Exploration of Drug Therapies for Post-Traumatic Elbow Joint Contracture

This semester I worked in the Musculoskeletal Soft Tissue Laboratory to explore the potential drug therapies for post-traumatic joint contracture (PTJC), or arthrofibrosis, in the elbow following a traumatic joint injury. To simulate the potential effects of these drugs in the elbow post-injury, this study utilized an in-vitro model using collagen gels and NIH-3T3 cells to mimick the contraction of capsule tissue in the elbow and the cells thought to contribute to disease progression in the capsule, namely fibroblasts and myofibroblasts. The first part of the study tested the effects of two drugs, losartan and simvastatin, on decreasing contraction. The standard testing procedure required that the gels be seeded with cells, then administered the appropriate drug concentration and mixture, and then observed for a period of six days. Once we narrowed down the drug formulations to a few possible candidates, we considered the issues related to timing of treatment and pharmacokinetics of these drugs if administered into the human elbow; more specifically, we wanted to understand how factors like drug clearance, or the treatment of PTJC after its onset, would affect the drug’s effectiveness. To this end, the second part of the study looked at how exposure time of the drug to the cells affected the drug’s function; more specifically, the impact of both time delay and a shorter exposure period on the performance of the drugs were explored. It quickly became apparent through these studies that simvastatin could halt contraction, but did nothing to reverse it. The third and final part of the study tested the ability of the hormone relaxing on decreasing contraction. By the end of the semester, we determined that,within the construct of our experimental set-up and parameters, simvastatin was the only promising candidate for treatment of PTJC

Policy Recommendations for Meeting the Grand Challenge to Close the Health Gap

This brief was created forSocial Innovation for America’s Renewal, a policy conference organized by the Center for Social Development in collaboration with the American Academy of Social Work & Social Welfare, which is leading theGrand Challenges for Social Work initiative to champion social progress. The conference site includes links to speeches, presentations, and a full list of the policy briefs

Cooling and the SU(2) Instanton Vaccuum

We present results of an investigation into the nature of instantons in 4-dimensional pure gauge lattice $SU(2)$\ obtained from configurations which have been cooled using an under-relaxed cooling algorithm. We discuss ways of calibrating the cooling and the effects of different degrees of cooling, and compare our data for the shapes, sizes and locations of instantons with continuum results. In this paper we extend the ideas and techniques developed by us for use in $O(3)$, and compare the results with those obtained by other groups.Comment: 22 pages, LaTeX, uuencoded compressed tarfile of figures sent separately. Full (compressed) postscript version (118k)available from ftp://rock.helsinki.fi/pub/preprints/tft/Year1995/HU-TFT-95-21/paper.ps.

A Simple Bioluminescent Method for Measuring D-Amino Acid Oxidase Activity

D-Amino acid oxidase (DAO) plays important roles in regulating D-amino acid neurotransmitters and was recently identified as a key enzyme integral to hydrogen sulfide production from D-Cys. We report here the development of a simple biocompatible, bioluminescent method for measuring DAO activity based on the highly selective condensation of D-Cys with 6-hydroxy-2-cyanobenzothiazole (CBT-OH) to form D-luciferin

Multifidelity Active Learning for Failure Estimation of TRISO Nuclear Fuel

The Tristructural isotropic (TRISO)-coated particle fuel is a robust nuclear fuel proposed to be used for multiple modern nuclear technologies. Therefore, characterizing its safety is vital for the reliable operation of nuclear technologies. However, the TRISO fuel failure probabilities are small and the computational model is time consuming to evaluate them using traditional Monte Carlo-type approaches. In the paper, we present a multifidelity active learning approach to efficiently estimate small failure probabilities given an expensive computational model. Active learning suggests the next best training set for optimal subsequent predictive performance and multifidelity modeling uses cheaper low-fidelity models to approximate the high-fidelity model output. After presenting the multifidelity active learning approach, we apply it to efficiently predict TRISO failure probability and make comparisons to the reference results

Validity of the Short Recovery and Stress Scale in Collegiate Weightlifters

Introduction: Monitoring an athlete’s stress and recovery state across sequential training bouts can be used to gauge fitness and fatigue levels (i.e., preparedness). Previous studies have used jumping performance, biochemical markers, and questionnaires to estimate preparedness. However, self-report questionnaires are the most common due to economical and practical means. The Short Recovery and Stress Scale (SRSS) is an 8-item questionnaire ideal for monitoring; however, convergent validity of the SRSS with physiological and performance measures needs to be investigated. Purpose: Thus, the purpose of this study was to determine whether changes in collegiate weightlifter’s training volume-load, biochemical markers, and jumping performance correlate to changes in the SRSS. Methods: 12 collegiate weightlifters (8 males, 4 females) with \u3e1yr of competition experience trained for 4 weeks and were tested at the beginning of each week (T1-T4). Training volume-load with displacement (VLd) was monitored weekly for all exercises. Testing was conducted following an overnight fast and included hydration, SRSS (0-6 scale with 6 indicating highest recovery and stress), and blood draws (resting testosterone (T), cortisol (C), T:C, creatine kinase (CK)) followed by unloaded (0kg) and loaded (20kg) squat jumps (SJ) on force platforms. Pearson correlation coefficients were calculated between the change in SRSS scores and all other variables from T1-T2, T1-T3, and T1-T4. Alpha level was set at p\u3c 0.05. Results: Inverse relationships were observed between changes in recovery items and C (r= -0.61 to -0.72, p\u3c 0.05), and unloaded and loaded SJ height and relative peak power (r= -0.59 to -0.64, p\u3c 0.05) from T1 to T2, and T1 to T3. Similarly, positive relationships were observed between changes in stress items and C (r=0.61 to 0.72, p\u3c 0.05), and unloaded and loaded SJ height and relative peak power (r=0.58 to 0.84, p\u3c 0.05) across all time points. No significant relationships were observed between changes in SRSS items and VLd or T, T:C, CK. Conclusion: Relationships between changes in some SRSS items and C agree with previous findings highlighting C as an indicator of training stress. Nonetheless, the non-significant relationships between changes in SRSS items, VLd, and other biochemical markers disagrees with previous findings. This may partly be explained by the smaller undulations in VLd in the current study, which is characteristic of actual training. Further, relationships between changes in some SRSS items and jumping performance were opposite of what was expected indicating athlete’s perception of their stress and recovery state does not always correspond with their ability to perform. Practical Application: These results provide some evidence for the convergent validity of the SRSS. Nonetheless, weightlifting coaches should be cautious in using results from a single test to estimate an athlete’s preparedness. Thus, we recommend the SRSS be included as part of a multi-dimensional monitoring program for weightlifters

A model for the break-up of a tuft of fibers

A simple model for the forces acting on a single fiber as it is withdrawn from a tangled fiber assembly is proposed. Particular emphasis is placed on understanding the dynamics of the reptating fiber with respect to the entanglement of fibers within the tuft. The resulting two-parameter model captures the qualitative features of experimental simulation. The model is extended to describe the break-up of a tuft. The results show good agreement with experiment and indicate where a fiber is most likely to fracture based on the density of fiber end-points