Inequalities in accelerated cognitive decline: Resolving observational window bias using nested non-linear regression.

Introduction: Limited observational windows lead to conflicting results in studies examining educational differences in Alzheimer's disease and related dementias (ADRD) risk, due to observational window bias relative to onset of accelerated cognitive decline. This study tested a novel model to address observational window bias and tested for the presence and sources of disparities in accelerated cognitive declines due to ADRD.

Methods: The sample examined 167,314 cognitive assessments from 32,441 Health and Retirement Study participants.

Incidence of Dementia Before Age 65 Years Among World Trade Center Attack Responders.

Importance: Reports suggest that the individuals who served in rescue operations following the terrorist attacks on the World Trade Center (WTC) have poorer brain health than expected.

Objective: To assess the incidence of dementia before age 65 years in a prospective study of WTC responders and to compare incidence among responders with severe exposures to debris vs responders not exposed to building debris or who wore personalized protective equipment (PPE).

Design, Setting, And Participants: This prospective cohort study was conducted from November 1, 2014, to January 1, 2023, in an academic medical monitoring program available to verified WTC responders residing on Long Island, New York.

Improving CRISPR-Cas9 directed faithful transgene integration outcomes by reducing unwanted random DNA integration.

Background: The field of genome editing has been revolutionized by the development of an easily programmable editing tool, the CRISPR-Cas9. Despite its promise, off-target activity of Cas9 posed a great disadvantage for genome editing purposes by causing DNA double strand breaks at off-target locations and causing unwanted editing outcomes. Furthermore, for gene integration applications, which introduce transgene sequences, integration of transgenes to off-target sites could be harmful, hard to detect, and reduce faithful genome editing efficiency.

No evidence for chunking in spatial memory of route experience.

Spatial memory is important for supporting the successful completion of everyday activities and is a particularly vulnerable domain in late life. Grouping items together in memory, or chunking, can improve spatial memory performance. In memory for desktop scale spaces and well-learned large-scale environments, error patterns suggest that information is chunked in memory.

Predicting internalizing symptoms with machine learning: identifying individuals that need care.

The current project aims to identify individuals in urgent need of mental health care, using a machine learning algorithm (random forest). Comparison/contrast with conventional regression analyses is discussed. A total of 2,409 participants were recruited from an anonymous university, including undergraduate and graduate students, faculty, and staff.