Using Residential History and Groundwater Modeling to Examine Drinking Water Exposure and Breast Cancer

BACKGROUND. Spatial analyses of case-control data have suggested a possible link between breast cancer and groundwater plumes in upper Cape Cod, Massachusetts. OBJECTIVE. We integrated residential histories, public water distribution systems, and groundwater modeling within geographic information systems (GIS) to examine the association between exposure to drinking water that has been contaminated by wastewater effluent and breast cancer. METHODS. Exposure was assessed from 1947 to 1993 for 638 breast cancer cases who were diagnosed from 1983 to 1993 and 842 controls; we took into account residential mobility and drinking water source. To estimate the historical impact of effluent on drinking water wells, we modified a modular three-dimensional finite-difference groundwater model (MODFLOW) from the U.S. Geological Survey. The analyses included latency and exposure duration. RESULTS. Wastewater effluent impacted the drinking water wells of study participants as early as 1966. For > 0-5 years of exposure (versus no exposure), associations were generally null. Adjusted odds ratios (AORs) for > 10 years of exposure were slightly increased, assuming latency periods of 0 or 10 years [AOR = 1.3; 95% confidence interval (CI), 0.9-1.9 and AOR = 1.6; 95% CI, 0.8-3.2, respectively]. Statistically significant associations were estimated for ever-exposed versus never-exposed women when a 20-year latency period was assumed (AOR = 1.9; 95% CI, 1.0-3.4). A sensitivity analysis that classified exposures assuming lower well-pumping rates showed similar results. CONCLUSION. We investigated the hypothesis generated by earlier spatial analyses that exposure to drinking water contaminated by wastewater effluent may be associated with breast cancer. Using a detailed exposure assessment, we found an association with breast cancer that increased with longer latency and greater exposure duration.National Cancer Institute (5R03CA119703-02); National Institute of Environmental Health Sciences (5P42 ES007381

Minimizing Acquisition Maximizing Inference -- A demonstration on print error detection

Is it possible to detect a feature in an image without ever looking at it? Images are known to have sparser representation in Wavelets and other similar transforms. Compressed Sensing is a technique which proposes simultaneous acquisition and compression of any signal by taking very few random linear measurements (M). The quality of reconstruction directly relates with M, which should be above a certain threshold for a reliable recovery. Since these measurements can non-adaptively reconstruct the signal to a faithful extent using purely analytical methods like Basis Pursuit, Matching Pursuit, Iterative thresholding, etc., we can be assured that these compressed samples contain enough information about any relevant macro-level feature contained in the (image) signal. Thus if we choose to deliberately acquire an even lower number of measurements - in order to thwart the possibility of a comprehensible reconstruction, but high enough to infer whether a relevant feature exists in an image - we can achieve accurate image classification while preserving its privacy. Through the print error detection problem, it is demonstrated that such a novel system can be implemented in practise

Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)

The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between international scientific teams by disseminating ideas through both specific oral/poster presentations and free discussions. For its second edition, the iTWIST workshop took place in the medieval and picturesque town of Namur in Belgium, from Wednesday August 27th till Friday August 29th, 2014. The workshop was conveniently located in "The Arsenal" building within walking distance of both hotels and town center. iTWIST'14 has gathered about 70 international participants and has featured 9 invited talks, 10 oral presentations, and 14 posters on the following themes, all related to the theory, application and generalization of the "sparsity paradigm": Sparsity-driven data sensing and processing; Union of low dimensional subspaces; Beyond linear and convex inverse problem; Matrix/manifold/graph sensing/processing; Blind inverse problems and dictionary learning; Sparsity and computational neuroscience; Information theory, geometry and randomness; Complexity/accuracy tradeoffs in numerical methods; Sparsity? What's next?; Sparse machine learning and inference.Comment: 69 pages, 24 extended abstracts, iTWIST'14 website: http://sites.google.com/site/itwist1

Contribution of pecan (Carya illinoinensis [Wangenh.| K. Koch) to Sustainable Development Goal 2 under the dual perspective of carbon storage and human nutrition.

