Search Results (297)

Background: The enhanced sensitivity of next-generation sequencing (NGS) for assessing hepatitis B virus (HBV) quasispecies heterogeneity over clone-based sequencing (CBS) is well documented. However, its comparative reliability for genotype determination remains an open question. Objective: This study aimed to directly compare the performance of NGS and CBS for genotyping HBV using the entire viral genome. Methods: We selected five challenging clinical samples that previously could not be subgenotyped or showed conflicting results when using direct sequencing of the S open reading frame (ORF). The full HBV genome from these subjects was amplified and then analyzed in parallel by both NGS and CBS. Phylogenetic analysis was subsequently used to assign genotypes. Results: Both methods identified a range of genotypes, including B, C, and I, as well as aberrant and recombinant forms. For three of the five subjects, genotyping results were identical between the two platforms. In the remaining two cases, however, CBS revealed greater complexity, identifying additional subgenotypes and recombinant/aberrant strains not detected by NGS. Notably, for three individuals, the genotypes determined by both modern methods contradicted earlier results from 2011 based on direct S ORF sequencing. Furthermore, the specific mutations detected were incongruent between the platforms, with CBS identifying a higher number of variants than NGS. Conclusions: Our findings indicate that genotyping results from NGS and CBS can be discordant. Contrary to expectations, CBS may uncover more genetic diversity, including a greater number of subgenotypes and mutations, than NGS in certain contexts. The study also confirms that genotyping based solely on direct sequencing of the S ORF can be unreliable and lead to misclassification. Full article

Understanding the processes that shape parasite community structure across spatial scales is essential for linking ecological theory with host–parasite dynamics. Using a metacommunity framework, we examined the metacommunity of helminth parasites infecting the freshwater fish Pseudoxiphophorus bimaculatus across 11 sites along the La Antigua River basin (Veracruz, Mexico). We combined β-diversity partitioning, local and species contributions to diversity, elements of metacommunity structure (EMS), and variance partitioning to identify the mechanisms underlying spatial variation in parasite composition. Helminth metacommunity was dominated by a few widespread taxa, with balanced variation in species abundances—indicative of turnover—emerging as the main driver of β-diversity at both host and site levels. Both rare and common species contributed disproportionately to regional diversity. EMS analyses revealed coherent, non-random community structures that varied from nested to quasi-Gleasonian and quasi-Clementsian types among sites and guilds, suggesting that species respond individually to shared environmental gradients. Variance partitioning indicated that environmental filtering, particularly through habitat structure, explained most of the variation in community composition, exceeding the effects of water quality and host size. Overall, our results demonstrate that turnover, species uniqueness, and environmental filtering interact to shape helminth parasite metacommunities in tropical freshwater systems, highlighting the integrative role of environmental heterogeneity and dispersal limitation in parasite community assembly. Full article

High-space industrial facilities often store substantial quantities of flammable volatile organic compounds (VOCs), posing significant fire and explosion hazards. This study employed computational fluid dynamics (CFD) to investigate the migration and diffusion characteristics of VOCs in a semi-enclosed, high-space wood chip fuel storage shed. A three-dimensional transient numerical model was developed based on a real-scale industrial prototype, incorporating the Realizable $k-\epsilon$ turbulence model with species transport equations. Validation using experimental data demonstrated good agreement between the model and experimental results, with a maximum relative error of 5.0%. A systematic assessment of key parameters was conducted, including time, ambient temperature, relative humidity, wood chip stack height, and VOCs type. Evaluation metrics comprised the surface-average mass fraction and the proportion of areas exceeding 5% of the lower explosive limit (LEL). The results show that peak concentrations occurred at 25~27 min. The system reaches quasi-steady state after 60 min. At 300~304 K, the lowest peak mass fractions are observed (0.31% and 0.43% at 19 m), yet the area exceeding 5% LEL was the largest. Moderate humidity (40~60%) reduces peaks by 0.06~0.11%. A stacking height of 7.5 m reduces peak values to 0.21% (left) and 0.28% (right), while a 10 m height increases the hazardous area to 48.87%. Low-polarity VOCs (C₁₀H₁₆) spread widely (34.10% exceeding 5% LEL area), whereas polar VOCs (C₁₅H₂₆O) accumulated locally (4.48%). These findings provide theoretical guidance for VOC hazard control and ventilation optimization in high-space biomass fuel storage facilities. Full article

