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.

BACKGROUND: Treatment with chimeric antigen receptor-T (CAR-T) cells has shown promising effectiveness in patients with relapsed/refractory B-cell acute lymphoblastic leukemia (R/R B-ALL), although the process of preparing for this therapy usually takes a long time. We have recently created CD19 Fast-CAR-T (F-CAR-T) cells, which can be produced within a single day. The objective of this study was to evaluate and contrast the effectiveness and safety of CD19 F-CAR-T cells with those of CD19 conventional CAR-T cells in the management of R/R B-ALL. METHODS: A multicenter, retrospective analysis of the clinical data of 44 patients with R/R B-ALL was conducted. Overall, 23 patients were administered with innovative CD19 F-CAR-T cells (F-CAR-T group), whereas 21 patients were given CD19 conventional CAR-T cells (C-CAR-T group). We compared the rates of complete remission (CR), minimal residual disease (MRD)-negative CR, leukemia-free survival (LFS), overall survival (OS), and the incidence of cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) between the two groups. RESULTS: Compared with the C-CAR-T group, the F-CAR-T group had significantly higher CR and MRD-negative rates (95.7% and 91.3%, respectively; 71.4% and 66.7%, respectively; P = 0.036 and P = 0.044). No significant differences were observed in the 1-year or 2-year LFS or OS rates between the two groups: the 1-year and 2-year LFS for the F-CAR-T group vs.C-CAR-T group were 47.8% and 43.5% vs. 38.1% and 23.8% (P = 0.384 and P = 0.216), while the 1-year and 2-year OS rates were 65.2% and 56.5% vs. 52.4% and 47.6% (P = 0.395 and P = 0.540). Additionally, among CR patients who underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT) following CAR-T-cell therapy, there were no significant differences in the 1-year or 2-year LFS or OS rates: 57.1% and 50.0% vs. 47.8% and 34.8% (P = 0.506 and P = 0.356), 64.3% and 57.1% vs. 65.2% and 56.5% (P = 0.985 and P = 0.883), respectively. The incidence of CRS was greater in the F-CAR-T group (91.3%) than in the C-CAR-T group (66.7%) (P = 0.044). The incidence of ICANS was also greater in the F-CAR-T group (30.4%) than in the C-CAR-T group (9.5%) (P = 0.085), but no treatment-related deaths occurred in the two groups. CONCLUSION Compared with C-CAR-T-cell therapy, F-CAR-T-cell therapy has a superior remission rate but also leads to a tolerably increased incidence of CRS/ICANS. Further research is needed to explore the function of allo-HSCT as an intermediary therapy after CAR-T-cell therapy.

A primary hallmark of pathological cardiac hypertrophy is excess protein synthesis due to enhanced translational activity. However, regulatory mechanisms at the translational level under cardiac stress remain poorly understood. Here we examined the translational regulations in a mouse cardiac hypertrophy model induced by transaortic constriction (TAC) and explored the conservative networks versus the translatome pattern in human dilated cardiomyopathy (DCM). The results showed that the heart weight to body weight ratio was significantly elevated, and the ejection fraction and fractional shortening significantly decreased 8 weeks after TAC. Puromycin incorporation assay showed that TAC significantly increased protein synthesis rate in the left ventricle. RNA-seq revealed 1,632 differentially expressed genes showing functional enrichment in pathways including extracellular matrix remodeling, metabolic processes, and signaling cascades associated with pathological cardiomyocyte growth. When combined with ribosome profiling analysis, we revealed that translation efficiency (TE) of 1,495 genes was enhanced, while the TE of 933 genes was inhibited following TAC. In DCM patients, 1,354 genes were upregulated versus 1,213 genes were downregulated at the translation level. Although the majority of the genes were not shared between mouse and human, we identified 93 genes, including Nos3, Kcnj8, Adcy4, Itpr1, Fasn, Scd1, etc., with highly conserved translational regulations. These genes were remarkably associated with myocardial function, signal transduction, and energy metabolism, particularly related to cGMP-PKG signaling and fatty acid metabolism. Motif analysis revealed enriched regulatory elements in the 5' untranslated regions (5'UTRs) of transcripts with differential TE, which exhibited strong cross-species sequence conservation. Our study revealed novel regulatory mechanisms at the translational level in cardiac hypertrophy and identified conserved translation-sensitive targets with potential applications to treat cardiac hypertrophy and heart failure in the clinic.
Animals ; Humans ; Cardiomegaly/physiopathology* ; Ribosomes/physiology* ; Protein Biosynthesis/physiology* ; Mice ; Cardiomyopathy, Dilated/genetics* ; Ribosome Profiling

