The hydrozoan fauna of the Mediterranean Sea is considered as the best-known fauna of this class in the world, and the last monograph covers 457 species representing about 12% of the 3,702 currently valid species reported in the last world assessment of hydrozoan diversity. In this paper the checklist of the hydrozoan marine species is reported for the nine Italian marine biogeographical units, updating the one previously published in the series ‘Checklist delle Specie della Fauna d'Italia’ in 1995 that reported 319 hydrozoans on 463 cnidarian taxa. This note describes the state of the art of the Italian Hydrozoa checklist data set until June 2024. In detail, the updated checklist includes 340 hydrozoan species (128 Anthoathecata; 121 Leptothecata; 53 Siphonophorae; 6 Limnomedusae; 3 Actinulida; 14 Narcomedusae; 15 Trachymedusae), representing 74% of Mediterranean hydrozoan species. In detail in the current Italian Hydrozoa checklist, 40 species were added (increase of 12%) compared to the previous checklist with 14 strictly endemic species (4% of the total) for the Italian waters, 55 (16%) subendemic ones, and 20 (6%) are alien species. On the other hand, 19 species reported in the previous checklist were removed because considered dubious, synonyms of older ones or without detailed distributions for our territory. In addition, 69 species (20%) expanded their biogeographic distribution. The checklist data set will be dynamically updated with new records, and it will be freely available from Lifewatch Italy at https://www.lifewatchitaly.eu/en/initiatives/checklist-fauna-italia-en/checklist. This note describes the state of the art of the Hydrozoan checklist data set until June 2024.

Optimizing germplasm characterization via phenotypic diversity assessment and descriptor selection in Passiflora spp.

A novel spectral marker-based diversity assessment of sesame germplasm.

Start codon targeted and internal transcribed spacer markers: Effective tools for assessment of genetic diversity, population study and DNA barcoding of wild and edible mushroom collections

A multi-step strategy to study trub, a beer by-product, using LC-MS/MS and feature-based molecular networking, evaluating its antioxidant potential.

Assessment of genetic diversity and pathogenicity of porcine rotavirus A, and immunogenicity of a bivalent inactivated vaccine in southern China.

Genetic diversity assessment and digital labeling (QR code) of 89 marigold germplasms: A synergistic study of phenotypic traits and SSR molecular markers

Successful language comprehension requires listeners to rapidly adapt to linguistic variability, including accented speech. While a growing body of research suggests that long-term exposure to diverse linguistic input can facilitate such adaptation, characterizing the real-world experience remains a challenge. Traditional self-report measures are limited by recall bias and fail to capture incidental exposure. To address this limitation, we introduce a novel geolocation-based metric that quantifies local linguistic diversity using US Census data at the zip code level. Specifically, we use the proportion of nonnative English speakers as a proxy for environmental exposure to accented speech. We report an initial application of this method in a large-scale online perceptual study (N = 647) of monolingual English speakers across the United States. Participants completed a cross-modal matching task designed to assess rapid adaptation to Chinese-accented English. Results show that our census-based metric predicted both subjective familiarity with the accent and perceptual adaptation during the first few moments of exposure. Crucially, adaptation was predicted by the prevalence of Chinese-accented speech in participants' local environment, but not by the prevalence of other accents (e.g., Spanish), suggesting accent-dependent facilitation. This new geolocation-based approach provides a scalable, objective complement to self-report measures, and is readily applicable even to populations where self-reporting proves infeasible or unreliable, such as older adults and clinical populations. It will enhance our understanding of how linguistic diversity in the environment shapes speech perception, adaptation, and learning.

ABSTRACT Composting is an effective way to recycle perishable waste (e.g. food, vegetable and fruit waste), while the effects of varying compost application rates on soil properties and bacterial communities are not well understood. Soil samples were taken from pot experiments that included an unfertilized control, a mineral NPK-only treatment and four compost-amended mineral fertilizer treatments at 0.7%, 2.1%, 3.5% and 4.9% w/w. Soil analysis included pH, electrical conductivity (EC), soil organic carbon, total nitrogen, total soluble salt, and assessment of diversity and community of soil bacteria. Results showed that perishable waste compost application enhanced soil salinity by significantly increasing soil total soluble salt content (67–174%) and EC (24–152%) compared with mineral fertilizer. Perishable waste compost addition affected soil bacterial community composition by increasing Cyanobacteria and decreasing Firmicutes relative abundance, which reflected changes in soil salinity. Soil bacterial community stability and potential biological activity, together with soil phosphorus availability and rice yield (increased by 41% and 36% compared to mineral fertilizer) were promoted under the 2.1% perishable waste compost addition, which suggested this rate was recommended for optimal productivity in paddy soil. These findings advanced our understanding of the soil salinity risk for perishable waste compost use as organic fertilizer.

