Search Results (3,190)

Background/Objective: The use of artificial intelligence to assist in medical applications is an emerging area of investigation and discussion. The researchers studied whether there was a difference between homeopathy guidance provided by artificial intelligence (AI) (automated) and live professional practitioners (live) for acute illnesses. Additionally, the study explored the practical challenges associated with validating AI tools used for homeopathy and sought to generate insights on the potential value and limitations of these tools in the management of acute health complaints. Method: Randomly selected cases at a homeopathy teaching clinic (n = 100) were entered into a commercially available homeopathic remedy finder to investigate the consistency between automated and live recommendations. Client symptoms, medical disclaimers, remedies, and posology were compared. The findings of this study show that the purpose-built homeopathic remedy finder is not a one-to-one replacement for a live practitioner. Result: In the 100 cases compared, the automated online remedy finder provided between 1 and 20 prioritized remedy recommendations for each complaint, leaving the user to make the final remedy decision based on how well their characteristic symptoms were covered by each potential remedy. The live practitioner-recommended remedy was included somewhere among the auto-mated results in 59% of the cases, appeared in the top three results in 37% of the cases, and was a top remedy match in 17% of the cases. There was no guidance for managing remedy responses found in live clinical settings. Conclusion: This study also highlights the challenge and importance of validating AI remedy recommendations against real cases. The automated remedy finder used covered 74 acute complaints. The live cases from the teaching clinic included 22 of the 74 complaints. Full article

Colorectal cancer (CRC) remains one of the most lethal malignancies worldwide, with high recurrence rates and limited curative options in metastatic settings. Cancer vaccines represent an emerging immunotherapeutic approach that aims to stimulate robust, tumor-specific immune responses. This review summarizes the current state of CRC vaccine development, including tumor cell-based, dendritic cell-based, peptide-based, nucleic acid-based (DNA and mRNA), and virus-based platforms. We highlight findings from key clinical trials that demonstrate immunogenicity, safety, and preliminary efficacy, with particular attention to combinations with chemotherapy and immune checkpoint inhibitors. Furthermore, we explore critical challenges such as tumor heterogeneity, immunosuppressive tumor microenvironments, and the logistical complexity; in this context, we particularly focus on the current development of personalized cancer vaccines, exploring the newly identified encouraging epitopes and their safety and efficacy in recent trials. The integration of cancer vaccines with in silico modeling, advanced delivery systems such as nanoparticles or AI-guided designs, and microbiome modulation represents a promising avenue for enhancing their clinical utility. Overall, therapeutic and prophylactic cancer vaccines may soon contribute meaningfully to the comprehensive management of CRC, especially in settings of minimal residual disease or early recurrence. Full article

Improving construction site safety remains a critical challenge in Saudi Arabia’s rapidly growing construction sector, where high accident rates and diverse labor forces demand evidence-based managerial interventions. This study investigated the influence of Managers’ Safety Perceptions and Practices (MSP) on Workers’ Safety Behaviors (WSB) in the Saudi construction industry, emphasizing the mediating roles of Workers’ Safety Awareness (WSA), Safety Competency (WSC), and Safety Actions (SA). The conceptual framework integrates these three mediators to explain how managerial attitudes and practices translate into frontline safety outcomes. A quantitative, cross-sectional design was adopted using a structured questionnaire distributed among construction workers, supervisors, and project managers. A total of 352 from 384 valid responses were collected, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4. The findings revealed that MSP does not directly influence WSB but has significant indirect effects through WSA, WSC, and SA. Among these, WSC emerged as the most powerful mediator, followed by WSA and SA, indicating that competency is the most critical driver of safe worker behavior. These results provide robust empirical support for a multidimensional mediation model, highlighting the need for managers to enhance safety behaviors not merely through supervision but through fostering awareness and competency, providing technical training, and implementing proactive safety measures. Theoretically, this study contributes a novel and integrative framework to the occupational safety literature, particularly within underexplored Middle Eastern construction contexts. Practically, it offers actionable insights for safety managers, industry practitioners, and policymakers seeking to improve construction safety performance in alignment with Saudi Vision 2030. Full article

