Search Results (1,211)

Non-coding RNAs have emerged as gene-regulatory molecules acting at epigenetic, transcriptional, and post-transcriptional levels. Among them, microRNAs are short RNA molecules consisting of approximately 22 nucleotides. Increased microRNA expression suppresses target protein expression, whereas decreased microRNA expression relieves this repression and can induce overexpression of target proteins. microRNAs integratively regulate highly complex biological processes, including cell proliferation, differentiation, apoptosis, morphogenesis, and immune responses. Therefore, alterations in microRNA expression profiles may be directly linked to the fundamental pathogenesis of systemic sclerosis (SSc), an autoimmune and fibrotic disease involving multiple organs. This focused narrative review examines microRNAs involved in SSc fibrosis, vasculopathy, and immune dysregulation; extracellular-particle-associated microRNAs; and circulating and hair-derived microRNAs as candidate biomarkers. It also summarizes evidence on long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), yRNAs, and PIWI-interacting RNAs (piRNAs). Finally, therapeutic perspectives, including microRNA mimics, antisense inhibitors, and broader RNA-targeted strategies, are discussed together with key challenges in validation and clinical translation. Full article

Reliable aquaculture monitoring requires spatial, administrative, and environmental evidence to be integrated without treating these sources as equivalent. This study characterized mapped aquaculture land-cover dynamics in six coastal provinces of Ecuador from 1985 to 2024, assessed their 2023 correspondence with authorized or concessioned shrimp-farm area, quantified 2023–2024 land-cover transitions, and described climate exposure over a fixed historical aquaculture footprint. Annual MapBiomas Ecuador Collection 3.0 classifications were aggregated by province, canton, and parish; MPCEIP records were harmonized with INEC administrative codes; and CHIRPS v3 precipitation and ERA5-Land temperature were summarized over the union of all pixels mapped as aquaculture at least once during the study period. Mapped class 31 area increased from 58,198.792 ha in 1985 to 138,200.970 ha in 2024, with a maximum of 153,516.642 ha in 2022. In 2023, mapped area represented 74.508% of 202,114.900 ha of authorized or concessioned area, with strong canton-level rank correspondence. Between 2023 and 2024, persistence reached 135,774.430 ha, gross loss 14,816.766 ha, gross gain 2426.130 ha, and net change −12,390.636 ha. Climate exposure was wettest in 1998 and warmest in 2023. Together, the results show that coastal aquaculture development cannot be inferred reliably from a single territorial measure: long-term mapped expansion, administrative extent, recent classification changes, and climate exposure describe complementary but non-equivalent dimensions of the system. This distinction provides a more defensible basis for interpreting aquaculture land-use change and for targeting territorial monitoring and administrative verification. Full article

Background: Rare diseases collectively affect millions of children worldwide and are a major cause of pediatric morbidity, mortality, and lifelong disability. Although most have a genetic basis, obtaining a timely molecular diagnosis remains challenging because of substantial clinical and genetic heterogeneity. Advances in genomic medicine are transforming rare disease diagnosis and establishing genomics as the center of precision medicine. Methods: This review summarizes current evidence on genomic approaches for pediatric rare diseases, including established and emerging sequencing technologies, their clinical applications, implementation challenges, and future directions. Results: Whole-genome sequencing is increasingly being adopted as a first-line genomic test for suspected rare genetic disorders, particularly when the phenotype is heterogeneous or does not point to a specific diagnosis. Conventional cytogenetic and targeted molecular techniques remain important complementary approaches for selected phenotypes, variant classes, and orthogonal confirmation. Gene panels are effective for well-defined phenotypes, whereas whole-exome sequencing remains a high-yield approach for genetically heterogeneous disorders, particularly when whole-genome sequencing is not available or is not clinically indicated. Long-read whole-genome sequencing expands diagnostic capacity by detecting structural variants, repeat expansions, complex rearrangements, and non-coding pathogenic variants that frequently escape short-read technologies. Emerging multi-omics approaches further improve variant interpretation and help resolve previously unsolved cases. Beyond diagnosis, molecular findings guide personalized clinical management, genetic counselling, reproductive planning, and access to targeted therapies and genotype-driven clinical trials. However, broad implementation is constrained by challenges in variant interpretation, ethical and legal considerations, data governance, workforce capacity, cost, and inequitable access to genomic services. Artificial intelligence, international data-sharing initiatives, and coordinated healthcare networks are helping overcome these barriers and improve diagnostic equity. Conclusions: Whole-genome sequencing is increasingly emerging as a first-line genomic strategy for pediatric rare diseases, while complementary technologies, expert phenotyping, and iterative data interpretation remain essential for comprehensive and accurate diagnosis and equitable access to genomic medicine. Full article

