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.

OBJECTIVES: To summarize the clinical characteristics, diagnosis, and treatment outcomes of neonatal venous thrombosis. METHODS: A retrospective analysis was conducted on the clinical data of 11 neonates with venous thrombosis admitted to the Department of Neonatology of Anhui Children's Hospital from January 2019 to September 2024. The clinical characteristics, diagnostic approaches, treatments, and outcomes were analyzed. RESULTS: Among the 11 neonates diagnosed with venous thrombosis, 5 were male, and 6 were preterm infants, with a median gestational age of 35⁺⁶ weeks, birth weight of (2 322±1 069) g, and admission temperature of (36.6±0.4)°C. The median age at symptom onset was 6 days. Of the 11 cases, 8 limb venous thromboses and 1 portal vein thrombosis were confirmed by vascular ultrasound, and 2 cases of intracranial venous sinus thrombosis were confirmed by magnetic resonance imaging. Ten cases received low molecular weight heparin for anticoagulation, with a treatment duration of (24±15) days; 2 cases were treated with urokinase thrombolysis, and 4 cases received fresh frozen plasma transfusion. Thrombosis resolved in 7 cases before discharge. Partial resolution occurred in 2 cases before discharge (1 continued outpatient treatment until resolution and 1 resolved during follow-up). One case was transferred to another hospital after 1 day of treatment and was discharged after thrombosis reduction. No adverse reactions such as bleeding were observed. One neonate with cerebral infarction at admission did not receive heparin anticoagulation and was followed up as an outpatient. CONCLUSIONS Vascular ultrasound is the most commonly used diagnostic method for neonatal venous thrombosis. Heparin anticoagulation is the recommended treatment. The overall prognosis of neonatal venous thrombosis is favorable.
Humans ; Male ; Venous Thrombosis/drug therapy* ; Infant, Newborn ; Female ; Retrospective Studies

ObjectiveTraditional Chinese medicine (TCM) constitutes a valuable cultural heritage and an important source of antitumor compounds. Poria (Poria cocos (Schw.) Wolf), the dried sclerotium of a polyporaceae fungus, was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia. Traditionally recognized for its diuretic, spleen-tonifying, and sedative properties, modern pharmacological studies confirm that Poria exhibits antioxidant, anti-inflammatory, antibacterial, and antitumor activities. Pachymic acid (PA; a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid), isolated from Poria, is a principal bioactive constituent. Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms, though these remain incompletely characterized. Neuroblastoma (NB), a highly malignant pediatric extracranial solid tumor accounting for 15% of childhood cancer deaths, urgently requires safer therapeutics due to the limitations of current treatments. Although PA shows multi-mechanistic antitumor potential, its efficacy against NB remains uncharacterized. This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking, dynamic simulations, and in vitro assays, aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays. MethodsThis study employed network pharmacology to identify potential targets of PA in NB, followed by validation using molecular docking, molecular dynamics (MD) simulations, MM/PBSA free energy analysis, RT-qPCR and Western blot experiments. Network pharmacology analysis included target screening via TCMSP, GeneCards, DisGeNET, SwissTargetPrediction, SuperPred, and PharmMapper. Subsequently, potential targets were predicted by intersecting the results from these databases via Venn analysis. Following target prediction, topological analysis was performed to identify key targets using Cytoscape software. Molecular docking was conducted using AutoDock Vina, with the binding pocket defined based on crystal structures. MD simulations were performed for 100 ns using GROMACS, and RMSD, RMSF, SASA, and hydrogen bonding dynamics were analyzed. MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex. In vitro validation included RT-qPCR and Western blot, with GAPDH used as an internal control. ResultsThe CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability. GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress, vesicle lumen, and protein tyrosine kinase activity. KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT, MAPK, and Ras signaling pathways. Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1, EGFR, SRC, and HSP90AA1. RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1, EGFR, and SRC while increasing the HSP90AA1 mRNA and protein levels. ConclusionIt was suggested that PA may exert its anti-NB effects by inhibiting AKT1, EGFR, and SRC expression, potentially modulating the PI3K/AKT signaling pathway. These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.

