Objective To systematically evaluate the therapeutic effects of video-assisted thoracoscopic surgery (VATS) and robot-assisted thoracic surgery (RATS) in treating mediastinal tumors. Methods A computer search was conducted on PubMed, Embase, Cochrane Library, Web of Science, Wanfang, CNKI, CBM, VIP databases for literature comparing the clinical efficacy of VATS and RATS in treating mediastinal tumors, with the search time from inception to March 31, 2024. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the included cohort studies, and Review Manager 5.4 software was used to perform a meta-analysis. Results A total of 32 articles were included, with 7868 patients. The NOS scores of the included cohort studies were all≥7 points. Meta-analysis results showed that compared with the VATS group, the RATS group had less intraoperative blood loss [MD=−16.71, 95%CI (−23.88, −9.54), P<0.001], lower conversion rate to open thoracotomy [OR=0.41, 95%CI (0.26, 0.67), P=0.003], lower overall postoperative complication rate [OR=0.66, 95%CI (0.48, 0.92), P=0.01], shorter postoperative drainage time [MD=−0.64, 95%CI (−0.92, −0.36), P<0.001], and shorter postoperative hospital stay [MD=−1.03, 95%CI (−1.28, −0.78), P<0.001]. There was no statistical difference between the two groups in terms of tumor size [MD=−0.06, 95%CI (−0.31, 0.19), P=0.64] or operation time [MD=5.52, 95%CI (−2.35, 13.40), P=0.17]. The RATS group had higher hospitalization costs than the VATS group [MD=1.69, 95%CI (1.26, 2.13), P<0.001]. Conclusion In mediastinal tumors resection, RATS is superior to VATS in terms of intraoperative blood loss, conversion rate to open thoracotomy, overall postoperative complication rate, postoperative drainage time, and postoperative hospital stay, but it increases hospitalization costs.

Objective To systematically evaluate the differences in outcomes between functional mitral regurgitation (FMR) and degenerative mitral regurgitation (DMR) in patients treated with transcatheter edge-to-edge repair (TEER) using the MitraClip device. Methods A systematic literature search was conducted in PubMed, Embase, the Cochrane Library, Web of Science, the CNKI, Wanfang Database, VIP Database, and the CBM from their inception to January 2024. Two researchers independently performed study selection, data extraction, and risk of bias assessment. The quality of cohort studies was evaluated using the Newcastle-Ottawa Scale (NOS). A meta-analysis was performed using Stata 18.0 software. Results A total of 13 cohort studies involving 6 402 patients were included, comprising 4 161 patients in the FMR group and 2 241 in the DMR group. All included studies had NOS scores of ≥6 points. The meta-analysis revealed that compared to the DMR group, the FMR group had a higher 1-year all-cause mortality rate [OR=1.53, 95%CI (1.30, 1.81), P＜0.01] and a higher 1-year rehospitalization rate for heart failure [OR=1.90, 95%CI (1.60, 2.26), P＜0.01]. Conversely, the FMR group had a lower post-procedural mean transmitral gradient [SMD=–0.47, 95%CI (–0.65, –0.30), P＜0.01] and a lower rate of subsequent mitral valve surgery [OR=0.41, 95%CI (0.20, 0.83), P=0.01]. Conclusion Following MitraClip therapy, patients with FMR exhibit favorable short-term outcomes, but their mid- to long-term outcomes are inferior to those of patients with DMR. When determining the treatment strategy with MitraClip, the specific etiology of mitral regurgitation should be considered for a more accurate prediction of therapeutic efficacy and prognosis.

The core pathogenesis of attention deficit hyperactivity disorder （ADHD） lies in deficiency， stasis and stagnation. Deficiency arises from kidney essence depletion and spleen dysfunction in transportation and transformation， leading to inadequate nourishment of the marrow sea. Stasis caused by qi deficiency leads to obstruction in channels and collaterals， resulting in obstructed marrow transport. Stagnation is associated with the excess of the five minds transforming into fire， which scorches the brain orifices and leads to loss of control over marrow utilisation. Based on this， a "supplementation-unblocking-regulation" therapeutic approach is proposed. For deficiency， the focus is on supplementing kidney and fortifying spleen， and replenishing the marrow sea. For stasis， the priority is to unblock and open the orifices， and clear the marrow channels. For stagnation， the core is to clear fire and contain the mind， regulate and restore vital activity. In clinical practice， it is necessary to identify the primary and secondary pathogenic mechanisms and apply dynamic， combined treatment， integrating Chinese herbal medicine， acupuncture， and guiding exercises throughout the process， aiming to provide a reference for the diagnosis and treatment of ADHD with traditional Chinese medical.