Antimicrobial resistance (AMR) poses a critical public health threat, with rising multidrug resistance cases compromising treatment effectiveness. Knowledge about the resistome in dairy production systems remains limited, particularly regarding lactating cows. This study investigated the microbiome and resistome across the hospital, fresh, and mid-lactation pens on 18 conventional dairy farms in California and Ohio using shotgun metagenomic sequencing of pooled fecal samples. Pooled fecal pat samples were collected as part of a larger field study using a quasi-experimental design that assigned farms to the training intervention group (six per state) or the control group (three per state). For the training intervention group, farm worker(s), identified as having the task of diagnosing and treating adult cows on the farm, participated in a training program on antimicrobial stewardship practices. Pooled fecal samples (n = 7) were collected at enrollment and 3 months after the intervention was completed on each participating farm (n = 18). A total of 10,221 bacterial species and 345 AMR genes conferring resistance to 22 antimicrobial classes were identified. The hospital pen exhibited a higher AMR gene diversity compared to fresh and mid-lactation pens (p < 0.05). Several AMR genes showed bimodal distribution, suggesting complex transmission mechanisms. Network analysis revealed distinct gene correlation profiles across pens, with the hospital pen showing fewer gene interactions. Our findings suggest that farm-level antimicrobial drug use may not be the sole or primary driver of resistome composition in pooled fecal samples from dairy cattle, highlighting the need to investigate other factors influencing AMR dynamics in livestock systems. Full article

The development of bioactive dental materials with antimicrobial and biocompatible properties is important for improving clinical outcomes and reducing complications associated with intraoral devices. This study presents a novel approach that combines a 3D-printed shape-memory resin (TC-85DAC) with green-synthesized zinc oxide nanoparticles (ZnO NPs) to enhance biological performance. ZnO NPs were synthesized using Dysphania ambrosioides extract, producing quasi-spherical particles with a crystalline hexagonal structure and sizes between 15 and 40 nm. Resin discs were coated with ZnO NPs at 10%, 20%, and 30%, then assessed for biocompatibility with human gingival fibroblasts and antibacterial activity against Porphyromonas gingivalis and Streptococcus mutans. Surface roughness was also considered with and without ZnO NPs. Biocompatibility assays revealed a concentration- and time-dependent increase in cell viability, with the highest values at 30% ZnO NPs after 72 h of exposure to the NPs. Antibacterial testing confirmed the inhibition of both species, with Porphyromonas gingivalis showing greater sensitivity. Surface roughness increased with higher ZnO NPs concentrations, significantly influencing biological interactions. The integration of green-synthesized ZnO NPs with shape-memory resin produced a multifunctional dental material with improved bioactivity. This sustainable strategy enables bioactive coatings on 3D-printed resins, with potential applications in the next generation of smart dental devices. Full article

Copper and iron species were co-deposited onto a hydroxyapatite surface to produce bimetallic catalysts. Characterization techniques (XRD, XPS, DR-UV spectroscopy and TEM-EDX) helped in unveiling the speciation, nuclearity, and electronic properties of copper and iron in samples with variable total metal loading (1–10 wt.%) and relative Cu-to-Fe ratios. The speciation of Cu was revealed to be not affected by Fe and vice versa. Conversely, the metal loading turned out to be a key factor ruling the aggregation state of Cu and Fe species. The samples were tested as catalysts in the Selective Catalytic Reduction of NO by NH₃ (NH₃-SCR) in dry and wet environments under quasi-real conditions (50,000 ppm O₂; 50,000 ppm H₂O, if present; 120,000 h⁻¹ GHSV) in the 200−500 °C interval. Although the combination of Cu and Fe affords a modest improvement in water resistance compared to their monometallic counterparts, no substantial enhancement in activity was observed for the bimetallic hydroxyapatite-based SCR catalysts. Full article

