Background and aims The mechanism of cholestatic liver injury (CLI) is unclear, and effective therapies are lacking. While peroxisome proliferator-activated receptor alpha (PPARα) agonists show potential hepatoprotective effect and pyroptosis is implicated in hepatocellular damage, how PPARα activation mitigates lithocholic acid (LCA)-induced pyroptosis remains unknown. Methods The hepatoprotective effect of PPARα agonists was evaluated in a mouse model of intrahepatic cholestasis induced by LCA. Liver injury was assessed via serum biochemistry, hematoxylin and eosin and TUNEL staining, and electron microscopy. Pyroptosis pathways were analyzed using real-time quantitative polymerase chain reaction, Western blot, and co-immunoprecipitation. Results Combined morphological, histopathological, and biochemical analyses confirmed that PPARα activation protects against CLI. Compared with LCA treatment alone, PPARα activation significantly attenuated the elevation of serum lactate dehydrogenase (LDH), the increased TUNEL-positive cells, and the formation of hepatocyte membrane pores. Mechanistically, PPARα activation suppressed both NOD-like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis and apoptosis protease-activating factor-1 (APAF-1)/CASPASE-3/GSDME-mediated pyroptosis. Furthermore, PPARα agonist pretreatment inhibited activation of the nuclear factor-kappa B (NF-κB) and forkhead box O1 (FOXO1) signaling pathways. Conclusions PPARα protects against LCA-induced CLI by inhibiting both NLRP3 inflammasome-mediated pyroptosis associated with NF-κB and APAF-1/CASPASE-3/GSDME-mediated pyroptosis associated with the FOXO1 signaling pathway.

Objective To compare the mid- and long-term clinical results of mitral valve plasty (MVP) and mitral valve replacement (MVR) in the treatment of functional mitral regurgitation (FMR). Methods Patients with FMR who underwent surgical treatment in the Department of Cardiovascular Surgery of the General Hospital of Northern Theater Command from 2012 to 2021 were collected. The patients who underwent MVP were divided into a MVP group, and those who underwent MVR into a MVR group. The clinical data and mid-term follow-up efficacy of two groups were compared. Results Finally 236 patients were included. There were 100 patients in the MVP group, including 53 males and 47 females, with an average age of (61.80±8.03) years. There were 136 patients in the MVR group, including 72 males and 64 females, with an average age of (61.29±8.97) years. There was no statistical difference in baseline data between the two groups (P＞0.05). There was no statistical difference between the two groups in the extracorporeal circulation time, aortic occlusion time, postoperative hospital and ICU stay, intraoperative blood loss, or hospitalization death (P＞0.05), but the time of mechanical ventilation in the MVP group was significantly shorter than that in the MVR group (P=0.022). The total follow-up rate was 100.0%, the longest follow-up was 10 years, and the average follow-up time was (3.60±2.55) years. There were statistical differences in the left atrial diameter, left ventricular end-diastolic diameter, left ventricular end-systolic diameter and cardiac function between the two groups compared with those before surgery (P<0.05). The postoperative left ventricular ejection fraction in the MVP group was statistically higher than that before surgery (P=0.002), but there was no statistical difference in the MVR group before and after surgery (P=0.658). The left atrial diameter in the MVP group was reduced compared with the MVR group (P=0.026). The recurrence rate of mitral regurgitation in the MVP group was higher than that in the MVR group, and the difference was statistically significant (10.0% vs. 1.5%, P=0.003). There were 14 deaths in the MVP group and 19 in the MVR group. The cumulative survival rate (P=0.605) and cardiovascular events-free survival rate (P=0.875) were not statistically significant between the two groups by Kaplan-Meier survival analysis. Conclusion The safety, and mid- and long-term clinical efficacy of MVP in the treatment of FMR patients are better than MVR, and the left atrial and left ventricular diameters are statistically reduced, and cardiac function is statistically improved. However, the surgeon needs to be well aware of the indications for the MVP procedure to reduce the rate of mitral regurgitation recurrence.

