Using the Predicted Structure of the Amot Coiled Coil Homology Domain to Understand Lipid Binding

Angiomotins (Amots) are a family of adapter proteins that modulate cellular polarity, differentiation, proliferation, and migration. Amot family members have a characteristic lipid-binding domain, the coiled coil homology (ACCH) domain that selectively targets the protein to membranes, which has been directly linked to its regulatory role in the cell. Several spot blot assays were used to validate the regions of the domain that participate in its membrane association, deformation, and vesicle fusion activity, which indicated the need for a structure to define the mechanism. Therefore, we sought to understand the structure-function relationship of this domain in order to find ways to modulate these signaling pathways. After many failed attempts to crystallize the ACCH domain of each Amot family member for structural analysis, we decided to pursue homologous models that could be refined using small angle x-ray scattering data. Theoretical models were produced using the homology software SWISS-MODEL and threading software I-TASSER and LOMETS, followed by comparison to SAXS data for model selection and refinement. We present a theoretical model of the domain that is driven by alpha helices and short random coil regions. These alpha helical regions form a classic dimer interface followed by two wide spread legs that we predict to be the lipid binding interface

Toward understanding the structure of Amot’s ACCH Domain

poster abstractAmots are a family of adaptor proteins widely involved in cell signaling and lipid binding. Amot80 has been linked to cellular proliferation in breast cancer via the VEGF and MAPK signaling pathways, while Amot130 and AmotL1 have been linked to cellular inhibition via the HIPPO signaling pathway. Amot family members also have a characteristic lipid-binding domain – named the ACCH Domain for its predicted coil-coil structure – that has the ability to selectively target phosphoinositols followed by deformation of the membrane. Understanding the structure-function relationship of this domain may provide options to modulate these signaling pathways, directly affecting cellular differentiation, proliferation, and migration. Extensive crystallization attempts for this domain have failed, leading to a bioinformatics and biophysics-combined approach. Using SAXS, data for the globular structure of Amot80 has been generated and analyzed. Additionally, the threading programs ITASSER and LOMETS were used to develop 20 computational theoretical models. By fitting the computational models to the SAXS data, potential ACCH domain models were generated, and then scored based on accuracy of fit via C-score, TMScore, and RMSD values. This 3D model can then be used to discover how Amot interacts with lipids and further the understanding of Amot’s role in the cancer-signaling cascade

Stocktake and analysis of legume evaluation for tropical pastures in Australia

There has been a large effort dedicated to the evaluation of a wide variety of sub-tropical and tropical pasture legumes in the past. This large body of information is very valuable for guiding any future legume development activities, yet much of this information was at risk of being lost. This project aimed to collate and store this tropical legume evaluation data and use this and knowledge from past researchers to recommend priority R&D approaches and activities for future pasture legume development. Together with retired pasture researchers, legume evaluation datasets were identified, prioritised, and collated into a database which captured over 180 000 data records collected from 567 sites across northern Australia. Using this large integrated dataset, high power statistical approaches were used to identify legume species which performed well across this large range of evaluation sites. Several species and genera were identified which warrant further investigation and further in-depth analysis of the database in species or genera of interest would be valuable. A gap analysis of commercially proven, underused and prospective legumes was conducted across the key production regions of northern Australia. A range of material was identified which could offer potential improvements in seed production, cold, drought or grazing tolerance compared to the current released varieties

After neoliberalisation? Monetary indiscipline, crisis and the state

Across the advanced capitalist states, the post-crisis conjuncture has been characterised by both marked continuity and profound change. While regressive distributional trends in place before the 2008 crisis have intensified, a number of highly unorthodox policy interventions have also emerged. In particular, a new regime of ‘loose’ monetary policy has crystallised, exemplified by record low interest rates and sustained programmes of quantitative easing. Existing approaches within economic geography are, we contend, ill-equipped to deal with these transformations. Engaging with the ‘variegated neoliberalisation approach’ – associated with Jamie Peck and his collaborators – the article argues that existing conceptualisations of neoliberalisation understate the key significance that central state institutions play in securing advanced capitalist development. They therefore miss the key role that monetary indiscipline has played in sustaining capitalist development since 2008. This argument is substantiated empirically through a case study of state intervention in the UK housing market in the post-crisis conjuncture. Focusing on the Help to Buy Scheme and the buy-to-let market, the article argues that the UK's loose monetary policy regime has produced novel patterns of spatial divergence across the UK regions while simultaneously consolidating the UK's dysfunctional financialised model of capitalism

