OBJECTIVE To explore the improvine mechanism of Yifei xuanfei jiangzhuo formula （YFXF） on vascular dementia （VAD） model rats based on the growth factor receptor-bound protein 2 （GRB2）/extracellular signal-regulated kinase （ERK）/cardiolipin synthase 1 （CRLS1） pathway. METHODS VAD rat model was established by permanent bilateral common carotid artery ligation. Forty-eight successfully modeled rats were randomly divided into the model group （normal saline）， donepezil hydrochloride group （positive control group， 0.2 g/kg）， and YFXF low- and high-dose groups （12.18 and 24.36 g/kg， calculated based on the total amount of crude drug）， respectively. In addition， a sham operation group （normal saline） was set up. There were 12 rats in each group. Daily intragastric administration of drug or normal saline was performed for 30 consecutive days. After the last administration， the spatial cognitive ability of the rats was evaluated， the pathological morphology of the hippocampus was observed， the contents of tumor necrosis factor-α （TNF-α） and interleukin-4 （IL-4） in serum were detected， the expression levels of GRB2/ERK/CRLS1 pathway-related proteins and the mRNA levels of GRB2， CRLS1， NADH dehydrogenase subunit 1（ND1）， Tafazzin （TAZ）， phospholipid scramblase 3（PLSCR3） and the ATP content in hippocampal tissue were measured. RESULTS Compared with the sham operation group， the escape latency of rats in the model group was significantly prolonged （ P ＜0.05）， and the number of crossing platform was significantly reduced （ P ＜0.05）， while the number of pyramidal cells and Nissl bodies in the hippocampus decreased sharply； the content of TNF-α in serum was significantly increased （ P ＜0.05）， and the content of IL-4 was significantly decreased （ P ＜0.05）； the expression levels of GRB2 and CRLS1 proteins， the phosphorylation level of ERK protein， the relative expression levels of GRB2， CRLS1，ND1， TAZ， and PLSCR3 mRNA， and the content of ATP in hippocampal tissue were significantly decreased （ P ＜0.05）. Compared with the model group， the above pathological changes in the hippocampal tissue of each administration group were alleviated， and the quantitative indicators were significantly restored （ P ＜0.05）. CONCLUSIONS YFXF may improve hippocampal neuron injury in VAD rats by activating the GRB2/ERK/CRLS1 pathway, maintaining cardiolipin homeostasis， and improving mitochondrial energy metabolism.

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.

Rheumatoid arthritis （RA） is a chronic autoimmune disease characterized by synovitis as its pathological basis. Although current therapeutic drugs can alleviate symptoms， they are often accompanied by a high risk of side effects. In recent years， the use of flavonoids from traditional Chinese medicine （TCM） in the treatment of RA has garnered significant attention. Studies have shown that the mechanisms by which flavonoids treat RA include inhibiting the release of pro-inflammatory factors， regulating multiple cellular signaling pathways， alleviating oxidative stress， modulating immune system functions， inhibiting bone destruction， and suppressing angiogenesis. Due to their notable anti-inflammatory， antioxidant， and immunomodulatory activities， flavonoids hold promise as potential therapeutic agents for RA. A substantial number of articles in this field have been published. By reviewing Chinese and international literature and applying bibliometric and visual analysis using CiteSpace， this paper explored research hotspots and frontiers in this field， systematically reviewed the structures and anti-RA mechanisms of TCM flavonoids， provided a theoretical basis for their use in RA treatment and clinical applications， and offered new perspectives and references for the discovery of novel TCM-based anti-RA drugs.

Rheumatoid arthritis （RA） is a chronic autoimmune disease characterized by synovitis as its pathological basis. Although current therapeutic drugs can alleviate symptoms， they are often accompanied by a high risk of side effects. In recent years， the use of flavonoids from traditional Chinese medicine （TCM） in the treatment of RA has garnered significant attention. Studies have shown that the mechanisms by which flavonoids treat RA include inhibiting the release of pro-inflammatory factors， regulating multiple cellular signaling pathways， alleviating oxidative stress， modulating immune system functions， inhibiting bone destruction， and suppressing angiogenesis. Due to their notable anti-inflammatory， antioxidant， and immunomodulatory activities， flavonoids hold promise as potential therapeutic agents for RA. A substantial number of articles in this field have been published. By reviewing Chinese and international literature and applying bibliometric and visual analysis using CiteSpace， this paper explored research hotspots and frontiers in this field， systematically reviewed the structures and anti-RA mechanisms of TCM flavonoids， provided a theoretical basis for their use in RA treatment and clinical applications， and offered new perspectives and references for the discovery of novel TCM-based anti-RA drugs.

