Browse Articles

Machine learning based analysis of leucocyte cell population data by Sysmex XN series hematology analyzer for the diagnosis of bacteremia

High-gravitational effect on process stabilization evaluation for material extrusion using polylactic acid filament

Deep neural network approach integrated with reinforcement learning for forecasting exchange rates using time series data and influential factors

Impact of massive open online courses in higher education using machine learning and decision based fuzzy frank power aggregation operators models

Flavonoids from Polygonum hydropiper L. regulate PCV2-induced oxidative stress of RAW264.7 cells via Pi3k/AKT and Nrf2/HO-1 signaling pathways

A hybrid reinforcement learning and knowledge graph framework for financial risk optimization in healthcare systems

An improved EAE-DETR model for defect detection of server motherboard

Analysing community-level spending behaviour contributing to high carbon emissions using stochastic block models

Abstract Large financial transaction datasets are increasingly used to estimate carbon emissions associated with individual spending. However, to effectively target high-emission spending areas and implement successful carbon reduction strategies, policymakers and financial institutions need to understand individual consumer spending behaviour. In this study, we describe an approach to identify spending patterns in large financial transaction datasets, using stochastic block modelling for community detection on a bipartite network. This is an effective method to form communities of consumers who share similar spending patterns across merchant categories, allowing us to identify the categories causing high carbon emissions for each group of consumers. We also introduce a modification to the weights of the bipartite network which allows us to keep the average community spending constant across different categories. The impact and applications of this study are twofold. First, it highlights the importance of transaction datasets and stochastic block modelling in providing insights for financial institutions in their efforts to decarbonise by identifying areas for targeted behavioural strategies for carbon reduction. Second, it provides researchers with a framework to examine how different factors, such as consumer spending patterns, energy usage, or transportation habits, interact with one another. This is done while keeping overall spending levels consistent across various communities, allowing for a controlled analysis of behavioural and economic impacts on carbon reduction efforts.

Reproducible Ala-Gly oligomerization catalyzed by the natural Borate colemanite in prebiotic conditions

Quantum computation for robot posture optimization

Dual branch attention network for image super-resolution

Abstract The advancement of deep convolutional neural networks (CNNs) has resulted in remarkable achievements in image super-resolution methods utilizing CNNs. However, these methods have been limited by a narrow perceptual field and often require a high number of parameters and computational complexity, making them unsuitable for resource-constrained devices. Recently, the Transformer architecture has shown significant potential in image super-resolution due to its ability to perceive global features. Yet, the quadratic computational complexity of self-attention mechanisms in these Transformer-based methods leads to substantial computational and parameter overhead, limiting their practical application. To address these challenges, we introduce the Dual Branch Attention Network (DBAN), a novel Transformer model that integrates prior knowledge from traditional dictionary learning with the global feature perception capabilities of Transformers, enabling image super-resolution. Our model features a ”token dictionary” mechanism that uses auxiliary labeling to provide external prior information, enhancing cross-attention and self-attention computations while maintaining a linear relationship between computational complexity and image size. We also propose a Feature Aggregation Module (FAM) that efficiently extracts local contextual information and performs channel feature fusion, substantially enhancing the model’s performance and efficiency. By reasonably arranging the number of modules and the depth of the network, we reduce the complexity of the model. Extensive experiments have demonstrated that our DBAN achieves excellent performance.

Evaluation of protection benefit of sand barrier fence with different heights on desert highway

