Medicine and Pharmacology

Abstract: The axon initial segment (AIS) is a highly specialized compartment of the neuron thought to be an essential regulator of how neurons encode their responses. This region is topographically and biophysically tuned to the precise generation of action potentials and the regulation of spiking output. In addition to serving as a threshold region like other axonal regions, the AIS is uniquely optimized as a signaling domain so that cytoskeletal polarization, ion channel clustering, and intracellular signaling pathways converge upon this subcellular domain to produce a precise regulation of neuronal firing rate and timing. The nanoscale cytoskeletons and anchoring scaffolds at the AIS serve both to confine and to dynamically mobilize key signaling proteins and channels for a rapid yet adaptable regulation of spike initiation. Evidence suggests that AIS structure is exquisitely plastic to cellular, environmental, immune, and genetic factors known to be involved in the neuropathology of mood disorders. Precursors to pathology such as stress, chronic glucocorticoid excess, neural inflammatory signals, and genetic variation perturbing excitability by governing ion channel and receptor expression, can all produce alterations in the positional or dimensional parameters of the AIS with functional consequence to neuronal gain. Such alterations occur specifically in circuit nodes of emotion regulation such as the prefrontal limbic circuit, across neuronal populations and cell types, and alter trajectories of circuit function seemingly aligned with affective disorder symptom states. This work integrates current knowledge in the structure and electrophysiology of AIS function, activity dependent plasticity, and psychiatric neuroscience, to develop the hypothesis that remodeling of the AIS represents a convergent readout of the interactions between the immune system, stress response, and genetic alleles on neuronal function, a cellular mechanism through which the large components of neural circuit-based disease shape affective illness, potentially as an “axonopathy”. Furthermore, this review highlights the AIS as a potential new therapeutic target aimed at rehabilitating excitability threshold and gain for effective circuit function in the treatment of affective disorders within the emerging paradigm of precision psychiatry.

Abstract: Background. Knowledge-graph models can rank existing drugs for a disease, but their benchmarks mostly reward rediscovering known treatments, and their scores rarely come with evidence a researcher can check. We built OREVID, an open tool that shows a ranked candidate only when an evidence line supports it and reports how often each line was right on held-out data, and compared it with TxGNN on identical data. Methods. The graph combines PrimeKG, Open Targets, STRING and PubTator3 (157,822 nodes, 9.46 million edges). For each disease, 22 degree-weighted metapath features and two gene-level columns (whether the drug moves its targets in the direction human genetics asks, from protein and expression QTLs that colocalise with the disease's genome-wide association studies, and whether it acts on a gene Orphanet lists for the disease) feed a LightGBM LambdaRank model trained with masked neighbourhoods. A candidate is shown only if it is indicated for an ontology-neighbour disease or for a disease sharing at least 3 associated genes (hypergeometric p < 10⁻⁵ over the genes with at least one associated disease). The acceptance criteria for these rules were set in advance; the rules were revised on the hidden-treatment benchmarks and then measured on an external set of approvals not used to choose them. TxGNN was retrained with its official code on the same PrimeKG splits, and all tasks and predictions are released as OREVID-bench. Results. Zero-shot Recall@100 (mean ± SD over five splits) was 0.812 ± 0.038 for OREVID, 0.412 ± 0.042 for TxGNN and 0.358 ± 0.040 for a popularity baseline, with OREVID ahead on every split (paired difference with TxGNN 0.400, 95% CI 0.354–0.444, resampling diseases). On nine disease areas held out it was 0.627 against 0.237, ahead in all nine, although TxGNN had the higher AUPRC in four. Training OREVID without validation labels and excluding diseases where TxGNN outputs constant scores gave 0.815 against 0.421. On 3,718 approvals absent from PrimeKG, Recall@100 was 0.355 against 0.121 (0.366 ± 0.011 against 0.126 ± 0.004 over five training splits), and 0.175 against 0.085 for the 2,719 approvals not obvious from the disease ontology; a logistic regression without the drug-popularity feature and a model without any Open Targets feature (0.348) performed similarly. Of the candidates the website's rules select in this external exam, 12.6% (95% CI 9.8–15.5%, resampling diseases) of direct extensions and 4.4% (3.2–5.8%) of shared-genes candidates were among the unseen approvals, against about 0.07% by chance; random gene sets of the same size selected candidates that were right as often, so the shared genes are not evidence of a shared mechanism, although they contained a protein of the curated mechanism (DrugMechDB) more often than random genes of the same disease (25% against 17%). A drug acting on a disease gene, with no other evidence, was right 1.8–3.4% of the time, no better than candidates with no evidence line at all. With the graph and the model rebuilt as known in 2015 and every drug dated by its first approval, the uses that later reached phase 3 or approval had a Recall@100 of 0.283 against 0.181 for popularity (paired difference 0.102, 95% CI 0.078–0.126) and 0.117 for TxGNN trained on the same graph (difference 0.167, 0.142–0.192), in pre-registered tests. On labels absent from the graph (CIViC oncology evidence, indications only DrugCentral or MED-RT record, and European orphan designations) OREVID was ahead of popularity by 0.32, 0.27 and 0.16, but the candidates the website shows did not meet trial end points more often than ranked drugs it hides. Conclusions. Reporting the hit rate of each evidence line makes repurposing predictions checkable and shows how low their precision is on approved uses missing from the training graph. Most of the signal comes from the ranking and from what already works in related diseases, not from the specific genes they share. OREVID is a hypothesis generator, not a clinical tool; code, data and benchmark are public (https://orevid.org, doi:10.5281/zenodo.23323226).

