Real-world Time to Positivity of 2 Widely Used Commercial Blood Culture Systems in Patients With Severe Manifestations of Sepsis: An Analysis of the FABLED Study
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SUBMITTER: Butler-Laporte G
PROVIDER: S-EPMC7518368 | biostudies-literature | 2020 Aug
REPOSITORIES: biostudies-literature
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Project description:Systems Toxicology aims to change the basis of how adverse biological effects of xenobiotics are characterized from empirical end points to describing modes of action as adverse outcome pathways and perturbed networks. Toward this aim, Systems Toxicology entails the integration of in vitro and in vivo toxicity data with computational modeling. This evolving approach depends critically on data reliability and relevance, which in turn depends on the quality of experimental models and bioanalysis techniques used to generate toxicological data. Systems Toxicology involves the use of large-scale data streams ("big data"), such as those derived from omics measurements that require computational means for obtaining informative results. Thus, integrative analysis of multiple molecular measurements, particularly acquired by omics strategies, is a key approach in Systems Toxicology. In recent years, there have been significant advances centered on in vitro test systems and bioanalytical strategies, yet a frontier challenge concerns linking observed network perturbations to phenotypes, which will require understanding pathways and networks that give rise to adverse responses. This summary perspective from a 2016 Systems Toxicology meeting, an international conference held in the Alps of Switzerland, describes the limitations and opportunities of selected emerging applications in this rapidly advancing field. Systems Toxicology aims to change the basis of how adverse biological effects of xenobiotics are characterized, from empirical end points to pathways of toxicity. This requires the integration of in vitro and in vivo data with computational modeling. Test systems and bioanalytical technologies have made significant advances, but ensuring data reliability and relevance is an ongoing concern. The major challenge facing the new pathway approach is determining how to link observed network perturbations to phenotypic toxicity.
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Project description:BackgroundProspective memory (PM) denotes the ability to remember to perform actions in the future. It has been argued that standard laboratory paradigms fail to capture core aspects of PM.Methodology/principal findingsWe combined functional MRI, virtual reality, eye-tracking and verbal reports to explore the dynamic allocation of neurocognitive processes during a naturalistic PM task where individuals performed errands in a realistic model of their residential town. Based on eye movement data and verbal reports, we modeled PM as an iterative loop of five sustained and transient phases: intention maintenance before target detection (TD), TD, intention maintenance after TD, action, and switching, the latter representing the activation of a new intention in mind. The fMRI analyses revealed continuous engagement of a top-down fronto-parietal network throughout the entire task, likely subserving goal maintenance in mind. In addition, a shift was observed from a perceptual (occipital) system while searching for places to go, to a mnemonic (temporo-parietal, fronto-hippocampal) system for remembering what actions to perform after TD. Updating of the top-down fronto-parietal network occurred at both TD and switching, the latter likely also being characterized by frontopolar activity.Conclusion/significanceTaken together, these findings show how brain systems complementary interact during real-world PM, and support a more complete model of PM that can be applied to naturalistic PM tasks and that we named PROspective MEmory DYnamic (PROMEDY) model because of its dynamics on both multi-phase iteration and the interactions of distinct neurocognitive networks.
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Project description:Much of our understanding of the function of histone post-translational modifications in metazoans is inferred from their genomic localization and / or extrapolated from yeast studies. For example, acetylation of histone H3 lysine 56 (H3 K56Ac) is assumed to be important for transcriptional regulation in metazoan cells based on its occurrence at promoters and its function in yeast. Here we directly assess the function of H3 K56Ac during chromatin disassembly from gene regulatory regions during transcriptional induction in human cells by using mutations that either mimic or prevent H3 K56Ac. Although there is rapid histone H3 disassembly during induction of some estrogen receptor responsive genes, depletion of the histone chaperone ASF1A/B, which is required for H3 K56 acetylation, has no effect on chromatin disassembly at these regions. During the course of this work, we found that all the commercially available antibodies to H3 K56Ac are non-specific in human cells and in Drosophila. We used H3-YFP fusions to show that the H3 K56Q mutation can promote chromatin disassembly from regulatory regions of some estrogen responsive genes in the context of transcriptional induction. However, neither the H3 K56R nor K56Q mutation significantly altered chromatin disassembly dynamics by FRAP analysis. These results indicate that unlike the situation in yeast, human cells do not use H3 K56Ac to promote chromatin disassembly from regulatory regions or from the genome in general. Furthermore, our work highlights the need for rigorous characterization of the specificity of antibodies to histone post-translational modifications in vivo.
