1.Effects of Guilu Erxian Glue on gut microbiota in rats with knee osteoarthritis:machine learning and 16S rDNA analysis
Fucheng GU ; Meixin YANG ; Weixin WU ; Weijun CAI ; Yangyi QIN ; Mingyi SUN ; Jian SUN ; Qiudong GENG ; Nan LI
Chinese Journal of Tissue Engineering Research 2026;30(4):1058-1072
BACKGROUND:The Guilu Erxian Glue consists of Testudinis Plastrum,Cornu Cervi,Lycii Fructus,and Ginseng Radix.In earlier clinical observations,it is discovered that using Guilu Erxian Glue to treat patients with liver-kidney deficiency type knee osteoarthritis effectively alleviated knee pain,increased the range of motion,and improved walking ability.However,the exact mechanism by which oral administration of Guilu Erxian Glue can produce local therapeutic effects on the knee joint is still unclear.OBJECTIVE:To investigate the effects of Guilu Erxian Glue on gut microbiota in rats with knee osteoarthritis and to evaluate its mechanism using 16S rDNA sequencing and machine learning analysis.METHODS:Totally 18 female SD rats were randomly divided into three groups:blank group,model group,and Guilu Erxian Glue group,with 6 rats in each group.A knee osteoarthritis model was prepared using the destabilization of the medial meniscus surgical method.After successful modeling,the Guilu Erxian Glue group was given a decoction of Guilu Erxian Glue by gavage,while the blank and model groups were given an equal amount of distilled water.After 28 days of continuous intervention,high performance liquid chromatography was used to detect the active ingredients of Guilu Erxian Glue.MRI imaging was used to observe the condition of rat knee articular cartilage.Fecal samples were collected;DNA was extracted using a kit,amplified and purified by PCR,and an Illumina sequencing library was constructed.The Illumina MiSeq platform was used for high-throughput sequencing to generate raw sequence data.After obtaining the raw data,QIIME2 software was used to process the data.Linear Discriminant Analysis Effect Size analysis and random forest algorithm were used to screen for differential species in microbial data.KEGG and MetaCyc functional pathway analyses were used to explore the association between key microbial communities and experimental groups.Linear discriminant analysis effect values and random forest algorithm were used to screen for differential species.Association networks were used to analyze the interactions between microbial communities,and machine learning methods were used to analyze the composition and changes of gut microbiota.RESULTS AND CONCLUSION:(1)LC-MS component identification was conducted on the traditional Chinese medicine formula of Guilu Erxian Glue,and a total of 7 effective ingredients were identified.(2)MRI imaging showed that synovitis scope of high-density shadows in rats of the Guilu Erxian Glue group was reduced,and the degeneration of medial femoral condyle cartilage was less than that in the model group.(3)16S rDNA sequencing showed that the model group rats exhibited significant microbial imbalance,with a significant decrease in the abundance of Firmicutes and Bacteroidetes at the phylum level,while the proportion of Proteobacteria increased significantly(P<0.05).The gut microbiota structure of rats in the Guilu Erxian Glue group was significantly improved,and the proportion of Firmicutes and Bacteroidetes increased,restoring a more diverse microbiota composition,approaching that of the blank group(P<0.05).(4)KEGG and MetaCyc functional pathway analysis showed that the Guilu Erxian Glue group significantly activated multiple metabolic pathways,including amino acid metabolism,lipid metabolism,and biotin synthesis pathways(P<0.05).(5)The results indicate that Guilu Erxian Glue contains seven active ingredients,and the changes in gut microbiota of knee osteoarthritis rats were analyzed using 16S rDNA sequencing.Guilu Erxian Glue can significantly improve the imbalance of gut microbiota,restore the abundance of beneficial bacteria,and have a significant impact on the composition of gut microbiota,providing scientific basis for the efficacy and mechanism of Guilu Erxian Glue.
