Search Results (2,435)

The seasonal patterns of viral diseases in farm animals present significant challenges to global livestock productivity, with cold stress emerging as a potential modulator of host–pathogen interactions. This review synthesizes current knowledge on the expression dynamics of heat shock protein 70 (HSP70) in farm animals under cold-stress conditions and its potential roles as (1) a viral replication facilitator and (2) an immune response regulator. This review highlights cold-induced HSP70 overexpression in essential organs, as well as its effects on significant virus life cycles, such as porcine epidemic diarrhea virus (PEDV), porcine reproductive and respiratory syndrome virus (PRRSV), and bovine viral diarrhea virus (BVDV), through processes like viral protein chaperoning, replication complex stabilization, and host defense modulation. By integrating insights from thermophysiology, virology, and immunology, we suggest that HSP70 serves as a crucial link between environmental stress and viral disease seasonality. We also discuss translational opportunities targeting HSP70 pathways to break the cycle of seasonal outbreaks, while addressing key knowledge gaps requiring further investigation. This article provides a framework for understanding climate-driven disease patterns and developing seasonally adjusted intervention strategies. Full article

Antimicrobial resistance (AMR) has emerged as one of the most pressing global health challenges of our time. Alarming projections of increasing mortality from resistant infections highlight the urgent need for innovative solutions. While many candidates have shown promise in preliminary studies, they often encounter challenges in terms of efficacy and safety during clinical translation. This review examines cutting-edge approaches to combat AMR, with a focus on engineered antimicrobial peptides, functionalized nanoparticles, and advanced genomic therapies, including Clustered Regularly Interspaced Short Palindromic Repeats-associated proteins (CRISPR-Cas systems) and phage therapy. Recent advancements in these fields are critically analyzed, with a focus on their mechanisms of action, therapeutic potential, and current limitations. Emphasis is given to strategies targeting biofilm disruption and quorum sensing interference, which address key mechanisms of resistance. By synthesizing current knowledge, this work provides researchers with a comprehensive framework for developing next-generation antimicrobials, highlighting the most promising approaches for overcoming AMR through rational drug design and targeted therapies. Ultimately, this review aims to bridge the gap between experimental innovation and clinical application, providing valuable insights for developing effective and resistance-proof antimicrobial agents. Full article

Natural products demonstrate potent immunomodulatory properties through checkpoint modulation, macrophage polarization, and T cell/natural killer (NK) cell activation. While cancer organoid-immune co-culture platforms enable physiologically relevant modeling of tumor–immune interactions, systematic investigation of natural product immunomodulation in these systems remains entirely unexplored. We conducted a comprehensive literature analysis examining natural products tested in cancer organoids, immunomodulatory mechanisms from traditional models, technical advances in organoid-immune co-cultures, and standardization requirements for clinical translation. Our analysis reveals a critical research gap: no published studies have investigated natural product-mediated immunomodulation using organoid-immune co-culture systems. Even though compounds like curcumin, resveratrol, and medicinal mushroom polysaccharides show extensive immunomodulatory effects in two-dimensional (2D) cultures, and organoid technology achieves high clinical correlation for drug response prediction, all existing organoid studies focus exclusively on direct cytotoxicity. Technical challenges include compound stability, limited matrix penetration requiring substantially higher concentrations than 2D cultures, and maintaining functional immune populations in three-dimensional (3D) systems. The convergence of validated organoid-immune co-culture platforms, Food and Drug Administration (FDA) regulatory support through the Modernization Act 2.0, and extensive natural product knowledge creates unprecedented opportunities. Priority research directions include systematic screening of immunomodulatory natural products in organoid-immune co-cultures, development of 3D-optimized delivery systems, and clinical validation trials. Success requires moving beyond cytotoxicity-focused studies to investigate immunomodulatory mechanisms in physiologically relevant 3D systems, potentially unlocking new precision cancer immunotherapy approaches. Full article

