Disability outcomes in early-stage African American and White people with multiple sclerosis.

BACKGROUND: Factors driving differences in disease burden between African American and White people with multiple sclerosis (pwMS) remain unclear. Here, we explored whether differences in disability outcomes could be observed after controlling for major sociodemographic factors and comorbidities, and assessed the presence of a possible interaction between MS and race. METHODS: In this cross-sectional study, 120 pwMS within 6 years from disease onset and 82 healthy controls between 18 and 70 years of age, self-identified as either African American or White, were prospectively enrolled. Inclusion criteria for pwMS were: diagnosis of MS according to the revised McDonald criteria, relapsing-remitting phenotype and Expanded Disability Status Scale (EDSS) < 6.5. Study outcomes included: (i) global disability (EDSS); (ii) quantitative mobility and leg function (Timed 25 Foot Walk Test-T25FWT); (iii) quantitative finger dexterity (9-Hole Peg Test-9HPT); (iv) cognitive efficiency and speed performance (Symbol Digit Modalities Test-SDMT). Differences in disability outcomes were assessed employing multivariable linear regression models. Based on their association with MS or disability, covariates included age, gender, race, years of education, total income, body mass index, comorbidities. The interaction between MS and race on disability outcomes was estimated via relative excess risk of interaction and attributable proportion. RESULTS: Accounting for age, gender, total income, education, body mass index and comorbidities, African American pwMS showed significantly worse performances in manual dexterity and cognition than White pwMS (White pwMS coeff. 3.24, 95% CI 1.55, 4.92 vs African American pwMS coeff. 5.52, 95% CI 3.55, 7.48 and White pwMS coeff. -5.87, 95% CI -8.86, -2.87 vs African American pwMS coeff. -7.99, 95% CI -11.58,-4.38). MS and race independently contributed to the observed gradient in disability severity. CONCLUSIONS: Complex social disparities and systemic racism might contribute to clinical heterogeneity in MS.

Classification of multiple sclerosis patients based on structural disconnection: A robust feature selection approach.

BACKGROUND AND PURPOSE: Although structural disconnection represents the hallmark of multiple sclerosis (MS) pathophysiology, classification attempts based on structural connectivity have achieved low accuracy levels. Here, we set out to fill this gap, exploring the performance of supervised classifiers on features derived from microstructure informed tractography and selected applying a novel robust approach. METHODS: Using microstructure informed tractography with diffusion MRI data, we created quantitative connectomes of 55 MS patients and 24 healthy controls. We then used a robust approach-based on two classical methods of feature selection- to select relevant features from three network representations (whole connectivity matrices, node strength, and local efficiency). Classification accuracy of the selected features was tested with five different classifiers, while their meaningfulness was tested via correlation with clinical scales. As a comparison, the same classifiers were run on features selected with the standard procedure in network analysis (thresholding). RESULTS: Our procedure identified 11 features for the whole net, five for local efficiency, and seven for node strength. For all classifiers, the accuracy was in the range 64.5%-91.1%, with features extracted from the whole net reaching the maximum, and overcoming results obtained with the standard procedure in all cases. Correlations with clinical scales were identified across functional domains, from motor and cognitive abilities to fatigue and depression. CONCLUSION: Applying a robust feature selection procedure to quantitative structural connectomes, we were able to classify MS patients with excellent accuracy, while providing information on the white matter connections and gray matter regions more affected by MS pathology.

2004 National Atrazine Occurrence Monitoring Program using the Abraxis ELISA method.

The goal of this project was to gain a better understanding of atrazine occurrence in the United States by surveying drinking water utilities' sources and finished water for atrazine on a weekly basis for seven months. Atrazine is a contaminant of interest because the United States Environmental Protection Agency (USEPA) has found short-term atrazine exposure above the drinking water maximum contaminant level (MCL) to potentially cause heart, lung, and kidney congestion, low blood pressure, muscle spasms, weight loss, and damage to the adrenal glands. Long-term exposure to atrazine concentrations above the drinking water MCL has been linked to weight loss, cardiovascular damage, retinal and muscle degeneration, and cancer. This survey effort improved upon previously conducted atrazine surveys through intensive, high frequency sampling (participating plants sampled their raw and finished water on a weekly basis for approximately seven months). Such an intensive effort allowed the authors to gain a better understanding of short-term atrazine occurrence and its variability in drinking water sources. This information can benefit the drinking water industry by facilitating (1) better atrazine occurrence management (i.e., awareness when plants may be more susceptible to atrazine), (2) more efficient atrazine control (e.g., effective treatment alternatives and more effective response to atrazine occurrence), and (3) treatment cost reduction (e.g., efficient atrazine control can result in substantial cost savings). Forty-seven drinking watertreatment plants located primarily in the Midwestern United States participated in the survey and sampled their raw and finished water on a weekly basis from March through October. Samples were analyzed using the Abraxis enzyme-linked immunosorbent assay (ELISA) test kit. Confirmation samples for quality assurance/quality control (QA/QC) purposes were analyzed using solid-phase extraction (SPE) followed by gas chromatography mass spectrophotometry (GC/MS). Several important conclusions can be drawn from this study including (1) surface waters were confirmed to be more vulnerable to atrazine contamination than groundwater sources, (2) peak atrazine concentrations corresponded well to precipitation/runoff events, and (3) atrazine occurrence tended to be uniform geographically when compared by river drainage basins. In addition, this project confirmed that the Abraxis atrazine ELISA test kit tended to have a positive bias (i.e., the measured ELISA concentration was higher than the actual concentration) in most measured samples. Finished samples tended to have more of a positive bias than raw water samples. Therefore, this bias may limit the effectiveness for ELISA for regulatory monitoring. There are many other applications for ELISA, however, including frequent monitoring for early detections of atrazine concentration changes that might trigger conventional analysis by GC/MS or be used for activated carbon dosing or other treatment operating controls.