2.Analysis of diagnosis and treatment of Epstein-Barr virus-negative diffuse large B-cell lymphoma (GCB type) after kidney transplantation
Yan LI ; Xiaoyan ZHANG ; Xiang REN ; Tong XU ; Guohui WANG ; Ruochen QI ; Dongjuan WU ; Kepu LIU ; Weijun QIN ; Shuaijun MA
Organ Transplantation 2026;17(2):257-265
Objective To analyze the clinical and therapeutic characteristics of Epstein-Barr virus (EBV)-negative posttransplant lymphoproliferative disease (PTLD) with diffuse large B-cell lymphoma (DLBCL) in the context of specific cases and literature. Methods A case of EBV-negative DLBCL (GCB type) after kidney transplantation is reported. The patient was a 45-year-old male who underwent living-related kidney transplantation in 2016 and has been receiving triple immunosuppressive therapy with tacrolimus, mycophenolate mofetil and methylprednisolone since then. In 2024, the patient presented with intermittent fever, night sweats and gastrointestinal symptoms. The diagnosis was confirmed by endoscopic pathology, immunohistochemical staining and positron emission tomography/computed tomography. The R-CDOP regimen (rituximab + cyclophosphamide + liposomal doxorubicin + vincristine + dexamethasone) was used for treatment. Results The patient was diagnosed with EBV-negative DLBCL (GCB type, Ann Arbor stage Ⅳ B). After 4 cycles of R-CDOP chemotherapy, the efficacy assessment was partial remission, and the transplant kidney function remained stable. Conclusions For EBV-negative PTLD after kidney transplantation, it is necessary to break through the "virus-dependent" diagnostic thinking. In clinical practice, the focus should be on protecting the transplant kidney, and individualized treatment plans should be developed for patients.
3.Effects of Guilu Erxian Glue on gut microbiota in rats with knee osteoarthritis:machine learning and 16S rDNA analysis
Fucheng GU ; Meixin YANG ; Weixin WU ; Weijun CAI ; Yangyi QIN ; Mingyi SUN ; Jian SUN ; Qiudong GENG ; Nan LI
Chinese Journal of Tissue Engineering Research 2026;30(4):1058-1072
BACKGROUND:The Guilu Erxian Glue consists of Testudinis Plastrum,Cornu Cervi,Lycii Fructus,and Ginseng Radix.In earlier clinical observations,it is discovered that using Guilu Erxian Glue to treat patients with liver-kidney deficiency type knee osteoarthritis effectively alleviated knee pain,increased the range of motion,and improved walking ability.However,the exact mechanism by which oral administration of Guilu Erxian Glue can produce local therapeutic effects on the knee joint is still unclear.OBJECTIVE:To investigate the effects of Guilu Erxian Glue on gut microbiota in rats with knee osteoarthritis and to evaluate its mechanism using 16S rDNA sequencing and machine learning analysis.METHODS:Totally 18 female SD rats were randomly divided into three groups:blank group,model group,and Guilu Erxian Glue group,with 6 rats in each group.A knee osteoarthritis model was prepared using the destabilization of the medial meniscus surgical method.After successful modeling,the Guilu Erxian Glue group was given a decoction of Guilu Erxian Glue by gavage,while the blank and model groups were given an equal amount of distilled water.After 28 days of continuous intervention,high performance liquid chromatography was used to detect the active ingredients of Guilu Erxian Glue.MRI imaging was used to observe the condition of rat knee articular cartilage.Fecal samples were collected;DNA was extracted using a kit,amplified and purified by PCR,and an Illumina sequencing library was constructed.The Illumina MiSeq platform was used for high-throughput sequencing to generate raw sequence data.After obtaining the raw data,QIIME2 software was used to process the data.Linear Discriminant Analysis Effect Size analysis and random forest algorithm were used to screen for differential species in microbial data.KEGG and MetaCyc functional pathway analyses were used to explore the association between key microbial communities and experimental groups.Linear discriminant analysis effect values and random forest algorithm were used to screen for differential species.Association networks were used to analyze the interactions between microbial communities,and machine learning methods were used to analyze the composition and changes of gut microbiota.RESULTS AND CONCLUSION:(1)LC-MS component identification was conducted on the traditional Chinese medicine formula of Guilu Erxian Glue,and a total of 7 effective ingredients were identified.(2)MRI imaging showed that synovitis scope of high-density shadows in rats of the Guilu Erxian Glue group was reduced,and the degeneration of medial femoral condyle cartilage was less than that in the model group.