Inteins are unique protein insertion sequences capable of self-excision, enabling the covalent ligation of flanking extein peptides via amide bond formation. This process proceeds spontaneously without requiring external enzymes, cofactors, or chemical reagents, granting inteins exceptional biocompatibility and traceless performance in protein engineering applications. Split inteins represent a specialized and versatile subclass whose splicing domains are encoded by two separate gene fragments rather than a single continuous open reading frame. These fragments, known as the N-terminal (IntN) and C-terminal (IntC) split inteins, associate through non-covalent interactions including hydrophobic forces, hydrogen bonds, and van der Waals forces to assemble into an active three-dimensional structure, which then drives efficient extein ligation and enables protein trans-splicing. Protein trans-splicing mediated by split inteins has become a cornerstone for traceless protein ligation owing to its high specificity and irreversibility, fundamentally reshaping strategies for protein modification, assembly, and functional regulation. Compared with traditional chemical ligation methods, split intein systems require no complex chemical derivatization of peptide fragments and can operate efficiently at micromolar concentrations under physiological conditions, thus avoiding structural and functional damage caused by organic reagents. In contrast to enzymatic ligation tools such as sortase, split inteins eliminate the need for additional enzymes or cofactors, simplifying reaction systems, reducing costs, and minimizing non-specific side products. These distinctive advantages render split inteins highly promising for applications in chemical biology, synthetic biology, and biopharmaceutical development. In recent years, deepened mechanistic understanding has established structure-guided rational design as the primary approach to overcoming key limitations of split inteins, including intrinsic aggregation propensity, strict extein sequence dependence, and limited splicing efficiency. Bioinformatic tools have been used to identify aggregation-prone regions in the IntN fragment, and site-directed mutagenesis of hydrophobic residues, relocation of split sites, or removal of misfolding-prone sequences has substantially reduced in vitro aggregation and improved soluble expression and assembly activity. Rational engineering of catalytic residues and adjacent flexible loops has relaxed strict amino acid preferences at extein junctions, enhancing sequence tolerance and reducing the risk of functional impairment in target proteins. Consensus design based on multiple sequence alignments has yielded ultra-fast splicing variants such as Cfa DnaE and Cat-TerL, which exhibit significantly accelerated kinetics and improved tolerance to denaturing conditions. Meanwhile, advances in structural biology have further clarified the conformational dynamics and catalytic mechanisms of splicing, supporting the precise design of high-performance intein modules. On this basis, electrostatic interaction tuning and metagenomic screening have yielded multiple mutually orthogonal split intein pairs, enabling selective multi-fragment protein ligation and providing new routes for the efficient synthesis of large multi-domain functional proteins. With these engineered split inteins offering continuously improved performance and expanded applicability, protein trans-splicing has been widely applied in numerous cutting-edge areas of protein research and biomedicine. In gene delivery, split intein-based systems overcome the packaging limit of adeno-associated viral vectors, enabling the accurate reconstitution of large therapeutic proteins and base editors in target cells, thereby enhancing the efficacy and scope of gene therapy for genetic diseases. In internal protein sequence editing, split inteins mediate precise sequence replacement and modification in flexible regions or loops of target proteins, without the need for complex multi-step ligation and protein refolding involved in traditional protein semisynthesis. In protein-protein interaction studies, intein-mediated splicing covalently captures transient and weak intracellular complexes, enabling sensitive, high-throughput interaction detection and drug screening. In synthetic biology, conditionally controllable splicing systems support the construction of diverse intracellular and cell-surface biological logic gates for the precise regulation of cellular behavior. In mechanistic biochemical research, split inteins enable photocatalytic proximity labeling and site-specific tagging, allowing the preparation of homogeneous protein samples carrying precise post-translational modifications such as ubiquitination and polyglutamylation for chromatin interactome analysis and epigenetic studies. Moreover, covalent trapping strategies using split inteins stabilize transient enzymatic intermediates, providing unprecedented insights into molecular mechanisms such as nucleosome ubiquitination that are difficult to elucidate using conventional methods. This review systematically summarizes key technological advances in split inteins over the past decade, highlighting engineering strategies, mechanistic insights, and the development of orthogonal components. It comprehensively surveys emerging applications at the frontiers of protein research, analyzes current core challenges, and proposes future directions, particularly emphasizing artificial intelligence-driven de novo design and novel splicing pathways to break existing technical bottlenecks. By enabling traceless, efficient, and versatile protein manipulation, split inteins continue to serve as indispensable tools that drive innovation in protein engineering and fundamental life science research.