Artificial intelligence (AI) is entering audit workflows while sustainability reporting expands the evidence subject to professional evaluation. This exploratory study examines how the UK Big Four publicly describe safeguards that keep AI-assisted work human-led, reviewable and accountable. The complete 2024 transparency-report cross-section was coded against seven pre-specified dimensions and summarized in an AI–Judgment Governance Disclosure Index (AI-JGDI). The index measures AI disclosure governance—the completeness of public accountability commitments—not internal control effectiveness. Firm evidence is reported with page-level passages and a decision-level coding log; the single-coder design remains a substantive limitation. The results are compared only as external context with recent inspection outcomes published by the UK Financial Reporting Council. All four firms disclose deployed AI capabilities and retained human responsibility; disclosure is most complete for oversight, accountability and learning, and least complete for AI-specific validation and engagement-level traceability. Sensitivity analysis supports the broad cross-firm pattern but not a precise ranking. The audit evidence is empirical; the sustainability-assurance extension is analytical. Across the four reports, AI disclosure governance and sustainability-assurance disclosures remain largely parallel, with no explicit engagement-level methodological link identified. Full article

Infantile hemangioma (IH) is the most common benign vascular tumor of infancy, characterized by a unique life cycle encompassing a rapid proliferative phase followed by spontaneous involution. Although the majority of cases exhibit a favorable prognosis, a small subset may be complicated by severe sequelae that adversely affect the physical and mental health of affected infants. Accumulating evidence indicates that the pathogenesis of IH involves a dynamic imbalance between angiogenesis and involution, which is tightly governed by the multilineage differentiation of hemangioma stem cells, core signaling pathway networks, and epigenetic regulation mediated by non-coding RNAs. A deeper understanding of the mechanisms underlying angiogenesis and involution will provide novel insights into both the fundamental biology and clinical management of IH. Furthermore, multiple bioactive constituents of the traditional Chinese medicine Salvia miltiorrhiza (Danshen) have demonstrated anti-angiogenic and pro-involution potential in tumor and ischemia models. This review systematically summarizes recent advances in the mechanistic understanding of IH angiogenesis and involution, and critically discusses the regulatory effects of Danshen active components on these processes, with the aim of offering a theoretical foundation for elucidating IH pathogenesis and facilitating the development of novel therapeutic agents. Full article

The regulation of transcriptional activity constitutes a primary layer of control over cellular function across diverse tissues and cell types. This regulatory transcriptional landscape is largely governed by epigenetic mechanisms, including DNA and histone modifications, the dynamic activity of epigenetic “writers” and “erasers,” and the influence of small regulatory molecules such as microRNAs (miRNAs). miRNAs are small non-coding RNA molecules that play critical roles in transcriptional and post-transcriptional gene regulation. By modulating the expression of transcription factors, kinases, and other regulatory proteins, miRNAs exert tight control over cellular processes and maintain homeostasis. Given the essential requirement for precise cellular coordination in reproductive biology, miRNAs have emerged as key regulators of reproductive function. They participate in multiple stages of reproductive processes, ranging from ovarian function to the establishment and maintenance of pregnancy, thereby influencing fertility outcomes across species. In this review, we summarize recent advances in understanding the roles of miRNAs in key reproductive events, including gametogenesis, oocyte maturation, embryonic genome activation, early embryonic development, implantation and pregnancy. We aim to highlight the principal miRNAs involved in the maintenance of reproductive function and fertility, and their molecular targets and the regulatory networks when known. Based on our review, we conclude that although their potential in clinical and/or agricultural applications still remains uncertain, their role in regulating fundamental aspects of cellular biology, particularly reproductive processes, is becoming increasingly clear. Full article

