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 investigate the temporal changes in pathological damage and macrophage polarization in liver and spleen tissues of mice infected with Angiostrongylus cantonensis, and to preliminarily unravel the peripheral immune responses during the early stage of A. cantonensis infection. Methods Forty female BALB/c mice at ages of 6 to 8 weeks were randomly divided into four groups, including the control group and 7-, 14-, and 21-day infection groups, with 10 mice in each group. Each mouse in the infection groups was inoculated with 30 third-stage (L3) larvae of A. cantonensis by oral gavage, and five mice were randomly selected from each infection group on days 7, 14, and 21 post-infection, while mice in the control group were given the same volume of physiological saline and five mice were randomly selected from the control group on the day of oral gavage. Mouse liver and spleen tissues were sampled. The histopathological changes of mouse liver and spleen tissues were observed using hematoxylin and eosin (HE) staining, and the percentage of positive staining area and the co-localization positive rates of the macrophage surface antigens F4/80, CD86, and CD206 were quantified in mouse liver and spleen tissues using immunohistochemical and immunofluorescence staining. In addition, five mice were collected from each infection group on days 7, 14, and 21 post-infection, and five mice were collected from the control group on the day of oral gavage. Mouse liver and spleen tissues were sampled for detection of macrophage markers CD86 and CD206 and macrophage phenotyping using flow cytometry, and the expression of M1 macrophage markers, including inducible nitric oxide synthase (Nos2), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) and M2 markers, including arginase 1 (Arg1), mannose receptor C-type 1 (Mrc1) and chitinase-like protein 3 (Chil3) was quantified in mouse liver and spleen tissues using real-time quantitative PCR (RT-qPCR) assay. Results Proliferative lesions of the hepatocyte were observed in mouse liver tissues and the follicular structures of the mouse spleen white pulp were disrupted 21 days post-infection with A. cantonensis. Immunohistochemical staining showed that there were significant differences in the percentages of F4/80, CD86 and CD206 positive staining areas in the liver and spleen tissues among the four groups of mice (F = 242.40, 197.14, 183.19, 157.65, 242.35 and 146.24; all P values < 0.001), and the percentages of positive staining in the liver and spleen tissues of mice in the 14-day infection group [(4.45 ± 0.51)%, (3.74 ± 0.67)%, (8.32 ± 0.72)%, (16.56 ± 1.14)%, (11.62 ± 0.52)%, and (8.29 ± 0.72)%, respectively] and the 21-day infection group [(3.70 ± 0.11)%, (3.22 ± 0.43)%, (11.53 ± 1.03)%, (12.59 ± 1.05)%, (9.02 ± 0.83)%, and (11.67 ± 1.10)%, respectively] were higher than in the control group [(0.35 ± 0.16)%, (0.40 ± 0.02)%, (0.93 ± 0.05)%, (2.78 ± 0.26)%, (2.33 ± 0.20)%, and (1.85 ± 0.20)%, respectively] (all P values < 0.05). Immunofluorescence staining showed significant differences in the positive rates of F4/80 co-localization with CD86 and CD206 in mouse liver and spleen tissues among the four groups (F = 24.42, 25.28, 54.51 and 130.55; all P values < 0.001). Flow cytometry detected significant differences in the proportions of CD86⁺ and CD206⁺ macrophages in mouse liver and spleen tissues among the four groups (F = 67.98, 18.41, 29.77, 172.80; all P values < 0.001), and the proportions of CD206⁺ macrophages in the liver and spleen of the 21-day infection group were significantly higher than those in the control group [(9.25 ± 2.55)% vs (3.83 ± 0.72)%, and (4.22 ± 0.56)% vs (0.47 ± 0.18)%, respectively] (both P values < 0.05). In addition, RT-qPCR assay quantified significant differences in the relative mRNA expression of M1 macrophage markers (IL-1β, TNF-α and Nos2) and M2 macrophage markers (Arg1, Chil3 and Mrc1) in mouse liver and spleen tissues among the four groups (F = 41.30, 31.82, 199.33, 19.96, 62.01, 119.76, 23.67, 95.90, 72.27, 82.59, 123.41 and 29.75; all P values < 0.05). Conclusions A. cantonensis infection may cause progressive pathological damage in mouse liver and spleen tissues, accompanied by dynamic temporal changes in macrophage polarization. M1 macrophage polarization predominates at the early stage of A. cantonensis infection and shifts towards M2 polarization at the later stages, suggesting that M2 polarization may participate in immune regulation at late stages of A. cantonensis infection by suppressing excessive inflammatory responses and promoting tissue repair.

