Search Results (146)

The application of essential oils and plant extracts as natural food preservatives has gained increasing interest; however, their potential impacts on gut health and host physiology remain unknown. This study evaluated the effects of synergistic combinations of peppermint essential oil (EO) + thyme EO and peppermint EO + feijoa peel extract on gut microbiota composition and colonic morphology in a rat model. Sprague–Dawley rats were orally given the synergistic combinations daily for 28 days, and their effects were assessed using 16S rRNA gene sequencing of the caecum microbiota and histological analysis of proximal colon tissues. Alpha diversity metrics showed no significant differences (p > 0.05) between treatment and control groups, and beta diversity indicated no treatment-related shift in the bacterial communities. Taxonomic profiling at the phylum, family, and genus levels showed comparable relative abundances of dominant microbial taxa across all treatments, with no evidence of dysbiosis. Histological examination of proximal colon tissues revealed no significant changes in crypt depth between treated and control groups, confirming the absence of adverse morphological effects on the intestinal epithelium. The results of this study indicate that synergistic combinations of peppermint EO, thyme EO, and feijoa peel extract do not adversely affect the gut microbiota composition and colonic morphology in rats, thereby supporting their application as preservatives in foods. Full article

Background: Functional diversity of aquatic macrophytes can provide mechanistic insight into community assembly beyond taxonomic diversity metrics. Aims: We tested whether functional diversity indices can help infer the dominant processes shaping macrophyte communities along hydromorphological and physicochemical gradients, and whether these signals remain interpretable after accounting for species richness. Methods: We surveyed aquatic macrophytes in the Dnipro–Orilsky Nature Reserve (Ukraine) during four field campaigns in 2024 (453 sampling sites), measured key environmental characteristics, and calculated functional diversity indices from plant trait data. Results: The indices showed distinct responses consistent with environmental filtering, dispersal limitation related to reduced hydrological connectivity, and biotic interactions. Anthropogenic degradation was associated with functional simplification and shifts toward opportunistic trait syndromes. Conclusions: A complementary set of functional diversity indices can distinguish major community assembly mechanisms in macrophyte assemblages and supports more robust assessment of ecosystem condition under combined natural and anthropogenic pressures. Full article

Background: Gut microbiota dysbiosis has been associated with childhood asthma; however, its role in adult bronchial asthma (BA), particularly in Japanese populations, remains unclear. The potential influence of sex-based differences also warrants investigation. We aimed to investigate the association between gut microbiota composition and adult BA in a Japanese cohort, focusing on sex-specific differences. Methods: Stool samples from 108 Japanese adults with BA (48 male and 60 female individuals) and 210 healthy controls (90 male and 120 female individuals) were analyzed using 16S rRNA gene sequencing. Analyses were stratified by sex. β-diversity was assessed using non-metric multidimensional scaling and permutational multivariate analysis of variance. Genus-level taxonomic comparisons were conducted using the ANOVA-Like Differential Expression version 2 tool on centered log-ratio-transformed data. Results: β-diversity significantly differed between the groups among both male and female individuals. In male individuals, 11 taxa had absolute effect sizes of ≥0.2. In female individuals, 19 taxa met this threshold, with 8 reaching significance after Benjamini–Hochberg correction. Streptococcus and Blautia were enriched in the BA group in both sexes, whereas other taxa showed sex-specific patterns, such as Veillonella in male and Flavonifractor and Eggerthella in female individuals. Several short-chain fatty acid (SCFA)-producing taxa were depleted in the BA group. Conclusions: Our findings suggest that gut microbiota dysbiosis occurs in Japanese adults with BA, characterized by enrichment of taxa associated with respiratory diseases and depletion of SCFA-producing bacteria. The observed patterns highlight the importance of considering sex-specific differences in future research. Full article

