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.

[Objective] To establish a cryopreservation protocol for small-volume (≤1 mL) red blood cells (RBCs) and to evaluate the reactivity and stability of blood group antigens after cryopreservation, so as to explore its potential application in immunohematology reference laboratories. [Methods] Small-volume RBCs were cryopreserved for 120 days, followed by thawing and deglycerolization to restore the RBC components. The quality of the RBCs was assessed. Serum antibodies were serially diluted and reacted with RBCs before and after cryopreservation, and agglutination scores were recorded to quantitatively evaluate the reactivity and stability of blood group antigens such as Rh, Duffy, Lewis, Kidd, M, and H. Flow cytometry was used to analyze the percentage and mean fluorescence intensity of ABO antigen expression on RBCs before and after cryopreservation to assess the usability of cryopreserved RBCs in flow immunophenotyping and blood group subtype studies. [Results] The hemolysis rate of thawed and deglycerolized RBCs was (0.27±0.10)%, with a supernatant free hemoglobin level of (0.52±0.14) g/L, and the RBC recovery rate was (69.12±7.91)%. The direct antiglobulin test (DAT) was negative for all thawed RBCs. There was no difference in the reactivity of blood group antigens before and after cryopreservation, and no difference in the percentage and mean fluorescence intensity of A and B antigen expression on RBCs before and after cryopreservation. [Conclusion] The small-volume RBC cryopreservation protocol can be applied to immunohematology analysis in reference laboratories and is expected to be widely used in blood group identification, antibody screening, identification, and blood group-related research.

Objective To analyze the disease burden of early-onset colorectal cancer (EOCRC) at the global, regional, and national levels from 1990 to 2021, and to predict the disease burden trend from 2022 to 2026. Methods Based on the Global Burden of Disease (GBD) database, the incidence, mortality, and disability-adjusted life year (DALY) rate of EOCRC across 204 countries and regions from 1990 to 2021 were obtained. The time trends of these indicators were assessed by calculating the estimated annual percentage change (EAPC), and the contributions of ten risk factors to the EOCRC burden were analyzed. The autoregressive integrated moving average (ARIMA) model was used to predict the disease burden from 2022 to 2026. Results From 1990 to 2021, the number of new global EOCRC cases increased from 107 310 to 211 890, with the incidence rising from 3.96 to 5.37 per 100 000 people. In 2021, global EOCRC incidence, mortality, and DALY rate increased with age; males had higher rates than females in terms of incidence, mortality, and DALY rate in all age groups. In 2021, East Asia had the highest number of new cases, deaths, and DALY. From 1990 to 2021, the global EAPC for incidence rate was 0.96%, and death rate was –0.38%. ARIMA model indicated that from 2022 to 2026, the global incidence of EOCRC would continue to rise, while mortality and DALY rate would be expected to decline. Conclusions The disease burden of EOCRC has significantly increased globally from 1990 to 2021, with notable regional, age, and sex differences. By 2026, the mortality and DALY rate of EOCRC will decline, while the incidence is expected to further increase, highlighting the urgency of taking active measures to address the growing trend of EOCRC.

Objective In this study,we investigated the correlation between the scores for different Liebowitz Social Anxiety Scale(LSAS)subscale models and the metabolic activity in specific regions of the brain using 18F-fluorodeoxyglucose(FDG)positron emission tomography/computed tomography(PET/CT)(18F-FDG PET),thereby improving the understanding of the neurobiological characteristics of social anxiety.Methods A total of 39 cognitively normal participants(29 men and 10 women,aged 30-63 years)were enrolled.All participants underwent LSAS assessment and brain 18F-FDG PET scanning.Correlations between metabolic activities in various brain regions and scores from the different LSAS subscales were analyzed accordingly.Results LSAS subscale scores were significantly correlated with metabolic activity in specific brain regions.In the Safren model,the score for the observation by others subscale was positively correlated with the left fusiform gyrus(P<0.001,false discovery rate[FDR]-corrected)and the left caudate tail(P<0.001,FDR-corrected),suggesting a close association between mood states related to observation by others and the metabolic activity in these regions.In the Baker model,the score for the eating and drinking subscale was negatively correlated with the right precuneus(P<0.001,FDR-corrected),while the score for the assertiveness subscale was positively correlated with the left caudate nucleus(P<0.001,FDR-corrected).These findings revealed the complex associative patterns between various mood and behavioral dimensions and metabolic activities in specific brain regions.Conclusion Social anxiety symptoms are closely associated with metabolic changes in specific brain regions,including the left insula,left caudate tail,and right precuneus.Moreover,different social situations activate distinct brain regions.Compared with individuals with social anxiety disorder,normal individuals exhibit involvement of fewer brain regions when experiencing social anxiety.These findings provide new experimental evidence for understanding the neural mechanisms underlying social anxiety.

