Inside the Black Box of Text-Message College Advising

Making college access and success more equitable at a national scale requires alternatives to intensive in-person modes of pre-college advising. Text-message advising campaigns are a promising intervention model for delivering college application and financial aid assistance affordably to large populations of college-intending, low-income students. College outcome results from a recent series of very large text-message programs have been disappointing however. Going inside the black box of text-message advising to understand why and how students engage in text-messaging programs can help explain program effects and inform the design of future virtual-advising programs. This study uses text mining techniques to investigate the content of 342,000 student text messages from a national text-message advising program. In the program under study, over 30,000 college-intending students from 745 high schools received two-way college advising for 15 months via text messaging with professional advisors. Data mining of the student text messages indicated that students needed substantial individualized assistance and that they used texting primarily for navigating discrete tasks related to testing, applications, and financial aid. In addition to providing substantive findings about college access advising, the study method illustrates how big data tools can extract meaning from large bodies of unstructured text like those generated by the growing number of text-message educational interventions

Parameterization for in-silico modeling of ion channel interactions with drugs

Since the first Hodgkin and Huxley ion channel model was described in the 1950s, there has been an explosion in mathematical models to describe ion channel function. As experimental data has become richer, models have concomitantly been improved to better represent ion channel kinetic processes, although these improvements have generally resulted in more model complexity and an increase in the number of parameters necessary to populate the models. Models have also been developed to explicitly model drug interactions with ion channels. Recent models of drug-channel interactions account for the discrete kinetics of drug interaction with distinct ion channel state conformations, as it has become clear that such interactions underlie complex emergent kinetics such as use-dependent block. Here, we describe an approach for developing a model for ion channel drug interactions. The method describes the process of extracting rate constants from experimental electrophysiological function data to use as initial conditions for the model parameters. We then describe implementation of a parameter optimization method to refine the model rate constants describing ion channel drug kinetics. The algorithm takes advantage of readily available parallel computing tools to speed up the optimization. Finally, we describe some potential applications of the platform including the potential for gaining fundamental mechanistic insights into ion channel function and applications to in silico drug screening and development

A Real Time Optical Biosensor Assay for Amoxicillin and Other β-Lactams in Water Samples

Antibiotic contamination of drinking water and sewage is a matter of environmental and public health concern. Traditionally, ELISA or HPLC methods have been used to detect and measure antibiotic contamination. By applying an optical biosensing method, biolayer inteferometry (BLI), we have developed a kinetic competition binding assay capable of quantitating less than 1ppm (~33 μM) amoxicillin. Similar to surface plasmon resonance, BLI senses changes that occur upon binding of one molecule to another near a surface to measure association and dissociation. Immobilized amoxicillin was used to screen for binding against an analyte solution of anti-amoxicillin equilibrated with amoxicillin-containing water samples, yielding binding that fit a one-state model. Maximal binding correlated highly with amoxicillin concentration. Simplified analysis of samples from water and sewage treatment plants in Georgia allowed quantitation without kinetic modeling. The assay is sensitive, cost-effective, fast and readily adaptable to a variety of samples and other small molecules

A Real Time Optical Biosensor Assay for Amoxicillin And Other β-Lactams in Water Samples

Antibiotic contamination of drinking water and sewage is a matter of environmental and public health concern. Traditionally, ELISA or HPLC methods have been used to detect and measure antibiotic contamination. By applying an optical biosensing method, biolayer inteferometry (BLI), we have developed a kinetic competition binding assay capable of quantitating less than lppm (~33 μM) amoxicillin. Similar to surface plasmon resonance, BLI senses changes that occur upon binding of one molecule to another near a surface to measure association and dissociation. Immobilized amoxicillin was used to screen for binding against an analyte solution of anti-amoxicillin equilibrated with amoxicillin-containing water samples, yielding binding that fit a one-state model. Maximal binding correlated highly with amoxicillin concentration. Simplified analysis of samples from water and sewage treatment plants in Georgia allowed quantitation without kinetic modeling. The assay is sensitive, cost-effective, fast and readily adaptable to a variety of samples and other small molecules

The self-assembly and evolution of homomeric protein complexes

We introduce a simple "patchy particle" model to study the thermodynamics and dynamics of self-assembly of homomeric protein complexes. Our calculations allow us to rationalize recent results for dihedral complexes. Namely, why evolution of such complexes naturally takes the system into a region of interaction space where (i) the evolutionarily newer interactions are weaker, (ii) subcomplexes involving the stronger interactions are observed to be thermodynamically stable on destabilization of the protein-protein interactions and (iii) the self-assembly dynamics are hierarchical with these same subcomplexes acting as kinetic intermediates.Comment: 4 pages, 4 figure