This study aims to explore the mechanism of Jiaotai Pills in treating depression based on metabolomics and network pharmacology. The chemical constituents of Jiaotai Pills were identified by UHPLC-Orbitrap Exploris 480, and the targets of Jiaotai Pills and depression were retrieved from online databases. STRING and Cytoscape 3.7.2 were used to construct the protein-protein interaction network of core targets of Jiaotai Pills in treating depression and the "compound-target-pathway" network. DAVID was used for Gene Ontology(GO) function and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses of the core targets. The mouse model of depression was established with chronic unpredictable mild stress(CUMS) and treated with different doses of Jiaotai Pills. The behavioral changes and pathological changes in the hippocampus were observed. UHPLC-Orbitrap Exploris 120 was used for metabolic profiling of the serum, from which the differential metabolites and related metabolic pathways were screened. A "metabolite-reaction-enzyme-gene" network was constructed for the integrated analysis of metabolomics and network pharmacology. A total of 34 chemical components of Jiaotai Pills were identified, and 143 core targets of Jiaotai Pills in treating depression were predicted, which were mainly involved in the arginine and proline, sphingolipid, and neurotrophin metabolism signaling pathways. The results of animal experiments showed that Jiaotai Pills alleviated the depression behaviors and pathological changes in the hippocampus of the mouse model of CUMS-induced depression. In addition, Jiaotai Pills reversed the levels of 32 metabolites involved in various pathways such as arginine and proline metabolism, sphingolipid metabolism, and porphyrin metabolism in the serum of model mice. The integrated analysis showed that arginine and proline metabolism, cysteine and methionine metabolism, and porphyrin metabolism might be the key pathways in the treatment of depression with Jiaotai Pills. In conclusion, metabolomics combined with network pharmacology clarifies the antidepressant mechanism of Jiaotai Pills, which may provide a basis for the clinical application of Jiaotai Pills in treating depression.
Animals ; Drugs, Chinese Herbal/chemistry* ; Depression/genetics* ; Mice ; Network Pharmacology ; Metabolomics ; Male ; Disease Models, Animal ; Humans ; Protein Interaction Maps/drug effects* ; Antidepressive Agents

OBJECTIVE: To investigate the accuracy and safety of pedicle screw placement using 3D-printed auxiliary guides in scoliosis correction surgery for adolescents. METHODS: A retrospective analysis was conducted on the clinical data of 51 patients who underwent posterior scoliosis correction surgery from January 2020 to March 2023. Among them, there were 35 cases of adolescent idiopathic scoliosis and 16 cases of congenital scoliosis. The patients were divided into two groups based on the auxiliary tool used:the 3D-printed auxiliary guide screw placement group (3D printing group) and the free-hand screw placement group (free-hand group, without auxiliary tools). The 3D printing group included 32 patients (12 males and 20 females) with an average age of (12.59±2.60) years;the free-hand group included 19 patients (7 males and 12 females) with an average age of (14.58±3.53) years. The two groups were compared in terms of screw placement accuracy and safety, spinal correction rate, intraoperative blood loss, number of intraoperative fluoroscopies, operation time, hospital stay, and preoperative and last follow-up scores of the Scoliosis Research Society-22 (SRS-22) questionnaire. RESULTS: A total of 707 pedicle screws were placed in the two groups, with 441 screws in the 3D printing group and 266 screws in the free-hand group. All patients in both groups successfully completed the surgery. There was a statistically significant difference in operation time between the two groups (P<0.05). The screw placement accuracy rate of the 3D printing group was 95.46% (421/441), among which the Grade A placement rate was 89.34% (394/441);the screw placement accuracy rate of the free-hand group was 86.47% (230/266), with a Grade A placement rate of 73.31% (195/266). There were statistically significant differences in the accuracy of Grade A, B, and C screw placements between the two groups (P<0.05), while no statistically significant differences were observed in intraoperative blood loss, number of fluoroscopies, correction rate, or hospital stay (P>0.05). In the SRS-22 questionnaire scores, the scores of functional status and activity ability, self-image, mental status, and pain of patients in each group at the last follow-up were significantly improved compared with those before surgery (P<0.05), but there were no statistically significant differences in all scores between the two groups (P>0.05). CONCLUSION In scoliosis correction surgery, compared with traditional free-hand screw placement, the use of 3D-printed auxiliary guides for screw placement significantly improves the accuracy and safety of screw placement and shortens the operation time.
Humans ; Male ; Scoliosis/surgery* ; Female ; Adolescent ; Printing, Three-Dimensional ; Retrospective Studies ; Pedicle Screws ; Child

Various techniques have been described for reconstructing the skin of the penile shaft; however, no universally accepted standard exists for correcting buried penis in adults. We aimed to describe a new technique for correcting an adult-acquired buried penis through a diamond-shaped incision at the penopubic junction. We retrospectively analyzed data from patients treated with our technique between March 2019 and June 2023 in the Department of Andrology, Nanjing Drum Tower Hospital (Nanjing, China). Forty-two adult males with buried penises, with a mean (±standard deviation [s.d.]) age of 26.6 (±6.6) years, underwent surgery. All patients were obese, with an average (±s.d.) body mass index of 35.56 (±3.23) kg m -2 . In addition to phalloplasty, 32 patients concurrently underwent circumcision, and 28 underwent suprapubic liposuction. The mean (±s.d.) duration of the operation was 98.02 (±13.28) min. The mean (±s.d.) duration of follow-up was 6.71 (±3.43) months. The length in the flaccid unstretched state postoperatively was significantly greater than that preoperatively (mean ± s.d: 5.55±1.19 cm vs 1.94±0.59 cm, P < 0.01). Only minor complications, such as wound disruption (7.1%) and infection (4.8%), were observed. The mean (±s.d.) score of patient satisfaction was 4.02 (±0.84) on a scale of 5. This technique provides excellent cosmetic and functional outcomes with a minimal risk of complications. However, additional clinical studies are needed to evaluate the long-term effects of this procedure.
Humans ; Male ; Patient Satisfaction ; Adult ; Lipectomy/methods* ; Penis/surgery* ; Retrospective Studies ; Treatment Outcome ; Plastic Surgery Procedures/methods* ; Young Adult ; Penile Diseases/surgery* ; Urologic Surgical Procedures, Male/methods*

