Search Results (1,863)

Background/Objectives: Neurodegenerative proteinopathies, such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and dementia with Lewy bodies (DLB), are increasingly prevalent worldwide mainly due to population aging. These conditions are marked by complex etiologies, overlapping pathologies, and progressive clinical decline, with significant consequences for patients, caregivers, and healthcare systems. This review aims to synthesize evidence on the healthcare complexities of major neurodegenerative proteinopathies to highlight current knowledge gaps, and to inform future care models, policies, and research directions. Methods: We conducted a comprehensive literature search in PubMed/MEDLINE using combinations of MeSH terms and keywords related to neurodegenerative diseases, proteinopathies, diagnosis, sex, management, treatment, caregiver burden, and healthcare delivery. Studies were included if they addressed the clinical, pathophysiological, economic, or care-related complexities of aging-related neurodegenerative proteinopathies. Results: Key themes identified include the following: (1) multifactorial and unclear etiologies with frequent co-pathologies; (2) long prodromal phases with emerging biomarkers; (3) lack of effective disease-modifying therapies; (4) progressive nature requiring ongoing and individualized care; (5) high caregiver burden; (6) escalating healthcare and societal costs; and (7) the critical role of multidisciplinary and multi-domain care models involving specialists, primary care, and allied health professionals. Conclusions: The complexity and cost of neurodegenerative proteinopathies highlight the urgent need for prevention-focused strategies, innovative care models, early interventions, and integrated policies that support patients and caregivers. Prevention through the early identification of risk factors and prodromal signs is critical. Investing in research to develop effective disease-modifying therapies and improve early detection will be essential to reducing the long-term burden of these disorders. Full article

Background: Delirium is a common, underdiagnosed neuropsychiatric syndrome in older adults, associated with high mortality and functional decline. Given its multifactorial nature and overlap with frailty, radiological markers may improve risk stratification in the emergency department (ED). Methods: We conducted a retrospective study on a small sample of 30 patients diagnosed with delirium in the emergency department who had recently undergone brain, thoracic, or abdominal CT scans for unrelated clinical indications. Using post-processing software, we analyzed radiological markers, including coronary artery calcifications (to estimate vascular age), cerebral atrophy (via the Global Cortical Atrophy scale), and cachexia (based on abdominal fat and psoas muscle volumetry). Results: Five domains were identified as significant predictors of 12-month mortality in univariate Cox regression: vascular age, delirium etiology, cerebral atrophy, delirium subtype (hyperactive vs. hypoactive), and cachexia. Based on these domains, we developed an exploratory 10-point delirium score. This score demonstrated acceptable diagnostic accuracy for mortality prediction (sensitivity 0.93, specificity 0.73, positive predictive value 0.77, negative predictive value 0.91) in this limited cohort. Conclusions: While preliminary and based on a small, retrospective sample of 30 patients, this multidimensional approach integrating clinical and radiological data may help improve risk stratification in elderly patients with delirium. Radiological phenotyping, particularly in terms of vascular aging and sarcopenia/cachexia, offers objective insights into patient frailty and could inform more personalized treatment pathways from the ED to safe discharge home, pending further validation. Full article

Wheat is one of the important grain crops, and spike counting is crucial for predicting spike yield. However, in complex farmland environments, the wheat body scale has huge differences, its color is highly similar to the background, and wheat ears often overlap with each other, which makes wheat ear detection work face a lot of challenges. At the same time, the increasing demand for high accuracy and fast response in wheat spike detection has led to the need for models to be lightweight function with reduced the hardware costs. Therefore, this study proposes a lightweight wheat ear detection model, CML-RTDETR, for efficient and accurate detection of wheat ears in real complex farmland environments. In the model construction, the lightweight network CSPDarknet is firstly introduced as the backbone network of CML-RTDETR to enhance the feature extraction efficiency. In addition, the FM module is cleverly introduced to modify the bottleneck layer in the C2f component, and hybrid feature extraction is realized by spatial and frequency domain splicing to enhance the feature extraction capability of wheat to be tested in complex scenes. Secondly, to improve the model’s detection capability for targets of different scales, a multi-scale feature enhancement pyramid (MFEP) is designed, consisting of GHSDConv, for efficiently obtaining low-level detail information and CSPDWOK for constructing a multi-scale semantic fusion structure. Finally, channel pruning based on Layer-Adaptive Magnitude Pruning (LAMP) scoring is performed to reduce model parameters and runtime memory. The experimental results on the GWHD2021 dataset show that the ${\mathrm{AP}}_{50}$ of CML-RTDETR reaches 90.5%, which is an improvement of 1.2% compared to the baseline RTDETR-R18 model. Meanwhile, the parameters and GFLOPs have been decreased to 11.03 M and 37.8 G, respectively, resulting in a reduction of 42% and 34%, respectively. Finally, the real-time frame rate reaches 73 fps, significantly achieving parameter simplification and speed improvement. Full article

