Objective To explore the application of plasma 7 microRNA (miR7) testing in the differential diagnosis of very early-stage hepatocellular carcinoma (HCC). Methods This study is a multicenter real-world study. Patients with single hepatic lesion (maximum diameter≤2 cm) who underwent plasma miR7 testing at Zhongshan Hospital, Fudan University, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Anhui Provincial Hospital, and Peking University People’s Hospital between January 2019 and December 2024 were retrospectively enrolled. Patients were divided into very early-stage HCC group and non-HCC group, and the clinical pathological characteristics of the two groups were compared. The value of plasma miR7 levels, alpha-fetoprotein (AFP), and des-gamma-carboxy prothrombin (DCP) in the differential diagnosis of very early-stage HCC was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). In patients with both negative AFP and DCP (AFP＜20 ng/mL, DCP＜40 mAU/mL), the diagnostic value of plasma miR7 for very early-stage HCC was analyzed. Results A total of 64 528 patients from 4 hospitals underwent miR7 testing, and 1 682 were finally included, of which 1 073 were diagnosed with very early-stage HCC and 609 were diagnosed with non-HCC. The positive rate of miR7 in HCC patients was significantly higher than that in non-HCC patients (67.9% vs 24.3%, P＜0.001). ROC curves showed that the AUCs for miR7, AFP, and DCP in distinguishing HCC patients from the non-HCC individuals were 0.718, 0.682, and 0.642, respectively. The sensitivities were 67.85%, 43.71%, and 44.45%, and the specificities were 75.70%, 92.78%, and 83.91%, respectively. The pairwise comparison of AUCs showed that the diagnostic efficacy of plasma miR7 detection was significantly better than that of AFP or DCP (P＜0.05). Although its specificity was slightly lower than AFP and DCP, the sensitivity was significantly higher. Among patients negative for both AFP and DCP, miR7 maintained an AUC of 0.728 for diagnosing very early-stage HCC, with 67.82% sensitivity and 77.73% specificity. Conclusions Plasma miR7 testing is a potential molecular marker with high sensitivity and specificity for the differential diagnosis of small hepatic nodules. In patients with very early-stage HCC lacking effective molecular markers (negative for both AFP and DCP), miR7 can serve as a novel and effective molecular marker to assist diagnosis.

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.

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

According to the principle and current domestic and international construction processes of core outcome set(COS) and the characteristics of post-stroke aphasia, this study built COS with evidence-based support for traditional Chinese medicine(TCM) treatment of post-stroke aphasia. Firstly, a comprehensive review was conducted on the articles about the TCM treatment of post-stroke aphasia that were published in the four major Chinese databases, three major English databases, and three clinical registration centers over the past five years. The articles were analyzed and summarized, on the basis of which the main part of the COS for clinical research on the TCM treatment of post-stroke aphasia was formed. Secondly, clinical doctors and related nursing personnel were interviewed, and important outcome indicators in the clinical diagnosis and treatment process were supplemented to form a pool of core outcome indicators. Two rounds of Delphi surveys were carried out to score the importance of the core outcome indicators in the pool. Finally, a consensus meeting of experts was held to establish the COS for clinical research on the TCM treatment of post-stroke aphasia. The final COS included a total of 268 studies [236 randomized controlled trials(RCTs), 21 Meta-analysis, and 11 clinical registration protocols] and 20 open questionnaire survey results. After two rounds of Delphi surveys, a total of 14 outcome indicators and their corresponding measurement tools were included in the expert consensus meeting. The final expert consensus meeting determined the COS for post-stroke aphasia, which included 9 indicator domains and 12 outcome indicators.
Humans ; Aphasia/therapy* ; Stroke/complications* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/therapeutic use* ; Treatment Outcome

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

This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*

OBJECTIVES: To investigate the prognostic value of molecular minimal residual disease (Mol-MRD) monitored before and after allogeneic hematopoietic stem cell transplantation (HSCT) in pediatric acute myeloid leukemia (AML). METHODS: Clinical data of 71 pediatric AML patients who underwent HSCT between August 2016 and December 2023 were analyzed. Mol-MRD levels were dynamically monitored in MRD-positive patients, and survival outcomes were evaluated. RESULTS: No significant difference in the 3-year overall survival (OS) rate was observed between patients with pre-HSCT Mol-MRD ≥0.01% and <0.01% (77.3% ± 8.9% vs 80.4% ± 7.9%, P=0.705). However, patients with pre-HSCT Mol-MRD <1.75% had a significantly higher 3-year OS rate than those with Mol-MRD ≥1.75% (86.6% ± 5.6% vs 44.4% ± 16.6%, P=0.020). The median Mol-MRD level in long-term survivors was significantly lower than in non-survivors [0.61% (range: 0.04%-51.58%)] vs 10.60% (range: 1.90%-19.75%), P=0.035]. Concurrent flow cytometry-based MRD positivity was significantly higher in non-survivors (80% vs 24%, P=0.039). There was no significant difference in the 3-year overall survival rate between patients with Mol-MRD ≥0.01% and those with <0.01% at 30 days post-HSCT (P=0.527). For children with Mol-MRD <0.22% at 30 days post-HSCT, the 3-year overall survival rate was 80.4% ± 5.9%, showing no significant difference compared to those with molecular negativity (87.0% ± 7.0%) (P=0.523). CONCLUSIONS Patients with pre-HSCT Mol-MRD <1.75% or post-HSCT Mol-MRD <0.22% may achieve long-term survival outcomes comparable to Mol-MRD-negative cases through HSCT and targeted interventions.
Humans ; Hematopoietic Stem Cell Transplantation ; Neoplasm, Residual ; Leukemia, Myeloid, Acute/genetics* ; Child ; Male ; Female ; Child, Preschool ; Prognosis ; Adolescent ; Infant ; Transplantation, Homologous