Multiple sclerosis (MS) and allergic diseases, traditionally considered immunologically opposing entities, may share pathogenic mechanisms rooted in immune dysregulation. While MS is predominantly mediated by Th1 and Th17 responses and allergies by Th2 responses, emerging evidence suggests overlapping immunological pathways, including the involvement of histamine, regulatory T cells, and innate lymphoid cells. This review synthesizes current knowledge on the epidemiological and immunopathological associations between MS and allergies. Epidemiological studies have yielded inconsistent results, with some suggesting a protective role for respiratory and food allergies against MS onset, while others find no significant correlation. Clinical studies indicate that food allergies in adults may be associated with increased MS inflammatory activity, whereas childhood atopy might exert a protective effect. In addition, we review hypersensitivity reactions to disease-modifying treatments for MS, detailing their immunological mechanisms, clinical presentation, and management, including desensitization protocols where applicable. Finally, we explore how treatments for allergic diseases—such as clemastine, allergen immunotherapy, montelukast, and omalizumab—may modulate MS pathophysiology, offering potential therapeutic synergies. Understanding the interplay between allergic and autoimmune processes is critical for optimizing care and developing innovative treatment approaches in MS. Full article

Chemotherapy remains a cornerstone in the treatment of esophageal cancer (EC), yet chemoresistance remains a critical challenge, leading to poor outcomes and limited therapeutic success. Mitochondrial DNA (mtDNA) has emerged as a pivotal player in mediating these responses, influencing cellular metabolism, oxidative stress regulation, and apoptotic pathways. This review provides a comprehensive overview of the mechanisms by which mtDNA alterations, including mutations and copy number variations, drive chemoresistance in EC. Specific focus is given to the role of mtDNA in metabolic reprogramming, including its contribution to the Warburg effect and lipid metabolism, as well as its impact on epithelial–mesenchymal transition (EMT) and mitochondrial bioenergetics. Recent advances in targeting mitochondrial pathways through novel therapeutic agents, such as metformin and mitoquinone, and innovative approaches like CRISPR/Cas9 gene editing, are also discussed. These interventions highlight the potential for overcoming chemoresistance and improving patient outcomes. By integrating mitochondrial diagnostics with personalized treatment strategies, we propose a roadmap for future research that bridges basic mitochondrial biology with translational applications in oncology. The insights offered in this review emphasize the critical need for continued exploration of mtDNA-targeted therapies to address the unmet needs in EC management and other diseases associated with mitochondria. Full article

Virgin coconut oil (VCO) has emerged as a functional food oil with considerable health benefits and wide applications in the food, pharmaceutical, and cosmetic industries due to its resident bioactive compounds, including lauric acid (LA). LA is the most abundant saturated medium-chain fatty acid in VCO and has been associated with several pharmacological activities. The literatures show the pharmacological effects of VCO and LA on chronic pathologies, infectious diseases, and metabolic disorders. A robust body of evidence shows that LA and other phenolic compounds are responsible for the VCO protection against toxicities and pharmacological efficacies. This review elucidates the anticancer mechanisms of VCO/LA and their modulation of the chemotherapy-induced side effect toxicity. VCO, LA, and their nanomaterial/encapsulated derivatives promote ROS generation, antiproliferation, apoptosis, cell cycle arrest, the inhibition of metastasis, and the modulation of cancer-related signaling pathways for cancer cell death in vivo and in vitro. VCO mitigates oxidative inflammation and apoptosis to block the underlying mechanisms of the side effect toxicity of chemotherapy. However, the possible beneficial effect of LA on the toxicity of chemotherapy is currently unknown. The available evidence emphasizes the anticancer effect and mechanism of VCO and LA, and the VCO potential to combat adverse side effects of chemotherapy. Thus, VCO and LA are potential adjuvant therapeutic agents in the management of various cancers. Nevertheless, future studies should be targeted at elucidating cancer-related molecular mechanisms to bridge the gap in knowledge. Full article

Floods are among the most devastating hydrometeorological natural disasters worldwide, causing massive infrastructure and economic loss in low-lying, flood-prone developing countries like Bangladesh. Effective disaster mitigation relies on organized and detailed flood damage information to facilitate emergency evacuation, coordinate relief distribution, and formulate an effective disaster management policy. Nevertheless, the nation confronts considerable obstacles due to insufficient historical flood damage data and the underdevelopment of near-real-time (NRT) flood monitoring systems. This study addresses this issue by developing a replicable methodology for flood damage assessment and NRT monitoring systems. Using the Google Earth Engine (GEE) platform, we analyzed flood events from 2019 to 2023, integrating geospatial layers such as roads, cropland, etc. Analysis of flood events over the five-year period revealed substantial impacts, with 21.60% of the total area experiencing inundation. This flooding affected 6.92% of cropland and 4.16% of the population. Furthermore, 18.10% of the road network, spanning over 21,000 km within the study area, was also affected. This system has the potential to enhance emergency response capabilities during flood events and inform more effective disaster mitigation policies. Full article

