Search Results (3,175)

Background/Objectives: Chemotherapy-induced neuropathic pain (CINP) represents a critical challenge in oncology, emerging as a common and debilitating side effect of widely used chemotherapeutic agents, such as paclitaxel (PTX). Current therapeutic interventions and preventive strategies for CINP are largely insufficient, as they fail to address the underlying peripheral nerve damage, highlighting an urgent need for the development of new drugs. This study aimed to investigate the dual-function effects on normal cell protection and tumor suppression of BMX-001, a redox-active manganese metalloporphyrin that has demonstrated antioxidant and anti-inflammatory properties, which offers potential in protecting central nervous system tissues and treating CINP. Methods: This study assessed BMX-001’s different roles in protecting normal cells while acting as a pro-oxidant and pro-inflammatory molecule in cancer cells in vitro. We also evaluated its neuroprotective effect in preclinical PTX-induced CINP models in vivo. Results: Our results showed significant reductions in mechanical and cold allodynia, decreased pro-inflammatory cytokine levels, and restored antioxidant capacity in peripheral nerves and dorsal root ganglia (DRGs) following BMX-001 treatment. Conclusions: Overall, our study highlights the therapeutic potential of BMX-001 to mitigate CINP and enhance anticancer efficiency. Its dual-selective mechanism supports the future clinical investigation of BMX-001 as a novel adjunct to chemotherapeutic regimens. Full article

Internet of Things (IoT)-based solar insecticidal lamps (SIL-IoTs) offer an eco-friendly alternative by merging solar energy harvesting with intelligent sensing, advancing sustainable smart agriculture. However, SIL-IoTs encounter practical challenges, e.g., hardware aging, electromagnetic interference, and abnormal data patterns. Therefore, developing an effective fault detection and diagnosis (FDD) system is essential. In this survey, we systematically identify and address the core challenges of implementing FDD of SIL-IoTs. Firstly, the fuzzy boundaries of sample features lead to complex feature interactions that increase the difficulty of accurate FDD. Secondly, the category imbalance in the fault samples limits the generalizability of the FDD models. Thirdly, models trained on single scenarios struggle to adapt to diverse and dynamic field conditions. To overcome these challenges, we propose a multi-level solution by discussing and merging existing FDD methods: (1) a data augmentation strategy can be adopted to improve model performance on small-sample datasets; (2) federated learning (FL) can be employed to enhance adaptability to heterogeneous environments, while transfer learning (TL) addresses data scarcity; and (3) deep learning techniques can be used to reduce dependence on labeled data; these methods provide a robust framework for intelligent and adaptive FDD of SIL-IoTs, supporting long-term reliability of IoT devices in smart agriculture. Full article

Wool has distinctive biological, physical, and chemical properties that contribute to its value both for the sheep and in global fibre and textile markets. Its fibres are primarily composed of proteins, principally keratin and keratin-associated proteins (KAPs). To better comprehend the genes that underpin key wool traits, this study examined the keratin-associated protein 36-1 gene (KRTAP36-1) in Chinese Tan lambs. We identified three previously reported alleles of the gene (named A, B and C) that were present in the lambs studied, with genotype frequencies as follows: 2.0% (n = 5; AA), 6.9% (n = 17; AB), 13.8% (n = 34; AC), 8.9% (n = 22; BB), 33.4% (n = 82; BC) and 35.0% (n = 86; CC). The frequencies of the individual alleles in the Chinese Tan lambs were 12.4%, 29.1% and 58.5% for alleles A, B and C, respectively. The three alleles were in Hardy–Weinberg Equilibrium. In an association analysis, it was revealed that allele C was associated with variation in the mean fibre curvature of the fine wool of the Chinese Tan lambs, but this association was not observed in their heterotypic hair fibres. This finding suggests that KRTAP36-1 might be differentially expressed in the wool follicles that produce the two fibre types, and that along with other KRTAP genes, it may be involved in determining fibre curvature and the distinctive curly coat of the lambs. Full article

