ObjectiveTo evaluate the impact of yang-reinforcing and blood-activating therapy on the long-term prognosis for patients with dilated cardiomyopathy （DCM） of yang deficiency and blood stasis syndrome. MethodsA retrospective cohort study was conducted involving 371 DCM patients with yang deficiency and blood stasis syndrome. The yang-reinforcing and blood-activating therapy was defined as the exposure factor. Patients were categorized into exposure group （186 cases） and non-exposure group （185 cases） according to whether they received yang-reinforcing and blood-activating therapy combined with conventional western medicine for 6 months or longer. The follow-up period was set at 48 months， and the Kaplan-Meier survival analysis was used to assess the cumulative incidence of major adverse cardiovascular events （MACE） in both groups. Cox regression analysis was used to explore the impact of yang-reinforcing and blood-activating therapy on the risk of MACE， and subgroup analysis was performed. Changes in traditional Chinese medicine （TCM） syndrome score， left ventricular ejection fraction （LVEF）， left ventricular fractional shortening （LVFS）， left ventricular end-diastolic diameter （LVEDD）， and Minnesota Living with Heart Failure Questionnaire （MLHFQ） score were compared between groups at the time of first combined use of yang-reinforcing and blood-activating therapy （before treatment） and 1 year after receiving the therapy （after treatment）. ResultsMACE occurred in 31 cases （16.67%） in the exposure group and 47 cases （25.41%） in the non-exposure group. The cumulative incidence of MACE in the exposure group was significantly lower than that in the non-exposure group ［HR=0.559， 95%CI（0.361，0.895）， P=0.014］. Cox regression analysis showed that yang-reinforcing and blood-activating therapy was an independent factor for reducing the risk of MACE in DCM patients ［HR=0.623， 95%CI（0.396，0.980）， P=0.041］， and consistent results were observed in different subgroups. Compared with pre-treatment， the exposure group showed decreased TCM syndrome score and MLHFQ score， reduced LVEDD， and increased LVEF and LVFS after treatment （P＜0.05）； in the non-exposure group， TCM syndrome score decreased， LVEF and LVFS increased， and LVEDD reduced after treatment （P＜0.05）. After treatment， the exposure group had higher LVEF and LVFS， smaller LVEDD， and lower TCM syndrome score and MLHFQ score compared with the non-exposure group （P＜0.05）. ConclusionCombining yang-reinforcing and blood-activating therapy with conventional western medicine can reduce the risk of MACE in DCM patients with yang deficiency and blood stasis syndrome， meanwhile improving their clinical symptoms， cardiac function， and quality of life.

Cats, owing to their physiological and immunological similarities with humans, have become increasingly valuable as model animals in virology research, drug development, and vaccine evaluation. They are irreplaceable in studies of feline immunodeficiency virus, feline coronavirus, and other related pathogens. However, cats are temperamentally sensitive, exhibit strong stress responses, and possess well-developed nervous systems as well as sharp claws and teeth. Consequently, the biosafety risks associated with infectious experiments using cats in animal biosafety level 2 laboratory (ABSL-2) are significantly higher than those encountered with conventional rodents. Drawing on long-term ABSL-2 operational experience, this article systematically reviews the entire workflow of infectious experiments in laboratory cats — from animal selection, pre-entry preparation, reception and quarantine, housing management, to infectious experimental procedures and incident response — identifying and addressing critical risk points at each stage. For strain selection, SPF-grade shorthair cats with defined genetic backgrounds and docile temperaments are recommended; sex and age should be scientifically matched to experimental objectives. During pre-entry preparation, emphasis is placed on dual-credential personnel management, health surveillance, standardized disinfection of environments and cages, feed and water standards, and robust record-keeping. During reception and quarantine, standardized protocols are established for transport control, appearance inspection, isolation quarantine, pathogen exclusion, and positive-reinforcement training. During infectious experimentation, a "three-fixed" husbandry principle is clearly implemented: dedicated caretakers, fixed feeding/cleaning times, and fixed cage positions. Disinfectant selection, autoclaving of waste, and daily veterinary rounds are rigorously enforced. Operational risk control includes detailed measures for graded personal protection, animal anesthesia and restraint, zoned operation within biosafety cabinets, and disposal of experimental waste. Contingency plans are formulated to address animal death, escape, personnel exposure, and spills of infectious materials. This study provides a reproducible and scalable technical pathway and operational standard for conducting infectious experiments in laboratory cats in ABSL-2 laboratories, offering a reference for other facilities undertaking similar work.

