Search Results (11,042)

Plastic debris is a pervasive and persistent threat to marine ecosystems. Microplastics (plastics < 5 mm) are increasing in a variety of marine habitats, including open water systems, shorelines, and benthic sediments. It remains unclear how microplastics distribute and accumulate in marine systems and the extent to which this pollutant is accessible to marine taxa. We examined subtidal benthic sediments and beach sediments in critical nearshore habitats for forage fish species—Pacific sand lance (Ammodytes personatus), Pacific herring (Clupea pallasi), and surf smelt (Hypomesus pretiosus)—to quantify microplastic concentrations in the spawning and deep-water habitats of these fish and better understand how microplastics accumulate and distribute in nearshore systems. In the San Juan Islands, we examined an offshore subtidal bedform in a high-flow channel and beach sites of protected and exposed shorelines. We also examined 12 beach sites proximate to urban areas in Puget Sound. Microplastics were found in all samples and at all sample sites. Microfibers were the most abundant, and flakes were present proximate to major shipyards and marinas. Microplastics were significantly elevated in Puget Sound compared to the San Juan Archipelago. Protected beaches had elevated concentrations relative to exposed beaches and subtidal sediments. Microplastics were in higher concentrations in sand and fine-grain sediments, poorly sorted sediments, and artificial sediments. Microplastics were also elevated at sites confirmed as spawning habitats for forage fish. The model results indicate that both current speed and proximate urban populations influence nearshore microplastic concentrations. Our research provides new insights into how microplastics are distributed, deposited, and retained in marine sediments and shorelines, as well as insight into potential exposure in benthic, demersal, and shoreline habitats. Further analyses are required to examine the relative influence of urban populations and shipping lanes and the effects of physical processes such as wave exposure, tidal currents, and shoreline geometry. Full article

This article investigates the revolutionary potential of AI-powered virtual assistants in augmented reality (AR) and virtual reality (VR) environments, concentrating primarily on their impact on special needs schooling. We investigate the complex characteristics of these virtual assistants, the influential elements affecting their development and implementation, and the joint efforts of educational institutions and technology developers, using a rigorous quantitative approach. Our research also looks at strategic initiatives aimed at effectively integrating AI into educational practices, addressing critical issues including infrastructure, teacher preparedness, equitable access, and ethical considerations. Our findings highlight the promise of AI technology, emphasizing the ability of AI-powered virtual assistants to provide individualized, immersive learning experiences adapted to the different needs of students with special needs. Furthermore, we find strong relationships between these virtual assistants’ features and deployment tactics and their subsequent impact on educational achievements. This study contributes to the increasing conversation on harnessing cutting-edge technology to improve educational results for all learners by synthesizing current research and employing a strong methodological framework. Our analysis not only highlights the promise of AI in increasing student engagement and comprehension but also emphasizes the importance of tackling ethical and infrastructure concerns to enable responsible and fair adoption. Full article

Drug repurposing or drug repositioning is the process of identifying new therapeutic uses for approved or investigational drugs beyond the original treatment indication. The discovery of new drugs for cancer therapy needs this cost-effective and time-saving alternative strategy to traditional drug development for a rapid clinical translation in Phase II/III studies, especially for unmet medical needs and rare diseases. Neuroendocrine tumors (NETs) are a heterogeneous group of rare neoplasms arising from cells of the neuroendocrine system that, though often indolent, can be aggressive and metastatic. In this context, drug repurposing has emerged as a promising strategy to improve treatment options due to the limited number of effective treatments and the heterogeneity of the disease. Indeed, a large number of non-oncology drugs have the potential to address more than one target that could be therapeutic for cancer patients. Although many repurposed drugs are used off-label, efficacy for the new use must be demonstrated in clinical trials. Within regulatory frameworks, both the Food and Drug Administration (FDA) and the European Medicines Agency (EMA) have procedures to reduce the need for extensive new studies and to expedite the review of drugs for serious conditions when preliminary evidence indicates substantial clinical improvement over available therapy. In spite of several advantages, including reduced development time, lower costs, known safety profiles, and faster regulatory approval, difficulty in obtaining new patents for old drugs with limited protection for intellectual property may reduce commercial returns and disincentivize investments. This review aims to provide comprehensive information on some marketed drugs currently under investigation to be repurposed or used in clinical practice for NETs and to discuss the major clinical challenges. Although drug repurposing is a useful strategy for early access to medicines, the monitoring of the clinical benefit of oncologic drugs during the post-marketing authorization is crucial to support the safety and effectiveness of treatments. Full article