Background/Objectives: Hepatic cancers, including hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), are major global health concerns due to rising incidence and limited therapeutic success. While traditional risk factors include chronic liver disease and environmental exposures, recent evidence underscores the significance of genetic alterations and gut microbiota in liver cancer development and progression. This review aims to integrate emerging knowledge on the interplay between host genomic changes and gut microbial dynamics in the pathogenesis and treatment of hepatic cancers. Methods: We conducted a comprehensive review of current literature on genetic and epigenetic drivers of HCC and CCA, focusing on commonly mutated genes such as TP53, CTNNB1, TERT, IDH1/2, and FGFR2. In parallel, we evaluated studies addressing the gut–liver axis, including the roles of dysbiosis, microbial metabolites, and immune modulation. Key clinical and preclinical findings were synthesized to explore how host–microbe interactions influence tumorigenesis and therapeutic response. Results: HCC and CCA exhibit distinct but overlapping genomic landscapes marked by recurrent mutations and epigenetic reprogramming. Alterations in the gut microbiota contribute to hepatic inflammation, genomic instability, and immune evasion, potentially enhancing oncogenic signaling pathways. Furthermore, microbiota composition appears to affect responses to immune checkpoint inhibitors. Emerging therapeutic strategies such as probiotics, fecal microbiota transplantation, and precision oncology based on mutational profiling demonstrate potential for personalized interventions. Conclusions: The integration of host genomics with microbial ecology provides a promising paradigm for advancing diagnostics and therapies in liver cancer. Targeting the gut–liver axis may complement genome-informed strategies to improve outcomes for patients with HCC and CCA. Full article

Background: Aortic stenosis (AS) has long been considered a degenerative disease and is typically diagnosed in older men at an advanced stage. However, accumulating evidence has highlighted the similarities between AS and atherosclerosis, particularly regarding shared risk factors and overlapping pathophysiological mechanisms. This connection has led to a paradigm shift, suggesting that AS may be preventable in its early stages. Methods: This narrative review synthesizes the existing literature exploring the parallels between AS and atherosclerosis, focusing on common risk factors, pathogenic pathways, and evolving therapeutic strategies. Clinical trials and translational studies were examined to assess the effectiveness of atherosclerosis-based treatments for AS. Results: Multiple studies have confirmed the shared inflammatory, lipid-mediated, and calcific mechanisms of AS and atherosclerosis. Despite these similarities, therapeutic strategies effective in atherosclerosis, such as statin therapy, have not consistently shown benefits in AS. New medical approaches aim to delay aortic valve replacement and reduce the associated morbidity. The partially overlapping pathogenesis continues to guide future research. Conclusions: While AS and atherosclerosis share several pathogenic features, their clinical courses and treatment responses diverge. Understanding the limits and potential of their overlap may inform future preventive and therapeutic strategies. Earlier detection and targeted intervention in AS remain key goals, drawing on insights from cardiovascular disease management. Full article