RNA-omics technologies have expanded poultry transcriptome research beyond tissue-level gene abundance. They now resolve intact transcripts, RNA chemical modifications, cellular origins, and spatial locations. This review centers on a core question: what specific, previously inaccessible RNA information does each RNA-omics technology provide? Based on their primary measurement targets, we categorize these technologies into four groups: bulk transcriptome and small RNA sequencing for analyzing gene expression and regulatory RNA networks; long-read and direct RNA sequencing for resolving transcript isoforms; epitranscriptomic methods for detecting RNA modifications; and single-cell and spatial transcriptomics for identifying the cellular origins and spatial distributions of signals. Methods for resolving RNA structure, RNA–protein interactions, and translation status (e.g., structure probing, CLIP-type mapping, and ribosome profiling) remain in their infancy in poultry, leaving translation and RNA–protein regulation largely unmeasured in tissues such as the oviduct, the lipogenic liver and nucleated erythrocytes. For each category, we discuss its direct measurement targets and primary outputs, the additional information it provides compared to established methods, representative applications in poultry, and its inherent limitations. Building on this framework, we discuss how to select and combine technologies based on specific research questions and summarize their applications in studies of production performance and product quality, reproduction, and health and resilience. Different technologies measure distinct types of RNA features and are not simply interchangeable. Future research must place greater emphasis on matching technologies to scientific questions, integrating complementary data, and improving three foundations: the annotation of poultry transcripts and non-coding RNAs, standardized analytical pipelines, and functional validation systems. Full article

Epigenetic dysregulation is a hallmark of glioblastoma (GBM) pathogenesis, with histone methylation playing a central role in chromatin remodeling and gene expression regulation. Enhancer of zeste homolog 2 (EZH2) is a key epigenetic regulator responsible for histone methylation. It primarily functions as a transcriptional repressor and regulates signaling pathways associated with tumor progression. Importantly, EZH2 is frequently recruited to long non-coding RNA (lncRNA) scaffolds, including HOTAIR and AGAP2-AS1, thereby enabling coordinated gene silencing by establishing repressive chromatin states. Although EZH2 expression is not consistently associated with overall survival in GBM, EZH2 remains a promising therapeutic target due to its roles in stemness and treatment resistance. This review summarizes current knowledge of EZH2 functions in normal and GBM cells, highlighting its complex functions and therapeutic potential. We also discuss the current status and limitations of EZH2-targeting therapies, including challenges related to blood–brain barrier penetration and clinical translation. Although a combination of EZH2 inhibitors and other epigenetic inhibitors may be beneficial in selected molecular contexts, its rationale depends on the underlying regulatory network. Future therapeutic development will require biomarker-driven patient stratification and precision medicine approaches to maximize clinical benefit in GBM. Full article

Artificial intelligence (AI) increasingly produces uncertainty outputs for sensing and measurement tasks, but the evidence supporting these outputs may not maintain a traceable correspondence with the relevant real-world conditions. This study conducted a structured 15-dimensional coding review of 566 studies, of which 556 formed stable dominant AI uncertainty claim units and entered the common analytic set. Each final code was linked to row-level audit evidence. The unidimensional distributions first showed breakpoint states with nonzero frequencies at the relevant nodes of the claim–condition–test–uncertainty-response chain, thereby confirming observable evidence discontinuities in the current corpus. The studies were then stratified using three sequential, non-compensatory evidence questions. Among the 556 studies, 347 (62.4%) were classified as Weak, 133 (23.9%) as Medium, and 76 (13.7%) as Strong. Descriptive cross-dimensional comparisons showed that specific OOD/drift risk or Error/quality estimation claims, Multiple uncertainty entry points, Multiple physical information types, and Sampling/ensemble approximation more often co-occurred with higher evidence traceability; Prediction reliability/confidence claims, a standalone Uncertainty proxy/score, and Latency/real-time inference constraints more often co-occurred with lower evidence traceability. This study summarizes the above evidence discontinuity as the physical fidelity gap (PFG), which refers to incomplete or unverifiable evidential links between AI uncertainty claims publicly reported in the literature and the relevant physical, measurement, or operational conditions. PFG provides a scope-bounded reference for locating links in the evidence chain that may need strengthening. The breakpoints observable in the current corpus indicate that the public evidence still has room for improvement in forming continuous, verifiable claim–condition–test–response correspondences; the tiered comparison indicates that subsequent work can strengthen the evidence chain by clarifying claim conditions, incorporating the relevant conditions into empirical testing, and reporting identifiable uncertainty responses and extended corroboration. Full article

