Kian Merchant-Borna's research while affiliated with University of Rochester Medical Center and other places

Publications (43)

The etiologic basis for sporadic forms of neurodegenerative diseases has been elusive but likely represents the product of genetic predisposition and various environmental factors. Specific gene-environment interactions have become more salient owing, in part, to the elucidation of epigenetic mechanisms and their impact on health and disease. The linkage between traumatic brain injury (TBI) and Parkinson's disease (PD) is one such association that currently lacks a mechanistic basis. Herein, we present preliminary blood-based metabolomic evidence in support of potential association between TBI and PD. Using untargeted and targeted high-performance liquid chromatography-mass spectrometry we identified metabolomic biomarker profiles in a cohort of symptomatic mild TBI (mTBI) subjects (n = 75) 3-12 months following injury (subacute) and TBI controls (n = 20), and a PD cohort with known PD (n = 20) or PD dementia (PDD) (n = 20) and PD controls (n = 20). Surprisingly, blood glutamic acid levels in both the subacute mTBI (increased) and PD/PDD (decreased) groups were notably altered from control levels. The observed changes in blood glutamic acid levels in mTBI and PD/PDD are discussed in relation to other metabolite profiling studies. Should our preliminary results be replicated in comparable metabolomic investigations of TBI and PD cohorts, they may contribute to an "excitotoxic" linkage between TBI and PD/PDD.
MS/MS-confirmed metabolite panel fluctuations over first week following mild traumatic brain injury in the athlete cohort. Individual mean metabolite relative values (RVs) ± SEM for Athlete NC and mTBI timepoints (≤6h, 2d, 3d, 7d) are plotted for each of the MS/MS confirmed metabolites. No statistically significant changes from NC values are noted for each metabolite, despite some fluctuations. NC = non-concussed controls. SEM = standard error of the mean. MS/MS = tandem mass spectrometry. (TIF)
Past and recent attempts at devising objective biomarkers for traumatic brain injury (TBI) in both blood and cerebrospinal fluid have focused on abundance measures of time-dependent proteins. Similar independent determinants would be most welcome in diagnosing the most common form of TBI, mild TBI (mTBI), which remains difficult to define and confirm based solely on clinical criteria. There are currently no consensus diagnostic measures that objectively define individuals as having sustained an acute mTBI. Plasma metabolomic analyses have recently evolved to offer an alternative to proteomic analyses, offering an orthogonal diagnostic measure to what is currently available. The purpose of this study was to determine whether a developed set of metabolomic biomarkers is able to objectively classify college athletes sustaining mTBI from non-injured teammates, within 6 hours of trauma and whether such a biomarker panel could be effectively applied to an independent cohort of TBI and control subjects. A 6-metabolite panel was developed from biomarkers that had their identities confirmed using tandem mass spectrometry (MS/MS) in our Athlete cohort. These biomarkers were defined at ≤6 hours following mTBI and objectively classified mTBI athletes from teammate controls, and provided similar classification of these groups at the 2, 3, and 7 days post-mTBI. The same 6-metabolite panel, when applied to a separate, independent cohort provided statistically similar results despite major differences between the two cohorts. Our confirmed plasma biomarker panel objectively classifies acute mTBI cases from controls within 6 hours of injury in our two independent cohorts. While encouraged by our initial results, we expect future studies to expand on these initial observations.