Background: Bipolar disorder (BD) is a chronic and disabling psychiatric condition characterized by recurring episodes of mania, hypomania, and depression. Despite the availability of mood stabilizers, antipsychotics, and antidepressants, long-term management remains challenging due to incomplete symptom control, adverse effects, and high relapse rates. Methods: This paper is a narrative review aimed at synthesizing emerging trends and future directions in the pharmacological treatment of BD. Results: Future pharmacotherapy for BD is likely to shift toward precision medicine, leveraging advances in genetics, biomarkers, and neuroimaging to guide personalized treatment strategies. Novel drug development will also target previously underexplored mechanisms, such as inflammation, mitochondrial dysfunction, circadian rhythm disturbances, and glutamatergic dysregulation. Physiological endophenotypes, such as immune-metabolic profiles, circadian rhythms, and stress reactivity, are emerging as promising translational tools for tailoring treatment and reducing associated somatic comorbidity and mortality. Recognition of the heterogeneous longitudinal trajectories of BD, including chronic mixed states, long depressive episodes, or intermittent manic phases, has underscored the value of clinical staging models to inform both pharmacological strategies and biomarker research. Disrupted circadian rhythms and associated chronotypes further support the development of individualized chronotherapeutic interventions. Emerging chronotherapeutic approaches based on individual biological rhythms, along with innovative monitoring strategies such as saliva-based lithium sensors, are reshaping the future landscape. Anti-inflammatory agents, neurosteroids, and compounds modulating oxidative stress are emerging as promising candidates. Additionally, medications targeting specific biological pathways implicated in bipolar pathophysiology, such as N-methyl-D-aspartate (NMDA) receptor modulators, phosphodiesterase inhibitors, and neuropeptides, are under investigation. Conclusions: Advances in pharmacogenomics will enable clinicians to predict individual responses and tolerability, minimizing trial-and-error prescribing. The future landscape may also incorporate digital therapeutics, combining pharmacotherapy with remote monitoring and data-driven adjustments. Ultimately, integrating innovative drug therapies with personalized approaches has the potential to enhance efficacy, reduce adverse effects, and improve long-term outcomes for individuals with bipolar disorder, ushering in a new era of precision psychiatry. Full article

Background: The progression of Alzheimer’s Disease (AD) deeply affects not only the diagnosed person but also their close relatives, who are often called to take on the role of informal caregivers. This transition is frequently unplanned and emotionally complex, yet poorly understood in its deeper processual dimensions. This study aims to explore and theorize the transition experienced by a family member becoming the primary informal caregiver for a person with advanced AD. Methods: A qualitative study based on the Constructivist Grounded Theory according to Charmaz’s approach (2006) was conducted. In-depth interviews were carried out with 10 participants who had become informal caregivers for a loved one with advanced AD. Data were analyzed using initial coding, focused coding, the constant comparative method, and theoretical coding. Results: Ten caregivers (mean age 39 years, range 35–54; nine females) of patients with advanced AD participated in the study. The analysis revealed a complex, emotionally intense caregiving experience marked by sacrifice, feelings of powerlessness, identity loss, and the necessity of sharing caregiving responsibilities. A core category emerged: A Silent and Certain Willingness to Care, representing the caregivers’ deep, often unconscious commitment to prioritize the care of their loved ones above their own needs. Four interconnected phases characterized the caregiving process: (1) The Changing Daily Life—involving significant sacrifices in personal and social life; (2) Feeling Powerless—confronting the inevitable decline without means to alter the course; (3) Losing Oneself—experiencing physical and psychological exhaustion and a sense of identity loss; and (4) Sharing with Others—seeking external support to sustain caregiving. These findings highlight the evolving nature of becoming a caregiver and the enduring dedication that sustains this role despite the challenges. Conclusions: The progression of AD deeply transforms the lives of caregivers, who become co-sufferers and active participants in the disease’s management. The results underscore the urgency of designing integrative care strategies—including psychological, social, and potentially technological support—that can enhance both patient outcomes and caregiver resilience. Grounded in real-world experiences, this study contributes to the broader neurodegeneration discourse by emphasizing caregiving as a critical factor in long-term disease management and therapeutic success. Full article