Descriptive Analysis of a Baseline Concussion Battery Among U.S. Service Academy Members: Results from the Concussion Assessment, Research, and Education (CARE) Consortium

Introduction The prevalence and possible long-term consequences of concussion remain an increasing concern to the U.S. military, particularly as it pertains to maintaining a medically ready force. Baseline testing is being used both in the civilian and military domains to assess concussion injury and recovery. Accurate interpretation of these baseline assessments requires one to consider other influencing factors not related to concussion. To date, there is limited understanding, especially within the military, of what factors influence normative test performance. Given the significant physical and mental demands placed on service academy members (SAM), and their relatively high risk for concussion, it is important to describe demographics and normative profile of SAMs. Furthermore, the absence of available baseline normative data on female and non-varsity SAMs makes interpretation of post-injury assessments challenging. Understanding how individuals perform at baseline, given their unique individual characteristics (e.g., concussion history, sex, competition level), will inform post-concussion assessment and management. Thus, the primary aim of this manuscript is to characterize the SAM population and determine normative values on a concussion baseline testing battery. Materials and Methods All data were collected as part of the Concussion Assessment, Research and Education (CARE) Consortium. The baseline test battery included a post-concussion symptom checklist (Sport Concussion Assessment Tool (SCAT), psychological health screening inventory (Brief Symptom Inventory (BSI-18) and neurocognitive evaluation (ImPACT), Balance Error Scoring System (BESS), and Standardized Assessment of Concussion (SAC). Linear regression models were used to examine differences across sexes, competition levels, and varsity contact levels while controlling for academy, freshman status, race, and previous concussion. Zero inflated negative binomial models estimated symptom scores due to the high frequency of zero scores. Results Significant, but small, sex effects were observed on the ImPACT visual memory task. While, females performed worse than males (p < 0.0001, pη2 = 0.01), these differences were small and not larger than the effects of the covariates. A similar pattern was observed for competition level on the SAC. There was a small, but significant difference across competition level. SAMs participating in varsity athletics did significantly worse on the SAC compared to SAMs participating in club or intramural athletics (all p’s < 0.001, η2 = 0.01). When examining symptom reporting, males were more than two times as likely to report zero symptoms on the SCAT or BSI-18. Intramural SAMs had the highest number of symptoms and severity compared to varsity SAMs (p < 0.0001, Cohen’s d < 0.2). Contact level was not associated with SCAT or BSI-18 symptoms among varsity SAMs. Notably, the significant differences across competition level on SCAT and BSI-18 were sub-clinical and had small effect sizes. Conclusion The current analyses provide the first baseline concussion battery normative data among SAMs. While statistically significant differences may be observed on baseline tests, the effect sizes for competition and contact levels are very small, indicating that differences are likely not clinically meaningful at baseline. Identifying baseline differences and significant covariates is important for future concussion-related analyses to inform concussion evaluations for all athlete levels

Trunk and lower extremity movement patterns, stress fracture risk factors, and biomarkers of bone turnover in military trainees

