OBJECTIVE:Patients with osteoporotic vertebral compression fractures still have residual back pain after vertebral augmentation.The current research is characterized by limited sample size,complex confounding factors,and inconsistent research results.To gain a deeper understanding of this phenomenon,the aim of this study was to identify and evaluate the risk factors for residual back pain after surgery through a systematic review and meta-analysis.METHODS:A comprehensive search was conducted in CNKI,VIP,WanFang,CBMdisc,PubMed,The Cochrane Library,Embase,and Web of Science for case-control studies on residual back pain after vertebral body augmentation for osteoporotic vertebral compression fractures from database inception to July 2024.The search terms were a combination of subject terms and free terms.The basic information,patient characteristics,surgical-related indicators,and risk factors for surgical back pain of the included studies were extracted.After evaluating the bias risk of all included studies,a meta-analysis was conducted using Stata 14.0 software on the relevant indicators.RESULTS:(1)21 case-control studies with a total of 8 043 patients were included.Among them,965 patients developed back pain.The quality score of all 21 studies was ≥7.(2)The meta-analysis results showed that age(WMD=0.98,95％CI:0.40-1.56,P=0.010),bone mineral density(WMD=-0.28,95％CI:-0.34 to-0.21,P=0.000),the number of vertebral fractures(OR=3.50,95％CI:2.65-4.62,P=0.000),thoracolumbar fracture index(OR=3.65,95％CI:2.61-5.11,P=0.000),cement volume(OR=6.89,95％CI:2.62-18.17,P=0.000),and cement distribution(OR=2.38,95％CI:1.93-2.93,P=0.000)were risk factors for the development of back pain after vertebral body augmentation in patients with osteoporotic vertebral compression fractures.CONCLUSION:Current evidence indicates that age,bone mineral density,the number of vertebral fractures,thoracolumbar fracture index,bone cement injection volume,and the distribution of bone cement are risk factors for low back pain.Specifically,bone mineral density,the number of vertebral fractures,thoracolumbar fracture index,and non-uniform distribution of bone cement are identified as independent risk factors for low back pain.Patients exhibiting these high-risk factors require vigilant monitoring and prompt intervention to mitigate the occurrence of clinical low back pain,thereby enhancing patient outcomes and quality of life.

OBJECTIVE:Patients with osteoporotic vertebral compression fractures still have residual back pain after vertebral augmentation.The current research is characterized by limited sample size,complex confounding factors,and inconsistent research results.To gain a deeper understanding of this phenomenon,the aim of this study was to identify and evaluate the risk factors for residual back pain after surgery through a systematic review and meta-analysis.METHODS:A comprehensive search was conducted in CNKI,VIP,WanFang,CBMdisc,PubMed,The Cochrane Library,Embase,and Web of Science for case-control studies on residual back pain after vertebral body augmentation for osteoporotic vertebral compression fractures from database inception to July 2024.The search terms were a combination of subject terms and free terms.The basic information,patient characteristics,surgical-related indicators,and risk factors for surgical back pain of the included studies were extracted.After evaluating the bias risk of all included studies,a meta-analysis was conducted using Stata 14.0 software on the relevant indicators.RESULTS:(1)21 case-control studies with a total of 8 043 patients were included.Among them,965 patients developed back pain.The quality score of all 21 studies was ≥7.(2)The meta-analysis results showed that age(WMD=0.98,95％CI:0.40-1.56,P=0.010),bone mineral density(WMD=-0.28,95％CI:-0.34 to-0.21,P=0.000),the number of vertebral fractures(OR=3.50,95％CI:2.65-4.62,P=0.000),thoracolumbar fracture index(OR=3.65,95％CI:2.61-5.11,P=0.000),cement volume(OR=6.89,95％CI:2.62-18.17,P=0.000),and cement distribution(OR=2.38,95％CI:1.93-2.93,P=0.000)were risk factors for the development of back pain after vertebral body augmentation in patients with osteoporotic vertebral compression fractures.CONCLUSION:Current evidence indicates that age,bone mineral density,the number of vertebral fractures,thoracolumbar fracture index,bone cement injection volume,and the distribution of bone cement are risk factors for low back pain.Specifically,bone mineral density,the number of vertebral fractures,thoracolumbar fracture index,and non-uniform distribution of bone cement are identified as independent risk factors for low back pain.Patients exhibiting these high-risk factors require vigilant monitoring and prompt intervention to mitigate the occurrence of clinical low back pain,thereby enhancing patient outcomes and quality of life.

