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.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

Surgical operation is the main treatment of oral and maxillofacial tumors.Dysphagia is a common postoperative complication.Swal-lowing disorder can not only lead to mis-aspiration,malnutrition,aspiration pneumonia and other serious consequences,but also may cause psychological problems and social communication barriers,affecting the quality of life of the patients.At present,there is no systematic evalua-tion and rehabilitation management plan for the problem of swallowing disorder after oral and maxillofacial tumor surgery in China.Combining the characteristics of postoperative swallowing disorder in patients with oral and maxillofacial tumors,summarizing the clinical experience of ex-perts in the field of tumor and rehabilitation,reviewing and summarizing relevant literature at home and abroad,and through joint discussion and modification,a group of national experts reached this consensus including the core contents of the screening of swallowing disorders,the phased assessment of prognosis and complications,and the implementation plan of comprehensive management such as nutrition management,respiratory management,swallowing function recovery,psychology and nursing during rehabilitation treatment,in order to improve the evalua-tion and rehabilitation of swallowing disorder after oral and maxillofacial tumor surgery in clinic.

Ankylosing spondylitis (AS) combined with lower cervical fracture is often categorized into unstable fracture, with a high incidence of neurological injury and a high rate of disability and morbidity. As factors such as shoulder occlusion may affect the accuracy of X-ray imaging diagnosis, it is often easily misdiagnosed at the primary diagnosis. Non-operative treatment has complications such as bone nonunion and the possibility of secondary neurological damage, while the timing, access and choice of surgical treatment are still controversial. Currently, there are no clinical practice guidelines for the treatment of AS combined with lower cervical fracture with or without dislocation. To this end, the Spinal Trauma Group of Orthopedics Branch of Chinese Medical Doctor Association organized experts to formulate Clinical guidelines for the treatment of ankylosing spondylitis combined with lower cervical fracture in adults ( version 2024) in accordance with the principles of evidence-based medicine, scientificity and practicality, in which 11 recommendations were put forward in terms of the diagnosis, imaging evaluation, typing and treatment, etc, to provide guidance for the diagnosis and treatment of AS combined with lower cervical fracture.

Objective:To determine incidence of seasonal influenza virus infection in the community and to analyze the factors influencing seasonal influenza virus infection.Methods:This study recruited residents aged 6-59 years to build a cohort in 15 villages/streets in Macheng city in November 2019. Meanwhile, a cross-sectional baseline survey was conducted immediately to collect sera, information on demographics and child protection knowledge, behaviors, as well as attitudes using a questionnaire from the participants enrolled in the cohort (i.e., before the influenza epidemic season). In July 2020, a cross-sectional follow-up survey was conducted to collect sera once again (i.e., after the influenza season). Paired sera from the two cross-sectional surveys were tested for influenza virus-specific antibodies by hemagglutination inhibition (HI) test or micro-neutralization (MN) test using a circulating representative strain of each subtype/lineage of influenza virus as the test antigen. The infections with influenza virus subtype/lineage was confirmed if there was a four-fold or more increase in titers of antibodies against circulating representative strain of the subtype/lineage of influenza virus. Factors influencing infection with influenza A (H3N2) and B/Victoria viruses were analyzed using univariable and multivariable logistic regression.Results:In November 2019, 800 study participants were enrolled in the cohort, including 340 children aged 6-17 years and 460 adults aged 18-59 years; 605 study participants (including 224 children and 381 adults) were followed up in July 2020 and their paired sera were obtained before and after the influenza season. 25.3% (153/605) of the participants were confirmed to be infected with at least one subtype/lineage of seasonal influenza virus by HI and MN tests. The overall incidence of influenza viruses of all subtypes/lineages in children was 44.2% (95% CI: 37.6%-50.8%) which was significantly higher than the incidence of 14.1% in adults (95% CI: 10.7%-17.7%). Children had the highest incidence of influenza A (H3N2) virus infection, followed by B/Victoria. MN or HI antibody titers in A (H3N2)[ OR=0.88 (95% CI: 0.84-0.93)] and B/Victoria[ OR=0.97 (95% CI: 0.95-0.99)] before the influenza season were significantly associated with whether children were infected with that subtype/lineage of influenza virus. Conclusions:The residents aged 6-59 years in Macheng city had a substantial incidence of seasonal influenza virus infection during the influenza season from winter 2019 to spring 2020. Notably, almost half of children aged 6-17 years have been infected with seasonal influenza virus. Higher titers of HI/MN antibodies against seasonal influenza virus before the influenza season would be likely to reduce the risk of infection with influenza A (H3N2) and B/Victoria.

