Advancing Open Science

Background: Chlorine dioxide (ClO₂), formulated as an aqueous solution (CDS), has been proposed as a therapeutic agent, yet its classification among oxidizing compounds is frequently confounded with chemically distinct species—sodium chlorite (NaClO₂) and sodium hypochlorite (NaOCl). Objective: This study aimed to synthesize the physicochemical, mechanistic and cellular basis of ClO₂ action and to delineate the distinctions between ClO₂ and related oxidants, with explicit separation of established data from hypothesized data. Methods: The methodology includes a narrative synthesis of electrochemical data, primary toxicological and clinical literature (PubMed) and the redox-biology literature on low-dose oxidant signaling. Results: ClO₂ is a neutral free radical that acts via one-electron transfer (E°′ = +0.95 V vs. SHE for the half-reaction ClO₂ + e⁻ → ClO₂⁻, essentially pH-independent over pH 4–8, pH-independent) without chlorination. Its antimicrobial action is attributable to oxidation of thiol-dependent enzymes and membrane constituents and to the inhibition of bacterial respiratory metabolism; host-cell sparing is consistent with differential glutathione-dependent buffering. Controlled human ingestion studies at low concentrations report a favorable short-term safety profile; conversely, the principal metabolite (chlorite) is associated with documented developmental toxicity in animals and regulatory caution by EPA/WHO. Low-dose ClO₂ exposure is hypothesized—but not yet directly demonstrated—to elicit dose-dependent adaptive redox responses and redox-regulatory modulation. Conclusions: The one-electron, non-chlorinating chemistry of ClO₂ provides a coherent mechanistic framework. The translation of this framework into clinical application requires prospective trials and direct mechanistic measurement, ideally conducted by independent investigators. The following mechanisms are hypothesized and have not yet been directly demonstrated in vivo: modulation of oxidative phosphorylation, mitochondrial oxygenation, and associated redox-regulatory signaling. Reported antimicrobial efficacy typically occurs in the low-ppm range (0.1–5 ppm), whereas adverse effects on mammalian cells in the reviewed literature are reported at concentrations at least one order of magnitude higher; direct head-to-head cytotoxicity comparisons remain scarce and are identified as a priority for future work. This differential thiol buffering—in particular, the higher glutathione content of many mammalian cells relative to many pathogens—has been proposed as a contributing basis for host-cell sparing; direct quantitative confirmation in vivo is not yet available. Bacterial species possess their own thiol-based defense systems (e.g., mycothiol in actinomycetes, bacillithiol in Firmicutes), and the interplay between ClO₂ and these systems requires further investigation.

Background/Objectives: Understanding genomic responses to environmental contamination is essential for assessing long-term ecological and genetic risk. The free-breeding dogs inhabiting the Chornobyl Exclusion Zone (CEZ) offer a unique, multigenerational model for investigating these responses within a chronically contaminated landscape. Following the 1986 radioecological disaster at the Chornobyl Nuclear Power Plant, and subsequent remediation activities, the surrounding environment was contaminated by ionizing radiation, heavy metals, organic compounds, and other environmental toxicants. Our previous work identified significant genetic differentiation between two distinct but geographically proximate dog populations within the CEZ, a pattern not explained by breed composition, spatial isolation, or increased mutation rates. Methods: In this study, we tested the hypothesis that the dogs residing at the nuclear power plant show genomic signatures consistent with adaptive evolution in response to chronic environmental stressors. This work extends prior population-genetic analyses by integrating whole-genome selection scans with estimates of effective population size and comparative measures of population divergence, providing a framework to evaluate whether the observed genomic differentiation is more consistent with selection than demography. Using these whole genomic data, we evaluated chromosome-level F_ST metrics, estimated effective population size (N_e), and analyzed a geographically isolated island dog population as a comparative reference for genetic divergence. Results: We continued to find that the levels of genetic differentiation are not comparable to other free-breeding dog populations. Genome-wide outlier analyses identified candidate loci showing evidence of positive selection across multiple metrics. Conclusions: Genes associated with these loci were enriched for biological functions related to DNA replication and repair, cell death and survival, cellular compromise, immune response, and cancer-associated pathways, suggesting biologically plausible mechanisms through which chronic environmental stress could influence fitness. These findings are consistent with directional selection in the nuclear power plant population, which could potentially be associated with the environmental variables present, and advance our understanding of local adaptation and genomic resilience under chronic environmental contamination.