Increasingly, the effects of computational exploration of form, structure and materiality are being felt even in the realms of contemporary abstract sculpture due to the availability of generative algorithms that allow exploration of form, structure and materiality to levels previously impossible in the realm of manual sculptural practice. In this paper, the authors explore the contribution of generative algorithms to the creation of abstract sculptures, and discuss how rule-based, evolutionary, learning-based, and hybrid computational methods assist in the creation of complex and emergent sculptural objects. The paper gives a coherent approach to the generative pipeline, including algorithmic form generation, computational representation, human-algorithm co-creation, and digital fabrication. To facilitate the systematic analysis and comparison, a common evaluation methodology is proposed that integrates aesthetic evaluation, assessment of novelty and diversity, structural feasibility, preparedness of fabrication, performance of materials, as well as usefulness of the process. The paper also contends on the implications of educational and studio practices, which explore system-based learning by integrating interdisciplinary practices alongside the importance of learning, which revolves around exploration, in sculpture learning. The problem of authorship, interpretability, bias in the dataset, and sustainability are addressed critically, and the directions of further research are described. In sum, the paper frames generative algorithms as collaborative generators of expressive and conceptual range of abstract sculpture with the primary emphasis on the human artistic will.

Sunflower (Helianthus annuus L.) is a valuable oilseed crop with significant economic importance. Enhancing breeding strategies in this species heavily relies on genetic diversity and molecular tools. Among these tools, SNP-based genotyping has proven to be an effective method for exploring genomic variation and understanding population structure in plants. This study aimed to evaluate the genetic diversity, population structure, and identify genomic regions under selection within a panel of sunflower inbred lines. A 10K SNP (single-nucleotide polymorphism) array was employed to examine genetic variation among 94 sunflower inbred lines. The results showed that SNPs were unevenly distributed across the 17 sunflower chromosomes, with a higher density observed in telomeric regions. The average transition-to-transversion ratio was 3.75, confirming the reliability and quality of the genotypic data. Analysis of population structure revealed two distinct subgroups, as supported by the results from STRUCTURE, PCoA, and WPGMA methods. AMOVA revealed that 16% of total genetic variance occurred among populations (Fst = 0.156), and overall genetic diversity was moderate to high (PPL = 92.94%). A total of 283 potential genes were linked to genomic areas that were under selection. Functional enrichment analysis revealed significant involvement of these genes in proteasome activity and pyruvate metabolism pathways. The findings validate the presence of considerable genetic diversity and moderate genetic differentiation within the studied sunflower germplasm. This study reports, for the first time, the use of the Fst statistic to identify pathways that contribute to population differentiation and are under selection pressure in a panel of sunflower inbred lines. These results provide valuable insights that could inform future sunflower breeding efforts through marker-assisted selection and offer insights into the genetic mechanisms underlying adaptation and population divergence in sunflower.

Diversity and ecological assessment of aquatic algal species of river Varuna in Varanasi

Oklahoma grapevine production interests are on the rise, however very little is known about the occurrence of major grapevine-infecting viruses in the state. To address this knowledge gap, a total of 85 grapevine samples were collected from eight vineyards across six counties in Oklahoma during the spring and fall of 2024. Total RNA extracts from each sample were assayed for 14 major viruses by RT-PCR, including grapevine leafroll-associated virus 1 (GLRaV-1), GLRaV-2, GLRaV-3, GLRaV-4, grapevine fanleaf virus (GFLV), grapevine red blotch virus (GRBV), tobacco ringspot virus, tomato ringspot virus, grapevine fleck virus, grapevine rupestris stem pitting-associated virus (GRSPaV), grapevine virus A (GVA), GVB, GVE, and GVH. Virus infection was detected in 68.2% of samples, with mixed infections (36.5%) being more common than single infections. Seven of the targeted viruses were detected at varying levels of incidences, including GRBV (48.2%), GRSPaV (40%) GLRaV-3 (20%), GFLV (11.8%), GVE (11.8%), GVA (5.9%), and GVH (2.4%). GRBV variants belonging to both clades I and II were identified in Oklahoma, with the clade II members being more predominant. Multigenic diversity assessments of GLRaV-3 isolates from Oklahoma showed the occurrence of variants belonging to both clades I and V, with the latter being more frequently detected in the state relative to results from other U.S. growing regions. The findings of the study underscore the importance of continued virus surveillance, use of clean plant materials, and targeted management strategies to protect Oklahoma's developing vineyards from the long-term impact of viral diseases.