Background/Objectives: BRIGHTLIGHT was the national evaluation of adolescent and young adult (AYA) cancer services in England. BRIGHTLIGHT results were not available when the most recent healthcare policy (NHSE service specifications for AYA Cancer) for AYA was drafted and therefore did not consider BRIGHTLIGHT findings and recommendations. We describe the co-development and delivery of a Policy Lab to expedite the implementation of the new service specification in the context of BRIGHTLIGHT results, examining the roles of multi-stakeholders to ensure service delivery is optimised to benefit AYA patients. We address the key question, “What is the roadmap for empowering different stakeholders to shape how the AYA service specifications are implemented?”. Methods: A 1-day face-to-face policy lab was facilitated, utilising a unique, user-centric engagement approach by bringing diverse AYA stakeholders together to co-design strategies to translate BRIGHTLIGHT evidence into policy and impact. This was accompanied by an online workshop and prioritisation survey, individual interviews, and an AYA patient workshop. Workshop outputs were analysed thematically and survey data quantitatively. Results: Eighteen professionals and five AYAs attended the face-to-face Policy Lab, 16 surveys were completed, 13 attended the online workshop, three professionals were interviewed, and three AYAs attended the patient workshop. The Policy Lab generated eight national and six local recommendations, which were prioritised into three national priorities: 1. Launching the service specification supported by compelling communication; 2. Harnessing the ideas of young people; and 3. Evaluation of AYA patient outcomes/experiences and establishing a national dashboard of AYA cancer network performance. An animation was created by AYAs to inform local hospitals what matters to them most in the service specification. Conclusions: Policy and research evidence are not always aligned, so when emerging evidence does not support current guidance, further exploration is required. We have shown through multi-stakeholder involvement including young people that it was possible to gain a different interpretation based on current knowledge and context. This additional insight enabled practical recommendations to be identified to support the implementation of the service specification. Full article

The environmental detriments of the growing global production and overconsumption of beef, including greenhouse gas emissions, deforestation, and biodiversity loss, are well-documented. However, public awareness of how dietary choices affect the environment remains limited. This study examines sustainability views on beef consumption and the potential for behavioral change as a step toward more sustainable intake levels. An observational web-based survey was conducted (n = 1367) to assess respondents’ current beef intake frequency, views on beef consumption related to planetary health, tropical deforestation, greenhouse gas emissions, and climate change, and willingness to modify beef consumption behavior. Chi-square tests were used for group comparisons, and weighted average scores were applied to rank levels of resistance to reducing beef intake. Environmental concern related to beef consumption was associated with greater beef cutback intentions and lower long-term intake reduction resistance amongst beef eaters. Beef eaters who strongly agreed that global beef consumption negatively impacts the environment were considerably more likely to express intentions to reduce their long-term beef intake compared to those who strongly disagreed (94.4% vs. 19.6%). Overall, 76.6% of beef eaters indicated wanting to eat less beef or phase it out entirely (30.7% reduce, 29.4% minimize, 16.6% stop), with only 23.4% of them intending to keep their consumption unchanged. Compelling messages that help translate awareness into action, such as the #NoBeefWeek concept explored in this study, may support individuals in adopting more sustainable food choices. These cross-national findings provide evidence for a ‘knowledge–intent’ gap in sustainable diet research, with relevance for health communicators and policymakers. Future research could examine the factors and motivations influencing decisions to modify beef consumption, including the barriers to achieving sustainable consumption levels and the role of suitable alternatives in facilitating this transition. Full article

Microglia, as the immune guardians of the central nervous system (CNS), have the ability to maintain neural homeostasis, respond to environmental changes, and remodel the synaptic landscape. However, persistent microglial activation can lead to chronic neuroinflammation, which can alter neuronal signaling pathways, resulting in accelerated cognitive decline. Phosphoinositol 3-kinase (PI3K) has emerged as a critical driver, connecting inflammation to neurodegeneration, serving as the nexus of numerous intracellular processes that govern microglial activation. This review focuses on the relationship between PI3K signaling and microglial activation, which might lead to cognitive impairment, inflammation, or even neurodegeneration. The review delves into the components of the PI3K signaling cascade, isoforms, and receptors of PI3K, as well as the downstream effects of PI3K signaling, including its effectors such as protein kinase B (Akt) and mammalian target of rapamycin (mTOR) and the negative regulator phosphatase and tensin homolog (PTEN). Experiments have shown that the overproduction of certain cytokines, coupled with abnormal oxidative stress, is a consequence of poor PI3K regulation, resulting in excessive synapse pruning and, consequently, impacting learning and memory functions. The review also highlights the implications of autonomously activated microglia exhibiting M1/M2 polarization driven by PI3K on hippocampal, cortical, and subcortical circuits. Conclusions from behavioral studies, electrophysiology, and neuroimaging linking cognitive performance and PI3K activity were evaluated, along with new approaches to therapy using selective inhibitors or gene editing. The review concludes by highlighting important knowledge gaps, including the specific effects of different isoforms, the risks associated with long-term pathway modulation, and the limitations of translational potential, underscoring the crucial role of PI3K in mitigating cognitive impairment driven by neuroinflammation. Full article