Abstract: Background. Toxic metals and essential minerals share transport, binding, and elimination pathways, so toxic-metal handling depends partly on mineral status. Interventions supplying a broad spectrum of minerals may therefore alter urinary toxic-metal excretion. Methods. Prospective, open-label, controlled pilot study. Experimental participants — a clinic population under treatment for chronic post-viral and post-vaccination illness — treated all drinking water with a biotite-derived sulfated ionic mineral solution at 5 mL per gallon and, as tolerated, added a concentrated oral dose of 1 mL per 20 pounds of body weight twice daily; healthy comparators received no intervention. Of 42 enrolled, 30 contributed paired specimens (20 experimental, 10 comparator) after withdrawals and the exclusion of six participants above the protocol age limit of 70 years. Urine panels covering 38 elements were obtained at baseline and follow-up (median interval 54 days, IQR 47–88). The protocol’s primary outcome was change in urinary toxic element levels; we compared changes from baseline between arms using the Mann–Whitney U test without multiplicity correction. A post hoc composite counted how many of six toxic metals — aluminum, arsenic, cadmium, lead, mercury, thallium — rose more than 15% from baseline; the threshold was fixed before that analysis and afterward a robustness check varied the threshold from 0 to 50% increases. Results. The protocol’s primary outcome — element-level change across the panel — was null: of the 38 elements measured, 29 had sufficient paired data for testing, and two reached nominal significance, aluminum (p = 0.024) and selenium (p = 0.018), against approximately 1.45 expected by chance; neither survives correction for multiplicity. The post hoc composite was not null. Experimental participants increased excretion across more toxic metals than comparators: a median of 3.0 of six versus 1.5 (p = 0.023, and p = 0.007–0.032 at every threshold from 0 to 50%). At least two metals rose in 95.0% versus 50.0% (p = 0.009). Applying the same threshold to six essential minerals, the arms did not differ (median 2.0 versus 2.0, p = 0.82). At post-study interview, eight of the 29 participants allocated to the experimental arm (27.6%) reported adverse effects: three were moderate to severe and required dose reduction or interruption; all resolved with adjustment, and none was serious. Five (17.2%) reported subjective improvement, and two more asked to continue treatment without describing a specific change; comparators were not interviewed. Conclusions. A biotite-derived sulfated ionic mineral complex was associated with increases in urinary excretion of more toxic metals than in contemporaneous comparators, while the number of essential minerals with increased excretion did not differ between arms. The direct within-person contrast favors selectivity for toxic elements by 15.8 percentage points (95% CI −10.3 to +41.5), an estimate this pilot is too small to resolve. The cause and mechanism of this change are uncertain, and urinary excretion alone cannot establish that body burden fell.

Abstract: Background: Diabetes mellitus is a chronic metabolic disorder associated with persistent hyperglycemia, oxidative stress, inflammation, and progressive organ damage. The present study investigated the antidiabetic potential of Kura Mynis (KM), a novel polyherbal formulation containing multiple bioactive plant extracts with reported glucose-lowering, antioxidant, and anti-inflammatory properties. Methods: The antidiabetic activity of KM was evaluated using in vitro α-amylase, α-glucosidase, xanthine oxidase, anti-inflammatory, and DPPH radical scavenging assays. Insulinotropic activity was assessed in MIN6 pancreatic β-cells, while cytotoxicity was determined using the MTT assay in HepG2 cells. In vivo efficacy was evaluated in streptozotocin-induced diabetic Wistar rats treated orally with KM (2055 and 4102 mg/kg) for 21 days. Blood glucose levels, body weight, lipid profile, liver function markers, and histopathological changes in pancreatic, hepatic, and renal tissues were assessed. Results: KM exhibited concentration-dependent inhibition of α-amylase (85%), α-glucosidase (58%), and xanthine oxidase (67%) at 100 µg/mL. Significant anti-inflammatory activity (44%) and potent antioxidant activity were observed, with 94.11% DPPH radical scavenging and an IC₅₀ value of 86.93 µg/mL. KM enhanced insulin secretion in MIN6 cells by approximately 2.6-fold at 100 µg/mL without inducing cytotoxicity. In diabetic rats, KM significantly reduced fasting and postprandial blood glucose levels, improved body weight, and produced group-dependent modulation of serum transaminase and lipid parameters. Pancreatic, hepatic and renal histoarchitecture were substantially restored in a dose-dependent manner. Conclusion: KM exerts significant antidiabetic effects through multiple mechanisms, including enzyme inhibition, antioxidant and anti-inflammatory activities, enhancement of insulin secretion, and histological preservation of pancreatic, hepatic and renal tissue. Effects on serum transaminases and lipids were modulatory and were not uniform across treatment groups. These findings support KM as a promising polyherbal candidate for diabetes management and its associated complications.