River sediments act not only as important sinks for heavy metal pollution in watersheds, but also as potential secondary sources under changing environmental conditions. Heavy metals can enter river systems through industrial wastewater discharge, agricultural non-point runoff, urban stormwater and sewage inputs, mining and smelting activities, and atmospheric deposition. During adsorption onto suspended particles, sedimentation, and resuspension, metals such as Cd, Pb, Cr, Cu, Zn, Ni, As, and Hg progressively accumulate in sediments. Because heavy metals are persistent, non-degradable, and bioaccumulative, contaminated sediments can record historical watershed pollution while also releasing metals back into overlying water under hydrodynamic disturbance, pH and redox fluctuations, organic matter mineralization, benthic bioturbation, and dredging activities, thereby threatening aquatic ecosystem stability and human health. Using a global methodological framework with particular emphasis on Chinese river basins, this review systematically summarizes key issues in the study of heavy metal pollution in river sediments, including spatial–temporal distribution and operationally defined fractionation, pollution levels and ecological risk assessment, source apportionment, and remediation and management technologies. Current evidence indicates that heavy metal contamination in river sediments exhibits pronounced spatial heterogeneity and watershed-specific characteristics. Its distribution is jointly controlled by geological background, land use patterns, source input intensity, hydrodynamic conditions, sediment particle size composition, and organic matter content. Methodologically, the field has evolved from single total concentration monitoring and exceedance-based evaluation toward integrated assessment systems that combine total concentrations, operationally defined fractionation, bioavailability, ecological risk, health risk, and source contribution. The joint use of BCR sequential extraction, the geoaccumulation index (Igeo), the pollution load index (PLI), the potential ecological risk index (RI), the risk assessment code (RAC), sediment quality guidelines (SQGs), receptor models, isotope tracing, and machine learning has substantially improved pollution identification, risk zoning, and source apportionment. Overall, research on heavy metal pollution in river sediments has shifted from descriptive judgments of whether contamination exists toward mechanistic and management-oriented questions concerning pollution sources, risk evolution, and remediation strategies. However, important gaps remain in compound pollution transformation mechanisms, regional background values and evaluation benchmarks, uncertainty in model parameters, long-term dynamic monitoring, and engineering-scale verification of remediation technologies. Future studies should strengthen multi-media, multi-scale, and long-term monitoring and further integrate fractionation analysis, toxicological effects, source apportionment models, and remediation technologies to provide a scientific basis for watershed ecological security and precision management of contaminated sediments. Full article

With extremely low odor thresholds and potent flavor activity, sulfur-containing aroma compounds (SACs) constitute the molecular cornerstone of characteristic flavors in meat, coffee, and fermented foods. Research has advanced from early component identification to the elucidation of structure–activity relationships, olfactory receptor recognition mechanisms, and food-flavor improvement. This review first summarizes the detection and quantification methods for SACs, their distribution in foods, key odor contributions, and major formation pathways. It then highlights progress in understanding molecular structural parameters, olfactory receptor recognition, and computational simulations that decode flavor perception mechanisms. From a translational perspective, we further discuss flavor retention in real food matrices, off-flavor regulation, cross-modal perceptual enhancement, and functional applications. Current challenges include food matrix complexity, high compound reactivity, and nonlinear olfactory combinatorial coding. Future directions involve constructing a multiscale predictive framework integrating neuroscience, developing explainable artificial intelligence to decode olfactory coding, and advancing closed-loop green biomanufacturing for the precise design and sustainable production of SACs. Full article

Generative artificial intelligence (GenAI) has moved from an emerging educational tool to a structural challenge for science, technology, engineering, and mathematics (STEM) higher education. This narrative review argues that the most consequential effect of GenAI is not the automation of existing teaching practices but the need to redesign curricula, learning outcomes, pedagogies, and assessment around disciplinary judgment, critical verification, intellectual independence, and transparent, ethical use of GenAI. Its distinctive contribution is to frame GenAI as a problem of curriculum and assessment validity rather than primarily as a question of tool adoption or academic integrity. Because widely available systems can generate code, solve quantitative problems, summarize literature, draft laboratory reports, and produce fluent scientific prose, conventional submitted artifacts have become weaker indicators of the reasoning and competence they are intended to demonstrate. The review therefore examines the full programme-to-classroom pathway, connecting definitions of graduate competence with course design, classroom and laboratory practice, assessment, feedback, faculty capability, technology adoption, and iterative evaluation. The analysis integrates cognitive load theory, constructive alignment, constructivist perspectives, and frameworks of faculty capability and technology adoption. The biological sciences serve as a recurring disciplinary case because they combine conceptual knowledge, laboratory practice, computational analysis, and ethical decision-making, and are also being transformed by AI-based scientific methods. A worked cell biology example, structured using the Analysis, Design, Development, Implementation, and Evaluation model, operationalizes the review’s conceptual argument and demonstrates how GenAI integration can translate into needs analysis, outcome specification, resource development, blended laboratory implementation, assessment, and iterative redesign. The resulting design logic is generalized into a transferable five-step template for STEM curriculum redesign, with recommendations at programme, course, and institutional levels. Full article