This paper aimed to investigate the therapeutic effect and mechanism of action of the Yiqi Fumai Formula(YQFM), a kind of traditional Chinese medicine(TCM), on mice with experimental heart failure based on the "heart-gut axis" theory. Based on the network pharmacology integrated with the group collaboration algorithm, the active ingredients were screened, a "component-target-disease" network was constructed, and the potential pathways regulated by the formula were predicted and analyzed. Next, the model of experimental heart failure was established by intraperitoneal injection of adriamycin at a single high dose(15 mg·kg~(-1)) in BALB/c mice. After intraperitoneal injection of YQFM(lyophilized) at 7.90, 15.80, and 31.55 mg·d~(-1) for 7 d, the protective effects of the formula on cardiac function were evaluated using indicators such as ultrasonic electrocardiography and myocardial injury markers. Combined with inflammatory factors in the cardiac and colorectal tissue, as well as targeted assays, the relevant indicators of potential pathways were verified. Meanwhile, 16S rDNA sequencing was performed on mouse fecal samples using the Illumina platform to detect changes in gut flora and analyze differential metabolic pathways. The results show that the administration of injectable YQFM(lyophilized) for 7 d significantly increased the left ventricular end-systolic internal diameter, fractional shortening, and ejection fraction of cardiac tissue of mice with experimental heart failure(P<0.05). Moreover, markers of myocardial injury were significantly decreased(P<0.05), indicating improved cardiac function, along with significantly suppressed inflammatory responses in cardiac and intestinal tissue(P<0.05). Additionally, the species of causative organisms was decreased, and the homeostasis of gut flora was improved, involving a modulatory effect on PI3K-Akt signaling pathway-related inflammation in cardiac and colorectal tissue. In conclusion, YQFM can affect the "heart-gut axis" immunity through the homeostasis of the gut flora, thereby exerting a therapeutic effect on heart failure. This finding provides a reference for the combination of TCM and western medicine to prevent and treat heart failure based on the "heart-gut axis" theory.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Heart Failure/microbiology* ; Mice ; Mice, Inbred BALB C ; Male ; Disease Models, Animal ; Gastrointestinal Microbiome/drug effects* ; Heart/physiopathology* ; Humans ; Signal Transduction/drug effects*

ObjectiveAutoimmune thyroiditis （AIT） is a complex and immune-mediated disorder， with no established treatment protocol. Both Western and traditional Chinese medicine （TCM） focus on the pathogenesis and treatment of AIT. This study evaluated the clinical consistency of existing AIT animal models based on the diagnostic criteria of both Western and TCM， using a novel evaluation method. Additionally， it proposed recommendations and future prospects for improving these models. MethodsA comprehensive literature review was conducted on existing AIT animal models， using databases and the diagnostic criteria of both Western and TCM. Core and accompanying symptoms of these models were scored based on the diagnostic criteria of both Western and TCM， and clinical consistency was assessed. ResultsMice are the primary experimental animals used in AIT modeling. Modeling methods include vaccine immunization， iodine induction， heterologous thyroid antigen immunization， and a combination of high iodine water and antigen immunization. The average consistency of clinical syndromes based on TCM and Western medicine is 40%， 60%， 54%， and 63%， with the highest consistency observed in the combined high iodine water and antigen immunization model. Pathological models based on TCM are less common， with the liver-stagnation-spleen-deficiency rat model showing high clinical consistency. While most models are designed according to Western medical theory， meeting the surface and structural effectiveness criteria of Western medicine. However， there is a lack of fine-tuning and clear differentiation of TCM syndromes. ConclusionCurrent AIT syndrome-disease combination animal models primarily reflect the pathological features of Western medicine， with limited integration of TCM syndromes. Future research should aim to combine the syndrome characteristics of TCM with the pathological features of Western medicine， creating multi-factor and dynamic syndrome-disease models. Such models would better facilitate an experimental platform that conforms to the theories of TCM， providing more comprehensive support and guidance for the pathogenesis and treatment strategies of AIT.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