Assessment of Genetic Diversity among Beauveria bassiana Isolates Using ISSR and SCoT-PCR Markers

Citrus is a genetically diverse genus widely cultivated across tropical and subtropical regions, yet its varieties often exhibit overlapping morphological traits that complicate accurate identification. In this study, the genetic diversity of nine Citrus varieties was assessed using 36 Simple Sequence Repeats (SSR) markers in combination with key morphological and biochemical traits. The CTAB method was employed to extract genomic DNA, followed by polymerase chain reaction (PCR) using a specific set of primers. Gel documentation was performed to score the bands obtained. This study aimed to utilize 36 SSR markers to characterize the genetic diversity of nine Citrus varieties collected from the Citrus Research Institute (CRI), Sargodha. Polymorphic information content (PIC) values ranged from 0.20 to 0.50, averaging 0.27, indicating moderate genetic variability among the varieties. Principal component analysis explained 68.7% of the total variation across the first two components, and cluster analysis grouped the varieties into two major clusters, demonstrating clear genetic differentiation. The integration of molecular and morphological data revealed distinct similarity groups, providing valuable insights for selecting superior parental lines. These findings support the development of improved Citrus varieties and the establishment of DNA‐certified true‐to‐type nursery plants for enhanced orchard productivity.

Inflammatory bowel disease (IBD), including ulcerative colitis (UC) and Crohn's disease (CD), is a chronic disorder marked by intestinal inflammation and immune dysregulation. While bacterial dysbiosis has been widely investigated, the gut virome remains less explored. Altered viral communities, particularly bacteriophages, may destabilize microbial balance and amplify host inflammation. To characterize virome alterations, we conducted a cross-sectional observational study in Tabriz, Iran, involving fifty participants divided into five groups: mild UC, severe UC, mild CD, severe CD, and healthy controls. Stool samples were processed for viral nucleic acid extraction and analyzed using metagenomic next-generation sequencing. Bioinformatics pipelines included diversity assessment, taxonomic profiling, functional annotation, and discriminant analysis (LEfSe). Predictive modeling was performed with random forest classifiers. Virome richness and diversity were reduced in severe UC and CD compared with controls, whereas mild cases showed values closer to healthy individuals. Taxonomic profiling revealed depletion of crAss-like phages and microviridae in IBD, along with enrichment of Caudovirales families such as siphoviridae and myoviridae. Among eukaryotic viruses, anelloviridae were prominent in severe IBD, and herpesviridae were enriched specifically in severe UC. Functional annotation highlighted enrichment of structural and lytic phage proteins in severe groups, whereas lysogeny-associated domains were more abundant in healthy controls. Random forest models based on viral features achieved appropriate accuracy, with an AUC of 0.89 for distinguishing IBD from controls and 0.83 for classifying mild versus severe disease. Thus, IBD is associated with reduced virome diversity, loss of core protective phages, and selective enrichment of bacteriophages and eukaryotic viruses. These findings suggest that virome features may have potential as biomarkers for non-invasive diagnosis and severity stratification in IBD, requiring validation in larger and longitudinal cohorts.

Grass species of the Poaceae family play central roles in terrestrial ecosystems and agriculture, and land management. Despite their ecosystem and economic importance, comprehensive comparative studies of the chloroplast genome characteristics and evolutionary patterns across Poaceae remain limited. In this study, we sequenced and assembled the complete chloroplast genome of Poa pratensis and conducted a comparative analysis with 29 additional Poaceae grass species. All 30 species exhibited the canonical quadripartite structure, with genome lengths ranging from 133,331 to 140,622bp and GC content between ranging from 38.10% to 38.82%. Codon usage analyses revealed a consistent bias toward A/T-ending codons, with 29-30 codons per species exhibiting relative synonymous codon usage (RSCU) values > 1, while effective number of codons (ENC) values indicated relatively weak codon usage bias (CUB) across all taxa. Simple-sequence-repeat (SSR) analyses identified 58-98 SSRs per species, predominantly mononucleotides and octanucleotides predominantly localized mainly non-coding regions. Integration of neutrality plots, PR2 analysis, and ENC-GC3s plots, indicated that natural selection, rather than mutation pressure, was the dominant force shaping codon usage patterns. Ka/Ks analysis demonstrated pervasive strong purifying selection (Ka/Ks < 0.5) across most genes, with only a few, exceptions, clpP, matK, infA, and select hypothetical genes exhibiting relaxed constraints. Phylogenetic and collinearity analyses revealed well-resolved relationships, confirming that Poa pratensis and Poa supina share the closest genetic affinity, and supporting established taxonomic classifications. Despite overall structural conservation, functional constraints preserved genome integrity while permitting adaptive diversification. Strong purifying selection observed across chloroplast genes underscores their essential roles in photosynthesis and other core cellular processes. The identified molecular markers and resolved phylogenetic relationships provide valuable resources for grass breeding, genetic diversity assessment, and conservation. Collectively, this study establishes a comprehensive chloroplast genomic framework for elucidating evolutionary dynamics in Poaceae and informs future molecular breeding and biotechnological applications.