Background/Objectives: Adolescent substance use and mental health problems frequently co-occur and share common risk and protective factors. Some school-based prevention programs address substance use and mental health within an integrated approach. However, the characteristics and intervention components of these integrated approaches remain insufficiently understood. This review aimed to describe the program characteristics of school-based integrated mental health and substance use prevention programs for adolescents that were evaluated in randomized or cluster randomized controlled trials (RCTs/cRCTs), with particular attention to their intervention components, delivery approaches and prevention strategies. Methods: This review used a structured approach comprising a systematic literature search, predefined eligibility criteria, independent study selection, standardized data extraction and coding, and descriptive synthesis. Electronic databases (PubMed, Embase, Cochrane Library, CINAHL, PsycINFO, KMbase, KoreaMed, ScienceON, DBpia, KISS, RISS, and PQDT) were searched for studies published between January 2016 and April 2026. Studies were eligible if they were randomized or cluster randomized controlled trials evaluating school-based interventions that incorporated both substance use prevention and mental health promotion components among adolescents. Data were extracted and synthesized descriptively at the program level to summarize program characteristics and intervention components. Results: Fifteen studies representing 10 unique programs were included. Mental health literacy was identified in 5 programs and emotional regulation in 4. Drug literacy and resistance skills were each identified in 6 programs, alcohol prevention in 5, and cannabis prevention in 4. A descriptive cross-domain analysis identified overlapping patterns involving literacy, self-regulation, help-seeking, social competence, peer support, and family-focused approaches rather than mutually exclusive program types. Conclusions: The school-based integrated prevention programs evaluated in randomized or cluster randomized controlled trials and included in this review combined substance use prevention with mental health promotion components, including psychosocial skill development, peer support, and, in one program, a family-focused approach. The descriptive synthesis of program characteristics provides an initial basis for understanding the diverse approaches used in integrated school-based prevention and may inform the future design and evaluation of programs targeting adolescent mental health and substance use. Full article

Essential thrombocythemia (ET) is a Ph(-) myeloproliferative neoplasm characterized by elevated platelet counts. Patients most often have one of the three following driver mutations: JAK2, MPL, or CALR. However, these mutations are not detected in approximately 10–15% of patients, who are thus referred to as “triple-negative” (TN). Background/Objectives: In recent years, there have been breakthroughs in the genetic diagnosis of hematological diseases and progress in understanding their epigenetic basis. Aim: This study aimed to review the available literature and systematize the current knowledge on the molecular abnormalities in essential thrombocythemia. Particular attention was paid to the impacts of genetic mutations and epigenetic changes—such as abnormalities in non-coding RNA expression, DNA methylation, and histone modifications—on disease development and their clinical significance in patients with essential thrombocythemia. The most important publications on genetic and epigenetic mechanisms in essential thrombocythemia were reviewed and summarized. Methods: A review of the available literature was conducted using selected online databases. Publications from 2003 to 2026 were considered, covering the diagnosis and classification criteria for essential thrombocythemia, its genetic and epigenetic basis, and the associated impacts on the disease course. Conclusions: Although understanding the precise roles of genetic and epigenetic abnormalities in essential thrombocythemia remains challenging, they offer many opportunities for use as new diagnostic biomarkers and for the development of novel targeted treatment options. Further research is needed to better understand the genetic and epigenetic changes occurring in ET. Full article

Biomolecular condensates are dynamic membraneless organelles composed of proteins and RNAs that assemble through multivalent interactions and provide cells with powerful means to regulate gene expression in space and time. Different epitranscriptomic marks such as m⁶A, m¹A, and m⁵C can reshape RNA structure—binding interfaces and multivalency and, in this manner, tuning which transcripts nucleate or partition into specific condensates and influencing their material state. This review summarizes how individual RNA modifications and their associated proteins regulate the formation and function of BMCs such as stress granules, P-bodies, nuclear bodies and disease-linked condensates in cancer and neurodegeneration. It highlights emerging concepts of combinatorial “epitranscriptomic codes” and bidirectional feedback between condensates and RNA-modifying enzymes and discusses the current experimental and technical gaps that still limit our understanding of modification crosstalk and condensate topology. Full article