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.

Objective:To investigate the diagnostic efficacy of time-dependent diffusion MRI (t d-dMRI)-derived microstructural parameters for clinically significant prostate cancer (csPCa) and their associations with the pathological grade of prostate cancer(PCa) based on the International Society of Urological Pathology (ISUP) grades. Methods:This cross-sectional study prospectively enrolled 196 patients suspected of PCa from March 2023 to March 2024 at the First Affiliated Hospital, Sun Yat-Sen University. All patients underwent multiparametric MRI and t d-dMRI to obtain microstructural parameters, including cell diameter (d), intracellular volume fraction (f in), extracellular diffusion coefficient (D ex), cellularity, and apparent diffusion coefficient (ADC) value at oscillation frequencies of 33 Hz, 17 Hz, 0 Hz (ADC 33, ADC 17, and ADC 0). Pathologically, 95 cases were classified as csPCa (ISUP 2-5), and the rest 101 cases were classified as non-csPCa (benign or ISUP 1). Comparison of these microstructural metrics was made between csPCa and non-csPCa groups by independent t-tests or Mann-Whitney U tests, and multivariable logistic regression was used to identify independent predictors. A combined diagnostic model was then constructed based on the independent predictors. The receiver operating characteristic curve analysis was used to evaluate the diagnostic performance. Finally, in PCa, the correlation between microstructural parameters and ISUP grades was investigated by Spearman correlation. Results:The t d-dMRI measurements, including d, f in, cellularity, ADC 33,ADC 17 and ADC 0, were significantly different between csPCa and non-csPCa groups (All P<0.05). But D ex was not significantly different between the two groups ( Z=-1.27, P=0.204). The area under the receiver operating characteristic curve (AUC) for diagnosing csPCa were 0.701 (95% CI 0.628-0.775) for d, 0.869 (95% CI 0.819-0.920) for f in, 0.884 (95% CI 0.835-0.932) for cellularity, 0.777 (95% CI 0.712-0.842) for ADC 33, 0.852 (95% CI 0.799-0.905) for ADC 17, and 0.840 (95% CI 0.786-0.894) for ADC 0. Cellularity ( OR=6.142, 95% CI 2.920-12.929, P<0.001) and ADC 17 ( OR=0.108, 95% CI 0.027-0.429, P=0.002) were identified as the independent predictors, and their combined model achieved an AUC of 0.896 (95% CI 0.852-0.941). In PCa f in and cellularity were positively correlated with ISUP grades ( r=0.490 and 0.397, P<0.001), while ADC 33, ADC 17, and ADC 0 were negatively correlated with ISUP grades ( r=-0.198, -0.345, -0.360; P=0.041,<0.001,<0.001). d and D ex were not correlated with ISUP grades ( P>0.05). Conclusion:t d-dMRI based microstructural mapping correlates with ISUP grades of PCa and may be useful for the differential diagnosis of csPCa.

OBJECTIVE: To assess the efficacy of Qingda Granule (QDG) in ameliorating hypertension-induced cardiac damage and investigate the underlying mechanisms involved. METHODS: Twenty spontaneously hypertensive rats (SHRs) were used to develope a hypertension-induced cardiac damage model. Another 10 Wistar Kyoto (WKY) rats were used as normotension group. Rats were administrated intragastrically QDG [0.9 g/(kg•d)] or an equivalent volume of pure water for 8 weeks. Blood pressure, histopathological changes, cardiac function, levels of oxidative stress and inflammatory response markers were measured. Furthermore, to gain insights into the potential mechanisms underlying the protective effects of QDG against hypertension-induced cardiac injury, a network pharmacology study was conducted. Predicted results were validated by Western blot, radioimmunoassay immunohistochemistry and quantitative polymerase chain reaction, respectively. RESULTS: The administration of QDG resulted in a significant decrease in blood pressure levels in SHRs (P<0.01). Histological examinations, including hematoxylin-eosin staining and Masson trichrome staining revealed that QDG effectively attenuated hypertension-induced cardiac damage. Furthermore, echocardiography demonstrated that QDG improved hypertension-associated cardiac dysfunction. Enzyme-linked immunosorbent assay and colorimetric method indicated that QDG significantly reduced oxidative stress and inflammatory response levels in both myocardial tissue and serum (P<0.01). CONCLUSIONS Both network pharmacology and experimental investigations confirmed that QDG exerted its beneficial effects in decreasing hypertension-induced cardiac damage by regulating the angiotensin converting enzyme (ACE)/angiotensin II (Ang II)/Ang II receptor type 1 axis and ACE/Ang II/Ang II receptor type 2 axis.
Animals ; Drugs, Chinese Herbal/therapeutic use* ; Hypertension/pathology* ; Renin-Angiotensin System/drug effects* ; Rats, Inbred SHR ; Oxidative Stress/drug effects* ; Male ; Rats, Inbred WKY ; Blood Pressure/drug effects* ; Myocardium/pathology* ; Rats ; Inflammation/pathology*

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.