(3)16S rDNA sequencing showed that the model group rats exhibited significant microbial imbalance,with a significant decrease in the abundance of Firmicutes and Bacteroidetes at the phylum level,while the proportion of Proteobacteria increased significantly(P<0.05).The gut microbiota structure of rats in the Guilu Erxian Glue group was significantly improved,and the proportion of Firmicutes and Bacteroidetes increased,restoring a more diverse microbiota composition,approaching that of the blank group(P<0.05).(4)KEGG and MetaCyc functional pathway analysis showed that the Guilu Erxian Glue group significantly activated multiple metabolic pathways,including amino acid metabolism,lipid metabolism,and biotin synthesis pathways(P<0.05).(5)The results indicate that Guilu Erxian Glue contains seven active ingredients,and the changes in gut microbiota of knee osteoarthritis rats were analyzed using 16S rDNA sequencing.Guilu Erxian Glue can significantly improve the imbalance of gut microbiota,restore the abundance of beneficial bacteria,and have a significant impact on the composition of gut microbiota,providing scientific basis for the efficacy and mechanism of Guilu Erxian Glue.
4.Mechanisms of Bushen Tongluo Jiangzhuo Prescription in Improving Renal Fibrosis in Rats with Chronic Kidney Disease Based on PI3K/Akt/mTOR Signaling Pathway
Xincui BAO ; Baosheng ZHAO ; Lingling QIN ; Haiyan WANG ; Jing YANG ; You WANG ; Lijia WU ; Yujin LI ; Ming GAO ; Cuiyan LYU ; Tonghua LIU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(6):100-108
ObjectiveTo investigate the mechanisms by which Bushen Tongluo Jiangzhuo prescription improves renal fibrosis in rats with chronic kidney disease (CKD) through the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR) signaling pathway. MethodsSeventy specific pathogen-free (SPF) Sprague-Dawley (SD) rats were randomly divided into a control group (n=15) and a modeling group (n=55). Rats in the modeling group were administered a 2.5% adenine suspension at a dose of 200 mg·kg-1·d-1 by gavage for 4 weeks to establish a CKD model. Successfully modeled rats were randomly divided into a model group, an irbesartan group (20.25 mg·kg-1·d-1), and Bushen Tongluo Jiangzhuo prescription low-, medium-, and high-dose groups (5.82, 11.64, and 23.28 g·kg-1·d-1, respectively), with 10 rats in each group. Each group was administered an equal volume of physiological saline, the corresponding concentration of irbesartan, or Bushen Tongluo Jiangzhuo prescription by gavage for 12 weeks. Body weight and renal function indices were dynamically monitored. Serum creatinine (SCr), blood urea nitrogen (BUN), urine albumin-to-creatinine ratio (ACR), 24-hour urinary total protein (24 hUTP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) levels were measured using an automatic biochemical analyzer. Renal histopathological changes were observed by hematoxylin-eosin (HE) and Masson staining. Immunohistochemistry (IHC) was used to detect the expression of PI3K, Akt, phosphorylated Akt (p-Akt), and mTOR in renal tissues. Western blot was performed to assess the protein expression of PI3K, p-Akt, Akt, phosphorylated mTOR (p-mTOR), and mTOR in renal tissues. Real-time quantitative polymerase chain reaction (Real-time PCR) was used to determine the mRNA expression levels of PI3K, Akt, and mTOR in renal tissues. ResultsCompared with the model group, rats in the irbesartan group and the low-, medium-, and high-dose Bushen Tongluo Jiangzhuo prescription groups showed significantly decreased levels of SCr, BUN, ACR, 24 hUTP, IL-1β, IL-6, and TNF-α (P<0.01). AST levels were significantly increased (P<0.01), while no significant difference was observed in ALT levels. Histopathological examination revealed that, compared with the model group, renal tubular epithelial cell edema and necrosis and Bowman's capsule dilation were alleviated, inflammatory cell infiltration was reduced, and interstitial and glomerular fibrosis was markedly improved in all treatment groups, with the most pronounced effect observed in the high-dose Bushen Tongluo Jiangzhuo prescription group. Real-time PCR results showed that mRNA expression levels of PI3K, Akt, and mTOR were significantly downregulated in the high-dose group (P<0.01). IHC results demonstrated that PI3K and p-Akt expression levels in renal tissues were significantly decreased in the high-dose group (P<0.01). Western blot analysis further confirmed that the expression levels of PI3K, p-Akt/Akt, and p-mTOR/mTOR were significantly reduced in the high-dose group (P<0.01). ConclusionBushen Tongluo Jiangzhuo prescription improves renal function indices in CKD rats, reduces collagen deposition in renal tissues, and decreases serum inflammatory factor levels. Its protective effect on renal function may be achieved by activating autophagy through downregulation of the PI3K/Akt/mTOR signaling pathway, thereby alleviating renal fibrosis.
