Assessing the Awareness of Lead Hazards in the Greater Burlington Area

Introduction. Lead is a heavy metal found in and around homes built before 1978, comprising more than 80% of the housing stock in Chittenden County, Vermont. Lead exposure during infancy and childhood can have deleterious effects on development. Our study assessed baseline community understanding of potential household lead hazards in Chittenden County, Vermont. Methods.. 123 paper, 10-question surveys were randomly administered to Chittenden County, VT residents to assess recognition of lead toxicology symptoms and awareness of lead safety programs. Scores were treated as continuous variables, demographically grouped, and analyzed using non-parametric statistical analysis (Mann-Whitney & Kruskal-Wallis). Individual questions were treated as dichotomous variables, demographically grouped and analyzed using chi-squared testing. Results.. 48% of survey participants understood the interaction between ADHD and lead or knew the importance of window maintenance. 54.5% were aware of the Burlington Lead Program\u27s assistance program. Participants earning less than $60,000 and those with less than a graduate degree scored statistically lower (p Conclusion.. Lesser-known lead poisoning symptoms and home interventions that decrease lead exposure should be emphasized to the community. High-risk groups requiring targeted education include those who rent, have lower income and education levels. Primary care providers could serve a larger role in educating patients. Additional efforts should be made to publicize services offered by the Burlington Lead Program.https://scholarworks.uvm.edu/comphp_gallery/1241/thumbnail.jp

Mathematical modelling of fluid flow and solute transport to define operating parameters for in vitro perfusion cell culture systems

In recent years, there has been a move away from the use of static in vitro two-dimensional cell culture models for testing the chemical safety and efficacy of drugs. Such models are increasingly being replaced by more physiologically relevant cell culture systems featuring dynamic flow and/or three-dimensional structures of cells. While it is acknowledged that such systems provide a more realistic environment within which to test drugs, progress is being hindered by a lack of understanding of the physical and chemical environment that the cells are exposed to. Mathematical and computational modelling may be exploited in this regard to unravel the dependency of the cell response on spatio-temporal differences in chemical and mechanical cues, thereby assisting with the understanding and design of these systems. In this paper, we present a mathematical modelling framework that characterizes the fluid flow and solute transport in perfusion bioreactors featuring an inlet and an outlet. To demonstrate the utility of our model, we simulated the fluid dynamics and solute concentration profiles for a variety of different flow rates, inlet solute concentrations and cell types within a specific commercial bioreactor chamber. Our subsequent analysis has elucidated the basic relationship between inlet flow rate and cell surface flow speed, shear stress and solute concentrations, allowing us to derive simple but useful relationships that enable prediction of the behaviour of the system under a variety of experimental conditions, prior to experimentation. We describe how the model may used by experimentalists to define operating parameters for their particular perfusion cell culture systems and highlight some operating conditions that should be avoided. Finally, we critically comment on the limitations of mathematical and computational modelling in this field, and the challenges associated with the adoption of such methods

Challenges of Data Management Training for Graduate Students at a Large Research University

Objective: To describe the challenges and outcomes of the University of Massachusetts Amherst Libraries\u27 Data Working Group\u27s series of training workshops for graduate students on the subject of data management and preservation, with specific regard to the data management requirements of the National Science Foundation and National Institutes of Health. Participants: The Libraries\u27 Data Working Group is composed of six members with expertise in project management, systems and web development, scholarly communication, digital archives and metadata, and science and social science librarianship. The Data Working Group is one of three subgroups of the Digital Strategies Group at the University Libraries. Description: The University of Massachusetts Amherst Libraries provides a number of services to faculty and graduate students in support of research at an institution classified as a Research University with Very High research activity (RU/VH) by the Carnegie Foundation[1]. Recognizing a high demand for greater data education, the Libraries\u27 Data Working Group has conducted workshops for graduate students in specific disciplines -- humanities, social sciences, and sciences -- designed to address their data needs and highlight smart data management practices. Graduate students were also guided through the data management requirements of national funding agencies and potential solutions. Results: In its current capacity the Data Working Group provides educational workshops and individual consulting sessions for faculty and graduate students. The Data Working Group observed a significant portion of graduate students who had no prior experience with smart data practices or useful data management resources. This process has identified a clear need for wider, more intensive education for graduate students on data practices and the data management requirements of national funding agencies. [1] http://www.umass.edu/umhome/research.ph

