Patients with Takayasu arteritis combined with aortic valve disease often have a poor prognosis following surgical valve replacement, frequently encountering complications such as perivalvular leakage, valve detachment, and anastomotic aneurysm. This article presents a high-risk case wherein severe aortic valve insufficiency associated with Takayasu arteritis was successfully managed through transcatheter aortic valve implantation via the transapical approach. The patient had satisfactory valve function with no complications observed during the six-month postoperative follow-up. This case provides a minimally invasive and feasible alternative for the clinical management of such high-risk patients.

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.

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.

Background: Seborrheic dermatitis (SD) is a chronic inflammatory scalp disorder associated with Malassezia dysbiosis and increased sebum production. AMPamide has been suggested to have anti-inflammatory and sebum-regulating effects, but its clinical efficacy and microbiome-modulating effects in SD remain unclear. Objective: To evaluate the clinical efficacy and scalp microbiome changes following 4 weeks of use of an AMPamide-containing shampoo in patients with SD. Methods: In this observational study, 30 patients with SD applied an AMPamide-containing shampoo for 4 consecutive weeks. Clinical outcomes, including sebum levels and overall severity scores, were assessed. Scalp bacterial and fungal communities were analyzed to evaluate α- and β-diversity and changes in Malassezia composition. Results: Treatment resulted in significant reductions in sebum levels and clinical severity scores, particularly in erythema, dandruff, and pruritus. Bacterial community composition remained largely stable, while fungal α-diversity increased, and β-diversity analysis revealed a decrease in the ratio of Malassezia restricta to Malassezia globosa. Conclusion AMPamide-containing shampoo was associated with improved clinical symptoms and a shift toward a more balanced fungal community composition in patients with SD, supporting its potential as a non-steroidal therapeutic option for SD.

Background/Aims: Treatment indications for patients with chronic hepatitis B (CHB) remain contentious, particularly for patients with mild alanine aminotransferase (ALT) elevation. We aimed to evaluate treatment effects in this patient population. Methods: This rollover study extended a placebo-controlled trial that enrolled non-cirrhotic patients with CHB and ALT levels below two times the upper limit of normal. Following 3 years of randomized intervention with either tenofovir disoproxil fumarate (TDF) or placebo, participants were rolled over to open-label TDF for 3 years. Liver biopsies were performed before and after the treatment to evaluate histopathological changes. Virological, biochemical, and serological outcomes were also assessed (NCT02463019). Results: Of 146 enrolled patients (median age 47 years, 80.8% male), 123 completed the study with paired biopsies. Overall, the Ishak fibrosis score decreased in 74 (60.2%), remained unchanged in 32 (26.0%), and increased in 17 (13.8%) patients (p<0.0001). The Knodell necroinflammation score decreased in 58 (47.2%), remained unchanged in 29 (23.6%), and increased in 36 (29.3%) patients (p=0.0038). The proportion of patients with an Ishak score ≥ 3 significantly decreased from 26.8% (n=33) to 9.8% (n=12) (p=0.0002). Histological improvements were more pronounced in patients switching from placebo. Virological and biochemical outcomes also improved in placebo switchers and remained stable in patients who continued TDF. However, serum HBsAg levels did not change and no patient cleared HBsAg. Conclusions In CHB patients with minimally raised ALT, favorable histopathological, biochemical, and virological outcomes were observed following 3-year TDF treatment, for both treatment-naïve patients and those already on therapy.

ObjectiveTo investigate the protective effect and mechanism of Shaoyaotang （SYD） on the lipopolysaccharide （LPS）-induced damage of tight junction proteins in the human colorectal adenocarcinoma （Caco-2） cell model of inflammation via the Ras homolog gene family member A （RhoA）/Rho-associated coiled-coil forming protein kinase （ROCK） pathway. MethodsCaco-2 cells were grouped as follows： Blank， model （LPS， 10 mg·L^-1）， SYD-containing serum （10%， 15%， and 20%）， and inhibitor （Fasudil， 25 μmol·L^-1）. After 24 hours of intervention， the cell viability in each group was examined by the cell-counting kit 8 （CCK-8） method. Enzyme-linked immunosorbent assay was employed to determine the levels of endothelin-1 （ET-1）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6）. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） and Western blot were employed to determine the mRNA and protein levels， respectively， of RhoA， ROCK2， claudin-5， and zonula occludens-1 （ZO-1） in cells of each group. ResultsCompared with the blank group， the model group showcased a marked reduction in the cell viability （P<0.01）， elevations in the levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.01）， declines in both mRNA and protein levels of ZO-1 and claudin-5 （P<0.01）， and rises in mRNA and protein levels of RhoA and ROCK2 （P<0.01）. Compared with the model group， the Shaoyaotang-containing serum （10%， 15%， and 20%） groups had enhanced cell viability （P<0.01）， lowered levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.01）， up-regulated mRNA and protein levels of ZO-1 and claudin-5 （P<0.05， P<0.01）， and down-regulated mRNA and protein levels of RhoA and ROCK2 （P<0.01）. Moreover， the inhibitor group and the 15% and 20% Shaoyaotang-containing serum groups had lower levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.05， P<0.01）， higher mRNA and protein levels of ZO-1 and claudin-5 （P<0.05， P<0.01）， and lower mRNA and protein levels of RhoA and ROCK2 （P<0.05， P<0.01） than the 10% Shaoyaotang-containing serum group. ConclusionThe Shaoyaotang-containing serum can lower the levels of LPS-induced increases in levels of inflammatory cytokines and endothelin to ameliorate the damage of tight junction proteins of the Caco-2 cell model of inflammation by regulating the expression of proteins in the RhoA/ROCK pathway.