Oakleaf: an S locus-linked mutation of Primula vulgaris that affects leaf and flower development

•In Primula vulgaris outcrossing is promoted through reciprocal herkogamy with insect-mediated cross-pollination between pin and thrum form flowers. Development of heteromorphic flowers is coordinated by genes at the S locus. To underpin construction of a genetic map facilitating isolation of these S locus genes, we have characterised Oakleaf, a novel S locus-linked mutant phenotype. •We combine phenotypic observation of flower and leaf development, with classical genetic analysis and next-generation sequencing to address the molecular basis of Oakleaf. •Oakleaf is a dominant mutation that affects both leaf and flower development; plants produce distinctive lobed leaves, with occasional ectopic meristems on the veins. This phenotype is reminiscent of overexpression of Class I KNOX-homeodomain transcription factors. We describe the structure and expression of all eight P. vulgaris PvKNOX genes in both wild-type and Oakleaf plants, and present comparative transcriptome analysis of leaves and flowers from Oakleaf and wild-type plants. •Oakleaf provides a new phenotypic marker for genetic analysis of the Primula S locus. We show that none of the Class I PvKNOX genes are strongly upregulated in Oakleaf leaves and flowers, and identify cohorts of 507 upregulated and 314 downregulated genes in the Oakleaf mutant

Standoff Methods for the Detection of Threat Agents: A Review of Several Promising Laser-Based Techniques

Detection of explosives, explosive precursors, or other threat agents presents a number of technological challenges for optical sensing methods. Certainly detecting trace levels of threat agents against a complex background is chief among these challenges; however, the related issues of multiple target distances (from standoff to proximity) and sampling time scales (from passive mines to rapid rate of march convoy protection) for different applications make it unlikely that a single technique will be ideal for all sensing situations. A number of methods for spanning the range of optical sensor technologies exist which, when integrated, could produce a fused sensor system possessing a high level of sensitivity to threat agents and a moderate standoff real-time capability appropriate for portal screening of personnel or vehicles. In this work, we focus on several promising, and potentially synergistic, laser-based methods for sensing threat agents. For each method, we have briefly outlined the technique and report on the current level of capability

Standoff Methods for the Detection of Threat Agents: A Review of Several Promising Laser-Based Techniques

Detection of explosives, explosive precursors, or other threat agents presents a number of technological challenges for optical sensing methods. Certainly detecting trace levels of threat agents against a complex background is chief among these challenges; however, the related issues of multiple target distances (from standoff to proximity) and sampling time scales (from passive mines to rapid rate of march convoy protection) for different applications make it unlikely that a single technique will be ideal for all sensing situations. A number of methods for spanning the range of optical sensor technologies exist which, when integrated, could produce a fused sensor system possessing a high level of sensitivity to threat agents and a moderate standoff real-time capability appropriate for portal screening of personnel or vehicles. In this work, we focus on several promising, and potentially synergistic, laser-based methods for sensing threat agents. For each method, we have briefly outlined the technique and report on the current level of capability

Intramuscular fat in ambulant young adults with bilateral spastic cerebral palsy

BACKGROUND: It is known that individuals with bilateral spastic cerebral palsy (BSCP) have small and weak muscles. However, no studies to date have investigated intramuscular fat infiltration in this group. The objective of this study is to determine whether adults with BSCP have greater adiposity in and around their skeletal muscles than their typically developing (TD) peers as this may have significant functional and cardio-metabolic implications for this patient group. METHODS: 10 young adults with BSCP (7 male, mean age 22.5 years, Gross Motor Function Classification System (GMFCS) levels I-III), and 10 TD young adults (6 male, mean age 22.8 years) took part in this study. 11 cm sections of the left leg of all subjects were imaged using multi-echo gradient echo chemical shift imaging (mDixon). Percentage intermuscular fat (IMAT), intramuscular fat (IntraMF) and a subcutaneous fat to muscle volume ratio (SF/M) were calculated. RESULTS: IntraMF was higher with BSCP for all muscles (p = 0.001-0.013) and was significantly different between GMFCS levels (p < 0.001), with GMFCS level III having the highest IntraMF content. IMAT was also higher with BSCP p < 0.001). No significant difference was observed in SF/M between groups. CONCLUSION: Young adults with BSCP have increased intermuscular and intramuscular fat compared to their TD peers. The relationship between these findings and potential cardio-metabolic and functional sequelae are yet to be investigated