Alzheimer's disease （AD） is a common type of dementia， primarily characterized by cognitive and behavioral impairments as well as deficits in learning and memory. The progression of AD has imposed a significant economic burden on society and families. However， its exact pathogenesis has not yet been fully elucidated. Currently， available therapeutic drugs are limited and are often accompanied by serious adverse effects. Traditional Chinese medicines （TCMs） and their extracts are mostly natural products and possess advantages such as multi-pathway regulation and relatively few adverse reactions. Experimental studies have shown that TCMs exhibit great potential in the prevention and treatment of AD. For example， Huanglian Jieduang， Danggui Shaoyaosan， Kaixin San， Liuwei Dihuangwan， Buyang Huanwutang， as well as Ginseng Radix et Rhizoma， Astragali Radix， Uncariae Ramulus cum Uncis， Coptidis Rhizoma， Gardeniae Fructus， Ginkgo Folium， Salviae Miltiorrhizae Radix et Rhizoma， and Curcumae Longae Rhizoma， can reduce β-amyloid deposition， inhibit excessive Tau protein phosphorylation， restore mitochondrial function， alleviate oxidative stress， suppress neuroinflammation and apoptosis， repair synaptic function， and improve gut microbiota. This article mainly summarizes the effects of several TCMs and compound prescriptions on AD， aiming to provide a reference for subsequent TCM-based treatment of AD.

Background/Aims: Lenvatinib resistance remains a critical barrier in advanced hepatocellular carcinoma (HCC) therapy. However, the underlying mechanisms and strategies for reversing resistance remain incompletely understood. Methods: Integrated transcriptomics of lenvatinib-resistant patient tumors and an acquired-resistance murine model identified a novel macrophage subpopulation. Functional validation employed CRISPR-SAM screening, conditioned medium (CM) assays, subcutaneous/orthotopic xenografts, patient-derived organoids (PDOs), and patient-derived xenografts (PDXs). Mechanistic studies included ChIP-qPCR, co-immunoprecipitation, and pharmacologic targeting. Clinical relevance was assessed in a retrospective cohort. Results: Resistant HCC exhibited significant enrichment of a COLEC12high TAM subset , which correlated with poor survival and treatment response. These TAMs secreted neuregulin-1 (NRG1) , activating HER2/HER3-AKT signaling in tumor cells to drive cancer stemness and lenvatinib resistance. Mechanistically, in TAMs COLEC12 sequestered STAT1 in the cytoplasm, preventing its phosphorylation, and thereby derepressing STAT3-mediated NRG1 transcription. Depletion of NRG1 reversed the stemness phenotypes and resensitized tumors to lenvatinib both in vitro and in vivo. Clinically, high NRG1 expression predicted an inferior lenvatinib response and shorter survival. Crucially, the bispecific anti-HER2/HER3 antibody zenocutuzumab restored lenvatinib efficacy in PDOs, PDXs, and murine models. Conclusions Our work establishes the COLEC12high TAM/NRG1 axis as a master regulator of therapeutic resistance and identifies NRG1 as a predictive biomarker, providing a clinically actionable strategy to overcome lenvatinib resistance in HCC.

OBJECTIVE: To evaluate the effects of Chinese patent medicine Huatuo Zaizao Pill (HTZZ) on neurological function and limb motor in ischemic stroke (IS) patients during convalescence. METHODS: This is a prospective, open-labelled, randomized controlled trial. Patients with IS were recruited from the Neurology Department of Xiyuan Hospital of China Academy of Chinese Medical Sciences from May 2021 to June 2023. Eligible participants were randomly assigned to the HTZZ (40 cases) or control group (40 cases) at a ratio of 1:1. The HTZZ group was treated with oral HTZZ (8 g, thrice daily) combined with conventional treatment, while the control group received only conventional treatment. The treatment duration was 12 weeks. The primary outcome was the change in Modified Ashworth Scale (MAS) score from baseline to week 6 and 12. Secondary outcomes included changes in scores of National Institute of Health Stroke Scale (NIHSS), Fugl-Meyer Assessment (FM), and Barthel Index (BI) from baseline to week 6 and 12, as well as lipid indices after 12 weeks. All adverse events (AEs) were recorded and liver and kidney indices were evaluated. RESULTS: A total of 72 patients completed the study (38 in the HTZZ group and 34 in the control group). Compared with the control group, the HTZZ group demonstrated significant improvements in MAS, NIHSS, FM, and BI scores following 6 and 12 weeks of treatment in both intent-to-treat and per-protocol analyses (all P<0.05). No significant differences were noted between groups in lipid indices, AEs, and liver and kidney dysfunction after 12 weeks (P>0.05). CONCLUSIONS HTZZ alleviated spasticity and enhanced neurological function and prognosis of IS patients during convalescence. However, further evaluation of HTZZ's effect on IS outcomes is warranted in clinical trials with larger sample sizes and extended observation periods. (Trial registration No. NCT04910256).
Humans ; Drugs, Chinese Herbal/pharmacology* ; Male ; Female ; Ischemic Stroke/physiopathology* ; Middle Aged ; Aged ; Recovery of Function/drug effects* ; Convalescence ; Extremities/physiopathology* ; Treatment Outcome ; Prospective Studies

