Molecular detection of Rickettsia species in ectoparasites collected from two southern provinces of Cambodia.

Arthropod-borne rickettsioses comprise a wide variety of subtypes that are endemic in Cambodia, but there remains very little data on the geographic distribution of the pathogens or their vectors. Surveys were conducted in Koh Kong and Preah Sihanouk Provinces between September 2017 and June 2018 to collect ectoparasites from peridomestic animals and the environment using dragging and flagging methods. Collected ectoparasites were sorted and identified morphologically, then pooled by species, host, and location for molecular detection using Rickettsia genus- and species-specific qPCR and/or multilocus sequence typing (MLST) assays.

Learning to reconstruct accelerated MRI through K-space cold diffusion without noise.

Deep learning-based MRI reconstruction models have achieved superior performance these days. Most recently, diffusion models have shown remarkable performance in image generation, in-painting, super-resolution, image editing and more. As a generalized diffusion model, cold diffusion further broadens the scope and considers models built around arbitrary image transformations such as blurring, down-sampling, etc.

Failure in a population: Tauopathy disrupts homeostatic set-points in emergent dynamics despite stability in the constituent neurons.

Homeostatic regulation of neuronal activity is essential for robust computation; set-points, such as firing rate, are actively stabilized to compensate for perturbations. The disruption of brain function central to neurodegenerative disease likely arises from impairments of computationally essential set-points. Here, we systematically investigated the effects of tau-mediated neurodegeneration on all known set-points in neuronal activity.

AI-based differential diagnosis of dementia etiologies on multimodal data.

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies.