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.

Objective To examine the quality of Zukamu preparations through the national drug sampling and testing,and further understand their current quality status and existing problems.This work is benefit for improving the quality standard of Zukamu preparations and providing technical support for the drug regulatory authorities.Methods Samples of Zukamu preparations were collected from a total of 29 provinces in China,and were tested for description,identification,other requirements(weight variation,particle size,determination of water,disprsion,and microbial limit items),and assay in accordance with the national pharmaceutical standards.The test data were analyzed to evaluate the quality status of the Zukamu preparations,and exploratory research was carried out to address the problems found in the test.Results A total of 97 batches of Zukamu preparations were sampled,and the passing rate was 100.0%according to the current quality standard.Exploratory study,revealed that Zukamu preparation were subject to 4 testing standards,with uneven test items,missing items,poor operability,and lack of exclusivity in some items.The test based on the existing standards can't comprehensively evaluate the quality of the preparation.Conclusions Based on the national drug sampling and testing,combined with exploratory research on drug safety,authenticity and effectiveness,it is recommended to unify the quality standards of Zukamu preparations by combining with the work of standard improving,revising the identification method of thin-layer chromatography,increasing the content determination,and establishing the quick test method,thereby effectively evaluating and controling the quality of the samples of Zukamu preparations.

Based on the results of the National Drug Sampling and Inspection Programme,we summarized the history,the standard collection,the production enterprises and the dosage form specifications,the quality standard study,the pharmacological and pharmacodynamic study,and the clinical application study of Wuwei Qingzhuo preparation of Mongolian medicine and Shiliu Jianwei preparation of Zang medicine,to provide the basis for improved quality standards for both preparations.The development of these two preparations was searched and analyzed through literature.The available information shows that there is very little research on the two preparations and insufficient pharmacological experimental and clinical experimental data.The two preparations are basically the same in prescription and efficacy.However,the quality standards are very different,which are not conducive to the quality control of the two and their related dosage forms.And it is suggested that the Chinese Pharmacopoeia should take the situation of this category into comprehensive consideration,and unify the quality standards of the two preparations.

Osteosarcoma is the most common primary malignant bone tumor,typically treated with a combination of surgery and chemotherapy in clinical practice.However,the increasing prevalence of chemotherapy resistance poses a significant challenge.Chemotherapy resistance can lead to a sharp decline in patients'survival rates.Traditional Chinese medicine,known for its low cost,wide-ranging efficacy,and diverse varieties,has attracted significant attention from researchers.Their attempts to investigate the sensitizing effect of extracted ingredients on osteosarcoma chemoresistance both in vitro and in vivo have yielded promising results.This review has summarized the studies of single traditional Chinese medicine ingredients on reversing osteosarcoma chemoresistance by the mechanisms of chemoresistance,and found that the current research of the clinical mechanism of traditional Chinese medicine ingredients in reversing osteosarcoma chemoresistance is still lacking,indicating significant potential for future development.Utilizing the theory of herbal medicine properties as the theoretical basis for ingredient development may provide novel strategies for the development of new therapeutic approaches.

To investigate the impact of preoperative serum follicle-stimulating hormone (FSH) levels on the probability of testicular sperm retrieval, we conducted a study of nonobstructive azoospermic (NOA) men with different testicular volumes (TVs) who underwent microdissection testicular sperm extraction (micro-TESE). A total of 177 NOA patients undergoing micro-TESE for the first time from April 2019 to November 2022 in Shenzhen Zhongshan Obstetrics and Gynecology Hospital (formerly Shenzhen Zhongshan Urology Hospital, Shenzhen, China) were retrospectively reviewed. The subjects were divided into four groups based on average TV quartiles. Serum hormone levels in each TV group were compared between positive and negative sperm retrieval subgroups. Overall sperm retrieval rate was 57.6%. FSH levels (median [interquartile range]) were higher in the positive sperm retrieval subgroup compared with the negative outcome subgroup when average TV was <5 ml (first quartile [Q1: TV <3 ml]: 43.32 [17.92] IU l -1 vs 32.95 [18.56] IU l -1 , P = 0.048; second quartile [Q2: 3 ml ≤ TV <5 ml]: 31.31 [15.37] IU l -1 vs 25.59 [18.40] IU l -1 , P = 0.042). Elevated serum FSH levels were associated with successful micro-TESE sperm retrieval in NOA men whose average TVs were <5 ml (adjusted odds ratio [OR]: 1.06 per unit increase; 95% confidence interval [CI]: 1.01-1.11; P = 0.011). In men with TVs ≥5 ml, larger TVs were associated with lower odds of sperm retrieval (adjusted OR: 0.84 per 1 ml increase; 95% CI: 0.71-0.98; P = 0.029). In conclusion, elevated serum FSH levels were associated with positive sperm retrieval in micro-TESE in NOA men with TVs <5 ml. In men with TV ≥5 ml, increases in average TVs were associated with lower odds of sperm retrieval.
Humans ; Male ; Azoospermia/surgery* ; Sperm Retrieval/statistics & numerical data* ; Adult ; Follicle Stimulating Hormone/blood* ; Retrospective Studies ; Testis/pathology* ; Microdissection ; Organ Size

A solid-phase extraction-ultra-performance liquid chromatography-tandem mass spectrometry(SPE-UPLC-MS/MS)method was established for simultaneous determination of 10 kinds of neonicotinoid pesticide residues in aquaculture water.Based on the chemical properties of neonicotinoid pesticides and the matrix characteristics of aquaculture water,suitable temporary storage methods for water samples and appropriate solid-phase extraction columns were selected,and the extraction conditions(including elution solvents and sample loading volumes)were optimized.The method employed acetonitrile and 5 mmol/L ammonium acetate solution(containing 0.1%formic acid)as the mobile phase and an Oasis HLB solid-phase extraction column combined with PSA as a dispersive sorbent for sample purification.The method exhibited good linearity in detection of neonicotinoid in concentration range of 0.2-50 ng/mL(R2>0.99797),with a detection limit of 0.5 ng/L and a quantification limit of 1 ng/L,which were significantly lower than the maximum acceptable method detection limits(9-500 ng/L)for neonicotinoid insecticides in water published by the European Commission.In pond water,rice-fish water,and seawater,the average recoveries of the 10 target analytes were 74.6%-114.1%,with relative standard deviations ranging from 0.3%to 9.6%.Using this method,actual sample tests were conducted on the Pearl River water,Zhaoqing pond water,and Qingyuan rice-fish aquaculture water.The total concentration of five neonicotinoid pesticides in the Pearl River water ranged from 154.8 to 246.6 ng/L,the total concentration of four neonicotinoid pesticides in the Zhaoqing pond water was 95.0-176.1 ng/L,and the total concentration of three neonicotinoid pesticides in the Qingyuan rice-fish aquaculture water was 2.3-11.7 ng/L.This method was simple in operation,highly sensitive,and had strong resistance to interference.It was suitable for detection of trace neonicotinoid pesticides in aquaculture water and could provide technical support for construction of a green aquaculture environment and resolution of international trade disputes.

OBJECTIVE: To investigate the expression and potential mechanism of calcium/calmodulin-dependent protein kinase II gamma (CaMKIIγ) in patients with acute myeloid leukemia (AML). METHODS: Peripheral blood samples were collected from 90 AML patients, and mononuclear cells were isolated. The expression of CaMKIIγ was measured using real-time quantitative PCR and Western blot. The diagnostic value of CaMKIIγ for AML was assessed, and its correlation with clinical characteristics was analyzed using the clinical data of patients. Additionally, the molecular mechanisms of CaMKIIγ were preliminarily explored. RESULTS: Compared with the control group, the expression of CaMKIIγ was significantly upregulated in AML patients. Receiver operating characteristic (ROC) curve analysis showed that CaMKIIγ could serve as a promising biomarker for distinguishing AML patients from healthy individuals. Furthermore, CaMKIIγ was significantly correlated with white blood cell (WBC) count and FLT3-ITD mutation. CaMKIIγ was highly expressed in both newly diagnosed and relapsed AML patients, while decreased during remission. In AML cell lines, the expression levels of CaMKIIγ were all elevated. Inhibition of phosphorylated CaMKIIγ by berbamine led to a decrease in pAKT and pSTAT5 expression. CONCLUSION CaMKIIγ is significantly upregulated in AML patients, and is associated with poor clinicopathological features and unfavorable prognosis. It may serve as a prognostic marker and potential therapeutic target in AML. Its expression may be related to the activation of pAKT and pSTAT5, suggesting that CaMKIIγ may contribute to the development and progression of AML through the activation of the AKT/STAT5 signaling pathway.
Humans ; Leukemia, Myeloid, Acute/metabolism* ; Calcium-Calmodulin-Dependent Protein Kinase Type 2/metabolism* ; STAT5 Transcription Factor/metabolism* ; Male ; Female ; Proto-Oncogene Proteins c-akt/metabolism* ; Mutation ; Middle Aged ; Adult ; Clinical Relevance