Background/Objectives: Immune checkpoint inhibitors have significantly transformed the treatment paradigm of advanced melanoma, leading to substantial improvements in survival outcomes. However, this therapeutic success is accompanied by a spectrum of treatment-related adverse events, some of which are increasingly recognised as enduring and non-reversible. Whilst early-onset immune-related toxicities have been well characterized, late-onset toxicities, often emerging in patients with long-term disease control, remain understudied and are frequently overlooked. Methods: To address this knowledge gap, we conducted a retrospective multicentre study in three UK tertiary referral centres, exploring immune-related adverse events in 246 patients with melanoma who received immune checkpoint inhibitors in the advanced setting. We defined late-onset immune-related adverse events as those occurring at least 3 months after the last cycle of immune checkpoint inhibitors. Results: Although most patients experienced early-onset toxicity, almost 15% of patients developed late-onset immune-related adverse events, including skin rash, colitis, hepatitis, and arthritis, among others. These were often challenging to manage and necessitated the use of systemic steroids. Up to 2% of patients presented ultra-late-onset toxicities, defined as those events occurring at least 12 months after treatment completion. Conclusions: This study provides valuable insights into the characteristics of late-onset immune-related adverse events. To further advance our understanding of these late-onset toxicities, dedicated prospective studies are needed to assess risk factors associated with their development and their impact on quality of life. Additionally, translational research focused on finding predictive biomarkers is essential to identify patients at a higher risk of developing delayed adverse events and to understand how best to manage them. Full article

Text-to-SQL for spatial databases enables the translation of natural language questions into corresponding SQL queries, allowing non-experts to easily access spatial data, which has gained increasing attention from researchers. Previous research has primarily focused on rule-based methods. However, these methods have limitations when dealing with complicated or unknown natural language questions. While advanced machine learning models can be trained, they typically require large labeled training datasets, which are severely lacking for spatial databases. Recently, Generative Pre-Trained Transformer (GPT) models have emerged as a promising paradigm for Text-to-SQL tasks in relational databases, driven by carefully designed prompts. In response to the severe lack of datasets for spatial databases, we have created a publicly available dataset that supports both English and Chinese. Furthermore, we propose a GPT-based method to construct prompts for spatial databases, which incorporates geographic and spatial database knowledge into the prompts and requires only a small number of training samples, such as 1, 3, or 5 examples. Extensive experiments demonstrate that incorporating geographic and spatial database knowledge into prompts improves the accuracy of Text-to-SQL tasks for spatial databases. Our proposed method can help non-experts access spatial databases more easily and conveniently. Full article

Background/objective: Tailoring involves adapting research findings and evidence to suit specific contexts and audiences. This study examines how international stroke guidelines can be tailored to address gait issues after a stroke. Methods: A three-phase consensus method approach was used. A 10-member health experts panel extracted recommendations from three national clinical guidelines in the first phase. In the second phase, 362 physiotherapists completed an online questionnaire to assess the feasibility of adopting the extracted recommendations. In the third phase, a 15-physical therapist consensus workshop was convened to clarify factors that might affect the tailoring process of the extracted recommendations of gait disorder rehabilitation. Results: In phase one, 21 recommendations reached consensus. In the second phase, 362 stroke physiotherapists rated the applicability of these recommendations: 14 rated high, 7 rated low, and none were rejected. The third phase, a nominal group meeting (NGM), explored four themes related to tailoring. The first theme, “organizational factors”, includes elements such as clinical setting, culture, and regulations. The second theme, “individual clinician factors”, assesses aspects like clinical experience, expertise, abilities, knowledge, and attitudes toward tailoring. The third theme, “patient factors”, addresses issues related to multimorbidity, comorbidities, patient engagement, and shared decision-making. The final theme, “other factors”, examines the impact of research design on tailoring. Conclusions: Tailoring international clinical guidelines involves multiple factors. This situation brings home the importance of a systematic strategy for tailoring that incorporates various assessment criteria to enhance the use of clinical evidence. Future research should investigate additional implementation theories to enhance the translation of evidence into practice. Full article

