186 research outputs found

    Environmental toxins and breast cancer on Long Island. I. Polycyclic aromatic hydrocarbon DNA adducts

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    Polycyclic aromatic hydrocarbons (PAH) are potent mammary carcinogens in rodents, but their effect on breast cancer development in women is not clear. To examine whether currently measurable PAH damage to DNA increases breast cancer risk, a population-based case-control study was undertaken on Long Island, NY. Cases were women newly diagnosed with in situ and invasive breast cancer; controls were randomly selected women frequency matched to the age distribution of cases. Blood samples were donated by 1102 (73.0%) and 1141 (73.3%) of case and control respondents, respectively. Samples from 576 cases and 427 controls were assayed for PAH-DNA adducts using an ELISA. The geometric mean (and geometric SD) of the log-transformed levels of PAH-DNA adducts on a natural scale was slightly, but nonsignificantly, higher among cases [7.36 (7.29)] than among controls [6.21 (4.17); p = 0.51]. The age-adjusted odds ratio (OR) for breast cancer in relation to the highest quintile of adduct levels compared with the lowest was 1.51 [95% confidence interval (CI), 1.04 –2.20], with little or no evidence of substantial confounding (corresponding multivariate-adjusted OR, 1.49; 95% CI, 1.00 –2.21). There was no consistent elevation in risk with increasing adduct levels, nor was there a consistent association between adduct levels and two of the main sources of PAH, active or passive cigarette smoking or consumption of grilled and smoked foods. These data indicate that PAH-DNA adduct formation may influence breast cancer development, although the association does not appear to be dose dependent and may have a threshold effect

    Modifiable risk factors predicting major depressive disorder at four year follow-up: a decision tree approach

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    <p>Abstract</p> <p>Background</p> <p>Relative to physical health conditions such as cardiovascular disease, little is known about risk factors that predict the prevalence of depression. The present study investigates the expected effects of a reduction of these risks over time, using the decision tree method favoured in assessing cardiovascular disease risk.</p> <p>Methods</p> <p>The PATH through Life cohort was used for the study, comprising 2,105 20-24 year olds, 2,323 40-44 year olds and 2,177 60-64 year olds sampled from the community in the Canberra region, Australia. A decision tree methodology was used to predict the presence of major depressive disorder after four years of follow-up. The decision tree was compared with a logistic regression analysis using ROC curves.</p> <p>Results</p> <p>The decision tree was found to distinguish and delineate a wide range of risk profiles. Previous depressive symptoms were most highly predictive of depression after four years, however, modifiable risk factors such as substance use and employment status played significant roles in assessing the risk of depression. The decision tree was found to have better sensitivity and specificity than a logistic regression using identical predictors.</p> <p>Conclusion</p> <p>The decision tree method was useful in assessing the risk of major depressive disorder over four years. Application of the model to the development of a predictive tool for tailored interventions is discussed.</p

    Atoms to phenotypes: Molecular design principles of cellular energy metabolism

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    We report a 100-million atom-scale model of an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium, that reveals the cascade of energy conversion steps culminating in the generation of ATP from sunlight. Molecular dynamics simulations of this vesicle elucidate how the integral membrane complexes influence local curvature to tune photoexcitation of pigments. Brownian dynamics of small molecules within the chromatophore probe the mechanisms of directional charge transport under various pH and salinity conditions. Reproducing phenotypic properties from atomistic details, a kinetic model evinces that low-light adaptations of the bacterium emerge as a spontaneous outcome of optimizing the balance between the chromatophore’s structural integrity and robust energy conversion. Parallels are drawn with the more universal mitochondrial bioenergetic machinery, from whence molecular-scale insights into the mechanism of cellular aging are inferred. Together, our integrative method and spectroscopic experiments pave the way to first-principles modeling of whole living cells

    Bilayer-spanning DNA nanopores with voltage-switching between open and closed state.

