Search Results (2,937)

Background: Large language models (LLMs) are becoming progressively integrated into clinical practice; however, their role in cardiovascular (CV) prevention remains unclear. This review synthesizes current evidence on LLM applications in preventive cardiology and proposes a governance framework for their safe translation into practice. Methods: We conducted a comprehensive narrative review of literature published between January 2015 and November 2025. Evidence was synthesized across three functional domains: (1) patient applications for health literacy and behavior change; (2) clinician applications for decision support and workflow efficiency; and (3) system applications for automated data extraction, registry construction, and quality surveillance. Results: Evidence suggests that while LLMs generate empathetic, guideline-concordant patient education, they lack the nuance required for unsupervised, personalized advice. For clinicians, LLMs effectively summarize clinical notes and draft documentation but remain unreliable for deterministic risk calculations and autonomous decision-making. System-facing applications demonstrate potential for automated phenotyping and multimodal risk prediction. However, safe deployment is constrained by hallucinations, temporal obsolescence, automation bias, and data privacy concerns. Conclusions: LLMs could help mitigate structural barriers in CV prevention but should presently be deployed only as supervised “reasoning engines” that augment, rather than replace, clinician judgment. To guide the transition from in silico performance to bedside practice, we propose the C.A.R.D.I.O. framework (Clinical validation, Auditability, Risk stratification, Data privacy, Integration, and Ongoing vigilance) as a roadmap for responsible integration. Full article

Background/Objectives: In severe peripheral artery disease (PAD) with limb ischemia, hypercholesterolemia (HC) is associated with impaired neovascularization. Extracellular vesicles (EVs) are present within ischemic muscles, and they contain microRNAs (miRs) involved in several biological functions, including angiogenesis and neovascularization. Methods: We used a mouse model of PAD and compared the response to hindlimb ischemia in hypercholesterolemic ApoE^−/− vs. normocholesterolemic mice. Next-generation sequencing (NGS) was used to perform full miR expression profiling in ischemic skeletal muscles and in EVs of varying sizes—large EVs (lEVs) and small EVs (sEVs)—within these muscles. Results: We identified several miRs with potential pro-angiogenic effects (angiomiRs) that are reduced by HC in lEVs (Let-7b-5p, miR-151-3p, Let-7c-5p) or sEVs (miR-21a-5p, miR-196b-5p, miR-340-5p). As proof of principle, we showed that the overexpression of Let-7b-5p in lEVs, or miR-21a-5p in sEVs, can significantly increase the angiogenic capacity of these EVs in vitro. HC also impaired the enrichment of specific angiomiRs in lEVs (miR-100-5p), sEVs (miR-142a-3p), or in both lEVs and sEVs (miR-146b-5p). In silico approaches, including the prediction of miR targets, pathway unions, and gene unions, identified the resulting predictive effects of HC-modulated miRs in EVs on processes with key roles in the modulation of angiogenesis and neovascularization, such as the regulation of the actin cytoskeleton and focal adhesion and the HIF-1, MAPK, AMPK, and PI3K-Akt signaling pathways. Conclusions: Our results constitute an important first step towards the identification of specific miRs that could be targeted to improve EV angiogenic function in hypercholesterolemic conditions and reduce tissue ischemia in patients with severe PAD. Full article

This study investigated the cytotoxic, antiproliferative, and molecular interaction profiles of the phenylpropanoids verbascoside and isoverbascoside from Pyrostegia venusta using in silico approaches. Computational predictions suggested differential cytotoxicity trends between tumor and non-tumor breast cell models compared with tamoxifen. QSAR analyses indicated antiproliferative potential, while docking studies revealed stable ligand–protein interactions with estrogen-related targets and PTEN. ADMET predictions suggested favorable metabolic characteristics, including limited CYP3A4 interaction. Overall, these results provide predictive insights that support further experimental investigation of these phenylpropanoids in ER⁺ breast cancer models. Full article