Context: Military service members commonly sustain lower extremity stress fractures (SFx). How SFx risk factors influence bone metabolism is unknown. Understanding how SFx risk factors influence bone metabolism may help to optimize risk-mitigation strategies. Objective: To determine how SFx risk factors influence bone metabolism. Design: Cross-sectional study. Setting: Military service academy. Patients or Other Participants: Forty-five men (agepre ¼ 18.56 6 1.39 years, heightpre ¼ 176.95 6 7.29 cm, masspre ¼ 77.20 6 9.40 kg; body mass indexpre ¼ 24.68 6 2.87) who completed Cadet Basic Training (CBT). Individuals with neurologic or metabolic disorders were excluded. Intervention(s): We assessed SFx risk factors (independent variables) with (1) the Landing Error Scoring System (LESS), (2) self-reported injury and physical activity questionnaires, and (3) physical fitness tests. We assessed bone biomarkers (dependent variables; procollagen type I amino-terminal propeptide [PINP] and cross-linked collagen telopeptide [CTx-1]) via serum. Main Outcome Measure(s): A markerless motion-capture system was used to analyze trunk and lower extremity biomechanics via the LESS. Serum samples were collected post-CBT; enzyme-linked immunosorbent assays determined PINP and CTx-1 concentrations, and PINP: CTx-1 ratios were calculated. Linear regression models demonstrated associations between SFx risk factors and PINP and CTx-1 concentrations and PINP: CTx-1 ratio. Biomarker concentration mean differences with 95% confidence intervals were calculated. Significance was set a priori using a ≤ .10 for simple and a ≤ .05 for multiple regression analyses. Results: The multiple regression models incorporating LESS and SFx risk factor data predicted the PINP concentration (R2 ¼ 0.47, P ¼ .02) and PINP: CTx-1 ratio (R2 ¼ 0.66, P ¼ .01). The PINP concentration was increased by foot internal rotation, trunk flexion, CBT injury, sit-up score, and pre- to post-CBT mass changes. The CTx-1 concentration was increased by heel-to-toe landing and post-CBT mass. The PINP: CTx-1 ratio was increased by foot internal rotation, lower extremity sagittal-plane displacement (inversely), CBT injury, sit-up score, and pre- to post-CBT mass changes. Conclusions: Stress fracture risk factors accounted for 66% of the PINP: CTx-1 ratio variability, a potential surrogate for bone health. Our findings provide insight into how SFx risk factors influence bone health. This information can help guide SFx risk-mitigation strategies

Biomechanical risk factors for lower extremity stress fracture

Objectives: Stress fracture injuries disproportionately affect athletes and military service members and little is known about the modifiable biomechanical risk factors associated with these injuries. The purpose of this study was to prospectively examine the association between neuromuscular and biomechanical factors upon entry to military service and the subsequent incidence of lower-extremity stress fracture injury during four years of follow-up. Methods: We analyzed data from the JUMP-ACL cohort, an existing prospective cohort study of military cadets. JUMP-ACL conducted detailed motion analysis during a jump landing task at the initiation of each subject’s military career. We limited our analyses to the class years 2009-2013 (i.e., subjects who completed baseline testing in 2005-2008). There were 1895 subjects available for analysis. Fifty-two subjects reported a history of stress fracture at baseline and were excluded from further analysis leaving 1843 subjects. Incident lower extremity-stress fracture cases were identified through the Defense Medical Surveillance System and the Cadet Injury and Illness Tracking System during the follow-up period. The electronic medical records of each potential incident case were reviewed and each case was confirmed by an adjudication committee consisting of two sports medicine fellowship trained orthopaedic surgeons. The primary outcome of interest was the incidence rate of lower-extremity stress fracture during the follow-up period. The association between incident stress fracture and sagittal, frontal, and transverse plane hip and knee kinematics during the jump-landing task were examined at initial contact (IC), 15%(T15), 50%(T50), 85%(T85) and 100%(T100) of stance phase. Descriptive plots of all biomechanical variables along with 95% confidence intervals (CI) were generated during the stance phase of the jump landing task. Univariate and multivariable Poisson regression models were used to estimate the association between baseline biomechanical factors and the incidence rate of lower-extremity stress fracture during follow-up. Results: Overall, 94 (5.1%, 95%CI: 4.14, 6.21) subjects sustained an incident stress fracture during the follow-up period. The incidence rate for stress fracture injuries among females was nearly three times greater when compared to males (IRR=2.86, 95%CI: 1.88, 4.34, p<0.001). Compared to those with greater than 5° of knee valgus, subjects with neutral or varus knee alignment experienced incidence rates for stress fracture that were 43%-53% lower at IC (IRR=0.57, 95%CI: 0.29, 1.11, p=0.10), T50 (IRR=0.47, 95%CI=0.23, 1.00, p=0.05), and T85 (IRR=0.53, 95%CI: 0.29, 0.98, p=0.04). Subjects with greater than 5° of internal knee rotation exhibited rates for stress fracture that were 2-4 times higher at T15 (IRR=2.31, 95%CI: 1.01, 5.27, p=0.05), T50 (IRR=3.98, 95%CI: 0.99, 16.00, p=0.05), and T85 (IRR=2.31, 95%CI: 0.86, 6.23, p=0.10), when compared to those with neutral or external knee rotation alignment. Conclusion: Several potentially modifiable biomechanical factors at the time of entry into military service appear to be associated with the subsequent rate of stress fracture. It is possible that injury prevention programs targeted to address these biomechanical movement patterns may reduce the risk of stress fracture injury in athletes and military service members