The Janus kinase/signal transducers and activators of transcription (JAK-STAT) control natural killer (NK) cells development and cytotoxic functions, however, whether long non-coding RNAs (lncRNAs) are involved in this pathway remains unknown. We found that miR155HG was elevated in activated NK cells and promoted their proliferation and effector functions in both NK92 and induced-pluripotent stem cells (iPSCs)-derived NK (iPSC-NK) cells, without reliance on its derived miR-155 and micropeptide P155. Mechanistically, miR155HG bound to miR-6756 and relieved its repression of JAK3 expression, thereby promoting the JAK-STAT pathway and enhancing NK cell proliferation and function. Further investigations disclosed that upon cytokine stimulation, STAT3 directly interacts with miR155HG promoter and induces miR155HG transcription. Collectively, we identify a miR155HG-mediated positive feedback loop of the JAK-STAT signaling. Our study will also provide a power target regarding miR155HG for improving NK cell generation and effector function in the field of NK cell adoptive transfer therapy against cancer, especially iPSC-derived NK cells.

The KCNQ potassium channels play a crucial role in modulating neural excitability, and their dysfunction is closely associated with epileptic disorders. While variants in KCNQ2 have been extensively studied, KCNQ3-related disorders have rarely been reported. With advances in next-generation sequencing technologies, an increasing number of cases of KCNQ3-related disorders have been identified. However, the correlation between genotype and phenotype remains poorly understood. In this study, we established a variant library consisting of 24 missense mutations in KCNQ3 and introduced these mutations into three different template types: KCNQ3, KCNQ3-A315T (Q3*), and KCNQ3-KCNQ2 tandem (Q3-Q2). We then analyzed the effects of these mutations on the KCNQ3 channel function using patch-clamp recording. The most informative parameter across all three backgrounds was the current density of the mutant channels. The current density patterns in the Q3* and Q3-Q2 backgrounds were similar, with most mutations resulting in an almost complete loss of function (LOF), they were concentrated in the pore-forming domain of KCNQ3. In contrast, mutations in the voltage-sensing domain or C-terminus did not show significant differences from the wild-type channel. Interestingly, these LOF mutations were typically associated with self-limited familial neonatal epilepsy, while neurodevelopmental disorders (NDD) were more closely associated with mutations that did not significantly differ from the wild-type. V_1/2, another important parameter of the electrophysiological properties, could not be accurately determined in the majority of KCNQ3 mutations due to its nearly complete LOF in the Q3* and Q3-Q2 backgrounds. Intriguingly, the V_1/2 of functional mutations were primarily leftward shifted, indicating a gain-of-function (GOF) effect, which was typically associated with NDD. In addition to previously reported mutations, we identified G553R as a novel GOF mutation. In the co-transfection background, parameters such as V_1/2 could be determined, but the dysfunctional effects of these mutations were mitigated by the co-expression of wild-type KCNQ3 and KCNQ2 subunits, resulting in no significant differences between most mutations and the wild-type channel. Furthermore, we applied KCNQ modulators to reverse the electrophysiological abnormalities caused by KCNQ3 variants. The LOF mutations were reversed by the application of Pynegabine (HN37), a KCNQ opener, while the GOF mutation responded well to Amitriptyline (AMI), a KCNQ inhibitor. These findings provide essential insights into the pathogenic mechanisms underlying KCNQ3-related disorders and may inform clinical decision-making.
KCNQ3 Potassium Channel/genetics* ; Humans ; Mutation, Missense/genetics* ; KCNQ2 Potassium Channel/genetics* ; Patch-Clamp Techniques ; HEK293 Cells ; Animals ; Phenylenediamines/pharmacology* ; Carbamates

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Antibody (Ab) humanization is critical to reduce immunogenicity and enhance efficacy in the preclinical phase of the development of therapeutic Abs originated from animal models. Computational suggestions have long been desired, but available tools focused on immunogenicity calculation of whole Ab sequences and sequence segments, missing the individual residue sites. This study introduces Site-specific Immunogenicity for Therapeutic Antibody (SITA), a novel computational framework that predicts B-cell immunogenicity score for not only the overall antibody, but also individual residues, based on a comprehensive set of amino acid descriptors characterizing physicochemical and spatial features for antibody structures. A transfer-learning-inspired framework was purposely adopted to overcome the scarcity of Ab-Ab structural complexes. On an independent testing dataset derived from 13 Ab-Ab structural complexes, SITA successfully predicted the epitope sites for Ab-Ab structures with a receiver operating characteristic (ROC)-area unver the ROC curve (AUC) of 0.85 and a precision-recall (PR)-AUC of 0.305 at the residue level. Furthermore, the SITA score can significantly distinguish immunogenicity levels of whole human Abs, therapeutic Abs and non-human-derived Abs. More importantly, analysis of an additional 25 therapeutic Abs revealed that over 70% of them were detected with decreased immunogenicity after modification compared to their parent variants. Among these, nearly 66% Abs successfully identified actual modification sites from the top five sites with the highest SITA scores, suggesting the ability of SITA scores for guide the humanization of antibody. Overall, these findings highlight the potential of SITA in optimizing immunogenicity assessments during the process of therapeutic antibody design.

