Chemical entity normalization for successful translational development of Alzheimer's disease and dementia therapeutics.

Background: Identifying chemical mentions within the Alzheimer's and dementia literature can provide a powerful tool to further therapeutic research. Leveraging the Chemical Entities of Biological Interest (ChEBI) ontology, which is rich in hierarchical and other relationship types, for entity normalization can provide an advantage for future downstream applications. We provide a reproducible hybrid approach that combines an ontology-enhanced PubMedBERT model for disambiguation with a dictionary-based method for candidate selection.

Automating literature screening and curation with applications to computational neuroscience.

Objective: ModelDB (https://modeldb.science) is a discovery platform for computational neuroscience, containing over 1850 published model codes with standardized metadata. These codes were mainly supplied from unsolicited model author submissions, but this approach is inherently limited.

GPT-4 Performance for Neurologic Localization.

Background And Objectives: In health care, large language models such as Generative Pretrained Transformers (GPTs), trained on extensive text datasets, have potential applications in reducing health care disparities across regions and populations. Previous software developed for lesion localization has been limited in scope. This study aims to evaluate the capability of GPT-4 for lesion localization based on clinical presentation.

Phytophthora pluvialis maintenance, spore production and detached needle assays.

Phytophthora pluvialis is an oomycete that primarily infects Pinus radiata and Pseudotsuga menziesii causing the destructive foliar disease red needle cast (RNC). Recent observations show that P. pluvialis can also infect western hemlock inducing resinous cankers.

Identifying Game-Based Digital Biomarkers of Cognitive Risk for Adolescent Substance Misuse: Protocol for a Proof-of-Concept Study.

Background: Adolescents at risk for substance misuse are rarely identified early due to existing barriers to screening that include the lack of time and privacy in clinic settings. Games can be used for screening and thus mitigate these barriers. Performance in a game is influenced by cognitive processes such as working memory and inhibitory control.