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Biology subjects

Meva, F. E.

Publications and source records attributed to Meva, F. E..

2 recordsLinked to original sources

A Physics-Constrained Marcus-Theory Optimization Framework Restores Parameter Identifiability in Deep-Pocket Oncogenic Drug Kinetics: A KRAS G12C and STAT3 Case Study

Background: More than 90% of drug candidates fail preclinically, partly because empirical dose-response models such as the Hill equation ignore microenvironmental effects inside the deep binding pockets of targets such as mutant KRAS G12C and STAT3. Bulk water is hypothesized to raise the reorganization energy (lambda_ext). Objective: To develop a physics-constrained framework, the Cluchagues-Marcus Framework, that links local dielectric permittivity to ligand-pocket kinetics, and to determine which constraints restore parameter identifiability. Methods: Non-adiabatic Marcus kinetics were coupled to a Hill-type equation derived from a steady-state scheme, and water exclusion was modeled as a collapse of epsilon_local from 80.4 to 2.0. Pocket radii and published reference constants were used for two pockets (KRAS G12C, PDB 6UT0; STAT3 SH2, PDB 6NJS). Three propositions were proved and checked with synthetic data and a global sensitivity analysis, and the identifiability result was numerically stress-tested on real napabucasin viability curves from 701 cancer cell lines. Results: Water exclusion lowered lambda_ext by 90%. At dG = -0.10 eV, k_C rose 8.0-fold (KRAS) and 3.6-fold (STAT3). Acceleration occurs if and only if |dG| < sqrt(lambda_s x lambda_u). The model has exactly two non-identifiable parameter directions: fixing nu_eff removes one and anchoring K_d removes the other. In real curves, fits were unchanged by the K_d anchor (SSE change < 10^-7 %) while the fitted k_off,q varied by 3.5 log units, as predicted. Conclusions: A dissociation-constant anchor makes the framework identifiable. The real-data stress test is not biological validation of the dielectric mechanism, which requires experiments.

pharmacology and toxicology↗

Larvicidal Potential of Cola nitida Endophytic Bacteria Against Insecticide-Resistant Anopheles gambiae

BackgroundInnovative vector control strategies are urgently needed to combat malaria transmission by Anopheles gambiae, given the limitations of current insecticides--namely resistance, human toxicity, environmental damage, and high costs. This study evaluated the larvicidal efficacy of endophytic bacteria isolated from Cola nitida against third-instar larvae of Anopheles gambiae. MethodsEndophytic bacteria were isolated from nine Cola nitida plant parts (leaves, roots, stems, fruits, flowers, stem bark, branches, root bark, whole plant extracts) using standard surface sterilization and culturing protocols. Thirty-two morphologically distinct strains were purified and screened for larvicidal activity against third-instar An. gambiae larvae using the WHO-recommended turbidity method at McFarland 4 standard. Six active isolates underwent dose-response testing (McFarland 0.5-4) with mortality recorded at 24 and 48 hours. Environmental safety was assessed via Lemna minor growth inhibition, and molecular identification employed the API 20E biochemical gallery. ResultsScreening identified six strains with significant larvicidal activity (LC < McFarland 2). At McFarland 2 concentration, all six strains achieved >50% mortality within 24-48 hours, with Lemna minor EC >100% indicating minimal phytotoxicity. API 20E identification (96-99.99% similarity) revealed three strains (6164, 6211, 6501) matching Photobacterium damselae, two (6186-1, 6512-1) matching Salmonella enterica subsp. arizonae, and one (6600) matching Pseudomonas sp., confirmed by distinctive biochemical profiles. ConclusionThis study provides the first evidence of potent, environmentally safe larvicidal activity from Cola nitida endophytic bacteria against Anopheles gambiae. These strains represent promising biocontrol candidates to address insecticide resistance, offering a sustainable alternative for malaria vector management in endemic regions.

microbiology↗