Pre- and post-batch correction relative abundances for the MS/MS-confirmed biomarkers. Mean relative values (RVs) ± SEM for NC and mTBI groups in the Athlete cohort at the ≤6h timepoint (A & C) and for the External cohort TBI and NC groups (B & D) are presented for each of the MS/MS-confirmed 6 plasma biomarkers. Note the relative improvement in quantitative comparability of metabolite RVs in both cohorts following Batch Correction (A vs. B; C vs. D). The individual analyte relative value (RV) differences did not reach statistical significance between the NC and mTBI (or TBI) groups, before or following batch correction. NC = non-concussed controls. TBI = traumatic brain injury. mTBI = mild TBI. SEM = standard error of the mean. MS/MS = tandem mass spectrometry. (TIF)
Principal component analysis plots of athlete and external cohort datasets before and after batch correction adjustment. Note the dense clustering of Athlete cohort data in PC1 prior to Batch Correction (left) compared to after (right). Both Athlete and External cohorts appear more evenly distributed based on PC2, before and after adjustment. Although the Athlete and External cohort data overlap is improved with the Adjustment, the datasets continue to show differences. (TIF)
Quality Control (QC) total ion chromatogram–positive mode. Athlete cohort discovery/internal validation specimen set. Note the complete QC pool overlay, and apparent consistency across all QCs. (PDF)
Biomarker panel classification in the athlete cohort at ≤6h, 2 days, 3 days, and 7 days after mTBI. Gray shaded areas depict comparison Athlete cohort mTBI and NC ≤6h timepoint comparisons for testing the null hypothesis with other Athlete cohort first week timepoints (2 day, 3 day, and 7 day). Training/Discovery = uses logistic regression analysis. mTBI = mild traumatic brain injury. NC = non-concussed teammate controls. CI = confidence interval. SVM = support vector machine. LASSO = least absolute shrinkage and selection operator. Internal Validation = uses logistic regression with 10-fold cross validation analysis. Replication = uses logistic regression analysis. ROC AUC = receiver operating characteristic area under the curve. sens/spec = sensitivity/specificity. MS/MS 6 = final metabolite panel confirmed via tandem mass spectrometry (MS/MS). *No statistically significant difference in ROC AUC values when compared to shaded values in same row, per Hanley-McNeil test. Statistical significance considered if p <0.05. (DOCX)
MS/MS 6 panel classification accuracy for the TBI severity groups. Gray shaded area depicts comparison Season Athlete ≤6h internal validation values for testing the null hypothesis on External cohort Replication ROC AUC results from each of the mTBI and >mTBI groups. CI = confidence interval. MS/MS 6 = Final six metabolite panel confirmed via tandem mass spectrometry (MS/MS). ROC = receiver operating characteristic. AUC = area under the curve. sens/spec = sensitivity/specificity. Training/Discovery = uses logistic regression analysis. Internal Validation = uses logistic regression with 10-fold cross validation analysis. Replication = uses logistic regression analysis. NC = non-concussed controls. mTBI = mild traumatic brain injury. >mTBI = TBI noted to be worse than mTBI, including mTBI with abnormal MRI, moderate TBI, or severe TBI. *No statistically significant difference when compared to shaded value in same row, via Hanley-McNeil test. Statistical significance considered if p <0.05. (DOCX)
Classification comparisons of preliminary and final biomarker panels between athlete and external cohorts, without and with batch correction adjustment. Gray shaded areas depict comparison values, within the same row, for testing the null hypothesis via Hanley-McNeil test between the Athlete and External cohort ROC AUC results. ROC AUC = receiver operating characteristic area under the curve. SVM = support vector machine. LASSO = least absolute shrinkage and selection operator. sens/spec = sensitivity/specificity. Training/Discovery = uses logistic regression analysis. Internal Validation = uses logistic regression with 10-fold cross validation analysis. Replication = uses logistic regression analysis. z = Hanley-McNeil statistic. p = 2-tailed level of significance. MS/MS = Resulting 6 metabolites confirmed via tandem mass spectrometry (MS/MS). Statistical significance considered if p <0.05. (DOCX)
Quality Control (QC) total ion chromatogram–negative mode. Athlete cohort discovery/internal validation specimen set. Note the complete QC pool overlay, and apparent consistency across all QCs. (PDF)
Athlete cohort—prior history of traumatic brain injury. mTBI = mild traumatic brain injury. NC = non-concussed teammate control. (DOCX)
The specific fragmentation spectra for each of the six MS/MS-confirmed metabolites. These six fragmentation spectra obtained from discovery specimens were matched with those known standards within the Human Metabolome or Lipid Maps Databases, using standard methods [38]. The six included spectra, therefore, confirmed our 6-metabolite panel that was discovered and internally validated within the Athlete cohort and replicated in the External cohort. (PDF)
Athlete cohort analysis using six feature selection-derived models. Shaded areas indicate models with best results when comparing ROC AUC values using various feature selection methods in the Athlete cohort. LR = logistic regression. CI = confidence interval. ROC = receiver operating characteristic. AUC = area under the curve. sens/spec = sensitivity/specificity. SVM = support vector machine. PLS-DA = partial least squares-discriminant analysis. LASSO = least absolute shrinkage and selection operator. Targeted 1 = selected based on highest-ranking metabolites AUC values in the Tester for analytes included in Biocrates AbsoluteIDQ® p180 Kit. Targeted 2 = selected based on the highest-ranking lipid AUC values in the Tester for analytes included in Biocrates AbsoluteIDQ® p180 Kit. (DOCX)