Objective: To investigate the health-related quality of life and its influencing factors in elderly patients with metabolic syndrome (MS), so as to provide the evidence for improving health-related quality of life in older adults with chronic diseases. Methods: In 2021, elderly MS patients aged ≥60 years from four districts in Nanjing City were selected as the study subjects using a multi-stage random sampling method. Data on social demographic information, lifestyle, disease history and blood biochemical indicators were collected through questionnaire surveys, physical examination and laboratory tests. Health utility value and EuroQol Visual Analog Scale (EQ-VAS) score were assessed using the EuroQol 5-dimension 3-level questionnaire. Factors affecting health-related quality of life were identified with the Tobit regression model and multiple linear regression model. Results: A total of 3 378 elderly MS patients were included, with a median age of 67.00 (interquartile range, 7.00) years. There were 1 558 males (46.12%) and 1 820 females (53.88%). The median (interquartile range) of health utility value and EQ-VAS score were 1.00 (0.03) and 80.00 (15.00). Tobit regression and multiple linear regression analysis showed that gender (female, β=-0.034), education level (middle school, β=0.024; junior college and above, β=0.046), marital status (married, β=0.014), physical activity (sufficient, β=0.013), vegetable intake (meet standard, β=-0.009) and fruit intake (meet standard, β=0.016) were the influencing factors of health utility value. Residence (urban area, β=1.933) and alcohol consumption (yes, β=1.761) were influencing factors of EQ-VAS score. Age, cardiovascular and cerebrovascular diseases, malignant tumors and chronic respiratory diseases were the influencing factors of health utility value and EQ-VAS score. Conclusion Age, sex, marital status, residence, lifestyle and disease are mainly associatied with the health-related quality of life in elderly MS patients.

Objective To track and evaluate the implementation and application of the occupational health standard Radiation shielding requirements for radiotherapy room—Part 4: Radiotherapy room of ²⁵²Cf neutron afterloading (GBZ/T 201.4-2015) by radiation health technical service agencies, medical institutions, health supervision agencies, and radiotherapy facility design units, and to provide a scientific basis for the further revision and implementation of this standard. Methods Following the Guideline for health standards tracking evaluation (WS/T 536-2017) and the project implementation plan, relevant practitioners were randomly selected for a questionnaire survey. The survey primarily focused on their awareness, standard training, application, and revision suggestions of GBZ/T 201.4-2015. The results were summarized and analyzed. Results A total of 168 evaluation questionnaires were collected from relevant practitioners in 28 provinces. Only 31.6% of the respondents reported being “well familiar” or “ familiar” with the standard, 27.4% of the respondents believed that the standard was widely used, and 45.2% of the respondents believed that the standard could meet the needs of their work. Only 14.9% of the respondents had received relevant training on the standard, more than half of the respondents had not applied the standard within the past 10 years, and 45.2% of the respondents believed that the standard "needs to be revised". Conclusion Due to the small number of californium-252 neutron afterloading radiotherapy devices in operation on the market, the overall awareness of the standard is low, suggesting that relevant authorities need to strengthen training and publicity of the standard, and that certain sections of the standard need to be revised or merged.