Abstract: Background: Liposomal vitamin C is marketed almost entirely on enhanced oral bioavailability, and preclinical rodent pharmacokinetic studies are routinely commissioned to support that positioning. Rats, unlike humans, retain a functional L-gulonolactone oxidase and synthesise ascorbate endogenously. Whether a rat can detect a difference in oral vitamin C delivery at all is seldom tested, because untreated control arms are seldom included. Methods: A spray-dried liposomal vitamin C powder was characterised by dynamic light scattering and administered to young adult male Sprague Dawley rats as a single oral dose in a four-arm design: reverse osmosis water, liposomal vitamin C at 1000 and at 2000 mg per kg body weight, and commercially available ascorbic acid at 2000 mg per kg as an active comparator. Plasma was sampled at seven time points to 24 hours and vitamin C quantified by liquid chromatography coupled to mass spectrometry. Non-compartmental pharmacokinetic parameters were derived for three animals per arm. Group means, dispersion and Welch two-tailed comparisons were recomputed by the present authors from the individual parameter values. Results: At the matched 2000 mg per kg dose, the liposomal arm showed 3.08 times the mean maximum plasma concentration (0.40 against 0.13 micrograms per millilitre) and 2.14 times the mean area under the curve (3.92 against 1.83 hour-micrograms per millilitre) of the ascorbic acid comparator. Neither difference reached statistical significance at three animals per arm (p = 0.19 and p = 0.18). The untreated control arm recorded a mean area under the curve of 1.65, statistically indistinguishable from the ascorbic acid arm (p = 0.90), and the liposomal arm at 1000 mg per kg recorded 0.69, below the untreated animals. Maximum concentration occurred at the terminal 24-hour sampling point in most animals, and absolute plasma concentrations across all arms, controls included, were one to two orders of magnitude below the accepted physiological range for rat plasma ascorbate. Dynamic light scattering returned a mean vesicle diameter of 392.7 nanometres and a zeta potential of minus 1.4 millivolts. Conclusions: A 2000 mg per kg oral dose of unencapsulated ascorbic acid produced plasma exposure indistinguishable from administering nothing. The Sprague Dawley rat therefore cannot resolve oral vitamin C bioavailability at these doses, because endogenous synthesis dominates the measured pool. The directionally consistent advantage of the liposomal formulation is compatible with enhanced delivery but is not established by these data. We argue that rodent pharmacokinetic studies of vitamin C formulations are uninterpretable without an untreated control arm, and that species incapable of ascorbate synthesis, or human crossover designs, are the appropriate test systems.

Abstract: Large language models (LLMs) and autonomous agents can synthesise scientific arguments and construct computational models rapidly, but fluency is not scientific validity. Neither expert status, human oversight, multi-agent consensus, publication nor patent protection substitutes for independent empirical testing. Experiments themselves can conflict because of bias, measurement error or genuine biological heterogeneity. We propose an evidence-to-decision trust architecture for drug research and model-informed drug development (MIDD) that links verifiable primary observations, provenance and uncertainty to competing mechanistic hypotheses, adversarial AI review, discriminating experiments and accountable decisions. Credibility is evaluated for a specified context of use, not assigned globally to people or algorithms. The framework spans target validation, translational pharmacology, dosing, clinical development and regulatory assessment, illustrated by a proposed IQANOVA ATLAS AI–quantitative systems pharmacology (AI-QSP) workflow. We extend the framework to regulatory agencies using AI agents: scientific assessment and model credibility are distinct from the legally binding act of medicine authorisation. Inspired by Juvenal's question of who checks the guardians and the historical Rabkrin inspection debate, we propose auditable agent roles, explicit legal decision rights, independent scrutiny and routes for challenge. A synthetic SBML/SED-ML/COMBINE package with provenance ontologies illustrates reproducible reporting without claiming biological validation. A prospective benchmark is proposed to test scientific quality, regulatory decision loss, agent independence and appeal outcomes. The final question—whether, when and under whose authority an AI could make binding decisions—remains unresolved.

