Search Results (15,999)

The use of chemical pesticides in agriculture has led to the development of resistant pest populations, posing a challenge to long-term pest management. This review aims to evaluate the scientific literature on the individual and combined use of baculoviruses with conventional chemical and biological insecticides to combat Plutella xylostella, Spodoptera exigua, and Spodoptera frugiperda in broccoli, tomato, and maize crops. Notable findings include that both individual Plutella xylostella nucleopolyhedrovirus (PxNPV) and the combination of Plutella xylostella granulovirus (PxGV) and azadirachtin at a low dose effectively control Plutella xylostella; both combinations of Spodoptera exigua multiple nucleopolyhedrovirus (SeMNPV) with emamectin benzoate and chlorfenapyr reduced resistance in Spodoptera exigua and increased the efficacy of the insecticides; and the combination of Spodoptera frugiperda nucleopolyhedrovirus (SfMNPV) and spinetoram is effective against Spodoptera frugiperda. Integrating baculoviruses into pest management strategies offers a promising approach to mitigate the adverse effects of chemical pesticides, such as resistance development, health risks, and environmental damage. However, there remains a broad spectrum of research opportunities regarding the use of baculoviruses in agriculture. Full article

Exposure to per- and polyfluoroalkyl substances (PFASs) can cause detrimental health effects. The consumption of contaminated food is viewed as a major exposure pathway for humans, but the relationship between agriculture and PFASs has not been investigated thoroughly, and it is becoming a pressing issue since health advisories are continuously being reassessed. This semi-systematic literature review connects the release, environmental fate, and agriculture uptake of PFASs to enhance comprehension and identify knowledge gaps which limit accurate risk assessment. It focuses on the heavily agricultural state of Minnesota, USA, which is representative of the large Midwestern US Corn Belt in terms of agricultural activities, because PFASs have been monitored in Minnesota since the beginning of the 21st century. PFAS contamination is a complex issue due to the over 14,000 individual PFAS compounds which have unique chemical properties that interact differently with air, water, soil, and biological systems. Moreover, the lack of field studies and monitoring of agricultural sites makes accurate risk assessments challenging. Researchers, policymakers, and farmers must work closely together to reduce the risk of PFAS exposure as the understanding of their potential health effects increases and legacy PFASs are displaced with shorter fluorinated replacements. Full article

Understanding the entrepreneurial profile is essential for developing effective regional policies that promote business growth. The path of an entrepreneur is shaped not only by individual decisions but also by the inherent risks of managing a business. This study aims to identify the characteristics of entrepreneurs at the regional level, specifically highlighting the impact of accumulated experience in their fields. Our central hypothesis asserts that entrepreneurial experience significantly influences how business owners perceive and respond to economic challenges. Utilizing survey data from 120 entrepreneurs in Romania’s Center Region (a NUTS 2 area), we reveal that entrepreneurial experience profoundly affects perceptions of key business challenges, such as legislative instability, taxation predictability, governmental support strategies, and access to SME financing. Importantly, our findings demonstrate that entrepreneurs with less than 10 years of experience express greater concerns about these challenges compared to their more seasoned peers. This novel insight highlights the need for tailored policy interventions aimed at enhancing regional economic resilience and fostering entrepreneurial sustainability. By addressing the specific needs of less experienced entrepreneurs, our study contributes to a deeper understanding of how experience shapes business dynamics in the region. Full article

Accurate forecasting of tropical cyclone (TC) tracks is critical for disaster preparedness and risk mitigation. While traditional numerical weather prediction (NWP) systems have long served as the backbone of operational forecasting, they face limitations in computational cost and sensitivity to initial conditions. In recent years, deep learning (DL) has emerged as a promising alternative, offering data-driven modeling capabilities for capturing nonlinear spatiotemporal patterns. This paper presents a comprehensive review of DL-based approaches for TC track forecasting. We categorize all DL-based TC tracking models according to the architecture, including recurrent neural networks (RNNs), convolutional neural networks (CNNs), Transformers, graph neural networks (GNNs), generative models, and Fourier-based operators. To enable rigorous performance comparison, we introduce a Unified Geodesic Distance Error (UGDE) metric that standardizes evaluation across diverse studies and lead times. Based on this metric, we conduct a critical comparison of state-of-the-art models and identify key insights into their relative strengths, limitations, and suitable application scenarios. Building on this framework, we conduct a critical cross-model analysis that reveals key trends, performance disparities, and architectural tradeoffs. Our analysis also highlights several persistent challenges, such as long-term forecast degradation, limited physical integration, and generalization to extreme events, pointing toward future directions for developing more robust and operationally viable DL models for TC track forecasting. To support reproducibility and facilitate standardized evaluation, we release an open-source UGDE conversion tool on GitHub. Full article