Computational analysis can accurately detect drug-gene interactions (DGIs) cost-effectively. However, transductive learning models are the hotspot to reveal the promising performance for unknown DGIs (both drugs and genes are present in the training model), without special attention to the unseen DGIs (both drugs and genes are absent in the training model). In view of this, this study, for the first time, proposed an inductive learning-based model for the precise identification of unseen DGIs. In our study, by integrating disease nodes to avoid data sparsity, a multi-relational drug-disease-gene (DDG) graph was constructed to achieve effective fusion of data on DDG intro-relationships and inter-actions. Following the extraction of graph features by utilizing graph embedding algorithms, our next step was the retrieval of the attributes of individual gene and drug nodes. In this way, a hybrid feature characterization was represented by integrating graph features and node attributes. Machine learning (ML) models were built, enabling the fulfillment of transductive predictions of unknown DGIs. To realize inductive learning, this study generated an innovative idea of transforming known node vectors derived from the DDG graph into representations of unseen nodes using node similarities as weights, enabling inductive predictions for the unseen DGIs. Consequently, the final model was superior to existing models, with significant improvement in predicting both external unknown and unseen DGIs. The practical feasibility of our model was further confirmed through case study and molecular docking. In summary, this study establishes an efficient data-driven approach through the proposed modeling, suggesting its value as a promising tool for accelerating drug discovery and repurposing.

Diabetic foot (DF) is one of the most serious chronic complications of diabetes. The incidence rate among global diabetes patients is as high as 15% to 25%, and about 50% of patients will develop contralateral foot ulcers within 5 years after the first unilateral ulcer. As a non-invasive prevention and control solution, the application progress of functional insoles is mainly reflected in the following aspects:(1) Material innovation. The application of new composite materials and smart materials has significantly enhanced the pressure reduction effect and comfort. (2) Structural optimization. The development of multi-layer design and local pressure reduction structure has achieved more precise pressure distribution regulation. (3) Manufacturing process. 3D printing and parametric design have enabled the personalized customization of functional insoles. (4) Intelligent monitoring. It integrates functions such as pressure sensing and temperature monitoring, achieving real-time monitoring and early warning of foot conditions. Clinical research has confirmed that personalized functional insoles could reduce the incidence of foot ulcers and shorten the healing time of ulcers. At present, the research hotspots mainly focus on the development of smart materials, the construction of multi-functional integration and remote monitoring systems. However, in-depth research is still needed in the aspects of biomechanical mechanisms, standardized evaluation systems and long-term efficacy assessment. The development of future functional insoles should focus on the coordinated advancement of "personalization-intelligence-standardization", with the aim of providing more effective solutions for the prevention and treatment of DF.
Humans ; Diabetic Foot/therapy* ; Foot Orthoses

OBJECTIVE: To investigate the clinical characteristics and prognostic factors of elderly patients with diffuse large B-cell lymphoma (DLBCL). METHODS: Clinical data of elderly DLBCL patients diagnosed pathologically between 2010 and 2015 were extracted from the SEER database. Cox proportional hazards model was used for multivariate analysis, and Kaplan-Meier survival curves were plotted to explore the prognostic factors affecting overall survival (OS). RESULTS: A total of 11 523 elderly DLBCL patients were included, of whom 58.6% had stage Ⅲ/Ⅳ disease, and 28.8% exhibited extranodal involvement. Besides lymph nodes (68.5%), common primary extranodal sites included the gastrointestinal tract (9.8%) and lip, mouth, and pharynx (4.1%). The median survival time for the entire cohort was 47 months, with a 3-year survival rate of 52.0%, and a 5-year survival rate of 47.8%. Multivariate Cox regression analysis revealed that age, sex, race, Ann Arbor stage, primary site, B symptoms, treatment modality, treatment sequence, and whether DLBCL was the first malignant primary indicator were independent prognostic factors affecting OS in elderly DLBCL patients (all P <0.05). CONCLUSION Age≥70 years, male, black race, advanced Ann Arbor stage, primary sites in the lungs, liver, or kidney, presence of B symptoms, and preoperative systemic therapy were independent risk factors for poor prognosis in elderly DLBCL patients.
Humans ; Lymphoma, Large B-Cell, Diffuse/diagnosis* ; Prognosis ; Aged ; Male ; Female ; Survival Rate ; Proportional Hazards Models ; Aged, 80 and over ; Kaplan-Meier Estimate ; Neoplasm Staging