κB p65）， SCF and c-kit were detected. RESULTS Compared with the control group， the model group showed significantly increased inflammatory cell infiltration in the gastric mucosal， extensive epithelial cell detachment， severe ultrastructural damage， and significantly elevated or up-regulated gastric mucosal atrophy score， TNF-α and IL-8 levels in gastric mucosal， cell apoptosis rate， and NF-κB p65 protein expression. Meanwhile， serum levels of GAS and MTL， PP activity， the level of IL-10 in gastric mucosal tissue， and protein expressions of PCNA and SCF， as well as the phosphorylation level of c-kit， were significantly decreased or down-regulated （ P ＜0.05）. Compared with the model group， Positive， PNS-L and PNS-H groups exhibited markedly improved pathological changes in the gastric mucosal and significant amelioration of the quantitative indicators， with the PNS-H group showing significantly better improvement than the PNS-L group （ P ＜0.05）. However， ISCK03 significantly reversed the ameliorative effects of high-dose PNS on the above indicators in rats （ P ＜0.05）. CONCLUSIONS PNS improves gastric mucosal injury in CAG rats by reducing the inflammatory response and promoting gastric mucosal repair； these effects may be related to the activation of the SCF/c-kit signaling pathway.

BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

ObjectiveThe nucleolar protein PES1 (Pescadillo homolog 1) plays critical roles in ribosome biogenesis and cell cycle regulation, yet its involvement in cellular senescence remains poorly understood. This study aimed to comprehensively investigate the functional consequences of PES1 suppression in cellular senescence and elucidate the molecular mechanisms underlying its regulatory role. MethodsInitially, we assessed PES1 expression patterns in two distinct senescence models: replicative senescent mouse embryonic fibroblasts (MEFs) and doxorubicin-induced senescent human hepatocellular carcinoma HepG2 cells. Subsequently, PES1 expression was specifically downregulated using siRNA-mediated knockdown in these cell lines as well as additional relevant cell types. Cellular proliferation and senescence were assessed by EdU incorporation and SA-β-gal staining assays, respectively. The expression of senescence-associated proteins (p53, p21, and Rb) and SASP factors (IL-6, IL-1β, and IL-8) were analyzed by Western blot or qPCR. Furthermore, Northern blot and immunofluorescence were employed to evaluate pre-rRNA processing and nucleolar morphology. ResultsPES1 expression was significantly downregulated in senescent MEFs and HepG2 cells. PES1 knockdown resulted in decreased EdU-positive cells and increased SA‑β‑gal-positive cells, indicating proliferation inhibition and senescence induction. Mechanistically, PES1 suppression activated the p53-p21 pathway without affecting Rb expression, while upregulating IL-6, IL-1β, and IL-8 production. Notably, PES1 depletion impaired pre-rRNA maturation and induced nucleolar stress, as evidenced by aberrant nucleolar morphology. ConclusionOur findings demonstrate that PES1 deficiency triggers nucleolar stress and promotes p53-dependent (but Rb-independent) cellular senescence, highlighting its crucial role in maintaining nucleolar homeostasis and regulating senescence-associated pathways.

Objective To analyze bedside radiation dose rates for interventional surgery operators in Guangdong Province, examine dose distribution patterns, and identify potential weaknesses in radiation protection, and to provide guidance for optimizing radiation monitoring and protection measures. Methods A total of 209 digital subtraction angiography devices measured in Guangdong Province between 2017 and 2024 were used as the research objects. The first and second operator positions were set at 30 cm and 90 cm horizontally from the X-ray tube focal point, respectively. Monitoring points were set up at 155, 125, 105, 80, and 20 cm above the ground. Results The median bedside radiation dose rate for interventional surgery operators in Guangdong Province was 83.0 (3.9, 1044.0) μSv/h, indicating instances of exceeding standard limits. The overall dose rates under the old and new standards were 29.8 (3.9-346.5) μSv/h and 114.0 (4.0-1044.0) μSv/h respectively. Results for both standards showed a higher dose rate at the second than the first operator position. The dose rates at the heights of 105 cm (abdomen), 125 cm (chest), and 155 cm (head) were higher in the second operator position than in the first operator position. Additionally, 71.5% and 56.8% of the highest dose rate points under the new and old standards, respectively, were concentrated at 105 cm (abdomen), 125 cm (chest) and 155 cm (head) in the second operator position. Conclusion The principle of protection optimization should be followed, auxiliary protective facilities should be placed correctly, and attention should be paid to the protection of the second surgery operator position, especially above the abdomen. The dose rate results under the new standard were lower than those under the old standard, suggesting that the measurement method may overestimate radiation exposure at the secondary operator position.

