OBJECTIVE: To investigate the characteristics of Vitamin D (VitD) and bone metabolism in patients with knee osteoarthritis (KOA) concurrent with osteoporosis (OP). METHODS: A retrospective analysis was performed on 240 patients who were admitted to the orthopedics department between March 2019 and March 2024. Patients were stratified into four distinct groups according to their respective disease categories.There were 90 patients in the simple KOA group, comprising 13 males and 77 females, age ranged from 50 to 91 years old with an average of (68.48±8.96) years old. There were 90 patients in the simple OP group, comprising 7 males and 83 females, age ranged from 52 to 88 years old with an average of (69.60±8.94 )years old. There were 30 patients in the KOA with OP group, comprising 1 male and 29 females, age ranged from 51 to 91 years old with an average of(69.03±7.93) years old. There were 30 patients in the physical examination group, comprising 5 males and 25 females, age ranged from 53 to 79 years old with an average of(64.93±6.51) years old. The general data and the levels of osteocalcin (OC), β-CrossLaps, parathyroid hormone(PTH) and VitD in each group were observed. RESULTS: The level of VitD in KOA with OP group (19.62±10.38) ng·ml^-1 and OP group (20.65±10.50) ng·ml^-1 was lower than that in physical examination group (27.46±8.00) ng·ml^-1 and KOA group (24.01±9.11) ng·ml^-1 (P<0.05). There were significant differences in β- CrossLaps and PTH levels among the four groups (P<0.001, P=0.019, respectively), while there was no significant difference in OC levels (P=0.763). Compared with the two simple disease groups, the KOA with OP group had higher levels of β - CrossLaps(0.81±0.30) ng·ml^-1 (P<0.001). There were significant differences in β-CrossLaps and PTH between the simple KOA group(0.54±0.22) ng·ml^-1, (46.03±18.08) pg·ml^-1 and the physical examination group (0.44±0.19) ng·ml^-1, (36.65±9.63) pg·mL^-1(P=0.038;P=0.006). There was a significant difference in PTH between the OP group(43.85±14.30) ng·ml-1, and the physical examination group, P=0.004. There was a significant difference in Kallgren-Lawrence grading between KOA with OP group and KOA group (P=0.006). Within KOA with OP group, the differences of β-CrossLaps and VitD levels among different K-L grades were statistically significant (P=0.016). The level of OC, β-CrossLaps and PTH within KOA with OP group was significantly different at different VitD levels (P=0.013, P=0.033, P=0.046). CONCLUSION Patients with KOA complicated by OP exhibit greater disturbances in bone metabolism and reduced VitD levels, particularly reflected by elevated β-CrossLaps. These findings underscore the importance of early monitoring of bone turnover and VitD supplementation in advanced-stage KOA with bone loss.
Humans ; Female ; Male ; Middle Aged ; Aged ; Vitamin D/blood* ; Osteoporosis/complications* ; Aged, 80 and over ; Osteoarthritis, Knee/complications* ; Retrospective Studies ; Bone and Bones/metabolism* ; Parathyroid Hormone/metabolism* ; Osteocalcin/metabolism*