Context: Recent changes to postconcussion guidelines indicate that postural-stability assessment may augment traditional neurocognitive testing when making return-to-participation decisions. The Balance Error Scoring System (BESS) has been proposed as 1 measure of balance assessment. A new, freely available software program to accompany the Nintendo Wii Balance Board (WBB) system has recently been developed but has not been tested in concussed patients. Objective: To evaluate the feasibility of using the WBB to assess postural stability across 3 time points (baseline and postconcussion days 3 and 7) and to assess concurrent and convergent validity of the WBB with other traditional measures (BESS and Immediate Post-Concussion Assessment and Cognitive Test [ImPACT] battery) of assessing concussion recovery. Design: Cohort study. Setting: Athletic training room and collegiate sports arena. Patients or other participants: We collected preseason baseline data from 403 National Collegiate Athletic Association Division I and III student-athletes participating in contact sports and studied 19 participants (age = 19.2 ± 1.2 years, height = 177.7 ± 8.0 cm, mass = 75.3 ± 16.6 kg, time from baseline to day 3 postconcussion = 27.1 ± 36.6 weeks) who sustained concussions. Main outcome measure(s): We assessed balance using single-legged and double-legged stances for both the BESS and WBB, focusing on the double-legged, eyes-closed stance for the WBB, and used ImPACT to assess neurocognition at 3 time points. Descriptive statistics were used to characterize the sample. Mean differences and Spearman rank correlation coefficients were used to determine differences within and between metrics over the 3 time points. Individual-level changes over time were also assessed graphically. Results: The WBB demonstrated mean changes between baseline and day 3 postconcussion and between days 3 and 7 postconcussion. It was correlated with the BESS and ImPACT for several measures and identified 2 cases of abnormal balance postconcussion that would not have been identified via the BESS. Conclusions: When accompanied by the appropriate analytic software, the WBB may be an alternative for assessing postural stability in concussed student-athletes and may provide additional information to that obtained via the BESS and ImPACT. However, verification among independent samples is required.
The aim of this study was to evaluate longitudinal changes in the diffusion characteristics of brain white matter (WM) in collegiate athletes at three time points: prior to the start of the football season (T1), after one season of football (T2), followed by six months of no-contact rest (T3). Fifteen male collegiate football players and 5 male non-athlete student controls underwent diffusion MR imaging and computerized cognitive testing at all three timepoints. Whole-brain tract-based spatial statistics (TBSS) were used to compare fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AD), and trace between all timepoints. Average diffusion values were obtained from statistically significant clusters for each individual. No athlete suffered a concussion during the study period. After one season of play (T1 to T2), we observed a significant increase in trace in a cluster located in the brainstem and left temporal lobe, and a significant increase in FA in the left parietal lobe. After six months of no-contact rest (T2 to T3), there was a significant decrease in trace and FA in clusters that were partially overlapping or in close proximity with the initial clusters (T1 to T2), with no significant changes from T1 to T3. Repetitive head impacts (RHI) sustained during a single football season may result in alterations of the brain’s WM in collegiate football players. These changes appear to return to baseline after 6 months of no-contact rest, suggesting remission of WM alterations. Our preliminary results suggest that collegiate football players might benefit from periods without exposure to RHI.
Objective: To determine whether tau changes after sport-related concussion (SRC) relate to return to play (RTP). Methods: Collegiate athletes underwent preseason plasma sampling and cognitive testing and were followed. After a SRC (n = 46), athletes and controls (n = 37) had sampling at 6 hours, and at 24 hours, 72 hours, and 7 days after SRC. A sample of 21 nonathlete controls were compared at baseline. SRC athletes were grouped by long (>10 days, n = 23) and short (≤10 days, n = 18) RTP. Total tau was measured using an ultrasensitive immunoassay. Results: Both SRC and athlete controls had significantly higher mean tau at baseline compared to nonathlete healthy controls (F101,3 = 19.644, p < 0.01). Compared to SRC athletes with short RTP, those with long RTP had higher tau concentrations overall, after controlling for sex (F39,1 = 3.59, p = 0.022), compared to long RTP athletes, at 6 (p < 0.01), 24 (p < 0.01), and 72 hours (p = 0.02). Receiver operator characteristic analyses showed that higher plasma tau 6 hours post-SRC was a significant predictor of RTP >10 days (area under the curve 0.81; 95% confidence interval 0.62-0.97, p = 0.01). Conclusions: Elevated plasma tau concentration within 6 hours following a SRC was related to having a prolonged RTP, suggesting that tau levels may help inform RTP.