Background: Cognitive decline is a growing public health concern in Latin America, driven by rapid aging, widespread micronutrient inadequacies, and socioeconomic disparities. Despite the recognized importance of nutrition, many older adults struggle to meet daily dietary micronutrients requirements, increasing the risk of mild cognitive impairment (MCI). This study aimed to establish expert consensus on the role of Multivitamin and Mineral supplements (MVMs) in promoting cognitive healthy aging among older adults in Latin America. Methods: A panel of nine experts in geriatrics, neurology, and nutrition applied a modified Delphi methodology to generate consensus statements. The panel reviewed the literature, engaged in expert discussions, and used structured voting to develop consensus statements. Results: Consensus was reached on 14 statements. Experts agreed that cognitive aging in Latin America is influenced by neurobiological, lifestyle, and socioeconomic factors, including widespread micronutrient inadequacies (vitamins B-complex, C, D, E, and minerals such as zinc, magnesium, chromium, copper, iron and selenium), which were identified as critical for global cognitive function and brain structures, yet commonly inadequate in the elderly. While a balanced diet remains essential, MVMs can be recommended as a complementary strategy to bridge nutritional gaps. Supporting evidence, including the COSMOS-Mind trials, demonstrate that MVM use improves memory and global cognition, and reduces cognitive aging by up to 2 years in older adults. Conclusions: MVMs offer a promising, accessible adjunct for cognitive healthy aging in Latin America’s elderly population, particularly where dietary challenges persist. Region-specific guidelines, public health initiatives, and targeted research are warranted to optimize outcomes and reduce health inequities. Full article

Stress in pigs poses significant challenges to animal welfare and productivity in modern pig farming, contributing to increased antimicrobial use and the rise of antimicrobial resistance (AMR). This study involves stress classification in pregnant sows by exploring five deep learning models: ConvNeXt, EfficientNet_V2, MobileNet_V3, RegNet, and Vision Transformer (ViT). These models are used for stress detection from facial images, leveraging an expanded dataset. A facial image dataset of sows was collected at Scotland’s Rural College (SRUC) and the images were categorized into primiparous Low-Stressed (LS) and High-Stress (HS) groups based on expert behavioural assessments and cortisol level analysis. The selected deep learning models were then trained on this enriched dataset and their performance was evaluated using cross-validation on unseen data. The Vision Transformer (ViT) model outperformed the others across the dataset of annotated facial images, achieving an average accuracy of 0.75, an F1 score of 0.78 for high-stress detection, and consistent batch-level performance (up to 0.88 F1 score). These findings highlight the efficacy of transformer-based models for automated stress detection in sows, supporting early intervention strategies to enhance welfare, optimize productivity, and mitigate AMR risks in livestock production. Full article