This study aimed to re-evaluate a historical war supply route within the context of cultural tourism, to revitalize its natural, historical, and cultural values, and to integrate it with existing hiking and trekking routes. Remote sensing (RS) and geographic information system (GIS) technologies were utilized, and land surveys were conducted to support the analysis and validate the existing data. Data for slope, one of the most critical factors for hiking route selection, were generated, and the optimal route between the starting and destination points was identified using least cost path analysis (LCPA). Historical, touristic, and recreational rest stops along the route were mapped with precise coordinates, and both the existing and the newly generated routes were assessed in terms of their accessibility to these points. Field validation was carried out based on the experiences of expert hikers. According to the results, the length of the existing hiking route was determined to be 15.72 km, while the newly developed trekking route measured 17.36 km. These two routes overlap for 7.75 km, with 9.78 km following separate paths in a round-trip scenario. It was concluded that the existing route is more suitable for hiking, whereas the newly developed route is better suited for trekking. Full article

The morphological diversity of Moroccan honey bees (Apis mellifera) was investigated using geometric morphometrics to assess wing venation patterns among three populations representing three climatic zones: desert, semiarid, and Mediterranean. A total of 193 honey bee samples were analyzed and compared to historical reference samples from the Morphometric Bee Data Bank in Oberursel, representing the three subspecies: A. m. intermissa, A. m. sahariensis, and A. m. major. Principal component analysis and linear discriminant analysis revealed significant, yet overlapping morphological differences among the climatic groups. Spatial modeling showed a significant southwest–northeast clinal gradient in wing morphology. Almost all samples were assigned to the African evolutionary lineage, except one, suggesting a dominant African genetic background. Interestingly, all three populations showed greater morphological affinity to A. m. intermissa than to A. m. sahariensis, which could indicate introgression or limitations in the current reference dataset. These discrepancies highlight the necessity of revising subspecies boundaries using updated morphometric and genomic approaches. These findings improve our understanding of honey bee biodiversity in Morocco and provide valuable information for conservation and breeding programs. Full article

Driven by the rapid development of e-commerce and intelligent logistics, the volume of express delivery services has surged, making the efficient and accurate identification of shipping information a core requirement for automatic sorting systems. However, traditional Optical Character Recognition (OCR) technology struggles to meet the accuracy and real-time demands of complex logistics scenarios due to challenges such as image distortion, uneven illumination, and field overlap. This paper proposes a three-level collaborative recognition method based on deep learning that facilitates structured information extraction through regional normalization, dual-path parallel extraction, and a dynamic matching mechanism. First, the geometric distortion associated with contour detection and the lightweight direction classification model has been improved. Second, by integrating the enhanced YOLOv5s for key area localization with the upgraded PaddleOCR for full-text character extraction, a dual-path parallel architecture for positioning and recognition has been constructed. Finally, a dynamic space–semantic joint matching module has been designed that incorporates anti-offset IoU metrics and hierarchical semantic regularization constraints, thereby enhancing matching robustness through density-adaptive weight adjustment. Experimental results indicate that the accuracy of this method on a self-constructed dataset is 89.5%, with an F1 score of 90.1%, representing a 24.2% improvement over traditional OCR methods. The dynamic matching mechanism elevates the average accuracy of YOLOv5s from 78.5% to 89.7%, surpassing the Faster R-CNN benchmark model while maintaining a real-time processing efficiency of 76 FPS. This study offers a lightweight and highly robust solution for the efficient extraction of order information in complex logistics scenarios, significantly advancing the intelligent upgrading of sorting systems. Full article

Aging in sexually reproducing organisms is shaped by the declining force of natural selection after reproduction begins. In Drosophila melanogaster, experimental evolution shows that altering the age of reproduction shifts the timing of aging. Using the Drosophila experimental evolution population (DEEP) resource, which includes long- and short- lived populations evolved under distinct reproductive schedules, we investigated how immune defense against Beauveria bassiana changes with age and evolved lifespan. We tested survival post-infection at multiple ages and examined genomic differentiation for immune-related genes. Both population types showed age-related declines in immune defense. Long-lived populations consistently exhibited age-specific defense when both long- and short-lived populations were tested. Genomic comparisons revealed thousands of differentiated loci, yet no enrichment for canonical immune genes or overlap with gene sets from studies of direct selection for immunity. These results suggest that enhanced immune defense can evolve alongside extended lifespan, likely via general physiological robustness rather than traditional immune pathways. A more detailed analysis may reveal that selection for lifespan favors tolerance-based mechanisms that reduce infection damage without triggering immune activation, in contrast to direct selection for resistance. Our findings demonstrate the utility of experimentally evolved populations for dissecting the genetic architecture of aging and immune defense to inform strategies to mitigate age-related costs associated with immune activation. Full article

