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/Aims: Pancreatic stenting reduces post-endoscopic retrograde cholangiopancreatography pancreatitis (PEP) and aids in cannulation in difficult cases. However, conservative endoscopists may stop at this step, resulting in suboptimal outcomes. This study assessed the efficacy of transpancreatic precut sphincterotomy (TPS) as a rescue procedure following pancreatic stenting. Methods: Between March 2013 and November 2018, 82 patients underwent pancreatic stenting at our institution prior to successful biliary cannulation. TPS was introduced in April 2016, and patients were divided into Before TPS and After TPS groups. The outcomes included cannulation success, PEP incidence, and predictors of TPS conversion. Results: There were 43 and 39 patients in the Before TPS and After TPS groups, respectively. Twenty-two patients (56.4%) underwent conversion to TPS in the After TPS group. The After TPS group had a higher bile duct cannulation rate (89.7% vs. 72.1%) than the Before TPS group, but this difference was not statistically significant (p=0.054). Multivariate analysis showed that age >50 years (odds ratio [OR], 0.181; p=0.021) and being in the After TPS group (OR, 0.712; p=0.039) were independently associated with reduced PEP risk. Haraldsson Type 2 and Type 4 papillae carried a relatively high TPS conversion rate. Conclusions A stepwise cannulation strategy that incorporates TPS after pancreatic stenting minimizes the need for advanced techniques and improves PEP outcomes.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Objective: To investigate the efficacy and safety of centrifugal and membrane double plasma molecular adsorption systems (DPMAS) combined with low-dose plasma exchange in the treatment of liver failure. Methods: A retrospective analysis was performed on 60 patients with liver failure treated in our hospital from April 2024 to June 2025. Based on different plasma separation methods, they were divided into the centrifugal DPMAS group (n=30) and the conventional membrane DPMAS group (n=30). The operational parameters, laboratory indicators, and adverse reactions were compared between the two groups. Results: Under the same plasma volume for adsorption and exchange (P>0.05), the centrifugal group showed lower total circulating blood volume, total blood flow rate, and treatment duration compared to the membrane group [10 794 (9 532, 12 637) vs 19 000 (19 000, 21 000) mL, 60 (60, 65) vs 125 (120, 130) mL/min, 169 (141, 193) vs 207 (183, 210) min, P<0.001]. The centrifugal group also had a lower rate of central venous catheter use [(24/30, 80.00%) vs (30/30, 100.00%), P=0.024] and required more calcium supplementation due to sodium citrate anticoagulation [6 (6, 8) vs 2 (2, 2) g, P<0.001]. No significant changes were observed in WBC, Hb, HCT, and PLT levels before and after treatment with the centrifugal group (P>0.05). There was no statistically significant difference in WBC levels before and after membrane group treatment (P=0.199), but the values of Hb, HCT, and PLT showed significant decreases post-treatment compared to pre-treatment [106.50 (102.75, 126.75) vs 123.00 (109.75, 132.00) g/L, 33.20 (29.90, 34.92) vs 34.85 (31.55, 37.52)%, 85.00 (43.25, 139.50) vs 93.00 (61.50, 145.00)×10 /L, P<0.05]. There was no significant difference in coagulation function indexes before and after treatment with centrifugal group (P>0.05). The membrane group showed reduction in fibrinogen (Fib) levels post-treatment [1.50 (1.20, 1.60) vs 1.60 (1.25, 1.80) g/L, P=0.033]. Both groups demonstrated significant decreases in total bilirubin (TBil) and direct bilirubin (DBil) levels after treatment (centrifugal group: 194.70 (107.50, 276.00) vs 239.15 (173.00, 304.17) μmol/L, 101.00 (64.00, 182.30) vs 157.00 (101.00, 195.00) μmol/L; membrane group: 211.50 (118.00, 240.00) vs 263.50 (204.75, 314.00) μmol/L, 188.00 (122.75, 232.25) vs 219.00 (178.50, 267.25) μmol/L, P<0.05]. The incidence of catheter-related complications was lower in the centrifugal group [(2/30, 6.67%) vs (8/30, 26.67%), P=0.038]. Conclusion: The centrifugal DPMAS system demonstrates advantages such as lower blood flow velocity requirements, shorter treatment duration, minimal impact on platelets, and reduced adverse event rates, indicating promising clinical applications.