As the first barrier of desert highway protection, sand-blocking fence is very important to the safety of the line. Based on the background of Wuma Expressway, this paper uses CFD numerical simulation to study the wind and sand-blocking effect of sand-blocking fence with different heights. The results show that: (1) Between the first and second sand-blocking fences, when the height of sand-blocking fence is 2m, 2.5m, 3.0m and 3.5m, the wind speed near the surface (0.1m ~ 0.3m) is reduced by 87% ~ 97% of the initial wind speed. Between the second and third sand-blocking fences, when the height of sand-blocking fence is 2.5m, the increase of wind speed is 13.87% lower than that of 2m height. The decrease is the largest, and sand particles are easy to deposit here in large quantities. When the height is 2.5m and above, the windbreak efficiency is greater than 90%, and the windbreak effect is significantly improved. (2) The change of sand barrier height has a significant effect on the windbreak efficiency between the second and third sand barriers. (3) Among the three sand-blocking fences, when the height of the sand-blocking fence is 2.5m, the thickness of the sand is 50.51% and 58.33% higher than that of the 2m high sand-blocking fence, and the sand-blocking effect is the most significant. After the height is increased to 3.5m, the thickness of the sand is no longer increased. (4) The height of sand-blocking fence is 2.5m, and the area of sand at the top of embankment is obviously reduced. The area of sand volume fraction 0.55–0.6 is 73.44% lower than that of 2m sand-blocking fence, and the effect of wind and sand prevention is the best.

Modulation of growth characteristics and endogenous hormone by cutting intensity in Eleutherococcus giraldii

Eleutherococcus giraldii (E. giraldii) is a quintessential medicinal plant in traditional Chinese medicine. This study established control, heavy pruning, and light pruning groups to reveal growth indexes and endogenous phytohormones in cultivated E. giraldii using enzyme-linked immunosorbent assay (ELISA). Results indicated that light pruning significantly promoted length of new branch elongation, thereby increasing E. giraldii branch bark yield. In contrast, heavy pruning inhibited length of new branch elongation and reduced branch bark production. Both pruning intensities enhanced the number and length of newly sprouted clonal plants, facilitating population expansion of E. giraldii. The heavy pruning altered the trends of indoleacetic acid (IAA) and abscisic acid (ABA) in apical leaves, as well as IAA and gibberellic acid 3 (GA3) in lateral leaves. The light pruning modified the trends of IAA, ABA, and isopentenyl adenine nucleoside (iPA) in apical leaves, as well as IAA and GA3 in lateral leaves. Apical leaf IAA promoted new branch growth in E. giraldii, while lateral leaf IAA exhibited the opposite effect. iPA played a significant role in eliminating apical dominance and enhancing stress resistance in E. giraldii. GA3 inhibited new branch growth while delaying leaf senescence. Apical leaf ABA was closely associated with improved stress resistance, whereas lateral leaf ABA primarily inhibited new branch growth. This study provides valuable insights for establishing sustainable logging strategies for E. giraldii, protecting wild resources, and offers reference for research on endogenous hormone responses in shrubs under logging interventions.

Commonalities and distinctions of pediatric patient and family engagement in clinical care, education, and research contexts: Protocol for a scoping review

Background Pediatric patient and family engagement is an active and collaborative process, that involves children, adolescents, and family members with lived experience contributing to the design, implementation, and evaluation of healthcare services. Prior studies have highlighted the patient engagement methods and impact in clinical care, education, and research. However, gaps remain in understanding the commonalities and distinctions of engagement approaches, patient/family partner roles, and outcomes in clinical care, education, and research contexts. Further, research examining the nuances of pediatric patient and family engagement within healthcare delivery, education, and research in pediatric institutions is needed to streamline efforts. Objective This scoping review will identify the commonalities of and distinctions between pediatric patient and family engagement in clinical care, education, and research contexts in pediatric healthcare institutions. Methods A scoping review, conducted in collaboration with a team of adolescent, young adult, and family partners, will allow us to systematically map out key concepts, evidence, and knowledge gaps regarding pediatric patient and family engagement in clinical care, education, and research. We will follow the Joanna Briggs Institute framework in the design and conduct of the review and guidance on engaging knowledge users within scoping reviews. The protocol for this scoping review has been registered with the Open Science Framework database (https://osf.io/63qx5). Results This study will describe the engagement types, approaches, and outcomes of pediatric patient and family engagement employed within clinical care, education, and research settings, highlighting commonalities and distinctions across contexts. In doing so, it will identify potential opportunities for collaboration and resource-sharing based on the context of engagement and provide needed clarity on streamlining pediatric patient and family engagement approaches within pediatric institutional settings. Conclusions It is anticipated that the results will produce preliminary evidence of relevance to pediatric institutions seeking to consolidate engagement practices across clinical care, education, and research domains.