Background/Objectives: Epilepsy is characterized by unpredictable seizures and drug resistance, along with rising antimicrobial resistance (AMR), highlighting the urgent need for innovative dual-action therapies. This study aimed to design, develop, and evaluate novel pyrazolone derivatives for a dual antimicrobial and antiepileptic potential. Methods: Novel pyrazolone derivatives were designed, synthesized (using 2,4-dinitrophenylhydrazine/semicarbazide condensation with ethyl acetoacetate), and evaluated through molecular docking against antimicrobial (4URM, 3FYV, 3FRA) and neuronal targets (4COF, 5TP9, 5L1F). The in vitro antimicrobial activity was assessed against Gram-positive (S. aureus) and in vitro Gram-negative (E. coli, P. aeruginosa) strains via agar cup plate assays, while in vivo antiepileptic efficacy was tested in a PTZ-induced seizure model in Swiss albino mice. Results: Compound IIa showed potent dual activity, inhibiting E. coli (9 mm zone at 80 μg/mL) and S. aureus (9.5 mm at 80 μg/mL), alongside a significantly delayed seizure onset in the PTZ-induced mouse model (100% survival rate, 45 sec delayed seizure onset, p < 0.001). Compounds Ia and Id showed selective activity against E. coli (6 mm at 80 μg/mL) and P. aeruginosa (7 mm at 80 μg/mL), respectively. Docking studies revealed that compound IIa has a superior binding affinity (−7.57 kcal/mol for 3FYV) compared to standards, driven by hydrogen bonds (SER X: 49) and hydrophobic interactions (LEU X: 20). Conclusions: This study presents a novel approach by proposing a rationally designed pyrazolone scaffold exhibiting both antimicrobial and antiepileptic activity, which integrates in silico modeling with experimental validation. Compound IIa emerged with preliminary dual biological activities, exhibiting strong antibacterial activity, a superior binding affinity toward both bacterial and neuronal targets, and notable seizure prevention in vivo. These findings show the potential of multifunctional pyrazolone derivatives as a new treatment strategy for addressing drug-resistant infections linked to epilepsy and support further optimization toward clinical development. Full article

Kratom (Mitragyna speciosa (Korth.) Havil.) oxindole alkaloids remain underexplored compared to the well-studied indole constituents mitragynine and 7-hydroxymitragynine. Previous research has primarily focused on phytochemical identification and preliminary pharmacology, with limited pharmacokinetic insight. This study pioneers an in silico ADMET modeling analysis of 27 kratom-derived oxindole alkaloids using ADMET Predictor™ v3.0, delivering the first comprehensive predictions of their physicochemical properties, CYP450/UGT enzyme interactions, transporter affinities, permeability, and pharmacokinetic parameters. Representative compounds such as speciophylline, isomitraphylline, and isospeciophylline displayed notably favorable predicted jejunal permeability and moderate metabolic stability, suggesting promising oral drug-like characteristics. Across the dataset, high CYP3A4 substrate affinity (98% confidence), variable CYP3A4, CYP2D6, CYP2C19 inhibition, strong P-gp substrate potential, and differential BBB penetration probabilities (46–99%) were observed. These findings provide a foundational computational framework to guide future experimental validation and rational drug development of kratom oxindole alkaloids. Full article

Cancer and Alzheimer’s disease (AD) display an inverse relationship, and there is a need to further explore this interplay. One key genetic contributor to AD is SORL1, the loss of which is thought to be causally related to AD development. SORL1 also appears to be implicated in cancer. To examine SORL1 and its network, this article simulated SORL1 and its interactions via signal-flow Boolean modelling, including in silico knockouts (mirroring in vivo loss-of-function mutations). This model (SKM034) predicted a total of 29 key changes in molecular relationships following the loss of SORL1 or another highly connected protein (ERBB2). Literature validation demonstrated that 2 of these predictions were at least partially validated experimentally, whilst 27 were Potentially Novel Predictions (PNPs). Complementing the in-depth relationship analyses was signal flow analysis through the network’s structure, validated using cell line and cancer patient RNA-seq data. Correct prediction rates for these analyses reached 60% (statistically significant relative to a random model). This article demonstrates the clinical relevance of this Alzheimer’s-related network in a cancer context and, through the PNPs, provides a strong starting point for in vitro experimental validation. As with previously published models using similar methods, the model may be reanalysed in different contexts for further discoveries. Full article

To enhance the screening efficiency of bioactive peptides, an AI-driven approach was employed to screen DPP-IV inhibitory peptides from goat blood proteins by an integrated in silico, in vitro, and machine learning strategy. Furthermore, the inhibitory mechanism of DPP-IV inhibitory peptides was elucidated by kinetics, molecular docking and simulation. Additionally, their in vitro digestive stability was assessed. In silico results revealed that goat blood proteins were promising precursors of DPP-IV inhibitory peptides, while bromelain was the optimal protease. Their peptide sequences were further identified by peptidomics and predicted by self-developed machine learning models (LightGBM) to identify the potent DPP-IV inhibitory peptides. Two novel DPP-IV inhibitory peptides were identified (FPL and FPHFDL). Enzyme kinetics, molecular docking and molecular simulation data indicated that FPL served as a competitive inhibitor, whereas FPHFDL was a non-competitive inhibitor. Overall, the integrative in silico and in vitro strategy is feasible for rapid screening of DPP-IV inhibitory peptides from goat blood proteins. Full article