ObjectiveTo clarify whether METTL14 mediates the core role of acupuncture at Neiguan (PC6) in promoting myelination and improving behavior in young autistic rats through gene intervention technology. MethodsThe ASD model was established by intraperitoneal injection of valproic acid (VPA) in pregnant rats. Male offspring were intracerebroventricularly injected with adenovirus-packaged METTL14 shRNA (sh-METTL14) or its control (sh-NC) on postnatal day 1, with a model group set as well. Subsequently, the juvenile rats were divided into model group, acupuncture group, acupuncture+sh-NC group, and acupuncture+sh-METTL14 group. The acupuncture group received acupuncture at Neiguan (PC6) from postnatal day 7, once daily for 21 consecutive days. Neurobehavioral changes were evaluated by behavioral tests; METTL14 knockdown efficiency and the expression of METTL14, METTL3, and PTEN were detected by quantitative real-time PCR (qRT-PCR) and Western blot (WB); PTEN m⁶A levels were measured by RNA immunoprecipitation-qPCR (RIP-qPCR); myelin ultrastructure, expression of myelin basic protein (MBP) and neurofascin 155 (NF155), and dendritic spine density were observed using transmission electron microscopy (TEM), enzyme-linked immunosorbent assay (ELISA), immunofluorescence, qRT-PCR, and primary neuron culture. ResultsBehaviorally, knockdown of METTL14 significantly counteracted the beneficial effects of acupuncture in improving self-grooming, open field exploration, three-chamber social interaction, and Morris water maze learning and memory (P<0.05, P<0.01). Compared with the acupuncture+sh-NC group, the acupuncture+sh-METTL14 group showed significantly decreased mRNA and protein expression of hippocampal METTL14 (P<0.01), and the upregulating effects of acupuncture on METTL3 and PTEN expression were reversed (P<0.01). Meanwhile, knockdown of METTL14 significantly inhibited the acupuncture-induced increase in PTEN m⁶A levels (P<0.01). Morphologically, knockdown of METTL14 attenuated the improvement of myelin structure by acupuncture, reversed the downregulation of MBP and upregulation of NF155 induced by acupuncture, and blocked the increase in dendritic spine density (P<0.05, P<0.01). ConclusionMETTL14 is a key molecule mediating the therapeutic effect of acupuncture at Neiguan. Acupuncture at Neiguan upregulates METTL14, thereby enhancing m⁶A methylation modification of PTEN mRNA to stabilize its expression, ultimately promoting myelin development and improving behavioral symptoms in ASD juvenile rats. This preliminarily reveals the modern biological connotation of “opening Xuanfu and dredging myelin”.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

