Relationships of Polychlorinated Biphenyls and Dichlorodiphenyldichloroethylene (p,p’-DDE) with Testosterone Levels in Adolescent Males

Background: Concern persists over endocrine-disrupting effects of persistent organic pollutants (POPs) on human growth and sexual maturation. Potential effects of toxicant exposures on testosterone levels during puberty are not well characterized. Objectives: In this study we evaluated the relationship between toxicants [polychlorinated biphenyls (PCBs), dichlorodiphenyldichloroethylene (p,p´-DDE), hexachlorobenzene (HCB), and lead] and testosterone levels among 127 Akwesasne Mohawk males 10 to \u3c 17 years of age with documented toxicant exposures. Methods: Data were collected between February 1996 and January 2000. Fasting blood specimens were collected before breakfast by trained Akwesasne Mohawk staff. Multivariable regression models were used to estimates associations between toxicants and serum testosterone, adjusted for other toxicants, Tanner stage, and potential confounders. Results: The sum of 16 PCB congeners (Σ16PCBs) that were detected in ≥ 50% of the population was significantly and negatively associated with serum testosterone levels, such that a 10% change in exposure was associated with a 5.6% decrease in testosterone (95% CI: –10.8, –0.5%). Of the 16 congeners, the more persistent ones (Σ8PerPCBs) were related to testosterone, whereas the less persistent ones, possibly reflecting more recent exposure, were not. When PCB congeners were subgrouped, the association was significant for the sum of eight more persistent PCBs (5.7% decrease; 95% CI: –11, –0.4%), and stronger than the sum of six less persistent congeners (3.1% decrease; 95% CI: –7.2, 0.9%). p,p´-DDE was positively but not significantly associated with serum testosterone (5.2% increase with a 10% increase in exposure; 95% CI: –0.5, 10.9%). Neither lead nor HCB was significantly associated with testosterone levels. Conclusions: Exposure to PCBs, particularly the more highly persistent congeners, may negatively influence testosterone levels among adolescent males. The positive relationship between p,p´-DDE and testosterone indicates that not all POPs act similarly

A clinical and EEG scoring system that predicts early cortical response (N20) to somatosensory evoked potentials and outcome after cardiac arrest

<p>Abstract</p> <p>Background</p> <p>Anoxic coma following cardiac arrest is a common problem with ethical, social, and legal consequences. Except for unfavorable somatosensory-evoked potentials (SSEP) results, predictors of unfavorable outcome with a 100% specificity and a high sensitivity are lacking. The aim of the current research was to construct a clinical and EEG scoring system that predicts early cortical response (N20) to somatosensory evoked potentials and 6-months outcome in comatose patients after cardiac arrest.</p> <p>Methods</p> <p>We retrospectively reviewed the records of all consecutive patients who suffered cardiac arrest outside our hospital and were subsequently admitted to our facility from November 2002 to July 2006. We scored each case based on early clinical and EEG factors associated with unfavorable SSEPs, and we assessed the ability of this score to predict SSEP results and outcome.</p> <p>Results</p> <p>Sixty-six patients qualified for inclusion in the cohort. Among them, 34 (52%) had unfavorable SSEP results. At day three, factors independently associated with unfavorable SSEPs were: absence of corneal (14 points) and pupillary (21 points) reflexes, myoclonus (25 points), extensor or absent motor response to painful stimulation (28 points), and malignant EEG (11 points). A score >40 points had a sensitivity of 85%, a specificity of 84%, and a positive predictive value (PPV) of 85% to predict unfavorable SSEP results. A score >88 points had a PPV of 100%, but a sensitivity of 18%. Overall, this score had an area under ROC curves of 0.919. In addition, at day three, a score > 69 points had a PPV of 100% with a sensitivity of 32% to predict death or vegetative state.</p> <p>Conclusion</p> <p>A scoring system based on a combination of clinical and EEG findings can predict the absence of early cortical response to SSEPs. In settings without access to SSEPs, this score may help decision-making in a subset of comatose survivors after a cardiac arrest.</p

Gene identification and protein classification in microbial metagenomic sequence data via incremental clustering