Analyzing and leveraging data effectively has been an advantageous strategy in the management workflows of many contemporary organizations. In business and finance, data-informed decision workflows are nowadays essential for enabling development and growth. However, there is yet a theoretical or quantitative approach for analyzing the cost–benefit of the processes in such workflows, e.g., in determining the trade-offs between machine- and human-centric processes and quantifying biases. The aim of this work is to translate an information-theoretic concept and measure for cost–benefit analysis to a methodology that is relevant to the analysis of hybrid decision workflows in business and finance. We propose to combine an information-theoretic approach (i.e., information-theoretic cost–benefit analysis) and an engineering approach (e.g., workflow decomposition), which enables us to utilize information-theoretic measures to estimate the cost–benefit of individual processes quantitatively. We provide three case studies to demonstrate the feasibility of the proposed methodology, including (i) the use of a statistical and computational algorithm, (ii) incomplete information and humans’ soft knowledge, and (iii) cognitive biases in a committee meeting. While this is an early application of information-theoretic cost–benefit analysis to business and financial workflows, it is a significant step towards the development of a systematic, quantitative, and computer-assisted approach for optimizing data-informed decision workflows. Full article

Brain tumours challenge the structural and functional integrity of the brain, yet remarkable neuroplastic adaptations often preserve critical functions. This review synthesises the current knowledge of the molecular events underlying neuroplasticity in the context of tumoural growth, spanning from early genetic and protein alterations to macroscopic functional reorganisation. We discuss the roles of stress-regulated molecules, synaptic proteins, trophic factors, and morphological changes in driving adaptive responses. Furthermore, we bridge the gap between microscopic molecular events and large-scale network adaptations, emphasising clinical implications for glioma surgery and patient outcomes. Despite advances, knowledge gaps persist regarding the dynamics, predictors, and therapeutic modulation of plasticity, underscoring the need for future longitudinal and translational research. Understanding and leveraging these molecular mechanisms holds promise for improving functional recovery and quality of life in patients with brain tumours. Full article

Inorganic polyphosphate (polyP) is an evolutionarily conserved polymer that has recently gained relevance in neuronal physiology and pathophysiology. Although its roles, such as mitochondrial bioenergetics, calcium homeostasis, and the oxidative stress response, for example, are increasingly recognized, its specific implications in neurological disorders remain underexplored. This review focuses on synthesizing the current knowledge of polyP in the context of central nervous system (CNS) diseases, highlighting how its involvement in key mitochondrial processes may influence neuronal survival and function. In particular, we examine recent evidence linking polyP to mechanisms relevant to neurodegeneration, such as the modulation of the mitochondrial permeability transition pore (mPTP), regulation of amyloid fibril formation, and oxidative stress responses. In addition, we analyze the emerging roles of polyP in inflammation and related cell signaling in CNS disorders. By organizing the existing data around the potential pathological and protective roles of polyP in the CNS, this review identifies it as a candidate of interest in the context of neurodegenerative disease mechanisms. We aim to clarify its relevance and stimulate future research on its molecular mechanisms and translational potential. Full article