Background: Pancreatic cystic lesions (PCLs), including intraductal papillary mucinous neoplasms (IPMNs) and mucinous cystic neoplasms (MCNs), pose a diagnostic challenge due to their variable malignant potential. Current guidelines, such as Fukuoka and American Gastroenterological Association (AGA), have moderate predictive accuracy and may lead to overtreatment or missed malignancies. Artificial intelligence (AI), incorporating machine learning (ML) and deep learning (DL), offers the potential to improve risk stratification, diagnosis, and management of PCLs by integrating clinical, radiological, and molecular data. This is the first systematic review to evaluate the application, performance, and clinical utility of AI models in the diagnosis, classification, prognosis, and management of pancreatic cysts. Methods: A systematic review was conducted in accordance with PRISMA guidelines and registered on PROSPERO (CRD420251008593). Databases searched included PubMed, EMBASE, Scopus, and Cochrane Library up to March 2025. The inclusion criteria encompassed original studies employing AI, ML, or DL in human subjects with pancreatic cysts, evaluating diagnostic, classification, or prognostic outcomes. Data were extracted on the study design, imaging modality, model type, sample size, performance metrics (accuracy, sensitivity, specificity, and area under the curve (AUC)), and validation methods. Study quality and bias were assessed using the PROBAST and adherence to TRIPOD reporting guidelines. Results: From 847 records, 31 studies met the inclusion criteria. Most were retrospective observational (n = 27, 87%) and focused on preoperative diagnostic applications (n = 30, 97%), with only one addressing prognosis. Imaging modalities included Computed Tomography (CT) (48%), endoscopic ultrasound (EUS) (26%), and Magnetic Resonance Imaging (MRI) (9.7%). Neural networks, particularly convolutional neural networks (CNNs), were the most common AI models (n = 16), followed by logistic regression (n = 4) and support vector machines (n = 3). The median reported AUC across studies was 0.912, with 55% of models achieving AUC ≥ 0.80. The models outperformed clinicians or existing guidelines in 11 studies. IPMN stratification and subtype classification were common focuses, with CNN-based EUS models achieving accuracies of up to 99.6%. Only 10 studies (32%) performed external validation. The risk of bias was high in 93.5% of studies, and TRIPOD adherence averaged 48%. Conclusions: AI demonstrates strong potential in improving the diagnosis and risk stratification of pancreatic cysts, with several models outperforming current clinical guidelines and human readers. However, widespread clinical adoption is hindered by high risk of bias, lack of external validation, and limited interpretability of complex models. Future work should prioritise multicentre prospective studies, standardised model reporting, and development of interpretable, externally validated tools to support clinical integration. Full article

European pig farmers are challenged by increasingly stringent EU regulations to protect the environment from pollution, to meet animal welfare standards and to make pig farming more sustainable. Economic sustainability is defined as the ability to achieve higher profits by respecting social and natural resources. This study is focused on the analysis of the economic resilience of intensive and extensive farming systems, based on data collected from 56 farms located in Denmark, Poland, Italy and Spain. Productive and economic performances of these farms are analyzed, and economic resilience is assessed through a survey including a selection of indicators, belonging to different themes: [i] resilience of resources, [ii] entrepreneurship, [iii] propensity to extensification. The qualitative data from the questionnaire allow for an exploration of how production systems relate to the three dimensions of resilience. Different levels of resilience were found and discussed for intensive and extensive farms. The findings suggest that intensive farms benefit from high standards and greater bargaining power within the supply chain. Extensive systems can achieve profitability through value-added strategies and generally display good resilience. Policies that support investment and risk reduction are essential for enhancing farm resilience and robustness, while strengthening farmer networks can improve adaptability. Full article

Infection control and bleeding management in deep wounds remain urgent and unmet clinical challenges that demand innovative, multifunctional, and sustainable solutions. Unlike previously reported sodium alginate and silk fibroin-based gel formulations, the present work introduces a dual-functional system combining antimicrobial and haemostatic activity in the form of conformable aerogel beads. This dual-functional formulation is designed to absorb exudate, promote clotting, and provide localized antimicrobial action, all essential for accelerating wound repair in high-risk scenarios within a single biocompatible system. Aerogel beads were obtained by supercritical drying of a silk fibroin–sodium alginate blend, resulting in highly porous, spherical structures measuring 3–4 mm in diameter. The formulations demonstrated efficient ciprofloxacin encapsulation (42.75–49.05%) and sustained drug release for up to 12 h. Fluid absorption reached up to four times their weight in simulated wound fluid and was accompanied by significantly enhanced blood clotting, outperforming a commercial haemostatic dressing. These findings highlight the potential of silk-based aerogel beads as a multifunctional wound healing platform that combines localized antimicrobial delivery, efficient fluid and exudate management, biodegradability, and superior haemostatic performance in a single formulation. This work also shows for the first time how the prilling encapsulation technique with supercritical drying is able to successfully produce silk fibroin and sodium alginate composite aerogel beads. Full article