Abstract: Cellular morphology captures compound-induced changes in cell state, but the relationship between the magnitude of these changes and absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties remains dependent on the endpoint and assay context. We developed MorphADMET to examine these relationships and evaluate complementary prediction and reference-retrieval tasks across six imaging datasets, seven morphological representations, eleven binary endpoints, and aqueous solubility. Endpoint comparisons used differences in median morphological response with 95% bootstrap confidence intervals from 2,000 resamples. Positive compounds showed greater responses in selected contexts, including A549–Ames, HUVEC–CYP1A2, HUVEC–CYP3A4, and HRCE–CYP2D6, whereas U2OS hERG-negative compounds showed greater responses. Structure-based ensembles predicted strong morphological responses with average precision (AP) of 0.353–0.472 and outperformed a compact descriptor baseline in four of five contexts. Models using measured morphology showed endpoint-dependent discrimination, including AP of 0.601 and AUROC of 0.786 for hERG in A549 cells. Exploratory compartment-level analyses identified differences in nuclear texture, cytoplasmic organization, and cell shape between endpoint-label groups. In the structure-based ADMET benchmark, MorphADMET achieved the highest observed AP for four of eleven classification endpoints and the lowest solubility mean absolute error, 0.660 log10 mol/L. Morphology-selected reference compounds showed higher class-balanced hERG label agreement than random references in all six cellular contexts. A CYP2D6 neighborhood illustrated shared physicochemical properties alongside partial scaffold similarity. These findings support endpoint-specific use of chemical and morphological information for compound assessment, while distinguishing overall perturbation, predictive discrimination, and retrospective reference agreement.

Abstract: Objective: Under in vivo conditions, empirical observation of competition for the same target in different living tissues is almost impossible. Moreover, in vitro \(\mathrm{K}_{\mathrm{i}}\) (inhibition constant – see p.2) values may not correlate with in vivo results. To investigate possible in vivo competitions more realistically, the author has proposed the concept of the "competition coefficient" (\(\mathrm{R}_{\mathrm{c}}\)) and a competition rule based on it. The objective has been to theoretically determine the relationships between the competition coefficient (\(\mathrm{R}_{\mathrm{c}}\)) and ligand-target binding affinity, therapeutic effect, adverse effects, volume of distribution (\(\mathrm{V}_{\mathrm{d}}\)), selectivity, and duration of action (\(\mathrm{T}_{1/2}\)), and to apply them in clinical practice. Materials and Methods: The theoretical calculation of \(\mathrm{R}_{\mathrm{c}}\) was defined as \(\mathrm{R}_{\mathrm{c}}=\mathrm{m}_{\mathrm{act}}/\max(\mathrm{f}_{\mathrm{u}},\mathrm{f}_{\mathrm{b}})\). Various in vivo competition cases for binding to the same target were investigated. Extensive statistical analysis was performed using comparative tables of different pharmacological groups including statins, angiotensin receptor blockers, proton pump inhibitors and antipsychotics. Protein binding (PB%), free fraction (\(\mathrm{f}_{\mathrm{u}}\)), bound fraction (\(\mathrm{f}_{\mathrm{b}}\)) and number of active metabolites (\(\mathrm{m}_{\mathrm{act}}\)) were analyzed from published literature and drug databases. The relationship between \(\mathrm{R}_{\mathrm{c}}\) and pharmacokinetic parameters was evaluated. Results: Within the same pharmacological group, an increase in \(\mathrm{R}_{\mathrm{c}}\) was associated with increased ligand-target binding affinity, therapeutic effect, selectivity and prolonged duration of action (\(\mathrm{T}_{1/2}\)). The competition rule accurately predicted displacement interactions in cases where drugs share the same binding site. Comparative analysis showed consistent patterns across different drug classes. Conclusion: Instances of competition within the body can involve not only medicinal substances but also other substances capable of binding to blood proteins. Theoretical findings were consistent with established practical data. The proposed \(\mathrm{R}_{\mathrm{c}}\) may be useful for predicting drug competition, rational drug combinations and drug development.