Seed germination is a critical developmental stage exhibiting high vulnerability to salt stress. The role of MYB transcription factors (TFs) in mediating this process in Cannabis sativa L. remains largely unexplored. In this study, we performed a genome-wide analysis and identified 115 CsMYB genes, which were phylogenetically classified into 12 distinct subgroups. In silico promoter analysis revealed a significant enrichment of abscisic acid (ABA)- and methyl jasmonate (MeJA)-responsive cis-elements, suggesting their potential linkage to phytohormone signaling pathways under stress conditions. To investigate their expression during salt stress, we profiled a subset of candidate CsMYB genes during seed germination under 150 mM NaCl treatment based on RNA-seq screening at 24 h post-imbibition (hpi) under salt stress. These candidates exhibited distinct temporal expression profiles: CsMYB33 and CsMYB44 were transiently induced at the early stage (12 h post-imbibition), while CsMYB14, CsMYB78, and CsMYB79 showed sustained upregulation from 24 h to 5 days. In contrast, CsMYB58 and CsMYB110 were downregulated. Synteny analysis indicated a closer evolutionary relationship between CsMYBs and their Arabidopsis thaliana orthologs compared to those in monocots. Protein–protein interaction predictions, based on orthology, further implicated these CsMYBs within putative ABA signaling and reactive oxygen species (ROS) homeostasis networks. Collectively, our findings provide a systematic genomic identification and genomic characterization of the CsMYB family and propose a model for the potential multi-phase involvement of selected CsMYBs in the salt stress response during seed germination. This work establishes a foundational resource and identifies key candidate genes for future functional validation aimed at enhancing salt tolerance in C. sativa. Full article

CRISPR-Cas9 systems have enabled unprecedented advances in genome engineering, particularly in developing treatments for human diseases, like cancer. Despite potential applications, limitations of Cas9 include its relatively large size and strict targeting requirements. Cas12j2, a variant ofCasΦ-2, shows promise for overcoming these limitations. However, its effectiveness in mammalian cells remains relatively unexplored. This study sought to develop an optimized CRISPR-Cas12j2 system for targeted knockout of the E6 oncogene in HPV-associated cancers. A combination of computational tools (ColabFold, CCTop, Cas-OFFinder, HADDOCK2.4, and Amber for Molecular Dynamics) was utilized to investigate the impact of engineered modifications on structural integrity and gRNA binding of Cas12j2 fusion constructs, in potential intracellular conditions. Cas12j2_F2, a Cas12j2 variant designed and evaluated in this study, behaves similarly to the wild-type Cas12j2 structure in terms of RMSD/RMSF profiles, compact Rg values, and minimal electrostatic perturbation. The computationally validated Cas12j2 variant was incorporated into a custom expression vector, co-expressing the engineered construct along with a dual gRNA for packaging into a viral vector for targeted knockout of HPV-associated cancers. This study provides a structural and computational foundation for the rational design of Cas12j2 fusion constructs with enhanced stability and functionality, supporting their potential application for precise genome editing in mammalian cells. Full article

A library of thirty-one quinazoline derivatives was assessed as potential inhibitors of epidermal growth factor receptor kinase (EGFR) using 3D-QSAR methods, namely Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA). Training and test sets were generated by aligning the molecules to the lowest-energy conformer of the most active compound. The optimized models exhibited strong statistical performance, with R² values of 0.981 (CoMFA) and 0.978 (CoMSIA), and cross-validation coefficients (Q²) of 0.645 and 0.729, respectively. External validation confirmed their predictive power, yielding R² values of 0.929 and 0.909. Guided by these models, eighteen new quinazoline candidates were designed and evaluated for drug likeness and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties using in silico approaches. Molecular docking and molecular dynamics simulations highlighted the binding features and stability of these derivatives, with compound Pred65 demonstrating superior affinity and stability compared to Erlotinib. Collectively, the study provides valuable insights for the optimization of quinazoline scaffolds as EGFR inhibitors, supporting the development of promising anticancer leads. Full article