<p>Abstract</p> <p>Background</p> <p>The identification and study of proteins from metagenomic datasets can shed light on the roles and interactions of the source organisms in their communities. However, metagenomic datasets are characterized by the presence of organisms with varying GC composition, codon usage biases etc., and consequently gene identification is challenging. The vast amount of sequence data also requires faster protein family classification tools.</p> <p>Results</p> <p>We present a computational improvement to a sequence clustering approach that we developed previously to identify and classify protein coding genes in large microbial metagenomic datasets. The clustering approach can be used to identify protein coding genes in prokaryotes, viruses, and intron-less eukaryotes. The computational improvement is based on an incremental clustering method that does not require the expensive all-against-all compute that was required by the original approach, while still preserving the remote homology detection capabilities. We present evaluations of the clustering approach in protein-coding gene identification and classification, and also present the results of updating the protein clusters from our previous work with recent genomic and metagenomic sequences. The clustering results are available via CAMERA, (http://camera.calit2.net).</p> <p>Conclusion</p> <p>The clustering paradigm is shown to be a very useful tool in the analysis of microbial metagenomic data. The incremental clustering method is shown to be much faster than the original approach in identifying genes, grouping sequences into existing protein families, and also identifying novel families that have multiple members in a metagenomic dataset. These clusters provide a basis for further studies of protein families.</p

Probable neuroimmunological link between Toxoplasma and cytomegalovirus infections and personality changes in the human host

BACKGROUND: Recently, a negative association between Toxoplasma-infection and novelty seeking was reported. The authors suggested that changes of personality trait were caused by manipulation activity of the parasite, aimed at increasing the probability of transmission of the parasite from an intermediate to a definitive host. They also suggested that low novelty seeking indicated an increased level of the neurotransmitter dopamine in the brain of infected subjects, a phenomenon already observed in experimentally infected rodents. However, the changes in personality can also be just a byproduct of any neurotropic infection. Moreover, the association between a personality trait and the toxoplasmosis can even be caused by an independent correlation of both the probability of Toxoplasma-infection and the personality trait with the third factor, namely with the size of living place of a subject. To test these two alternative hypotheses, we studied the influence of another neurotropic pathogen, the cytomegalovirus, on the personality of infected subjects, and reanalyzed the original data after the effect of the potential confounder, the size of living place, was controlled. METHODS: In the case-control study, 533 conscripts were tested for toxoplasmosis and presence of anti-cytomegalovirus antibodies and their novelty seeking was examined with Cloninger's TCI questionnaire. Possible association between the two infections and TCI dimensions was analyzed. RESULTS: The decrease of novelty seeking is associated also with cytomegalovirus infection. After the size of living place was controlled, the effect of toxoplasmosis on novelty seeking increased. Significant difference in novelty seeking was observed only in the largest city, Prague. CONCLUSION: Toxoplasma and cytomegalovirus probably induce a decrease of novelty seeking. As the cytomegalovirus spreads in population by direct contact (not by predation as with Toxoplasma), the observed changes are the byproduct of brain infections rather than the result of manipulation activity of a parasite. Four independent lines of indirect evidence, namely direct measurement of neurotransmitter concentration in mice, the nature of behavioral changes in rodents, the nature of personality changes in humans, and the observed association between schizophrenia and toxoplasmosis, suggest that the changes of dopamine concentration in brain could play a role in behavioral changes of infected hosts

Impacts of climate change on plant diseases – opinions and trends

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods

Ten considerations for effectively managing the COVID-19 transition

Governments around the world have implemented measures to manage the transmission of coronavirus disease 2019 (COVID-19). While the majority of these measures are proving effective, they have a high social and economic cost, and response strategies are being adjusted. The World Health Organization (WHO) recommends that communities should have a voice, be informed and engaged, and participate in this transition phase. We propose ten considerations to support this principle: (1) implement a phased approach to a 'new normal'; (2) balance individual rights with the social good; (3) prioritise people at highest risk of negative consequences; (4) provide special support for healthcare workers and care staff; (5) build, strengthen and maintain trust; (6) enlist existing social norms and foster healthy new norms; (7) increase resilience and self-efficacy; (8) use clear and positive language; (9) anticipate and manage misinformation; and (10) engage with media outlets. The transition phase should also be informed by real-time data according to which governmental responses should be updated

Complex Feeding Tracks of the Sessile Herbivorous Insect Ophiomyia maura as a Function of the Defense against Insect Parasitoids