Abstract: Background/Objectives: Postoperative central nervous system (CNS) infections are severe compli-cations of neurosurgery, and vancomycin is a cornerstone of empirical and targeted therapy; how-ever, longitudinal vancomycin exposure in this population is poorly characterized. Methods: We conducted a single-centre retrospective cohort study of 189 postoperative CNS infection episodes in 174 adults treated between 2020 and 2026, focusing on longitudinal vancomycin exposure and pharmacokinetic.pharmacodynamic (PK/PD) target attainment according to therapeutic drug mon-itoring (TDM) status. A population pharmacokinetic (PopPK) model, developed from 193 concen-trations was used to reconstruct exposure in TDM episodes and simulate exposure for no TDM ep-isodes. Results: The final PopPK model confirmed creatinine clearance (CrCl) as the principal de-terminant of vancomycin clearance; higher baseline CrCl independently predicted a greater propor-tion of treatment time with AUC24 <400 mg·h/L. Underexposure occurred throughout: patients spent 37.2% (TDM) and 47.5% (no TDM) of evaluable treatment time below AUC24 400 mg·h/L, with early underexposure even more common in both groups. The TDM group spent more time within the AUC₂₄ 400–600 mg·h/L range (43.23% vs 29.91%). No statistically significant exposure–outcome associations were identified in the overall population. In an exploratory ICU subgroup analysis, higher mean AUC₂₄ was associated with clinical improvement within 72 h (OR 1.92 per 100 mg·h/L increase, 95% CI 1.12–3.28), although the exposure-by-ICU interaction was not statistically signifi-cant. Conclusions: These findings support early and repeated vancomycin TDM throughout treat-ment to identify and address underexposure, particularly in patients with augmented renal function and those treated in ICU.

Abstract: Drug-safety evaluation rests on a largely implicit structural-determinist premise: that a defined molecular design feature, such as an engineered silencing modification, secures safety across host contexts. Extreme human populations living under sustained environmental stress (for example, indigenous communities at chronic high altitude) constitute naturally occurring, high-sensitivity settings in which this premise can be probed, because a molecular design that is unremarkable in a standard-population trial may behave differently under extreme host conditions. This review articulates a framework that treats extreme populations as a natural stress-test for drug safety and that converts a single, catastrophic sentinel toxicity event into defensible causal inference without over-claiming. We synthesize three strands: the theoretical case for extreme-population pharmacology as an institutionalized observation window; the methodological status of the sentinel case as a naturally imposed, exhaustively documented experiment whose inferential weight derives from inference architecture rather than sample size; and an operational four-tier causal ladder, FOCUS (spatial necessity, temporal priority, biological plausibility, and counterfactual intervention), expressed through a DABR workflow (Data-anchored, Assumption-explicit, Boundary-declared, Reproducible). FOCUS functions as a gate rather than a verdict: a claim advances only as far as its evidence supports, and unmet tiers are declared rather than imputed. We further specify the disciplines that keep a low-n framework honest, namely explicit grading of certainty, the rule that claim strength must not exceed evidence strength, and the treatment of a declared absence of evidence as an evidentiary asset. Finally, we argue that novelty should be asserted as a bounded claim, that reproducibility is a governance requirement rather than an aspiration, and that the framework's value lies in stating both the standard such studies should meet and the claims they should not make. This review is framework-level and deliberately contains no primary data claims; the applied analytic operations implied by the framework belong to companion work.

Abstract: Population estimation methods in routine use (FOCE-I, SAEM, importance-sampling EM) assume that model predictions vary smoothly with the individual parameters. That makes residuals informative and lets the individual likelihood be approximated locally. Both assumptions fail for chaotic structural models, which matter more and more for oscillatory pharmacodynamic systems such as hormone pulsatility and glucose–insulin dynamics. We present a reproducible two-stage pipeline and test it on an intentionally challenging benchmark: 16 Lorenz-63 subjects with log-normal inter-individual variability (IIV), a bimodal population straddling a bifurcation (8 chaotic, 8 periodic), one observed state, and 20% proportional residual error. Stage 1 replaces residual-based likelihoods with feature matching by the simulated method of moments, using features scaled to each subject’s own oscillation period. It also replaces covariance-based standard errors, which inflated the IIV of the weakly identified parameter σ more than five-fold, with objective-function profiles. The scale of these profiles is calibrated per regime by simulating at the subject’s own estimates. Stage 2 combines the profiles in exact-grid or Gibbs hierarchical posteriors, including a mixture model analogous to NONMEM $MIXTURE. Diagnostics include feature-based, marginal-quantile, and peak-aligned visual predictive checks (VPCs), EBEs with shrinkage, and Lyapunov classification. The method recovered the residual error (0.1992 vs 0.200), mixture fraction (0.500 vs 0.500), σ typical value (10.04 vs 10.12), and β IIV (0.057 vs 0.052), and cut individual-estimate EBE error five-fold with respect to the Stage 1 estimates. The IIV of σ was underestimated (0.017 vs 0.032). Chaotic subjects carry almost no information on σ (93% shrinkage), so this estimate effectively reflects the periodic subpopulation. Peak-aligned VPCs passed in the periodic stratum (9% of points outside the 90% intervals) but not in the chaotic stratum (20%), indicating residual misspecification.

