Search Results (187)

Background: The Taiwanese loach (Paramisgurnus dabryanus ssp. Taiwan, Dabry de Thiersant, 1872.) is an economically important aquaculture species in East Asia, and its body color directly affects its ornamental and market value. Our research group recently discovered a golden-red mutant, named “Gan Hong No. 1” (MR), within a wild-type (WT) population. During embryogenesis, MR individuals exhibit almost no melanophore deposition, and after hatching, xanthophores and erythrophores appear sequentially, suggesting that the body color variation likely originates from alterations in the gene regulatory network during early development. Objective: To systematically compare the transcriptomes of WT and MR-Taiwanese loach during early development, to identify the key regulatory pathways underlying red body color formation from a temporal perspective, to test whether the classical melanin synthesis pathway is impaired, and to provide a theoretical basis for selective breeding of body color traits. Methods: High-throughput transcriptome sequencing was performed on eight early developmental stages (0, 5, 10, 15, 20, 23, 28 and 43 h post-fertilization) of both loach types. Differential expression analysis, time-series trend analysis, and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment were used to systematically characterize gene expression dynamics. Transcriptomic data validation was performed using real-time PCR. Results: In MR, the core transcription factor mitfa was significantly downregulated, whereas the expression of melanin synthesis genes such as kita and dct showed no significant difference, indicating that the impairment of melanogenesis is caused by mitfa downregulation. Trend analysis and pathway enrichment revealed that in MR embryos, pathways related to oxidative stress, unsaturated fatty acid biosynthesis, C-type lectin receptor signaling, p53 signaling, and apoptosis were significantly activated, while the thyroid hormone synthesis pathway was markedly upregulated. In WT, these pathways showed the opposite trend. qRT-PCR results were consistent with the transcriptome data. Conclusions: This study demonstrates that downregulation of mitfa serves as the initial trigger for red body color variation in the Taiwanese loach. This mutation impedes melanin synthesis and concurrently activates a coordinated regulatory network involving oxidative stress, immune inflammation, and thyroid hormone signaling. Accumulation of unsaturated fatty acids alleviates oxidative damage and supports carotenoid deposition, while immune signals eliminate aberrant melanocytes and promote compensatory generation of red and yellow chromatophores. The upregulated thyroid hormone further fine-tunes pigment cell differentiation. For the first time in a cobitid species, this study elucidates the mitfa-mediated, multi-pathway synergistic molecular mechanism driving the transition from melanin-based to carotenoid/pteridine-based red coloration in fish, thereby providing a theoretical reference for molecular breeding of body color in aquaculture. Full article

Background: Hearing loss is a widespread sensory disorder affecting over 1.5 billion people worldwide, with the number projected to exceed 700 million by 2050. It imposes social and economic burdens across all ages and regions. Approximately half of adult cases are preventable, but the underlying causes are complex, with 75–80% due to autosomal recessive genetic factors and key roles for mutations in genes such as GJB2. Advances in sequencing technologies have accelerated gene discovery, but challenges remain in interpreting variants. Epigenetic mechanisms such as DNA methylation and histone modifications are increasingly recognized as crucial in auditory biology and could offer new biomarkers and therapeutic targets. Integrating epidemiological, genetic, and epigenomic data is essential to developing targeted prevention and treatment strategies to reduce the global burden of hearing loss. Methods: This narrative review examines recent genomic and epigenomic advances in hearing loss, with particular emphasis on molecular mechanisms, emerging diagnostic applications, and translational therapeutic opportunities. A comprehensive review of current epidemiological data, genetic studies, and epigenomic research was conducted using the peer-reviewed literature from international databases. Key areas of interest include inheritance patterns, molecular pathways, and recent advances in omics technologies. Results: Epigenetic mechanisms, including DNA methylation and histone modifications, are increasingly recognized as important regulators of cochlear development and hair cell survival, although much of the current evidence remains preclinical. Studies suggest that peripheral epigenetic signatures may serve as biomarkers for early diagnosis and risk stratification. Conclusions: Integrating established screening pathways with epidemiological trends and molecular knowledge offers a promising path toward precision medicine in hearing care. Connecting these domains is essential to developing equitable and effective interventions and addressing persistent global disparities in hearing health. This review highlights the evolving landscape of auditory genetics and epigenetics and outlines future directions for translational research and personalized therapy. Full article