Because insect herbivores generally suffer from high mortality due to their natural enemies, reducing the risk of being located by natural enemies is of critical importance for them, forcing them to develop a variety of defensive measures. Larvae of leaf-mining insects lead a sedentary life inside a leaf and make conspicuous feeding tracks called mines, exposing themselves to the potential risk of parasitism. We investigated the defense strategy of the linear leafminer Ophiomyia maura Meigen (Diptera: Agromyzidae), by focusing on its mining patterns. We examined whether the leafminer could reduce the risk of being parasitized (1) by making cross structures in the inner area of a leaf to deter parasitoids from tracking the mines due to complex pathways, and (2) by mining along the edge of a leaf to hinder visually searching parasitoids from finding mined leaves due to effective background matching of the mined leaves among intact leaves. We quantified fractal dimension as mine complexity and area of mine in the inner area of the leaf as interior mine density for each sample mine, and analyzed whether these mine traits affected the susceptibility of O. maura to parasitism. Our results have shown that an increase in mine complexity with the development of occupying larvae decreases the probability of being parasitized, while interior mine density has no influence on parasitism. These results suggest that the larval development increases the host defense ability through increasing mine complexity. Thus the feeding pattern of these sessile insects has a defensive function by reducing the risk of parasitism

Reliable identification of protein-protein interactions by crosslinking mass spectrometry

Protein-protein interactions govern most cellular pathways and processes, and multiple technologies have emerged to systematically map them. Assessing the error of interaction networks has been a challenge. Crosslinking mass spectrometry is currently widening its scope from structural analyses of purified multi-protein complexes towards systems-wide analyses of protein-protein interactions (PPIs). Using a carefully controlled large-scale analysis of Escherichia coli cell lysate, we demonstrate that false-discovery rates (FDR) for PPIs identified by crosslinking mass spectrometry can be reliably estimated. We present an interaction network comprising 590 PPIs at 1% decoy-based PPI-FDR. The structural information included in this network localises the binding site of the hitherto uncharacterised protein YacL to near the DNA exit tunnel on the RNA polymerase.TU Berlin, Open-Access-Mittel – 2021DFG, 390540038, EXC 2008: Unifying Systems in Catalysis "UniSysCat"DFG, 392923329, GRK 2473: Bioaktive Peptide - Innovative Aspekte zur Synthese und BiosyntheseDFG, 426290502, Erfassung der strukturellen Organisation des Mycoplasma pneumoniae Proteoms mittels in-Zell Crosslinking-Massenspektrometri

Nitration of the Pollen Allergen Bet v 1.0101 Enhances the Presentation of Bet v 1-Derived Peptides by HLA-DR on Human Dendritic Cells

Nitration of pollen derived allergens can occur by NO2 and ozone in polluted air and it has already been shown that nitrated major birch (Betula verrucosa) pollen allergen Bet v 1.0101 (Bet v 1) exhibits an increased potency to trigger an immune response. However, the mechanisms by which nitration might contribute to the induction of allergy are still unknown. In this study, we assessed the effect of chemically induced nitration of Bet v 1 on the generation of HLA-DR associated peptides. Human dendritic cells were loaded with unmodified Bet v 1 or nitrated Bet v 1, and the naturally processed HLA-DR associated peptides were subsequently identified by liquid chromatography-mass spectrometry. Nitration of Bet v 1 resulted in enhanced presentation of allergen-derived HLA-DR-associated peptides. Both the copy number of Bet v 1 derived peptides as well as the number of nested clusters was increased. Our study shows that nitration of Bet v 1 alters antigen processing and presentation via HLA-DR, by enhancing both the quality and the quantity of the Bet v 1-specific peptide repertoire. These findings indicate that air pollution can contribute to allergic diseases and might also shed light on the analogous events concerning the nitration of self-proteins

Automatic prediction of catalytic residues by modeling residue structural neighborhood

Background: Prediction of catalytic residues is a major step in characterizing the function of enzymes. In its simpler formulation, the problem can be cast into a binary classification task at the residue level, by predicting whether the residue is directly involved in the catalytic process. The task is quite hard also when structural information is available, due to the rather wide range of roles a functional residue can play and to the large imbalance between the number of catalytic and non-catalytic residues.Results: We developed an effective representation of structural information by modeling spherical regions around candidate residues, and extracting statistics on the properties of their content such as physico-chemical properties, atomic density, flexibility, presence of water molecules. We trained an SVM classifier combining our features with sequence-based information and previously developed 3D features, and compared its performance with the most recent state-of-the-art approaches on different benchmark datasets. We further analyzed the discriminant power of the information provided by the presence of heterogens in the residue neighborhood.Conclusions: Our structure-based method achieves consistent improvements on all tested datasets over both sequence-based and structure-based state-of-the-art approaches. Structural neighborhood information is shown to be responsible for such results, and predicting the presence of nearby heterogens seems to be a promising direction for further improvements.Journal ArticleResearch Support, N.I.H. Extramuralinfo:eu-repo/semantics/publishe