Microalgae are an evolutionarily ancient and morphologically diverse group of photosynthetic eukaryotes, with taxonomic resolution complicated by environmentally driven phenotypic plasticity. This study merges deep learning and explainable artificial intelligence (XAI) to establish a transparent, reliable, and biologically meaningful framework for green microalgae (Chlorophyta) classification. Microscope images from three morphologically distinct algal species—Desmodesmus flavescens, Desmodesmus subspicatus, and Tetradesmus dimorphus representing the genera Desmodesmus and Tetradesmus within Chlorophyta—were analyzed using twelve convolutional neural networks, including EfficientNet-B0–B7, DenseNet201, NASNetLarge, Xception, and ResNet152V2. A curated dataset comprising 3624 microscopic images from three Chlorophyta species was used, split into training, validation, and test subsets. All models were trained using standardized preprocessing and data augmentation procedures, including grayscale conversion, CLAHE-based contrast enhancement, rotation, flipping, and brightness normalization. The model’s performance was assessed using accuracy and loss metrics on independent test datasets, while interpretability was evaluated through saliency maps and Gradient-weighted Class Activation Mapping (Grad-CAM) visualizations. ResNet152V2 achieved the highest overall performance among all evaluated architectures, outperforming EfficientNet variants, NASNetLarge, and Xception in terms of macro F1-score. Visualization analysis showed that both Grad-CAM and saliency mapping consistently highlighted biologically relevant regions—including cell walls, surface ornamentation, and colony structures—confirming that the models relied on taxonomically meaningful features rather than background artifacts. The findings indicate that the integration of deep learning and XAI can attain consistently high test accuracy for microalgal species, even with constrained datasets. This approach enables automated taxonomy and supports biodiversity monitoring, ecological assessment, biomass optimization, and biodiesel production by integrating interpretability with high predictive accuracy. Full article

Gastrointestinal microbiota (GIM) play a crucial role in host physiology and are modulated by host biology, environmental conditions, and temporal dynamics. The GIM of two types of fishes, the redbreast sunfish (Lepomis auritus) and the bullhead catfish (Ameiurus spp.), from three streams over two seasons were sampled for host health (hepatosomatic index, Fulton’s condition factor), age, and additional environmental metadata. A total of 56 of these were fully analyzed using 16S rRNA amplicon sequencing and QIIME2. Specific taxonomic lineages were identified as significant with respect to observed differences between variables, including season, stream, and host taxonomic affiliation. The relative abundance of bacterial phyla varied significantly based on host type and between the three sites. However, the most significant effects for both relative abundance and alpha diversity metrics were seen when combining variables of site and season or host and season. Principal Component Analysis using weighted and unweighted Unifrac indicated the primacy of season in beta diversity analyses. Analysis of Compositions of Microbiomes (ANCOM) to identify taxa responsible for these differences revealed distinct amplicon sequence variants enriched by season, stream, host taxonomy, and host age. The larger picture emerging from these data suggests that there is a complex interplay between the host, season, and environment that shapes the structure of fish microbiota and associated host health. Full article

High-quality bacterial genomes are essential for robust comparative genomics, reliable taxonomic assignment, and accurate pathogen and antimicrobial resistance (AMR) surveillance. Yet, public repositories still contain highly heterogeneous assemblies, and genome quality is often judged using single metrics in isolation. Here we develop an integrative Genome Quality Index (GQI) that combines four complementary metrics—including BUSCO single-copy completeness, contig number, N50, and unmapped read percentage—into a composite, interpretable score. We re-assembled and evaluated 474 pathogenic bacterial genomes submitted from South Korea using a standardized Illumina-based pipeline and validated the framework on an independent Enterobacteriaceae dataset (n = 5781). Species-level analyses and unsupervised clustering revealed pronounced variation in genome quality (one-way ANOVA, p < 1.05 × 10⁻³³), with Cronobacter sakazakii and Listeria monocytogenes showing consistently high GQI scores, whereas Mycobacterium tuberculosis exhibited broad variability, including clear low-quality outliers. After log-transforming skewed variables, contig count and N50 remained strongly negatively correlated (r = −0.83), while BUSCO completeness showed moderate positive association with N50 and negative association with unmapped reads. GQI scores spanned 0.23–0.96, with most genomes clustering between 0.70 and 0.85. A Random Forest classifier trained on the four raw metrics predicted GQI-based quality tiers (low, medium, high) with 97% accuracy. From the top-decile genomes, we derived empirical thresholds like BUSCO ≥ 98.6%, contigs ≤ 30, N50 ≥ 1 Mb, and unmapped reads ≤ 0.82% that refine existing recommendations and provide actionable curation criteria. Our framework complements tools such as CheckM, gVolante, and Hybracter by offering a platform-agnostic composite scoring system that can be integrated into submission workflows and surveillance pipelines to systematically flag low-quality genomes and improve the reliability of microbial genomics. Full article