One football season of sub-concussive head blows has been shown to be associated with subclinical white matter (WM) changes on diffusion tensor imaging (DTI). Prior research analyses of helmet-based impact metrics using mean and peak linear and rotational acceleration showed relatively weak correlations to these WM changes; however, these analyses failed to account for the emerging concept that neuronal vulnerability to successive hits is inversely related to the time between hits (TBH). To develop a novel method for quantifying the cumulative effects of sub-concussive head blows during a single season of collegiate football by weighting helmet-based impact measures for time between helmet impacts. We further aim to compare correlations to changes in DTI after one season of collegiate football using weighted cumulative helmet-based impact measures to correlations using non-weighted cumulative helmet-based impact measures and non-cumulative measures. We performed a secondary analysis of DTI and helmet impact data collected on ten Division III collegiate football players during the 2011 season. All subjects underwent diffusion MR imaging before the start of the football season and within 1 week of the end of the football season. Helmet impacts were recorded at each practice and game using helmet-mounted accelerometers, which computed five helmet-based impact measures for each hit: linear acceleration (LA), rotational acceleration (RA), Gadd Severity Index (GSI), Head Injury Criterion (HIC15), and Head Impact Technology severity profile (HITsp). All helmet-based impact measures were analyzed using five methods of summary: peak and mean (non-cumulative measures), season sum-totals (cumulative unweighted measures), and season sum-totals weighted for time between hits (TBH), the interval of time from hit to post-season DTI assessment (TUA), and both TBH and TUA combined. Summarized helmet-based impact measures were correlated to statistically significant changes in fractional anisotropy (FA) using bivariate and multivariable correlation analyses. The resulting R 2 values were averaged in each of the five summary method groups and compared using one-way ANOVA followed by Tukey post hoc tests for multiple comparisons. Total head hits for the season ranged from 431 to 1850. None of the athletes suffered a clinically evident concussion during the study period. The mean R 2 value for the correlations using cumulative helmet-based impact measures weighted for both TUA and TBH combined (0.51 ± 0.03) was significantly greater than the mean R 2 value for correlations using non-cumulative HIMs (vs. 0.19 ± 0.04, p < 0.0001), unweighted cumulative helmet-based impact measures (vs. 0.27 + 0.03, p < 0.0001), and cumulative helmet-based impact measures weighted for TBH alone (vs. 0.34 ± 0.02, p < 0.001). R 2 values for weighted cumulative helmet-based impact measures ranged from 0.32 to 0.77, with 60% of correlations being statistically significant. Cumulative GSI weighted for TBH and TUA explained 77% of the variance in the percent of white matter voxels with statistically significant (PWMVSS) increase in FA from pre-season to post-season, while both cumulative GSI and cumulative HIC15 weighted for TUA accounted for 75% of the variance in PWMVSS decrease in FA. A novel method for weighting cumulative helmet-based impact measures summed over the course of a football season resulted in a marked improvement in the correlation to brain WM changes observed after a single football season of sub-concussive head blows. Our results lend support to the emerging concept that sub-concussive head blows can result in sub-clinical brain injury, and this may be influenced by the time between hits. If confirmed in an independent data set, our novel method for quantifying the cumulative effects of sub-concussive head blows could be used to develop threshold-based countermeasures to prevent the accumulation of WM changes with multiple seasons of play.
We conducted a prospective study to identify genome-wide changes in peripheral gene expression before and after sports-related concussion (SRC). A total of 253 collegiate contact athletes underwent collection of peripheral blood mononuclear cells (PBMCs) before the sport season (baseline). Sixteen athletes who subsequently developed an SRC, along with 16 non-concussed teammate controls, underwent repeat collection of PBMCs within 6 h of injury (acutely). Concussed athletes underwent additional sample collection at 7 days post-injury (sub-acutely). Messenger RNA (mRNA) expression at baseline was compared with mRNA expression acutely and sub-acutely post-SRC. To estimate the contribution of physical exertion to gene changes, baseline samples from athletes who subsequently developed an SRC were compared with samples from uninjured teammate controls collected at the acute time-point. Clinical outcome was determined by changes in post-concussive symptoms, postural stability, and cognition from baseline to the sub-acute time-point. SRC athletes had significant changes in mRNA expression at both the acute and sub-acute time-points. There were no significant expression changes among controls. Acute transcriptional changes centered on interleukins 6 and 12, toll-like receptor 4, and NF-κB. Sub-acute gene expression changes centered on NF-κB, follicle stimulating hormone, chorionic gonadotropin, and protein kinase catalytic subunit. All SRC athletes were clinically back to baseline by Day 7. In conclusion, acute post-SRC transcriptional changes reflect regulation of the innate immune response and the transition to adaptive immunity. By 7 days, transcriptional activity is centered on regulating the hypothalamic-pituitary-adrenal axis. Future efforts to compare expressional changes in fully recovered athletes with those who do not recover from SRC could suggest putative targets for therapeutic intervention.