Abstract: Background: Cholestasis liver diseases involve impaired bile flow and the buildup of potentially harmful bile acids in liver, which damages hepatocytes and cholangiocytes. Ongoing, cholestasis triggers inflammation, oxidative stress, mitochondrial dysfunction, apoptosis and progressive liver fibrosis. Although oxidative stress is now acknowledged as a key factor in cholestatic liver injury, its connection to metabolic and inflammatory pathways and its therapeutic potential still need further investigation. Main body: This review explores the relationship between obstructive liver injury and oxidative stress, focusing on the molecular mechanisms involved and potential treatments. The buildup of bile acids leads to increased production of reactive oxygen species, lipid peroxidation, oxidative DNA damage, and mitochondrial dysfunction, which worsens cell damage and inflam-matory signals. Mitochondrial impairment disrupts energy metabolism and redox balance, while changes in fatty acid oxidation and increased glycolysis contribute to metabolic reprogramming during cholestatis. Neutrophils and other inflammatory cells can further exacerbate oxidative damage by producing reactive oxygen and nitrogen species. These processes lead to apoptosis of hepatocytes and cholangiocytes, activation of hepatic stellate cells, deposition of extracellular ma-trix, and advancement to fibrosis. The review compiles current evidence from primary sclerosing cholangitis, primary biliary cholangitis, intrahepatic cholestasis, and experimental models of ob-structive and drug- induced cholestatic liver injury. Special focus is placed on antioxidant defenses, protecting mitochondria, regulating bile acid balance, and pharmacological approaches to reduce oxidative and inflammatory damage. New treatments that target redox imbalance and enhance bile flow may offer ways to slow disease progression, especially for patients who do not respond well to standard therapies. Conclusion: Oxidative stress is central mechanistic link between bile acid ac-cumulation, inflammation, mitochondrial dysfunction, and fibrosis in cholestatic liver disease. A deeper insight into this interconnected network may aid in developing targeted antioxidant and mitochondrial therapies,improving outcomes in obstructive liver injury.

Abstract: To provide a comprehensive context, this review first elaborates on the history, mechanism of action, environmental fate, toxicological profile, and general toxicokinetics of Glyphosate (GLY). While the primary ingredient in Roundup®, GLY is traditionally characterized by rapid systemic clearance and low bioaccumulation, this review challenges that paradigm by proposing the skeletal system acts as a critical ‘deep compartment’ for long-term sequestration. Due to the strong affinity of its phosphonate functional group for bone minerals, GLY binds readily to hydroxyapatite, the same mineral matrix targeted by bisphosphonates. Research indicates that while GLY levels decline rapidly in soft tissues, the skeleton acts as a significant reservoir, maintaining high concentrations long after initial exposure. We propose a dual role for the skeleton: first, as "victim," in which sequestered GLY induces oxidative stress and disrupts mineral structure; and second, as "perpetrator," in which the herbicide is released back into the bloodstream during bone remodeling. This endogenous release suggests that physiological states involving high bone turnover, such as pregnancy, lactation, and postmenopause, may trigger chronic internal exposure, even without external intake. Finally, current safety assessments likely suffer from a "one-compartment bias," underestimating GLY’s true biological half-life and its contribution to chronic diseases like renal failure and cancer.

Abstract: Kawasaki disease (KD) is an acute systemic vasculitis and the leading cause of acquired heart dis-ease in children, highlighting the need for alternative therapeutic strategies, particularly for pa-tients resistant to intravenous immunoglobulin therapy. This study comparatively investigated the therapeutic potential of Vitis vinifera leaf and fruit exocarp phytochemicals against KD using an integrated in silico framework consisting of network pharmacology, molecular docking, molecular dynamics simulation, and an evidence-weighted target ranking model. After ADME screening, three leaf-derived and seven exocarp-derived bioactive compounds were retained for analysis. Network pharmacology identified 127 overlapping KD-associated targets for the leaves and 109 for the fruit exocarp, with both datasets demonstrating significant protein–protein interaction en-richment. Molecular docking and molecular dynamics analyses revealed stable interactions of quercetin with AKT1 and myricetin with MMP9, supporting their potential therapeutic relevance. Multi-objective target prioritization further identified biologically relevant and druggable candi-date targets. Overall, the findings suggest that V. vinifera contains promising multi-target phyto-chemicals capable of modulating key inflammatory pathways involved in Kawasaki disease and provide a computational foundation for future experimental validation and therapeutic develop-ment.