The global horse racing industry relies heavily on elite breeding. Therefore, a molecular understanding of athletic traits is crucial for the industry’s advancement. This study utilized Bibliometrix, VOSviewer, and CiteSpace to conduct a comprehensive bibliometric analysis of 869 publications in the Web of Science Core Collection (2011–2025), decoding the academic landscape and evolutionary trajectory of equine genetics. The results indicate a significant upward trend in academic output since 2019, with the United States, South Korea, and the United Kingdom emerging as the primary contributors. Institutions such as the University of California, Davis, and University College Dublin serve as key hubs within a highly structured global collaborative network. Analysis of keyword co-occurrence and bursts reveals a distinct paradigm shift: research has evolved from early single-gene identification (e.g., MSTN) to large-scale genome-wide scans, and more recently to functional genomics and bioethical issues. Contemporary research frontiers increasingly focus on “gene doping” “homozygosity” and “risk factors” signaling that horse genetics is shifting from performance-oriented selection toward a comprehensive framework that integrates phenotypes, health, and genetic diversity. This study provides researchers with a strategic roadmap to help them align with emerging trends and foster international collaboration in equine genomic selection. Full article

Virophages are satellite viruses that depend on the replication machinery of giant double-stranded DNA viruses and influence the structure and dynamics of viral communities through multilayered interactions among giant viruses, their hosts, and virophages. Since the discovery of the Sputnik virophage in 2008, virophages have been increasingly recognized for their roles in regulating giant virus replication, contributing to host defense mechanisms, and shaping the evolution of mobile genetic elements. However, quantitative syntheses examining how virophage research has developed over time, particularly in marine environments, remain limited. Here, we conducted a bibliometric analysis of virophage research published between 2008 and 2025 using the Web of Science Core Collection. By comparing an overall virophage research corpus with a marine virophage sub-corpus, we assessed publication and citation trends, collaboration structures, and keyword-based intellectual and thematic evolution. Our results show that virophage research has gradually transitioned from an early phase dominated by landmark discoveries and experimental model systems to a data-intensive stage driven by genome- and metagenome-based analyses and computational approaches. Although marine virophage studies represent a relatively small proportion of the total literature, they exhibit sustained citation impact and form a distinct research axis within the field. In particular, marine-focused studies emphasize metagenomic discovery, genome sequence alignment, and the analysis of mobile genetic elements such as polinton-like viruses, highlighting the role of marine environments in accelerating the intellectual transition of virophage research. Collectively, these findings demonstrate that virophage research has moved beyond a “discovery and definition” phase toward data-driven integrative interpretation, with marine virophage research emerging as a key domain for understanding the structure and evolutionary dynamics of marine viral ecosystems. Full article