Background: Breast implant-associated anaplastic large cell lymphoma (BIA-ALCL) is a mature T-cell lymphoma linked to textured breast implants. A leading hypothesis suggests that chronic inflammation, combined with immunological and genetic factors, drives its pathogenesis. Two previous studies investigating bacterial biofilms on breast implant capsules have produced conflicting results, particularly regarding the enrichment of Ralstonia spp. Methods: We analyzed the microbiota profiles in seroma samples from 10 BIA-ALCL patients and 12 patients with non-neoplastic effusion, subclassified into acute-, mixed-, and chronic-type based on cellular composition. We used two metagenomic approaches: 16S rRNA gene sequencing and Nanopore sequencing with the “What’s in My Pot?” (WIMP) taxonomic classifier. Our analyses included alpha and beta diversity metrics, as well as comparisons of Gram status and oxygen requirements. Results: Both sequencing methods identified Staphylococcaceae, Propionibacteriaceae, and Bradyrhizobiaceae as the most prevalent bacterial families in both BIA-ALCL and benign seroma samples. Notably, the Burkholderiaceae family was more abundant in some of the benign seromas according to the 16S rRNA sequencing, but Ralstonia spp. were not detected. BIA-ALCL showed higher richness (based on Nanopore data) and higher evenness (based on 16S rRNA data) compared to acute-type seromas, indicating a more homogenous representation of the different taxa identified. BIA-ALCL seromas did not cluster together based on Nanopore data, but they did form a distinct cluster with 16S rRNA data. This cluster was differentiated from the other two clusters by a relatively balanced presence of multiple families without overt dominance. We observed no significant differences in Gram staining between BIA-ALCL and benign samples using either method. However, non-aerobic bacterial families were enriched in BIA-ALCL cases only when analyzed with the Nanopore pipeline. Conclusions: Overall, our findings did not identify a distinctive microbial signature specifically associated with BIA-ALCL. Full article

Ecological restoration in degraded landscapes requires understanding the factors driving ecosystem function. We ask the central question: Do microtopography and plant functional traits control water-carbon coupling efficiency (WCCI) in mining-affected grasslands? We developed a novel, decoupled WCCI metric balancing water-use efficiency (1/SLA) and carbon-stock potential (Height + Foliage Cover). We hypothesized that (1) microhabitats with severe environmental filters (e.g., drought, erosion) would exhibit the lowest WCCI, and (2) this function could be optimized by assembling species that balance these two distinct trait strategies. Our objectives were to: (i) quantify the new WCCI across five microhabitat zones (A–E); (ii) assess how soil filters shape existing community functions; and (iii) identify optimized, zone-specific species assemblages using a dual-filter CATS model that maximizes WCCI. Results show significant variability in WCCI. The most degraded zones, A (arid) and B (high erosion), exhibited the lowest functional performance (mean WCCI = 0.029 and 0.078), supporting our first hypothesis. The dual-filter CATS model, constrained by abiotic targets (Tolerance = 10%) and a diversity cap (Max Abundance = 30%), successfully generated distinct, functionally tailored species assemblages for each zone. For instance, the optimized community for arid Zone A included the drought-adapted grass Stipa capillata (15.9%), while the resource-rich Zone D was recommended Medicago lupulina (12.7%). Conclusion: These findings confirm that a “one-size-fits-all” approach is insufficient. We demonstrate the necessity of a trait-based, microhabitat-specific framework to move beyond taxonomic mimicry and truly optimize biogeochemical functions in restoration. Full article

Fungal endophytes can be identified in a wide range of plant species which help to protect from both abiotic and biotic stressors. This research focused on using high-throughput sequencing (HTS) analysis to gain insight into the foliar endophytic fungal diversity between Morinda tinctoria and Pithecellobium dulce. The study obtained a total of 118,547 sequencing reads, which were grouped into 266 Operational Taxonomic Units (OTUs) with a 97% similarity threshold. M. tinctoria had more OTUs than P. dulce. Alpha diversity results show that both plant species support varied microbial communities with similar but distinct biodiversity profiles. The Shannon index revealed that M. tinctoria had considerably more fungal diversity than P. dulce. The correlation matrix and PCoA depicts the pairwise correlations between several soil metrics such as the total nitrogen level, entire phosphorus, overall potassium, and the electrical conductivity, total carbon from organic matter, pH levels, manganese, iron, zinc, copper, and boron. The OTUs were classified into 5 phyla, 18 classes, 40 orders, 70 families, and 36 genera, where the phylum Ascomycota has a relative abundance of (50–55%), followed by Basidiomycota at (55–60%). The most abundant genera were Wallemia (30–35%), Saitozyma (30–40%), and Talaromyces (20–25%), with average relative abundances. Unassigned genera show a significant proportion of fungal taxa that are still taxonomically unclear. A comparative analysis has been performed between the two plants, M. tinctoria has a higher fungal diversity, which is frequently associated with increased ecological stability, disease resistance, and better functional relationships with the host plant. Full article