The current research study in chickpea programme was aimed to determine variability and genetic diversity in 24 desi genotypes raised at Regional Agricultural Research Station, Nandyal in a Randomized Block Design during Rabi 2024 - 25. The traits studied were days to 50% flowering, days to maturity, final plant stand, plant height, number of pods per plant and seed yield. Analysis of variance (ANOVA) study revealed existence of significant exploitable variation for all the traits. Moderate estimates of PCV and low GCV were noticed for seed yield coupled with moderate heritability and genetic advance. Diversity study through Principle Component Analysis implied two principal components with eigen values more than one i.e., PC1 and PC2 describes 38.6% and 19.69% respectively with a cumulative effect of 58.30% of the total variation. The 24 chickpea genotypes were grouped in three clusters based on different traits using Ward’s method of clustering, in which cluster III is the largest with 15 entries. The genotypes NBeG 2049, NBeG 2110, NBeG 2106, NBeG 2120, NBeG 2051 were found to be promising entries as they were more diverse in performance of different traits and high yielding as well and can be used for improvement of yield and its attributing traits in chickpea breeding programme.

Cranial morphology assessed through anthropometric indices is fundamental for understanding population diversity, forensic identification, and clinical assessment, particularly within Nigeria’s multi-ethnic context. This cross-sectional study aimed to compare cephalic indices—defined as the ratio of maximum head breadth to maximum head length—between the Jhar and Sayawa ethnic groups in Tafawa-Balewa Local Government Area, Bauchi State, Nigeria, and to generate baseline reference data for these populations. A total of 410 participants (103 Jhar and 307 Sayawa), aged 5–66 years (mean = 24.0 ± 11.2; 291 males and 119 females), were recruited, and socio-demographic information was obtained using a structured pro forma. Head length and breadth were measured following standardized anthropometric techniques, and cephalic indices were calculated accordingly. Data were analyzed using Microsoft Excel and SPSS (Version 27), with descriptive statistics, charts, and tables for presentation, and categorical associations evaluated using Chi-square tests (p &lt; 0.05). The mean cephalic index was 79.33 ± 4.85 for Jhar and 78.32 ± 5.19 for Sayawa, values that fall within the mesocephalic range indicative of intermediate head shapes typical of populations in the region. No statistically significant differences were observed between the two ethnic groups (p &gt; 0.05), suggesting a broadly shared cranial profile. These findings enrich the anthropometric database for Nigerian ethnic groups and have practical implications for forensic anthropology, clinical assessment, and future research on craniofacial variation in multi-ethnic populations.

Plant diversity makes India one of the megabiodiverse countries in the world. But mankind has been exploiting plants for food and medicinal purposes since time immemorial. The vast number of plant species occupying the earth shows large diversity with respect to their habit, habitat, structure, function and life span. A Study was conducted to enumerate the tree diversity of plants of the College of Agriculture, Bheemarayanagudi campus during the year 2023-24. The whole campus was visited many times and collected information about the type of plants, their abundance and plants were identified based on the literature cited. The college campus has a total of 1678 no. of individuals of trees belonging to 52 species, 47 genera and 23 families. The maximum number of tree species has been recorded in Azadirachta indica A. Juss. (741) Simarouba glauca DC. (118), Pongamia pinnata (L.) Pierre. (109), Tectonagrandis L.f. (96), Cassia siamea Lam. (68), Monoon longifolium (Sonn.) B.Xue &amp; R.M.K.Saunders, (68), Santalum album L. (53), Albizia lebbeck (L.) Benth. (45), Ficus lacor Buch-Ham. (43) and Roystonea regia (Kunth) O.F. Cook (43), etc. The results found that Meliaceae, Fabaceae, Simaroubaceae, Lamiaceae, and Moraceae were the dominant families. The campus has 2 endangered and economically important medicinal plants, such as Swietenia Mahagoni (L.) Jacq., and Tecoma undulata (Sm.) G.Don. and 01 vulnerable Santalum album L. species. The rationale of the present work is to document the tree species of each tax with scientific information about the campus.