Anchote (Coccinia abyssinica) is a neglected high-potential food and nutrition security tuber crop in Ethiopia. Phenotyping core germplasm collections using agro-morphological and physiological markers is essential for effective crop improvement and utilization. A total of 282 anchote germplasms were profiled using six qualitative and twenty-six quantitative agro-morphological and physiological traits. Augmented Block Design was used for the experiment at the Debre Zeit Agricultural Research Center. The chi-square test and Shannon diversity index indicated the presence of substantial phenotypic variation and diversity among the accessions based on the predominant qualitative traits studied. The quantitative agro-morphological and physiological traits showed wider variability and ranges for the accessions. The broad-sense heritability and genetic advance as a percentage of the mean were notably high for quantitative traits such as root yield, vine length, and leaf area index. A significantly positive correlation was observed among agronomically important traits such as root yield and root diameter as well as root yield and leaf area. The principal component analysis for qualitative and quantitative traits found that ten components explained 72.2% of the variation for qualitative traits, whereas nine components accounted for 69.96% of the variation in quantitative traits. The primary contributors to the variations are traits such as root (shape, flesh color, and yield), leaf (color, length, diameter, area) and fruit (length, diameter, and weight). Further, the accessions were grouped into two and three clusters based on qualitative and quantitative traits, respectively, indicating that quantitative characters better differentiated among the accessions. Similarly, the tanglegram showed little similarity between the qualitative and quantitative agro-morphological and physiological traits in clustering the accessions. These findings indicate the presence of sizable trait variation among the accessions that can be exploited as a selection marker to design and facilitate conservation and breeding strategies of anchote. Full article

Obesity is a growing global health concern with widespread impacts on physical, psychological, and social well-being. Clinically, it is a major driver of type 2 diabetes (T2D), cardiovascular disease (CVD), non-alcoholic fatty liver disease (NAFLD), and cancer, reducing life expectancy by 5–20 years and imposing a staggering economic burden of USD 2 trillion annually (2.8% of global GDP). Despite its significant health and socioeconomic impact, earlier obesity medications, such as fenfluramine, sibutramine, and orlistat, fell short of expectations due to limited effectiveness, serious side effects including valvular heart disease and gastrointestinal issues, and high rates of treatment discontinuation. The advent of glucagon-like peptide-1 (GLP-1) receptor agonists (e.g., semaglutide, tirzepatide) has revolutionized obesity management. These agents demonstrate unprecedented efficacy, achieving 15–25% mean weight loss in clinical trials, alongside reducing major adverse cardiovascular events by 20% and T2D incidence by 72%. Emerging therapies, including oral GLP-1 agonists and triple-receptor agonists (e.g., retatrutide), promise enhanced tolerability and muscle preservation, potentially bridging the efficacy gap with bariatric surgery. However, challenges persist. High costs, supply shortages, and unequal access pose significant barriers to the widespread implementation of obesity treatment, particularly in low-resource settings. Gastrointestinal side effects and long-term safety concerns require close monitoring, while weight regain after medication discontinuation emphasizes the need for ongoing adherence and lifestyle support. This review highlights the transformative potential of incretin-based therapies while advocating for policy reforms to address cost barriers, equitable access, and preventive strategies. Future research must prioritize long-term cardiovascular outcome trials and mitigate emerging risks, such as sarcopenia and joint degeneration. A multidisciplinary approach combining pharmacotherapy, behavioral interventions, and systemic policy changes is critical to curbing the obesity epidemic and its downstream consequences. Full article