We numerically study a quasi-one-dimensional classical Poisson–Nernst–Planck system with two oppositely charged ion species under different setups. Of particular interest is the following: (i) to numerically identify ten critical potentials, which play critical roles in characterizing the qualitative properties of individual fluxes; (ii) to numerically verify some interesting scaling laws related to boundary concentrations of the system; and (iii) to investigate the effects on the individual fluxes from finite ion sizes. Some numerical results support the analytical ones obtained in previous work and provide more intuitive illustrations of the abstract results, while some others provide important insights for future studies; particularly, the scaling law observed with both small permanent charges and finite ion sizes is quite different from previous results. Full article

Modeling ion transport through membrane channels is crucial for understanding cellular processes, and Poisson–Nernst–Planck (PNP) equations provide a fundamental continuum framework for such ionic fluxes. We investigate a quasi-one-dimensional steady-state PNP system for two oppositely charged ion species, focusing on how large permanent charges within the channel and realistic boundary conditions impact ion transport. In contrast to classical models that impose ideal electroneutrality at the channel ends (a simplification that eliminates boundary layers near the membrane interfaces), we adopt relaxed neutral boundary conditions that allow small charge imbalances at the boundaries. Using asymptotic analysis treating the large permanent charge as a singular perturbation, we derive explicit first-order expansions for each ionic flux, incorporating boundary layer parameters $(\sigma ,\rho )$ to quantify slight deviations from electroneutrality. This analysis enables a qualitative characterization of individual cation and anion flux behaviors. Notably, we identify two critical transmembrane potentials, $V_{1c}$ and $V_{2c}$, at which the cation and anion fluxes, respectively, vanish, signifying flux-reversal thresholds that delineate distinct monotonic regimes in the flux-voltage response; these critical values depend on the permanent charge magnitude and the boundary layer parameters. We further show that both ionic fluxes exhibit saturation: as the applied voltage becomes extreme, each flux approaches a finite limiting value, with the saturation level modulated by the degree of boundary charge imbalance. Moreover, allowing even small boundary charge deviations reveals non-intuitive discrepancies in flux behavior relative to the ideal electroneutral case. For example, in certain parameter regimes, a large permanent charge that enhances an ionic current under strict electroneutral conditions will instead suppress that current under relaxed-neutral conditions (and vice versa). This new analytical framework exposes subtle yet essential nonlinear dynamics that classical electroneutral assumptions would otherwise obscure. It provides deeper insight into the interplay between large fixed charges and boundary-layer effects, emphasizing the importance of incorporating such realistic boundary conditions to ensure accurate modeling of ion transport through membrane channels. Numerical simulations are performed to provide more intuitive illustrations of our analytical results. Full article

RNA virus populations exist as quasispecies-complex, dynamic clouds of closely related but genetically diverse variants generated by high mutation rates during replication. Assessing quasispecies structure and diversity is crucial for understanding viral evolution, adaptation, and response to antiviral treatments. However, comparing single quasispecies observations from individual biosamples, especially at different infection or treatment time points, presents statistical challenges. Traditional inferential tests are inapplicable due to the lack of replicate observations, and resampling-based approaches such as the bootstrap and jackknife are limited by biases and non-independence, particularly for diversity indices sensitive to rare haplotypes. In this study, we address these limitations by applying the delta method to derive analytical variances for a set of quasispecies structure indicators specifically designed to assess the quasispecies maturation state. We demonstrate the utility of this approach using high-depth next-generation sequencing data from hepatitis C virus (HCV) quasispecies evolving in vitro under various conditions, including free evolution and exposure to antiviral or mutagenic treatments. Our results reveal that with highly fit HCV quasispecies, sofosbuvir inhibits quasispecies genetic diversity, while mutagenic treatments accelerate maturation, compared to untreated controls. We emphasize the interpretation of results through absolute differences, log-fold changes, and standardized effect sizes, moving beyond mere statistical significance. This framework enables robust, quantitative comparisons of quasispecies diversity from single observations, providing valuable insights into viral adaptation and treatment response. The R code and session info with required libraries and versions is provided in the supplementary material. Full article