High-mobility group box 1 (HMGB1) is a nuclear protein that can interact with a transmembrane cell surface receptor for advanced glycation end products (RAGEs) and mediates the inflammatory pathways that lead to various pathological conditions like cancer, diabetes, cardiovascular diseases, and neurodegenerative disorders. Blocking the HMGB1/RAGE axis using various small synthetic or natural molecules has been proven to be an effective therapeutic approach to treating these inflammatory conditions. However, the low water solubility of these pharmacoactive molecules limits their clinical use. Pharmaceutically active molecules with low solubility and bioavailability in vivo convey a higher risk of failure for drug development and drug innovation. The pharmacokinetic and pharmacodynamics parameters of these compounds are majorly affected by their solubility. Enhancement of the bioavailability and solubility of drugs is a significant challenge in the area of pharmaceutical formulations. This review mainly describes various technologies utilized to improve the bioavailability of synthetic or natural molecules which have been particularly used in various inflammatory conditions acting specifically through the HMGB1/RAGE pathway. Full article

Osteoarthritis (OA) remains a major contributor to pain and disability; however, the current management is largely reactive, focusing on symptoms rather than preventing irreversible cartilage loss. This review first examines the mechanistic foundations for pharmacological chondroprotection—illustrating how conventional agents, such as glucosamine sulfate and chondroitin sulfate, can potentially restore extracellular matrix (ECM) components, may attenuate catabolic enzyme activity, and might enhance joint lubrication—and explores the delivery challenges posed by avascular cartilage and synovial diffusion barriers. Subsequently, a practical “What–How–When” framework is introduced to guide community pharmacists in risk screening, DMOAD selection, chronotherapeutic dosing, safety monitoring, and lifestyle integration, as exemplified by the CHONDROMOVING infographic brochure designed for diverse health literacy levels. Building on these strategies, the P4–4P Chondroprotection Framework is proposed, integrating predictive risk profiling (physicians), preventive pharmacokinetic and chronotherapy optimization (pharmacists), personalized biomechanical interventions (physiotherapists), and participatory self-management (patients) into a unified, feedback-driven OA care model. To translate this framework into routine practice, I recommend the development of DMOAD-specific clinical guidelines, incorporation of chondroprotective chronotherapy and interprofessional collaboration into health-professional curricula, and establishment of multidisciplinary OA management pathways—supported by appropriate reimbursement structures, to support preventive, team-based management, and prioritization of large-scale randomized trials and real-world evidence studies to validate the long-term structural, functional, and quality of life benefits of synchronized DMOAD and exercise-timed interventions. This comprehensive, precision-driven paradigm aims to shift OA care from reactive palliation to true disease modification, preserving cartilage integrity and improving the quality of life for millions worldwide. Full article

Container liner shipping companies operate within a complex environment where they must balance profitability and service reliability. Meanwhile, evolving regulatory policies, such as surcharges imposed on ships of a particular origin or type on specific trade lanes, introduce new operational challenges. This study addresses the heterogeneous ship routing and demand acceptance problem, aiming to maximize two conflicting objectives: weekly profit and total transport volume. We formulate the problem as a bi-objective mixed-integer programming model and prove that the ship chartering constraint matrix is totally unimodular, enabling the reformulation of the model into a partially relaxed MIP that preserves optimality while improving computational efficiency. We further analyze key mathematical properties showing that the Pareto frontier consists of a finite union of continuous, piecewise linear segments but is generally non-convex with discontinuities. A case study based on a realistic liner shipping network confirms the model’s effectiveness in capturing the trade-off between profit and transport volume. Sensitivity analyses show that increasing freight rates enables higher profits without large losses in volume. Notably, this paper provides a practical risk management framework for shipping companies to enhance their adaptability under shifting regulatory landscapes. Full article