Tacit knowledge of tongue inspection is content that affects diagnostic results but is difficult to be explicit. Its cognitive characteristics are rooted in xiang thinking and embodiment. It constructs multidimensional associations between tongue manifestations and disease mechanisms through imagery mapping， and it relies on the practitioner's bodily perception， clinical context， and long-term practice for continuous internalization. In response to the neglect of tacit transmission and individual cognitive processes in current traditional Chinese medicine （TCM） tacit knowledge research， an empirical research framework integrating cognitive neuroscience is proposed. Specifically， event-related potential （ERP） and eye tracking （ET） technologies can be used to capture the brain electrical activity and eye movement trajectories of experts and novices in different tongue diagnosis cognitive tasks. By integrating multimodal cognitive data such as behaviorism， ERP components， and ET indicators， the implicit cognitive advantages of experts in the perception， mapping， and decision-making stages of tongue diagnosis are presented， and the possibility of achieving tacit knowledge transformation through visual cognitive transfer training is explored. Exploring empirical pathways to uncover the cognitive mechanisms of tongue diagnosis tacit knowledge is of great significance for the inheritance of traditional Chinese medicine.

As cardiac magnetic resonance imaging technology advances,T1 mapping has emerged as a non-invasive method offering visual and quantitative insights into myocardial fibrosis,edema,and infiltration associated with cardiac dis-eases.The application of T1 mapping in myocardial diseases allows for evaluating both focal and diffuse myocardial fibro-sis,playing a crucial clinical role in the differentiation,treatment,and prognostic risk assessment of diseases.This arti-cle aims to provide a thorough overview of the clinical applications of T1 mapping in patients with cardiomyopathy,summa-rizing the commonly employed scanning techniques and imaging principles.

Objective:To address the critical issue of missing dynamic border molding information in edentulous direct digital impression technology, this study explores innovative digital solutions and conducts preliminary application validation.Methods:Based on the myostatic line theory, a methodology was established: intraoral scanner (IOS) high-frequency video was utilized to dynamically capture functional molding data of soft tissues, integrated with a self-developed mobility gradient recognition algorithm to achieve dynamic threshold segmentation between the muscle dynamic zone and myostatic zone, termed "optical digital molding technology". Ten edentulous patients with well-fitting complete dentures, treated at the Department of Prosthodontics, Peking University School and Hospital of Stomatology from January 2024 to December 2024, were enrolled. The standard deviation between the muscle static line (generated by mobility gradient algorithm with thresholds of 0.3-0.7 mm) and the denture border curve was analyzed to optimize the dynamic threshold, followed by single-case clinical validation.Results:Among the mobility thresholds of 0.3-0.7 mm, the 0.5 mm threshold yielded the smallest standard deviation between the myostatic line and denture border. Clinical validation demonstrated that dentures designed with this threshold exhibited no displacement during dynamic functional tests, with marginal sealing meeting clinical standards.Conclusions:The optical digital border molding technique for edentulous soft tissue boundaries translates the myostatic line theory into quantifiable parameters for the first time. Based on data from 10 cases, a mobility threshold of 0.5 mm is recommended for clinical application.

Objective:To conduct a visual analysis of the research status, hotspots, and trends concerning fear of falling in stroke patients both at home and abroad based on CiteSpace.Methods:Literature on fear of falling in stroke patients was retrieved from the Web of Science Core Collection, China National Knowledge Infrastructure, Wanfang Data, and VIP. The retrieval time is from the establishment of the database to December 31, 2023. CiteSpace 5.8.R3 was used for visual analysis of countries, institutions, authors, and keywords.Results:A total of 113 English and 53 Chinese papers were included, showing an overall upward trend in publications. The United States ranked first in the number of English publications, followed by China, with the UK and Canada tied for third. Institutional and author collaborations were more cohesive internationally than domestically. Research hotspots included the elderly population, influencing factors, quality of life, intervention methods, and psychological states.Conclusions:The visual analysis using CiteSpace reveals research hotspots and trends in fear of falling among stroke patients globally, offering a novel perspective for researchers. Future research in China should integrate international research trends and pursue multidisciplinary, large-sample, multi-center studies to promote methodological diversity and broaden research content, thereby providing effective interventions for stroke patients with fear of falling.