The relationship between hyperuricemia (HUA) and erectile dysfunction (ED) remains inadequately understood. Given that HUA is often associated with various metabolic disorders, this study aims to explore the multivariate linear impacts of metabolic parameters on erectile function in ED patients with HUA. A cross-sectional analysis was conducted involving 514 ED patients with HUA in the Department of Andrology, Jiangsu Province Hospital of Chinese Medicine (Nanjing, China), aged 18 to 60 years. General demographic information, medical history, and laboratory results were collected to assess metabolic disturbances. Sexual function was evaluated using the 5-item version of the International Index of Erectile Function (IIEF-5) questionnaire. Based on univariate analysis, variables associated with IIEF-5 scores were identified, and the correlations between them were evaluated. The effects of these variables on IIEF-5 scores were further explored by multiple linear regression models. Fasting plasma glucose ( β = -0.628, P < 0.001), uric acid ( β = -0.552, P < 0.001), triglycerides ( β = -0.088, P = 0.047), low-density lipoprotein cholesterol ( β = -0.164, P = 0.027), glycated hemoglobin (HbA1c; β = -0.562, P = 0.012), and smoking history ( β = -0.074, P = 0.037) exhibited significant negative impacts on erectile function. The coefficient of determination ( R ²) for the model was 0.239, and the adjusted R ² was 0.230, indicating overall statistical significance ( F -statistic = 26.52, P < 0.001). Metabolic parameters play a crucial role in the development of ED. Maintaining normal metabolic indices may aid in the prevention and improvement of erectile function in ED patients with HUA.
Humans ; Male ; Erectile Dysfunction/metabolism* ; Hyperuricemia/metabolism* ; Adult ; Middle Aged ; Cross-Sectional Studies ; Glycated Hemoglobin/metabolism* ; Blood Glucose/metabolism* ; Uric Acid/blood* ; Young Adult ; Triglycerides/blood* ; Adolescent ; Cholesterol, LDL/blood* ; Penile Erection/physiology* ; Surveys and Questionnaires

This consensus will introduce the characteristics of fillers used in the surgical cavities of domestic nasal surgery patients based on relevant literature and expert opinions. It will also provide recommendations for the selection of cavity fillers for different nasal diseases, with chronic sinusitis as a representative example.
Humans ; Nasal Cavity/surgery* ; Nasal Surgical Procedures ; China ; Consensus ; Sinusitis/surgery* ; Dermal Fillers

A novel analytical method was developed in this study by combining online solid phase extraction with ultra performance liquid chromatography-tandem mass spectrometry(Online SPE-UPLC-MS/MS)for simultaneous determination of 50 kinds of steroid hormones in surface water.Specifically,after high-speed centrifugation of 4 mL water samples,the supernatant was directly injected into an Oasis HLB online SPE column for enrichment and purification.Subsequently,the target compounds were transferred to the analytical column via valve switching for separation and analysis.The chromatographic separation was performed on a Thermo Acclaim RSLC C18 column(100 mm×2.1 mm,2.2 μm),using a mobile phase composed of 5 mmol/L ammonium fluoride aqueous solution and acetonitrile.Mass spectrometric detection was conducted in positive ion mode,utilizing multiple reaction monitoring(MRM)with quantification achieved by the internal standard method.The method validation demonstrated that the limits of detection(LOD)for the 50 kinds of steroid hormones ranged from 0.02 to 0.50 ng/L,while the limits of quantification(LOQ)were between 0.08 and 1.67 ng/L.The average recoveries in surface water samples at spiked concentrations of 5,20 and 200 ng/L were between 74.1％and 119％,with relative standard deviations(RSDs)of 0.2％to 9.9％.This method was applied to analyze 11 surface water samples collected from sites surrounding a pharmaceutical and chemical industrial park.A total of 44 kinds of steroid hormones were detected,with concentrations ranging from 0.11 to 88.6 ng/L,revealing the presence of hormone contamination in the environmental waters surrounding industrial areas.Compared with the traditional offline SPE methods,the proposed online SPE technique significantly reduced sample volume requirements and pretreatment time,while minimizing the loss of target compounds during the pretreatment process.Moreover,compared to reported online SPE techniques,this method achieved high-throughput analysis of multiple classes of steroid hormones,with lower detection limits and higher recoveries.Overall,this method provided rapid sample preparation,high sensitivity,and excellent stability,making it suitable for the direct analysis of trace steroid hormones in surface water.

