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.

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

Objective To describe the significance of the pretreatment inflammatory indicators in predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC) after undergoing radical radiotherapy. Methods The data of 246 ESCC patients who underwent radical radiotherapy were retrospectively collected. Receiver operating characteristic (ROC) curves were drawn to determine the optimal cutoff values for platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII). The Kaplan-Meier method was used for survival analysis. We conducted univariate and multivariate analyses by using the Cox proportional risk regression model. Software R (version 4.2.0) was used to create the nomogram of prognostic factors. Results The results of the ROC curve analysis showed that the optimal cutoff values of PLR, NLR, and SII were 146.06, 2.67, and 493.97, respectively. The overall response rates were 77.6% and 64.5% in the low and high NLR groups, respectively (P<0.05). The results of the Kaplan-Meier survival analysis revealed that the prognosis of patients in the low PLR, NLR, and SII group was better than that of patients in the high PLR, NLR, and SII group (all P<0.05). The results of the multivariate Cox regression analysis showed that gender, treatment modalities, T stage, and NLR were independent factors affecting the overall survival (OS). In addition, T stage and NLR were independent factors affecting the progression-free survival (PFS) (all P<0.05). The nomogram models of OS and PFS prediction were established based on multivariate analysis. The C-index values were 0.703 and 0.668. The calibration curves showed excellent consistency between the predicted and observed OS and PFS. Conclusion The pretreatment values of PLR, NLR, and SII are correlated with the prognosis of patients with ESCC who underwent radical radiotherapy. Moreover, NLR is an independent factor affecting the OS and PFS of ESCC patients. The NLR-based nomogram model has a good predictive ability.

BACKGROUND:We have successfully established an animal model of small ear pig in southern Yunnan province with internal tension relieving technique combined with autologous Achilles tendon for anterior cruciate ligament reconstruction,and verified the stability and reliability of the model.However,whether internal tension relieving technique can promote the ligamentalization process of autologous Achilles tendon graft has not been studied. OBJECTIVE:To investigate the differences in the process of ligamentalization between conventional reconstruction and internal reduction reconstruction of the anterior cruciate ligament by gross view,histology and electron microscopy. METHODS:Thirty adult female small ear pigs in southern Yunnan province were selected.Anterior cruciate ligament reconstruction was performed on the left knee joint with the ipsilateral knee Achilles tendon(n=30 in the normal group),and anterior cruciate ligament reconstruction was performed on the right knee joint with the ipsilateral knee Achilles tendon combined with the internal relaxation and enhancement system(n=30 in the relaxation group).The autogenous right forelimb was used as the control group;the anterior cruciate ligament was exposed but not severed or surgically treated.At 12,24,and 48 weeks after surgery,10 animals were sacrificed,respectively.The left and right knee joint specimens were taken for gross morphological observation to evaluate the graft morphology.MAS score was used to evaluate the excellent and good rate of the ligament at each time point.Hematoxylin-eosin staining was used to evaluate the degree of ligament graft vascularization.Collagen fibers and nuclear morphology were observed,and nuclear morphology was scored.Ultrastructural remodeling was evaluated by scanning electron microscopy and transmission electron microscopy. RESULTS AND CONCLUSION:(1)The ligament healing shape of the relaxation group was better at various time points after surgery,and the excellent and good rate of MAS score was higher(P<0.05).Moreover,the relaxation group could obtain higher ligament vascularization score(P<0.05).(2)The arrangement of collagen bundles and fiber bundles in the two groups gradually tended to be orderly,and the transverse fiber connections between collagen gradually increased and thickened,suggesting that the strength and shape degree of the grafts were gradually improved,but the ligament remodeling in the relaxation group was always faster than that in the normal group at various time points after surgery.(3)The diameter,distribution density,and arrangement degree of collagen fibers in the relaxation group were better than those in the normal group at all time points,especially in the comparison of collagen fiber diameter between and within the relaxation group(P<0.05).