Abstract: Kidney diseases, including acute kidney injury and chronic kidney disease, represent a growing global health burden associated with nephrotoxic drugs, environmental toxins, metabolic disorders, and aging. Nephrotoxicity arises through complex and interconnected mechanisms, including oxidative stress, inflammation, mitochondrial dysfunction, apoptosis, tubular epithelial cell injury, fibrosis, and altered glomerular hemodynamics, ultimately leading to progressive renal dysfunction. The limited sensitivity of conventional biomarkers for early diagnosis and the lack of effective targeted therapies highlights the need for novel preventive and therapeutic strategies. In recent years, phytomedicines have attracted considerable attention owing to their multitargeted pharmacological actions and favorable safety profiles. This comprehensive review summarizes the molecular mechanisms underlying nephrotoxicity, major nephrotoxic agents, and recent advances in nephroprotective medicinal plants, herbal formulations, and phytocompounds. Bioactive constituents, including flavonoids, polyphenols, alkaloids, terpenoids, saponins, and phenolic acids, exert renoprotective effects by attenuating oxidative stress, suppressing inflammatory signaling pathways such as NF-κB, regulating apoptosis and autophagy, preserving mitochondrial function, and activating cytoprotective pathways, particularly Nrf2/HO-1. Experimental studies consistently demonstrate that phytocompounds such as curcumin, dioscin, ferulic acid, thymoquinone, quercetin, and resveratrol improve renal biochemical, molecular, and histopathological outcomes across diverse models of nephrotoxicity. The review also critically discusses available clinical evidence, pharmacokinetic limitations, issues of standardization and quality control, safety considerations, and emerging strategies to enhance clinical translation. Collectively, evidences highlight phytomedicines as promising candidates for preventing and managing nephrotoxicity and kidney diseases while providing a scientific framework for future mechanistic studies, biomarker-guided investigations, and well-designed clinical trials to facilitate the development of effective renoprotective therapeutics.

Abstract: ICH Q1B defines the standard photostability-testing requirements for drug products, including exposure to at least 1.2 million lux hours of visible light and 200 W·h/m² of near-ultraviolet radiation. Finalized in 1996, the guideline was developed when biologics represented only a small share of approved medicines. Today, biologics account for roughly one-third of new FDA approvals, raising the question of whether Q1B remains fit for purpose for monoclonal antibodies. This review identifies four major mismatches between the guideline and antibody products: the test exposure is often too harsh, the spectral profile differs from ordinary manufacturing and clinical lighting, indirect photochemical routes through excipients and trace metals are not adequately represented, and conventional endpoints do not capture key antibody liabilities such as aggregation, fragmentation, charge heterogeneity, and loss of Fc receptor binding. The article reviews the underlying photochemistry of antibody photodegradation, maps light exposure across the product life cycle, examines formulation and packaging mitigation strategies, and proposes a two-track framework that separates forced-degradation hazard identification from testing against realistic product exposure.

Abstract: The multi-attribute method (MAM) is a liquid chromatography–mass spectrometry (LC–MS) platform that combines site-specific quantitation of critical quality attributes (CQAs) with non-targeted new peak detection (NPD) in a single workflow, and can consolidate several conventional chromatographic and electrophoretic assays used to control biotherapeutics. More than a decade after its introduction, MAM is widely used for characterization, yet its adoption for release and stability testing in current Good Manufacturing Practice (cGMP) quality control (QC) laboratories remains limited, primarily by technical rather than conceptual or regulatory barriers. In this review, we examine method-induced artifacts and their control during sample preparation, the role of automation, chromatographic and mass spectrometric requirements, software-dependent variability, and the parameter setting and false-positive management required for robust NPD. In addition, we summarize applications across the product lifecycle and the regulatory framework for QC implementation. For each barrier, we assess the readiness of the reported solutions for implementation and identify the gaps where further innovation is most needed. Within the literature identified, most barriers have documented solutions, although only a subset have been demonstrated across independent laboratories. This review is intended as a practical reference for laboratories developing, qualifying, or transferring MAM workflows.