OBJECTIVE: To investigate the role of MK2 inhibitor MMI-0100 on inflammatory response after allogeneic hematopoietic stem cell transplantation (allo-HSCT) and related mechanisms. METHODS: An allo-HSCT mouse model was established. Recipient rats were randomly divided into BMT+NaCl group and BMT+MMI-0100 group, and were injected with NaCl and MMI-0100 every day after transplantation, respectively. Samples of the two groups were collected on d 7 and 14, femur paraffin sections were stained with HE, and pathological changes in the bone marrow cavity were observed under the light microscope. The gene and protein expression levels of pro-inflammatory cytokines IL-1β and IL-18 were detected by qPCR and Western blot. Macrophage typing was detected by flow cytometry. The expression levels of NLRP3 and Caspase-1 were detected by Western blot. RESULTS: Inflammatory cell infiltration in the bone marrow cavity was significantly reduced in the BMT+MMI-0100 group. Western blot results showed that the protein expression levels of IL-1β and IL-18 in the BMT+MMI-0100 group were decreased compared to the BMT+NaCl group on day 7 and day 14 (all P <0.01). The qPCR results showed that compared to the BMT+NaCl group, the IL-18 gene expression levels in the BMT+MMI-0100 group were significantly reduced on day 7 and day 14 (both P <0.01). In the BMT+MMI-0100 group, the expression level of IL-1β gene decreased on day 7 (P <0.05), but increased and was higher than that in the BMT+NaCl group on day 14 (P <0.05). Flow cytometry results showed that the expression of M1 macrophages and M1/M2 ratio decreased in the BMT+MMI-0100 group compared to BMT+NaCl group (all P <0.05). Western blot results showed that the protein expression levels of NLRP3 and Caspase-1 in the BMT+MMI-0100 group were lower than those in the BMT+NaCl group (all P <0.05). CONCLUSION MMI-0100 can ameliorate bone marrow inflammatory injury after allo-HSCT and may act by reducing NLRP3 expression to promote M2 polarization.
Animals ; Interleukin-1beta/metabolism* ; Rats ; Interleukin-18/metabolism* ; Hematopoietic Stem Cell Transplantation/adverse effects* ; Mice ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Inflammation ; Bone Marrow/pathology* ; Protein Serine-Threonine Kinases/metabolism* ; Intracellular Signaling Peptides and Proteins/antagonists & inhibitors* ; Caspase 1/metabolism* ; Macrophages ; Transplantation, Homologous

BACKGROUND: Blood glucose and serum albumin have been associated with cardiovascular disease prognosis, but the impact of admission-blood-glucose-to-albumin ratio (AAR) on adverse outcomes in critical ill coronary artery disease (CAD) patients was not investigated. METHODS: Patients diagnosed with CAD were non-consecutively selected from the MIMIC-IV database and categorized into quartiles based on their AAR. The primary outcome was 1-year mortality, and secondary endpoints were in-hospital mortality, acute kidney injury (AKI), and renal replacement therapy (RRT). A restricted cubic splines model and Cox proportional hazard models assessed the association between AAR and adverse outcomes in CAD patients. Kaplan-Meier survival analysis determined differences in endpoints across subgroups. RESULTS: A total of 8360 patients were included. There were 726 patients (8.7%) died in the hospital and 1944 patients (23%) died at 1 year. The incidence of AKI and RRT was 63% and 4.3%, respectively. High AAR was markedly associated with in-hospital mortality (HR = 1.587, P = 0.003), 1-year mortality (HR = 1.502, P < 0.001), AKI incidence (HR = 1.579, P < 0.001), and RRT (HR = 1.640, P < 0.016) in CAD patients in the completely adjusted Cox proportional hazard model. Kaplan-Meier survival analysis noted substantial differences in all endpoints based on AAR quartiles. Stratified analysis and interaction test demonstrated stable correlations between AAR and outcomes. CONCLUSIONS The results highlight that AAR may be a potential indicator for assessing in-hospital mortality, 1-year mortality, and adverse renal prognosis in critical CAD patients.

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 correlation between triglyceride-glucose (TyG) index-body mass index (BMI) product (TyG-BMI) and hypertension.Methods:Based on the cross-sectional survey data of adult hypertension prevalence in Hunan Province from June 2013 to May 2014, 4 012 subjects aged ≥18 years with complete key data were included. Binary logistic regression analysis was used to analyze the correlation between TyG-BMI and hypertension, and receiver operating characteristic (ROC) curve was used to compare the ability of TyG index and TyG-BMI to identify hypertension.Results:A total of 4 012 subjects were included in this study, with an average age of (54.6±12.6)years, and males accounted for 40.98%(1 644/4 012). The prevalence of hypertension was 38.33%(1 538/4 012). Logistic regression analysis showed that elevated TyG-BMI was an independent risk factor for hypertension ( P<0.05). In the fully adjusted model, each 1/4 increase in TyG-BMI was associated with a 1.017-fold increase in the risk of hypertension ( OR=1.017, 95% CI: 1.014-1.019). Compared with the lowest quartile group (Q 1), the higher quartile groups (Q 2, Q 3, Q 4) of TyG-BMI had a higher risk of hypertension, with OR values of 1.841, 2.265, and 4.386, respectively. Restricted cubic spline plot showed a linear dose-response relationship between TyG-BMI and the risk of hypertension (overall trend P<0.001). In subgroup analyses stratified by age, gender, smoking and drinking status, TyG-BMI was positively correlated with hypertension. In addition, ROC curve analysis showed that TyG-BMI had better diagnostic value for hypertension compared with TyG index. Conclusions:TyG-BMI is an independent risk factor for hypertension. Excessively high TyG-BMI or gradual increase of TyG-BMI will increase the risk of hypertension, and TyG-BMI has higher value in identifying hypertension compared with TyG index.