ObjectiveTo prepare rabbit anti-porcine inhibin polypeptide-keyhole limpet hemocyanin(KLH) conjugated polyclonal antibody and evaluate its effect on superovulation in C57BL/6J mice. MethodsNew Zealand white rabbits were immunized with a synthesized porcine inhibin polypeptide conjugated with KLH to produce anti-inhibin serum (AIS, i.e., inhibin polyclonal antibody). Female C57BL/6J mice received intraperitoneal injections of purified AIS in combination with pregnant mare serum gonadotropin (PMSG), followed by human chorionic gonadotropin (hCG) after 48 hours to induce superovulation. Oocytes obtained from superovulation were collected and counted 15 hours post-hCG administration, and the number of 2-cell embryos was assessed 24 hours after in vitro fertilization. ResultsAIS prepared by immunizing New Zealand White rabbits with KLH-conjugated porcine inhibin polypeptide was subjected to titer determination by indirect ELISA, showing titers reaching 1∶ 512 000. SDS-polyacrylamide gel electrophoresis analysis of ammonium sulfate-purified AIS revealed distinct 50 kDa and 25 kDa bands corresponding to the theoretical molecular weights of IgG antibody heavy and light chains, confirming successful production of porcine inhibin polyclonal antibody. Compared with conventional superovulation methods, AIS diluted 10-fold combined with PMSG significantly increased the number of oocytes obtained from superovulation in mice (P<0.05) by approximately 1.5-fold. ConclusionPorcine inhibin polyclonal antibody, as an improved superovulation reagent, can improve superovulation efficiency in C57BL/6J mice, and shows promising prospects for future applications.

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.

ObjectiveRecent studies have highlighted the critical role of NUDT19 in the initiation, progression, and prognosis of specific cancer types. However, its involvement in pan-cancer analysis has not been fully characterized. This study aims to systematically explore the expression patterns, clinical significance, and immune-related functions of NUDT19 in various cancer types through multi-omics analysis, further revealing its potential role in cancer, particularly its functional and therapeutic target value in leukemia. MethodsTo achieve this goal, various bioinformatics approaches were employed to evaluate the expression patterns, clinical significance, and immune-related functions of NUDT19 in tumors and normal tissues. Additionally, we analyzed the mutation characteristics of NUDT19 and its relationship with epigenetic modifications. Using the single-cell analysis tool SingleCellBase, we explored the distribution of NUDT19 across different cell subpopulations in tumors. To validate these findings, qRT-PCR was used to measure NUDT19 expression levels in specific tumor cell lines, and we established acute myeloid leukemia (AML) cell lines (HL-60 and THP-1) to conduct NUDT19 knockdown and overexpression experiments, assessing its effects on leukemia cell proliferation, apoptosis, and invasion. ResultsPan-cancer analysis revealed the dysregulated expression of NUDT19 across multiple cancer types, which was closely associated with poor prognosis, clinical staging, and diagnostic markers. Furthermore, NUDT19 was significantly correlated with tumor biomarkers, immune-related genes, and immune cell infiltration in different cancers. Mutation analysis showed that multiple mutations in NUDT19 were significantly associated with epigenetic changes. Single-cell analysis revealed the heterogeneity of NUDT19 expression in cancer cells, suggesting its potentially diverse functional roles in different cell subpopulations. qRT-PCR experiments confirmed the significant upregulation of NUDT19 in various tumor cell lines. In AML cell lines, NUDT19 knockdown led to reduced cell proliferation and invasion, with increased apoptosis, while NUDT19 overexpression significantly enhanced cell proliferation and invasion while reducing apoptosis. ConclusionThis study demonstrates the diverse roles of NUDT19 in various cancer types, with a particularly prominent functional role in leukemia. NUDT19 is not only associated with tumor initiation and progression but may also influence cancer progression through the regulation of immune microenvironment and epigenetic mechanisms. Our research highlights the potential of NUDT19 as a therapeutic target, particularly for targeted therapies in malignancies such as leukemia, with significant clinical application prospects.