OBJECTIVE: To explore the clinical and genetic characteristics of two children diagnosed with two rare genetic diseases simultaneously. METHODS: Two children with comorbidity of two genetic diseases due to dual genetic mutations diagnosed at the Third Affiliated Hospital of Zhengzhou University respectively in May 2022 and March 2023 were selected as the study subjects. Clinical and genetic data of the two children were retrospectively analyzed. This study has been approved by the Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (Ethic No. 2021-062-01). RESULTS: Child 1 was a 2-year-and-4-month-old boy whose clinical manifestations included facial dysmorphism, developmental delay, short stature, microcephaly, cleft palate, cryptorchidism, hypospadias, recurrent infections and immunological abnormalities. Whole exome sequencing revealed that he had harbored a heterozygous c.6595delT (p.Y2199Ifs*65) variant of the KMT2D gene and a heterozygous c.1892G>A (p.R631Q) variant of the PIK3R1 gene. This has led to a dual genetic diagnosis of Kabuki syndrome and PI3Kδ-related immunodeficiency type 36. Child 2 was a 15-year-old girl whose clinical manifestations included epilepsy, Albright's hereditary osteodystrophy, long body trunk, short limbs, hypocalcemia, hyperphosphatemia and hyperparathyroidism. The child also had a family history of short stature. Whole exome sequencing revealed that she had harbored a heterozygous c.2T>C (p.Met1?) variant of the GNAS gene and deletion of exons 2 to 6 of the SHOX gene. The two variants have led to dual diagnose of pseudohypoparathyroidism and X-linked idiopathic short stature. CONCLUSION When the clinical phenotype of a genetic disease is complex and cannot be fully explained with a single genetic variant, multiple pathogenic variants should be considered, and this may lead to the diagnosis of co-morbid genetic diseases. To adopt or supplement corresponding genetic testing in time and re-analyze the genetic data may facilitate accurate diagnosis of co-morbid genetic diseases.
Child, Preschool ; Female ; Humans ; Male ; Class Ia Phosphatidylinositol 3-Kinase/genetics* ; Comorbidity ; Exome Sequencing ; Mutation ; Rare Diseases/genetics* ; Retrospective Studies ; Adolescent

Rumination is a core cognitive symptom of post-traumatic stress disorder(PTSD),which significantly exacerbates difficulties in emotional regulation and impedes symptom recovery.Its occurrence is closely associated with gray matter structural impairments and abnormal white matter connectivity in the prefrontal-limbic system,including the hippocampus,amygdala,and prefrontal cortex.Functional neuroimaging studies indicate that the neural basis of rumination involves hyperactivation of the default mode network and the salience network,coupled with reduced functionality of the executive control network.Neurochemical research suggests that metabolic imbalances in the glutamate/γ-aminobutyric acid system may further contribute to the maintenance and reinforcement of rumination.Systematically elucidating the neural mechanisms of rumination in PTSD patients based on multimodal neuroimaging evidence will facilitate a deeper understanding of its neuropathological mechanisms and help expand future research directions.

OBJECTIVES: To report the development, validation, and findings of the Multi-dimensional Attention Rating Scale (MARS), a self-report tool crafted to evaluate six-dimension attention levels. METHODS: The MARS was developed based on Classical Test Theory (CTT). Totally 202 highly educated healthy adult participants were recruited for reliability and validity tests. Reliability was measured using Cronbach's alpha and test-retest reliability. Structural validity was explored using principal component analysis. Criterion validity was analyzed by correlating MARS scores with the Toronto Hospital Alertness Test (THAT), the Attentional Control Scale (ACS), and the Attention Network Test (ANT). RESULTS: The MARS comprises 12 items spanning six distinct dimensions of attention: focused attention, sustained attention, shifting attention, selective attention, divided attention, and response inhibition.As assessed by six experts, the content validation index (CVI) was 0.95, the Cronbach's alpha for the MARS was 0.78, and the test-retest reliability was 0.81. Four factors were identified (cumulative variance contribution rate 68.79%). The total score of MARS was correlated positively with THAT (r = 0.60, P < 0.01) and ACS (r = 0.78, P < 0.01) and negatively with ANT's reaction time for alerting (r = -0.31, P = 0.049). CONCLUSIONS The MARS can reliably and validly assess six-dimension attention levels in real-world settings and is expected to be a new tool for assessing multi-dimensional attention impairments in different mental disorders.
Humans ; Adult ; Male ; Attention/physiology* ; Female ; Middle Aged ; Reproducibility of Results ; Young Adult ; Psychometrics