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 identify the independent predictors of programmed death-1 (PD-1) inhibitor-related endocrine adverse events and construct a clinically usable risk prediction model. Methods A total of 302 patients with solid tumors treated with PD-1 inhibitors were retrospectively enrolled. According to the presence or absence of endocrine immune-related adverse events (irAEs), the patients were divided into case group and control group. The clinical and laboratory indexes were compared between the two groups. Multivariable logistic regression was used to confirm independent predictors of endocrine irAEs. The nomogram was constructed, while the receiver operating characteristic (ROC) curve was used to test the prediction performance of the model. Results The overall incidence of endocrine irAEs was 21.9% (66/302), and the incidence of hypothyroidism was 19.5% (59/302). The age, PD-1 inhibitors, free thyroxine, thyroid peroxidase antibody (TPOAb), thyroglobulin, amylase, lymphocyte subset CD3 expression were statistically different between the two groups (P＜0.05). Multivariable logistic regression showed that higher expression of lymphocyte subset CD3 was a protective factor to prevent endocrine irAEs occurrence (P＝0.004), while age＜60 years, higher TPOAb and use of pembrolizumab were independent risk factors of endocrine irAEs (P＜0.05). The nomogram model thus constructed, and when the threshold probability of the model exceeded 0.1, its net benefit was higher. ROC curve showed that the AUC of the model to predict endocrine irAEs was 0.760. The prediction result of the model was highly consistent with the actual result. Conclusions The age, type of PD-1 inhibitor, baseline TPOAb level, and baseline CD3 expression can independently predict endocrine irAEs occurrence or not. The nomogram model based on this model has good predictive efficiency, which can provide reference for early identification of high-risk patients and immunotherapy management.

Objective: To investigate the effects of Zuogui Jiangtang Jieyu Formula (ZGJTJYF) on histone H3 lysine 18 lactylation (H3K18la) in the hippocampus of rats with diabetes mellitus complicated with depression (DD) and predict the regulatory genes of H3K18la. Methods: Male Sprague-Dawley rats were divided into control, model, and positive drug (metformin [0.18 g/kg] and fluoxetine [1.8 mg/kg]) groups, and the three groups were treated with high, medium, and low ZGJTJYF doses (20.52, 10.26, and 5.13 g/kg, respectively), with 10 rats per group. After treatment, the forced swimming and water maze tests were performed to assess depressive-like behaviors and cognitive function. An enzyme-linked immunosorbent assay was used to measure blood insulin, glycosylated hemoglobin, lactate levels, and lactate content in the hippocampus. Western blotting was used to detect H3K18la expression in the hippocampus. Cleavage Under Targets and lagmentation(CUT&Tag) experiments targeted hippocampal H3K18la epigenetic modification regions to analyze the transcription factors bound by H3K18la. Kyoto Encyclopedia of Genes and Genomes and Protein-Protein Interaction networks were constructed to identify key pathways and target genes regulated by H3K18la. Results: Compared with the normal group, the model group rats showed prolonged immobility time in the forced swim test, increased escape latency in the water maze experiment, decreased target quadrant distance ratio (P<0.01), increased serum lactate content, and decreased lactate content in hippocampal homogenate (P<0.01), as well as decreased H3K18la protein expression in the hippocampus (P<0.01). Compared with the model group, ZGJTJYF reduced the immobility time in the forced swim test and the escape latency in the water maze test (P<0.01), while the distance ratio in the target quadrant increased (P<0.01) in model rats. Lowered fasting blood glucose, insulin, and glycosylated hemoglobin levels (P<0.05, P<0.01) were also observed. ZGJTJYF also increased the lactate content and H3K18la protein expression in hippocampal homogenate (P<0.05, P<0.01). The DNA sequences bound by H3K18la were predominantly enriched at the transcription start sites. ZGJTJYF modulated H3K18la-associated pathways, including cell adhesion junctions, tumor growth factor-beta (TGF-β) signaling, stem cell pluripotency regulation, mitogen-activated protein kinase(MAPK) signaling pathway, and insulin resistance, leading to the identification of 12 target genes. Conclusion ZGJTJYF enhances hippocampal lactate levels and H3K18la modification in DD rats, which may regulate neural cell interactions, neurogenic stem cell function, TGF-β signaling, MAPK signaling, and insulin resistance pathways.