This work aims to contextualize and analyze the potential contribution of pecan to SDG2 under the dual perspective of carbon storage and human nutrition. Particularly, the study focuses on the pecan agroecosystems in the Americas, representing the most important pecan-producing countries (the United States, Mexico, Brazil, Argentina, Uruguay, and Peru). We observed that pecan is a reliable sink for storing atmospheric C and also for quality nuts with high nutritional density. The Americas, hold a population of ca. 23 M pecan trees, with the younger tree populations and the highest C-storing potential in South America. This pecan tree population has removed 51.3 Mt CO2eq immobilizing the OC in their aboveground biomass, but if the C sequestration for the whole system is considered, the value reaches nearly 80 Mt CO2eq. From a nutritional perspective, there are different dietary needs to cover according to the country, although the common analysis output is a low proportion of nuts in the diet, which is expected to improve, given the efforts of each country to promote domestic consumption. All the mentioned countries in this study have a low pecan consumption going from 8 to 293 g per capita yr-1, which in the light of the Global Burden of Disease represents 0.08 to 3.2% of the recommended yearly dietary basis for nuts overall. The inclusion of pecan nuts in the daily diet is of utmost importance to offset the food nutrient dilution carbohydrates-based, linked to the excess of atmospheric CO2. Also, pecan orchards function as a platform to integrate sustainable systems. The global benefit of having pecan and alley crops has been proved in regions other than the Americas with interesting economic outputs leading to energizing the life of rural communities. Pecan orchards and pecan agroforestry may lead to sustainable agri-food systems, with global gains in SOC and nutritional richness and diversity. Therefore, more in-depth studies are needed not only to fully understand the functioning of the systems at a productive level but also to design and plan sustainable landscapes in rural land.Published 14 April 2023

Abundant Degenerate Miniature Inverted-Repeat Transposable Elements in Genomes of Epichloid Fungal Endophytes of Grasses

Miniature inverted-repeat transposable elements (MITEs) are abundant repeat elements in plant and animal genomes; however, there are few analyses of these elements in fungal genomes. Analysis of the draft genome sequence of the fungal endophyte Epichloë festucae revealed 13 MITE families that make up almost 1% of the E. festucae genome, and relics of putative autonomous parent elements were identified for three families. Sequence and DNA hybridization analyses suggest that at least some of the MITEs identified in the study were active early in the evolution of Epichloë but are not found in closely related genera. Analysis of MITE integration sites showed that these elements have a moderate integration site preference for 5′ genic regions of the E. festucae genome and are particularly enriched near genes for secondary metabolism. Copies of the EFT-3m/Toru element appear to have mediated recombination events that may have abolished synthesis of two fungal alkaloids in different epichloae. This work provides insight into the potential impact of MITEs on epichloae evolution and provides a foundation for analysis in other fungal genomes

Simple sequence repeats in Neurospora crassa: distribution, polymorphism and evolutionary inference

<p>Abstract</p> <p>Background</p> <p>Simple sequence repeats (SSRs) have been successfully used for various genetic and evolutionary studies in eukaryotic systems. The eukaryotic model organism <it>Neurospora crassa </it>is an excellent system to study evolution and biological function of SSRs.</p> <p>Results</p> <p>We identified and characterized 2749 SSRs of 963 SSR types in the genome of <it>N. crassa</it>. The distribution of tri-nucleotide (nt) SSRs, the most common SSRs in <it>N. crassa</it>, was significantly biased in exons. We further characterized the distribution of 19 abundant SSR types (AST), which account for 71% of total SSRs in the <it>N. crassa </it>genome, using a Poisson log-linear model. We also characterized the size variation of SSRs among natural accessions using Polymorphic Index Content (PIC) and ANOVA analyses and found that there are genome-wide, chromosome-dependent and local-specific variations. Using polymorphic SSRs, we have built linkage maps from three line-cross populations.</p> <p>Conclusion</p> <p>Taking our computational, statistical and experimental data together, we conclude that 1) the distributions of the SSRs in the sequenced N. crassa genome differ systematically between chromosomes as well as between SSR types, 2) the size variation of tri-nt SSRs in exons might be an important mechanism in generating functional variation of proteins in <it>N. crassa</it>, 3) there are different levels of evolutionary forces in variation of amino acid repeats, and 4) SSRs are stable molecular markers for genetic studies in <it>N. crassa</it>.</p

