Examining the Role of Neuroticism Polygenic Risk in Late Life Cognitive Change: A UK Biobank Study.

Cognitive decline is a public health concern affecting about 50 million individuals worldwide. Neuroticism, defined as the trait disposition to experience intense and frequent negative emotions, has been associated with an increased risk of late-life cognitive decline. However, the underlying biological mechanisms of this association remain unknown.

Identifying Psychosocial and Ecological Determinants of Enthusiasm In Youth: Integrative Cross-Sectional Analysis Using Machine Learning.

Background: Understanding the factors contributing to mental well-being in youth is a public health priority. Self-reported enthusiasm for the future may be a useful indicator of well-being and has been shown to forecast social and educational success. Typically, cross-domain measures of ecological and health-related factors with relevance to public policy and programming are analyzed either in isolation or in targeted models assessing bivariate interactions.

Effect of machine learning models on clinician prediction of postoperative complications: the Perioperative ORACLE randomised clinical trial.

Background: Anaesthesiologists might be able to mitigate risk if they know which patients are at greatest risk for postoperative complications. This trial examined the impact of machine learning models on clinician risk assessment.

Methods: This single-centre, prospective, randomised clinical trial enrolled surgical patients aged ≥18 yr.

Social vulnerability and surgery outcomes: a cross-sectional analysis.

Background: Post-operative complications present a challenge to the healthcare system due to the high unpredictability of their incidence. Socioeconomic conditions have been established as social determinants of health. However, their contribution relating to postoperative complications is still unclear as it can be heterogeneous based on community, type of surgical services, and sex and gender.

Effect of Machine Learning on Anaesthesiology Clinician Prediction of Postoperative Complications: The Perioperative ORACLE Randomised Clinical Trial.

Background: Anaesthesiology clinicians can implement risk mitigation strategies if they know which patients are at greatest risk for postoperative complications. Although machine learning models predicting complications exist, their impact on clinician risk assessment is unknown.

Methods: This single-centre randomised clinical trial enrolled patients age ≥18 undergoing surgery with anaesthesiology services.

Effect of Telemedicine Support for Intraoperative Anaesthesia Care on Postoperative Outcomes: The TECTONICS Randomised Clinical Trial.

Background: Novel applications of telemedicine can improve care quality and patient outcomes. Telemedicine for intraoperative decision support has not been rigorously studied.

Methods: This single centre randomised clinical trial (RCT, clinicaltrials.

Ten simple rules for pushing boundaries of inclusion at academic events.

Inclusion at academic events is facing increased scrutiny as the communities these events serve raise their expectations for who can practically attend. Active efforts in recent years to bring more diversity to academic events have brought progress and created momentum. However, we must reflect on these efforts and determine which underrepresented groups are being disadvantaged.

Multi-view representation learning for tabular data integration using inter-feature relationships.

Objective: An applied problem facing all areas of data science is harmonizing data sources. Joining data from multiple origins with unmapped and only partially overlapping features is a prerequisite to developing and testing robust, generalizable algorithms, especially in healthcare. This integrating is usually resolved using meta-data such as feature names, which may be unavailable or ambiguous.

Social Vulnerability and Surgery Outcomes: A Cross-sectional Analysis.

Background: Post-operative complications present a challenge to the healthcare system due to the high unpredictability of their incidence. However, the socioeconomic factors that relate to postoperative complications are still unclear as they can be heterogeneous based on communities, types of surgical services, and sex and gender.

Methods: In this study, we conducted a large population cross-sectional analysis of social vulnerability and the odds of various post-surgical complications.

Opposing brain signatures of sleep in task-based and resting-state conditions.

Sleep and depression have a complex, bidirectional relationship, with sleep-associated alterations in brain dynamics and structure impacting a range of symptoms and cognitive abilities. Previous work describing these relationships has provided an incomplete picture by investigating only one or two types of sleep measures, depression, or neuroimaging modalities in parallel. We analyze the correlations between brainwide neural signatures of sleep, cognition, and depression in task and resting-state data from over 30,000 individuals from the UK Biobank and Human Connectome Project.

Reconstructing visual illusory experiences from human brain activity.

Visual illusions provide valuable insights into the brain's interpretation of the world given sensory inputs. However, the precise manner in which brain activity translates into illusory experiences remains largely unknown. Here, we leverage a brain decoding technique combined with deep neural network (DNN) representations to reconstruct illusory percepts as images from brain activity.

An in vivo assay to study locomotion in Caenorhabditis elegans.

Adaptation in the sensory-mechanical loop during locomotion is a powerful mechanism that allows organisms to survive in different conditions and environments. Motile animals need to alter motion patterns in different environments. For example, crocodiles and other animals can walk on solid ground but switch to swimming in water beds.

Sex-specific associations between lifetime diagnosis of bipolar disorder and cardiovascular disease: A cross-sectional analysis of 257,673 participants from the UK Biobank.

Background: Sex is seldom considered as a potential moderator of the impact of bipolar disorder (BD) on cardiovascular disease (CVD) risk. We aimed to characterize the sex-specific association of CVD and BD using data from the UK Biobank.

Methods: In a cross-sectional analysis, we compared the odds ratio between women and men with BD for seven CVD diagnoses (coronary artery disease, myocardial infarction, angina, atrial fibrillation, heart failure, stroke, and essential hypertension) and four cardiovascular biomarkers (arterial stiffness index, low-density lipoprotein, C-reactive protein, and HbA1c) in 293 participants with BD and 257,380 psychiatrically healthy controls in the UK Biobank.

Machine Learning-Based Predictive Modeling of Anxiety and Depressive Symptoms During 8 Months of the COVID-19 Global Pandemic: Repeated Cross-sectional Survey Study.

Background: The COVID-19 global pandemic has increased the burden of mental illness on Canadian adults. However, the complex combination of demographic, economic, and lifestyle factors and perceived health risks contributing to patterns of anxiety and depression has not been explored.

Objective: The aim of this study is to harness flexible machine learning methods to identify constellations of factors related to symptoms of mental illness and to understand their changes over time during the COVID-19 pandemic.

Sharpening of Hierarchical Visual Feature Representations of Blurred Images.

The robustness of the visual system lies in its ability to perceive degraded images. This is achieved through interacting bottom-up, recurrent, and top-down pathways that process the visual input in concordance with stored prior information. The interaction mechanism by which they integrate visual input and prior information is still enigmatic.

Regional differences in Purkinje cell morphology in the cerebellar vermis of male mice.

Regional differences in dendritic architecture can influence connectivity and dendritic signal integration, with possible consequences for neuronal computation. In the cerebellum, analyses of Purkinje cells (PCs), which are functionally critical as they provide the sole output of the cerebellar cortex, have suggested that the cerebellar cortex is not uniform in structure as traditionally assumed. However, the limitations of traditional staining methods and microscopy capabilities have presented difficulties in investigating possible local variations in PC morphology.

Comparative morphology of dendritic arbors in populations of Purkinje cells in mouse sulcus and apex.

Foliation divides the mammalian cerebellum into structurally distinct subdivisions, including the concave sulcus and the convex apex. Purkinje cell (PC) dendritic morphology varies between subdivisions and changes significantly ontogenetically. Since dendritic morphology both enables and limits sensory-motor circuit function, it is important to understand how neuronal architectures differ between brain regions.