OBJECTIVE: To explore the early clinical outcomes of 3D printed individualised customised prostheses for in hip revision in patients with combined severe bone defects. METHODS: Twenty-two patients from January 2021 to May 2023 underwent hip revision using 3D printed personalised customised prostheses were retrospective analyzed, including 10 males and 12 females, age 28 to 78 with a mean of (58.9±12.8) years old. All of patients were combined with severe bone defects (Parprosky type Ⅲ). Among of them, 9 patients had periprosthetic infections and 13 patients had aseptic prosthesis loosening. All patients were treated with a 3D printed personalised prosthesis protocol, patients with the periprosthetic infection received a second stage revision after infection control. The operation time, preoperative waiting time, intraoperative and postoperative complications were recorded, and the clinical efficacy were evaluated at the final follow-up using the visual analogue scale (VAS) for pain, the Harris hip score. RESULTS: One patient was lost to follow-up and the remaining 21 patients were followed up for 10 to 15 with a mean of (12.91±1.44) months after surgery. All patients completed surgery as planned, with an operative time of 135 to 390 with a mean of (165.4±39.3) minutes and a preoperative waiting time of 7 to 16 with a mean of (10.5±3.3) days. Regarding patient complications:one patient had a severe intraoperative periprosthetic femoral fracture due to the combination of severe osteoporosis; one patient had an intraoperative greater trochanteric femur fracture. At the latest follow-up, all patients had good position of the custom-made prosthesis and no loosening of the prosthesis;all patients had good wound healing and no local redness or swelling. The total Harris score at the final follow-up (85.86±7.04) was significantly improved compared to the preoperative (44.86±2.36), P<0.001. The VAS at the last follow-up (2.19±0.87) was significantly improved compared with preoperative (7.41±0.96), P<0.001. CONCLUSION The clinical efficacy of 3D-printed personalised customised prosthesis in combined severe bone defect hip revision is satisfactory, but due to the increased preoperative waiting time of the patients and certain risks, certain indications should be mastered when applying in the clinic.
Humans ; Male ; Female ; Printing, Three-Dimensional ; Middle Aged ; Aged ; Adult ; Retrospective Studies ; Hip Prosthesis ; Arthroplasty, Replacement, Hip ; Reoperation ; Prosthesis Design ; Treatment Outcome

OBJECTIVE: To reveal the molecular basis of knee osteoarthritis (KOA) with Yang deficiency and blood stasis syndrome by analyzing the gene expression profiles in synovial fluid and blood of KOA patients with this syndrome. METHODS: A total of 80 KOA patients were recruited from October 2022 to June 2024, including 40 cases in the non-Yang deficiency and blood stasis group (27 males and 13 females), with an average age of (61.75±3.45) years old;and 40 cases in the Yang deficiency and blood stasis group (22 males and 18 females), with an average age of (62.00±2.76) years old. The levels of body mass index (BMI), high-density lipoprotein (HDL), low-density lipoprotein (LDL), fibrinogen, total cholesterol, and D-dimer were recorded and summarized. Blood and synovial fluid samples from patients were collected for gene expression profile microarray sequencing, and then PCR and immunohistochemistry were used for clinical verification on the patients' synovial fluid and cartilage samples. RESULTS: Logistic regression analysis showed that compared with KOA patients with non-Yang deficiency and blood stasis syndrome, those with Yang deficiency and blood stasis syndrome had increased BMI, LDL, fibrinogen, total cholesterol, and D-dimer, and decreased HDL, with a clear correlation between the two groups. There were 562 differential genes in the blood, among which 322 were up-regulated and 240 were down-regulated;755 differential genes were found in the synovial fluid, with 350 up-regulated and 405 down-regulated. KEGG signaling pathway analysis of synovial fluid revealed changes in lipid metabolism-related pathways, including cholesterol metabolism, fatty acid metabolism, and PPARG signaling pathway. Analysis of the involved differential genes identified 6 genes in synovial fluid that were closely related to lipid metabolism, namely LRP1, LPL, ACOT6, TM6SF2, DGKK, and PPARG. Subsequently, PCR and immunohistochemical verification were performed using synovial fluid and cartilage samples, and the results were consistent with those of microarray sequencing. CONCLUSION This study explores the clinical and genomic correlation between traditional Chinese medicine syndromes and knee osteoarthritis from the perspective of lipid metabolism, and proves that abnormal lipid metabolism is closely related to KOA with Yang deficiency and blood stasis syndrome from both clinical and basic aspects.
Humans ; Male ; Female ; Middle Aged ; Synovial Fluid/metabolism* ; Osteoarthritis, Knee/metabolism* ; Yang Deficiency/complications* ; Aged

