The design and fabrication of functional scientific instrumentation allows students to forge a link between commonly reported numbers and physical material properties. Here, a two-point and four-point probe station for measuring electrical properties of solid materials is fabricated via 3D printing utilizing an inexpensive benchtop fused-deposition modeling system and designed by standard computer-aided design software. Stainless steel tapestry needles serve as probes for contacting a sample; these are also electroplated in order to study their electrical performance, and provide a framework for discussion of electrical charge transport, contact resistance, and conductivity in materials. A microcontroller board is integrated into the probe and controlled using open-source software. Our robust and simple design provides an instrument that is easily fabricated by students and readily applied to a wide range of classroom settings focused on materials science, mechanical and electrical engineering, as well as solid-state physics and chemistry. This 3D printed probe station costs less than $100 US in materials per unit excluding source meter. We demonstrate that two- and four-point resistance measurements carried out on a solid-state semiconductor differ only by less than 5% in magnitude when compared to data collected using a standard and expensive commercial probe station. Two- and four-point resistance measurements carried out on gold deposited on silicon and on the soft nanostructured organic semiconductor poly­(3,4-ethylenedioxythiophene) result in reproducible and accurate current versus voltage (I–V) curves.

PEDOT nanofibers show unprecedented cycling stability in aqueous supercapacitors, 90% capacitance for 350 000 cycles, and exhibit excellent power and energy density (25 kWkg−1 and 4.3 W h kg−1) at 1 V.

These authors contributed equally to this work Affiliations:Abstract Pediatric brain tumor survivors experience significant cognitive sequelae from their diagnosis and treatment. The exact mechanisms of these injuries are poorly understood, and validated predictors of cognitive outcome are lacking. The current study aims to determine if there are abnormalities in functional brain network organization and cognitive performance in pediatric brain tumor patients, measured via resting state functional magnetic resonance imaging (rsfMRI) and the NIH Toolbox Cognition Battery, respectively. Further, we assess potential relationships between changes in brain network architecture and behavior in the patients.Patients ages 4-18 years old with diagnosis of a brain tumor underwent awake rsfMRI during regularly scheduled clinical imaging and were tested with the NIH Toolbox Cognition Battery. Overall, functional brain network organization was significantly different in patients compared to age-and sex-matched healthy controls (p < 0.001).Network integrity within the dorsal attention network was particularly affected, with 86% of patients having connectivity strength 2+ SD below the mean of controls (p < 0.0001).Moreover, cognitive testing of patients demonstrated significant impairments in multiple domains, including attention (p < 0.05, FDR corrected). Finally, a significant amount of variance of age-adjusted total composite scores from the Toolbox was explained by changes in segregation between the dorsal attention and default mode networks as well as sex (R 2 = 0.52, p < 0.05). Pediatric brain tumor patients demonstrated statistically significant deficits in multiple cognitive domains and multiple abnormalities in brain network architecture.Thus, rsfMRI may provide insight into neural systems that underlie these changes in cognitive function, suggesting that these metrics may serve as a biomarker for cognitive performance.

INTRODUCTION: Survivors of pediatric brain tumors experience significant cognitive deficits from their diagnosis and treatment. Mechanisms of cognitive injury are poorly understood, and predictors of long-term outcome are lacking. Large-scale, distributed brain systems provide a window into brain organization and function that may yield insight into these mechanisms and outcomes. Recent evidence suggests that systems-level changes are related to cognitive performance across the lifespan. Here, we evaluated brain network architecture, cognitive performance, and brain-behavior relationships in pediatric brain tumor patients. METHODS: Forty-nine patients (ages 7-18y.o.) with any brain tumor diagnosis underwent resting state functional Magnetic Resonance Imaging (rsfMRI) during regularly scheduled clinical visits. All patients were tested with the NIH Toolbox Cognition Battery. One-hundred thirty-nine age- and sex-matched typically developing children were used as controls. All data were processed to minimize artifactual sources of variance. Functional brain networks were created for each patient via rsfMRI data from 300 regions of interest that sample the whole brain. Multilinear models were implemented to examine brain-behavior relationships, while accounting for demographic and clinical factors. RESULTS: Functional network organization was significantly altered in patients compared to controls (p&lt;0.001). Network organization was more affected in patients who received whole-brain radiation therapy than those who did not (t=2.52, p&lt;0.015). Patients demonstrated significant impairments in multiple domains of cognitive performance, e.g. attention (p&lt;0.0001). Weak relationships were found between cognitive performance and network organization, none of which survived multiple comparison correction. CONCLUSIONS: Brain network architecture is significantly altered in pediatric brain tumor patients. Whole-brain radiation was related to the largest changes. Most network and cognitive changes were significant with large effect sizes, yet brain-behavior relationships were weak. Our results suggest that systems-level changes in brain organization may provide insight into long-term changes in brain function in pediatric brain tumor patients.