A method for determination and targeted screening of diflorasone components in health products using ultra performance liquid chromatography-quadrupole time of flight mass spectrometry(UPLC-Q-TOF/MS)was established.Four representative diflorasone and esters(diflorasone,diflorasone diacetate,diflorasone-17-propionate,and diflorasone-21-propionate)were selected to optimize the pretreatment conditions,and 10 mL of extraction solvent dosage,15 min of extraction time and 5 g of salting-out agent as the optimal conditions were selected by response surface methodology.The results showed that the four analytes exhibited good linearity within the concentration range of 2.0?100 μg/L with the chromatographic peak area,and the correlation coefficients(R2)were all greater than 0.9990,while the results of recovery and relative standard deviation could satisfy the requirements of determination.The common characteristic ions of diflorasone and esters werem/z121 andm/z335,and their specific structures were obtained by analyzing the cleavage pathway based on the optimized determination conditions.A targeted screening method for other esters of diflorasone based on characteristic ions guidance strategy was established.This method had many advantages such as high efficiency,high sensitivity and good reproducibility,and could be used for targeted screening of diflorasone and esters in health products.The developed characteristic ion guided strategy could be employed to construct mass spectral databases for various glucocorticoids,enabling comprehensive targeted screening across a broad range of compounds.

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.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

The development status of the key technologies of first-aid robotics was introduced in autonomous system,embo-died intelligence,digital twins,large artificial intelligence model and autonomous unmanned medical treatment.The present situation in first-aid robotics equipment was reviewed for first-aid diagnosis,treatment,assistance and transportation.The development trends of the key technology and equipment of first-aid robotics were analyzed.It was pointed out the involve-ment of big model-based embodied intelligence technology and digital twins technology in first aid might provide new pers-pectives for the application and advancement of specialized first-aid robotics.[Chinese Medical Equipment Journal,2025,46(3):96-114]

Aim To evaluate the role of the glucose transporter protein 1(GLUT1)-dependent glycolytic in the attenuation of oxygen-glucose deprivation-reoxygen-ation(OGD/R)injury in HK-2 cells by dexmedetomi-dine(Dex).Methods C57/BL6 mice were random-ly divided into three groups(n=6),namely,sham operation group(Sham group),renal ischemia reper-fusion group(I/R group)and Dex group(I/R+Dex group).Serum creatinine(Cr)and urea nitrogen(BUN)were measured,while the levels of key glyco-lytic enzymes HK2,PFKFB3 and GLUT1 were meas-ured.HK-2 cells were cultured and randomised into seven groups(n=6),which was treated with OGD/R,overexpression or interference with GLUT1,Dex and glycolysis inhibitor 2-DG.CCK-8 and LDH activi-ty were used to detect cellular damage.Glycolysis lev-els were detected by lactate and ECAR.The inflamma-tory level was reflected by qRT-PCR for IL-6 and TNF-α.qRT-PCR and Western blot were performed to de-tect the levels of GLUT1,HK2,and PFKFB3.Results Dex significantly ameliorated kidney injury and HK-2 cell injury(P＜0.05).Dex inhibited the OGD/R-induced rise in lactate and extracellular acidification rate(ECAR),as evidenced by suppression of the ex-pression of GLUT1,HK2 and PFKFB3(P＜0.05).In vitro experiments showed that GLUT1 knockdown sig-nificantly improved OGD/R-induced cellular damage.Lactate,ECAR,glycolysis-related mRNAs and pro-teins were inhibited by GLUT1 knockdown(P＜0.05).Significantly,there were no significant differ-ences in above indexes after Dex treatment based on GLUT1 knockdown.Overexpression of GLUT1 abroga-ted the protective effects of Dex,while reversing the inhibitory effects of Dex on the expression of GLUT1,HK2,and PFKFB3(P＜0.05).Conclusions Dexmedetomidine attenuates OGD/R induced injury in HK-2 cells by inhibiting GLUT1-dependent glycolysis.