Autoencoder imputation of missing heterogeneous data for Alzheimer's disease classification.

Missing Alzheimer's disease (AD) data is prevalent and poses significant challenges for AD diagnosis. Previous studies have explored various data imputation approaches on AD data, but the systematic evaluation of deep learning algorithms for imputing heterogeneous and comprehensive AD data is limited. This study investigates the efficacy of denoising autoencoder-based imputation of missing key features of heterogeneous data that comprised tau-PET, MRI, cognitive and functional assessments, genotype, sociodemographic, and medical history.

Mapping resistance to Sclerotinia white mold in two pinto bean recombinant inbred line populations.

White mold, caused by the fungus Sclerotinia sclerotiorum (Lib.) de Bary, is a devastating disease affecting common bean (Phaseolus vulgaris L.) production worldwide.

GWAS of resistance to three bacterial diseases in the Andean common bean diversity panel.

Bacterial brown spot (BBS) caused by pv. (), common bacterial blight (CBB) caused by pv. () and subsp.

T and Z, partial seed coat patterning genes in common bean, provide insight into the structure and protein interactions of a plant MBW complex.

Flavonoids are secondary metabolites associated with plant seed coat and flower color. These compounds provide health benefits to humans as anti-inflammatory and antioxidant compounds. The expression of the late biosynthetic genes in the flavonoid pathway is controlled by a ternary MBW protein complex consisting of interfacing MYB, beta-helix-loop-helix (bHLH), and WD40 Repeat (WDR) proteins.

Evolution, diversity, and function of the disease susceptibility gene Snn1 in wheat.

Septoria nodorum blotch (SNB), caused by Parastagonospora nodorum, is a disease of durum and common wheat initiated by the recognition of pathogen-produced necrotrophic effectors (NEs) by specific wheat genes. The wheat gene Snn1 was previously cloned, and it encodes a wall-associated kinase that directly interacts with the NE SnTox1 leading to programmed cell death and ultimately the development of SNB. Here, sequence analysis of Snn1 from 114 accessions including diploid, tetraploid, and hexaploid wheat species revealed that some wheat lines possess two copies of Snn1 (designated Snn1-B1 and Snn1-B2) approximately 120 kb apart.

Impact of Different Diagnostic Measures on Drug Class Association with Dementia Progression Risk: A Longitudinal Prospective Cohort Study.

Background: The Clinical Dementia Rating Scale Sum of Boxes (CDRSOB) score is known to be highly indicative of cognitive-functional status and is regularly employed for clinical and research purposes.

Objective: Our aim is to determine whether CDRSOB is consistent with clinical diagnosis in evaluating drug class associations with risk of progression to mild cognitive impairment (MCI) and dementia.

Methods: We employed weighted Cox regression analysis on longitudinal NACC data, to identify drug classes associated with disease progression risk, using clinical diagnosis and CDRSOB as the outcome.

Simulations of multiple breeding strategy scenarios in common bean for assessing genomic selection accuracy and model updating.

The aim of this study was to evaluate the accuracy of the ridge regression best linear unbiased prediction model across different traits, parent population sizes, and breeding strategies when estimating breeding values in common bean (Phaseolus vulgaris). Genomic selection was implemented to make selections within a breeding cycle and compared across five different breeding strategies (single seed descent, mass selection, pedigree method, modified pedigree method, and bulk breeding) following 10 breeding cycles. The model was trained on a simulated population of recombinant inbreds genotyped for 1010 single nucleotide polymorphism markers including 38 known quantitative trait loci identified in the literature.

The Potential of a Stratified Approach to Drug Repurposing in Alzheimer's Disease.

Alzheimer's disease (AD) is a complex neurodegenerative condition that is characterized by the build-up of amyloid-beta plaques and neurofibrillary tangles. While multiple theories explaining the aetiology of the disease have been suggested, the underlying cause of the disease is still unknown. Despite this, several modifiable and non-modifiable factors that increase the risk of developing AD have been identified.

The alleles bc-u and bc-u (previously bc-4 gene), representing coding mutations within Vps4 AAA+ ATPase ESCRT protein, interact with other genes to condition resistance to BCMV and BCMNV in common bean.

Bean common mosaic virus (BCMV) and bean common mosaic necrosis virus (BCMNV) have a damaging impact on global common bean (Phaseolus vulgaris L.) cultivation, causing potential yield losses of over 80%. The primary strategy for controlling these viruses is through host plant resistance.

Integrating de novo QTL-seq and linkage mapping to identify quantitative trait loci conditioning physiological resistance and avoidance to white mold disease in dry bean.

White mold (WM), caused by the ubiquitous fungus Sclerotinia sclerotiorum, is a devastating disease that limits production and quality of dry bean globally. In the present study, classic linkage mapping combined with QTL-seq were employed in two recombinant inbred line (RIL) populations, "Montrose"/I9365-25 (M25) and "Raven"/I9365-31 (R31), with the initial goal of fine-mapping QTL WM5.4 and WM7.

Linked candidate genes of different functions for white mold resistance in common bean ( L) are identified by multiple QTL mapping approaches.

White mold (WM) is a major disease in common bean ( L.), and its complex quantitative genetic control limits the development of WM resistant cultivars. WM2.

Simulations of rate of genetic gain in dry bean breeding programs.