Abstract: Background/Objectives: Antineoplastic therapies have improved cancer survival but remain a major source of treatment-related cardiotoxicity. Previous pharmacovigilance studies have largely focused on drug-specific cardiac signals or individual therapeutic pathways, whereas cross-class differences in cardiovascular reporting across MedDRA categories and their impact on disproportionality estimates remain less well characterized. We therefore compared cardiac adverse-event reporting patterns across anthracyclines, anti-HER2 agents, and anti-VEGF agents within a restricted antineoplastic comparator cohort. Methods: A retrospective pharmacovigilance study was conducted using aggregated ICSR data from VigiBase accessed through the public VigiAccess interface (March 23, 2026). Eight antineoplastic agents were grouped into three therapeutic classes. Descriptive analyses of demographic characteristics, System Organ Class (SOC) distributions, and cardiac Preferred Terms (PT) were performed. Reporting Odds Ratios (ROR) with 95% confidence intervals were calculated using a restricted antineoplastic comparator cohort. Signals were defined as a lower 95% CI bound >1 with at least five cardiac reports. Results: Across eight drug-specific VigiAccess queries, 389,068 drug-specific report observations were analyzed. Anti-HER2 agents showed the highest proportional cardiac-reporting burden (10.43%) and the strongest class-level disproportionality signal (ROR 2.04; 95% CI: 1.99–2.10), with trastuzumab showing the strongest individual-drug estimate (ROR 2.22; 95% CI: 2.16–2.29). Anthracyclines accounted for the largest number of cardiac reports (n = 11,273), with a reporting pattern dominated by myocardial-dysfunction Preferred Terms, led by cardiomyopathy and heart failure. Anti-VEGF agents showed greater reporting within the Vascular disorders (10.86%) and Renal and urinary disorders (6.08%) SOCs, with myocardial infarction among the most frequently reported cardiac PTs. Conclusions: Cardiac adverse event reporting for antineoplastic therapy follows class-specific patterns rather than a uniform profile. Anti-HER2 agents showed the highest proportion of reports classified under Cardiac disorders, anthracyclines the greatest absolute volume, and anti-VEGF therapies exhibited a distinct vascular–ischemic reporting profile. These reporting-based signals may support hypotheses regarding class-specific cardiovascular surveillance consistent with established cardio-oncology guidance, while highlighting both the value and the inherent limitations of global spontaneous-reporting pharmacovigilance data. These findings are hypothesis-generating and should be interpreted as reporting patterns rather than incidence estimates, comparative clinical risks, or causal effects. Spontaneous-reporting data remain susceptible to reporting bias, unmeasured confounding, and incomplete clinical information.

Abstract: Background: Phenol matrixectomy is widely utilised to manage onychocryptosis. Concerns regarding its safety in pregnancy and breastfeeding persist, despite limited direct evidence of adverse events. Previous work by the authors suggested that systemic phenol dosage to a pregnant woman during nail surgery was negligible; however, a subsequent review of that publication identified a mathematical calculation error and an underestimation of phenol dose.Methods: We conducted a narrative critical review in 2022, drawing on clinical, toxicological, occupational, and epidemiological literature, including original work. We recalculated exposure estimates and contextualised them against established toxicological thresholds.Results: Epidemiological studies demonstrate widespread background exposure to a range of phenolic compounds during pregnancy, with inconsistent associations with adverse outcomes. Animal studies indicate developmental toxicity at high systemic doses. Corrected calculations demonstrate that phenol exposure during nail surgery may be substantially higher than we previously reported; however, actual systemic phenol absorption remains unknown. Conclusion: Phenol exposure during matrixectomy remains a risk-uncertain intervention because the lack of pharmacokinetic data prevents definitive risk assessment.

Abstract: The underrepresentation of Nigerian genetic diversity in global databases presents an evidence gap in the population-specific effects of pharmacogenotypes on the therapeutic efficacy and safety within the country and relative to other populations. We investigated the implementation of pharmacogenetics in clinical trials and conducted a systematic review to identify clinical pharmacogenetic studies in Nigerians. Out of 11 clinical trials that have pharmacogenetic implications per U.S. FDA guidelines, only two implemented pharmacogenetics, predisposing participants to potential adverse drug effects and efficacy issues. Nigerian pharmacogenetic studies are limited, as fewer studies investigated the clinical significance of allele frequencies. Distribution of allele frequencies varied significantly within Nigerians and between other populations in high-impact variants, including CYP2C9*8, CYP2D6*29, and CYP3A5*7. CYP2C8*2 was observed at 17.9-19.5% in Nigerians compared to <2% in Europeans and Asians and resulted in lower imatinib concentrations in homozygous carriers, raising concerns about efficacy and safety. Marked ethnic differences within Nigerians (1% in Esan and 4.2% in Yoruba), compared to 2.6% in Sub-Saharan Africans, were observed in the African-ancestry DPYD 557A>G variant, which is not always present in UK and European genotyping panels, raising concerns about fluorouracil toxicity in Nigerians in diaspora and mixed-race populations. In conclusion, we found poor implementation of pharmacogenetics in clinical trials within the country and limited understanding of allele frequencies and their clinical implications. Therefore, it is important to investigate intra-Nigerian and intercontinental differences between genotypes and phenotypes to advance global precision medicine initiatives.