INTRODUCTION: Adolescent depression is prevalent, and teen suicide rates are on the rise locally. A systemic review to understand associated risk and protective factors is important to strengthen measures for the prevention and early detection of adolescent depression and suicide in Singapore. This systematic review aims to identify the factors associated with adolescent depression in Singapore. METHODS: A systematic search on the following databases was performed on 21 May 2020: PubMed, EMBASE and PsycINFO. Full texts were reviewed for eligibility, and the included studies were appraised for quality using the Newcastle Ottawa Scale. Narrative synthesis of the finalised articles was performed through thematic analysis. RESULTS: In total, eight studies were included in this review. The four factors associated with adolescent depression identified were: (1) sociodemographic factors (gender, ethnicity); (2) psychological factors, including childhood maltreatment exposure and psychological constructs (hope, optimism); (3) coexisting chronic medical conditions (asthma); and (4) lifestyle factors (sleep inadequacy, excessive internet use and pathological gaming). CONCLUSION The identified factors were largely similar to those reported in the global literature, except for sleep inadequacy along with conspicuously absent factors such as academic stress and strict parenting, which should prompt further research in these areas. Further research should focus on current and prospective interventions to improve mental health literacy, targeting sleep duration, internet use and gaming, and mitigating the risk of depression in patients with chronic disease in the primary care and community setting.
Humans ; Singapore/epidemiology* ; Adolescent ; Risk Factors ; Depression/etiology* ; Protective Factors ; Male ; Female ; Life Style ; Suicide

ObjectiveTo investigate the mechanism of action of modified Shaofu Zhuyutang in antagonizing cellular pyroptosis and fibrosis in ectopic endometrial tissues of endometriosis through the Toll-like receptor 4/nuclear factor-κB/NOD-like receptor protein 3 （TRL4/NF-κB/NLPR3） signaling pathway. MethodsSeventy-two SPF-grade female SD rats were randomly divided into a sham-operated group （n = 12） and a modeling group （n = 60）. The rats in the sham-operated group underwent a caesarean section， while the rats in the modeling group were used to establish an endometriosis model through the auto-transplantation method. After successful modeling， the animals were randomly divided into the model group， progesterone group （0.25 mg·kg^-1）， and modified Shaofu Zhuyutang low-， medium-， and high-dose groups （7.5， 15， 30 g·kg^-1）， with 12 animals in each group. After 4 weeks of drug administration， voluntary activity and heat pain latency were observed. The rats were sacrificed for tissue collection， and Masson staining were used to observe histopathological changes in the endometrial tissues. Enzyme-linked immunosorbent assay （ELISA） was used to measure serum levels of interleukin-18 （IL-18）， interleukin-1β （IL-1β）， tumor necrosis factor-α （TNF-α）， and transforming growth factor-β （TGF-β）. Immunohistochemistry （IHC） was used to detect the protein expression area of tumor necrosis factor-related factor 6 （TRAF6） and NLPR3 in the endometrial tissues. Immunofluorescence （IF） was used to detect the relative fluorescence intensity of Caspase-1 and gasdermin D （GSDMD） in the endometrial tissues. Western blot was employed to measure the relative expression of TRL4， myeloid differentiation factor 88 （MyD88）， TRAF6， NF-κB p65， phosphorylated NF-κB p65 （p-NF-κB p65）， and NLPR3 proteins in endometrial tissues. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of TRL4， MyD88， TRAF6， NF-κB， and NLPR3 in the endometrial tissues. ResultsCompared with the sham-operated group， rats in the model group showed reduced voluntary activity and shorter heat pain latency. Serum levels of IL-18， IL-1β， TNF-α， and TGF-β were elevated. The relative expression areas of TRAF6 and NLPR3 proteins were increased， and the relative fluorescence intensity of Caspase-1 and GSDMD was enhanced. The relative expression of TRL4， MyD88， TRAF6， NF-κB p65， p-NF-κB p65， and NLPR3 proteins， along with the expression of TRL4， MyD88， TRAF6， NF-κB， and NLPR3 mRNA， were significantly increased （P<0.01）. Compared with the model group， rats in the progesterone group and the modified Shaofu Zhuyutang medium- and high-dose groups exhibited improved voluntary activity， longer heat pain latency， the fibrosis of endometrial tissue is alleviated. Serum levels of IL-18， IL-1β， TNF-α， and TGF-β were decreased. The relative expression areas of TRAF6 and NLPR3 proteins decreased， and the relative fluorescence intensity of Caspase-1 and GSDMD weakened. The relative expression of TRL4， MyD88， TRAF6， p-NF-κB p65， NLPR3 proteins， and TRL4， MyD88， TRAF6， NF-κB， and NLPR3 mRNA expression were reduced （P<0.05， P<0.01）. ConclusionModified Shaofu Zhuyutang may play a therapeutic role in endometriosis by interfering with key proteins in the TRL4/NF-κB/NLPR3 signaling pathway， reducing NLRP3 inflammasome-induced cellular pyroptosis， antagonizing the fibrosis process in ectopic endometrial tissues， improving the inflammatory microenvironment in the pelvic cavity， and alleviating pain.