With the increasing scale of industrial devices and the growing complexity of multi-source heterogeneous sensor data, traditional methods struggle to address challenges in fault detection, data security, and trustworthiness. Ensuring tamper-proof data storage and improving prediction accuracy for imbalanced anomaly detection for potential deployment in the Industrial Internet of Things (IIoT) remain critical issues. This study proposes a blockchain-powered Long Short-Term Memory Network (LSTM)–Attention hybrid model: an LSTM-based Encoder–Attention–Decoder (LEAD) for industrial device anomaly detection. The model utilizes an encoder–attention–decoder architecture for processing multivariate time series data generated by industrial sensors and smart contracts for automated on-chain data verification and tampering alerts. Experiments on real-world datasets demonstrate that the LEAD achieves an $F_{0.1}$ score of 0.96, outperforming baseline models (Recurrent Neural Network (RNN): 0.90; LSTM: 0.94; and Bi-directional LSTM (Bi-LSTM, 0.94)). We simulate the system using a private FISCO-BCOS network with a multi-node setup to demonstrate contract execution, anomaly data upload, and tamper alert triggering. The blockchain system successfully detects unauthorized access and data tampering, offering a scalable solution for device monitoring. Full article

Background/Objectives: Although MRI with fat-suppression sequences is the gold standard for diagnosis of bone marrow edema (BME), Dual-Layer Spectral CT (DL-SCT) with electron density (ED) provides a viable alternative, particularly in situations where an MRI is not accessible. Using MRI as the reference standard, this study analyzed how DL-SCT with ED reconstructions may be a valid alternative in the detection of BME. Methods: This retrospective study included 28 patients with a suspected diagnosis of BME via MRI conducted between March and September 2024. Patients underwent DL-SCT using ED reconstructions obtained through IntelliSpace software v. 12.1. Images were evaluated by two experienced radiologists and one young radiologist in a blinded way, giving a grade from 0 to 3 to classify BME (0 absence; 1 mild; 2 moderate; 3 severe). To reduce the recall bias effect, the order of image evaluations was set differently for each reader. p-Values were considered significant when <0.05. Fleiss’ Kappa was used to assess inter-rater reliability: agreement was considered poor for k < 0; slight for k 0.01–0.20; fair for 0.21–0.40; moderate for 0.41–0.60; substantial for 0.61–0.80; and almost perfect for 0.81–1.00. Results: All the readers detected the presence or absence of BME using DL-SCT. Inter-rater reliability for grade 0 resulted in 1 (p-value < 0.001); for grade 1: 0.21 (p-value < 0.001); for grade 2: 0.197 (p-value < 0.001); and for grade 3: 0.515 (p-value < 0.001). Conclusions: ED reconstructions allowed the identification of BME presence or absence in all analyzed cases, thus suggesting DL-SCT as a potentially effective method for its detection. Full article

The ongoing genetic erosion of natural Prunus armeniaca populations in their native habitats underscores the urgent need for targeted conservation and restoration strategies. This study provides the first comprehensive characterization of P. armeniaca populations in the Almaty region of Kazakhstan, integrating morphological descriptors (46 parameters), molecular markers, geobotanical, and remote sensing analyses. Geobotanical and remote sensing analyses enhanced understanding of accession distribution, geological features, and ecosystem health across sites, while also revealing their vulnerability to various biotic and abiotic threats. Of 111 morphologically classified accessions, 54 were analyzed with 13 simple sequence repeat (SSR) markers and four DNA barcoding regions. Our findings demonstrate the necessity of integrated morphological and molecular analyses to differentiate closely related accessions. Genetic analysis identified 11 distinct populations with high heterozygosity and substantial genetic variability. Eight populations exhibited 100% polymorphism, indicating their potential as sources of adaptive genetic diversity. Cluster analysis grouped populations into three geographic clusters, suggesting limited gene flow across Gorges (features of a mountainous landscape) and greater connectivity within them. These findings underscore the need for site-specific conservation strategies, especially for genetically distinct, isolated populations with unique allelic profiles. This study provides a valuable foundation for prioritizing conservation targets, confirming genetic redundancies, and preserving genetic uniqueness to enhance the efficiency and effectiveness of the future conservation and use of P. armeniaca genetic resources in the region. Full article