Increasing the feasibility, impact, and equity of the Medicare Annual Wellness Visit (AWV) with a practice tailored AWV intervention: A stepped wedge clinical trial protocol

Background Older adults vastly underutilize evidence-based preventive health services and screenings that reduce illness, morbidity and mortality. The free-to-patient Medicare Annual Wellness Visit (AWV) is an opportunity to enhance preventive healthcare use, but also is underused. Objectives To evaluate the effect of a practice-tailored intervention on the sustained use of Medicare AWVs and on guideline-recommended preventive services and racial/ethnic disparities in 3 types of practice settings. Methods This is a stepped wedge cluster randomized controlled trial. The intervention will be implemented at the practice level in 24 primary care practices across the country (8 community-based, 8 academic, and 8 serving medically underserved populations). Electronic health record data will be used to assess changes in AWV and preventive service delivery rates and racial, ethnic, and gender disparities. Semi-structured interviews will be conducted with clinicians/staff and patients, and clinicians will be surveyed to assess the process and acceptability of the intervention. The protocol is registered on clinicaltrials.gov (NCT05910736). Results Analyses will determine the effect of the intervention on AWV visit and preventive health services use at 12- and 24-months post-intervention implementation. Additional analyses will evaluate the effect of the intervention on reducing racial/ethnic disparities. Conclusions A practice-tailored intervention has the potential to increase use of AWVs and preventive health services, and reduce racial/ethnic disparities, in diverse practice settings.

Glial reactivity and cognitive decline follow chronic heterochromatin loss in neurons

Abstract In aging cells and animal models of premature aging, heterochromatin loss coincides with transcriptional disruption including the activation of normally silenced endogenous retroviruses (ERVs). Here we show that loss of heterochromatin maintenance and de-repression of ERVs result in a chronic inflammatory environment characterized by neurodegeneration and cognitive decline in mice. We identify distinct roles for HP1 proteins to ERV silencing where HP1γ is necessary and sufficient for H4K20me3 deposition and HP1β deficiency causes aberrant DNA methylation. Combined loss of HP1β and HP1γ results in loss of DNA methylation at ERVK elements. Progressive ERV de-repression in HP1β/γ DKO mice is followed by stimulation of the integrated stress response, an increase of Complement 3+ reactive astrocytes and phagocytic microglia. This chronic inflammatory state coincides with age-dependent reductions in dendrite complexity and cognition. Our results demonstrate the importance of preventing loss of epigenetic maintenance that is necessary for protection of postmitotic neuronal genomes.

Perceived stress and allostatic load: Results from the All of Us Research Program

The rising prevalence of individuals reporting extreme stress has major public health implications as it increases vulnerability to accelerated premature biological aging, thus increasing risk of chronic disease. To examine the impact of stress on premature biological aging, we assessed the association between exposure to increased stress, quantified by the Perceived Stress Scale, and odds of high allostatic load (AL). To illuminate previously unexplored socio-contextual factors, we controlled for self-reported individual and neighborhood social determinants of health that included discrimination, loneliness, food insecurity, neighborhood disorder, and neighborhood social cohesion. We utilized a cross-sectional design to examine the association between perceived stress and AL among 7,415 participants ages 18–65 in the All of Us Research Program, who enrolled from 2017–2022. We used logistic regression to evaluate the association between stress and high AL, controlling for sociodemographic factors and self-reported social determinants of health. Participants who were younger, receiving Medicaid, or Hispanic had increased prevalence of high stress. High stress was associated with elevated odds of high AL in age and sex-adjusted models (OR=2.18, 95%CI = 1.78, 2.66, high stress vs. low), an association which remained significant after adjusting for social determinants of health (OR=1.29, 95%CI = 1.01, 1.65). Using restricted cubic splines, high stress was significantly associated with increased odds of high AL, even after controlling for upstream individual and neighborhood-level determinants of health. While individuals living below the medium poverty-to-income ratio demonstrated little appreciable association between high stress and increased odds of high allostatic load, those living above the median poverty-to-income ratio reporting increased stress appeared to have increased odds of high allostatic load. Through addressing the upstream factors causing undue burdens of stress, which particularly affect marginalized communities and younger generations, we can begin to address premature biological aging and the comorbid conditions it accompanies.

