Five compounds were isolated and purified from the water extract of Elaeagnus oxycarpa Schlechtend leaf by multi-dimensional reversed-phase preparative liquid chromatographic system based on the separation and enrichment model. Their structures were identified by spectral analysis such as NMR, MS, UV, IR and by comparison with literature information as 2,4(1H,3H)-pyrimidinedione (1), elaeagnussugarester B (2), elaeagnussugarester A (3), elaeagnussugarester C (4), gallic acid (5). Compounds 2-4 are new compounds, compound 1 was isolated from Elaeagnus oxycarpa Schlechtend for the first time. The antioxidant and anti-tyrosinase activities of these compounds were evaluated by using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical method, the 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) free radical method, the potassium ferricyanide reduction method and the colorimetric method with L-tyrosine as substrate. The results showed that compounds 2-5 have good antioxidant activities and inhibitory effect on tyrosinase. Compound 4 exhibited the most strong antioxidant activities, with IC₅₀ = 3.59 ± 0.06 μmol·L^-1 for DPPH free radical scavenging ability, IC₅₀ = 10.04 ± 0.20 μmol·L^-1 for ABTS free radical scavenging ability, and total reduction capacity of compound 4 was better than vitamin C respectively. Compound 3 possessed better inhibitory effect on tyrosinase with IC₅₀ = 0.25 ± 0.06 mmol·L^-1.

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 investigate the effect of oral fish oil on wound healing and related indexes in patients with diabetic foot ulcer(DFU).Methods A randomized,double-blind,placebo-controlled design was used to recruit 68 patients with DFU aged 18-80 years old in the hospital,and the baseline clinical data of the patients were collected.The patients were randomly divided into experimental group(32 cases,fish oil soft capsule,3 g/d)and control group(33 cases,corn oil soft capsule,3 g/d)by random number generated by Ex-cel,and the intervention lasted for 12 weeks.The primary endpoints included the proportion of complete wound healing and healing area≥50%.The secondary endpoints included wound area,healing time,inflamma-tion index,glucose metabolism index,nutrition related index and wound reinfection.Additionally,the influen-cing factors of wound healing were analyzed.Results After intervention,the proportion of complete wound healing and healing area≥50%in the experimental group was significantly higher than that in the control group(P=0.007,0.039).In the subjects with complete wound healing,the mean healing time in the experi-mental group was shorter than that in the control group,but the difference was not statistically significant(P=0.132).The reduction area of wound area in the experimental group was significantly larger than that in the control group(P=0.045).The decrease of interleukin(IL)-6 and IL-8 in the experimental group was significantly higher than that in the control group(P<0.05).There was no significant difference in the reduc-tion of C-reactive protein(CRP),tumor necrosis factor-α(TNF-α),neutrophil-to-lymphocyte ratio(NLR),glycated hemoglobin A1c(HbA1c)and platelet-to-lymphocyte ratio(PLR)between the two groups(P>0.05).The improvement of prealbumin(PA)in the experimental group was higher than that in the control group,but the difference was not statistically significant(P>0.05).Multivariate logistic regression analysis showed that oral fish oil intervention(OR=6.771,95%CI:1.787-25.652),HbA1c(OR=4.149,95%CI:1.026-16.770)and ulcer type(OR=4.319,95%CI:1.026-18.173)were the influencing factors of wound healing(P<0.05).Conclusion Oral fish oil promotes wound healing in patients with DFU,which may be re-lated to improving the level of chronic inflammation in the body.