A distinct form of chronic kidney disease of unknown etiology (CKDu) has emerged in tropical regions of Sri Lanka, predominantly affecting individuals aged 30–60 years in the North Central Province. Unlike conventional chronic kidney disease (CKD), CKDu occurs independently of diabetes or hypertension and is characterized by tubulointerstitial damage, including tubular atrophy, interstitial inflammation, and fibrosis. Epidemiological studies showed familial clustering, suggesting an underlying genetic predisposition. This study aimed to identify genetic variants associated with CKDu in Sri Lankan populations using whole-exome sequencing (WES). Eighty-six individuals (47 CKDu patients and 39 controls) were recruited from endemic and non-endemic regions. Physiological, biochemical, and geographic parameters were recorded. DNA extracted from blood was subjected to WES to identify variants associated with CKDu. Results: A total of 171 unique variants across 121 genes were identified. Among the most prevalent genes were ATXN3, LFNG, PNLDC1, LINC02456, and HLA-DRB1. In the case–control comparison, only LFNG showed statistically significant enrichment in affected individuals, whereas signals in ATXN3, PNLDC1, and LINC02456 were not statistically significant, but have an association with renal dysfunction, and thus are included as hypothesis-generating variant observations. HLA-DRB1 variants showed trends toward a protective haplotype. LFNG showed the greatest prevalence in affected individuals (71.7%), followed by PNLDC1 (63%), ATXN3 (56%), FIP1L1 (41%), and HLA-DRB1 (32%). Conclusion: Findings suggest genetic variants in combination with environmental factors may contribute to CKDu susceptibility in the Sri Lankan population. We underscore the multi-factorial nature of CKDu and highlight the need for integrative genomic and environmental research to elucidate disease mechanisms and inform targeted prevention strategies. Full article

Vegetation restoration can regulate soil microbial habitat and carbon supply by altering soil physicochemical properties. However, it remains unclear how different vegetation restoration patterns influence soil microbial carbon cycling functions through these changes. This study investigated four vegetation restoration models including two coniferous forests —Platycladus orientalis (L.) Franco. (Cupressaceae, PO) and Pinus densiflora Siebold and Zucc. (Pinaceae, PS); one broadleaf forest—Quercus acutissima Carruth. (Fagaceae, QA); and a shrub (SH), using wasteland (WL) as a control. This study employed metagenomic sequencing technology in conjunction with analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The research examined alterations in soil physicochemical characteristics, microbial community structure, and functional pathway associated with carbohydrate metabolism, carbon fixation, and methane metabolism. Vegetation restoration patterns had a strong impact on soil characteristics and microbial composition. Compared to WL, the PO treatment exhibited significant increases in soil organic carbon (SOC, 110.71%), phosphorus (TP, 400%), and bulk density (BD, 22.4%). Significant differences were observed in soil carbon cycle functional pathways, with overall abundance following the trend PO > WL > SH > PS > QA. The relative abundance of carbon fixation, methane metabolism, and carbohydrate metabolism pathways was highest in PO, significantly higher than in QA. Mantel test showed soil phosphorus, pH, and C; N strongly linked to microbial carbon cycling pathways, marking them as key regulators. We found that PO showed the highest abundance of carbon-cycling-related functional pathways, whereas PS showed a comparatively weaker response, suggesting species-specific variation rather than a uniform coniferous–broadleaf pattern. Vegetation restoration controls microbial carbon cycling through soil properties, especially phosphorus, pH, and nutrient balances. This knowledge supports better restoration planning for ecosystem carbon management. Full article

Drought, a major abiotic stressor affecting global agricultural productivity, significantly reduces crop yields and threatens food security worldwide. As the primary organ for perceiving soil moisture signals and absorbing water, the crop root system architecture plays a pivotal role in plant adaptation to drought conditions. With the development of high-throughput imaging technologies (i.e., 2D/3D image acquisition), high-throughput genotyping platforms, and gene-editing technologies, significant progress has been achieved in the characterization of root traits and the dissection of molecular genetic regulatory networks underlying these traits in crops. This review comprehensively synthesizes recent advances in the phenotypic characterization, underlying molecular regulatory networks, and functional roles of key root architectural traits, including the root length, angle, density, and root hair development, in enhancing drought resilience. Finally, we discuss the existing challenges in the current research and provide an outlook on the future trend of integrating multi-omics, high-throughput phenomics, and genome editing technologies to breed new drought-resistant crop varieties with ideal drought-resistant root architectures. Full article