AIM: To compare the efficacy of small-incision lenticule extraction(SMILE)and femtosecond assisted laser in situ keratomileusis(FS-LASIK)in the treatment of patients with myopia and astigmatism.METHODS: Retrospective analysis. A total of 100 cases(200 eyes)of patients with myopia and astigmatism treated in our hospital from December 2021 to December 2022 were collected. Among them, 50 cases(100 eyes)were divided into SMILE group and 50 cases(100 eyes)were divided into FS-LASIK group according to the treatment plans. The visual acuity and astigmatism, corneal morphology parameters, subjective visual quality scores, ocular surface indicators, postoperative complications, and quality of life were compared between the two groups before and after surgery.RESULTS: There was no significant difference in uncorrected visual acuity(UCVA), best corrected visual acuity(BCVA), astigmatism, corneal asphericity Q value, corneal surface regularity index(SRI), corneal thickness, and corneal curvature between the two groups before surgery and at 1 d, 1, and 6 mo after surgery(all P>0.05). At 1 and 6 mo after surgery, the subjective visual quality score, the quality of life score, Schirmer I test(SⅠt)and tear film break-up time(BUT)in the SMILE group were better than that in the FS-LASIK group(all P<0.05). The incidence of complications in the SMILE group was lower than that in the FS-LASIK group at 6 mo after surgery(P=0.005).CONCLUSION: Both SMILE and FS-LASIK have good clinical effects in the treatment of myopia with astigmatism, but the SMILE could alleviate ocular surface injury, reduce the risk of complications and improve the quality of lifes for patients.

ObjectiveTo establish steroid-induced osteonecrosis of the femoral head （SANFH） cell model by using dexamethasone （DEX）-induced bone marrow mesenchymal stem cells （BMSCs） and demonstrate that Gushing Granules （GSNs） exert an improving effect by activating the phosphatidylinositol-3-kinase/protein kinase B/B-lymphoma-2 gene related promoter （PI3K/Akt/Bad） signalling pathway. MethodsFirstly， SD rats were orally administered with drugs at a dose of 0.9 g·kg^-1 to prepare GSN-containing serum， and CCK-8 screening was used to determine the optimal dosage and duration of action. Then， BMSCs were cultured and treated with 1×10^-6 mol·L^-1 DEX， 10% GSN-containing serum， and inhibitor LY294002 of PI3K/Akt signalling pathway for 24 hours to model and group SANFH cells. Cell viability and proliferation were detected by using CCK-8 assay kit and EdU staining kit. Flow cytometry was used to detect cell apoptosis. An alkaline phosphatase （ALP） assay kit was employed to detect ALP expression. In order to detect the PI3K/Akt/Bad signalling pathway and protein and mRNA expression of apoptosis-related proteins such as apoptosis regulatory factors B-cell lymphoma-2 gene （Bcl-2）， and Bcl-2-associated X protein （Bax）， osteocalcin （OCN）， and Collagen Ⅰ， we used Western blot and Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. ResultsThe CCK-8 assay kit determined that the optimal dosage for GSN-containing serum is 10%， and the duration of action is 48 hours. After modelling and grouping the cells in each group， the detection results showed that the SANFH model group had significantly lower cell viability， cell proliferation， and ALP expression， as well as protein and mRNA expressions of PI3K， Akt， Bad， Bcl-2， OCN， and Collagen I compared to the blank group. The nucleic acid and protein levels of the Bax index and the cell apoptosis rate detected by flow cytometry significantly increased （P<0.05，P<0.01）. After treatment with GSN-containing serum， cell viability， cell proliferation， and ALP expression， as well as expressions of PI3K， Akt， Bad， Bcl-2， OCN， and Collagen Ⅰ nucleic acids and proteins were significantly increased， while the nucleic acid and protein levels of the Bax index and the cell apoptosis rate detected by flow cytometry significantly decreased（P<0.05，P<0.01）. Compared with the GSN drug-containing serum group， the simultaneous treatment with the inhibitor LY294002 and GSN drug-containing serum reversed the improvement effect of GSN. Specifically， the cell viability， cell proliferation， ALP expression， and the nucleic acid and protein levels of PI3K， Akt， Bad， Bcl-2， OCN， and Collagen Ⅰ were all significantly decreased， while the nucleic acid and protein levels of the Bax index and the cell apoptosis rate detected by flow cytometry were significantly increased （P<0.05， P<0.01）. ConclusionGSNs antagonize DEX-induced apoptosis of BMSCs by activating the PI3K/Akt/Bad signalling pathway， providing a scientific theoretical basis for the clinical treatment of SANFH with GSNs.

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.