Aim Mouse model of myocardial hypertro-phy was established via intraperitoneal injection of iso-proterenol(ISO)in mice.This approach allows for an in-depth investigation into the pharmacological effects and mechanisms of action of emodin,offering novel in-sights and directions for the improvement of myocardial hypertrophy.Methods The mice were randomly di-vided into the following groups:control group(CON),emodin group(EMO),MAPK activator control group(EMO+Ani),model group(ISO),treatment group(ISO+EMO),and activator intervention group(ISO+EMO+Ani).After treatment with emodin and inter-vention with MAPK activator,the heart weight ratio and cardiac size of each group were observed.Hematoxy-lin-eosin(HE)staining was used to observe the patho-logical changes in cardiac tissue,and kits were utilized to measure the levels of GSH,LDH,and MDA in the serum.Western blot was employed to detect the protein expression levels of inflammatory and oxidative factors,as well as p-p38,p-ERK,p38,and ERK in cardiac tis-sue.Results Emodin can significantly inhibit the production of myocardial inflammatory and oxidative factors induced by ISO,thereby effectively alleviating the degree of myocardial hypertrophy and fibrosis.Af-ter the p38/ERK signaling pathway was specifically ac-tivated by farnesol,the improvement effect of emodin on myocardial hypertrophy was weakened.Further comparison revealed that,compared with the myocardi-al hypertrophy pathological model group,the pathologi-cal protein expression levels in the farnesol-treated group showed no significant difference,and were even higher in some indicators.Conclusion Emodin can effectively inhibit the release of inflammatory factors and improve the state of oxidative stress by modulating the p38/ERK signaling pathway,thereby exerting an ameliorative effect on myocardial hypertrophy.

Aim Mouse model of myocardial hypertro-phy was established via intraperitoneal injection of iso-proterenol(ISO)in mice.This approach allows for an in-depth investigation into the pharmacological effects and mechanisms of action of emodin,offering novel in-sights and directions for the improvement of myocardial hypertrophy.Methods The mice were randomly di-vided into the following groups:control group(CON),emodin group(EMO),MAPK activator control group(EMO+Ani),model group(ISO),treatment group(ISO+EMO),and activator intervention group(ISO+EMO+Ani).After treatment with emodin and inter-vention with MAPK activator,the heart weight ratio and cardiac size of each group were observed.Hematoxy-lin-eosin(HE)staining was used to observe the patho-logical changes in cardiac tissue,and kits were utilized to measure the levels of GSH,LDH,and MDA in the serum.Western blot was employed to detect the protein expression levels of inflammatory and oxidative factors,as well as p-p38,p-ERK,p38,and ERK in cardiac tis-sue.Results Emodin can significantly inhibit the production of myocardial inflammatory and oxidative factors induced by ISO,thereby effectively alleviating the degree of myocardial hypertrophy and fibrosis.Af-ter the p38/ERK signaling pathway was specifically ac-tivated by farnesol,the improvement effect of emodin on myocardial hypertrophy was weakened.Further comparison revealed that,compared with the myocardi-al hypertrophy pathological model group,the pathologi-cal protein expression levels in the farnesol-treated group showed no significant difference,and were even higher in some indicators.Conclusion Emodin can effectively inhibit the release of inflammatory factors and improve the state of oxidative stress by modulating the p38/ERK signaling pathway,thereby exerting an ameliorative effect on myocardial hypertrophy.