Plant-derived vesicle-like nanoparticles (PDVLNs) are bioactive nanovesicles secreted by plant cells, emerging as a novel therapeutic tool for tissue repair and regeneration due to their low immunogenicity, intrinsic bioactivity, and potential as drug delivery carriers. This review examines PDVLNs’ biogenesis mechanisms, isolation techniques, and compositional diversity, emphasizing their roles in promoting essential regenerative processes—cell proliferation, differentiation, migration, immune modulation, and angiogenesis. We explore their therapeutic applications across multiple tissue types, including skin, bone, neural, liver, gastrointestinal, cardiovascular, and dental tissues, using both natural and engineered PDVLNs in various disease models. Compared to mammalian exosomes, PDVLNs offer advantages such as reduced immune rejection and ethical concerns, enhancing their sustainability and appeal for regenerative medicine. However, challenges in clinical translation, including scalability, standardization, and safety remain. This paper consolidates current knowledge on PDVLNs, highlighting their versatility and providing insights into engineering strategies to optimize efficacy, ultimately outlining future research directions to advance their clinical potential. Plant vesicle-like nanoparticles (PDVLNs) may become a new avenue for the treatment of tissue injury, promoting tissue repair and regeneration through their intrinsic bioactivity or as drug delivery carriers. In addition, PDVLNs can be engineered and modified to achieve better results. Full article

Background and Objectives: Investigating the adherence to antihypertensive medication and identifying patients with low adherence allows targeted interventions to improve therapeutic outcomes. Artificial intelligence (AI) offers advanced tools for analyzing medication adherence data. This study aimed to develop and validate several predictive models for non-adherence, using patient-reported data collected via a structured questionnaire. Materials and Methods: A cross-sectional, multi-center study was conducted on 3095 hypertensive patients from community pharmacies. A structured questionnaire was administered, collecting data on sociodemographic factors, medical history, self-monitoring behaviors, and informational exposure, alongside medication adherence measured using the Romanian-translated and validated ARMS (Adherence to Refills and Medications Scale). Five machine learning models were developed to predict non-adherence, defined by ARMS quartile-based thresholds. The models included Logistic Regression, Random Forest, and boosting algorithms (CatBoost, LightGBM, and XGBoost). Models were evaluated based on their ability to stratify patients according to adherence risk. Results: A total of 79.13% of respondents had an ARMS Score ≥ 15, indicating a high prevalence of suboptimal adherence. Better adherence was statistically associated (adjusted for age and sex) with more frequent blood pressure self-monitoring, a reduced salt intake, fewer daily supplements, more frequent reading of medication leaflets, and the receipt of specific information from pharmacists. Among the ML models, CatBoost achieved the highest ROC AUC Scores across the non-adherence classifications, although none exceeded 0.75. Conclusions: Several machine learning models were developed and validated to estimate levels of medication non-adherence. While the performance was moderate, the results demonstrate the potential of AI in identifying and stratifying patients by adherence profiles. Notably, to our knowledge, this study represents the first application of permutation and SHapley Additive exPlanations feature importance in combination with probability-based adherence stratification, offering a novel framework for predictive adherence modelling. Full article

Agrivoltaic (Agri-PV) systems face the critical challenge of balancing photovoltaic energy generation with crop productivity, yet systematic approaches to quantifying the trade-offs between these objectives remain scarce. In this study, we identify nine essential design indicators: panel tilt angle, elevation, photovoltaic coverage ratio, shading factor, land equivalent ratio, photosynthetically active radiation (PAR) utilization, crop yield stability index, water use efficiency, and return on investment. We introduce a novel dual matrix Analytic Hierarchy Process (AHP) to evaluate their relative significance. An international panel of eighteen Agri-PV experts, encompassing academia, industry, and policy, provided pairwise comparisons of these indicators under two objectives: maximizing annual energy yield and sustaining crop output. The high consistency observed in expert responses allowed for the derivation of normalized weight vectors, which form the basis of two Weighted Influence Matrices. Analysis of Total Weighted Influence scores from these matrices reveal distinct priority sets: panel tilt, coverage ratio, and elevation are most influential for energy optimization, while PAR utilization, yield stability, and elevation are prioritized for crop productivity. This methodology translates qualitative expert knowledge into quantitative, actionable guidance, clearly delineating both synergies, such as the mutual benefit of increased elevation for energy and crop outcomes, and trade-offs, exemplified by the negative impact of high photovoltaic coverage on crop yield despite gains in energy output. By offering a transparent, expert-driven decision-support tool, this framework enables practitioners to customize Agri-PV system configurations according to local climatic, agronomic, and economic contexts. Ultimately, this approach advances the optimization of the food energy nexus and supports integrated sustainability outcomes in Agri-PV deployment. Full article