Objective: To determine changes in global gene expression in peripheral leukocytes in the acute and subacute periods following a sports-related concussion in athletes. Setting: Samples were collected at 2 universities in Rochester, New York. Participants: Fifteen contact sport athletes who experienced a sports-related concussion, and 16 nonconcussed teammates served as controls. Design: Blood samples were collected at the start of the season (baseline), within 6 hours of injury (acute), and at 7 days (subacute) postinjury. Differential gene expression was measured using the GeneChip 3' in vitro transcription Expression kit and Affymetrix microarrays, and genes with fold difference of 2 or more were identified using Partek. Main measures: Whole genome differential gene expression, and cognitive and balance measures to asses for clinical symptoms pre- and postinjury. Results: In the concussed athletes, we observed 67 downregulated and 4 upregulated genes in the acute period and 63 downregulated and 2 upregulated genes in the subacute period compared with baseline. Of these, there were 28 genes from both time points involved in the inflammatory response. No significant differences in gene expression were detected in the control group. Conclusions: Our findings suggest that recovery from sports-related concussion relates to modulation of inflammation through cytokine and chemokine gene pathways, which can contribute to future development of personalized therapeutic agents.
This study investigated the biomarkers that fluctuate due to an SRC by collecting samples before the season (baseline) and then 6 hours (acute) and 7 days (sub-acute) after an SRC.
To the Editor That the Quanterix platform was able to detect elevated levels of tau at subfentamole concentrations after sports-related concussion is indeed an exciting development in the article by Shahim and colleagues.1 However, the conclusion made by Shahim et al,1 and by the accompanying editorial,2 that S-100 calcium-binding protein B (S-100B) and neuron-specific enolase (NSE) lack use as diagnostic markers is flawed for several reasons.
The impact of sub-concussive head hits (sub-CHIs) has been recently investigated in American football players, a population at risk for varying degrees of post-traumatic sequelae. Results show how sub-CHIs in athletes translate in serum as the appearance of reporters of blood-brain barrier disruption (BBBD), how the number and severity of sub-CHIs correlate with elevations of putative markers of brain injury is unknown. Serum brain injury markers such as UCH-L1 depend on BBBD. We investigated the effects of sub-CHIs in collegiate football players on markers of BBBD, markers of cerebrospinal fluid leakage (serum beta 2-transferrin) and markers of brain damage. Emergency room patients admitted for a clinically-diagnosed mild traumatic brain injury (mTBI) were used as positive controls. Healthy volunteers were used as negative controls. Specifically this study was designed to determine the use of UCH-L1 as an aid in the diagnosis of sub-concussive head injury in athletes. The extent and intensity of head impacts and serum values of S100B, UCH-L1, and beta-2 transferrin were measured pre- and post-game from 15 college football players who did not experience a concussion after a game. S100B was elevated in players experiencing the most sub-CHIs; UCH-L1 levels were also elevated but did not correlate with S100B or sub-CHIs. Beta-2 transferrin levels remained unchanged. No correlation between UCH-L1 levels and mTBI were measured in patients. Low levels of S100B were able to rule out mTBI and high S100B levels correlated with TBI severity. UCH-L1 did not display any interpretable change in football players or in individuals with mild TBI. The significance of UCH-L1 changes in sub-concussions or mTBI needs to be further elucidated.
