Genome-wide association neural networks identify genes linked to family history of Alzheimer's disease.

Augmenting traditional genome-wide association studies (GWAS) with advanced machine learning algorithms can allow the detection of novel signals in available cohorts. We introduce "genome-wide association neural networks (GWANN)" a novel approach that uses neural networks (NNs) to perform a gene-level association study with family history of Alzheimer's disease (AD). In UK Biobank, we defined cases (n = 42 110) as those with AD or family history of AD and sampled an equal number of controls.

Efficiency at scale: Investigating the performance of diminutive language models in clinical tasks.

The entry of large language models (LLMs) into research and commercial spaces has led to a trend of ever-larger models, with initial promises of generalisability. This was followed by a widespread desire to downsize and create specialised models without the need for complete fine-tuning, using Parameter Efficient Fine-tuning (PEFT) methods. We present an investigation into the suitability of different PEFT methods to clinical decision-making tasks, across a range of model sizes, including extremely small models with as few as 25 million parameters.

Anemia, hemoglobin concentration and cognitive function in the Longitudinal Ageing Study in India-Harmonized Diagnostic Assessment of Dementia (LASI-DAD) and the Health and Retirement Study.

Background: In India, anemia is widely researched in children and women of reproductive age, however, studies in older populations are lacking. Given the adverse effect of anemia on cognitive function and dementia this older population group warrants further study. The Longitudinal Ageing Study in India - Harmonized Diagnostic Assessment of Dementia (LASI-DAD) dataset contains detailed measures to allow a better understanding of anaemia as a potential risk factor for dementia.

Predicting AT(N) pathologies in Alzheimer's disease from blood-based proteomic data using neural networks.

Background And Objective: Blood-based biomarkers represent a promising approach to help identify early Alzheimer's disease (AD). Previous research has applied traditional machine learning (ML) to analyze plasma omics data and search for potential biomarkers, but the most modern ML methods based on deep learning has however been scarcely explored. In the current study, we aim to harness the power of state-of-the-art deep learning neural networks (NNs) to identify plasma proteins that predict amyloid, tau, and neurodegeneration (AT[N]) pathologies in AD.

Comparative effect of metformin versus sulfonylureas with dementia and Parkinson's disease risk in US patients over 50 with type 2 diabetes mellitus.

Introduction: Type 2 diabetes is a risk factor for dementia and Parkinson's disease (PD). Drug treatments for diabetes, such as metformin, could be used as novel treatments for these neurological conditions. Using electronic health records from the USA (OPTUM EHR) we aimed to assess the association of metformin with all-cause dementia, dementia subtypes and PD compared with sulfonylureas.

The relationship between isolated hypertension with brain volumes in UK Biobank.

Background: Hypertension is a well-established risk factor for cognitive impairment, brain atrophy, and dementia. However, the relationship of other types of hypertensions, such as isolated hypertension on brain health and its comparison to systolic-diastolic hypertension (where systolic and diastolic measures are high), is still relatively unknown. Due to its increased prevalence, it is important to investigate the impact of isolated hypertension to help understand its potential impact on cognitive decline and future dementia risk.

PyTrack: An end-to-end analysis toolkit for eye tracking.

Eye tracking is a widely used tool for behavioral research in the field of psychology. With technological advancement, we now have specialized eye-tracking devices that offer high sampling rates, up to 2000 Hz, and allow for measuring eye movements with high accuracy. They also offer high spatial resolution, which enables the recording of very small movements, like drifts and microsaccades.

Implementation of a basement membrane invasion assay using mesenteric tissue.

Metastasis accounts for nearly 90% of all cancer associated mortalities. A hallmark of metastasis in malignancies of epithelial origin such as in the pancreas and breast, is invasion of the basement membrane (BM). While various in vitro assays have been developed to address questions regarding the invasiveness of tumors with relation to the BM, most fail to recapitulate a physiologically accurate cell-membrane interface.