Astragalus membranaceus(A. membranaceus), a traditional tonic, contains flavonoids as one of its main bioactive components and key indicators for quality standard detection. These compounds predominantly exist in glycosylated forms after glycosylation modification within the plant. The catalytic products of flavonoid glycosyltransferases in A. membranaceus have been reported to be mostly monoglycosides, and only AmUGT28 catalyzes luteolin to form diglycosides. In this study, we cloned a glycosyltransferase gene, AmGT90, from A. membranaceus, with an ORF length of 1 335 bp, encoding 444 amino acids, and the protein had a relative molecular mass of 50.5 kDa. Phylogenetic tree analysis indicated that AmGT90 belongs to the UGT74 family. In vitro enzymatic reaction showed that AmGT90 had broad substrate specificity and could catalyze the glycosylation of various flavonoids, including isoflavones, flavones, flavanones, and chalcones. AmGT90 not only catalyzed the formation of monoglycosides but also diglycosides. In addition, the mechanism of AmGT90 catalyzing the formation of diglycosides from luteolin was preliminarily explored. The experimental results showed that AmGT90 may preferentially recognize C4'-OH of luteolin and then recognize C7-OH to form diglycosides. This study reported a glycosyltransferase from A. membranaceus capable of converting flavonoids into monoglycosides and diglycosides. This finding not only enhances our understanding of the biosynthetic pathways of flavonoid glycosides in A. membranaceus but also introduces a new component for glycoside production through synthetic biology.
Glycosyltransferases/chemistry* ; Flavonoids/chemistry* ; Astragalus propinquus/classification* ; Phylogeny ; Glycosylation ; Plant Proteins/chemistry* ; Substrate Specificity ; Cloning, Molecular ; Amino Acid Sequence

This paper explored the specific mechanism of ginsenoside Rg_1 in regulating mitochondrial fusion through the neurogenic gene Notch homologous protein 1(Notch1) pathway to alleviate hypoxia/reoxygenation(H/R) injury in HL-1 cells. The relative viability of HL-1 cells after six hours of hypoxia and two hours of reoxygenation was detected by cell counting kit-8(CCK-8). The lactate dehydrogenase(LDH) activity in the cell supernatant was detected by the lactate substrate method. The content of adenosine triphosphate(ATP) was detected by the luciferin method. Fluorescence probes were used to detect intracellular reactive oxygen species(Cyto-ROS) levels and mitochondrial membrane potential(ΔΨ_m). Mito-Tracker and Actin were co-imaged to detect the number of mitochondria in cells. Fluorescence quantitative polymerase chain reaction and Western blot were used to detect the mRNA and protein expression levels of Notch1, mitochondrial fusion protein 2(Mfn2), and mitochondrial fusion protein 1(Mfn1). The results showed that compared with that of the control group, the cell activity of the model group decreased, and the LDH released into the cell culture supernatant increased. The level of Cyto-ROS increased, and the content of ATP decreased. Compared with that of the model group, the cell activity of the ginsenoside Rg_1 group increased, and the LDH released into the cell culture supernatant decreased. The level of Cyto-ROS decreased, and the ATP content increased. Ginsenoside Rg_1 elevated ΔΨ_m and increased mitochondrial quantity in HL-1 cells with H/R injury and had good protection for mitochondria. After H/R injury, the mRNA and protein expression levels of Notch1 and Mfn1 decreased, while the mRNA and protein expression levels of Mfn2 increased. Ginsenoside Rg_1 increased the mRNA and protein levels of Notch1 and Mfn1, and decreased the mRNA and protein levels of Mfn2. Silencing Notch1 inhibited the action of ginsenoside Rg_1, decreased the mRNA and protein levels of Notch1 and Mfn1, and increased the mRNA and protein levels of Mfn2. In summary, ginsenoside Rg_1 regulated mitochondrial fusion through the Notch1 pathway to alleviate H/R injury in HL-1 cells.
Ginsenosides/pharmacology* ; Receptor, Notch1/genetics* ; Signal Transduction/drug effects* ; Mice ; Animals ; Mitochondrial Dynamics/drug effects* ; Mitochondria/metabolism* ; Cell Line ; Reactive Oxygen Species/metabolism* ; Oxygen/metabolism* ; Cell Hypoxia/drug effects* ; Cell Survival/drug effects* ; Membrane Potential, Mitochondrial/drug effects* ; Humans