Neglected tropical diseases (NTDs) caused by Leishmania and Schistosoma species continue to impose a significant health burden in endemic regions, largely due to limited therapeutic options, drug resistance, and incomplete understanding of parasite biology at the molecular level. A major restriction in the development of targeted interventions is the structural inaccessibility of parasite membrane-associated proteins, which are central to host invasion, nutrient transport, immune evasion, and survival. Recent advances in cryogenic electron microscopy (cryo-EM) have expanded the structural biology toolkit available for studying difficult parasite proteins, particularly large and membrane-associated macromolecular assemblies. However, experimentally resolved cryo-EM structures remain limited for many of the Leishmania and Schistosoma targets relevant to therapeutic and vaccine development. This review therefore distinguishes experimentally determined structures from partial structural information and computational models and examines how potential cryo-EM approaches may address unresolved structural questions. We discuss current structural knowledge of selected parasite targets, approaches for recombinant expression and membrane-protein stabilization, membrane-mimetic systems for structural characterization, and computational methods that complement experimental structural biology. We further examine how experimentally supported structural information, complemented by computational predictions where appropriate, could contribute to structure-guided drug discovery, vaccine design, and targeted nanomedicine. At present, however, the direct translation of parasite structural information into rational nanotherapeutic design remains limited. Key gaps include the scarcity of experimentally resolved parasite membrane protein structures, challenges in their expression and structural characterization, and limited integration of structural biology with nanoparticle engineering. Resolving these gaps may improve the prospects for structure-informed therapeutic and nanomedicine applications against leishmaniasis, schistosomiasis, and other NTDs.

The behavior of ions at the electric double layer interfacial region between solid and liquid phases is well known in surface and material science. However, this is not fully the case in soil science, where the electric double layer develops due to the inherent complexity and diversity of negatively charged soil organic matter molecules that sorb at the mineral surface. This lack of knowledge opens questions regarding the interaction mechanisms at the molecular scale that lead to the stabilization of such soil building blocks, the so-called organo-mineral aggregates. By using classical molecular dynamics simulations, we studied the interactions between Kaolinite and four standardized soil organic matter samples with different aromatic and carboxylic content and Ca²⁺ cations clustering OM molecules and stabilizing them to the surface. We assessed the influence of (i) organic content, (ii) water content, and (iii) competing Cl⁻ ions. Cluster aggregates are favored in soils with a high aliphatic fraction at low-water content, whereas aggregation is favored in soils with high aromatic fraction at high-water content and in the presence of Cl⁻ ions. Moreover, samples with a low acid fraction favor clustering due to non-bonded interactions and hydrogen bonds. All of these environments are reflected as unique charge-density “fingerprints” and surface coverage for each OM sample. This work represents a step towards the characterization and study of natural soils tunable to specific local conditions.

Non-dilated left ventricular cardiomyopathy (NDLVC) presents a unique clinical paradox: patients with nearly identical phenotypes can face radically different clinical outcomes. NDLVC has been recently recognized as a distinct dynamic phenotype within the spectrum of non-ischemic cardiomyopathies, linked by a high risk of life-threatening arrhythmias. Recent advances in genetics have overcome clinical phenotyping in prognostic accuracy. Specifically, gene-specific scores have been introduced to guide primary prevention ICD in high-risk gene carriers. On the other hand, while gene-elusive cases present a more favourable arrhythmic profile, their long-term clinical outcome is more challenging to predict. Despite advancements in therapeutic strategies, the heterogeneity of the disease represents an ongoing dilemma for risk stratification and long-term surveillance. This review offers a comprehensive analysis of NDLVC management in clinical practice, highlighting the profound prognostic divergence between genetic (both in actionable and VUS carriers) and gene-elusive cohorts. By synthesizing current evidence, we aim to clarify how genotype–phenotype correlations influence clinical outcomes and to provide a framework for more personalized approaches in the follow-up and treatment of these distinct patient populations. Furthermore, we address the current lack of standardized guidelines specifically tailored to gene-elusive phenotypes. In conclusion, NDLVC management requires a paradigm shift towards a multi-parametric, genotype-directed framework, where cardiac magnetic resonance tissue characterisation and personalized risk scores are essential to optimize sudden cardiac death prevention. Future research must leverage artificial intelligence and polygenic risk scores (PRSs) to integrate multi-parametric clinical-imaging data and refine risk stratification beyond traditional binary models. Concurrently, human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) will be pivotal as a translational platform to clarify VUS pathogenicity, unravel gene-specific arrhythmic mechanisms, and accelerate targeted therapeutic interventions.

Extreme precipitation and hail events over complex terrain are strongly dependent on the multiscale evolution of convective systems, yet their development remains challenging to observe and model. In this study, we apply a self-supervised learning (SSL) framework to Meteosat infrared 10.8 μm imagery over the Alpine region to derive physically meaningful representations of convective cloud organization across the full daily cycle. The learned representation organizes convective cloud scenes into three primary regimes: early convection (EC), deep convection (DC), and overcast anvil systems (OA), each exhibiting distinct cloud-top properties, spatial structures, and day–night distributions consistent with established convective development stages. Within the developed SSL framework, reported extreme precipitation and hail events are preferentially associated with these regimes, occupying the upper tail of cloud-top height, optical thickness, and cloud coverage distributions within the latent space. This indicates that extremes correspond to rare, intense realizations of continuous convective variability. Two dominant pathways of cloud structure evolution are identified: a rapid EC→DC transition and a persistent DC mode. The former is characterized by fast cloud growth and intensification, while the latter corresponds to mature convective systems with sustained cloud properties. Overall, the results demonstrate that infrared-based SSL representations capture physically consistent convective stages and their transitions, providing a novel observational framework for characterizing extreme convective events and supporting the evaluation of convection-resolving numerical weather prediction models.