5.Impact of birth weight on the trajectory of blood pressure among primary school students
CUI Chengpeng, YE Siyan, FANG Yanfei, LI Yan, PENG Zeqin, XIAO Yuqing, WU Meng, LIU Qin
Chinese Journal of School Health 2026;47(3):309-313
Objective:
To explore the early effects of birth weight at different gestational ages on blood pressure trajectory among primary school students, so as to provide evidence for incorporating gestational age birth weight into individualized early warning and intervention strategies for childhood hypertension.
Methods:
From May to November 2023, a purposeful sampling method was used to recruit 1 676 students in grade 1-3 from three primary schools in a certain urban district of Chongqing. Follow up assessments were conducted in May 2024(T1), November 2024(T2), and May 2025(T3). General demographic and birth related information were collected via self administered questionnaires, while height, weight and blood pressure were obtained through physical examinations. Linear mixed effects model was used to analyze the associations between birth weight at different gestational ages and blood pressure trajectories.
Results:
During the T1-T3 period, the systolic blood pressure of boys were 98.5 (93.0, 104.5 ),98.5 (93.5, 105.0), and 97.5 (92.5, 103.5)mmHg, respectively, while the diastolic blood pressure were 60.5 (56.5, 65.0), 61.5 ( 57.0 , 65.5), and 60.0 (56.0, 64.0)mmHg, respectively. For girls, the systolic blood pressure were 95.5 (90.0, 102.0),95.5 (90.5, 101.5), and 96.0 (90.5, 101.5)mmHg, respectively, and the diastolic blood pressure were 60.5 (56.0, 64.5 ),61.5 (57.5, 65.5), and 59.5 (56.0, 63.0)mmHg, respectively. Through Friedman test within both boys and girls, diostolic blood pressure were statistically significant across three measurements( χ 2=48.85,81.54,both P <0.01). The proportion of normal blood pressure increased , and the proportion of prehypertension and hypertension decreased with time( χ 2=39.72,25.62,both P < 0.01 ). Linear mixed effects model analysis revealed that after adjusting for age, sex, household income monthly, parental education, family history of hypertension and maternal pregnancy complications, large for gestational age had significantly higher trajectories of systolic ( β = 1.50) and diastolic( β =0.94) blood pressure compared to appropriate for gestational age(both P <0.01).
Conclusion
Large for gestational age is associated with elevated blood pressure trajectories during school age, and it may be considered as an early indicator for individualized screening and intervention for childhood hypertension.