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.

T7 RNA polymerase (T7 RNAP) is one of the simplest known RNA polymerases. Its unique structural features make it a critical model for studying the mechanisms of RNA synthesis. This review systematically examines the static crystal structure of T7 RNAP, beginning with an in-depth examination of its characteristic “thumb”, “palm”, and “finger” domains, which form the classic “right-hand-like” architecture. By detailing these structural elements, this review establishes a foundation for understanding the overall organization of T7 RNAP. This review systematically maps the functional roles of secondary structural elements and their subdomains in transcriptional catalysis, progressively elucidating the fundamental relationships between structure and function. Further, the intrinsic flexibility of T7 RNAP and its applications in research are also discussed. Additionally, the review presents the structural diagrams of the enzyme at different stages of the transcription process, and through these diagrams, it provides a detailed description of the complete transcription process of T7 RNAP. By integrating structural dynamics and kinetics analyses, the review constructs a comprehensive framework that bridges static structure to dynamic processes. Despite its advantages, T7 RNAP has a notable limitation: it generates double-stranded RNA (dsRNA) as a byproduct. The presence of dsRNA not only compromises the purity of mRNA products but also elicits nonspecific immune responses, which pose significant challenges for biotechnological and therapeutic applications. The review provides a detailed exploration of the mechanisms underlying dsRNA formation during T7 RNAP catalysis, reviews current strategies to mitigate this issue, and highlights recent progress in the field. A key focus is the semi-rational design of T7 RNAP mutants engineered to minimize dsRNA generation and enhance catalytic performance. Beyond its role in transcription, T7 RNAP exhibits rapid development and extensive application in fields, including gene editing, biosensing, and mRNA vaccines. This review systematically examines the structure-function relationships of T7 RNAP, elucidates the mechanisms of dsRNA formation, and discusses engineering strategies to optimize its performance. It further explores the engineering optimization and functional expansion of T7 RNAP. Furthermore, this review also addresses the pressing issues that currently need resolution, discusses the major challenges in the practical application of T7 RNAP, and provides an outlook on potential future research directions. In summary, this review provides a comprehensive analysis of T7 RNAP, ranging from its structural architecture to cutting-edge applications. We systematically examine: (1) the characteristic right-hand domains (thumb, palm, fingers) that define its minimalistic structure; (2) the structure-function relationships underlying transcriptional catalysis; and (3) the dynamic transitions during the complete transcription cycle. While highlighting T7 RNAP’s versatility in gene editing, biosensing, and mRNA vaccine production, we critically address its major limitation—dsRNA byproduct formation—and evaluate engineering solutions including semi-rationally designed mutants. By synthesizing current knowledge and identifying key challenges, this work aims to provide novel insights for the development and application of T7 RNAP and to foster further thought and progress in related fields.

Objective To evaluate cardiac involvement in patients with anti-neutrophil cytoplasmic antibody-associated vasculitis (AAV) using echocardiography combined with electrocardiography. Methods A retrospective analysis was performed on the detailed medical records of AAV patients treated in Jining First People’s Hospital between January 2020 and December 2024. Eighty patients were enrolled in the AAV group, and the risk of heart disease was compared between the AAV group and a control group with 80 subjects matched for age, sex, and cardiovascular disease risk factors. Results Electrocardiographic abnormalities were observed in 78.75% of patients in the AAV group, while significant electrocardiographic abnormalities only occurred in symptomatic patients in the control group. There were no differences in left atrial enlargement or interventricular septal thickening between the AAV group and the control group. The overall left ventricular systolic function in the AAV group was lower than that in the control group (8.75% vs. 0). The incidence of reduced diastolic function in the AAV group was significantly higher than that in the control group (37.5% vs. 15%). The incidence rates of tricuspid regurgitation, mitral regurgitation, aortic regurgitation, and pericardial effusion in the AAV group were significantly higher than those in the control group. Pericardial thickening, aortic stenosis, pulmonary hypertension, and rare periaortic granulomas were found in the AAV group, but not in the control group. Conclusion Echocardiography and electrocardiography are important examination methods for evaluating cardiac involvement in AAV. These methods have key roles in disease screening, diagnosis and treatment, follow-up, and prognosis judgment.