Milk microbiota is a complex microbial ecosystem with implications for product quality, safety, and animal health. However, limited data exist on goat milk microbiota, particularly in local breeds. This study provides the first detailed characterization of the milk microbiota of Girgentana goats, a resilient Sicilian breed valued for high-quality dairy products. Illumina NovaSeq sequencing was used to analyze the 16S rRNA V3–V4 regions of 44 individual and 3 bulk milk samples. Briefly, 16S rRNA-gene sequencing produced a total of 8,135,944 high-quality reads, identifying 1134 operational taxonomic units (OTUs) across all individual samples. On average, each sample showed 864 OTUs with counts > 0. Alpha diversity metrics, based on richness estimators (Chao1: 948.1; ACE: 936.3) and diversity indices (Shannon: 4.06; Simpson: 0.95; Fisher: 118.5), indicated a heterogeneous community with both common and low-abundance taxa. Firmicutes (51%) and Proteobacteria (27%) were the predominant phyla, with Lactobacillaceae (54%) and Bifidobacteriaceae (22%) dominating at the family level. Notably, farm bulk milk profiles closely mirrored individual samples. These results establish a milk microbiota baseline for the Girgentana breed and offer valuable insights into microbial ecology in traditional dairy systems, supporting future comparisons across breeds and farming practices. Full article

Infections caused by nontuberculous mycobacteria are becoming significant due to the increasing number of vulnerable individuals worldwide. Understanding the evolutionary relationships within the genus Mycobacterium is critical for improving species identification and, consequently, enhancing diagnosis, treatment, and epidemiological tracking. Pairwise comparisons of average nucleotide identity, genome–genome distance calculations, Mash values, multilocus sequence analyses, and average amino acid identities (AAIs) revealed that the AAI metric is the best to distinguish Mycobacterium from other genera of Mycobacteriales. Furthermore, genes encoding 16S and 23S rRNAs could also be used for the genus delineation: the previously established threshold of 94.5–95.0% of the rrs was confirmed, and the value for the rrl gene was estimated at 88.5–89.0%. The genus-delineating thresholds do not confirm the proposed splitting of the Mycobacterium into five genera, and the overall performance of conserved signatures used for splitting was not satisfactory. We estimated that Mycobacterium contains at least 402 distinct species, 246 of which were identified in clinical human specimens. The obtained tree and the corresponding list of species with proposed corrections to the names made from whole-genome sequences provide a reliable framework for the identification and taxonomic positioning of novel species within the genus. Full article

Benthic macroinvertebrates are widely used for river ecosystem health monitoring, yet challenges remain in non-wadable rivers, particularly regarding sampling effort. We evaluated hand-net sampling efficiency at three sites along the Danjiang River (a Yangtze River tributary) by analyzing taxa richness across taxonomic levels under varying replicate numbers. In total, 61 taxa (41 families) of benthic macroinvertebrates were identified. Non-metric multidimensional scaling analysis indicated no significant spatiotemporal variation in community composition. However, sampling effort increased, and the benthic macroinvertebrate taxa richness at both genus/species and family levels also increased. At eight sample replicates, the taxa accumulation curve at the genus/species level did not show an asymptote, with the observed richness reaching 67–80% of the predicted values calculated by Jackknife 1. In contrast, the family-level curve exhibited a clear asymptotic trend, with the observed richness reaching 82–100% of the predicted values. As sampling effort increased, bias decreased and accuracy improved, particularly for family-level taxa. Additionally, the BMWP scores also increased with the sampling effort. When the replicate number was no less than six, the BMWP reached stable assessment grades for all cases. From the perspective of bioassessment in non-wadable rivers, the hand net is suitable for collecting benthic macroinvertebrates. However, there is a risk of underestimating taxa richness due to insufficient sampling effort. Using family-level taxa can partially mitigate the impacts caused by insufficient sampling efforts to a certain extent, but further validation is needed for other non-wadable rivers (e.g., those with soft substrates). In conclusion, our research results indicate that six replicate hand-net samplings in non-wadable hard-bottom rivers can be regarded as a cost-effective and reliable sampling method for benthic macroinvertebrate BMWP assessment. This strategy provides a relatively practical reference for the monitoring of benthic macroinvertebrate in the same type of rivers in China. Full article