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

Association of Blood Biomarkers With Acute Sport-Related Concussion in Collegiate Athletes: Findings From the NCAA and Department of Defense CARE Consortium

Importance: There is potential scientific and clinical value in validation of objective biomarkers for sport-related concussion (SRC). Objective: To investigate the association of acute-phase blood biomarker levels with SRC in collegiate athletes. Design, Setting, and Participants: This multicenter, prospective, case-control study was conducted by the National Collegiate Athletic Association (NCAA) and the US Department of Defense Concussion Assessment, Research, and Education (CARE) Consortium from February 20, 2015, to May 31, 2018, at 6 CARE Advanced Research Core sites. A total of 504 collegiate athletes with concussion, contact sport control athletes, and non-contact sport control athletes completed clinical testing and blood collection at preseason baseline, the acute postinjury period, 24 to 48 hours after injury, the point of reporting being asymptomatic, and 7 days after return to play. Data analysis was conducted from March 1 to November 30, 2019. Main Outcomes and Measures: Glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase-L1 (UCH-L1), neurofilament light chain, and tau were quantified using the Quanterix Simoa multiplex assay. Clinical outcome measures included the Sport Concussion Assessment Tool-Third Edition (SCAT-3) symptom evaluation, Standardized Assessment of Concussion, Balance Error Scoring System, and Brief Symptom Inventory 18. Results: A total of 264 athletes with concussion (mean [SD] age, 19.08 [1.24] years; 211 [79.9%] male), 138 contact sport controls (mean [SD] age, 19.03 [1.27] years; 107 [77.5%] male), and 102 non-contact sport controls (mean [SD] age, 19.39 [1.25] years; 82 [80.4%] male) were included in the study. Athletes with concussion had significant elevation in GFAP (mean difference, 0.430 pg/mL; 95% CI, 0.339-0.521 pg/mL; P < .001), UCH-L1 (mean difference, 0.449 pg/mL; 95% CI, 0.167-0.732 pg/mL; P < .001), and tau levels (mean difference, 0.221 pg/mL; 95% CI, 0.046-0.396 pg/mL; P = .004) at the acute postinjury time point compared with preseason baseline. Longitudinally, a significant interaction (group × visit) was found for GFAP (F7,1507.36 = 16.18, P < .001), UCH-L1 (F7,1153.09 = 5.71, P < .001), and tau (F7,1480.55 = 6.81, P < .001); the interaction for neurofilament light chain was not significant (F7,1506.90 = 1.33, P = .23). The area under the curve for the combination of GFAP and UCH-L1 in differentiating athletes with concussion from contact sport controls at the acute postinjury period was 0.71 (95% CI, 0.64-0.78; P < .001); the acute postinjury area under the curve for all 4 biomarkers combined was 0.72 (95% CI, 0.65-0.79; P < .001). Beyond SCAT-3 symptom score, GFAP at the acute postinjury time point was associated with the classification of athletes with concussion from contact controls (β = 12.298; 95% CI, 2.776-54.481; P = .001) and non-contact sport controls (β = 5.438; 95% CI, 1.676-17.645; P = .005). Athletes with concussion with loss of consciousness or posttraumatic amnesia had significantly higher levels of GFAP than athletes with concussion with neither loss of consciousness nor posttraumatic amnesia at the acute postinjury time point (mean difference, 0.583 pg/mL; 95% CI, 0.369-0.797 pg/mL; P < .001). Conclusions and Relevance: The results suggest that blood biomarkers can be used as research tools to inform the underlying pathophysiological mechanism of concussion and provide additional support for future studies to optimize and validate biomarkers for potential clinical use in SRC

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A cohort study to identify and evaluate concussion risk factors across multiple injury settings: findings from the CARE Consortium