ObjectiveTo clarify whether METTL14 mediates the core role of acupuncture at Neiguan (PC6) in promoting myelination and improving behavior in young autistic rats through gene intervention technology. MethodsThe ASD model was established by intraperitoneal injection of valproic acid (VPA) in pregnant rats. Male offspring were intracerebroventricularly injected with adenovirus-packaged METTL14 shRNA (sh-METTL14) or its control (sh-NC) on postnatal day 1, with a model group set as well. Subsequently, the juvenile rats were divided into model group, acupuncture group, acupuncture+sh-NC group, and acupuncture+sh-METTL14 group. The acupuncture group received acupuncture at Neiguan (PC6) from postnatal day 7, once daily for 21 consecutive days. Neurobehavioral changes were evaluated by behavioral tests; METTL14 knockdown efficiency and the expression of METTL14, METTL3, and PTEN were detected by quantitative real-time PCR (qRT-PCR) and Western blot (WB); PTEN m⁶A levels were measured by RNA immunoprecipitation-qPCR (RIP-qPCR); myelin ultrastructure, expression of myelin basic protein (MBP) and neurofascin 155 (NF155), and dendritic spine density were observed using transmission electron microscopy (TEM), enzyme-linked immunosorbent assay (ELISA), immunofluorescence, qRT-PCR, and primary neuron culture. ResultsBehaviorally, knockdown of METTL14 significantly counteracted the beneficial effects of acupuncture in improving self-grooming, open field exploration, three-chamber social interaction, and Morris water maze learning and memory (P<0.05, P<0.01). Compared with the acupuncture+sh-NC group, the acupuncture+sh-METTL14 group showed significantly decreased mRNA and protein expression of hippocampal METTL14 (P<0.01), and the upregulating effects of acupuncture on METTL3 and PTEN expression were reversed (P<0.01). Meanwhile, knockdown of METTL14 significantly inhibited the acupuncture-induced increase in PTEN m⁶A levels (P<0.01). Morphologically, knockdown of METTL14 attenuated the improvement of myelin structure by acupuncture, reversed the downregulation of MBP and upregulation of NF155 induced by acupuncture, and blocked the increase in dendritic spine density (P<0.05, P<0.01). ConclusionMETTL14 is a key molecule mediating the therapeutic effect of acupuncture at Neiguan. Acupuncture at Neiguan upregulates METTL14, thereby enhancing m⁶A methylation modification of PTEN mRNA to stabilize its expression, ultimately promoting myelin development and improving behavioral symptoms in ASD juvenile rats. This preliminarily reveals the modern biological connotation of “opening Xuanfu and dredging myelin”.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

ObjectiveTo investigate the role of Ras-GTPase-activating protein SH3 domain-binding protein 2 （G3BP2） in regulating the activation， proliferation， and migration of hepatic stellate cells （HSCs）. MethodsThe mouse HSCs （JS-1 cell line） were treated with 5 μg/L transforming growth factor-beta 1（TGF-β1） for 24 hours to establish an HSC activation and proliferation model. A G3BP2 knockdown system was constructed using siRNA interference technology. The experiment was divided into four groups： Control， TGF-β1 treatment， TGF-β1+si-NC， and TGF-β1+ G3BP2-siRNA. The expression levels of key fibrosis indicators， including type I collagen （Collagen I）， α-smooth muscle actin （α-SMA）， and G3BP2， were detected by Western blot and RT-qPCR. Cell proliferation activity was assessed using the CCK-8 proliferation assay kit and EdU fluorescence labeling technology. Cell migration ability was analyzed by scratch wound healing assay and Transwell migration assay. The formation level of stress granules was quantified by immunofluorescence microscopy to investigate the effects of G3BP2 on stress granule formation in activated HSCs. ResultsStimulation with TGF-β1 upregulated the expression of G3BP2 in JS-1 cells （RT-qPCR： P0.000 1； Western blot： P0.000 1）， while a downward trend in its expression was observed in the G3BP2‑silenced group （RT-qPCR： P0.01； Western blot： P0.000 1）. Compared with the control group， the TGF-β1 group exhibited increased protein expression levels of α-SMA and Collagen I （RT-qPCR： both P0.01； Western blot： P0.01 and P0.05， respectively）， concomitant with an increased number of stress granules and enhanced cell proliferation and migration capacity （all P0.001）. The experimental results demonstrated that G3BP2 knockout effectively reversed the aforementioned phenotypes， with the G3BP2-silenced group showing reduced expression of fibrotic markers （all P0.01）， decreased stress granule formation （P0.01）， and reduced cell proliferation and migration capacity （all P0.05）， compared to the negative control group. ConclusionG3BP2 enhances the activation， proliferation， and migration of HSCs by promoting the formation of stress granules， thereby accelerating the pathological progression of liver fibrosis. This suggests that stress granules may serve as important regulators in controlling the activation， proliferation， and migration of HSCs.