Poor water solubility is the primary obstacle preventing the development of many pharmacologically active compounds into oral preparations. Self-nanoemulsifying drug delivery systems(SNEDDS) have become a widely used strategy to enhance the oral bioavailability of poorly soluble drugs by inducing a supersaturated state, thereby improving their apparent solubility and dissolution rate. However, the supersaturated solutions formed in SNEDDS are thermodynamically unstable systems with solubility levels exceeding the crystalline equilibrium solubility, making them prone to drug precipitation in the gastrointestinal tract and ultimately hindering drug absorption. Therefore, maintaining a stable supersaturated state is crucial for the effective delivery of poorly soluble drugs. Incorporating polymers as precipitation inhibitors(PPIs) into the formulation of supersaturated self-nanoemulsifying drug delivery systems(S-SNEDDS) can inhibit drug aggregation and crystallization, thus maintaining a stable supersaturated state. This has emerged as a novel preparation strategy and a key focus in SNEDDS research. This review explores the preparation design of SNEDDS and the technical challenges involved, with a particular focus on polymer-based S-SNEDDS for enhancing the solubility and oral bioavailability of poorly soluble drugs. It further elucidates the mechanisms by which polymers participate in transmembrane transport, summarizes the principles by which polymers sustain a supersaturated state, and discusses strategies for enhancing drug absorption. Altogether, this review provides a structured framework for the development of S-SNEDDS preparations with stable quality and reduced development risk, and offers a theoretical reference for the application of S-SNEDDS technology in improving the oral bioavailability of poorly soluble drugs.
Solubility ; Administration, Oral ; Polymers/chemistry* ; Drug Delivery Systems/methods* ; Humans ; Emulsions/chemistry* ; Biological Availability ; Animals ; Pharmaceutical Preparations/administration & dosage*

PURPOSE: Lateral patellar compression syndrome (LPCS) is characterized by a persistent abnormally high stress exerted on the lateral articular surface of the patella due to lateral patellar tilt without dislocation and lateral retinaculum contracture, leading to anterior knee pain. The purpose of this study is to evaluate the efficacy and prognosis of lateral retinaculum release (LRR) combined with chondroplasty in the treatment of LPCS. METHODS: This retrospective study evaluated 40 patients who underwent LRR combined with chondroplasty for LPCS between 2020 and 2021. The assessment included improvement in postoperative tenderness and knee joint function. Patients were evaluated using the Lysholm, Tegner, and International Knee Documentation Committee 2000 scoring systems, as well as the visual analog scale, both preoperatively and postoperatively, with the paired comparisons analyzed using a t-test. Additionally, intraoperative observations were made regarding knee joint lesions, including cartilage damage and osteophyte formation, with analysis by the Chi-square test. RESULTS: The visual analog scale score for tenderness showed a significant decrease after surgery (p < 0.001). Evaluation of knee joint function also indicated significant improvements, as demonstrated by increased Lysholm, Tegner, and International Knee Documentation Committee 2000 scores postoperatively (p < 0.001, p = 0.011, p < 0.001, respectively). Furthermore, all LPCS patients included in the study presented with cartilage injuries and osteophyte formation. Significant differences were noted in the incidence of cartilage damage and osteophyte formation at different locations within the knee among patients with LPCS. CONCLUSION LRR combined with chondroplasty is an effective surgical approach for treating patients with LPCS, with satisfactory recovery observed at the 1-year follow-up. Additionally, the incidence of cartilage damage and osteophyte formation in LPCS patients varies significantly depending on the specific location within the knee joint.
Humans ; Male ; Female ; Retrospective Studies ; Adult ; Middle Aged ; Patella/surgery* ; Knee Joint/physiopathology* ; Recovery of Function ; Young Adult ; Treatment Outcome ; Cartilage, Articular/surgery* ; Adolescent