Background/Objectives: The RTK-RAS signaling cascade is a central axis in colorectal cancer (CRC) pathogenesis, governing cellular proliferation, survival, and therapeutic resistance. Somatic alterations in key pathway genes—including KRAS, NRAS, BRAF, and EGFR—are pivotal to clinical decision-making in precision oncology. However, the integration of these genomic events with clinical and demographic data remains hindered by fragmented resources and a lack of accessible analytical frameworks. To address this challenge, we developed AI-HOPE-RTK-RAS, a domain-specialized conversational artificial intelligence (AI) system designed to enable natural language-based, integrative analysis of RTK-RAS pathway alterations in CRC. Methods: AI-HOPE-RTK-RAS employs a modular architecture combining large language models (LLMs), a natural language-to-code translation engine, and a backend analytics pipeline operating on harmonized multi-dimensional datasets from cBioPortal. Unlike general-purpose AI platforms, this system is purpose-built for real-time exploration of RTK-RAS biology within CRC cohorts. The platform supports mutation frequency profiling, odds ratio testing, survival modeling, and stratified analyses across clinical, genomic, and demographic parameters. Validation included reproduction of known mutation trends and exploratory evaluation of co-alterations, therapy response, and ancestry-specific mutation patterns. Results: AI-HOPE-RTK-RAS enabled rapid, dialogue-driven interrogation of CRC datasets, confirming established patterns and revealing novel associations with translational relevance. Among early-onset CRC (EOCRC) patients, the prevalence of RTK-RAS alterations was significantly lower compared to late-onset disease (67.97% vs. 79.9%; OR = 0.534, p = 0.014), suggesting the involvement of alternative oncogenic drivers. In KRAS-mutant patients receiving Bevacizumab, early-stage disease (Stages I–III) was associated with superior overall survival relative to Stage IV (p = 0.0004). In contrast, BRAF-mutant tumors with microsatellite-stable (MSS) status displayed poorer prognosis despite higher chemotherapy exposure (OR = 7.226, p < 0.001; p = 0.0000). Among EOCRC patients treated with FOLFOX, RTK-RAS alterations were linked to worse outcomes (p = 0.0262). The system also identified ancestry-enriched noncanonical mutations—including CBL, MAPK3, and NF1—with NF1 mutations significantly associated with improved prognosis (p = 1 × 10⁻⁵). Conclusions: AI-HOPE-RTK-RAS exemplifies a new class of conversational AI platforms tailored to precision oncology, enabling integrative, real-time analysis of clinically and biologically complex questions. Its ability to uncover both canonical and ancestry-specific patterns in RTK-RAS dysregulation—especially in EOCRC and populations with disproportionate health burdens—underscores its utility in advancing equitable, personalized cancer care. This work demonstrates the translational potential of domain-optimized AI tools to accelerate biomarker discovery, support therapeutic stratification, and democratize access to multi-omic analysis. Full article