BACKGROUND: Severe acute pancreatitis (SAP) is commonly associated with acute organ failure, but its effects on cerebral function within intensive care unit (ICU) patients remains inadequately researched. This study aims to determine the prevalence of delirium in critically ill patients diagnosed with SAP, and to identify risk factors associated with delirium in this patient population. METHODS: This was a retrospective, multicenter study, which enrolled adult patients diagnosed with SAP who admitted intensive care unit (ICU) for at least 24 h. Patient assessment was conducted using the Richmond Agitation-Sedation Scale (RASS) and the Confusion Assessment Method for the ICU (CAM-ICU). The cumulative incidence of delirium was determined. Demographic, clinical data, and length of ICU stay were compared between patients with and without delirium. A logistic regression model was employed to identify potential risk factors for delirium. RESULTS: A total of 1,814 patients were included from seven hospitals in Anhui province, China. Delirium was observed in 25.2% of patients. Logistic regression analysis identified APACHE II scores (odds ratio [OR]=3.37, 95% confidence interval [CI]: 1.09-10.43, P=0.04), physical restraint (OR=11.11, 95%CI: 4.35-28.39, P<0.05), invasive mechanical ventilation (IMV) (OR=2.44, 95%CI: 1.41-4.25, P=0.002), and ICU length of stay ≥ 7 days (OR=3.14, 95%CI: 2.27-4.36, P<0.05) as independent risk factors of delirium. CONCLUSION: The present study revealed a substantial incidence of delirium in critically ill patients with SAP, associated with factors including APACHE II score, IMV, physical restraint, and prolonged ICU stays.

ObjectiveTo explore the pharmacological effects and molecular mechanisms of a Jiao'ai decoction (JAD) in treating premature ovarian failure. Specifically, we evaluated the receptor for advanced glycation end (RAGE) products pathway, metabolic disorders, and intestinal flora dysbiosis.MethodsForty female rats with normal estrous cycles were randomly divided into five groups: control, model, estradiol, low-dose JAD, and high-dose JAD, with 8 rats in each. Except for the control group, the rats in other groups were injected intraperitoneally with cisplatin for 8 days (1.5 mg/kg) to establish a premature ovarian failure model. Starting on the fifth day of cisplatin injections, the estradiol, low-dose JAD, and high-dose JAD groups were administered corresponding drugs for 21 days. Sex hormone levels and pathological changes in the ovaries were measured. Key proteins in the RAGE pathway related to apoptosis, aging, and inflammation, were tested using Western blot. A 16S rRNA analysis of feces and non-targeted metabolism in serum was performed to determine the effects of JAD on intestinal flora and metabolism.ResultsBody weight, ovarian index, and the number of follicles at all levels increased in the JAD group. Regarding serum hormones, estradiol, anti-mullerian hormone (AMH) and P levels increased, whereas follicle-stimulating hormone (FSH) and luteinizing hormone (LH) levels decreased in the JAD group. The levels of phosphorylated Akt protein (P-Akt), receptor for advanced glycation end products (RAGE), tumor protein p53 (P53), C-reactive protein (CRP), apoptosis regulator BAX (BAX) and Caspase3 were downregulated by JAD, whereas B cell leukemia/lymphoma 2 (Bcl-2) and Endothelial nitric oxidase synthase (eNOS) were upregulated. JAD was also found to play an important role in the regulation of metabolic disorders and intestinal ecological imbalances by adjusting species composition and diversity.ConclusionJAD can protect ovaries by exerting anti-inflammatory and anti-apoptotic effects via inhibition of the RAGE pathway. JAD can also regulate metabolic disorders and maintain the dynamic balance of intestinal flora, thereby contributing to the improvement of the ovarian reserve function.

Photodynamic immunotherapy is a promising strategy for cancer treatment. However, the dysfunctional tumor vasculature results in tumor hypoxia and the low efficiency of drug delivery, which in turn restricts the anticancer effect of photodynamic immunotherapy. In this study, we designed photosensitive lipid nanoparticles. The synthesized PFBT@Rox Lip nanoparticles could produce type I/II reactive oxygen species (ROS) by electron or energy transfer through PFBT under light irradiation. Moreover, this nanosystem could alleviate tumor hypoxia and promote vascular normalization through Roxadustat. Upon irradiation with white light, the ROS produced by PFBT@Rox Lip nanoparticles in situ dysregulated calcium homeostasis and triggered endoplasmic reticulum stress, which further promoted the release of damage-associated molecular patterns, enhanced antigen presentation, and stimulated an effective adaptive immune response, ultimately priming the tumor microenvironment (TME) together with the hypoxia alleviation and vessel normalization by Roxadustat. Indeed, in vivo results indicated that PFBT@Rox Lip nanoparticles promoted M1 polarization of tumor-associated macrophages, recruited more natural killer cells, and augmented infiltration of T cells, thereby leading to efficient photodynamic immunotherapy and potentiating the anti-primary and metastatic tumor efficacy of PD-1 antibody. Collectively, photodynamic immunotherapy with PFBT@Rox Lip nanoparticles efficiently program TME through the induction of immunogenicity and oxygenation, and effectively suppress tumor growth through immunogenic cell death and enhanced anti-tumor immunity.