Background/Objectives: Executive function (EF) difficulties are increasingly recognized as closely linked to ADHD, particularly when assessed via rating scales. Methods: The present study investigated the nature of these associations, using the Conners 3 Rating Scales to assess ADHD symptoms and the Executive Function Questionnaire (EFQU) to assess EF impairments, in a sample of 1068 children (40.8% males, 38.8% females) aged 7–14 years (M = 10.7, SD = 1.74). Results: Both parent and teacher ratings revealed strong correlations, particularly between inattentive symptoms and EF difficulties, across multiple executive domains. To examine whether these associations stemmed from construct or phrasing overlap, exploratory and confirmatory factor analyses were conducted. The results demonstrate that the Conners 3 and the EFQU capture distinct latent dimensions of functioning, with virtually no overlap in item content. Conclusions: The strength and consistency of the associations between these latent factors support the interpretation that, although conceptually distinct, ADHD symptoms and EF impairments are empirically intertwined in everyday functioning, as consistently reported by both parents and teachers. Interestingly, teachers provided more integrated views of behavior, while parents tended to distinguish ADHD and EF traits more clearly. These findings underscore the importance of multi-informant assessment and contextual variability in understanding children’s functioning. Full article

Idiopathic pulmonary fibrosis (IPF) is a progressive fibrosing lung disease characterized by chronic inflammation, vascular remodeling, and immune dysregulation. COVID-19, caused by SARS-CoV-2, shares several systemic immunohematologic disturbances with IPF, including cytokine storms, endothelial injury, and prothrombotic states. Unlike general comparisons of viral infections and chronic lung disease, this review offers a focused analysis of the shared hematologic and immunologic mechanisms between COVID-19 and IPF. Our aim is to better understand how SARS-CoV-2 infection may worsen disease progression in IPF and identify converging pathophysiological pathways that may inform clinical management. We conducted a narrative synthesis of the peer-reviewed literature from PubMed, Scopus, and Web of Science, focusing on clinical, experimental, and pathological studies addressing immune and coagulation abnormalities in both COVID-19 and IPF. Both diseases exhibit significant overlap in inflammatory and fibrotic signaling, particularly via the TGF-β, IL-6, and TNF-α pathways. COVID-19 amplifies coagulation disturbances and endothelial dysfunction already present in IPF, promoting microvascular thrombosis and acute exacerbations. Myeloid cell overactivation, impaired lymphocyte responses, and fibroblast proliferation are central to this shared pathophysiology. These synergistic mechanisms may accelerate fibrosis and increase mortality risk in IPF patients infected with SARS-CoV-2. This review proposes an integrative framework for understanding the hematologic and immunologic convergence of COVID-19 and IPF. Such insights are essential for refining therapeutic targets, improving prognostic stratification, and guiding early interventions in this high-risk population. Full article

This study provides a comprehensive assessment and synthesis of the literature on short-selling. It performs a lexicometric analysis, providing a quantitative review of 1093 peer-reviewed journal articles to identify and illustrate the main themes in short-selling research. Almost half the published literature on short-selling is thematically clustered around portfolio management techniques. Other key themes involve short-selling as it relates to risk management, strategic management, and market irregularities. Descending hierarchical classification examines the overall structure of the textual corpus of the short-selling literature and the relationships between its key terms. Similarity analysis reveals that the short-selling literature is highly concentrated, with most conceptual groups closely aligned and fitting into overlapping or conceptually similar areas. Some notable groups highlight prior short-selling studies of market dynamics, behavioral factors, technological advancements, and regulatory frameworks, which can serve as a foundation for market regulators to make more informed decisions that enhance overall market stability. Additionally, this study proposes a conceptual framework in which short-selling can be either a driver or an outcome by integrating the literature on its antecedents, consequences, explanatory variables, and boundary conditions. Finally, it suggests directions for future research. Full article

