Trace metal applications in atmospheric and watershed dynamics: Case studies of mercury deposition in New England and bedrock groundwater-surface water mixing

The studies presented in this dissertation focus on the environmental chemistry of two trace metals, mercury (Hg) and strontium (Sr). Both are naturally occurring and exist in the environment at trace levels. Chapters II-IV of this dissertation focus on understanding the atmospheric chemistry of Hg and the wet and dry deposition of this toxic element. Chapter II presents results from Hg wet deposition measurements and ambient reactive gaseous Hg (RGM) measurements collected at Thompson Farm located in Durham, NH over a 3 year time period. The duration of this study allowed for seasonal and inter-annual comparisons. Seasonally, Hg wet deposition was greatest in the summer and spring and lowest in the winter and fall. Evidence of ineffective scavenging of RGM is provided due to the less frequent depletion of RGM during winter precipitation events in comparison with other seasons. RGM dry deposition estimates based on real time concentration measurements are greatest during the winter and spring. Ratios of the seasonal Hg wet deposition to RGM dry deposition vary greatly from 1.6 to 80. A comparison between Hg wet deposition at Thompson Farm and a marine site, Appledore Island, is included in Chapter III. There were no significant differences in event concentration or deposition between the two sites, however, the sample collection efficiency varied greatly between the sites and may effect the results. Additionally, major ion concentrations were measured at the Appledore Island site and compared to the Hg concentrations. The analytical results coupled with air mass back trajectories suggest that the greatest amount of Hg wet deposition occurs when polluted continental air mixes with marine air. A new filter extraction method for determining the environmentally mobile Hg concentration in bulk aerosol filters is presented in Chapter IV. This method is applied during a 2 week intensive sampling campaign at Appledore Island during summer 2009. Chapter V explores the use of Sr isotope ratios to determine groundwater inputs to the Lamprey River. The groundwater and surface waters in the watershed exhibit large differences in 87Sr/86Sr indicating this geochemical indicator could be a useful tool in hydrogeologic studies of the watershed

Increasing African genomic data generation and sharing to resolve rare and undiagnosed diseases in Africa: a call-to-action by the H3Africa rare diseases working group

The rich and diverse genomics of African populations is significantly underrepresented in reference and in disease-associated databases. This renders interpreting the Next Generation Sequencing (NGS) data and reaching a diagnostic more difficult in Africa and for the African diaspora. It increases chances for false positives with variants being misclassified as pathogenic due to their novelty or rarity. We can increase African genomic data by (1) making consent for sharing aggregate frequency data an essential component of research toolkit; (2) encouraging investigators with African data to share available data through public resources such as gnomAD, AVGD, ClinVar, DECIPHER and to use MatchMaker Exchange; (3) educating African research participants on the meaning and value of sharing aggregate frequency data; and (4) increasing funding to scale-up the production of African genomic data that will be more representative of the geographical and ethno-linguistic variation on the continent. The RDWG of H3Africa is hereby calling to action because this underrepresentation accentuates the health disparities. Applying the NGS to shorten the diagnostic odyssey or to guide therapeutic options for rare diseases will fully work for Africans only when public repositories include sufficient data from African subjects

Biochemical characterization and low-resolution SAXS shape of a novel GH11 exo-1,4-β-xylanase identified in a microbial consortium

Biotechnologies that aim to produce renewable fuels, chemicals, and bioproducts from residual ligno(hemi)cellulosic biomass mostly rely on enzymatic depolymerization of plant cell walls (PCW). This process requires an arsenal of diverse enzymes, including xylanases, which synergistically act on the hemicellulose, reducing the long and complex xylan chains to oligomers and simple sugars. Thus, xylanases play a crucial role in PCW depolymerization. Until recently, the largest xylanase family, glycoside hydrolase family 11 (GH11) has been exclusively represented by endo-catalytic β-1,4- and β-1,3-xylanases. Analysis of a metatranscriptome library from a microbial lignocellulose community resulted in the identification of an unusual exo-acting GH11 β-1,4-xylanase (MetXyn11). Detailed characterization has been performed on recombinant MetXyn11 including determination of its low-resolution small angle Xray scattering (SAXS) molecular envelope in solution. Our results reveal that MetXyn11 is a monomeric globular enzyme that liberates xylobiose from heteroxylans as the only product. MetXyn11 has an optimal activity in a pH range from 6 to 9 and an optimal temperature of 50 oC. The enzyme maintained above 65% of its original activity in the pH range 5 to 6 after being incubated for 72 h at 50 oC. Addition of the enzyme to a commercial enzymatic cocktail (CelicCtec3) promoted a significant increase of enzymatic hydrolysis yields of hydrothermally pretreated sugarcane bagasse (16% after 24 h of hydrolysis)

Mutations in the parkin gene are a minor cause of Parkinson's disease in the South African population