The study aimed to investigate the effect of the CD200R1 gene deletion on microglia activation and nigrostriatal dopamine neuron loss in the Parkinson's disease (PD) process. The CRISPR-Cas9 technology was applied to construct the CD200R1^-/- mice. The primary microglia cells of wild-type and CD200R1^-/- mice were cultured and treated with bacterial lipopolysaccharide (LPS). Microglia phagocytosis level was assessed by a fluorescent microsphere phagocytosis assay. PD mouse model was prepared by nigral stereotaxic injection of recombinant adeno-associated virus vector carrying human α-synuclein (α-syn). The changes in the motor behavior of the mice with both genotypes were evaluated by cylinder test, open field test, and rotarod test. Immunohistochemical staining was used to assess the loss of dopamine neurons in substantia nigra. Immunofluorescence staining was used to detect the expression level of CD68 (a key molecule involved in phagocytosis) in microglia. The results showed that CD200R1 deletion markedly enhanced LPS-induced phagocytosis in vitro by the microglial cells. In the mouse model of PD, CD200R1 deletion exacerbated motor behavior impairment and dopamine neuron loss in substantia nigra. Fluorescence intensity analysis results revealed a significant increase in CD68 expression in microglia located in the substantia nigra of CD200R1^-/- mice. The above results suggest that CD200R1 deletion may further activates microglia by promoting microglial phagocytosis, leading to increased loss of the nigrostriatal dopamine neurons in the PD model mice. Therefore, targeting CD200R1 could potentially serve as a novel therapeutic target for the treatment of early-stage PD.
Animals ; Microglia/physiology* ; Mice ; Phagocytosis ; Parkinson Disease/genetics* ; Disease Models, Animal ; Receptors, Cell Surface/physiology* ; Dopaminergic Neurons/pathology* ; Antigens, CD/metabolism* ; Gene Deletion ; Substantia Nigra ; Mice, Inbred C57BL ; Mice, Knockout ; Cells, Cultured ; Male ; alpha-Synuclein ; CD68 Molecule ; Orexin Receptors

The study aims to examine the effects and potential mechanisms of disulfiram (DSF) on cardiac hypertrophic injury, focusing on the role of transforming growth factor-β-activated kinase 1 (TAK1)-mediated pan-apoptosis (PANoptosis). H9C2 cardiomyocytes were treated with angiotensin II (Ang II, 1 µmol/L) to establish an in vitro model of myocardial hypertrophy. DSF (40 µmol/L) was used to treat cardiomyocyte hypertrophic injury models, either along or in combination with the TAK1 inhibitor, 5z-7-oxozeaenol (5z-7, 0.1 µmol/L). We assessed cell damage using propidium iodide (PI) staining, measured cell viability with CCK8 assay, quantified inflammatory factor levels in cell culture media via ELISA, detected TAK1 and RIPK1 binding rates using immunoprecipitation, and analyzed the protein expression levels of key proteins in the TAK1-mediated PANoptosis pathway using Western blot. In addition, the surface area of cardiomyocytes was measured with Phalloidin staining. The results showed that Ang II significantly reduced the cellular viability of H9C2 cardiomyocytes and the binding rate of TAK1 and RIPK1, significantly increased the surface area of H9C2 cardiomyocytes, PI staining positive rate, levels of inflammatory factors [interleukin-1β (IL-1β), IL-18, and tumor necrosis factor α (TNF-α)] in cell culture media and p-TAK1/TAK1 ratio, and significantly up-regulated key proteins in the PANoptosis pathway [pyroptosis-related proteins NLRP3, Caspase-1 (p20), and GSDMD-N (p30), apoptosis-related proteins Caspase-3 (p17), Caspase-7 (p20), and Caspase-8 (p18), as well as necroptosis-related proteins p-MLKL, RIPK1, and RIPK3]. DSF significantly reversed the above changes induced by Ang II. Both 5z-7 and exogenous IL-1β weakened these cardioprotective effects of DSF. These results suggest that DSF may alleviate cardiac hypertrophic injury by inhibiting TAK1-mediated PANoptosis.
Animals ; MAP Kinase Kinase Kinases/physiology* ; Rats ; Myocytes, Cardiac/pathology* ; Disulfiram/pharmacology* ; Cardiomegaly ; Apoptosis/drug effects* ; Cell Line ; Angiotensin II ; Necroptosis/drug effects* ; Interleukin-1beta/metabolism* ; Receptor-Interacting Protein Serine-Threonine Kinases/metabolism* ; Lactones ; Resorcinols ; Zearalenone/administration & dosage*