Generation gap

BACKGROUND: The generation of research evidence and knowledge in primary health care (PHC) is crucial for informing the development and implementation of interventions and innovations and driving health policy, health service improvements, and potential societal changes. PHC research has broad effects on patients, practices, services, population health, community, and policy formulation. The in-depth exploration of the definition and measures of research impact within PHC is essential for broadening our understanding of research impact in the discipline and how it compares to other health services research...

To enhance the appeal and informativeness of data news, there is an increasing reliance on data analysis techniques and visualizations, which poses a high demand for journalists' abilities. While numerous visual analytics systems have been developed for deriving insights, few tools specifically support and disseminate viewpoints for journalism. Thus, this work aims to facilitate the automatic creation of sports news from natural language insights. To achieve this, we conducted an extensive preliminary study on the published sports articles...

OBJECTIVES: Confocal laser endomicroscopy (CLE) is an optical method that enables microscopic visualization of oral mucosa. Previous studies have shown that it is possible to differentiate between physiological and malignant oral mucosa. However, differences in mucosal architecture were not taken into account. The objective was to map the different oral mucosal morphologies and to establish a "CLE map" of physiological mucosa as baseline for further application of this powerful technology...

For plant protection products applied as seed treatments, the risk to birds and mammals possibly feeding on such treated seeds needs to be addressed in the EU, in order to register these products for commercial use. For this purpose, the European Food Safety Food Authority (EFSA) has provided guidance on how to execute such a risk assessment. The risk assessment follows a tiered approach. In the Tier 1 risk assessment of the EFSA guidance (2023), it is assumed that birds or mammals have ad libitum access to treated seeds and exclusively feed on treated seeds...

The progress of research focused on cholangiocytes and the biliary tree during development and following injury is hindered by limited available quantitative methodologies. Current techniques include two-dimensional standard histological cell-counting approaches, which are rapidly performed error-prone and lack architectural context; or three-dimensional analysis of the biliary tree in opacified livers, which introduce technical issues along with minimal quantitation. The present study aims to fill these quantitative gaps with a supervised machine learning model (BiliQML) able to quantify biliary forms in the liver of anti-Keratin 19 antibody-stained whole slide images...

INTRODUCTION: Physician educators are essential in training the next generation of physicians. However, physician educators' perspectives about what experiences they find beneficial to their teaching and the prevalence of these experiences remain unknown. Guided by social cognitive career theory (SCCT) and communities of practice (CoP), we explored what experiences physician educators perceive as beneficial in preparing them to teach. METHODS: In 2019, the Uniformed Services University School of Medicine in the United States surveyed its physician alumni to understand their education experiences during medical school, their current career path and what has contributed to their teaching role...

INTRODUCTION: For transmasculine spectrum individuals, there is a lack of validated surveys to assess sexual well-being (SWB) post-genital gender-affirming surgery. Currently, either providers are designing their own SWB surveys or surveys designed for cisgender men are being used. OBJECTIVE: This study investigated the applicability of SWB surveys validated for cisgender men to transmasculine spectrum individuals post-genital gender-affirming surgery (TMSX). Recognizing the paucity of validated tools for assessing SWB in transmasculine individuals post-genital gender-affirming surgery (TMSX), we evaluated current surveys for their inclusiveness and relevance to this population...

BACKGROUND AND PURPOSE: The single layer of cells lining all blood vessels, the endothelium, is a sophisticated signal co-ordination centre that controls a wide range of vascular functions including the regulation of blood pressure and blood flow. To co-ordinate activities, communication among cells is required for tissue level responses to emerge. While a significant form of communication occurs by the propagation of signals between cells, the mechanism of propagation in the intact endothelium is unresolved...

Plant water uptake from the soil is a crucial element of the global hydrological cycle and essential for vegetation drought resilience. Yet, knowledge of how the distribution of water uptake depth (WUD) varies across species, climates, and seasons is scarce relative to our knowledge of aboveground plant functions. With a global literature review, we found that average WUD varied more among biomes than plant functional types (i.e. deciduous/evergreen broadleaves and conifers), illustrating the importance of the hydroclimate, especially precipitation seasonality, on WUD...

Diabetic retinopathy disease contains lesions (e.g., exudates, hemorrhages, and microaneurysms) that are minute to the naked eye. Determining the lesions at pixel level poses a challenge as each pixel does not reflect any semantic entities. Furthermore, the computational cost of inspecting each pixel is expensive because the number of pixels is high even at low resolution. In this work, we propose a hybrid image processing method. Simple Linear Iterative Clustering with Gaussian Filter (SLIC-G) for the purpose of overcoming pixel constraints...