Genesis of a Fungal Non-Self Recognition Repertoire

Conspecific allorecognition, the ability for an organism to discriminate its own cells from those of another individual of the same species, has been developed by many organisms. Allorecognition specificities are determined by highly polymorphic genes. The processes by which this extreme polymorphism is generated remain largely unknown. Fungi are able to form heterokaryons by fusion of somatic cells, and somatic non self-recognition is controlled by heterokaryon incompatibility loci (het loci). Herein, we have analyzed the evolutionary features of the het-d and het-e fungal allorecognition genes. In these het genes, allorecognition specificity is determined by a polymorphic WD-repeat domain. We found that het-d and het-e belong to a large gene family with 10 members that all share the WD-repeat domain and show that repeats of all members of the family undergo concerted evolution. It follows that repeat units are constantly exchanged both within and between members of the gene family. As a consequence, high mutation supply in the repeat domain is ensured due to the high total copy number of repeats. We then show that in each repeat four residues located at the protein/protein interaction surface of the WD-repeat domain are under positive diversifying selection. Diversification of het-d and het-e is thus ensured by high mutation supply, followed by reshuffling of the repeats and positive selection for favourable variants. We also propose that RIP, a fungal specific hypermutation process acting specifically on repeated sequences might further enhance mutation supply. The combination of these evolutionary mechanisms constitutes an original process for generating extensive polymorphism at loci that require rapid diversification

Learning to live together: mutualism between self-splicing introns and their hosts

Group I and II introns can be considered as molecular parasites that interrupt protein-coding and structural RNA genes in all domains of life. They function as self-splicing ribozymes and thereby limit the phenotypic costs associated with disruption of a host gene while they act as mobile DNA elements to promote their spread within and between genomes. Once considered purely selfish DNA elements, they now seem, in the light of recent work on the molecular mechanisms regulating bacterial and phage group I and II intron dynamics, to show evidence of co-evolution with their hosts. These previously underappreciated relationships serve the co-evolving entities particularly well in times of environmental stress

Recovery of dialysis patients with COVID-19 : health outcomes 3 months after diagnosis in ERACODA

Background. Coronavirus disease 2019 (COVID-19)-related short-term mortality is high in dialysis patients, but longer-term outcomes are largely unknown. We therefore assessed patient recovery in a large cohort of dialysis patients 3 months after their COVID-19 diagnosis. Methods. We analyzed data on dialysis patients diagnosed with COVID-19 from 1 February 2020 to 31 March 2021 from the European Renal Association COVID-19 Database (ERACODA). The outcomes studied were patient survival, residence and functional and mental health status (estimated by their treating physician) 3 months after COVID-19 diagnosis. Complete follow-up data were available for 854 surviving patients. Patient characteristics associated with recovery were analyzed using logistic regression. Results. In 2449 hemodialysis patients (mean ± SD age 67.5 ± 14.4 years, 62% male), survival probabilities at 3 months after COVID-19 diagnosis were 90% for nonhospitalized patients (n = 1087), 73% for patients admitted to the hospital but not to an intensive care unit (ICU) (n = 1165) and 40% for those admitted to an ICU (n = 197). Patient survival hardly decreased between 28 days and 3 months after COVID-19 diagnosis. At 3 months, 87% functioned at their pre-existent functional and 94% at their pre-existent mental level. Only few of the surviving patients were still admitted to the hospital (0.8-6.3%) or a nursing home (∼5%). A higher age and frailty score at presentation and ICU admission were associated with worse functional outcome. Conclusions. Mortality between 28 days and 3 months after COVID-19 diagnosis was low and the majority of patients who survived COVID-19 recovered to their pre-existent functional and mental health level at 3 months after diagnosis