Repetitive head impacts (RHI) sustained in contact sports are thought to be necessary for the long-term development of chronic traumatic encephalopathy (CTE). Our objectives were to: 1) characterize the magnitude and persistence of RHI-induced white matter (WM) changes; 2) determine their relationship to kinematic measures of RHI; and 3) explore their clinical relevance. Prospective, observational study of 10 Division III college football players and 5 non-athlete controls during the 2011-12 season. All subjects underwent diffusion tensor imaging (DTI), physiologic, cognitive, and balance testing at pre-season (Time 1), post-season (Time 2), and after 6-months of no-contact rest (Time 3). Head impact measures were recorded using helmet-mounted accelerometers. The percentage of whole-brain WM voxels with significant changes in fractional anisotropy (FA) and mean diffusivity (MD) from Time 1 to 2, and Time 1 to 3 was determined for each subject and correlated to head impacts and clinical measures. Total head impacts for the season ranged from 431-1,850. No athlete suffered a clinically evident concussion. Compared to controls, athletes experienced greater changes in FA and MD from Time 1 to 2 as well as Time 1 to 3; most differences at Time 2 persisted to Time 3. Among athletes, the percentage of voxels with decreased FA from Time 1 to 2 was positively correlated with several helmet impact measures. The persistence of WM changes from Time 1 to 3 was also associated with changes in serum ApoA1 and S100B autoantibodies. WM changes were not consistently associated with cognition or balance. A single football season of RHIs without clinically-evident concussion resulted in WM changes that correlated with multiple helmet impact measures and persisted following 6 months of no-contact rest. This lack of WM recovery could potentially contribute to cumulative WM changes with subsequent RHI exposures.
The on-field diagnosis of sports-related concussion (SRC) is complicated by the lack of an accurate and objective marker of brain injury. To compare subject-specific changes in the astroglial protein, S100B, before and after SRC among collegiate and semi-professional contact sport athletes, and compare these changes to differences in S100B before and after non-contact exertion. Longitudinal cohort study. From 2009-2011, we performed a prospective study of athletes from Munich, Germany, and Rochester, New York, USA. Serum S100B was measured in all SRC athletes at pre-season baseline, within 3 hours of injury, and at days 2, 3 and 7 post-SRC. Among a subset of athletes, S100B was measured after non-contact exertion but before injury. All samples were collected identically and analyzed using an automated electrochemiluminescent assay to quantify serum S100B levels. Forty-six athletes (30 Munich, 16 Rochester) underwent baseline testing. Thirty underwent additional post-exertion S100B testing. Twenty-two athletes (16 Rochester, 6 Munich) sustained a SRC, and 17 had S100B testing within 3 hours post-injury. The mean 3-hour post-SRC S100B was significantly higher than pre-season baseline (0.099±0.008 µg/L vs. 0.058±0.006 µg/L, p = 0.0002). Mean post-exertion S100B was not significantly different than the preseason baseline. S100B levels at post-injury days 2, 3 and 7 were significantly lower than the 3-hour level, and not different than baseline. Both the absolute change and proportional increase in S100B 3-hour post-injury were accurate discriminators of SRC from non-contact exertion without SRC (AUC 0.772 and 0.904, respectively). A 3-hour post-concussion S100B >0.122 µg/L and a proportional S100B increase of >45.9% over baseline were both 96.7% specific for SRC. Relative and absolute increases in serum S100B can accurately distinguish SRC from sports-related exertion, and may be a useful adjunct to the diagnosis of SRC.
Behavioral experience can critically influence later behavior and brain function, but the central nervous system (CNS) consequences of most developmental neurotoxicants are examined in the absence of any such context. We previously demonstrated marked differences in neurotransmitter changes produced by developmental lead (Pb) exposure ± prenatal stress (PS) depending upon whether or not rats had been given behavioral experience (Cory-Slechta et al., 2009). The current study examined the hypothesis that the nature of the behavioral experience itself would be a critical determinant of outcome in mice that had been continually exposed to 0 or 100 ppm Pb acetate in drinking water alone or in combination with prenatal restraint stress. Half of the offspring in each of the 4 resulting groups/gender were exposed to positively-reinforced (food rewarded Fixed Interval (FI) schedule-controlled behavior) or negatively-reinforced (inescapable forced swim (FS)) behavioral experience. Brain monoamines and amino acids differed significantly in relation to behavioral experience, even in control animals, as did the trajectory of effects of Pb ± PS, particularly in frontal cortex, hippocampus (both genders), and midbrain (males). In males, Pb ± PS-related changes in neurotransmitters correlated with behavioral performance. These findings suggest that CNS consequences of developmental toxicants studied in the absence of a broader spectrum of behavioral experiences may not necessarily be predictive of human outcomes. Evaluating the role of specific behavioral experiences as a modulator of neurodevelopmental insults offers the opportunity to determine what specific behavioral experiences may ameliorate the associated impacts and can assist in establishing underlying neurobiological mechanisms.