This study investigates the genetic diversity and evolutionary relationships of different Artemisia argyi germplasm resources to provide a basis for germplasm identification, variety selection, and resource protection. A total of 192 germplasm resources of A. argyi were studied, and EST-based simple sequence repeat(EST-SSR) primers were designed based on transcriptomic data of A. argyi. Polymerase chain reaction(PCR) amplification was performed on these resources, followed by fluorescence capillary electrophoresis to detect genetic diversity and construct DNA fingerprints. From 197 pairs of primers designed, 28 pairs with polymorphic and clear bands were selected. A total of 278 alleles were detected, with an average of 9.900 0 alleles per primer pair and an average effective number of alleles of 1.407 2. The Shannon's diversity index(I) for the A. argyi germplasm resources ranged from 0.148 1 to 0.418 0, with an average of 0.255 7. The polymorphism information content(PIC) ranged from 0.454 5 to 0.878 0, with an average of 0.766 9, showing high polymorphism. Cluster analysis divided the A. argyi germplasm resources into three major groups: Group Ⅰ contained 136 germplasm samples, Group Ⅱ contained 45, and Group Ⅲ contained 11. Principal component analysis also divided the resources into three groups, which was generally consistent with the clustering results. Mantel test results showed that the genetic variation in A. argyi populations was to some extent influenced by geographic distance, but the effect was minimal. Structure analysis showed that 190 germplasm materials had Q≥ 0.6, indicating that these germplasm materials had a relatively homogeneous genetic origin. Furthermore, 8 core primer pairs were selected from the 28 designed primers, which could distinguish various germplasm types. Using these 8 core primers, DNA fingerprints for the 192 A. argyi germplasm resources were successfully constructed. EST-SSR molecular markers can be used to study the genetic diversity and phylogenetic relationships of A. argyi, providing theoretical support for the identification and molecular-assisted breeding of A. argyi germplasm resources.
Artemisia/classification* ; Microsatellite Repeats ; Genetic Variation ; Expressed Sequence Tags ; DNA Fingerprinting ; Phylogeny ; Polymorphism, Genetic ; DNA, Plant/genetics* ; Genetic Markers

This study aims to investigate the molecular mechanism by which naringin alleviates cerebral ischemia/reperfusion(CI/R) injury through DRP1/LRRK2/MCU signaling axis. A total of 60 SD rats were randomly divided into the sham group, the model group, the sodium Danshensu group, and low-, medium-, and high-dose(50, 100, and 200 mg·kg~(-1)) naringin groups, with 10 rats in each group. Except for the sham group, a transient middle cerebral artery occlusion/reperfusion(tMCAO/R) model was established in SD rats using the suture method. Longa 5-point scale was used to assess neurological deficits. 2,3,5-Triphenyl tetrazolium chloride(TTC) staining was used to detect the volume percentage of cerebral infarction in rats. Hematoxylin-eosin(HE) staining and Nissl staining were employed to assess neuronal structural alterations and the number of Nissl bodies in cortex, respectively. Western blot was used to determine the protein expression levels of B-cell lymphoma-2 gene(Bcl-2), Bcl-2-associated X protein(Bax), cleaved cysteine-aspartate protease-3(cleaved caspase-3), mitochondrial calcium uniporter(MCU), microtubule-associated protein 1 light chain 3(LC3), and P62. Mitochondrial structure and autophagy in cortical neurons were observed by transmission electron microscopy. Immunofluorescence assay was used to quantify the fluorescence intensities of MCU and mitochondrial calcium ion, as well as the co-localization of dynamin-related protein 1(DRP1) with leucine-rich repeat kinase 2(LRRK2) and translocase of outer mitochondrial membrane 20(TOMM20) with LC3 in cortical mitochondria. The results showed that compared with the model group, naringin significantly decreased the volume percentage of cerebral infarction and neurological deficit score in tMCAO/R rats, alleviated the structural damage and Nissl body loss of cortical neurons in tMCAO/R rats, inhibited autophagosomes in cortical neurons, and increased the average diameter of cortical mitochondria. The Western blot results showed that compared to the sham group, the model group exhibited increased levels of cleaved caspase-3, Bax, MCU, and the LC3Ⅱ/LC3Ⅰ ratio in the cortex and reduced protein levels of Bcl-2 and P62. However, naringin down-regulated the protein expression of cleaved caspase-3, Bax, MCU and the ratio of LC3Ⅱ/LC3Ⅰ ratio and up-regulated the expression of Bcl-2 and P62 proteins in cortical area. In addition, immunofluorescence analysis showed that compared with the model group, naringin and positive drug treatments significantly decreased the fluorescence intensities of MCU and mitochondrial calcium ion. Meanwhile, the co-localization of DRP1 with LRRK2 and TOMM20 with LC3 in cortical mitochondria was also decreased significantly after the intervention. These findings suggest that naringin can alleviate cortical neuronal damage in tMCAO/R rats by inhibiting DRP1/LRRK2/MCU-mediated mitochondrial fragmentation and the resultant excessive mitophagy.
Animals ; Rats, Sprague-Dawley ; Reperfusion Injury/genetics* ; Flavanones/administration & dosage* ; Rats ; Dynamins/genetics* ; Male ; Brain Ischemia/genetics* ; Protein Serine-Threonine Kinases/genetics* ; Signal Transduction/drug effects* ; Humans ; Drugs, Chinese Herbal/administration & dosage*