Candidozyma auris (formerly Candida auris) is an emerging multidrug-resistant fungal pathogen with confirmed cases in over 30 countries. Although whole-genome sequencing (WGS) analysis defined distinct clades during characterization of underlying genetic mechanism behind multidrug resistance, Clade II remains under-evaluated. In this study, a three-level comparative genomic strategy (Global, Clade, Phenotype) was employed by integration of unbiased genome-wide comparative SNP screening (GATK v4.1.9.0), targeted BLAST profiling (BLAST+ v2.17.0), and in silico protein analysis (ColabFold v1.5.5; DynaMut2 v2.0) for systematic evaluation of mechanisms of antifungal resistance in thirty-nine Clade II C. auris clinical isolates and fourteen reference strains. Global and clade-level analyses confirmed that all the clinical isolates belong to Clade II, according to phylogenetic clustering and mating type locus (MTL) conservation. At the phenotype level, a distinct subclade of fluconazole-resistant mutants was identified to have a heterogenous network of mutations in seven key enzymes associated with cell membrane dynamics and the metabolic stress response. Among these, four core mutations (TAC1B, CAN2, NIC96, PMA1) were confirmed as functional drivers based on strict criteria during multitier in silico protein analysis: cross-species conservation, surface exposure, active site proximity, thermodynamic stability, and protein interface interaction. On the other hand, three high-level fluconazole-resistant clinical isolates (≥128 μg/mL) that lacked these functional drivers were subjected to comprehensive subtractive genomic profiling analysis. The absence of coding mutations in validated resistance drivers, yeast orthologs, and convergent variants suggests that there is an alternative novel non-coding or regulatory mechanism behind fluconazole resistance. These findings highlight Clade II’s evolutionary divergence into two distinct trajectories towards the development of a high level of fluconazole resistance: canonical protein alteration versus regulatory modulation. Full article

Background/Objectives: The development of specific inhibitors for cyclooxygenase-2 (COX-2) is a challenge for public health. A series of 17 N-phthalimide hybrids was evaluated using a functional M06 meta-GGA hybrid in combination with a polarized 6-311G (d, p) basis set. The top three candidates (6, 10, and 17) were synthesized and evaluated as selective COX-2 inhibitors of PGE-2 using an integrated in silico–in vitro approach. Methods: Molecular docking against COX-2 (PDB 5KIR) and COX-1 (PDB 6Y3C), supported by homology modeling and DFT geometry optimization (B3LYP/6-31G*), revealed that the phthalimide carbonyl groups and the 3,4,5-trimethoxyphenyl or geranyl-derived moieties establish key hydrogen bonds and hydrophobic contacts with Arg120, Tyr355, Tyr385, and Ser530 in the COX-2 active site, conferring predicted selectivity ΔGCOX−2 vs. COX−1 = −1.4 to −2.8 kcal/mol. Results: The compounds complied with Lipinski’s and Veber’s rules and displayed favorable ADMET profiles. In vitro assessment in LPS-stimulated J774A.1 murine macrophages confirmed potent inhibition of PGE₂ production, 3.05 µg/mL, with compound 17 exhibiting the highest efficacy, 97.79 ± 5.02% inhibition at 50 µg/mL, and 10 showing 95.22 ± 6.03% inhibition at 50 µg/mL. Notably, all derivatives maintained >90% cell viability up to 250 µg/mL by resazurin assay and showed no evidence of cytotoxicity or mitosis potential in the tests at 24 h. Conclusions: These results demonstrate that strategic hybridization of phthalimide with natural and synthetic product-derived fragments yields highly potential PGE2 inhibitors. Therefore, compounds 6, 10, and 17 are promising lead candidates for the development of safer anti-inflammatory agents. Full article