Per- and polyfluoroalkyl substances (PFASs) have gained significant attention due to their widespread distribution in the environment and potential adverse health effects. While ingestion, especially through contaminated drinking water, is considered the primary route of human exposure, recent research suggests that other pathways, such as inhalation and dermal absorption, also play a significant role. This review provides a concise overview of the toxicological impacts of both legacy and emerging PFASs, such as GenX and perfluorobutane sulfonic acid (PFBS), with a particular focus on their effects on the liver, kidneys, and immune and nervous systems, based on findings from recent in vivo, in vitro, and epidemiological studies. Despite the transition to PFAS alternatives, much of the existing toxicity data focus on a few legacy compounds, such as perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS), which have been linked to adverse immune outcomes, particularly in children. However, evidence for carcinogenic risk remains limited to populations with extremely high exposure levels, and data on neurodevelopmental effects remain underexplored. While epidemiological and experimental animal studies supported these findings, significant knowledge gaps persist, especially regarding emerging PFASs. Therefore, this review examines the visceral, neural, and immunotoxicity data for emerging PFASs and mixtures from recent studies. Given the known risks from well-studied PFASs, a precautionary principle should be adopted to mitigate human health risks posed by this large and diverse group of chemicals. Full article

An unintended consequence of cystic fibrosis (CF) newborn screening (NBS) is the identification of infants with a positive NBS who do not meet the diagnostic criteria for CF (two CF-causing variants and/or sweat chloride > 60 mmol/L). This indeterminate diagnosis is called cystic fibrosis transmembrane conductance regulator (CFTR)-related metabolic syndrome (CRMS) or CF screen positive, inconclusive diagnosis (CFSPID). CRMS/CFSPID occurs when it is not clearly known whether CFTR variants are disease-causing. In 2024, the CFTR2 classification of many CFTR variants was changed from unknown significance to either CF-causing variants or variants of varying clinical consequences (VVCCs). We conducted a meta-analysis of CRMS/CFSPID cases from manuscripts to describe how the diagnoses would change using two different variant panels: (1) only CF-causing CFTR variants (Panel_CF-causing) and (2) CF-causing variants and VVCCs (Panel_{CF-causing+VVCCs}). Using the Panel_CF-causing, 8.7% had two CF-causing variants (reclassified as CF), while 91.3% had less than two CF-causing variants (reclassified as Undetected). Using the Panel_{CF-causing+VVCCs}, 51.4% had either two VVCCs or one VVCC with one CF-causing variant detected (reclassified as CRMS/CFSPD), 39.9% had less than two CF-causing variants detected (reclassified as Undetected), and 8.7% had two CF-causing variants (reclassified as CF). In conclusion, using the updated CFTR2 classification of CFTR variants significantly decreases the number of children with CRMS/CFSPID and gives a definitive diagnosis of CF to some children while not detecting as many children who are unlikely to develop CF. Full article

The American Cancer Society estimates that over 152,000 new cases of colorectal cancer (CRC) were diagnosed in 2024, with more than 105,000 cases affecting the colon and 46,000 involving the rectum. CRC remains the second leading cause of cancer-related deaths in the United States, with an estimated 53,010 deaths in 2024. In the era of precision medicine, which incorporates molecular and environmental information into clinical decision-making, identifying patients harboring a deficiency in Deoxyribonucleic acid (DNA) repair allowed for targeted immunotherapies and significantly reduced CRC-related mortality. A significant advancement in this domain is the application of liquid biopsy, which has emerged as a promising tool for prognostication, guiding therapy, and monitoring treatment response in CRC. This review aims to comprehensively explore the role of liquid biopsy in colorectal malignancies, describing its practical applications, prognostic significance, and potential to revolutionize CRC management in the future. At the end, we also aim to show a schematic representation of showing integration of Circulating Tumor (Ct) DNA in routine clinical management of CRC. The highlight of this article is the structured and evidence-based schematic framework and its integration into future practice. The schematic pathway is designed to optimize ctDNA utilization across various stages of colorectal cancer management. Full article

The popularity of bioactive compounds extracted from sea cucumbers is growing due to their wide application in the pharmaceutical industry, particularly in the development of drugs for neurological disorders. Different types of compounds, such as saponins, phenolic compounds, cerebrosides, and glucocerebrosides, are being studied intensively for their efficacy in assessing the treatment of neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, and brain tumors, among others. Positive results have been observed in the upregulation in the content of p-CREB, p-PL3K, BDNF, SOD, and MDA. Furthermore, the neuroprotective mechanism of the compounds against Alzheimer’s disease revealed that suppressing the phosphorylation of tau protein by the PI3K/Akt/GSK3β pathway leads to improved synaptic plasticity and reduced nerve fiber tangles. This comprehensive review explores recent findings on the therapeutic potential of sea cucumber bioactives in the treatment of brain-related disorders. Full article