Background: An increased incidence of hair loss disorders has been noted among patients with coronavirus disease 2019 (COVID-19) and individuals vaccinated against COVID-19. However, research involving large populations on this topic is lacking. Objective: To investigate the risks associated with developing hair loss disorders in patients with COVID-19 and individuals vaccinated against COVID-19. Methods: This nationwide, population-based, cross-sectional study included patients diagnosed with COVID-19 and healthy individuals without a history of COVID-19 infection registered in the Korean National Health Insurance Service (NHIS) database between January 1, 2021, and December 31, 2021. COVID-19 infection and vaccine databases were integrated using this NHIS database. The odds ratios of hair loss disorders were compared using multivariate logistic regression models. Results: COVID-19 infection was associated with an increased risk of total alopecia (adjusted odds ratio [aOR], 1.076; 95% confidence interval [CI], 1.002–1.156), although this association was not significant after propensity score matching. No significant associations were found between COVID-19 infection and alopecia areata or telogen effluvium. However, COVID-19 vaccination was positively correlated with total alopecia (aOR, 1.266; 95% CI, 1.191–1.346), alopecia areata (aOR, 1.243; 95% CI, 1.154–1.339), and telogen effluvium (aOR, 1.495; 95% CI, 1.133–1.974). Conclusion COVID-19 vaccination was positively correlated with hair loss disorders but not COVID-19 infection. However, given the advantages of vaccines in reducing COVID-19 mortality and morbidity, alopecia may be relatively reversible and less severe. Physicians need to understand the benefits and possible side effects of the COVID-19 vaccine.

ObjectiveTo investigate the protective effect and mechanism of Shaoyaotang （SYD） on the lipopolysaccharide （LPS）-induced damage of tight junction proteins in the human colorectal adenocarcinoma （Caco-2） cell model of inflammation via the Ras homolog gene family member A （RhoA）/Rho-associated coiled-coil forming protein kinase （ROCK） pathway. MethodsCaco-2 cells were grouped as follows： Blank， model （LPS， 10 mg·L^-1）， SYD-containing serum （10%， 15%， and 20%）， and inhibitor （Fasudil， 25 μmol·L^-1）. After 24 hours of intervention， the cell viability in each group was examined by the cell-counting kit 8 （CCK-8） method. Enzyme-linked immunosorbent assay was employed to determine the levels of endothelin-1 （ET-1）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6）. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） and Western blot were employed to determine the mRNA and protein levels， respectively， of RhoA， ROCK2， claudin-5， and zonula occludens-1 （ZO-1） in cells of each group. ResultsCompared with the blank group， the model group showcased a marked reduction in the cell viability （P<0.01）， elevations in the levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.01）， declines in both mRNA and protein levels of ZO-1 and claudin-5 （P<0.01）， and rises in mRNA and protein levels of RhoA and ROCK2 （P<0.01）. Compared with the model group， the Shaoyaotang-containing serum （10%， 15%， and 20%） groups had enhanced cell viability （P<0.01）， lowered levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.01）， up-regulated mRNA and protein levels of ZO-1 and claudin-5 （P<0.05， P<0.01）， and down-regulated mRNA and protein levels of RhoA and ROCK2 （P<0.01）. Moreover， the inhibitor group and the 15% and 20% Shaoyaotang-containing serum groups had lower levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.05， P<0.01）， higher mRNA and protein levels of ZO-1 and claudin-5 （P<0.05， P<0.01）， and lower mRNA and protein levels of RhoA and ROCK2 （P<0.05， P<0.01） than the 10% Shaoyaotang-containing serum group. ConclusionThe Shaoyaotang-containing serum can lower the levels of LPS-induced increases in levels of inflammatory cytokines and endothelin to ameliorate the damage of tight junction proteins of the Caco-2 cell model of inflammation by regulating the expression of proteins in the RhoA/ROCK pathway.