Background: Trypanosoma cruzi, the causative agent of Chagas disease, remains a major public health concern, and there is a continued need for new antitrypanosomal agents. Thiosemicarbazone (TSC) derivatives have emerged as a promising class of compounds with potential antiparasitic activity. Objectives: This study aimed to report the synthesis, characterization, and biological profiling of a novel series of thiosemicarbazone derivatives as antitrypanosomal agents against Trypanosoma cruzi. Methods: Fourteen new compounds and six previously described analogues were prepared and characterized by ¹H/¹³C nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). As a preliminary in vitro screen, activity was assessed by direct parasite counting in epimastigote and bloodstream trypomastigote forms, as tractable models of replicative and infective stages sharing core metabolic targets with intracellular amastigotes. Epimastigote potency was quantified as half-maximal effective concentrations (EC₅₀) derived from dose–response curves, whereas trypomastigote response was evaluated as percent viability after treatment at a fixed concentration of 20 µM. Mechanistic profiling included inhibition assays against the cysteine protease cruzipain (CZP) and selected redox defense enzymes, complemented by in silico similarity clustering and binding-pose affinity scoring. Results: A nitro-methoxy-substituted TSC showed potent CZP inhibition but limited trypomastigote efficacy, whereas brominated analogues displayed dual-stage activity independent of CZP inhibition. Tanimoto similarity analysis identified distinct structure–activity clusters, linking nitro-methoxy substitution to epimastigote selectivity and brominated scaffolds to broader antiparasitic profiles, with hydrophobicity and steric complementarity as key determinants. Enzymatic assays revealed no significant inhibition of cytosolic tryparedoxin peroxidase (cTXNPx) or glutathione peroxidase type I (TcGPx-I), suggesting redox disruption is not a primary mode of action. In vitro and in silico analyses showed low or no non-specific cytotoxicity under the tested conditions, supporting further optimization of these derivatives as antitrypanosomal preliminary hits. Key hits included derivative 3e (epimastigote EC₅₀ = 0.36 ± 0.02 µM) and brominated analogues 2c and 2e (epimastigote EC₅₀ = 3.92 ± 0.13 and 4.36 ± 0.10 µM, respectively), while docking supported favorable binding-pose affinity (e.g., ΔG_S-pose = −20.78 ± 2.47 kcal/mol for 3e). Conclusions: These results support further optimization of the identified thiosemicarbazone derivatives as preliminary antitrypanosomal hits and provide insight into structure–activity relationships and potential mechanisms of action. Full article

Organoids are self-organizing multicellular structures generated in vitro that recapitulate the micro-architecture and function of an organ. They are commonly derived from stem cells but can also emerge from pieces of proliferative tissues. Organoid technology has opened novel ways to model development and disease, but it is not without challenges. Computational models of organoids have been established to elucidate organoid growth and facilitate the optimization of organoid cultures. This article is a systematic review of in silico organoid models constructed at single-cell or subcellular resolution. PubMed, Scopus, and Web of Science were searched for original papers published in peer-reviewed journals before 26 September 2025, yielding 439 records after deduplication. Two independent reviewers screened their titles and abstracts, retrieved 84 papers for full-text scrutiny, and identified 32 papers that met the inclusion criteria. They were grouped by organoid type: 12 intestinal, 1 airway, 2 pancreas, 3 neural, 1 kidney, 1 inner cell mass, 9 tumor, and 3 generic. The analysis of these works revealed that computer simulations guided experimental work. Parsimonious computational models provided insights into diverse organoid behaviors, such as the rotation of airway organoids, size oscillations of pancreatic organoids, epithelial patterning of neural tube organoids, or nephron segment formation in kidney organoids. Generally, a deep understanding was achieved through combined in silico and in vitro investigations (e.g., optic cup morphogenesis). Recent research trends suggest that next-generation computational models of organoids may emerge from a more detailed understanding of the complex regulatory circuits that govern stem cell fate, and machine-learning-based, high-throughput imaging of organoids. Full article

This study evaluated two formulations of L-carnitine, which were developed and impregnated in an oil-based self-emulsifying system (SEDDS), the first with tyrphostin AG17 and the second without the addition of tyrphostin AG17. The formulation with tyrphostin AG17 showed the presence of stable microvesicles up to 498 h after its preparation. To establish a robust safety profile in compliance with modern regulatory frameworks and the 3Rs principle (replacement, reduction, and refinement), a toxicological evaluation was conducted integrating an in silico quantitative structure–activity relationship (QSAR) analysis with confirmatory in vivo subchronic toxicity studies. The QSAR analysis, performed using the OECD QSAR Toolbox and strictly adhering to Organization for Economic Co-operation and Development (OECD) validation principles, predicted an acute oral LD50 of 91.5 mg/kg in rats, a value showing high concordance with the historical experimental data (87 mg/kg). Furthermore, computational modeling for repeated-dose toxicity yielded a no-observed-adverse-effect level (NOAEL) of 80.0 mg/kg bw/day, a no-observed-effect level (NOEL) of 60.4 mg/kg bw/day, and an ADI = 56 mg/day. These computational findings were substantiated by a 90-day subchronic toxicity study in male Wistar rats, where daily intragastric administration of tyrphostin AG17 at doses up to 1.75 mg/kg resulted in not statistically significant hematotoxic activity (p < 0.05), with a maximum cumulative dose over 90 days of 157.5 mg/kg. Collectively, these data indicate that tyrphostin AG17 combines high stabilizing efficacy with a manageable safety profile, supporting its proposed regulatory status as a functional food additive. Based on these results, it is concluded that tyrphostin AG17 shows promising characteristics for use as a stabilizer in food and other substances. Full article