Background/objectives: The increasing prevalence of multidrug-resistant (MDR) bacteria, particularly Klebsiella pneumoniae, calls for the development of new antimicrobial agents. This study investigates a series of fluorinated azolium salts and their rhodium(I) complexes for antibacterial activity against clinical and reference strains of K. pneumoniae. Methods: Eleven fluorinated azolium salts and their corresponding Rh(I) complexes (22 compounds total) were synthesized and tested against several K. pneumoniae strains, including three MDR clinical isolates (U–13685, H–9871, U–13815) and ATCC reference strains. Minimum inhibitory concentrations (MICs) were determined. In silico ADMET analyses were conducted to evaluate intestinal absorption, oral bioavailability, Caco-2 permeability, carcinogenicity, solubility, and synthetic accessibility. Results: Among the Rh(I) complexes, Rh–1, Rh–3, and Rh–11 showed activity against the three MDR isolates (MIC = 62.5–250 µg/mL), while Rh–1, Rh–4, Rh–6, and Rh–11 were active against all ATCC strains (MIC = 3.9–250 µg/mL). The corresponding azolium salts displayed weak or no activity, highlighting the critical role of the metal center. ADMET predictions indicated that most Rh complexes had good intestinal absorption, and all except Rh–3, Rh–4, and Rh–9 were predicted to be orally bioavailable. Compounds Rh–1 to Rh–7 showed Caco-2 permeability, and all were classified as non-carcinogenic. Rh–8 to Rh–11 exhibited lower solubility and synthetic accessibility. Conclusions: The results underscore the potential of fluorinated Rh(I) complexes as antibacterial agents against MDR K. pneumoniae, with Rh–1 and Rh–11 emerging as promising leads based on activity and favorable predicted pharmacokinetics. Full article

Measuring methane (CH₄) emissions from dairy systems is crucial for advancing sustainable agricultural practices aimed at mitigating climate change. However, current CH₄ measurement techniques are primarily designed for controlled research settings and are not readily scalable to diverse production environments. Thus, there is a need to develop accessible, production-level methods for estimating CH₄ emissions. This review examines the relationship between enteric CH₄ emissions and milk fatty acid (FA) composition, highlights key FA groups with potential as biomarkers for indirect CH₄ estimation, and outlines critical factors of predictive model development. Several milk FAs exhibit strong and consistent correlations to CH₄ emissions, supporting their utility as predictive biomarkers. Saturated and branched-chain FAs are generally positively associated with CH₄ emissions, while unsaturated FAs, including linolenic acid, conjugated linoleic acids, and odd-chain FAs, are typically negatively associated. Variability in the strength and direction of correlations across studies is often attributable to differences in diet or lactation stage. Similarly, differences in experimental design, data processing, and model development contribute to much of the variation observed in predictive equations across studies. Future research should aim to (1) identify milk FAs that consistently correlate with CH₄ emissions regardless of diet, (2) develop robust and standardized prediction models, and (3) prioritize the external validation of prediction models across herds and production systems. Full article

Background/Objectives: Syphilis, a re-emerging global public health issue, has shown increasing incidence over the past decade, particularly among key populations such as men who have sex with men (MSM), people living with HIV, and pregnant women. This narrative review aimed to synthesize global epidemiological trends of syphilis from 2015 to 2025, with a focus on surveillance gaps, regional disparities, and structural determinants. Methods: A broad narrative approach was used to collect and analyze epidemiological data from 2015 to 2025. The literature was retrieved from databases (PubMed, Scopus) and official reports from the WHO, CDC, and ECDC. Included materials span observational studies, surveillance reports, and modeling data relevant to global trends and public health responses. Results: Globally, syphilis incidence has increased, with notable surges in North America, Europe, and Asia. MSM remain disproportionately affected, while congenital syphilis is resurging even in high-income countries. Low- and middle-income countries report persistent burdens, especially among women of reproductive age, often exacerbated by limited screening and surveillance infrastructure. The COVID-19 pandemic disrupted syphilis-related services and further exacerbated underreporting, hindering timely detection and response efforts. Surveillance systems vary widely in their completeness and quality, which significantly hinders global data comparability and coordinated public health responses. Conclusions: Despite its curability, syphilis continues to spread due to fragmented prevention strategies, inequities in access to care, and insufficient surveillance. Strengthening diagnostic access, integrating prevention efforts into broader health systems, and addressing social determinants are essential. Improved surveillance, equitable access, and innovation—including diagnostics and potential vaccine research—are critical to controlling the global syphilis epidemic. Full article