Jet propulsion fuel-8 (JP-8) is the primary jet fuel used by the US military, collectively consuming ~2.5 billion gallons annually. Previous reports suggest that JP-8 is potentially toxic to the immune, respiratory, and nervous systems. The objectives of this study were to evaluate inhalation exposure to JP-8 constituents among active duty United States Air Force (USAF) personnel while performing job-related tasks, identify significant predictors of inhalation exposure to JP-8, and evaluate the extent to which surrogate exposure classifications were predictive of measured JP-8 exposures. Seventy-three full-time USAF personnel from three different air force bases were monitored during four consecutive workdays where personal air samples were collected and analyzed for benzene, ethylbenzene, toluene, xylenes, total hydrocarbons (THC), and naphthalene. The participants were categorized a priori into high- and low-exposure groups, based on their exposure to JP-8 during their typical workday. Additional JP-8 exposure categories included job title groups and self-reported exposure to JP-8. Linear mixed-effects models were used to evaluate predictors of personal air concentrations. The concentrations of THC in air were significantly different between a priori exposure groups (2.6 mg m(-3) in high group versus 0.5 mg m(-3) in low, P < 0.0001), with similar differences observed for other analytes in air. Naphthalene was strongly correlated with THC (r = 0.82, P < 0.0001) and both were positively correlated with the relative humidity of the work environment. Exposures to THC and naphthalene varied significantly by job categories based on USAF specialty codes and were highest among personnel working in fuel distribution/maintenance, though self-reported exposure to JP-8 was an even stronger predictor of measured exposure in models that explained 72% (THC) and 67% (naphthalene) of between-worker variability. In fact, both self-report JP-8 exposure and a priori exposure groups explained more between-worker variability than job categories. Personal exposure to JP-8 varied by job and was positively associated with the relative humidity. However, self-reported exposure to JP-8 was an even stronger predictor of measured exposure than job title categories, suggesting that self-reported JP-8 exposure is a valid surrogate metric of exposure when personal air measurements are not available.
Urban community gardens worldwide provide significant health benefits to those gardening and consuming fresh produce from them. Urban gardens are most often placed in locations and on land in which soil contaminants reflect past practices and often contain elevated levels of metals and organic contaminants. Garden plot dividers made from either railroad ties or chromated copper arsenate (CCA) pressure treated lumber contribute to the soil contamination and provide a continuous source of contaminants. Elevated levels of polycyclic aromatic hydrocarbons (PAHs) derived from railroad ties and arsenic from CCA pressure treated lumber are present in the gardens studied. Using a representative garden, we 1) determined the nature and extent of urban community garden soil contaminated with PAHs and arsenic by garden timbers; 2) designed a remediation plan, based on our sampling results, with our community partner guided by public health criteria, local regulation, affordability, and replicability; 3) determined the safety and advisability of adding city compost to Boston community gardens as a soil amendment; and 4) made recommendations for community gardeners regarding healthful gardening practices. This is the first study of its kind that looks at contaminants other than lead in urban garden soil and that evaluates the effect on select soil contaminants of adding city compost to community garden soil.

Citations (250)

... [3][4][5][6][7][8][9][10][11][12] Beginning in the 21st century, S100B has been under investigation as a serum biomarker of mild traumatic brain injury in sport, specifically as an indicator of sport-related concussion and subconcussion injury. [13][14][15][16][17][18][19][20][21][22][23][24][25] Although serum S100B concentration ( [S100B]) has been shown to increase in response to the number of contacts an athlete experi- ences, [16][17][18]21,25 [S100B] has also been shown to rise in rela- tion to exercise alone. 16 jogging 10 km, 16 running for 40 minutes at ventilatory threshold, 28 sprinting for 2 minutes, 16 and a 7600 m swim- ming race, 26 paired with the presence of S100B in extracra- nial tissue, [29][30][31] have cast doubt over the use of S100B as a valid biomarker of brain injury in sport. ...
... As previously mentioned, PD is a multifactorial disease with compelling epidemiological data that suggest a probable link between traumatic brain injury (TBI) and PD; however, such association is still controversial due to the lack of mechanistic basis [60]. Based on untar- geted and targeted LC-MS approaches, a statistically sig- nificant alteration of glutamate level was identified in blood samples from both TBI and PD, implying a pos- sible "excitotoxic" link between TBI and PD [61]. Add- itionally, the overlap of clinical symptoms between PD and other neurodegenerative diseases, such as primary progressive multiple sclerosis (PPMS), progressive supra- nuclear palsy (PAP) and MSA often lead to high rates of misdiagnosis for PD [3]. ...