Heart failure (HF) represents a growing public health concern, driven by rising prevalence and the challenge of frequent, costly (re-)hospitalizations from decompensation. To address these, HF management has progressed towards incorporating devices for remote patient monitoring (RPM), with most being focused on identifying decompensation and providing timely, tailored pharmacological interventions. To date, the pool of devices has enlarged substantially, forming a spectrum of invasive and non-invasive options whose clinical adoption potential is yet to be determined. This review summarizes existing devices for RPM in HF care, with a major focus on technical characteristics and potential clinical efficacy. To unify the two traditionally separated groups, we re-classify the sampled devices in a single taxonomical dimension, the physical location of the sensing element(s), and objectively assess their current development state using the Medical Device Readiness Level, a metric that merges technical and clinical perspectives. Furthermore, we outline additional evaluative metrics within two complementary dimensions, focused on process efficiency and patient outcomes, ultimately offering a structured framework to evaluate clinical adoption. Full article

Limited access to electricity and high levels of CO₂ emissions—over 35 billion metric tons in recent years—highlight the urgent need for sustainable energy solutions, particularly in rural areas dependent on polluting fuels. To address this challenge, three single-chamber microbial fuel cells (MFCs) with carbon anodes and zinc cathodes were designed and operated for 35 days in a closed circuit. Voltage, current, pH, conductivity, ORP, and COD were monitored. FTIR-ATR spectroscopy (range 4000–400 cm⁻¹) was applied to identify structural changes, and polarization curves were constructed to estimate internal resistance. The main FTIR peaks were observed at 1027, 1636, 3237, and 3374 cm⁻¹, indicating the degradation of polysaccharides and hydroxyl groups. The maximum voltage reached was 0.961 ± 0.025 V, and the peak current was 3.052 ± 0.084 mA on day 16, coinciding with an optimal pH of 4.977 ± 0.058, a conductivity of 194.851 ± 2.847 mS/cm, and an ORP of 126.707 ± 6.958 mV. Connecting the three MFCs in series yielded a total voltage of 2.34 V. Taxonomic analysis of the anodic biofilm revealed a community dominated by Firmicutes (genus Lactobacillus: L. acidophilus, L. brevis, L. casei, L. delbrueckii, L. fermentum, L. helveticus, and L. plantarum), along with Bacteroidota and Proteobacteria (electrogenic bacteria). This microbial synergy enhances electron transfer and validates the use of carrot waste as a renewable source of bioelectricity for low-power applications. Full article

This study examines fish communities in the heavily impacted Bistrița River, located in the Eastern Carpathians of Romania, where diffuse pollution from mining, domestic wastewater, agricultural and forestry activities emerged as the most severe pressures. Fish sampling was conducted at twenty sites across two Natura 2000 protected areas. Results showed that species richness and diversity were higher downstream (Z1–Z5), indicating improved ecological conditions compared to the upstream section (B1–B15). The fish-based Index of Biological Integrity (IBI) suggested overall good biological integrity, with excellent conditions (class I) recorded in 70% of sites. Redundancy analysis (RDA) further revealed that elevation and conductivity significantly shaped community structure, while the site-specific impact score had only marginal effects. To assess water quality and biotic integrity based on different communities, as required by the Water Framework Directive (WFD), five sites were selected for parallel sampling of diatoms and benthic invertebrates. Among these, zoobenthos proved the most sensitive to water quality degradation, with biotic indices indicating classes I to III. These findings demonstrate that assessments based solely on fish may underestimate ecological impacts, underscoring the need for complementary approaches that account for multiple biotic communities when monitoring riverine ecosystem health. Full article