Biology: Weird Science?

Papers Presented: The Relationship of the Second Light Treatment to Cell Germination and Polarization in Ceratopteris Fern Spores by Ao Liu Abstract: This research about the Ceratopteris richardii fern spores, which is part of the Discovery Lab in Plant Biology course at UT Austin led by Dr. Stan Roux. We focused on the relationship between the second light treatment and germination as well as polarization of the spores. Several groups of students tested different amounts of light and darkness on the influence of germination rate and the gravity response of the germinated spores. A Mathematical Model of Skeletal Muscle Regeneration by Elizabeth Stephenson Abstract: We introduce a system of seven ordinary differential equations modeling the response of healthy mammalian skeletal muscle tissue to sudden and severe damage. The system is analyzed, yielding one stable, biologically meaningful equilibrium. A set of numerical simulations is performed to illustrate the performance of the proposed equations. We conduct a sensitivity analysis to rank the parameters’ influence on the system. This model can help doctors and scientists forecast the outcomes of medicinal treatments prior to implementation. Chronically Underwhelmed: The Modern Journey Back to Happiness by Audrey Hendrickso

BIBSnet

<p>This software provides the utility of creating a nnU-Net anatomical MRI segmentation and mask with a infant brain trained model for the purposes of circumventing JLF within Nibabies.</p&gt

Polyneuro risk scores capture widely distributed connectivity patterns of cognition

Resting-state functional connectivity (RSFC) is a powerful tool for characterizing brain changes, but it has yet to reliably predict higher-order cognition. This may be attributed to small effect sizes of such brain-behavior relationships, which can lead to underpowered, variable results when utilizing typical sample sizes (N∼25). Inspired by techniques in genomics, we implement the polyneuro risk score (PNRS) framework - the application of multivariate techniques to RSFC data and validation in an independent sample. Utilizing the Adolescent Brain Cognitive Development® cohort split into two datasets, we explore the framework's ability to reliably capture brain-behavior relationships across 3 cognitive scores - general ability, executive function, learning & memory. The weight and significance of each connection is assessed in the first dataset, and a PNRS is calculated for each participant in the second. Results support the PNRS framework as a suitable methodology to inspect the distribution of connections contributing towards behavior, with explained variance ranging from 1.0 % to 21.4 %. For the outcomes assessed, the framework reveals globally distributed, rather than localized, patterns of predictive connections. Larger samples are likely necessary to systematically identify the specific connections contributing towards complex outcomes. The PNRS framework could be applied translationally to identify neurologically distinct subtypes of neurodevelopmental disorders

Personalized functional brain network topography is associated with individual differences in youth cognition

Abstract Individual differences in cognition during childhood are associated with important social, physical, and mental health outcomes in adolescence and adulthood. Given that cortical surface arealization during development reflects the brain’s functional prioritization, quantifying variation in the topography of functional brain networks across the developing cortex may provide insight regarding individual differences in cognition. We test this idea by defining personalized functional networks (PFNs) that account for interindividual heterogeneity in functional brain network topography in 9–10 year olds from the Adolescent Brain Cognitive Development℠ Study. Across matched discovery (n = 3525) and replication (n = 3447) samples, the total cortical representation of fronto-parietal PFNs positively correlates with general cognition. Cross-validated ridge regressions trained on PFN topography predict cognition in unseen data across domains, with prediction accuracy increasing along the cortex’s sensorimotor-association organizational axis. These results establish that functional network topography heterogeneity is associated with individual differences in cognition before the critical transition into adolescence