Objective:To explore the correlation between triglyceride-glucose (TyG) index-body mass index (BMI) product (TyG-BMI) and hypertension.Methods:Based on the cross-sectional survey data of adult hypertension prevalence in Hunan Province from June 2013 to May 2014, 4 012 subjects aged ≥18 years with complete key data were included. Binary logistic regression analysis was used to analyze the correlation between TyG-BMI and hypertension, and receiver operating characteristic (ROC) curve was used to compare the ability of TyG index and TyG-BMI to identify hypertension.Results:A total of 4 012 subjects were included in this study, with an average age of (54.6±12.6)years, and males accounted for 40.98%(1 644/4 012). The prevalence of hypertension was 38.33%(1 538/4 012). Logistic regression analysis showed that elevated TyG-BMI was an independent risk factor for hypertension ( P<0.05). In the fully adjusted model, each 1/4 increase in TyG-BMI was associated with a 1.017-fold increase in the risk of hypertension ( OR=1.017, 95% CI: 1.014-1.019). Compared with the lowest quartile group (Q 1), the higher quartile groups (Q 2, Q 3, Q 4) of TyG-BMI had a higher risk of hypertension, with OR values of 1.841, 2.265, and 4.386, respectively. Restricted cubic spline plot showed a linear dose-response relationship between TyG-BMI and the risk of hypertension (overall trend P<0.001). In subgroup analyses stratified by age, gender, smoking and drinking status, TyG-BMI was positively correlated with hypertension. In addition, ROC curve analysis showed that TyG-BMI had better diagnostic value for hypertension compared with TyG index. Conclusions:TyG-BMI is an independent risk factor for hypertension. Excessively high TyG-BMI or gradual increase of TyG-BMI will increase the risk of hypertension, and TyG-BMI has higher value in identifying hypertension compared with TyG index.

Objective To explore the method for measurement of tritium in nuclear power plant liquid effluent purified by a mixed ion-exchange resin, to verify the feasibility of the method by experiments, and to provide technical support for the development of standard methods for the measurement of tritium in liquid effluent of nuclear power plants. Methods The purification effect of the mixed ion-exchange resin was determined by measuring the quenching factor, conductivity, and β-nuclide adsorption efficiency of the samples purified using the resin. A comparison was made between the ion-exchange resin method and the atmospheric distillation method for tritium determination. The precision and accuracy of the method were verified by calculating the relative standard deviation and the recovery in repeated measurement of samples with different activity concentrations and spiked samples. Results There were no significant differences in quenching factor, conductivity, and tritium activity concentration between the two methods. The adsorption efficiencies of EC20MB resin for common β-nuclides such as carbon, iron, nickel, strontium, yttrium, and cesium ranged from 99.28% to 99.88%. Repeated measurement of the same sample showed relative standard deviations of 5.2%-9.4% and recoveries of 86.8%-107%. Conclusion There were no significant differences between the results of the ion-exchange resin purification method and the atmospheric distillation method. The precision and accuracy of the method met the requirements of the ecological and environmental management authorities for monitoring tritium in liquid effluent from nuclear power plants. This method can be widely used in daily monitoring work.

Objective To investigate the value of wrist MRI in bone age estimation for male adoles-cents in Shanghai,Zhejiang and Jiangsu.Methods A total of 124 Han male adolescents aged 6.0 to 18.0 years from Shanghai,Zhejiang and Jiangsu were selected as subjects.Their weight and height were measured,and T1WI and T2WI sequences of the wrist were scanned.The distal ends of the ra-dius and ulna,and the first to five metacarpal epiphyses and corresponding metaphyses were selected as observational indexes after MRI images of the wrist were obtained.The development of each index was classified(0-2 grades)by a deputy senior imaging expert,then the maximum width of each in-dex was measured by another deputy senior expert.Height,weight,classification and maximum width of indexes were used as input variables,and age was used as the target variable.Support vector ma-chine,random forest,current reality tree,and linear regression models were established to estimate the bone age,and the model with the highest accuracy was selected.Results The height,weight,classifica-tion of wrist bone epiphysis development,maximum width of each bone metaphysis and epiphysis were all correlated with age(P<0.05).The accuracies of the support vector machine were the highest when the differences between bone age and actual chronological age were within 1.0 and 1.5 years(88.7%and 96.0%,respectively).Conclusion It is feasible to estimate bone age by using MRI images.Quantifying the maximum width of the epiphysis and corresponding metaphysis of bone and combining it with MRI image classification can effectively reduce the estimation error.