Background/Objectives: The advent of tyrosine kinase inhibitors (TKIs) revolutionized the management of chronic myeloid leukemia (CML), achieving survival rates near those of the general population. Despite this success, prolonged therapy presents challenges, including physical, emotional, and financial burdens. Treatment-free remission (TFR), defined as sustained deep molecular response (DMR) after discontinuing TKIs, has emerged as a viable clinical goal. This study evaluates real-world data from the Canary Islands Registry of CML (RCLMC) to explore outcomes, predictors, and the feasibility of TFR. Methods: This retrospective observational study included 393 patients diagnosed with CML-CP between 2007 and 2023. Molecular response was monitored according to international guidelines. Survival probabilities were estimated using the Kaplan–Meier method. Logistic regression analysis was performed to identify predictors of molecular relapses after TKI discontinuation. Results: Of the 383 patients who received TKI treatment, 58.3% achieved molecular response grade 2 (MR2) (BCR-ABL1 ≤ 1%), 95.05% achieved MR2, and 50.5% reached MR4 within the first year. Of the 107 patients attempting TFR, 73.2% maintained remission at 36 months. Relapses occurred in 24 patients, all regaining molecular response upon reintroduction of TKIs. No cases of disease progression were observed. Conclusions: Our findings support the feasibility and safety of TFR in a real-world clinical setting for well-selected patients, with outcomes consistent with international studies. The study underscores the importance of molecular monitoring and patient-specific strategies to optimize outcomes. Full article

Reactive molecules, including oxygen and nitrogen species, serve dual roles in human physiology. While they function as essential signaling molecules under normal physiological conditions, they contribute to cellular dysfunction and damage when produced in excess by normal metabolism or in response to stressors. Oxidative/nitrosative stress is a pathological state, resulting from the overproduction of reactive species exceeding the antioxidant capacity of the body, which is implicated in several chronic human diseases. Antioxidant therapies aimed at restoring redox balance and preventing oxidative/nitrosative stress have demonstrated efficacy in preclinical models. However, their clinical applications have met with inconsistent success owing to efficacy, safety, and bioavailability concerns. This summative review analyzes the role of reactive species in human pathophysiology, the mechanisms of action of antioxidant protection, and the challenges that hinder their translation into effective clinical therapies in order to evaluate potential emerging strategies such as targeted delivery systems, precision medicine, and synergistic therapeutic approaches, among others, to overcome current limitations. By integrating recent advances, this review highlights the value of targeting reactive species in the prevention and management of chronic diseases. Full article

Produce supply chains play a critical role in ensuring fruits and vegetables reach consumers efficiently, affordably, and at optimal freshness. In recent decades, hub-and-spoke network models have emerged as valuable tools for optimizing sustainable cold food supply chains. Traditional optimization efforts typically focus on removing inefficiencies, minimizing lead times, refining inventory management, strengthening supplier relationships, and leveraging technological advancements for better visibility and control. However, the majority of models rely on deterministic approaches that overlook the inherent uncertainties of crop yields, which are further intensified by climate variability. Rising atmospheric CO₂ concentrations, along with shifting temperature patterns and extreme weather events, have a substantial effect on crop productivity and availability. Such uncertainties can prompt distributors to seek alternative sources, increasing costs due to supply chain reconfiguration. This research introduces a stochastic hub-and-spoke network optimization model specifically designed to minimize transportation expenses by determining optimal distribution routes that explicitly account for climate variability effects on crop yields. A use case involving a cold food supply chain (CFSC) was carried out using several weather scenarios based on climate models and real soil data for California. Strawberries were selected as a representative crop, given California’s leading role in strawberry production. Simulation results show that scenarios characterized by increased rainfall during growing seasons result in increased yields, allowing distributors to reduce transportation costs by sourcing from nearby farms. Conversely, scenarios with reduced rainfall and lower yields require sourcing from more distant locations, thereby increasing transportation costs. Nonetheless, supply chain configurations may vary depending on the choice of climate models or weather prediction sources, highlighting the importance of regularly updating scenario inputs to ensure robust planning. This tool aids decision-making by planning climate-resilient supply chains, enhancing preparedness and responsiveness to future climate-related disruptions. Full article