6.Research Progress of Traditional Chinese Medicine in Improving Diabetic Retinopathy Based on Nrf2 Signaling Pathway
Xueqing LIU ; Xinyu ZHONG ; Tingting WANG ; Ning WANG ; Man LIU ; Li WU ; Lili WU ; Lingling QIN ; Tonghua LIU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(9):69-78
Diabetic retinopathy (DR) is a microvascular complication of diabetes and one of its most common complications. Prolonged hyperglycemia induces oxidative stress, inflammatory responses, apoptosis, and pathological angiogenesis, ultimately disrupting the blood-retinal barrier(BRB) and leading to visual impairment or even blindness. Recent studies show that the nuclear factor erythroid 2-related factor 2 (Nrf2) signaling pathway plays an important role in the development of DR's pathological changes. Meanwhile, Chinese herbal monomers have been shown to modulate the Nrf2 signaling pathway, thereby intervening in the development of DR. In terms of inhibiting oxidative stress, saponin compounds such as platycodin-D and ginsenoside Rb1 downregulate the expression of malondialdehyde (MDA), thereby ameliorating retinal oxidative stress. Flavonoids such as total flavonoids from Pueraria lobata flower and puerarin upregulate the expression of superoxide dismutase (SOD) and glutathione peroxidase (GPx), effectively clearing lipid peroxides. Regarding the suppression of inflammation, phenolic compounds like resveratrol and chlorogenic acid inhibit the nuclear factor kappa B (NF-κB) pathway, reducing the release of tumor necrosis factor-alpha (TNF-α) and mitigating inflammatory responses. In the context of inhibiting apoptosis, polysaccharides such as Polygonatum sibiricum polysaccharide and Angelica sinensis polysaccharide downregulate the expression of the pro-apoptotic protein Bcl-2-associated X protein (Bax) and suppress the activity of the executioner Caspase-3, thereby reducing the apoptosis rate. As for the inhibition of neovascularization, compounds including bilobalide and physcion significantly decrease the protein expression of vascular endothelial growth factor (VEGF), leading to a reduction in retinal pathological angiogenesis. Furthermore, Chinese herbal compound prescriptions such as Tongluo Zhujing pills, Yiqi Huoxue Yangyin decoction, Qiming granules, and Danlou tablets can also intervene in the onset and progression of DR through the mechanisms described above. In summary, both Chinese herbal monomers and Chinese herbal compound prescriptions can modulate the Nrf2 signaling pathway to inhibit oxidative stress, alleviate inflammation, and participate in maintaining BRB integrity, suppressing retinal neovascularization, and preventing neurodegeneration, thereby delaying the progression of DR. Therefore, this paper reviews and summarizes recent studies at home and abroad on how traditional Chinese medicine (TCM) works to treat DR, and the relationship between the Nrf2 pathway and DR. It aims to provide research ideas for preventing and treating DR.
7.A Computational Perspective on Differences Between MHC-I and MHC-II in TCR-pMHC Structure Prediction Resources: Review and Benchmarking
Xiao-Qin WU ; Da-Wei LIU ; Bin-Yu LI ; Yang LIU ; Yang CAO ; Wen-Tao DAI
Progress in Biochemistry and Biophysics 2026;53(5):1376-1399
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.
8.A Computational Perspective on Differences Between MHC-I and MHC-II in TCR-pMHC Structure Prediction Resources: Review and Benchmarking
Xiao-Qin WU ; Da-Wei LIU ; Bin-Yu LI ; Yang LIU ; Yang CAO ; Wen-Tao DAI
Progress in Biochemistry and Biophysics 2026;53(5):1376-1399
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.