The molecular basis of Parkinson's disease (PD) has been extensively studied in numerous population groups over the past decade. However, very little is known of the molecular etiology of PD in the South African population. We aimed to assess the genetic contribution of parkin mutations to PD pathology by determining the frequency of both point mutations and exon rearrangements in all 12 exons of the parkin gene in a group of 229 South African patients diagnosed with PD. This was done by performing high resolution melt (HRM) as well as multiplex ligation-dependent probe amplification (MLPA) analyses. In total, seven patients (3.1%; 7/229) had either compound heterozygous or homozygous mutations in parkin, and seven patients (3.1%) had heterozygous sequence variants. Two of the patients with parkin mutations are of Black African ancestry. Reverse-transcription PCR on lymphocytes obtained from two patients verified the presence of parkin mutations on both alleles. In conclusion, the present study reveals that mutations in the parkin gene are not a major contributor to PD in the South African population. Further investigations of the molecular etiology of PD in the unique South African population, particularly the Black African and mixed ancestry sub-populations, are warranted. (C) 2011 Elsevier Ltd. All rights reserved

A pilot randomized control study to investigate the effect of the South African Adolescence Group Sleep Intervention (SAASI) on adolescent sleep and PTSD.

Background: Trauma exposure prevalence and consequent post-traumatic stress disorder among South African adolescents are significant. Sleep disturbances are among the most frequently reported difficulties faced by those dealing with PTSD. The current study examined the feasibility and preliminary efficacy of the South African Adolescence Group Sleep Intervention on PTSD symptom severity and sleep disturbance when delivered to South African adolescents with PTSD.Method: Sixty-one adolescents with PTSD diagnoses and sleep disturbance were randomly assigned (1:1) to one individual and four group sessions of a sleep intervention (SAASI) or a control group. At baseline, post- and 1-month follow-up participants completed the Child PTSD symptom scale for DSM5 (CPSS-5) and the Pittsburgh Sleep Quality Index (PSQI) among other sleep and psychiatric measures. The trial was registered on the Pan African Trial Registry (PACTR202208559723690)Results: There was a significant but similar decrease in PSQI scores in both groups over time indicating no overall intervention effect (wald test = -2.18, p=0.029), mean slope = -0.2 (95%CI: -0.37 to -0.02) (p=0.583). On the CPSS-5, interaction between groups was also not significant (p=0.291). Despite this overall finding, the mean difference in CPSS-SR-5 scores increased over time, with the difference between groups post-treatment -9.10 (95%CI: -18.00 to -0.21), p=.045 and the 1-month follow-up contrast -11.22 (95%CI: -22.43 to -0.03), p=0.049 suggesting that PTSD symptom severity decreased more in the intervention group than the control group. The dropout rate was higher than expected for both the intervention (n=10; 32%) and control (n=8; 26,7%) groups. Reasons provided for dropout were mostly school commitments or travel related.Conclusions: Early findings suggest a trend towards dual improvement in sleep quality and PTSD symptom severity in adolescents with a sleep disturbance and PTSD receiving a group sleep intervention (SAASI). Further investigation in a properly powered RCT with detailed retention planning is indicated. <br/

Machine Learning Models of Arsenic in Private Wells Throughout the Conterminous United States As a Tool for Exposure Assessment in Human Health Studies.

Arsenic from geologic sources is widespread in groundwater within the United States (U.S.). In several areas, groundwater arsenic concentrations exceed the U.S. Environmental Protection Agency maximum contaminant level of 10 μg per liter (μg/L). However, this standard applies only to public-supply drinking water and not to private-supply, which is not federally regulated and is rarely monitored. As a result, arsenic exposure from private wells is a potentially substantial, but largely hidden, public health concern. Machine learning models using boosted regression trees (BRT) and random forest classification (RFC) techniques were developed to estimate probabilities and concentration ranges of arsenic in private wells throughout the conterminous U.S. Three BRT models were fit separately to estimate the probability of private well arsenic concentrations exceeding 1, 5, or 10 μg/L whereas the RFC model estimates the most probable category (≤5, &gt;5 to ≤10, or &gt;10 μg/L). Overall, the models perform best at identifying areas with low concentrations of arsenic in private wells. The BRT 10 μg/L model estimates for testing data have an overall accuracy of 91.2%, sensitivity of 33.9%, and specificity of 98.2%. Influential variables identified across all models included average annual precipitation and soil geochemistry. Models were developed in collaboration with public health experts to support U.S.-based studies focused on health effects from arsenic exposure

High-throughput small molecule screening reveals Nrf2-dependent and -independent pathways of cellular stress resistance.

Aging is the dominant risk factor for most chronic diseases. Development of antiaging interventions offers the promise of preventing many such illnesses simultaneously. Cellular stress resistance is an evolutionarily conserved feature of longevity. Here, we identify compounds that induced resistance to the superoxide generator paraquat (PQ), the heavy metal cadmium (Cd), and the DNA alkylator methyl methanesulfonate (MMS). Some rescue compounds conferred resistance to a single stressor, while others provoked multiplex resistance. Induction of stress resistance in fibroblasts was predictive of longevity extension in a published large-scale longevity screen in Caenorhabditis elegans, although not in testing performed in worms and flies with a more restricted set of compounds. Transcriptomic analysis and genetic studies implicated Nrf2/SKN-1 signaling in stress resistance provided by two protective compounds, cardamonin and AEG 3482. Small molecules identified in this work may represent attractive tools to elucidate mechanisms of stress resistance in mammalian cells