With a rapidly growing incidence and prevalence, Alzheimer’s disease (AD) is rapidly becoming one of the most disabling, lethal, and expensive diseases of the century. To diagnose AD as early as possible, the scientific world struggles to find reliable and non-invasive biomarkers that could predict the conversion of mild cognitive impairment to AD and delineate the ongoing pathogenic vicious pathways to be targeted with therapy. Research supports the use of blood biomarkers, such as Aβ_1-42/Aβ_1-40 ratio, phosphorylated tau181, and p-tau217 for diagnostic purposes, although the cut-offs are not clearly established and can depend on the assays used. For more accurate diagnosis, markers of neurodegeneration (neurofilament light) and neuroinflammation (glial fibrillary acidic protein) could be introduced in the biomarker panel. The recent approval of the Lumipulse G p-tau217/Aβ_1-42 plasma ratio by the FDA for the early detection of amyloid plaques associated with Alzheimer’s disease in adult patients, aged 55 years and older, exhibiting signs and symptoms of the disease represents a significant advancement in the diagnosis of Alzheimer’s disease, offering a more accessible and less invasive way to diagnose this devastating disease and allow potentially earlier access to treatment options. Full article

Background: Second-generation androgen receptor signaling inhibitors are one of the main treatment options in metastatic castration-resistant prostate cancer (mCRPC). Nonetheless, a considerable proportion show limited response to treatment, which indicates the need for convenient, easily accessible predictor biomarkers, a role suited for liquid biopsy. Methods: We conducted a PRISMA-compliant systematic review of four databases (Embase, Medline, Scopus, Web of Science) to identify all studies (observational studies and clinical trials) investigating cell-free DNA, circulating tumor cells, exosomes, and circulating RNAs as prognostic markers in metastatic castration-resistant patients starting androgen receptor signaling inhibitors. We excluded studies that evaluated combination therapies, rare histological subtypes or included nonmetastatic or castrate-sensitive disease. We also evaluated whether published papers followed reporting guidelines (REMARK, STROBE, or CONSORT for abstracts). Results: We identified a total of 123 reports, from which we identified only a few well-studied and consistent biomarkers: androgen receptor overexpression/copy number gain and splice variant 7, as well as disease burden markers (circulating tumor DNA fraction and circulating tumor cell concentration). Alterations or copy number loss in tumor suppressors PTEN, RB1, and TP53 were second in terms of quantity and consistency of evidence. However, a large majority of identified biomarkers were relatively understudied or inconsistent. We identified two potential vulnerabilities: inconsistent adherence to reporting guidelines and the under-inclusion of patients of non-Western European ancestry. Conclusions: A large number of biomarkers were linked to worse outcomes in prostate cancer; nonetheless, in most cases, the evidence is limited or inconsistent, or even contradictory. The main exceptions pertain to androgen receptor signaling and disease burden, and, to a smaller extent, to certain tumor suppressor genes. Further studies are needed to confirm their clinical utility, using clear and consistent methodologies and including patients from currently understudied populations. Full article

Traditional type I sourdoughs are being rediscovered and increasingly used in artisanal and industrial bakeries due to the unique taste and texture, potential health benefits, and longer shelf life they confer on to baked products. These unique properties are attributed to the diverse microbial communities of sourdough, comprising both yeasts and bacteria. The traditional preservation method for type I sourdough (i.e., continuous backslopping) may lead, over time, to taxonomic and functional rearrangements of its microbial communities. Consequently, significant deviations in the characteristics of baked products can occur. In this context, this review aims to summarize the recent literature on the long-term preservation and maintenance strategies for type I sourdough and highlight the essential role that microbial biological resource centers (mBRCs) could play in the preservation and sharing of sourdough microbiomes. Specifically, the identification of appropriate preservation methods, implementation of well-defined access and benefit-sharing protocols, and development of microbiome-specific datasets, should be encouraged within the context of mBRCs. These infrastructures are expected to play a pivotal role in preserving the microbiota of fermented foods, serving as a crucial element for innovation and the safeguarding of traditional foods and culinary heritage. Full article