BACKGROUND: Concussion, or mild traumatic brain injury, is a major public health concern affecting 42 million individuals globally each year. However, little is known regarding concussion risk factors across all concussion settings as most concussion research has focused on only sport-related or military-related concussive injuries. METHODS: The current study is part of the Concussion, Assessment, Research, and Education (CARE) Consortium, a multi-site investigation on the natural history of concussion. Cadets at three participating service academies completed annual baseline assessments, which included demographics, medical history, and concussion history, along with the Sport Concussion Assessment Tool (SCAT) symptom checklist and Brief Symptom Inventory (BSI-18). Clinical and research staff recorded the date and injury setting at time of concussion. Generalized mixed models estimated concussion risk with service academy as a random effect. Since concussion was a rare event, the odds ratios were assumed to approximate relative risk. RESULTS: Beginning in 2014, 10,604 (n = 2421, 22.83% female) cadets enrolled over 3 years. A total of 738 (6.96%) cadets experienced a concussion, 301 (2.84%) concussed cadets were female. Female sex and previous concussion were the most consistent estimators of concussion risk across all concussion settings. Compared to males, females had 2.02 (95% CI: 1.70-2.40) times the risk of a concussion regardless of injury setting, and greater relative risk when the concussion occurred during sport (Odds Ratio (OR): 1.38 95% CI: 1.07-1.78). Previous concussion was associated with 1.98 (95% CI: 1.65-2.37) times increased risk for any incident concussion, and the magnitude was relatively stable across all concussion settings (OR: 1.73 to 2.01). Freshman status was also associated with increased overall concussion risk, but was driven by increased risk for academy training-related concussions (OR: 8.17 95% CI: 5.87-11.37). Medical history of headaches in the past 3 months, diagnosed ADD/ADHD, and BSI-18 Somatization symptoms increased overall concussion risk. CONCLUSIONS: Various demographic and medical history factors are associated with increased concussion risk. While certain factors (e.g. sex and previous concussion) are consistently associated with increased concussion risk, regardless of concussion injury setting, other factors significantly influence concussion risk within specific injury settings. Further research is required to determine whether these risk factors may aid in concussion risk reduction or prevention

Plasma Biomarker Concentrations Associated With Return to Sport Following Sport-Related Concussion in Collegiate Athletes—A Concussion Assessment, Research, and Education (CARE) Consortium Study

Importance: Identifying plasma biomarkers associated with the amount of time an athlete may need before they return to sport (RTS) following a sport-related concussion (SRC) is important because it may help to improve the health and safety of athletes. Objective: To examine whether plasma biomarkers can differentiate collegiate athletes who RTS in less than 14 days or 14 days or more following SRC. Design, Setting, and Participants: This multicenter prospective diagnostic study, conducted by the National Collegiate Athletics Association–Department of Defense Concussion Assessment, Research, and Education Consortium, included 127 male and female athletes who had sustained an SRC while enrolled at 6 Concussion Assessment, Research, and Education Consortium Advanced Research Core sites as well as 2 partial–Advanced Research Core military service academies. Data were collected between February 2015 and May 2018. Athletes with SRC completed clinical testing and blood collection at preseason (baseline), postinjury (0-21 hours), 24 to 48 hours postinjury, time of symptom resolution, and 7 days after unrestricted RTS. Main Outcomes and Measures: A total of 3 plasma biomarkers (ie, total tau protein, glial fibrillary acidic protein [GFAP], and neurofilament light chain protein [Nf-L]) were measured using an ultrasensitive single molecule array technology and were included in the final analysis. RTS was examined between athletes who took less than 14 days vs those who took 14 days or more to RTS following SRC. Linear mixed models were used to identify significant interactions between period by RTS group. Area under the receiver operating characteristic curve analyses were conducted to examine whether these plasma biomarkers could discriminate between RTS groups. Results: The 127 participants had a mean (SD) age of 18.9 (1.3) years, and 97 (76.4%) were men; 65 (51.2%) took less than 14 days to RTS, and 62 (48.8%) took 14 days or more to RTS. Linear mixed models identified significant associations for both mean (SE) plasma total tau (24-48 hours postinjury, <14 days RTS vs ≥14 days RTS: −0.65 [0.12] pg/mL vs −0.14 [0.14] pg/mL; P = .008) and GFAP (postinjury, 14 days RTS vs ≥14 days RTS: 4.72 [0.12] pg/mL vs 4.39 [0.11] pg/mL; P = .04). Total tau at the time of symptom resolution had acceptable discrimination power (area under the receiver operating characteristic curve, 0.75; 95% CI, 0.63-0.86; P < .001). We also examined a combined plasma biomarker panel that incorporated Nf-L, GFAP, and total tau at each period to discriminate RTS groups. Although the analyses did reach significance at each time period when combined, results indicated that they were poor at distinguishing the groups (area under the receiver operating characteristic curve, <0.7). Conclusions and Relevance: The findings of this study suggest that measures of total tau and GFAP may identify athletes who will require more time to RTS. However, further research is needed to improve our ability to determine recovery following an SRC.This publication was made possible with support from the Grand Alliance Concussion Assessment, Research, and Education (CARE) Consortium, funded, in part by the NCAA and the Department of Defense. The US Army Medical Research Acquisition Activity, 820 Chandler St, Ft Detrick, MD 21702, is the awarding and administering acquisition office. This work was supported by the Office of the Assistant Secretary of Defense for Health Affairs through the Psychological Health and Traumatic Brain Injury Program under award No. W81XWH-14-2-0151