A reference study for breeders aiming at maximizing genetic gain in common bean. Depending on trait heritability and genetic architecture, conventional approaches may provide an advantage over other frameworks. Dry beans (Phaseolus vulgaris L.

Alzheimer's disease classification using cluster-based labelling for graph neural network on heterogeneous data.

Biomarkers for Alzheimer's disease (AD) diagnosis do not always correlate reliably with cognitive symptoms, making clinical diagnosis inconsistent. In this study, the performance of a graphical neural network (GNN) classifier based on data-driven diagnostic classes from unsupervised clustering on heterogeneous data is compared to the performance of a classifier using clinician diagnosis as an outcome. Unsupervised clustering on tau-positron emission tomography (PET) and cognitive and functional assessment data was performed.

Modified screening method of middle american dry bean genotypes reveals new genomic regions on Pv10 associated with anthracnose resistance.

Anthracnose, caused by the fungal pathogen (Sacc. & Magnus) Lams.-Scrib.

Multi-dimensional relationships among dementia, depression and prescribed drugs in England and Wales hospitals.

Background: Dementia is a group of symptoms that largely affects older people. The majority of patients face behavioural and psychological symptoms (BPSD) during the course of their illness. Alzheimer's disease (AD) and vascular dementia (VaD) are two of the most prevalent types of dementia.

Multiple Cost Optimisation for Alzheimer's Disease Diagnosis.

Current machine learning techniques for dementia diagnosis often do not take into account real-world practical constraints, which may include, for example, the cost of diagnostic assessment time and financial budgets. In this work, we built on previous cost-sensitive feature selection approaches by generalising to multiple cost types, while taking into consideration that stakeholders attempting to optimise the dementia care pathway might face multiple non-fungible budget constraints. Our new optimisation algorithm involved the searching of cost-weighting hyperparameters while constrained by total budgets.

Distinguishing Lewy Body Dementia from Alzheimer's Disease using Machine Learning on Heterogeneous Data: A Feasibility Study.

Dementia with Lewy Bodies (DLB) is the second most common form of dementia, but diagnostic markers for DLB can be expensive and inaccessible, and many cases of DLB are undiagnosed. This work applies machine learning techniques to determine the feasibility of distinguishing DLB from Alzheimer's Disease (AD) using heterogeneous data features. The Repeated Incremental Pruning to Produce Error Reduction (RIPPER) algorithm was first applied using a Leave-One-Out Cross-Validation protocol to a dataset comprising DLB and AD cases.

Dry Bean: A Protein-Rich Superfood With Carbohydrate Characteristics That Can Close the Dietary Fiber Gap.

Consumer food choices are often focused on protein intake, but the chosen sources are frequently either animal-based protein that has high fat content or plant-based protein that is low in other nutrients. In either case, these protein sources often lack dietary fiber, which is a nutrient of concern in the 2020-2025 Dietary Guide for Americans. Pulse crops, such as dry edible beans ( L.

Alzheimer's Disease Assessments Optimized for Diagnostic Accuracy and Administration Time.

Objective: Despite the potential of machine learning techniques to improve dementia diagnostic processes, research outcomes are often not readily translated to or adopted in clinical practice. Importantly, the time taken to administer diagnostic assessment has yet to be taken into account in feature-selection based optimisation for dementia diagnosis. We address these issues by considering the impact of assessment time as a practical constraint for feature selection of cognitive and functional assessments in Alzheimer's disease diagnosis.

Genetic mapping and genomic prediction of sclerotinia stem rot resistance to rapeseed/canola (Brassica napus L.) at seedling stage.

GWAS detected ninety-eight significant SNPs associated with Sclerotinia sclerotiorum resistance. Six statistical models resulted in medium to high predictive ability, depending on trait, indicating potential of genomic prediction for disease resistance breeding. The lack of complete host resistance and a complex resistance inheritance nature between rapeseed/canola and Sclerotinia sclerotiorum often limits the development of functional molecular markers that enable breeding for sclerotinia stem rot (SSR) resistance.

The Common Bean Gene Encodes Flavonoid 3'5' Hydroxylase: A Major Mutational Target for Flavonoid Diversity in Angiosperms.

The classic (violet, purple) gene of common bean () functions in a complex genetic network that controls seed coat and flower color and flavonoid content. was cloned to understand its role in the network and the evolution of its orthologs in the Viridiplantae. mapped genetically to a narrow interval on chromosome Pv06.

Simvastatin is associated with superior lipid and glycaemic control to atorvastatin and reduced levels of incident Type 2 diabetes, in men and women, in the UK Biobank.

Introduction: Cardiovascular disease (CVD) is the leading cause of mortality in people with Type 2 diabetes mellitus (T2DM). Statins reduce low-density lipoproteins and positively affect CVD outcomes. Statin type and dose have differential effects on glycaemia and risk of incident T2DM; however, the impact of gender, and of individual drugs within the statin class, remains unclear.

The impact of hearing impairment and hearing aid use on progression to mild cognitive impairment in cognitively healthy adults: An observational cohort study.

Introduction: We assessed the association of self-reported hearing impairment and hearing aid use with cognitive decline and progression to mild cognitive impairment (MCI).

Methods: We used a large referral-based cohort of 4358 participants obtained from the National Alzheimer's Coordinating Center. The standard covariate-adjusted Cox proportional hazards model, the marginal structural Cox model with inverse probability weighting, standardized Kaplan-Meier curves, and linear mixed-effects models were applied to test the hypotheses.