BACKGROUND:There is no consensus on the optimal bone tunnel position in the lateral clavicle,which guides coracoclavicular ligament reconstruction.Postoperative complications such as enlargement of the lateral clavicle bone tunnel,bone osteolysis,clavicle fracture,and failure of internal fixation are likely to occur.Bone mass density plays an important role in the strength and stability of endophytic fixation.Regional differences in the bone mass density of the distal clavicle should not be overlooked in the repair and reconstruction of acromioclavicular dislocation.Currently,there are no quantitative clinical studies in humans regarding the bone mass density of the distal clavicle. OBJECTIVE:To measure the magnitude of bone mass density in different regions of the distal clavicle by quantitative CT to provide a reference for surgeons to repair and reconstruct the coracoclavicular ligament. METHODS:101 patients undergoing quantitative CT checking in Fuyang People's Hospital Affiliated to Anhui Medical University from October to December 2022 were enrolled,from which 1 616 samples of subdivisional bone mass density of the distal clavicle were measured.For each of the quantitative CT samples,firstly,the distal clavicle was divided medially to laterally into the following four regions:conical nodal region(region A),inter-nodal region(region B),oblique crest region(region C)and distal clavicular region(region D).Secondly,each region was divided into the first half and the second half to determine eight subdivisions,then setting semiautomatic region of interest(ROI)in each subdivision:(ROI A1,A2,B1,B2,C1,C2,D1,and D2).Thirdly,each quantitative CT scan was transferred to the quantitative CT pro analysis workstation,and cancellous bone mass density was measured in the distal clavicle ROI.Finally,the clavicular cortex was avoided when measuring. RESULTS AND CONCLUSION:(1)There was no statistically significant difference in bone mineral density on the different sides of the shoulder(P＞0.05).(2)The analysis of bone mineral density in eight sub-areas of the distal clavicle A1,A2,B1,B2,C1,C2,D1,and D2 showed statistically significant differences(P＜0.05).It could be considered that there were differences in bone mineral density in different areas of the distal clavicle.After pairwise comparison,there was no statistically significant difference in bone mineral density between A1 and A2,D1 and D2,A2 and B1(P＞0.05),and there was a statistically significant difference in bone mineral density between the other sub-areas(P＜0.05).(3)The bone mineral density in the region A2 of the anatomical insertion of the conical ligament was significantly higher than that in the inter-nodular area(region B)(P＜0.05).The bone mineral density in the region A1 was higher than that in the region A2,but the difference was not statistically significant(P＞0.05).The bone mineral density in the region C1 of the anatomical insertion of the trapezium ligament was higher than that in regions C2,D1 and D2,and the bone mineral density in the inter-nodular area(region B)was significantly higher than that in regions C and D(P＜0.05).(4)These results have suggested that there are differences in bone mass density in different regions of the distal clavicle;regional differences in bone mass density in the distal clavicle during repair and reconstruction of acromioclavicular dislocation cannot be ignored.Consideration should be given not only to biomechanical factors but also to the placement of implants or bone tunnels in regions of higher bone mass density,which could improve the strength and stability of implant fixation and reduce the risk of complications such as bone tunnel enlargement,osteolysis,fracture and implant failure.

OBJECTIVE To evaluate the effectiveness and safety of Panlongqi tablets in the treatment of fractures based on real-world research. METHODS From September 2021 to September 2023， fracture patients admitted to 33 medical institutions were collected retrospectively. Patients who received conventional treatment were divided into control group （n＝3 750）， and patients who received combination of Panlongqi tablets on the basis of conventional treatment were divided into observation group （n＝ 3 706）. Self-reported indicators of patients were collected through telephone follow-up at 0， 4， 7 and 14 days after treatment. The improvement values of pain score， swelling score and health utility value， as well as effective rate and adverse drug reactions were compared between 2 groups. The propensity matching score （PSM） method was adopted to perform baseline matching on patient’s age， gender， fracture site， fracture severity， surgical type， type of hospital， and other indicators. Statistical analysis was performed on each therapeutic effect indicator. RESULTS After PSM， a total of 6 425 patients were included， of which 3 055 were in the observation group and 3 370 were in the control group. After 14 days of treatment， the observation group showed significant improvement in pain score （4.768 vs. 4.353）， swelling fangshiyuan2008@126.com grading score （2.979 vs. 2.391）， and life quality utility value （0.430 vs. 0.363）， as well as effective rate （87.20% vs.75.99%） compared to the control group （P＜0.05）. The results of subgroup analyses conducted by gender， age， hospital type， and fracture site were consistent with the aforementioned results. In terms of safety， the observation group had no serious adverse reactions， with a total of 29 cases of mild adverse reactions such as dizziness， stomach pain， and allergies， with an incidence rate of 0.78%. CONCLUSIONS Panlongqi tablets combined with conventional treatment are significantly better than conventional treatment in improving pain， swelling， quality of life， and effective rate in patients with fractures， and have good safety.