... [3][4][5][6][7][8][9][10][11][12] Beginning in the 21st century, S100B has been under investigation as a serum biomarker of mild traumatic brain injury in sport, specifically as an indicator of sport-related concussion and subconcussion injury. [13][14][15][16][17][18][19][20][21][22][23][24][25] Although serum S100B concentration ( [S100B]) has been shown to increase in response to the number of contacts an athlete experi- ences, [16][17][18]21,25 [S100B] has also been shown to rise in rela- tion to exercise alone. 16 jogging 10 km, 16 running for 40 minutes at ventilatory threshold, 28 sprinting for 2 minutes, 16 and a 7600 m swim- ming race, 26 paired with the presence of S100B in extracra- nial tissue, [29][30][31] have cast doubt over the use of S100B as a valid biomarker of brain injury in sport. ...
... Although the variability observed in the PAH concentrations in the present study (range ¼ 1.2– 34.9 mg/kg) is consistent with the variability reported for urban soils in the northeastern United States [27], we wondered whether the observed differences in PAH concentrations in gardens may be related to the presence of in situ factors, specifically soil amendments and visible sources of PAHs. Gardens are subject to numerous management practices that may alter PAH concentrations [45]. One of the most common gardening practices is the addition of soil amendments, which can modify the soil structure, texture, and sorption capacity for deposited PAHs and affect PAH degradation and bioavailabil- ity [46]. ...
... Findings from the Rochester studies to date indicate that combined exposures to metals and stressors that share biological substrates (here, the HPA axis and brain MESO circuitry) and that produce common adverse effects (e.g., cognitive deficits) can produce enhanced toxicity, or unmask effects of chemical exposures, providing support for the hypothesis of biological interactions consistent with cumulative risk (Figure 1). The enhanced toxicity related to chronic stress is not specific to Pb exposures [47][48][49]51,[53][54][55][56][57][58][59], but has been shown for other metals (e.g., MeHg, arsenic (As)) [52,60], suggesting some generalizability. Furthermore, neurotoxicity of developmental exposures to Pb and MeHg can also be enhanced postnatally under conditions of stress to the offspring, for example by early exposure to adversity vs. early positive experience [54]. ...
... Shahim et al., 2014) Gill et al. reported that increased concentrations of tau within six hours after SRC were associated with RTP >10 days compared to those with RTP ≤10 days.( Gill et al., 2017) In their comparative study of NfL and T-tau, Shahim et al. reported that T-tau concentrations 1 hour after concussion were correlated well with recovery from concussion symptoms and RTP. However, several years later, T-tau was reported to have diagnostic and prognostic utility inferior to that of NfL at all of the times measured. ...
... Alterations in the WM microstructure have also been observed in contact-sport college athletes with repeated subconcussive blows to the head, whereas no such changes have been identified in con- trol participants ( Bazarian et al., 2014;Lao et al., 2015). ...
... This study underwent NSE screening within 24 h since the half-life of NSE in the serum is approximately 48 h ( Wunderlich et al., 1999). The NSE cut-off value is 10 ng/ml (Bazarian & Merchant-Borna, 2014). ...
... Our current findings are not consistent with longitudinal studies of diffusion kurtosis in medical center patients with mTBI, which have found decreased MK and K rad across time, including at 6 months and greater than 9 months postinjury ( Grossman et al., 2013;Stokum et al., 2015 active, are in concordance with these findings. In support of the potential effect of repetitive head impact exposure, increases in diffu- sion have been demonstrated from preseason to postseason evalua- tions in nonconcussed college athletes (Mayinger et al., 2017;McAllister et al., 2014). Furthermore, McAllister et al. (2014) to aid in interpretation and rule out preexisting WM differences in concussed athletes, head impact sensors to better characterize mech- anisms of injury, additional information collected regarding activity on the day of scanning (i.e., whether it was a rest or practice day), and measures of physical activity in the off-season, when chronic mea- surements were made. ...
... Breath, blood, urine, and microRNA tissue biomarkers have been studied and aid in confirming JP-8 exposure. Self-reported JP-8 exposure in the workplace is a reliable indicator and a stronger predictor of measured exposure than job title (27). After controlling for work shift smoking, measurements of blood volatile organic compounds (ethylbenzene, toluene, xylene) are higher among US Air Force personnel self-reporting JP-8 exposure in asso- ciation with elevated hydrocarbons in the breathing zone (28). ...