To analyze the occurrence of early complications after total hip arthroplasty (THA) in patients with systemic lupus erythematosus (SLE).

ObjectiveTo find out whether there is any difference in the monitoring results of mosq-ovitraps placed in different orientations in multi-storey residential areas, so as to provide a scientific basis for routine and emergency monitoring of Aedes albopictus with mosq-ovitraps in residential areas. MethodsFrom July 6th to October 26th 2023, one mosquito ovitrap was set up in each of the 4 orientations of east, south, west and north around the buildings in a multi-storey residential area in Jinhui Town, Fengxian District, Shanghai. Data was collected and recorded 72 hours after placement. The chi-square test was used to compare the mosquito ovitrap indices (MOIs) of two independent samples, and the Kruskal⁃Wallis H test was used to compare the MOIs of multiple independent samples. ResultsAfter 16 weeks of surveillance, 997 mosquito ovitraps were recovered, of which 211 were positive, with the mosquito ovitrap index (MOI) of 21.16% and the Aedes albopictus density index of 1.03 mosquitoes·ovitrap^-1. The MOIs were higher in September (24.22%) and October (23.96%), and the MOIs in the west, south and north within the two months were all above 20.00%. From July to October, the MOIs in the east, west, south and north were 20.70%, 22.20%, 25.50% and 16.20%, respectively, and the difference in MOIs among the 4 orientations was not statistically significant (χ²=6.647, P=0.084). Stratified analysis by month showed that in August, the south side of the multi-storey residential areas had the highest MOI (31.30%), the north side had the lowest MOI (1.30%), and there was a statistically significant difference in MOI in the east, west, south and north (χ²=25.986, P<0.001). In October, the MOI in the west was the highest (33.30%) and the MOI in the east was the lowest (6.30%), the difference in MOIs of the 4 orientations was statistically significant (χ²=12.007, P=0.007). The MOIs in the south side of the building in the outskirts of the residential area from the 1st week in July to the 4th week in October was lower (19.20%) than that in the south side of the inner building (31.70%), and the difference in MOI was statistically significant (χ²=5.118, P=0.024). ConclusionThe study of MOI in different orientations in a multi-storey residential area is a preliminary exploration based on field work, and the results show that there is a difference in MOIs in different orientations during the peak breeding period of mosquitoes. Further indicators such as temperature, humidity and wind speed in different orientations can be collected to explore the influencing factors of MOIs.

The chemical constituents of sesquiterpenes from 95% ethanol extract of Aquilariae Lignum Resinatum were isolated and purified by various column chromatography techniques, including silica gel, Sephadex LH-20, octadecylsilyl(ODS), and semi-preparative high performance liquid chromatography(HPLC). Their planar structures and absolute configurations were elucidated by ultraviolet(UV) spectrometry, infrared(IR) spectroscopy, mass spectrometry(MS), nuclear magnetic resonance(NMR), electronic circular dichroism(ECD), and other techniques. Eight sesquiterpenoids were isolated and identified as(+)-(7R,10R)-selina-4,11-dien-12-dimethoxy-15-al(1),(+)-(7R,10R)-selina-4,11-diene-12,15-dial(2), agalleudesmanol B(3), aquisinenoid C(4), 12,15-dioxo-α-selinen(5), agarospiranic aldehyde B(6), neopetasane(7), and eremophila-7(11),9-dien-8-one(8). Compound 1 was a new compound, and it was the first time to find a dimethoxy substitution on the side chain of eudesmane-type sesquiterpene skeleton.
Sesquiterpenes/isolation & purification* ; Thymelaeaceae/chemistry* ; Molecular Structure ; Drugs, Chinese Herbal/isolation & purification* ; Magnetic Resonance Spectroscopy