Applying physico-analytical methods to whole hair fibers enables investigation of hair dye performance. Light microscopy, SEM imaging and EDX mapping of intact hair fibers, as well as TEM imaging of microtome cuts, provided insights into the distribution, size, shape and growth patterns of the dyeing species and particles, thus demonstrating the correlation between silver nanoparticles (AgNPs) and dye impression. Yak hair fibers were treated with a polyphenol-containing Reseda luteola L. extract (RE), which had been acidified using either hydrochloric acid (HCl) or citric acid (CA), and subsequently exposed to silver nitrate (AgNO₃), resulting in the formation of quasi-spherical silver nanoparticles (AgNPs) that were depicted several microns deep inside the hair fiber, regardless of the additive used. The particles appeared to aggregate preferentially in sulfur-rich domains within the hair fiber, probably due to the affinity of silver ions on the NP’s surface towards sulfur. The additives significantly affected the size and aggregation behavior of the particles. Using HCl, larger, aggregated particles were formed, whereas the application of CA yielded smaller, more uniform particles and a higher penetration depth. Despite different particle sizes, the dye outcome was comparable. In strands treated with HCl, washing brought the particles deeper into the hair cortex and resulted in further aggregation. Thus, HCl promoted the formation of larger particles whereas CA yielded more uniformly sized particles. These findings open a new route for metal nanoparticle-based hair dyes with excellent wash fastness. Full article

Halide perovskite-based memristors are promising neuromorphic devices due to their unique ion migration and interface tunability, yet their conduction mechanisms remain unclear, causing stability and performance issues. Here, we engineer interstitial Ag⁺ ions within a quasi-two-dimensional (quasi-2D) halide perovskite ((C₆H₅C₂H₄NH₃)₂Cs_n−1Pb_nI_3n+1) to enhance device stability and controllability. The introduced Ag⁺ ions occupy organic interlayers, forming thermodynamically stable structures and introducing deep-level energy states without structural distortion, which do not act as non-radiative recombination centers, but instead serve as efficient charge trapping centers that stabilize intermediate resistance states and facilitate controlled filament evolution during resistive switching. This modification also leads to enhanced electron transparency near the Fermi level, contributing to improved charge transport dynamics and device performance. Under external electric fields, these Ag⁺ ions act as mobile ionic species, facilitating controlled filament formation and stable resistive switching. The resulting devices demonstrate exceptional performance, featuring an ultrahigh on/off ratio (∼10⁸) and low operating voltages (∼0.31 V), surpassing existing benchmarks. Our findings highlight the dual role of Ag⁺ ions in structural stabilization and conduction modulation, providing a robust approach for high-performance perovskite memristor engineering. Full article

In the field of advanced electrical energy conversion and storage, remarkable attention has been given to the development of new, more sustainable electrolytes. In this regard, the combination of redox shuttles with aqueous bio-polymer gels seems to be a valid alternative via which to overcome the typical drawbacks of common liquid electrolytes such as corrosion, volatility or leakage. Despite the promising results obtained so far, redox-active species such as bis(6,6′-dimethyl-2,2′-bipyridine)copper(I) trifluoromethanesulfonylimide, ([Cu(I)(dmby)₂]TFSI), still present inherent challenges associated with their poor water solubility and oxidative lability, which prevents their employment in cheap and sustainable aqueous electrolytes. The present study investigates the stabilization of the Cu(I) complex ([Cu(I)(dmby)₂]TFSI) within two natural hydrogels based on the biopolymers κ-carrageenan and galactomannan, using ZnO nanoparticles as gelling agents. These eco-friendly and biocompatible systems are proposed as potential matrices for quasi-solid electrolytes (QSEs), offering a promising platform for advanced electrolyte design in electrochemical applications. Both hydrogels effectively stabilized and retained the redox species within their networks. In order to shed light on distinct stabilization mechanisms, complementary FTIR and SEM analyses were relevant to reveal the structural rearrangements, specific to each matrix, upon complex incorporation. Furthermore, thermogravimetric analysis confirmed notable thermal resilience in both systems, with the galactomannan-based gel demonstrating enhanced performance. Altogether, this work introduces a novel strategy for embedding copper-based redox couples into gelled electrolytes, paving the way toward their integration in real electrochemical devices, where long-term stability, redox retention, and energy conversion efficiency are critical evaluation criteria. Full article