(1) Medical training is changing, especially for surgeons. Virtual reality simulation is an excellent way to train surgeons safely. Studies show that surgeons who train with simulation have demonstrated improved technical skills in fundamental surgical procedures. The purpose of this study is to determine the overall impact of virtual reality training on laparoscopic cholecystectomy performance and to explore whether specific training protocols or the addition of feedback confer any advantages for future surgeons. (2) MEDLINE (PubMed), Embase (Ovid SP), Web of Science, Google Scholar, and Scopus were searched for the literature related to virtual reality training, immersive simulation, laparoscopic surgical skills training, and medical education. Study quality was assessed using the Cochrane Risk of Bias Tool and NIH Quality Assessment Tool. (3) A total of 55 full-text articles were reviewed. Meta-analysis showed that virtual reality training is an effective method for learning cholecystectomy surgical skills. (4) Conclusions: Performance, measured by objective structured assessments and time to task completion, is improved with virtual reality training compared with no additional training. Positive effects of simulation training were evident in global rating scores and operative time. Continuous feedback on movement parameters during laparoscopic cholecystectomy skills training impacts skills acquisition and long-term retention. Full article

This study aimed to evaluate cow longevity and identify the main culling reasons in dairy herds in Southern Brazil. Two data sets from 26 predominantly confined Holstein herds were analyzed over a 10-year period (2007–2016). The first included 11,150 cows that were culled, died, or sold, and the second comprised 636,739 cows for demographic analysis. The average annual culling rate was 24.2%, mainly due to reproductive disorders (34.0%), mastitis/high somatic cell count (20.4%), and feet and leg problems (17.9%). Involuntary causes represented 89.5% of all culling. The death rate averaged 3.8%, with the most frequent causes being unknown (27.3%), other reasons (25.6%), tick fever (10.2%), and accidents/injuries (10.0%). Larger herds had higher culling rates than smaller ones (26.2% vs. 22.8%; p = 0.04), as did higher-producing herds compared to lower-producing ones (25.7% vs. 22.0%; p = 0.02). Cows with ≥5 calvings were culled more often (p < 0.01) than those in earlier lactations. Culling was lowest (p < 0.02) in spring and highest (p < 0.01) during early (0–60 d) and late (>420 d) lactation. Herds with a higher proportion of older cows had slightly lower milk yields (p < 0.01), indicating longevity does not always enhance productivity. Full article

Spodoptera eridania (Stoll, 1781) (Lepidoptera: Noctuidae) is an important pest with a broad host range and growing relevance due to its high dispersal capacity, recent invasions into Africa and Asia, and documented resistance to biological insecticides. Here, we assessed S. eridania flight phenology and seasonal dynamics in the Florida Panhandle, using pheromone trapping data to evaluate population trends and environmental drivers. Moths were collected year-round, showing consistent patterns across six consecutive years, including two distinct annual flight peaks: an early crop season flight around March, and a more prominent flight peak during September–October. Moth abundance followed a negative quadratic relationship with temperature, with peak activity occurring between 15 °C and 26 °C. No significant relationship was found with precipitation or wind. These results underscore the strong influence of abiotic factors, particularly temperature, on seasonal abundance patterns of this species. Our findings offer key insights by identifying predictable periods of high pest pressure and the environmental conditions that drive population increases. Understanding the flight phenology and behavior of this species provides an ultimate contribution to the development of effective IPM and insect resistance management (IRM) programs, promoting the development of forecasting tools for more effective, timely pest management interventions. Full article

Improving curriculum structure is critical for enhancing student success and on-time graduation, yet few methods exist to evaluate how prerequisite paths shape student progression and graduation outcomes. This study proposes a data-driven, graph-based framework that integrates course prerequisite networks with student performance data to systematically analyze curricular structure and student outcomes. We identify high-risk courses by jointly modeling their structural importance and pass rates, and quantify the time and survivability of different prerequisite paths using probabilistic models. Additionally, we introduced grade transition patterns to capture more nuanced transitions in student performance and pinpoint bottlenecks along prerequisite paths. Applying the model on four science and engineering majors from a public institution, the results not only identify high-risk courses often missed in conventional analyses, but also reveal path-level disparities and structural bottlenecks that affect student progression and time to graduation. For example, in the Computer Science major, we identified that the architecture and operating systems pathway is more challenging than the software engineering pathway. A closer examination of the course pairs along this trajectory revealed that the difficulty stems from a significant drop in student performance between a prerequisite–successor course pairs.This type of analysis fills a gap in conventional curriculum studies, which often overlook path-level dynamics, and offers actionable insights for educators a to identify high risk curricular components. Full article