Swirl spray combustion has attracted significant attention due to its common usage in gas turbines. However, the high pressure in many practical applications remains a major obstacle to the deep understanding of flame stability and pollutant formation. To address this concern, this study investigated a swirl spray flame fueled with n-decane at elevated pressure. Planar laser-induced fluorescence (PLIF) of OH and polycyclic aromatic hydrocarbons (PAHs) were used simultaneously, enabling the distinction of the locations of OH, PAHs, and mixtures of them, providing detailed information on flame structure and evolution of PAHs. The effects of swirl number and ambient pressure on reaction zone characteristics and PAHs’ formation were studied, with the swirl number ranging from 0.30 to 1.18 and the pressure ranging from 1 to 3 bar. The data suggest that the swirl number changes the flame structure from V-shaped to crown-shaped, as observed at both atmospheric and elevated pressures. Additionally, varying swirl numbers lead to the initiation of flame divergence at distinct pressure levels. Moreover, PAHs of different molecular sizes exhibit significant overlap, with larger PAHs able to further extend downstream. The relative concentration of PAH increased with pressure, and the promoting effect of pressure on producing larger PAHs was significant. Full article

Background: The emergency department (ED) often represents the entry point to care for patients that require urgent medical attention or have no alternative for medical treatment. This has implications on scope of practice and how quality of care is measured. A diverse array of methodologies has been developed to evaluate the quality of clinical care and broadly includes quality improvement (QI), quality assurance (QA), observational research (OR) and clinical quality registries (CQRs). Considering the overlap between QI, QA, OR and CQRs, we conceptualized a modular framework for TECOR to effectively and efficiently streamline clinical quality evaluations. Streamlining is both appropriate and justified as it reduces redundancy, enhances clarity and optimizes resource utilization, thereby allowing clinicians to focus on delivering high-quality patient care without being overwhelmed by excessive data and procedural complexities. The objective of this study is to describe the process for designing a modular framework for ED CQRs using TECOR as a case study. Methods: We performed a scoping audit of all quality projects performed in our ED over a 1-year period (1 January 2021 to 31 December 2021) as well as data mapping and categorical formulation of key themes from the TECOR dataset with clinical data sources. Both these processes then informed the design of TECOR. Results: For the audit of quality projects, we identified 29 projects. The quality evaluation methodologies for these projects included 12 QI projects, 5 CQRs and 12 OR projects. Data mapping identified that clinical information was fragmented across 11 distinct data sources. Through thematic analysis during data mapping, we identified three extraction techniques: self-extractable, manual entry and on request. Conclusions: The modular framework for TECOR aims to enable an efficient streamlined approach that caters to all aspects of clinical quality evaluation to enable higher throughput of clinician-led quality evaluations and improvements. TECOR is also an essential component in the development of a learning health system to drive evidence-based practice and the subject of future research. Full article

Triple-negative breast cancer (TNBC) remains a major clinical challenge due to its aggressive behavior and lack of targeted therapies. Accurate early prediction of response to neoadjuvant chemotherapy (NACT) is essential for guiding personalized treatment strategies and improving patient outcomes. In this study, we present an attention-based multiple instance learning (MIL) framework designed to predict pathologic complete response (pCR) directly from pre-treatment hematoxylin and eosin (H&E)-stained biopsy slides. The model was trained on a retrospective in-house cohort of 174 TNBC patients and externally validated on an independent cohort (n = 30). It achieved a mean area under the curve (AUC) of 0.85 during five-fold cross-validation and 0.78 on external testing, demonstrating robust predictive performance and generalizability. To enhance model interpretability, attention maps were spatially co-registered with multiplex immunohistochemistry (mIHC) data stained for PD-L1, CD8+ T cells, and CD163+ macrophages. The attention regions exhibited moderate spatial overlap with immune-enriched areas, with mean Intersection over Union (IoU) scores of 0.47 for PD-L1, 0.45 for CD8+ T cells, and 0.46 for CD163+ macrophages. The presence of these biomarkers in high-attention regions supports their biological relevance to NACT response in TNBC. This not only improves model interpretability but may also inform future efforts to identify clinically actionable histological biomarkers directly from H&E-stained biopsy slides, further supporting the utility of this approach for accurate NACT response prediction and advancing precision oncology in TNBC. Full article