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

Objective:To investigate effect and mechanism of hydroxysafflor yellow A(HSYA)activating neuronal autophagy on cerebral ischemia-reperfusion injury through a combination of in vitro and in vivo experiments.Methods:SD rat MCAO/R model was established by improved suture method.Rats were randomly divided into sham surgery(Sham)group,MCAO/R group and MCAO/R+HSYA group,following indicators were detected to determine extent of cerebral ischemia-reperfusion nerve damage:Z-Longa neu-rological function score was detected,TTC staining to measure cerebral infarction area,and TUNEL staining to measure cell apopto-sis;Western blot was used to detect protein expressions of autophagy related markers LC3,Beclin1,P62 and SIRT1 in rat brain tis-sue;immunofluorescence staining was used to observe expression of LC3 co-localization with neurons.OGD/R injury model of SH-SY5Y cells was established and randomly divided into Normal group,OGD/R group,OGD/R+HSYA group,OGD/R+SIRT1 inhibitor(EX-527)group and OGD/R+EX-527+HSYA group.Western blot was used to detect protein expressions of LC3,Beclin1,P62 and SIRT1.Results:Compared with Sham group,model group rats showed impaired neurological function,significantly increased neu-robehavioral scores,widespread cerebral infarction,significantly increased neuronal cell apoptosis,significantly increased autophagy related protein Beclin1 expression and LC3-Ⅱ/LC3-Ⅰ,significantly decreased P62 expression,significantly increased LC3/NeuN co-stained cells,and decreased SIRT1 expression;compared with model group,HSYA intervention group showed a significant decrease in neurological functional scores,a significant reduction in cerebral infarction area,a significant decrease in neuronal cell apoptosis,a further increase in Beclin1 expression and LC3-Ⅱ/LC3-Ⅰ,a further decrease in P62 expression,number of LC3/NeuN and P62/NeuN co-stained cells also increased,and SIRT1 expression significantly increased.Expression trends of Beclin1,LC3-Ⅱ/LC3-Ⅰ,P62 and SIRT1 of cells between normal group,model group and HSYA intervention group were same as animal experiment;compared with model group,expressions of SIRT1,Beclin1 and LC3-Ⅱ/LC3-Ⅰ in OGD/R+EX-527 group were significantly reduced,while expression of P62 was significantly increased;compared with OGD/R+EX-527 group,there was no significant change in SIRT1 expression in OGD/R+EX-527+HSYA group,LC3-Ⅱ/LC3-Ⅰ and Beclin1 expression were significantly increased,and P62 expres-sion was significantly decreased.Conclusion:HSYA can significantly improve neurological deficits in rats after cerebral ischemia-reperfusion,reduce cerebral infarction area,and decrease neuronal cell apoptosis rate,whose neuroprotective effect may be related to its activation of SIRT1,which significantly enhances neuronal autophagy.

Objective:To explore the effect of kidney-strengthening and blood stasis-eliminating formula on nutritional status and quality of life in patients with osteoporosis combined with hemodialysis.Methods:From January 2024 to January 2025,60 patients with liver and kidney yin deficiency and blood stasis obstruction were selected from the Pizhou City Traditional Chinese Medicine Hospital's Hemodialysis Center.60 patients were randomly divided into two groups,30 in each group.The matched group received general treatment plus paricalcitol,while the treatment group received the same treatment plus Yishen Zhuyu Fang(a traditional Chinese medicine formula for kidney and blood stasis).The treatment course lasted 12 weeks.Changes in TCM syndrome scores,the Modified Subjective Global Assessment(MQSGA),the Kidney and Life Quality(KDQOLTM-36)scale,lipid levels,and nutritional indicators were compared before and after treatment.Results:After treatment,the TCM syndrome scores in both groups decreased(P＜0.05),with a more pronounced decrease in the treatment group(P＜0.05).The KDQOLTM-36 score in the treatment group increased(P＜0.05),while the increase was not significant in the matched group(P＞0.05),indicating that the treatment group performed better than the matched group(P＜0.05).Both groups experienced a decrease in the MQSGA score(P＜0.05),although the difference was not statistically significant(P＞0.05),the treatment group showed a more noticeable decline.The TC,TG,LDL,and TG/HDL levels in the treatment group all decreased significantly,while HDL levels increased(P＜0.05).In contrast,the TC and HDL levels in the matched group did not change(P＞0.05),while the TG,LDL,and TG/HDL levels increased(P＜0.05).The treatment group performed significantly better than the matched group(P＜0.05).The TRF,Hb,and ALB levels in the treatment group increased(P＜0.05),while the increase was not significant in the matched group(P＞0.05).The total effective rate of the treatment group was 90％,higher than the matched group(23.3％)(P＜0.05).Conclusion:The formula of tonifying the kidney and removing stasis can improve the nutritional status and quality of life of patients with liver and kidney yin deficiency and blood stasis obstruction in hemodialysis combined with osteoporosis.