The Ichubamba Yasepan wetlands, in the Andean páramos of Ecuador, suffer heavy metal contamination due to anthropogenic activities and volcanic ash from Sangay, impacting biodiversity and ecosystem services. This quasi-experimental study evaluated the bioaccumulation and tolerance of metals in high Andean species through stratified random sampling and linear transects in two altitudinal ranges. Concentrations of Cr, Pb, Hg, As, and Fe in water and the tissues of eight dominant plant species were analyzed using atomic absorption spectrophotometry, calculating bioaccumulation indices (BAIs) and applying principal component analysis (PCA), clustering, and linear discriminant analysis (LDA). Twenty-five species from 14 families were identified, predominantly Poaceae and Cyperaceae, with Calamagrostis intermedia as the most relevant (IVI = 12.74). The water exceeded regulatory limits for As, Cr, Fe, and Pb, indicating severe contamination. Carex bonplandii showed a high BAI for Cr (47.8), Taraxacum officinale and Plantago australis for Pb, and Lachemilla orbiculata for Hg, while Fe was widely accumulated. The LDA highlighted differences based on As and Pb, suggesting physiological adaptations. Pollution threatens biodiversity and human health, but C. bonplandii and L. orbiculata have phytoremediation potential. Full article

This study investigated the mechanisms determining macrophyte species composition in 23 Andalusian Mediterranean mountain wetlands (southern Spain). We employed a methodology combining two approaches: a pattern-based approach utilizing Elements of Metacommunity Structure (EMS) and a mechanistic approach involving Redundancy Analysis (RDA) and variance partitioning. This allowed us to identify the relevance of interactions between environmental and spatial factors. Data collection in these wetlands included macrophyte samples and physicochemical variables, alongside spatial variables generated using Moran’s Eigenvector Maps (MEMs). To refine the analysis of metacommunity structuring, the species matrix was partitioned based on macrophyte dispersal strategy (charophytes by spores and macrophyte vascular plants by seeds). Our results reveal that the macrophyte metacommunity in these wetlands exhibits quasi-clumped species loss for the total community, while charophytes and vascular plants showed quasi-random species loss. In conclusion, this study demonstrates that macrophyte communities in Mediterranean mountain wetlands do not follow a simple species replacement pattern. Instead, they are organized in a quasi-nested pattern, strongly shaped by environmental filters and, to a lesser extent, by spatial connectivity, with a prominent role for random processes. Understanding these mechanisms is crucial for predicting species responses to environmental changes and for designing effective conservation strategies within these vulnerable ecosystems. Full article

In this study, we used a causal analysis approach to assess the impact of deforestation on bird abundance in Mexico. Based on records in the eBird and GBIF databases, ten species were selected in 807 grids on the mainland. Relative abundances by species were estimated using a fixed-effects panel data regression for the period 2016–2018. Deforestation was used as a quasi-natural experiment, classifying treatment and control groups according to the distribution of relative abundances by quintiles of gross deforestation rates during the period 2001–2018. The treatment group was defined as relative abundances of birds present in grids in the last deforestation quintile (≥4% to 12%); the control group included relative abundances of birds present in grids of the first four quintiles (<4%). Extended regression models were used to estimate the impacts of high deforestation rates on the relative abundance of birds, finding mixed causal effects: five showed statistically significant declines in abundance (Ruddy Ground Dove (Columbina talpacoti), Black Vulture (Coragyps atratus), Melodious Blackbird (Dives dives), Bewick’s Wren (Thryomanes bewickii), and Rufous-backed Thrush (Turdus rufopalliatus)), while one specie Yellow-winged Cacique (Cassiculus melanicterus) exhibited significant increases. These findings highlight the importance of causal effect studies in contributing to empirical evidence-based conservation decision-making. Full article