This paper shows that artificial intelligence is fundamentally transforming college curricula by enabling data-driven personalization, which enhances student outcomes and better aligns educational programs with evolving workforce demands. Specifically, predictive analytics, machine learning algorithms, and natural language processing were applied here, grounded in constructivist learning theory and Human–Computer Interaction principles, to evaluate student performance and identify at-risk students to propose personalized learning pathways. Results indicated that the AI-based curriculum achieved much higher course completion rates (89.72%) as well as retention (91.44%) and dropout rates (4.98%) compared to the traditional model. Sentiment analysis of learner feedback showed a more positive learning experience, while regression and ANOVA analyses proved the impact of AI on enhancing academic performance to be real. Therefore, the learning content delivery for each student was continuously improved based on individual learner characteristics and industry trends by AI-enabled recommender systems and adaptive learning models. Its advantages notwithstanding, the study emphasizes the need to address ethical concerns, ensure data privacy safeguards, and mitigate algorithmic bias before an equitable outcome can be claimed. These findings can inform institutions aspiring to adopt AI-driven models for curriculum innovation to build a more dynamic, responsive, and learner-centered educational ecosystem. Full article

Background: Protein kinase R (PKR) inhibits general mRNA translation by phosphorylating the alpha subunit of eukaryotic translation initiation factor 2 (eIF2). PKR also modulates NF-κB signaling during viral infections, but comparative studies of PKR-mediated NF-κB responses across mammalian species and their regulation by viral inhibitors remain largely unexplored. This study aimed to characterize the conserved antiviral and inflammatory roles of mammalian PKR orthologs and investigate their modulation by poxviral inhibitors. Methods: Using reporter gene assays and quantitative RT-PCR, we assessed the impact of 17 mammalian PKR orthologs on general translation inhibition, stress-responsive translation, and NF-κB-dependent induction of target genes. Congenic human and rabbit cell lines infected with a myxoma virus strain lacking PKR inhibitors were used to compare the effects of human and rabbit PKR on viral replication and inflammatory responses. Site-directed mutagenesis was employed to determine key residues responsible for differential sensitivity to the viral inhibitor M156. Results: All 17 mammalian PKR orthologs significantly inhibited general translation, strongly activated stress-responsive ATF4 translation, and robustly induced NF-κB target genes. Inhibition of these responses was specifically mediated by poxviral K3 orthologs that effectively suppressed PKR activation. Comparative analyses showed human and rabbit PKRs similarly inhibited virus replication and induced cytokine transcripts. Amino acid swaps between rabbit PKRs reversed their sensitivity to viral inhibitor M156 and NF-κB activation. Conclusions: Our data show that the tested PKR orthologs exhibit conserved dual antiviral and inflammatory regulatory roles, which can be antagonized by poxviral K3 orthologs that exploit eIF2α mimicry to modulate the PKR-NF-κB axis. 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

Cyanobacteria (also called blue-green algae)-based dietary supplements are commonplace, but cyanobacteria-enhanced foods, such as spirulina crackers, are just appearing on New Zealand supermarket shelves. While much research has been devoted to consumer attitudes towards macro-algae-based products, little research has been devoted to micro-algae-based or cyanobacteria-enhanced consumer products. The current study, following the Capability–Opportunity–Motivation to Behaviour theory, examines likely consumer drivers of favouring or disfavouring spirulina crackers. These drivers include food neophilia, food neophobia, perception of sustainability and health-related product attributes, involvement with algae and an exploratory driver, snacking behaviour. Fully supported drivers (related to increased favour and decreased disfavour) included food neophilia and perception of sustainability and health-related product attributes. Algae involvement was only related to increased favour, and food neophobia was not supported. Surprisingly, snacking behaviour was related to increased disfavour of spirulina crackers. Both theoretical and managerial implications are offered. Full article