Automated quantification of the landing error scoring system with a markerless motion-Capture system

Context: The Landing Error Scoring System (LESS) can be used to identify individuals with an elevated risk of lower extremity injury. The limitation of the LESS is that raters identify movement errors from video replay, which is time-consuming and, therefore, may limit its use by clinicians. A markerless motion-capture system may be capable of automating LESS scoring, thereby removing this obstacle. Objective: To determine the reliability of an automated markerless motion-capture system for scoring the LESS. Design: Cross-sectional study. Setting: United States Military Academy. Patients or Other Participants: A total of 57 healthy, physically active individuals (47 men, 10 women; age ¼ 18.6 6 0.6 years, height ¼ 174.5 6 6.7 cm, mass ¼ 75.9 6 9.2 kg). Main Outcome Measure(s): Participants completed 3 jump-landing trials that were recorded by standard video cameras and a depth camera. Their movement quality was evaluated by expert LESS raters (standard video recording) using the LESS rubric and by software that automates LESS scoring (depth-camera data). We recorded an error for a LESS item if it was present on at least 2 of 3 jump-landing trials. We calculated j statistics, prevalence- and bias-adjusted j (PABAK) statistics, and percentage agreement for each LESS item. Interrater reliability was evaluated between the 2 expert rater scores and between a consensus expert score and the markerless motion-capture system score. Results: We observed reliability between the 2 expert LESS raters (average j ¼ 0.45 6 0.35, average PABAK ¼ 0.67 6 0.34; percentage agreement ¼ 0.83 6 0.17). The markerless motion-capture system had similar reliability with consensus expert scores (average j ¼ 0.48 6 0.40, average PABAK ¼ 0.71 6 0.27; percentage agreement ¼ 0.85 6 0.14). However, reliability was poor for 5 LESS items in both LESS score comparisons. Conclusions: A markerless motion-capture system had the same level of reliability as expert LESS raters, suggesting that an automated system can accurately assess movement. Therefore, clinicians can use the markerless motion-capture system to reliably score the LESS without being limited by the time requirements of manual LESS scoring

Automated Landing Error Scoring System Performance and the Risk of Bone Stress Injury in Military Trainees

Context: Lower extremity bone stress injuries (BSIs) place a significant burden on the health and readiness of the US Armed Forces. Objective: To determine if preinjury baseline performance on an expanded and automated 22-item version of the Landing Error Scoring System (LESS-22) was associated with the incidence of BSIs in a military training population. Design: Prospective cohort study. Setting: US Military Academy at West Point, NY. Patients or Other Participants: A total of 2235 incoming cadets (510 females [22.8%]). Main Outcome Measure(s): Multivariable Poisson regression models were used to produce adjusted incidence rate ratios (IRRs) to quantify the association between preinjury LESS scores and BSI incidence rate during follow-up and were adjusted for pertinent risk factors. Risk factors were included as covariates in the final model if the 95% CI for the crude IRR did not contain 1.00. Results: A total of 54 BSIs occurred during the study period, resulting in an overall incidence rate of 0.07 BSI per 1000 person-days (95% CI = 0.05, 0.09). The mean number of exposure days was 345.4 6 61.12 (range = 3–368 days). The final model was adjusted for sex and body mass index and yielded an adjusted IRR for a LESS-22 score of 1.06 (95% CI = 1.002, 1.13; P = .04), indicating that each additional LESS error documented at baseline was associated with a 6.0% increase in the incidence rate of BSI during the follow-up period. In addition, 6 individual LESS-22 items, including 2 newly added items, were significantly associated with the BSI incidence. Conclusions: We provided evidence that performance on the expanded and automated version of the LESS was associated with the BSI incidence in a military training population. The automated LESS-22 may be a scalable solution for screening military training populations for BSI risk

Reference Values for the Marx Activity Rating Scale in a Young Athletic Population: History of Knee Ligament Injury Is Associated With Higher Scores

Activity-related patient-reported outcome measures are an important component of assessment after knee ligament injury in young and physically active patients; however, normative data for most activity scales are limited