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*

PURPOSE: To compare the efficacy of continuous renal replacement therapy (CRRT) using either oXiris or conventional hemopurification filters in the treatment of intra-abdominal sepsis. METHODS: We conducted a retrospective analysis of septic patients with severe intra-abdominal infections admitted to our hospital from October 2019 to August 2023. Patients who meet the criteria for intra-abdominal sepsis based on medical history, symptoms, physical examination, and laboratory/imaging findings were included. EXCLUSION CRITERIA: pregnancy, terminal malignancy, prior CRRT before intensive care unit admission, pre-existing liver or renal failure. Heart rate (HR), mean arterial pressure, oxygenation index, lactic acid level (Lac), platelet count (PLT), neutrophil percentage, serum levels of procalcitonin, C-reactive protein, interleukin (IL)-6, norepinephrine dosage, acute physiology and chronic health evaluation II (APACHE II), and sequential organ failure assessment (SOFA) scores before and after 24 h and 72 h of treatment, as well as ventilator use time, hemopurification treatment time, intensive care unit and hospital lengths of stay, and 14-day and 28-day mortality were compared between patients receiving CRRT using either oXiris or conventional hemofiltration. Statistical analysis was performed using SPSS Statistics 26.0 software, including the construction of predictive models via logistic regression equations and repeated measures ANOVA. RESULTS: Baseline values including time to antibiotic administration, time to source control, and time to initiation of CRRT were similar between the 2 groups (all p>0.05). Patients receiving conventional CRRT exhibited significant changes in HR but of none of the other indexes at the 24 h and 72 h time points (p=0.041, p=0.026, respectively). The oXiris group showed significant improvements in HR, Lac, IL-6, and APACHE II score 24 h after treatment (p<0.05); after 72 h, all indexes were improved except PLT (all p<0.05). Intergroup comparison disclosed significant differences in HR, Lac, norepinephrine dose, APACHE II, SOFA, neutrophil percentage, and IL-6 after 24 h of treatment (p<0.05). Mean arterial pressure, serum levels of procalcitonin, C-reactive protein, SOFA score, and norepinephrine dosage were similar between the 2 groups at 24 h (p>0.05). Except for HR, oxygenation index, and PLT, post-treatment change rates of △ (%) were significantly greater in the oXiris group (p < 0.05). Duration of ventilator use, CRRT time, and intensive care unit and hospital lengths of stay were similar between the 2 groups (p>0.05). The 14-day mortality rates of the 2 groups were similar (p=0.091). After excluding patients whose CRRT was interrupted, 28-day mortality was significantly lower in the oXiris than in the conventional group (25.0% vs. 54.2%; p=0.050). The 28-day mortality rate increased by 9.6% for each additional hour required for source control and by 21.3% for each 1-point increase in APACHE II score. CONCLUSIONS In severe abdominal infections, the oXiris filter may have advantages over conventional CRRT, which may provide an alternative to clinical treatment. Meanwhile, early active infection source control may reduce the case mortality rate of patients with severe abdominal infections.
Humans ; Retrospective Studies ; Female ; Male ; Middle Aged ; Sepsis/mortality* ; Aged ; Adult ; Continuous Renal Replacement Therapy/methods* ; Intraabdominal Infections/mortality* ; APACHE ; Organ Dysfunction Scores ; Intensive Care Units ; Treatment Outcome