Erectile dysfunction (ED) is prevalent among men, but its relationship with dietary habits is uncertain. The aim of our study was to assess whether dietary patterns enhance erectile function by reviewing the literature published before August 1, 2022, via PubMed, Web of Science, and EMBASE databases. The data compiled included author details; publication dates, countries, treatments, patient numbers, ages, follow-ups, and clinical trial outcomes, such as ED cases, odds ratios (ORs), confidence intervals (CIs), and International Index of Erectile Function-5 (IIEF-5) scores with means and standard deviations. An analysis of 14 studies with 27 389 participants revealed that plant-based diets (OR = 0.71, 95% CI: 0.66-0.75; P < 0.00001), low-fat diets (OR = 0.27, 95% CI: 0.13-0.53; P = 0.0002), and alternative diets such as intermittent fasting and organic diets (OR = 0.54, 95% CI: 0.36-0.80; P = 0.002) significantly reduced ED risk. High-protein low-fat diets (hazard ratio [HR] = 1.38, 95% CI: 1.12-1.64; P < 0.00001) and high-carb low-fat diets (HR = 0.79, 95% CI: 0.55-1.04; P < 0.00001) improved IIEF-5 scores. Combined diet and exercise interventions decreased the likelihood of ED (OR = 0.49, 95% CI: 0.28-0.85; P = 0.01) and increased the IIEF-5 score (OR = 3.40, 95% CI: 1.69-5.11; P < 0.0001). Diets abundant in fruits and vegetables (OR = 0.97, 95% CI: 0.96-0.98; P < 0.00001) and nuts (OR = 0.54, 95% CI: 0.37-0.80; P = 0.002) were also correlated with lower ED risk. Our meta-analysis underscores a strong dietary-ED association, suggesting that low-fat/Mediterranean diets rich in produce and nuts could benefit ED management.
Humans ; Male ; Erectile Dysfunction/epidemiology* ; Diet ; Diet, Fat-Restricted ; Feeding Behavior ; Penile Erection/physiology* ; Diet, Vegetarian

A 12-year-old boy was admitted with symptoms of cough and fever lasting over a month, accompanied by weight loss 2 kg. Prior anti-infective treatments proved ineffective in alleviating the symptoms. Chest imaging revealed diffuse interstitial pulmonary edema in the right lung with obstructed lymphatic drainage. Combined with histopathological examinations, the diagnosis was confirmed as lung cancer with pulmonary lymphangitic carcinomatosis. The patient underwent chemotherapy with docetaxel and carboplatin, yet the disease progressively worsened, resulting in death three months after diagnosis. This case highlights lung cancer should not be overlooked in patients with persistent respiratory symptoms of unknown etiology. Early imaging examinations, along with necessary pathological evaluations, are crucial for timely detection and diagnosis. The presence of pulmonary lymphangitic carcinomatosis often indicates an advanced-stage of cancer, associated with a poor prognosis.
Humans ; Male ; Lung Neoplasms/complications* ; Child ; Carcinoma/drug therapy*

OBJECTIVES: To investigate the prognostic value of molecular minimal residual disease (Mol-MRD) monitored before and after allogeneic hematopoietic stem cell transplantation (HSCT) in pediatric acute myeloid leukemia (AML). METHODS: Clinical data of 71 pediatric AML patients who underwent HSCT between August 2016 and December 2023 were analyzed. Mol-MRD levels were dynamically monitored in MRD-positive patients, and survival outcomes were evaluated. RESULTS: No significant difference in the 3-year overall survival (OS) rate was observed between patients with pre-HSCT Mol-MRD ≥0.01% and <0.01% (77.3% ± 8.9% vs 80.4% ± 7.9%, P=0.705). However, patients with pre-HSCT Mol-MRD <1.75% had a significantly higher 3-year OS rate than those with Mol-MRD ≥1.75% (86.6% ± 5.6% vs 44.4% ± 16.6%, P=0.020). The median Mol-MRD level in long-term survivors was significantly lower than in non-survivors [0.61% (range: 0.04%-51.58%)] vs 10.60% (range: 1.90%-19.75%), P=0.035]. Concurrent flow cytometry-based MRD positivity was significantly higher in non-survivors (80% vs 24%, P=0.039). There was no significant difference in the 3-year overall survival rate between patients with Mol-MRD ≥0.01% and those with <0.01% at 30 days post-HSCT (P=0.527). For children with Mol-MRD <0.22% at 30 days post-HSCT, the 3-year overall survival rate was 80.4% ± 5.9%, showing no significant difference compared to those with molecular negativity (87.0% ± 7.0%) (P=0.523). CONCLUSIONS Patients with pre-HSCT Mol-MRD <1.75% or post-HSCT Mol-MRD <0.22% may achieve long-term survival outcomes comparable to Mol-MRD-negative cases through HSCT and targeted interventions.
Humans ; Hematopoietic Stem Cell Transplantation ; Neoplasm, Residual ; Leukemia, Myeloid, Acute/genetics* ; Child ; Male ; Female ; Child, Preschool ; Prognosis ; Adolescent ; Infant ; Transplantation, Homologous