Obstructive sleep apnea (OSA) could increase pulmonary artery pressure. However, the clinical consequences vary, mainly depending on comorbidities. Patients with pulmonary hypertension associated with lung diseases (World Health Organization (WHO) Group 3 pulmonary hypertension) are particularly vulnerable increases in pulmonary artery pressure. Managing pulmonary hypertension in this specific patient population presents a considerable challenge. While positive airway pressure therapy for OSA has shown promise in improving pulmonary hemodynamics in patients with obesity hypoventilation syndrome and chronic obstructive pulmonary disease, evidence is lacking for similar improvements in those with other pulmonary diseases and hypoventilation disorders. Furthermore, pulmonary-artery-specific therapies may carry a risk of clinical worsening in this group. Weight management and new pharmacotherapy have together emerged as a crucial intervention, demonstrating benefits for both OSA and pulmonary hemodynamics. We reviewed key studies that provide insights into the influence of OSA on WHO Group 3 pulmonary hypertension and the clinical management of both conditions. Full article

Background: Pulmonary involvement is the most common prognosis-related organ involvement in idiopathic inflammatory myopathy (IIM). Owing to the large number of antibodies, the evidence for lung involvement and rare antibodies is limited. In everyday clinical practice, the interpretation of positive myositis antibodies represents a challenge. Methods: This study is a retrospective monocentric analysis. The data collection regarding positive myositis antibodies and possible pulmonary involvement was carried out from July 2019 to May 2022. Data analysis revealed positive results for one of the following antibodies: EJ, PL7, OJ, PL12, Mi-2α, TIF1γ, MDA5, SAE, NXP2, SRP, Ku, PM-Scl100 and PM-Scl75. In our analysis, patients with IIM, patients with inflammatory rheumatic disease other than IIM and patients without inflammatory rheumatic disease are described. The results of high-resolution computed tomography (HRCT), pulmonary function tests, echocardiographic examinations and their associated clinical findings are examined. Results: In the entire cohort, 209 patients with positive myositis antibodies were detected. In total, 22 (10.5%) patients had interstitial lung disease (ILD) patterns on HRCT. In the subgroup of patients with IIM, a significantly higher proportion of patients with lung involvement (n = 13, 35.1%) was found than in the group with other inflammatory rheumatic diseases (IRDs) (n = 6, 6.7%) or in the group without IRDs (n = 3, 3.7%). When the antibody groups were considered, the PL12-positive patients had the largest proportion of ILD (42%), followed by the MDA5-positive patients (40%). Conclusions: In patients with IIM, myositis antibodies are highly relevant for assessing the risk of lung involvement. In groups with other IRD or without IRD, antibody detection does not represent this high relevance for lung involvement. A differentiated assessment of the various MSAs or MAAs detected, as well as clinical parameters, allows for further important risk assessment for prognosis-relevant lung involvement. Full article

Background/Objectives: Infertility, defined as the failure to achieve pregnancy after one year of regular unprotected intercourse, represents a significant global health challenge, with male factors contributing to approximately 50% of cases. In this epidemiological context, both primary male infertility (the inability to conceive a first child) and secondary male infertility (which occurs when a man who has already fathered a child faces difficulty conceiving again) remain poorly understood at the genetic level. This study explored the role of single-nucleotide polymorphisms (SNPs) in mitochondrial genes (MT-ND3, MT-ND4L, and MT-ND4) in primary and secondary male infertility. Methods: This study analyzed the genotype distributions of SNPs in 68 infertile males (49 with primary infertility and 19 with secondary infertility) using Sanger sequencing. Results: Key findings revealed that studied SNPs were significantly associated with infertility type. Specifically, rs2857285 (T>C,G) in the ND4 gene showed a significant correlation (p = 0.023) with the TT genotype, which is prominent in primary infertility. Another SNP, rs28358279 (T>A,C) in the ND4L gene, also demonstrated a significant correlation (p = 0.046) with the TT genotype, being more common in primary infertility. In addition, rs869096886 (A>G) in the ND4 gene had a borderline correlation (p = 0.051), indicating a possible association between this SNP and reproductive duration. Conclusions: This study emphasizes the potential relevance of mitochondrial malfunction in male infertility, specifically the effects of studied SNPs on sperm survival and function over time. These findings suggest that certain mitochondrial SNPs might be potential biomarkers for infertility risk. Larger studies are needed to confirm these associations and examine the functional effects of these SNPs. Combining genetic analysis with environmental and lifestyle factors could enhance our understanding of male infertility and improve diagnostic and therapeutic strategies. Full article