Assessment of Blood Biomarker Profile After Acute Concussion During Combative Training Among US Military Cadets

Importance: Validation of protein biomarkers for concussion diagnosis and management in military combative training is important, as these injuries occur outside of traditional health care settings and are generally difficult to diagnose. Objective: To investigate acute blood protein levels in military cadets after combative training-associated concussions. Design, setting, and participants: This multicenter prospective case-control study was part of a larger cohort study conducted by the National Collegiate Athletic Association and the US Department of Defense Concussion Assessment Research and Education (CARE) Consortium from February 20, 2015, to May 31, 2018. The study was performed among cadets from 2 CARE Consortium Advanced Research Core sites: the US Military Academy at West Point and the US Air Force Academy. Cadets who incurred concussions during combative training (concussion group) were compared with cadets who participated in the same combative training exercises but did not incur concussions (contact-control group). Clinical measures and blood sample collection occurred at baseline, the acute postinjury point (<6 hours), the 24- to 48-hour postinjury point, the asymptomatic postinjury point (defined as the point at which the cadet reported being asymptomatic and began the return-to-activity protocol), and 7 days after return to activity. Biomarker levels and estimated mean differences in biomarker levels were natural log (ln) transformed to decrease the skewness of their distributions. Data were collected from August 1, 2016, to May 31, 2018, and analyses were conducted from March 1, 2019, to January 14, 2020. Exposure: Concussion incurred during combative training. Main outcomes and measures: Proteins examined included glial fibrillary acidic protein, ubiquitin C-terminal hydrolase-L1, neurofilament light chain, and tau. Quantification was conducted using a multiplex assay (Simoa; Quanterix Corp). Clinical measures included the Sport Concussion Assessment Tool-Third Edition symptom severity evaluation, the Standardized Assessment of Concussion, the Balance Error Scoring System, and the 18-item Brief Symptom Inventory. Results: Among 103 military service academy cadets, 67 cadets incurred concussions during combative training, and 36 matched cadets who engaged in the same training exercises did not incur concussions. The mean (SD) age of cadets in the concussion group was 18.6 (1.3) years, and 40 cadets (59.7%) were male. The mean (SD) age of matched cadets in the contact-control group was 19.5 (1.3) years, and 25 cadets (69.4%) were male. Compared with cadets in the contact-control group, those in the concussion group had significant increases in glial fibrillary acidic protein (mean difference in ln values, 0.34; 95% CI, 0.18-0.50; P < .001) and ubiquitin C-terminal hydrolase-L1 (mean difference in ln values, 0.97; 95% CI, 0.44-1.50; P < .001) levels at the acute postinjury point. The glial fibrillary acidic protein level remained high in the concussion group compared with the contact-control group at the 24- to 48-hour postinjury point (mean difference in ln values, 0.22; 95% CI, 0.06-0.38; P = .007) and the asymptomatic postinjury point (mean difference in ln values, 0.21; 95% CI, 0.05-0.36; P = .01). The area under the curve for all biomarkers combined, which was used to differentiate cadets in the concussion and contact-control groups, was 0.80 (95% CI, 0.68-0.93; P < .001) at the acute postinjury point. Conclusions and relevance: This study's findings indicate that blood biomarkers have potential for use as research tools to better understand the pathobiological changes associated with concussion and to assist with injury identification and recovery from combative training-associated concussions among military service academy cadets. These results extend the previous findings of studies of collegiate athletes with sport-associated concussions