OBJECTIVE: To investigate the influencing factors of pathological positive surgical margins (PSM) after radical resection of prostate cancer. METHODS: The clinical data of 407 patients who underwent radical resection of prostate cancer in our hospital from 2011 to 2020 were retrospectively analyzed. And the patients were divided into two groups according to postoperative pathological results. Single factor analysis was used to evaluate the differences in postoperative Gleason score, preoperative total prostate-specific antigen (tPSA), preoperative serum free prostate-specific antigen to preoperative tPSA ratio (fPSA/ tPSA), clinical stage, postoperative pathological stage, operation method, age, body mass index (BMI), diameter and volume of prostate tumor. Multivariate logistic regression was used to determine the independent risk factor of PSM. RESULTS: Among 407 patients with prostate cancer, 179 cases (43.98%) were positive. Univariate analysis showed that there were significant differences in postoperative Gleason score, preoperative tPSA, clinical stage and postoperative pathological stage between the two groups (P<0.05). And Gleason score, preoperative tPSA and pathologic stage were independent risk factors for PSM. CONCLUSION There are relationships between PSM and postoperative Gleason score, tPSA, clinical T stage, postoperative pathologic pT stage. Among them, postoperative Gleason score (Gleason=7 points, Gleason≥8 points), preoperative total prostate-specific antigen (tPSA > 20 μg/L), and postoperative pathologic pT stage (pT3a, pT3b) were independent risk factors for positive pathological margins of prostate cancer.
Margins of Excision ; Prostatic Neoplasms/surgery* ; Prostatectomy/statistics & numerical data* ; Prostate/surgery* ; Retrospective Studies ; Neoplasm Grading/statistics & numerical data* ; Prostate-Specific Antigen/blood* ; Neoplasm Staging/statistics & numerical data* ; Postoperative Period ; Risk Factors ; Humans ; Male

T-cell acute lymphoblastic leukemia (T-ALL) is a highly aggressive hematologic malignancy with a poor prognosis, despite advancements in treatment. Many patients struggle with relapse or refractory disease. Investigating the role of the super-enhancer (SE) regulated gene ubiquitin-specific protease 20 (USP20) in T-ALL could enhance targeted therapies and improve clinical outcomes. Analysis of histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) data from six T-ALL cell lines and seven pediatric samples identified USP20 as an SE-regulated driver gene. Utilizing the Cancer Cell Line Encyclopedia (CCLE) and BloodSpot databases, it was found that USP20 is specifically highly expressed in T-ALL. Knocking down USP20 with short hairpin RNA (shRNA) increased apoptosis and inhibited proliferation in T-ALL cells. In vivo studies showed that USP20 knockdown reduced tumor growth and improved survival. The USP20 inhibitor GSK2643943A demonstrated similar anti-tumor effects. Mass spectrometry, RNA-Seq, and immunoprecipitation revealed that USP20 interacted with hypoxia-inducible factor 1 subunit alpha (HIF1A) and stabilized it by deubiquitination. Cleavage under targets and tagmentation (CUT&Tag) results indicated that USP20 co-localized with HIF1A, jointly modulating target genes in T-ALL. This study identifies USP20 as a therapeutic target in T-ALL and suggests GSK2643943A as a potential treatment strategy.

OBJECTIVES: To investigate the active components and possible mechanisms of n-butanol fraction of Periploca forrestii Schltr. ethanol extract for treating Alzheimer's disease (AD). METHODS: The active components of n-butanol fraction of Periploca forrestii Schltr. ethanol extract were analyzed using UPLC-QE-MS technique. In a SD rat model of AD induced by treatment with AlCl₃ and D-gal, the therapeutic effects of low, moderate and high doses of the n-butanol fraction, saline, and donepezil hydrochloride were evaluated using ELISA, HE and Nissl staining, immunohistochemistry and Western blotting. The therapeutic mechanisms of the n-butanol fraction were explored using network pharmacology and molecular docking. RESULTS: Seventeen active components were identified from the n-butanol fraction of Periploca forrestii Schltr. ethanol extract, including phenylpropanoids, flavonoids, anthraquinones, triterpenoids, steroids, and volatile oils. In the rat models of AD, treatment with the n-butanol fraction significantly lowed AChE content in the hippocampus, increased the contents of ACh, SOD, CAT, and GSH-Px, enhanced the expressions of neuronal apoptotic factors Bcl-2, PI3K, Akt, p-PI3K, and p-Akt, and reduced the expressions of Bax and caspase-3 proteins. The treatment also dose-dependently up-regulated hippocampal expressions of Nrf-2, HO-1 and BDNF and down-regulated Keap-1, Aβ and Tau expressions. Bioinformatics analysis identified 14 key intersected targets (including TNF, AKT1 and ESR1) between the n-butanol fraction and AD. CONCLUSIONS The therapeutic effect of n-butanol fraction of Periploca forrestii Schltr. ethanol extract in AD mice is mediated by its multiple active components that regulate multiple targets and pathways.
Animals ; Rats, Sprague-Dawley ; Rats ; 1-Butanol/chemistry* ; Plant Extracts/pharmacology* ; Periploca/chemistry* ; Ethanol/chemistry* ; Alzheimer Disease/drug therapy* ; Male ; Molecular Docking Simulation ; Apoptosis/drug effects*