Geometric morphometrics is an important component of quantitative research on insect morphology, widely applied in taxonomy, intraspecific variation, and phylogenetic studies. However, systematic research in this field remains limited, with few comprehensive summaries of research trends, hotspots, and core theories. This study, based on scientometric methods, analyzed 1321 publications indexed in the Web of Science database up to 31 December 2025, and presents a meta-scientific review from a macro perspective, revealing the research trends, hotspots, and future directions in the field. The results show that: (1) annual publications exhibit overall growth, while research methods evolved from single landmark analysis to multimodal and interdisciplinary approaches; (2) scientists from Brazil, the USA, and France are major contributors, with studies spanning morphology, taxonomy, and ecology; (3) taxonomic studies centered on wing shape analysis constitutes a major research hotspot, closely related to phylogeny, allometry, and sexual dimorphism; (4) highly co-cited studies provide the main theoretical and methodological foundations for the field. Future research, building on existing hotspots, will further integrate geometric morphometrics with genomics, ecological functional data, three-dimensional geometric morphometrics, and artificial intelligence-assisted approaches to advance integrative taxonomy within interdisciplinary and data-driven frameworks. Full article

Studies on Carica papaya have focused on addressing challenges in cultivation, postharvest management, and its medicinal properties. Given the extensive volume of information produced, a quantitative analysis is required to clarify the intellectual framework of C. papaya research. This study aims to delineate the scientific landscape of C. papaya, identify research trends in agriculture and food science, and analyze correlations between secondary metabolites and bioactivities using bibliometric analysis. Our analysis examined 6546 documents from 1737 journals, consisting of 6076 articles, 379 reviews, and 91 conference papers. The United States, India, Brazil, and China lead scientific production and maintain robust international partnerships. The main research domains were applied sciences (40.9%), analytical studies (36.6%), and experimental research (16.9%), with topics including postharvest quality, disease resistance, genomic sequencing, and biological activities. A co-occurrence analysis revealed an association between polar leaf extracts and phenolic and flavonoid compounds, which are linked to antioxidant, anticancer, and antimicrobial activities. Furthermore, antioxidant activity was the most frequent finding (945 articles). In conclusion, scientific knowledge of C. papaya primarily comprises studies on the plant genome, crop diseases, and bioactive compounds. Research highlights the plant as a valuable resource for sustainable agriculture, specifically its leaves as a source of novel phytopharmaceuticals. Full article

Several researchers have documented the occurrence of the unfamiliar severe acute respiratory syndrome coronavirus 2 ribonucleic acid (also known as SARS-CoV-2 RNA) in various raw wastewater (WW) samples analyzed globally. The efficiency of strategic WW-based epidemiology (WBE) approach as a timely cautioning tool for human coronavirus disease-2019 (COVID) and other similar outbreaks is highly promising. This strategy offers a cost-effective, population-wide surveillance tool that can detect rising case trends, from days to weeks before clinical reports, thus enabling proactive public health interventions. This study aimed to detect the occurrence of the viral genome in WW over four seasons, which contributes to the database for multi-plant surveillance research in South Africa. About 480 WW influent samples were amassed from ten sampling points situated in nine wastewater treatment facilities (WWTFs) in Amathole District Municipality (ADM) located in the Province of Eastern Cape (EC), South Africa (SA). The study was carried out for a period of one year. Quantitative real-time polymerase chain reaction (i.e., RT-PCR) was operated to identify the viral genomes in the respective total RNA samples. Of the 480 extracted RNA samples, 210 (44%) were positive with viral genome copies (gc) that ranged from 700 to 40,000 GC/mL. Our results were contrasted with existing COVID-19-positive cases throughout the COVID omicron wave in the ECP. Variations in gc were observed across different seasons, with the highest GC observed in winter. In contrast, there were significant inconsistencies in the existing data of COVID-19 clinical cases, thus indicating no connection between both data. However, with more similar studies, advanced innovative WBE strategies could possibly act as prompt warning tools to signal public health officials about potential future outbreaks. Full article