Objective:To predict the short-term postoperative recurrence status of patients with refractory temporal lobe epilepsy (TLE) by analyzing preoperative 18F-FDG PET images and patients′ clinical characteristics based on deep residual neural network (ResNet). Methods:Retrospective analysis was conducted on preoperative 18F-FDG PET images and clinical data of 220 patients with refractory TLE (132 males and 88 females, age 23.0(20.0, 30.2) years)) in the First Affiliated Hospital of Jinan University between January 2014 and June 2020. ResNet was used to perform high-throughput feature extraction on preprocessed PET images and clinical features, and to perform a postoperative recurrence prediction task for differentiating patients with TLE. The predictive performance of ResNet model was evaluated by ROC curve analysis, and the AUC was compared with that of classical Cox proportional risk model using Delong test. Results:Based on PET images combined with clinical feature training, AUCs of the ResNet in predicting 12-, 24-, and 36-month postoperative recurrence were 0.895±0.073, 0.861±0.058 and 0.754±0.111, respectively, which were 0.717±0.093, 0.697±0.081 and 0.645±0.087 for Cox proportional hazards model respectively ( z values: -3.00, -2.98, -1.09, P values: 0.011, 0.018, 0.310). The ResNet showed best predictive effect for recurrence events within 12 months after surgery. Conclusion:The ResNet model is expected to be used in clinical practice for postoperative follow-up of patients with TLE, helping for risk stratification and individualized management of postoperative patients.

Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of national bloodstream infection Bacterial Resistant Investigation Collaborative System（BRICS）were collected during January 2022 to December 2022. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute（CLSI）. WHONET 5.6 and SPSS 25.0 software were used to analyze the data.Results:During the study period，9 035 strains of Gram-negative bacteria were collected from 51 hospitals，of which 7 895（87.4%）were Enterobacteriaceae and 1 140（12.6%）were non-fermenting bacteria. The top 5 bacterial species were Escherichia coli（ n=4 510，49.9%）， Klebsiella pneumoniae（ n=2 340，25.9%）， Pseudomonas aeruginosa（ n=534，5.9%）， Acinetobacter baumannii complex（ n=405，4.5%）and Enterobacter cloacae（ n=327，3.6%）. The ESBLs-producing rates in Escherichia coli， Klebsiella pneumoniae and Proteus spp. were 47.1%（2 095/4 452），21.0%（427/2 033）and 41.1%（58/141），respectively. The prevalence of carbapenem-resistant Escherichia coli（CREC）and carbapenem-resistant Klebsiella pneumoniae（CRKP）were 1.3%（58/4 510）and 13.1%（307/2 340）；62.1%（36/58）and 9.8%（30/307）of CREC and CRKP were resistant to ceftazidime/avibactam combination，respectively. The prevalence of carbapenem-resistant Acinetobacter baumannii（CRAB）complex was 59.5%（241/405），while less than 5% of Acinetobacter baumannii complex was resistant to tigecycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa（CRPA）was 18.4%（98/534）. There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of main Gram-negative bacteria resistance among different regions，with statistically significant differences in the prevalence of CRKP and CRPA（ χ2=20.489 and 20.252， P<0.001）. The prevalence of CREC，CRKP，CRPA，CRAB，ESBLs-producing Escherichia coli and Klebsiella pneumoniae were higher in provinicial hospitals than those in municipal hospitals（ χ2=11.953，81.183，10.404，5.915，12.415 and 6.459， P<0.01 or <0.05），while the prevalence of CRPA was higher in economically developed regions（per capita GDP ≥ 92 059 Yuan）than that in economically less-developed regions（per capita GDP <92 059 Yuan）（ χ2=6.240， P=0.012）. Conclusions:The proportion of Gram-negative bacteria in bloodstream infections shows an increasing trend，and Escherichia coli is ranked in the top，while the trend of CRKP decreases continuously with time. Decreasing trends are noted in ESBLs-producing Escherichia coli and Klebsiella pneumoniae. Low prevalence of carbapenem resistance in Escherichia coli and high prevalence in CRAB complex have been observed. The composition ratio and antibacterial spectrum of bloodstream infections in different regions of China are slightly different，and the proportion of main drug resistant bacteria in provincial hospitals is higher than those in municipal hospitals.

