Developing Topics.

Background: Comprehending the role of participatory lifestyle factors influencing the aging process and subsequent cognitive outcomes is imperative for postulating ways to combat cognitive decline. Recent research points to the independent impacts of leisure time activities (LTAs), physical performance (measures of physical fitness) and socialization (relationships and interaction frequency) on healthy cognitive aging, although the relative importance of this triad of factors is poorly delineated.

Method: From baseline data of two studies examining cognitive aging in older, diverse populations- "Study of Healthy Aging in African Americans" and "Kaiser Healthy Aging and Diverse Life Experiences," we scraped subjects' self-reported data and Spanish and English Neuropsychological Assessment Scales (SENAS) measured cognitive performance scores.

Integrating genetic subtypes with PET scan monitoring to predict outcome in diffuse large B-cell lymphoma.

Next Generation Sequencing-based subtyping and interim- and end of treatment positron emission tomography (i/eot-PET) monitoring have high potential for upfront and on-treatment risk assessment of diffuse large B-cell lymphoma patients. We performed Dana Farber Cancer Institute (DFCI) and LymphGen genetic subtyping for the HOVON84 (n = 208, EudraCT-2006-005174-42) and PETAL (n = 204, EudraCT-2006-001641-33) trials retrospectively combined with DFCI genetic data (n = 304). For all R-CHOP treated patients (n = 592), C5/MCD- and C2/A53-subtypes show significantly worse outcome independent of the international prognostic index.

Biologically plausible gated recurrent neural networks for working memory and learning-to-learn.

The acquisition of knowledge and skills does not occur in isolation but learning experiences amalgamate within and across domains. The process through which learning can accelerate over time is referred to as learning-to-learn or meta-learning. While meta-learning can be implemented in recurrent neural networks, these networks tend to be trained with architectures that are not easily interpretable or mappable to the brain and with learning rules that are biologically implausible.

The Feasibility of Personalized Endpoints in Assessing Treatment Outcomes in Rare Disease: A Pilot Study of Goal Attainment Scaling in SCN2A-Associated Developmental Epileptic Encephalopathy.

Objectives: For individuals living with rare neurodevelopmental disorders, especially those who are at the most severe end of the spectrum, standardized outcome measures may lack the sensitivity to capture small but meaningful changes. Personalized endpoints such as Goal Attainment Scaling (GAS) allow the assessment of treatment response across variable baseline states and disease manifestations and thus provide a highly sensitive measure of efficacy. The current study tested the feasibility of using GAS in rare SCN2A-associated developmental and epileptic encephalopathy (SCN2A-DEE).