Early Locus Coeruleus noradrenergic axon loss drives olfactory dysfunction in Alzheimer’s disease

Abstract Alzheimer’s disease (AD) often begins with non-cognitive symptoms such as olfactory deficits, which can predict later cognitive decline, though the mechanisms remain unclear. Pathologically, the brainstem locus coeruleus (LC), the main source of the neurotransmitter noradrenalin (NA) modulating olfactory information processing is affected early. Here we show early and distinct loss of noradrenergic input to the olfactory bulb (OB) coinciding with impaired olfaction in an AD mouse model, before appearance of amyloid plaques. Mechanistically, OB microglia recognize and phagocytose LC axons. Reducing phagocytosis genetically preserves LC axons and olfaction. Prodromal AD patients display elevated TSPO-PET signals in the OB, similarly to App NL-G-F mice. We further confirm early LC axon degeneration in post-mortem OBs in patients with early AD. Our findings reveal a mechanism linking early LC damage to hyposmia in AD, suggesting olfactory testing and neurocircuit imaging for early diagnosis and enable timely therapeutic intervention for Alzheimer’s disease.

Psychoeducation Group for Depression (PEG-D): Study protocol for a prospective, randomized, single-blind, crossover trial

Background Considered a leading contributor to the global health burden, depression is characterized by its multifaceted nature. Recognizing the limitations of pharmacological treatments, non-pharmacological alternatives have been suggested to enhance full remission and increase quality of life. Aim To contribute to this field, we aim to develop and investigate the efficacy of a short psychoeducational program as an adjunctive treatment for depression. Methods/design We propose a single-center, prospective, crossover, single blind, randomized controlled trial, with 190 patients diagnosed with Major Depressive Disorder-MDD (DSM-5-TR), and moderate or intense severity by Hamilton Depression Rating Scale -HAMD-17. Participants will be randomly assigned to one of two arms, Treatment as usual (TAU) + Psychoeducation (n = 96) or TAU (n = 96). The psychoeducational program will consist of six weekly group sessions (6–10 participants) with each session lasting 90 minutes, covering information and techniques for identifying and coping with depression. Reduction in depressive levels, measured by the Beck Depression Inventory-BDI-II, and an increase in their level of knowledge on depression will be considered our primary outcome. Secondary outcomes, such as improvement in functionality and quality of life, will be measured by the Global Functioning Rating Scale (GAF), Clinical Global Impression Scale, and cognitive and behavioral factors by the Cognitive and Behavioral Avoidance Scale-CBAS, and Thoughts Scale Depressants-DTS (EPD). Discussion Developing and validating a structured psychoeducational program for depression is crucial for understanding the contribution of psychoeducation for depression and to facilitate the replication of findings, if positive. If our program demonstrates efficacy-superiority compared to TAU treatment, it might present as an interesting, cost-effective alternative as an adjunctive treatment. An expansion to other modalities, including open groups, euthymic patients, and online formats, might be considered, depending on our results. Trial registration NCT06467474

Regional heterogeneity of the blood-brain barrier

Abstract The blood-brain barrier (BBB), formed by specialized endothelial cells (ECs), regulates the extracellular composition of the central nervous system (CNS). Little is known about whether there are regional specializations of the BBB that may control the function of specific neural circuits. We use single cell RNA-seq to characterize ECs from nine CNS regions in male mice: cortex, hippocampus, cerebellum, spinal cord, striatum, thalamus, hypothalamus, midbrain, and medulla/pons. Although there is a core BBB transcriptional profile, there are significant regional specializations. Stra6, a retinoid transporter, is highly enriched in the BBB of the nucleus accumbens shell (ShNAc) and ventral cochlear nucleus, and is controlled by dietary vitamin A, through endothelial RARƔ. EC Stra6 regulates the deposition of retinoids specifically in the ShNAc and cochlear nucleus, and is required for the function of the ShNAc, in a retinoid-dependent manner. Thus regional specializations of the BBB can regulate the function of local brain regions.