177Lu-prostate specific membrane antigen(PSMA)radio-ligand therapy has been approved abroad for advanced prostate cancer and has been in several clinical trials in China.Based on domestic clinical practice and experimental data and referred to international experience and viewpoints,the expert group forms a consensus on the clinical application of 177Lu-PSMA radio-ligand therapy in prostate cancer to guide clinical practice.

Pneumococcal vaccine plays a key role in preventing diseases such as pneumonia and meningitis caused by Streptococcus pneumoniae(S.pneumoniae).Capsular polysaccharide,C-polysaccharide and phosphorus content are important indicators for quality control of polysaccharide antigens in vaccine development and production.In this study,a quantitative 1H NMR and 31P NMR method based on a single internal standard hexamethylphosphoramide(HMPA)was developed to achieve simultaneous determination of capsular polysaccharide,C-polysaccharide and phosphorus content in 6A,6B,18C,19A,19F and 23F S.pneumoniae polysaccharide antigens.Using the internal reference comparison method,the effect of solubility of polysaccharide on quantitative 1H NMR determination was investigated.It was found that the determination results of quantitative 1H NMR were affected by the viscosity and concentration of polysaccharide solution.It was found that high viscosity polysaccharides at 3-15 mg/mL and low viscosity polysaccharides at 5-25 mg/mL were the optimal detection solution concentration range.This"one internal standard three quantitative"NMR method has good precision,specificity and accuracy,and provides a valuable new strategy for the quality control of pneumococcal vaccine.

Objectives:To investigate the impact of baseline non-high-density lipoprotein cholesterol(non-HDL-C)levels on new-onset cardiovascular disease(CVD)in postmenopausal women. Methods:This prospective cohort study selected 8 893 postmenopausal women who participated from 2006 to 2018 employee health examination of Kailuan Group and had complete total cholesterol(TC)and HDL-C data and no history of CVD.Participants were followed up to 31 December,2021.The primary endpoint was the occurrence of CVD or death.According to the Chinese Lipid Management Guidelines(2023),the participants were divided into non-HDL-C<4.1 mmol/L group(n=6 079),4.1 mmol/L≤non-HDL-C<4.9 mmol/L group(n=1 824)and non-HDL-C≥4.9 mmol/L group(n=990).The cumulative incidence of CVD in different groups of non-HDL-C levels was calculated using the Kaplan-Meier method and tested by log-rank analysis.Multivariate Cox regression model was used to analyze the effects of different non-HDL-C levels on CVD. Results:The mean follow-up time was(10.78±4.48)years,the cumulative incidence of CVD in different non-HDL-C level groups was 1.82%,3.24%and 2.89%,respectively.Kaplan-Meier survival curve showed a statistically significant difference in cumulative incidence among the three groups(log-rank P<0.0001).The results of Cox regression analysis showed that after adjusting for confounding factors such as age and sex,the HR(95%CI)values for CVD in the 4.1≤non-HDL-C<4.9 mmol/L group and the non-HDL-C≥4.9 mmol/L group were 1.40(1.13-1.74)and 1.35(1.03-1.78),respectively. Conclusions:High non-HDL-C levels are an independent risk factor for new-onset CVD in postmenopausal women.