Heterosis is a landmark innovation in modern agriculture, which has been widely exploited to boost crop productivity. As a staple food for over half of the global population, rice depends heavily on heterosis for yield improvement. Notably, hybrid rice has made remarkable contributions to global food security over the past several decades. Male sterility serves as the fundamental basis for efficient hybrid rice breeding, with cytoplasmic male sterility (CMS) and genic male sterility (GMS) as the core systems employed in practical production. CMS, induced by mitochondrial genes, can be restored to fertility by nuclear restorer genes, thereby forming the essential genetic basis for the three-line hybrid rice system. GMS, mainly regulated by the nuclear genome, includes dominant and recessive nuclear sterility. Specifically, recessive environment-sensitive genic male sterility (EGMS) has facilitated the development of the two-line hybrid rice system for commercial hybrid seed production. The third-generation hybrid rice technology (TGHRT) is a transgenic approach developed for propagating stable recessive GMS lines. This review comprehensively summarizes the latest advances in rice male sterility systems, focusing on their genetic classification, origin, and molecular mechanisms. It further analyzes their application status, inherent limitations, future research directions, and development trends in hybrid rice production, aiming to deepen our understanding of the innovation and optimization of hybrid rice breeding technologies. Full article

Heavy metals such as copper are commonly found in aquatic environments. Microalgae can effectively adsorb heavy metals, while high concentrations impair their physiological and biochemical processes. This research investigated the impact of varying concentrations of sodium thiosulfate (Na₂S₂O₃) on the heavy metal tolerance of Chlorella vulgaris. Results showed that Na₂S₂O₃ and copper ions Cu(II) co-stress significantly improved the tolerance of C. vulgaris to Cu(II). To explore the mechanism, weighted gene co-expression network analysis (WGCNA) and trend analysis were applied to study the gene regulatory network under combined stress. A total of 103 significantly differentially expressed genes (DEGs) were identified. Further Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that the majority of DEGs are associated with photosynthesis, energy and liposome metabolisms. Physiological metrics, including chlorophyll content, photosynthetic activity, malondialdehyde (MDA), superoxide dismutase (SOD), and catalase (CAT), also aligned with bioinformatics results. This research offers a promising approach to reduce heavy metal pollution in water bodies. Full article

Following the COVID-19 pandemic, researchers have increasingly focused on monitoring the spread of the virus and improving methods to detect changes in the SARS-CoV-2 genome. Although clinical surveillance provides direct and reliable results, it has limited applicability. Wastewater-based epidemiology (WBE) has therefore emerged as a valuable, non-invasive complementary tool for disease surveillance. It provides a comprehensive picture of virus circulation in a population, including asymptomatic individuals and those who do not seek healthcare. In addition, it facilitates early detection of outbreaks and the collection of epidemiologic data at the community level. However, WBE also presents technical challenges, including variations in sampling and testing protocols, the presence of inhibitors that affect viral RNA extraction, and the need for standardised procedures between studies. These challenges should be addressed for possible future infectious disease outbreaks. One of the challenges facing researchers was to develop efficient methods that could overcome the extraction and detection problems related to inhibitors present in wastewater. To this aim, this systematic review highlights the potential use of WBE, the variety of techniques, and the most effective methods for the detection and quantification of SARS-CoV-2 in wastewater samples. A reproducible electronic search of the literature was conducted in the Web of Science (WoS) and PubMed databases for articles published between 2020 and 2024. Our search revealed that the majority of observed WBE applications emphasised a correlation between SARS-CoV-2 RNA concentration trends in wastewater and epidemiological data. Another relevant issue that the articles often discussed and compared was the techniques used in different steps of sample processing, such as sample collection, concentration and detection, hence the lack of standardised procedures. This paper provides a framework regarding previous research on WBE to gain a better understanding that will lead to functional solutions. Full article