Objective:To investigate the prevalence of baseline dyslipidemia in HIV-infected people before starting antiviral therapy (ART) in China.Methods:The data were collected from HIV/AIDS ART database of Chinese Disease Prevention and Control Information System. A national sample of HIV- infected people who initiated ART from 2018 to 2023 was used to collect baseline information, including sociodemographic characteristics and laboratory test results. According to the Chinese Lipid Management Guidelines (2023) and the National Cholesterol Education Program Adult Treatment Panel Ⅲ guidelines, triglyceride (TG) ≥1.7 mmol/L or total cholesterol (TC) ≥5.2 mmol/L were identified as dyslipidemia. Statistical analysis was performed with software SAS 9.4. An unconditional logistic regression model was used to analyze the factors influencing TG and TC abnormalities in HIV-infected patients before ART.Results:A total of 359 952 adults infected with HIV were included in this study, the prevalence rate of dyslipidemia was 38.41% (138 263/359 952). The abnormal rates of TG and TC were 31.40% (113 041/359 952) and 13.75% (49 494/359 952), respectively. In all age groups except for the 25-44 age groups, the abnormal rates of TG and TC were higher in HIV-infected women than in HIV-infected men. In HIV-infected patients, women, those aged 45-64 years, those lived in northeast region, those had heterosexual transmission, and those with BMI ≥28.0 kg/m 2, CD4 +T lymphocytes counts ≥500 cells/μl had higher rates of baseline dyslipidemia (all P<0.05). Conclusions:The abnormal rate of TG in HIV-infected people before ART was higher in China from 2018 to 2023, especially in HIV-infected women, and the abnormal rate of TG and TC increased with age. Attention should be paid to the clinical diagnosis and ART selection in the treatment of HIV infection.

Objective:To establish a model based on the characteristics of breast cancer ultrasound images through deep learning methods to predict the risk of axillary lymph node metastasis（ALNM）in patients with breast cancer（maximum diameter ≤2.5 cm）before surgery.Methods:A total of 419 patients（3 433 breast tumor ultrasound images）with breast cancer（maximum diameter ≤2.5 cm）who underwent axillary lymph node dissection at Beijing Tiantan Hospital，Capital Medical University from January 2019 to December 2024 were retrospectively included. According to the pathological results of axillary lymph nodes，they were divided into 220 cases in the ALNM occurrence group（positive group）and 199 cases in the non-ALNM occurrence group（negative group）. The breast cancer ultrasound images of the two groups of cases were randomly classified into the training set（2 404 images），the validation set（687 images）and the test set（342 images）according to a ratio of 7∶2∶1. YOLOv8 was used as the basic model of You Only Look Once（YOLO）and optimized. The optimized model was applied to locate and capture the potential ultrasound features of breast cancer cases in the training set. A prediction model was constructed based on the captured ultrasound features. The model was adjusted and optimized through the validation set，and then matched with the case images in the test set. The confusion classification matrix graph and the curve graph for measuring the model performance were used to evaluate the model prediction performance and interpret the model，and the efficacy of this model in identifying breast cancer patients at risk of ALNM was analyzed.Results:There were statistically significant differences between the positive and negative groups in terms of the pathological maximum diameter of breast tumors，pathological T staging，the differentiation degree，the presence of distant metastasis，the maximum diameter measured by ultrasound，the quadrant of breast tumor occurrence，the Breast Imaging - Reporting and Data System（BI-RADS）classification of breast tumors，and the presence of abnormal ultrasound features of lymph node（all P<0.05）. The established deep learning model could automatically perform bounding box localization for the breast cancer of patients.The breast tumors in the positive group had potential ultrasound features that could be captured by the model compared with those in the negative group. The mean average precision（mAP）50 was 0.883，mAP 50-95 was 0.636，PR-AUC was 0.884 5，strict PR-AUC was 0.636 4，the sensitivity was 90.5%，and the specificity was 91.2%，and it had a good predictive efficacy. Conclusions:This prediction model based on the ultrasound characteristics of breast cancer through deep learning can effectively predict breast cancer（maximum diameter ≤ 2.5 cm）with the risk of ALNM，providing an effective basis for the clinical management of axillary lymph nodes in breast cancer patients.