Osteosarcoma is the most common primary malignant bone tumor,typically treated with a combination of surgery and chemotherapy in clinical practice.However,the increasing prevalence of chemotherapy resistance poses a significant challenge.Chemotherapy resistance can lead to a sharp decline in patients'survival rates.Traditional Chinese medicine,known for its low cost,wide-ranging efficacy,and diverse varieties,has attracted significant attention from researchers.Their attempts to investigate the sensitizing effect of extracted ingredients on osteosarcoma chemoresistance both in vitro and in vivo have yielded promising results.This review has summarized the studies of single traditional Chinese medicine ingredients on reversing osteosarcoma chemoresistance by the mechanisms of chemoresistance,and found that the current research of the clinical mechanism of traditional Chinese medicine ingredients in reversing osteosarcoma chemoresistance is still lacking,indicating significant potential for future development.Utilizing the theory of herbal medicine properties as the theoretical basis for ingredient development may provide novel strategies for the development of new therapeutic approaches.

Objective To compare the effects of different exercise acclimatization(EA)durations on liver injury and inflammatory response in mice with exertional heatstroke(EHS).Methods A total of 168 male C57BL/6 mice were randomly assigned to four groups using a random number table:no exercise acclimation group(EA0W,n=54),1-week exercise acclimation group(EA1W,n=54),2-week exercise acclimation group(EA2W,n=54),and blank control group(n=6).The blank control group did not undergo acclimatization training or EHS modeling.The EA1W and EA2W groups underwent daily 2-hour exercise training at a speed of 10 m/min in an environment maintained at(26.0±0.5)℃for 1 and 2 weeks,respectively,followed by a 2-day rest after training completion.EHS modeling was performed in mice of EA0W,EA1W,and EA2W groups through running at 10 m/min under controlled environmental conditions(39.5℃ambient temperature,65%relative humidity).The modeling endpoint was defined as loss of consciousness accompanied by a core body temperature≥42.7℃.All modeling procedures were systematically documented.Following modeling,18 mice from EA0W,EA1W,and EA2W groups underwent 24-hour survival analysis.Blood samples from the abdominal aorta and liver tissues were collected at 6,12 and 24 hours post-modeling(6 mice per time point for each group).Plasma levels of alanine aminotransferase(ALT),aspartate aminotransferase(AST),and creatine kinase(CK)were quantified.Interleukin(IL)-1β and IL-6 concentrations were determined using enzyme-linked immunosorbent assay(ELISA).Liver tissue specimens underwent hematoxylin-eosin(HE)staining and pathological scoring.Results The EHS model was successfully established in all EA groups.When all mice in EA0W group developed EHS(65 min after the modeling initiation),the incidence rates in EA1W and EA2W groups were 50.0%and 22.2%,respectively,with a statistically significant difference between EA0W group and the latter two groups(P<0.05).When all mice in the three groups developed EHS,the time to EHS onset was significantly longer in both EA1W and EA2W groups compared to EA0W group,with EA2W group showing a longer onset time than EA1W group(P<0.05).Survival analysis revealed a significantly higher 24-hour survival rate in EA2W group(61.1%)compared to EA0W group(33.3%)(P<0.05),while no significant difference was observed between EA1W group and the other two groups(P>0.05).The levels of IL-1β,IL-6,and CK were highest at 6 h post-modeling in all EA groups(P<0.05),and liver injury was most severe at 12 h post-modeling(P<0.05).Compared to EA0W group,the levels of ALT,AST,and IL-1β,as well as liver pathology scores,were significantly lower at 12 h post-modeling in both EA1W and EA2W groups(P<0.05),with EA2W group showing significantly lower ALT and AST levels,as well as liver pathology scores than EA1W group(P<0.05).At 6 h post-modeling,CK levels were significantly higher in EA1W and EA2W groups compared to EA0W group(P<0.05),with EA2W group exhibiting higher CK levels than in EA1W group(P<0.05).Conclusions Exercise acclimation helps reduce the incidence of EHS.Following EHS onset,the survival rate of exercise-acclimated mice is higher than that non-acclimated mice,with a significantly higher survival rate in mice acclimated for 2 weeks compared to non-acclimated mice.However,no significant difference in survival rate is observed between mice acclimated for 1 week and non-acclimated mice.Additionally,exercise acclimation for 2 weeks is more effective in reducing liver injury and inflammatory responses compared to 1-week acclimation.