Objective:To compare the efficacy of anrikefon and tegileridine for analgesia in patients with moderate-to-severe pain after abdominal surgery with general anesthesia.Methods:In this multicenter, randomized, double-blind, active-controlled clinical trial, 101 patients with moderate to severe pain (numeric pain rating scale [NRS] score ≥4 within 4 h after operation) after abdominal surgery with general anesthesia between February 24 and April 1, 2025, aged 18-70 yr, with a body mass index of 18-40 kg/m 2, were assigned to anrikefon group ( n=50) and tegileridine group ( n=51) in a 1∶1 ratio using stratified blocked randomization. Double-dummy design was employed to maintain blinding. Each group received an initial intravenous injection of anrikefon 1 μg/kg or tegileridine 1 mg, followed by connection to a patient-controlled intravenous analgesia (PCIA) pump (the PCIA solution contained normal saline in anrikefon group; the PCIA solution contained tegileridine 5 mg in tegileridine pump) within 10 min. If the patient′s NRS score ≥4 at 8 and 16 h after the initial injection, anrikefon 1 μg/kg was intravenously injected in anrikefon group, and tegileridine group received the equal volume of normal saline. The primary efficacy endpoint was the sum of pain intensity difference (SPID) over the first 24 h after the initial dose (SPID 0-24h). The secondary efficacy endpoints included the incidence and severity of vomiting and nausea, incidence of postoperative nausea and vomiting(PONV), the proportion of patients who received antiemetic treatment, and total consumption of antiemetics within 0-24 h after the initial dose, NRS score at rest ≤ 1 at 24 h after the initial dose, and NRS score at rest ≤ 3 over the first 24 h after the initial dose. Safety indicators included adverse events, vital signs, physical examination findings, 12-lead ECG and laboratory test indicators, and adverse events of special interest. Results:Compared with tegileridine group, no significant change was found in the SPID 0-24h ( P>0.05), and the incidence of vomiting, PONV, proportion of patients requiring antiemetic medication, and total consumption of antiemetics were significantly decreased within the first 24 h after the initial dose in tegileridine group ( P<0.05). One treatment-emergent adverse event of Common Terminology Criteria for Adverse Events grade 3 or higher occurred in tegileridine group, while no treatment-emergent adverse events of Common Terminology Criteria for Adverse Events grade 3 or higher were found in anrikefon group. Among the adverse events of special interest, one case of respiratory depression and one case of cough occurred in tegileridine group, while one case of cough occurred in anrikefon group, with no respiratory depression. Conclusions:Anrikefon and tegileridine provide comparable analgesic efficacy for moderate-to-severe pain after abdominal surgery with general anesthesia. However, anrikefon exhibits an advantage in reducing the risk of PONV, with a superior safety profile.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Hemodialysis patients exhibit compromised immune function and require long-term repeated vascular punctures as therapeutic approach,the risk of infection increases.Hospital-associated infection in hemodialysis de-partment(center)happens from time to time,which has already become a concern for the medical community,patients and social media.This paper outlines the task origin of China's"Standard for infection prevention and control in hemodialysis department(center)"(WS/T854-2025),the compilation basis and explanations for its key content,feasibility and implementation recommendations,as well as the clarifications on common issues encoun-tered during its promotion and enforcement.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To explore the value of proton density fat fraction(PDFF)and R2* based on iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification(IDEAL-IQ)sequence in the assessment of vertebral fat and trabecular structure in postmenopausal women with osteoporosis.Methods A total of 85 postmenopausal women who underwent abdominal CT scans were selected and divided into three groups using quantitative computed tomography(QCT):osteoporosis group(30 cases),osteopenia group(29 cases),and normal bone mass group(26 cases).MRI examinations were performed within 2 weeks,the sequences including lumbar sagittal IDEAL-IQ and T2* mapping.The images were uploaded to the post-processing workstation,and the mean PDFF,IDEAL-R2* and gradient echo(GRE)-R2* were calculated for the L1-L5 vertebral body.One-way ANOVA was used to analyze the differences between the parameters among the three groups,and Spearman was used to compare the correlations between PDFF and bone mineral density(BMD),R2* value,as well as BMD and R2* value.The Bland-Altman plot was drawn to evaluate the consistency of IDEAL-R2* and GRE-R2*,and the receiver operating characteristic(ROC)curve was used to further evaluate the diagnostic performance of PDFF and R2* values for osteoporosis and osteopenia.Results There were significant differences in PDFF and BMD values among normal bone mass group,osteopenia group and osteoporosis group(P＜0.05),and R2* values were reduced in the osteoporosis group compared to the normal bone mass group(P＜0.05).Correlation analysis showed that PDFF was negatively correlated with BMD(r=-0.558,P＜0.05),negatively correlated with R2*[r=-0.250(IDEAL),-0.354(GRE),both P＜0.05],and positively correlated with BMD and R2*[r=0.351(IDEAL),0.457(GRE),both P＜0.05].The Bland-Altman plots showed that the mean value of the difference between IDEAL-R2* and GRE-R2* was-4.5 Hz,and the results were highly consistent.ROC curves showed no significant difference in the diagnostic efficacy of IDEAL-R2* and GRE-R2* in the assessment of osteoporosis and osteopenia(Z=0.526,1.327,P=0.599,0.185),but the diagnostic efficacy of both was lower than PDFF[area under the curve(AUC)=0.846(osteoporosis),0.684(oseopenia)].Conclusion IDEAL-IQ sequence-derived PDFF and R2* values are effective biological indicators for one-stop assessment of vertebral fat and microscopic trabecular structure in osteoporosis,which have certain clinical value.