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    Membrane-spanning nanopores from folded DNA are a recent example of biomimetic man-made nanostructures that can open up applications in biosensing, drug delivery, and nanofluidics. In this report, we generate a DNA nanopore based on the archetypal six-helix-bundle architecture and systematically characterize it via single-channel current recordings to address several fundamental scientific questions in this emerging field. We establish that the DNA pores exhibit two voltage-dependent conductance states. Low transmembrane voltages favor a stable high-conductance level, which corresponds to an unobstructed DNA pore. The expected inner width of the open channel is confirmed by measuring the conductance change as a function of poly(ethylene glycol) (PEG) size, whereby smaller PEGs are assumed to enter the pore. PEG sizing also clarifies that the main ion-conducting path runs through the membrane-spanning channel lumen as opposed to any proposed gap between the outer pore wall and the lipid bilayer. At higher voltages, the channel shows a main low-conductance state probably caused by electric-field-induced changes of the DNA pore in its conformation or orientation. This voltage-dependent switching between the open and closed states is observed with planar lipid bilayers as well as bilayers mounted on glass nanopipettes. These findings settle a discrepancy between two previously published conductances. By systematically exploring a large space of parameters and answering key questions, our report supports the development of DNA nanopores for nanobiotechnology.The SH lab is supported by the Leverhulme Trust (RPG-170), UCL Chemistry, EPSRC (Institutional Sponsorship Award), the National Physical Laboratory, and Oxford Nanopore Technologies. KG acknowledges funding from the Winton Program of Physics for Sustainability, Gates Cambridge and the Oppenheimer Trust. UFK was supported by an ERC starting grant #261101.This is the final version of the article. It was first published by ACS under the ACS AuthorChoice license at http://dx.doi.org/10.1021/nn5039433 This permits copying and redistribution of the article or any adaptations for non-commercial purposes

    Ultra-rare RTEL1 gene variants associate with acute severity of COVID-19 and evolution to pulmonary fibrosis as a specific long COVID disorder

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    Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a novel coronavirus that caused an ongoing pandemic of a pathology termed Coronavirus Disease 19 (COVID-19). Several studies reported that both COVID-19 and RTEL1 variants are associated with shorter telomere length, but a direct association between the two is not generally acknowledged. Here we demonstrate that up to 8.6% of severe COVID-19 patients bear RTEL1 ultra-rare variants, and show how this subgroup can be recognized. Methods: A cohort of 2246 SARS-CoV-2-positive subjects, collected within the GEN-COVID Multicenter study, was used in this work. Whole exome sequencing analysis was performed using the NovaSeq6000 System, and machine learning methods were used for candidate gene selection of severity. A nested study, comparing severely affected patients bearing or not variants in the selected gene, was used for the characterisation of specific clinical features connected to variants in both acute and post-acute phases. Results: Our GEN-COVID cohort revealed a total of 151 patients carrying at least one RTEL1 ultra-rare variant, which was selected as a specific acute severity feature. From a clinical point of view, these patients showed higher liver function indices, as well as increased CRP and inflammatory markers, such as IL-6. Moreover, compared to control subjects, they present autoimmune disorders more frequently. Finally, their decreased diffusion lung capacity for carbon monoxide after six months of COVID-19 suggests that RTEL1 variants can contribute to the development of SARS-CoV-2-elicited lung fibrosis. Conclusion: RTEL1 ultra-rare variants can be considered as a predictive marker of COVID-19 severity, as well as a marker of pathological evolution in pulmonary fibrosis in the post-COVID phase. This notion can be used for a rapid screening in hospitalized infected people, for vaccine prioritization, and appropriate follow-up assessment for subjects at risk. Trial Registration NCT04549831 (www.clinicaltrial.org

    Il contributo di La Volpe alla teoria dinamica dell'economia

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    The paper presents the dynamic theory proposed by La Volpe in 1936. This analysis has been innovative in many ways: general equilibrium is defined as temporary, the presence and the role of expectations are introduced, the intertemporal choice of the agents is determined in such a way as to anticipate the life-cycle theory, and some important problems that emerge in the dynamic analysis are addressed. The relevance of La Volpe's book led Michio Morishima to publish its English translation
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