Objective:To explore the causal relationship between human immune cell phenotypes and keloids.Methods:This study was based on a two-sample Mendelian randomization (MR) analysis. Human immune cell phenotypes were considered as the exposure factors, and keloid was the outcome. Data on immune cell phenotypes (3 757 samples) and keloids (668 samples) were obtained from the genome-wide association study database. Using single nucleotide polymorphisms (SNPs) significantly associated with immune cell phenotypes as instrumental variables with the influence of weak instrumental variables being excluded, two-sample MR analysis was employed to evaluate the causal relationship between 731 human immune cell phenotypes and keloids. The inverse variance weighted (IVW) method was used to infer causal relationships, and the MR-Egger, weighted median, and weighted mode methods were used for validation. For SNPs of immune cell phenotypes meeting the hypothesis, the Cochran Q test was used to assess heterogeneity, and the MR-Egger regression and MR-PRESSO outlier tests were used to evaluate horizontal pleiotropy.Results:A total of 18 204 SNPs meeting the significant threshold ( P<1×10??) were selected as instrumental variables for 731 immune cell phenotypes, and none of these SNPs were weak instrumental variables (with F values all >10). According to the IVW method, 21 immune cell phenotypes were identified with potential causal relationships to keloids, among which the CD62L - monocyte absolute count, CD19 on naive-mature B cell, CD19 on IgD + B cell, CD27 on plasma blast-plasma cell, CD86 on CD62L + myeloid dendritic cell, CD45 on natural killer T cell, CD25 on CD39 + CD4 + regulatory T cell, CD45 on monocytic myeloid-derived suppressor cells, CD8 on effector memory CD8 + T cell, and CD45RA on resting CD4 + regulatory T cell showed significant positive correlations with keloids (with odds ratios of 1.12, 1.09, 1.08, 1.21, 1.13, 1.12, 1.17, 1.11, 1.10, and 1.07, respectively, 95% confidence intervals of 1.03-1.23, 1.02-1.16, 1.01-1.15, 1.06-1.38, 1.02-1.25, 1.01-1.24, 1.03-1.33, 1.00-1.23, 1.00-1.20, and 1.01-1.13, respectively, P<0.05), while the activated and secreted CD4 + regulatory T cell absolute count, CD25 on unswitched memory B cell, plasmacytoid dendritic cell absolute count, CD14 on monocytic myeloid-derived suppressor cells, CD8 on natural killer T cell, CD20 on IgD + CD38 + B cell, CD11c + CD62L - monocyte absolute count, CD66b ++ myeloid cell absolute count, CD11c on granulocytes, CD14 on CD14 + CD16 + monocyte, and CD3 on central memory CD8 + T cell showed significant negative correlations with keloids (with odds ratios of 0.95, 0.93, 0.93, 0.93, 0.91, 0.89, 0.89, 0.88, 0.87, 0.86, and 0.85, respectively, 95% confidence intervals of 0.90-1.00, 0.87-0.99, 0.88-0.99, 0.87-0.99, 0.84-1.00, 0.81-0.98, 0.81-0.98, 0.79-0.99, 0.78-0.96, 0.75-0.99, and 0.74-0.96, respectively, P<0.05). MR-Egger method confirmed the potential causal relationship existing respectively between CD25 on CD39 + CD4 + regulatory T cell, CD86 on CD62L + myeloid dendritic cell, CD19 on IgD + B cell, CD45RA on resting CD4 + regulatory T cell, CD3 on central memory CD8 + T cell and keloids (with odds ratios of 1.32, 1.22, 1.11, 1.09, and 0.73, respectively, 95% confidence intervals of 1.03-1.70, 1.04-1.44, 1.02-1.21, 1.01-1.19, and 0.55-0.95, respectively, P<0.05). The weighted median method confirmed the potential causal relationship existing respectively between CD45 on natural killer T cell, activated and secreted CD4 + regulatory T cells absolute count, CD20 on IgD + CD38 + B cell, CD66b ++ myeloid cell absolute count and keloids (with odds ratios of 1.15, 0.93, 0.87, and 0.83, respectively, 95% confidence intervals of 1.01-1.31, 0.86-1.00, 0.77-0.98, and 0.71-0.96, respectively, P<0.05). Among them, the potential causal relationship between CD20 on IgD + CD38 + B cell and keloids was further verified by the weighted mode method (with odds ratio of 0.86, 95% confidence interval of 0.77-0.97, P<0.05). According to the aforementioned IVW method analysis results, the SNPs associated with the 21 immune cell phenotypes that had a significant causal relationship with keloids showed no significant heterogeneity ( P>0.05) or significant horizontal pleiotropy ( P>0.05). Conclusions:From a genetic perspective, the potential causal relationships between 21 human immune cell phenotypes and keloids have been revealed, of which 10 immune cell phenotypes may be risk factors for keloids, while 11 immune cell phenotypes may act as protective factors for keloids.