ObjectiveTo investigate the association between serum fasting triglyceride glucose-body mass index （TyG-BMI） and new-onset metabolic dysfunction-associated fatty liver disease （MAFLD） within 10 years. MethodsA retrospective analysis was performed for the data of individuals who underwent physical examination in The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University in 2013， 2018， and 2023 and were not diagnosed with MAFLD in 2013， and a total of 1 340 valid subjects were enrolled according to the inclusion and exclusion criteria. The gbmt package in R 4.3.0 was used to construct the dynamic change trajectory model of TyG-BMI， and four different TyG-BMI trajectory groups were determined， i.e.， the low-level group （n=352）， the medium-level group （n=517）， the high-level group （n=314）， and the extremely high-level group （n=157）. The data on general information and blood biochemical parameters were collected from all subjects and were then compared between groups. The chi-square test was used for comparison of categorical data between groups， and the Kruskal-Wallis H test was used for comparison of non-normally distributed continuous data with heterogeneity of variance between multiple groups. The Cox regression analysis was used to investigate the association between different TyG-BMI trajectories and the risk of MAFLD， and the receiver operating characteristic （ROC） curve was used to assess the value of TyG-BMI in the diagnosis of MAFLD. ResultsThe cumulative incidence rate of MAFLD increased with the increase in the level of TyG-BMI trajectory， with a cumulative incidence rate of 4.83% in the low-level group， 29.98% in the medium-level group， 61.15% in the high-level group， and 83.44% in the extremely high-level group （P<0.001）， and the cumulative incidence rate of MAFLD in men was significantly higher than that in women （51.34% vs 20.67%， P<0.001）. The multivariate Cox regression analysis showed that increases in the levels of TyG-BMI trajectory， uric acid， diastolic blood pressure， hemoglobin， and alanine aminotransferase were independent risk factors for the onset of MAFLD （all P<0.05）， while the increase in high-density lipoprotein cholesterol was an independent protective factor against MAFLD （P<0.001）. After adjustment for confounding factors， the medium-， high-， and extremely high-level groups had a hazard ratio of 4.430 （95% confidence interval ［CI］： 2.660 — 7.377， P<0.001）， 6.937 （95%CI： 4.110 — 11.708， P<0.001）， and 7.989 （95%CI： 4.616 — 13.827， P<0.001）， respectively. The ROC curve analysis showed that TyG-BMI had the highest diagnostic value， with an area under the ROC curve of 0.859 （95%CI： 0.840 — 0.879）， a sensitivity of 79.8%， and a specificity of 76.3%. ConclusionThe risk of MAFLD increases with the increase in the level of TyG-BMI trajectory， and TyG-BMI can be used as a predictive indicator for MAFLD.

Background Amid global climate change, extreme environmental events are occurring more frequently, and it is imperative to investigate the impacts of combined exposure to fine particluate matter (PM_2.5) and cold spells (CS) on population mortality. Objective To analyze the association between sequential extreme PM_2.5-cold spell (EP-CS) events and non-accidental mortality among residents in Zigong City from 2016 to 2021. Methods Using time-series study design, meteorological data in Zigong were collected from the Zigong Meteorological Bureau for the period from January 1, 2016 to December 31, 2021, while daily non-accidental mortality data were obtained from the mortality surveillance system of the Zigong Center for Disease Control and Prevention. We adopted the percentile method to define extreme PM_2.5 events and cold spells. We analyzed the risk effect of EP-CS events on non-accidental mortality among residents in this city and explored the potential amplification of damage resulting from different patterns of consecutive extreme events by using distributed lag nonlinear model (DLNM). We also conducted stratified analyses based on age, gender, education level, and marital status. Results The EP-CS events demonstrated a significant impact on non-accidental mortality among the local residents, exhibiting a certain lagged effect. The effects on the overall residents lasted from lag0 (RR=1.030, 95%CI: 1.013, 1.048) to lag14 (RR=1.035, 95%CI: 1.019, 1.052). Notably, the effects were more pronounced among females, individuals aged 65 years and above, and those who were never married, divorced, or widowed. Different patterns of EP-CS events all associated with adverse effects, the health impact of EP-CS events was significantly greater than that of individual PM_2.5 pollution or CS events. The analysis of lag effects across different event patterns revealed that the overall effect of EP-CS events with shorter intervals (0–7 d) had a stronger effect compared to EP-CS with longer intervals (8–14 d), and the RR values of lag14 were 1.034 (95%CI: 1.015, 1.054) and 1.017 (95%CI: 1.007, 1.027), suggesting that the damaging effect of compound events occurring in the short term was more significant. Conclusion All sequential extreme EP-CS events have an impact on non-accidental mortality among residents in this city, with compound events demonstrating a stronger effect. Females, individuals aged ≥65 years, and those who were never married, divorced, or widowed are more sensitive to EP-CS events.