Fundamental knowledge of wet clutches' drag loss behavior is essential for designing low-loss clutch systems. In contrast to the widely investigated injection lubrication, more comprehensive knowledge is needed on the drag loss behavior of dip-lubricated wet clutches. In the development phase, data-driven models allow drag loss predictions with low computational effort and, at the same time, sufficient accuracy. Therefore, this study aimed to deepen and expand knowledge of the drag loss behavior of dip-lubricated wet clutches based on experimental investigations...

CONTEXT.—: Rare thalassemia subtypes are often undiagnosed because conventional testing methods can only identify 23 common types of α- and β-thalassemia. OBJECTIVE.—: To assess a comprehensive approach for the screening and diagnosis of rare thalassemia. DESIGN.—: The study cohort included 72 individuals with suspected rare thalassemia variants. Screening was conducted by next-generation sequencing (NGS) combined with third-generation sequencing (TGS) and chromosomal microarray analysis (CMA)/copy number variation sequencing...

Temporal graph learning aims to generate high-quality representations for graph-based tasks with dynamic information, which has recently garnered increasing attention. In contrast to static graphs, temporal graphs are typically organized as node interaction sequences over continuous time rather than an adjacency matrix. Most temporal graph learning methods model current interactions by incorporating historical neighborhood. However, such methods only consider first-order temporal information while disregarding crucial high-order structural information, resulting in suboptimal performance...

Widely used organophosphorus pesticide triazophos (TAP) can easily cumulate in aquatic system due to its high stability chemically and photochemically and thus posing significant threat to aquatic creatures and humans' health. Urging demand for rapid determining TAP in water has risen. Photoelectrochemical (PEC) sensing turns out to be a good candidate for its simplicity in fabrication and swiftness in detection. Nevertheless, traditional PEC sensors often lack selectivity as their signal generation primarily relies on the oxidation of organic compounds in the electrolyte by photo-induced holes...

Machine learning interatomic potential (MLIP) overcomes the challenges of high computational costs in density-functional theory and the relatively low accuracy in classical large-scale molecular dynamics, facilitating more efficient and precise simulations in materials research and design. In this review, the current state of the four essential stages of MLIP is discussed, including data generation methods, material structure descriptors, six unique machine learning algorithms, and available software. Furthermore, the applications of MLIP in various fields are investigated, notably in phase-change memory materials, structure searching, material properties predicting, and the pre-trained universal models...

The language faculty is physically realized in the neurobiological infrastructure of the human brain. Despite significant efforts, an integrated understanding of this system remains a formidable challenge. What is missing from most theoretical accounts is a specification of the neural mechanisms that implement language function. Computational models that have been put forward generally lack an explicit neurobiological foundation. We propose a neurobiologically informed causal modeling approach which offers a framework for how to bridge this gap...

To maintain normal functionality, it is necessary for a multicellular organism to generate robust responses to external temporal signals. However, the underlying mechanisms to coordinate the collective dynamics of cells remain poorly understood. Here we study the calcium activity of micropatterned biological neuron networks excited by periodic ATP stimuli. Combining quantitative experiments, physical and biological manipulation of cells, as well as mathematical modeling, we show that isolated cells in a network become more synchronized at longer period of stimuli through noise cancellation...

Protein-protein interactions (PPIs) are ubiquitous in biology, yet a comprehensive structural characterization of the PPIs underlying biochemical processes is lacking. Although AlphaFold-Multimer (AF-M) has the potential to fill this knowledge gap, standard AF-M confidence metrics do not reliably separate relevant PPIs from an abundance of false positive predictions. To address this limitation, we used machine learning on well curated datasets to train a S tructure P rediction and O mics informed C lassifier called SPOC that shows excellent performance in separating true and false PPIs, including in proteome-wide screens...

In the realm of human motion recognition systems, the augmentation of 3D human pose data plays a pivotal role in enriching and enhancing the quality of original datasets through the generation of synthetic data. This augmentation is vital for addressing the current research gaps in diversity and complexity, particularly when dealing with rare or complex human movements. Our study introduces a groundbreaking approach employing Generative Adversarial Networks (GANs), coupled with Support Vector Machine (SVM) and DenseNet, further enhanced by robot-assisted technology to improve the precision and efficiency of data collection...

In this work, a workflow has been developed for the generation of surrogate metamodels to predict and evaluate failure with a confidence above 95 % in initial service conditions of high-performance cylindrical vessels manufactured in composites by Roll Wrapping technology. Currently, there is no specific testing standardization for this type of vessel and to fill this gap probabilistic numerical models were developed, performed by the Finite Element Method, fed with the material characteristics obtained experimentally by 2D digital image correlation from flat specimens...