With the popularization of social media, information related to public health events has seen explosive growth online, making it essential to accurately identify informative tweets with decision-making and management value for public health emergency response and risk monitoring. However, existing methods often suffer performance degradation during cross-event transfer due to differences in data distribution, and research specifically targeting public health events remains limited. To address this, we propose the Label Confusion Domain Adversarial Network (LCDAN), which innovatively integrates label confusion with domain adaptation to enhance the detection of informative tweets across different public health events. First, LCDAN employs an adversarial domain adaptation model to learn cross-domain feature representation. Second, it dynamically evaluates the importance of different source domain samples to the target domain through label confusion to optimize the migration effect. Experiments were conducted on datasets related to COVID-19, Ebola disease, and Middle East Respiratory Syndrome public health events. The results demonstrate that LCDAN significantly outperforms existing methods across all tasks. This research provides an effective tool for information detection during public health emergencies, with substantial theoretical and practical implications. Full article

Multi-objective evolutionary algorithms (MOEAs) have emerged as powerful optimization tools for addressing the complex, often conflicting goals present in modern waste disposal systems. This review explores recent advances and practical applications of MOEAs in key areas, including waste collection routing, waste-to-energy (WTE) systems, and facility location and allocation. Real-world case studies from cities like Braga, Lisbon, Uppsala, and Cyprus demonstrate how MOEAs can enhance operational efficiency, boost energy recovery, and reduce environmental impacts. While these algorithms offer significant advantages, challenges remain in computational complexity, adapting to dynamic environments, and integrating with emerging technologies. Future research directions highlight the potential of combining MOEAs with machine learning and real-time data to create more flexible and responsive waste management strategies. By leveraging these advancements, MOEAs can play a pivotal role in developing sustainable, efficient, and adaptive waste disposal systems capable of meeting the growing demands of urbanization and stricter environmental regulations. Full article

Background: Pleural mesothelioma (PM) is a type of cancer that is difficult to diagnose and treat. Patients may have vastly varying prognoses, and prognostic factors may help guide the clinical approach. As a recently identified biomarker, the pan-Immune-Inflammation-Value (PIV) is a simple, comprehensive, and peripheral blood cell-based biomarker. Methods: The present study represents a retrospective observational analysis carried out within a single-center setting. Ninety-five patients with PM stages I–IV were enrolled in the study. We analyzed the correlation between patients’ demographic characteristics, clinicopathological factors such as histological subtypes, surgery status, tumor thickness, blood-based parameters, and treatment options with their prognoses. PIV was calculated by the following formula: (neutrophil count × monocyte count × platelet count)/lymphocyte count. Additionally, blood-based parameters were used to calculate the platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and systemic immune inflammation index (SII). Results: We categorized the patients into two groups, low PIV group (PIV ≤ 732.3) and high PIV group (PIV > 732.3) according to the determined cut-off value, which was defined as the median. It was revealed that high PIV was associated with poor survival outcomes. The median follow-up period was 15.8 months (interquartile range, IQR, 7.1 to 29.8 months). The median overall survival (OS) was significantly longer in patients in the low PIV group (median 29.8 months, 95% confidence interval (CI), 15.6 to 44) than the high PIV group (median 14.7 months, 95% CI, 10.8 to 18.6 p < 0.001). Furthermore, the study revealed that patients with low PIV, NLR, and SII values were more likely to be eligible for surgery and were diagnosed at earlier stages. Additionally, these markers were identified as potential predictors of disease-free survival (DFS) in the surgical cohort and of treatment response across the entire patient population. Conclusions: In addition to well-established clinical factors such as stage, histologic subtype, resectability, and Eastern Cooperative Oncology Group (ECOG) performance status (PS), PIV emerged as an independent and significant prognostic factor of overall survival (OS) in patients with PM. Moreover, PIV also demonstrated a remarkable independent prognostic value for disease-free survival (DFS) in this patient population. Additionally, some clues are provided for conditions such as treatment responses, staging, and suitability for surgery. As such, in this cohort, it has outperformed the other blood-based markers based on our findings. Given its ease of calculation and cost-effectiveness, PIV represents a promising and practical prognostic tool in the clinical management of pleural mesothelioma. It can be easily calculated using routinely available laboratory parameters for every cancer patient, requiring no additional cost or complex procedures, thus facilitating its integration into everyday clinical practice. Full article