9.Evaluation of CARIFS Score and Negative Antigen Conversion Rate of Qingxuan Daozhi Formula in Treatment of Influenza in Children (Heat Accumulation in Lung and Stomach Syndrome):A Multi-center Randomized Controlled Clinical Study
Jing WANG ; Liqun WU ; Tiegang LIU ; Yongning CAO ; Jing QIU ; Jing LI ; Huaqing TAN ; Ying ZHANG ; Xulei GOU ; Jia WANG ; Jing LI ; Haipeng CHEN ; Xueying QIN ; Yuanshuo TIAN ; Yang WANG ; Chen BAI ; Zhendong WANG ; Qianqian LI ; He YU ; Xueyan MA ; Fei DONG ; Lin JIANG ; Yingqi XU ; Jianping LIU ; Xiaohong GU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(13):188-196
ObjectiveThis paper aims to observe the syndrome improvement and negative antigen conversion rate of Qingxuan Daozhi formula in the treatment of influenza in children (heat accumulation in the lung and stomach syndrome). MethodsThrough a multi-center randomized controlled methodology design,confirmed influenza cases were collected from October 2022 to April 2023 in the pediatrics department of eight hospitals,such as Dongfang Hospital of Beijing University of Chinese Medicine. A total of 180 children with influenza and heat accumulation in the lung and stomach syndrome conforming to the standard were recruited through the clinic. The sick children meeting the inclusion criteria were randomly divided into groups by a block-randomized method. The children in the experimental group were treated with Qingxuan Daozhi formula for five days,and those in the control group were treated with Oseltamivir Phosphate Granules for five days. The primary efficacy indicator was the negative conversion rate of influenza antigen detection. Secondary efficacy indicators were the Canadian acute respiratory illness and flu scale (CARIFS) and the incidence of complications,severe cases, and critical cases. Follow-up observation was conducted on the day of enrollment,48 hours after medication,72 hours after medication, and (6+1) d after medication. ResultsOne hundred and eighty participants were randomly assigned to the experimental group (90 cases) or the control group (90 cases). All participants were followed up during the study. Comparison of influenza antigen detection results in the primary efficacy indicators showed that the average time of negative influenza antigen conversion in the experimental group was (5.29±1.25) d,and that in the control group was (5.40±1.68) d,without a statistically significant difference. After five days of intervention,52 cases in the experimental group and 51 cases in the control group converted to negative,without a statistically significant difference. CARIFS score results in the secondary efficacy indicators showed that during 72 hours after intervention,there were statistically significant differences between the experimental group and the control group in three dimensions, including headache,muscle soreness, and the need for extra care (P<0.05). On the (6+1) days after the intervention,the differences in both the experimental group and the control group were statistically significant in 10 dimensions, including sore throat,bad sleep,uncomfortable feeling,poor spirit and fatigue,crying more than usual,the need for extra care,symptom,function,influence on parents,and total score (P<0.05). The comparison results within the group in the dimensional scores of symptom, function, and influence on parents,as well as the CARIFS total score showed that with the delay of follow-up time,scores of both groups decreased significantly,with a statistically significant difference (P<0.01). Inter-group comparison results showed that the mean score of the experimental group was higher than that of the control group at the time of enrollment. With the progress of intervention,the score of the experimental group was significantly decreased compared with that of the control group. At the end of follow-up,the mean score of the experimental group was lower than that of the control group,with no statistically significant difference. In terms of the incidence of complications,severe cases, and critical cases, there were no complications,severe cases, and critical cases in the two groups,without a statistically significant difference. ConclusionThe symptom improvement effect and negative antigen conversion rate of Qingxuan Daozhi formula in the treatment of influenza in children (heat accumulation in the lung and stomach syndrome) are not inferior to Oseltamivir Phosphate granules, and children's acceptance is better. It can be more widely used in clinical treatment of influenza in children (heat accumulation in the lung and stomach syndrome).
10.Progress of researches on Triatoma rubrofasciata-transmitted trypanosomes
Ziyi WANG ; Yong SHEN ; Lirong HUANG ; Yuanyuan LI ; Di WU ; Qin LIU
Chinese Journal of Schistosomiasis Control 2026;38(2):213-218
Triatoma rubrofasciata is currently the most widely distributed species of Triatoma worldwide, and it is also widespread in southern China. T. rubrofasciata has been proven to transmit Trypanosoma cruzi, and is one of vectors transmitting Chagas disease, which poses a potential risk for transmission of imported Chagas disease in China. Findings from latest studies have shown that T. rubrofasciata naturally infects T. lewisi, T. conorhini, and T. rangeli, which undoubtedly increases significant risks of and challenges to trypanosomiasis control in China. This article briefly describes the species of T. rubrofasciata-transmitted trypanosomes, and summarizes the epidemiological characteristics of trypanosomiasis, so as to provide insights into T. rubrofasciata-transmitted trypanosomiasis surveillance and control, and prevention of trypanosomiasis development and transmission in China.


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