Neck dissection(ND)is one of the main treatment methods for oral and maxillofacial malignancies.Although ND type is in con-stant improvement,but intraoperative peal-pull-push injury of the accessory nerve,muscle,muscle membrane,fascia and ligament induced shoulder syndrome(SS)is still a common postoperative complication,combined with the influence of radiochemotherapy,not only can cause pain,stiffness,numbness,limited dysfunction of shoulder neck and arm,but also may have serious impact on patient's life quality and phys-ical and mental health.At present,there is still a lack of a systematic evaluation and rehabilitation management program for postoperative SS of oral and maxillofacial malignant tumors.Based on the previous clinical practice and the current available evidence,refer to the relevant lit-erature at home and abroad,the experts in the field of maxillofacial tumor surgery and rehabilitation were invited to discuss,modify and reach a consenusus on the etiology,assessment diagnosis,differential diagnosis,rehabilitation strategy and prevention of SS,in order to provide clinical reference.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

The incidence of osteoporotic thoracolumbar vertebral fracture (OTLVF) in the elderly is gradually increasing. The kyphotic deformity caused by various factors has become an important characteristic of OTLVF and has received increasing attention. Its clinical manifestations include pain, delayed nerve damage, sagittal imbalance, etc. Currently, the definition and diagnosis of OTLVF with kyphotic deformity in the elderly are still unclear. Although there are many treatment options, they are controversial. Existing guidelines or consensuses pay little attention to this type of fracture with kyphotic deformity. To this end, the Lumbar Education Working Group of the Spine Branch of the Chinese Medicine Education Association and Editorial Committee of Chinese Journal of Trauma organized the experts in the relevant fields to jointly develop Clinical guidelines for the diagnosis and treatment of osteoporotic thoracolumbar vertebral fractures with kyphotic deformity in the elderly ( version 2024), based on evidence-based medical advancements and the principles of scientificity, practicality, and advanced nature, which provided 18 recommendations to standardize the clinical diagnosis and treatment.

Objective To construct an artificial intelligence assisted diagnosis model based on deep learning for dynamically recognizing gastric lesions and their locations under gastroscopy in real time,and to evaluate its ability to detect and recognize gastric lesions and their locations.Methods The gastroscopy videos of 104 patients in our hospital was retrospectively analyzed,and the video frames were manually annotated.The annotated picture frames of lesion category were divided into the training set and the validation set according to the ratio of 8∶2,and the annotated picture frames of location category were divided into the training set and the validation set according to the patient sources at the ratio of 8∶2.These sets were utilized for training and validating the respective models.YoloV4 model was used for the training of lesion recognition,and ResNet152 model was used for the training of location recognition.The accuracy,sensitivity,specificity,positive predictive value,negative predictive value and location recognition accuracy of the auxiliary diagnostic model were evaluated.Results A total of 68 351 image frames were annotated,with 54 872 frames used as the training set,including 41 692 frames for lesion categories and 13 180 frames for location categories.The validation set consisted of 13 479 frames,comprising 10 422 frames for lesion categories and 3 057 frames for location categories.The lesion recognition model achieved an overall accuracy of 98.8%,with a sensitivity of 96.6%,specificity of 99.3%,positive predictive value of 96.3%,and negative predictive value of 99.3% in validation set.Meanwhile,the location recognition model demonstrated an top-5 accuracy of 87.1% .Conclusion The artificial intelligence assisted diagnosis model based on deep learning for real-time dynamic recognition of gastric lesions and their locations under gastroscopy has good ability in lesion detection and location recognition,and has great clinical application prospects.

Objective To investigate the safety and efficacy of novel bioabsorbable vascular scaffold(BVS)in the treatment of patients with complex coronary artery disease.Methods This was a retrospective,matched,single-center observational study.45 patients with coronary atherosclerotic cardiopathy received BVS treatment in the cardiovascular medicine department Department of the Affiliated Hospital of Guangdong Medical University from June 2020 to June 2021(BVS),and 45 patients treated with drug-eluting stents(DES)group were selected according to matching study requirements during the same period.Baseline,surgical,and follow-up data were compared between the two groups to evaluate safety and efficacy.The main measures of safety were:surgical time,intraoperative adverse events,etc.,and the end point of efficacy was target lesion failure(TLF),including cardiac death,target vessel myocardial infarction,and ischa-driven target lesion revascularization.Results A total of 90 patients were enrolled in this study,all of whom were followed up for at least 3 years.There were 20 cases of bifurcation lesions and 25 cases of diffuse long lesions in the two groups,and 50 cases of imaging were reviewed among the 90 patients.The proportion of stable coronary heart disease,history of diabetes,history of hypertension,history of smoking,pre-dilated balloon pressure and postoperative diastolic blood pressure in BVS group was higher than that in DES group,and the proportion of family history was lower than that in DES group(all P＜0.05).There were no statistically significant differences in the rates of cardiac death,target vessel myocardial infarction,and ischemia-driven revascularization of target lesions between the two groups(all P＞0.05).Binary Logistic regression model analysis showed that the diameter stenosis ratio of target lesions was an independent risk factor for intrastent restenosis(OR 2.786,95％CI 1.096-7.081,P=0.031).Conclusions Compared with traditional DES,BVS implantation has consistent safety and efficacy in the treatment of complex coronary artery disease within 3 years.The diameter stenosis ratio of target lesions was an independent risk factor for intrastent restenosis.