Age-related macular degeneration(ARMD)is a progressive visual impairment fundus disease that frequently occurs in individuals aged >55 years. The main risk factors are aging, long-term smoking, genetics, and racial differences. Pathogenesis includes abnormal function of the retinal pigment epithelium, damaged blood-retinal barrier, and abnormal immune function. Currently, intravitreal injection(IVI)of anti-vascular endothelial growth factor(VEGF)drugs is the preferred treatment option for ARMD in clinical practice. However, it also faces challenges such as repeated treatments, high medical costs, and poor patient compliance. The predicament in the treatment of ARMD has given rise to several new treatment options. This article aims to review the treatment methods and progress of dry ARMD and wet ARMD, providing new ideas for addressing the limitations of the current clinical anti-VEGF treatment.

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*

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.

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

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*

Objective To investigate the role and mechanism of inflammatory marker C5a in regulating the polarization of M2 macro-phages as well as its clinical application value in the prognosis evaluation of lung cancer.Methods The phorbol 12-myristate 13-ace-tate(PMA)-pulsed human monocytic leukemia cell line THP-1 was stimulated with C5a for 0,6,12,24,and 48 h or 0,1,2,3,6,and 12 h,and then the expression levels of M2 markers CD163 and CD206 mRNA were determined by real-time fluorescence quantita-tive PCR(qRT-PCR).The expression level of general control non-repressed protein 5(GCN5)with histone acetyltransferase(HAT)activity was detected by Western blot.Co-immunoprecipitation(co-IP)was used to determine the acetylation of GATA binding protein 3(GATA3),a key transcription factor for macrophages,and its binding ability to GCN5 and E1A binding protein p300(Ep300/p300).After the macrophages pre-treated with GCN5 inhibitor butyrolactone 3(MB-3)were stimulated with C5a,the expression levels of CD163 and CD206,acetylation of GATA3,and its binding ability to GCN5 were determined by Western blot and co-IP.The clinical significance of the expression of C5a receptor 1(C5aR1)and GCN5 in lung cancer tissues in the prognosis of lung cancer patients was analyzed using the KM plotter database.Results C5a could significantly increase the expression levels of CD163 and CD206 mRNA,expression of GCN5,acetylation of GATA3,and its binding ability to GCN5 in PMA-induced adherent macrophages,but did not affect the binding of GATA3 to p300.Inhibiting the activity of GCN5 not only significantly reduced the acetylation of GATA3 and its binding ability to GCN5,but also down-regulated the expressions of CD163 and CD206.The overall survival rate of lung cancer patients with high expression of C5aR1 or GCN5 was significantly reduced.Conclusion C5a promotes the polarization of M2 macrophages by indu-cing GCN5 to acetylate GATA3.The expressions of C5aR1 and GCN5 in lung cancer tissues may have certain clinical application value for the prognosis of the patients.

Objective To analyze the correlation between lesion volume,lesion mass,and maximum lesion diameter in the assessment of advanced hepatocarcinoma with lung metastasis,and to evaluate the application value of total volume response and total mass response of lung metastatic lesions in efficacy assessment.Methods A retrospective analysis was conducted on the CT imaging data of 20 patients clinically confirmed with hepatocarcinoma and lung metastases,followed by subsequent follow-up to monitor their survival outcomes.Volume measurement software was used to measure the volume of lesions before and after treatment.We recored lesion diameter,volume measurements and CT values,calculated the mass of the lesions.The correlation between lesion volume,mass and diameter was analyzed,as well as the correlation between the change rates of volume,mass and lesion diameter.Additionally,the total volume and total mass of all lesions were calculated.The correlation between the change rates of total volume/total mass and the change rate of pulmonary lesion diameter under the RECIST 1.1 criteria,as well as the correlation with changes in patients'tumor markers,were analyzed.Furthermore,the overall volume response and overall mass response of lesions were evaluated based on changes in total volume and total mass,and their consistencies with the RECIST 1.1 criteria for efficacy evaluation were analyzed.Finally,univariate Cox regression analysis was performed to explore the association between these variables and patient survival outcomes.Results There was strong correlation between lesion volume,mass and tumor diameter(r=0.771,0.775),between the rate of change in mass and the rate of change in lesion diameter(r=0.846),and between the rates of change in total volume/total mass and the rate of change in pulmonary lesion diameter under the RECIST 1.1 criteria(r=0.800,0.896).The correlation between the rates of change in total volume/total mass and patients'tumor markers was not statistically significant.There was moderate correlation between the rate of change in volume and the rate of change in lesion diameter(r=0.692).The evaluation results of total volume response and total mass response for pulmonary lesions in advanced hepatocarcinoma with lung metastasis were generally consistent with the RECIST 1.1 criteria(Kappa=0.486,0.426).Univariate Cox regression analysis revealed that total lesion volume(P=0.047)and total lesion mass(P=0.049)were independent prognostic factors for survival outcomes.Conclusion Lesion volume,mass,and diameter,as well as their respective change rates,were found to be interrelated.Furthermore,total lesion volume and total lesion mass were identified as independent prognostic factors for survival outcomes.The total volume response and total mass response are promising evaluation methods in evaluating the efficacy of lung metastasis of hepatocarcinoma,which are different from the RECIST 1.1 evaluation criteria.

Oropharyngeal squamous cell carcinoma(OPSCC)is a malignant tumor originating from the squamous epithelium of the oro-pharyngeal mucosa,accounting for more than 90％of oropharyngeal malignancies.In recent years,human papillomavirus(HPV)infec-tion has become one of the primary etiological factors of oropharyngeal squamous carcinoma.The incidence of HPV-associated oropharyn-geal squamous carcinoma has been rising annually,with a noticeable trend toward younger populations,posing a significant threat to hu-man health.Due to the distinct biological behavior and clinical characteristics of HPV-associated oropharyngeal squamous carcinoma com-pared to its non-HPV-related counterpart,the diagnostic and treatment strategies for oropharyngeal squamous carcinoma have undergone substantial changes.Prevention and screening for oropharyngeal squamous carcinoma are of critical importance.The diagnostic and treat-ment process involves multi-disciplinary collaboration,including oral and maxillofacial surgery,otolaryngology,head and neck surgery,oncology,radiology and pathology.Based on evidence from clinical practice,a comprehensive,integrated diagnostic and therapeutic ap-proach has been established,centered around the concept of"prevention,screening,diagnosis,treatment,and rehabilitation",covering the entire patient lifecycle and providing a valuable reference for clinical practice.