Objective:To investigate the diagnostic efficacy of time-dependent diffusion MRI (t d-dMRI)-derived microstructural parameters for clinically significant prostate cancer (csPCa) and their associations with the pathological grade of prostate cancer(PCa) based on the International Society of Urological Pathology (ISUP) grades. Methods:This cross-sectional study prospectively enrolled 196 patients suspected of PCa from March 2023 to March 2024 at the First Affiliated Hospital, Sun Yat-Sen University. All patients underwent multiparametric MRI and t d-dMRI to obtain microstructural parameters, including cell diameter (d), intracellular volume fraction (f in), extracellular diffusion coefficient (D ex), cellularity, and apparent diffusion coefficient (ADC) value at oscillation frequencies of 33 Hz, 17 Hz, 0 Hz (ADC 33, ADC 17, and ADC 0). Pathologically, 95 cases were classified as csPCa (ISUP 2-5), and the rest 101 cases were classified as non-csPCa (benign or ISUP 1). Comparison of these microstructural metrics was made between csPCa and non-csPCa groups by independent t-tests or Mann-Whitney U tests, and multivariable logistic regression was used to identify independent predictors. A combined diagnostic model was then constructed based on the independent predictors. The receiver operating characteristic curve analysis was used to evaluate the diagnostic performance. Finally, in PCa, the correlation between microstructural parameters and ISUP grades was investigated by Spearman correlation. Results:The t d-dMRI measurements, including d, f in, cellularity, ADC 33,ADC 17 and ADC 0, were significantly different between csPCa and non-csPCa groups (All P<0.05). But D ex was not significantly different between the two groups ( Z=-1.27, P=0.204). The area under the receiver operating characteristic curve (AUC) for diagnosing csPCa were 0.701 (95% CI 0.628-0.775) for d, 0.869 (95% CI 0.819-0.920) for f in, 0.884 (95% CI 0.835-0.932) for cellularity, 0.777 (95% CI 0.712-0.842) for ADC 33, 0.852 (95% CI 0.799-0.905) for ADC 17, and 0.840 (95% CI 0.786-0.894) for ADC 0. Cellularity ( OR=6.142, 95% CI 2.920-12.929, P<0.001) and ADC 17 ( OR=0.108, 95% CI 0.027-0.429, P=0.002) were identified as the independent predictors, and their combined model achieved an AUC of 0.896 (95% CI 0.852-0.941). In PCa f in and cellularity were positively correlated with ISUP grades ( r=0.490 and 0.397, P<0.001), while ADC 33, ADC 17, and ADC 0 were negatively correlated with ISUP grades ( r=-0.198, -0.345, -0.360; P=0.041,<0.001,<0.001). d and D ex were not correlated with ISUP grades ( P>0.05). Conclusion:t d-dMRI based microstructural mapping correlates with ISUP grades of PCa and may be useful for the differential diagnosis of csPCa.

OBJECTIVE To design and synthesize rifamycin S derivatives and load them into milk exosomes to evaluate their in vitro antimicrobial activity.METHODS Rifamycin S derivatives were synthe-sized and characterized by mass spectrometry and NMR.Using the dilution assay method,the inhibitory activity of each rifamycin S derivatives molecule against Staphylococcus aureus and Pseudomonas aerugi-nosa was determined,and the IC50 was calculated.Derivatives molecules with excellent antimicrobial activity were selected and loaded into milk exosomes using the ultrasonication method,resulting in the preparation of milk exosome-loaded rifamycin S derivatives.The antimicrobial activity against Staphylo-coccus aureus was determined using the dilution assay method.The inhibitory effect of the exosome-loaded rifamycin S derivatives on Staphylococcus aureus residing within macrophages was detected using the plate colony counting method.RESULTS Three rifamycin S derivatives were successfully designed and synthesized,which demonstrated superior antimicrobial activity against Staphylococcus aureus(the parent compound's antimicrobial activity is merely from 1/20 to 1/80 of that of the three rifamycin S derivatives)and Pseudomonas aeruginosa(the parent compound's antimicrobial activity is only 1/14 and 1/9 of that of compound 1 and compound 3)compared to the parent compound.The loading of milk exosomes with the rifamycin S derivatives compound 3 was successfully achieved,with a loading efficiency of 10.9％.The antimicrobial activity of the compound after exosome loading was significantly enhanced against Staphylococcus aureus in vitro and against Staphylococcus aureus residing within macrophages(P＜0.01).CONCLUSION The designed and synthesized derivatives of rifamycin S possess stronger anti-microbial activity,and their antibacterial efficacy against both extracellular and intracellular bacteria can be further enhanced after loading into exosomes.

OBJECTIVE To design and synthesize rifamycin S derivatives and load them into milk exosomes to evaluate their in vitro antimicrobial activity.METHODS Rifamycin S derivatives were synthe-sized and characterized by mass spectrometry and NMR.Using the dilution assay method,the inhibitory activity of each rifamycin S derivatives molecule against Staphylococcus aureus and Pseudomonas aerugi-nosa was determined,and the IC50 was calculated.Derivatives molecules with excellent antimicrobial activity were selected and loaded into milk exosomes using the ultrasonication method,resulting in the preparation of milk exosome-loaded rifamycin S derivatives.The antimicrobial activity against Staphylo-coccus aureus was determined using the dilution assay method.The inhibitory effect of the exosome-loaded rifamycin S derivatives on Staphylococcus aureus residing within macrophages was detected using the plate colony counting method.RESULTS Three rifamycin S derivatives were successfully designed and synthesized,which demonstrated superior antimicrobial activity against Staphylococcus aureus(the parent compound's antimicrobial activity is merely from 1/20 to 1/80 of that of the three rifamycin S derivatives)and Pseudomonas aeruginosa(the parent compound's antimicrobial activity is only 1/14 and 1/9 of that of compound 1 and compound 3)compared to the parent compound.The loading of milk exosomes with the rifamycin S derivatives compound 3 was successfully achieved,with a loading efficiency of 10.9％.The antimicrobial activity of the compound after exosome loading was significantly enhanced against Staphylococcus aureus in vitro and against Staphylococcus aureus residing within macrophages(P＜0.01).CONCLUSION The designed and synthesized derivatives of rifamycin S possess stronger anti-microbial activity,and their antibacterial efficacy against both extracellular and intracellular bacteria can be further enhanced after loading into exosomes.

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.