The quality of traditional Chinese medicine(TCM) is a critical foundation for ensuring the stability of its efficacy, as well as the safety and effectiveness of its clinical use. The identification of critical quality attributes(CQAs) is one of the core components of TCM preparation quality control. This study focuses on Jianwei Xiaoshi Tablets and explores their CQAs related to property and flavor from the perspective of taste receptor proteins. Three taste receptor proteins, T1R2, T1R3, and TRPV1, were selected, and a biosensor based on high-electron-mobility transistor(HEMT) was constructed to detect the interactions between Jianwei Xiaoshi Tablets and taste receptor proteins. Simultaneously, liquid chromatography-mass spectrometry(LC-MS) technology was used to analyze the chemical composition of Jianwei Xiaoshi Tablets. In examining the interaction strength, the results indicated that the interaction between Jianwei Xiaoshi Tablets and TRPV1 protein was the strongest, followed by T1R3, with the interaction with T1R2 being relatively weaker. By combining biosensing technology with LC-MS, 16 chemical components were identified from Jianwei Xiaoshi Tablets, among which six were selected as CQAs for sweetness and seven for pungency. Further validation experiments demonstrated that CQAs such as hesperidin and hesperetin had strong interactions with their corresponding taste receptor proteins. Through the combined use of multiple technological approaches, this study successfully determined the property and flavor-related CQAs of Jianwei Xiaoshi Tablets. It provides novel ideas and approach for the identification of CQAs in TCM preparations and offers comprehensive theoretical support for TCM quality control, contributing to the improvement and development of TCM preparation quality control systems.
Drugs, Chinese Herbal/chemistry* ; Biosensing Techniques/methods* ; TRPV Cation Channels/chemistry* ; Tablets/chemistry* ; Receptors, G-Protein-Coupled/genetics* ; Quality Control ; Taste ; Humans ; Mass Spectrometry

OBJECTIVE: To investigate the effects of bone density, plate bending degree and proximal screw type on the stress fracture of clavicle hook. METHODS: Three sows weighing between 45 and 50 kg were selected, from which a total of 40 rivs were collected. The 15 ribs of sows were divided into 3 groups according to bone density and bone hardness with 5 rivs in each group. And then the 3 groups were fixed with 6-hole collarbone hook plates and 3 locking screws. Measure the maximum torsion force when the ribs were fractured by force. The same size 15 rids were divided into 3 groups, named forward bending group, 0° group(the angle between the plate surface and the rib surface) and reverse bending group. All fixed with 6-hole collarbone hook plates and locking screws to measure the maximum torsion force of rib stress fracture. Then the same size 10 rids were divided into 2 groups, the normal screw group and the locking screw group with 5 ribs in each group. Both groups were fixed with 6-hole collarbone hook plates and screws. The normal screw group was a normal screw, fixed in proximal end, and two locking screws. The locking screw group was fixed by locking screws. Measure the maximum torsion force of the two groups when the ribs fracture by force. RESULTS: In the bone density experiment, the torque force of hard bone group (104.51±6.27) N was greater than the normal bone group (75.04±3.81) N(t=8.979, P<0.05). The force of normal bone group was greater than the osteoporosis group (49.99±2.12) N(t=12.832, P<0.05). In the bending collarbone hook experiment, the order of the torque force generated by each group as follow:the forward bending group (343.59±6.18) N greater than the 0° group (106.01±5.29) N(t=65.279, P<0.05) greater than the reverse bending group (95.82±4.12) N(t=3.398, P<0.05). The force of the normal screw group (98.68±0.70) N was greater than the locking screw group (50.20±0.95) N(t=91.484, P<0.05). The data comparisons of each group were statistically significant. CONCLUSION Bone density, plate bending degree and proximal screw type had an impact on stress fracture of clavicle hook plate. Higher bone density, forward bending of the steel plate, and ordinary screws in proximal end can reduce the rates of stress fractures of clavicle hooks.
Animals ; Bone Plates ; Clavicle/surgery* ; Swine ; Fractures, Stress/etiology* ; Female ; Risk Factors ; Fracture Fixation, Internal/instrumentation* ; Bone Screws ; Biomechanical Phenomena ; Bone Density

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