The microbiome-gut-brain axis involves the bidirectional connection between the gastrointestinal tract, gut microbiome, and central nervous system, and it is pivotal for mental well-being. Imbalances in the gut microbiome (dysbiosis) can disrupt neurotransmitter synthesis, leading to neurodegenerative diseases. Recent researches highlight psychobiotics as effective treatments for mental health conditions like depression. With advancements in artificial intelligence (AI) and large datasets, psychobiotic research has accelerated. AI tools are increasingly used for the prediction, identification, and diagnosis of gut microbiome compositions, enabling faster and more accurate discovery of therapeutic candidates. This review explores the role of AI in enhancing microbiome-gut-brain-axis-related disease therapies through psychobiotics and discusses future directions for this rapidly evolving research field.

Background: Fungal infections have emerged as an increasingly serious public health challenge globally. Four Formulations of amphotericin B are widely used in antifungal therapy. Despite the same active ingredient, they probably differ in efficacy, safety and economics.

Aim: This study aimed to explore the differences in efficacy, safety and economy among different formulations of amphotericin B in patients with IFD.

Methods: We conducted a retrospective study at a tertiary hospital, examining patients who were administered amphotericin B from June 2023 to March 2025, to assess the efficacy, safety and economy of different amphotericin B Formulations in invasive fungal disease.

Results: (1) A total of 71 patients were included. Patients with potential renal injury are more likely to choose liposomal amphotericin B (p = 0.021). (2) Liposomal amphotericin has the accelerated therapeutic onset (p = 0.042), amphotericin B deoxycholate has the delayed therapeutic effect (p = 0.031), the effective response of liposomal amphotericin B in elders was significantly lower (p = 0.022), and the counterpart of amphotericin B deoxycholate in females was significantly higher (p = 0.01). (3) The main adverse events of the three amphotericin B formulations were kidney injury (p < 0.001), there was no significant inter-group difference. (4) The amphotericin B deoxycholate group incurred the most economical total cost (p < 0.01), daily cost (p < 0.01) and cost-effectiveness.

Conclusion: Amphotericin B formulations exhibit marked variations in efficacy and economy profiles, necessitating individualized selection guided by specific clinical characteristics. Rigorous monitoring of renal function remains imperative throughout the therapeutic course.

Background: Neurological disorders are one of the major contributors to the burden of disease, affecting the quality of life of the global population.Statins, known for their cholesterol-lowering properties, have garnered substantial interest due to their potential neuroprotective effects and association with subjective cognitive decline.The study aims to provide a comprehensive bibliometric analysis of the literature on the nexus between neurological disorders and statins.

Methods: Using VOSviewer (1.6.20), CiteSpace (6.3.1 and 5.7.R2), and R (4.4.1), the systematic bibliometric analysis offers valuable insights into the research landscape of neurological disorders and statins from 2004 to 2024.

Results: The findings reveal a notable increase in scholarly output on neurological disorders and statins over the past two decades, with a particular emphasis on clinical trials and pharmacological mechanisms of statins. The remarkable multidisciplinary nature of the field is an important reason for its continued development.Compared to initial exploratory research, recent studies have placed increased emphasis on the neuroprotective roles of statins and their therapeutic potential in managing neurological disorders.Future research is anticipated to focus on precision medicine and personalized therapeutic strategies involving statins.The United States, China and Germany are leading the way in this field of research.

Conclusion: The study's findings are instrumental in informing future research directions and contribute to a broader understanding of the subject matter across various scientific disciplines. Statins have great potential in the treatment of neurological disorders and neuroprotection and are moving towards customized medicine and personalized therapy.

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder with an insidious onset, and effective therapeutic agents are urgently needed.

Objective: This study employed a multi-omics integration strategy for drug repurposing against AD.

Methods: Firstly, transcriptomic and proteomic data from AD patients were utilized to identify differentially expressed genes. Potential anti-AD small-molecule compounds were screened by integrating the Reverse Gene Expression Score (RGES) and Connectivity Map (C-Map) approaches with drug-perturbed gene expression profiles from the Library of Integrated Network-Based Cellular Signatures (LINCS), followed by blood-brain barrier (BBB) permeability prediction and structural similarity analysis. Secondly, a drug-disease network was constructed, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. The therapeutic potential of candidate drugs was further evaluated via network proximity analysis. Finally, in vitro validation was conducted using Okadaic acid (OA) induced SH-SY5Y and Lipopolysaccharide (LPS) induced BV2 cell models to assess cell viability and nitric oxide (NO) levels. This integrated approach provides a novel framework for identifying repurposed drugs with potential efficacy against AD.

Results: Following the collection of omics data, 227 overlapping candidate compounds were identified through two computational approaches. After BBB prediction screening, 104 drugs were selected for subsequent structural similarity analysis and literature/patent review, ultimately leading to the selection of TNP-470 and Terreic acid for validation. Network pharmacology analysis revealed that potential targets of TNP-470 for AD treatment were significantly enriched in neuroactive ligand-receptor interaction, TNF signaling, and AD-related pathways, while anti-AD targets of Terreic acid primarily involved calcium signaling, AD pathway, and cAMP signaling. Network proximity analysis demonstrated significant associations between both candidates and AD. In vitro assays demonstrated that TNP-470 significantly enhanced the viability of OA-induced SH-SY5Y cells at concentrations of 10 μM and 50 μM (p < 0.01 and p < 0.05, respectively). Additionally, within the concentration range of 0.016-10 μM, TNP-470 markedly inhibited NO production in the LPS-induced BV2 microglial cell model. Terreic acid also promoted the survival of OA-treated SH-SY5Y cells at concentrations ranging from 2 to 50 μM, and significantly reduced nitric oxide (NO) levels at a concentration of 10 μM.

Conclusion: This drug repositioning strategy based on multi-omics integration provides a novel approach for AD therapeutic development, with both TNP-470 and Terreic acid demonstrating anti-AD potential.

Recurrent glioblastoma (rGBM) remains one of the most formidable challenges in neuro-oncology due to its aggressive evolution, treatment resistance, and profound intratumoral heterogeneity. Despite advances in multimodal first-line therapy, recurrence is nearly universal and represents a genetically divergent, therapy-adapted malignancy. This review dissects the evolutionary dynamics of rGBM, including clonal selection, therapy-induced mutagenesis, and proneural-to-mesenchymal shifts. It explores the translational potential of longitudinal sampling, circulating tumor DNA, and multi-omics profiling to dynamically monitor tumor progression and resistance emergence. Personalized therapeutic strategies are critically evaluated, including targeted inhibition of EGFR, PI3K/AKT/mTOR, and PDGFR pathways, immunotherapeutic approaches such as CAR T-cell therapy and neoantigen vaccines, and functional drug screening using patient-derived organoids. Moreover, the manuscript highlights innovations in AI-assisted therapy mapping, precision-guided re-irradiation, and adaptive trial designs that redefine individualized care in rGBM. Persistent challenges such as blood-brain barrier penetration, immune evasion, and lack of real-world clinical integration are also addressed. The convergence of high-throughput molecular diagnostics, AI analytics, and targeted therapies underscores a shift from static to dynamic, biomarker-guided interventions. Realizing the full promise of personalized medicine in rGBM demands systemic reforms, multi-disciplinary integration, and equitable clinical adoption.