Medical artificial intelligence (AI) systems depend heavily on high-quality data representations to support accurate prediction, diagnosis, and clinical decision-making. However, the availability of large, well-annotated medical datasets is often constrained by cost, privacy concerns, and the need for expert labeling, motivating growing interest in self-supervised representation learning. Among these approaches, contrastive learning has emerged as one of the most influential paradigms, driving major advances in representation learning across computer vision and natural language processing. This paper presents a comprehensive review of contrastive learning in medical AI, highlighting its theoretical foundations, methodological developments, and practical applications in medical imaging, electronic health records, physiological signal analysis, and genomics. Furthermore, we identify recurring challenges, including pair construction, sensitivity to data augmentations, and inconsistencies in evaluation protocols, while discussing emerging trends such as multimodal alignment, federated learning, and privacy-preserving frameworks. Through a synthesis of current developments and open research directions, this review provides insights to advance data-efficient, reliable, and generalizable medical AI systems. Full article

Background: Radiomics has emerged as a promising approach to non-invasively characterize the molecular landscape of gliomas, providing quantitative, high-dimensional data derived from routine MRI. Given the recent shift toward molecularly driven classification, radiomics may support precision oncology by predicting key genomic, epigenetic, and phenotypic alterations without the need for invasive tissue sampling. This systematic review aimed to synthesize current radiomics applications for the non-invasive prediction of molecular biomarkers in gliomas, evaluating methodological trends, performance metrics, and translational readiness. Methods: This review followed the PRISMA 2020 guidelines. A systematic search was conducted in PubMed, Ovid MEDLINE, and Scopus on 10 January 2025, and updated on 1 February 2025, using predefined MeSH terms and keywords related to glioma, radiomics, machine learning, deep learning, and molecular biomarkers. Eligible studies included original research using MRI-based radiomics to predict molecular alterations in human gliomas, with reported performance metrics. Data extraction covered study design, cohort size, MRI sequences, segmentation approaches, feature extraction software, computational methods, biomarkers assessed, and diagnostic performance. Methodological quality was evaluated using the Radiomics Quality Score (RQS), Image Biomarker Standardization Initiative (IBSI) criteria, and Newcastle–Ottawa Scale (NOS). Due to heterogeneity, no meta-analysis was performed. Results: Of 744 screened records, 70 studies met the inclusion criteria. A total of 10,324 patients were included across all studies (mean 140 patients/study, range 23–628). The most frequently employed MRI sequences were T2-weighted (59 studies, 84.3%), contrast-enhanced T1WI (53 studies, 75.7%), T1WI (50 studies, 71.4%), and FLAIR (48 studies, 68.6%); diffusion-weighted imaging was used in only 7 studies (12.8%). Manual segmentation predominated (52 studies, 74.3%), whereas automated approaches were used in 13 studies (18.6%). Common feature extraction platforms included 3D Slicer (20 studies, 28.6%) and MATLAB-based tools (17 studies, 24.3%). Machine learning methods were applied in 47 studies (67.1%), with support vector machines used in 29 studies (41.4%); deep learning models were implemented in 27 studies (38.6%), primarily convolutional neural networks (20 studies, 28.6%). IDH mutation was the most frequently predicted biomarker (49 studies, 70%), followed by ATRX (27 studies, 38.6%), MGMT methylation (8 studies, 11,4%), and 1p/19q codeletion (7 studies, 10%). Reported AUC values ranged from 0.80 to 0.99 for IDH, approximately 0.71–0.953 for 1p/19q, 0.72–0.93 for MGMT, and 0.76–0.97 for ATRX, with deep learning or hybrid pipelines generally achieving the highest performance. RQS values highlighted substantial methodological variability, and IBSI adherence was inconsistent. NOS scores indicated high-quality methodology in a limited subset of studies. Conclusions: Radiomics demonstrates strong potential for the non-invasive prediction of key glioma molecular biomarkers, achieving high diagnostic performance across diverse computational approaches. However, widespread clinical translation remains hindered by heterogeneous imaging protocols, limited standardization, insufficient external validation, and variable methodological rigor. Full article