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Project description:BACKGROUND:Existence of bacterial host-cell DNA contamination in biopharmaceutical products is a potential risk factor for patients receiving these drugs. Hence, the quantity of contamination must be controlled under the regulatory standards. Although different methods such as hybridization assays have been employed to determine DNA impurities, these methods are labor intensive and rather expensive. In this study, a rapid real-time PCR test was served as a method of choice to quantify the E. coli host- cell DNA contamination in widely used recombinant streptokinase (rSK) , and alpha interferon (IFN-?) preparations. METHODS:A specific primer pair was designed to amplify a sequence inside the E. coli 16S rRNA gene. Serial dilutions of DNA extracted from E. coli host cells, along with DNA extracted from Active Pharmaceutical Ingredients of rSK, and IFN-? samples were subjected to an optimized real-time PCR assay based on SYBR Green chemistry. RESULTS:The test enabled us to detect a small quantity of genomic DNA contamination as low as 0.0002 pg in recombinant protein-based drugs. For the first time, this study showed that DNA contamination in rSK and IFN-? preparation manufactured in Pasteur Institute of Iran is much lower than the safety limit suggested by the US FDA. CONCLUSION:Real-time PCR is a reliable test for rapid detection of host-cell DNA contamination, which is a major impurity of therapeutic recombinant proteins to keep manufacturers' minds on refining drugs, and provides consumers with safer biopharmaceuticals.
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Project description:Language models have contributed to breakthroughs in interdisciplinary research, such as protein design and molecular dynamics understanding. In this study, we reveal that beyond language, representations of other entities, such as human behaviors, that are mappable to learnable sequences can be learned by language models. One compelling example is the real-world delivery route optimization problem. We here propose a novel approach based on the language model to optimize delivery routes on the basis of drivers' historical experiences. Although a broad range of optimization-based approaches have been designed to optimize delivery routes, they do not capture the implicit knowledge of complex delivery operating environments. The model we propose integrates this knowledge in the route optimization process by learning from driving behaviors in experienced drivers. A real-world delivery route that preserves drivers' implicit behavioral patterns is first analogized to a sentence in natural language. Through unsupervised learning, we then learn the vector representations of words and infer the drivers' delivery chains on the basis of the tailored chain-reaction-based algorithm. We also provide insights into the fusion of language models and operations research methods. In our approach, language models are applied to learn drivers' delivery behaviors and infer new deliveries at the delivery zone level, while the classic traveling salesman problem (TSP) model is embedded into the hybrid framework for intra-zone optimization. Numerical experiments performed on real-world data from Amazon's delivery service demonstrate that the proposed approach outperforms pure optimization, supporting the effectiveness, efficiency, and extensibility of our model. As a versatile approach, the proposed framework can easily be extended to various disciplines in which the data follow certain grammar rules. We anticipate that our work will serve as a stepping stone toward the understanding and application of language models in tackling interdisciplinary research problems.
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Project description:BackgroundThere is increasing evidence for the role of impaired intestinal permeability in obesity and associated metabolic diseases. Zonulin is an established serum marker for intestinal permeability and identical to pre-haptoglobin2. Here, we aimed to investigate the relationship between circulating zonulin and metabolic traits related to obesity.MethodsSerum zonulin was measured by using a widely used commercial ELISA kit in 376 subjects from the metabolically well-characterized cohort of Sorbs from Germany. In addition, haptoglobin genotype was determined in DNA samples from all study subjects.ResultsAs zonulin concentrations did not correlate to the haptoglobin genotypes, we investigated the specificity of the zonulin ELISA assay using antibody capture experiments, mass spectrometry, and Western blot analysis. Using serum samples that gave the highest or lowest ELISA signals, we detected several proteins that are likely to be captured by the antibody in the present kit. However, none of these proteins corresponds to pre-haptoglobin2. We used increasing concentrations of recombinant pre-haptoglobin2 and complement C3 as one of the representative captured proteins and the ELISA kit did not detect either. Western blot analysis using both the polyclonal antibodies used in this kit and monoclonal antibodies rose against zonulin showed a similar protein recognition pattern but with different intensity of detection. The protein(s) measured using the ELISA kit was (were) significantly increased in patients with diabetes and obesity and correlated strongly with markers of the lipid and glucose metabolism. Combining mass spectrometry and Western blot analysis using the polyclonal antibodies used in the ELISA kit, we identified properdin as another member of the zonulin family.ConclusionOur study suggests that the zonulin ELISA does not recognize pre-haptoglobin2, rather structural (and possibly functional) analog proteins belonging to the mannose-associated serine protease family, with properdin being the most likely possible candidate.
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Project description:Fenpropathrin is one of the widely used pyrethroids in agriculture and household and also reported to have neurotoxic effects in rodent models. In our Parkinson's disease (PD) clinic, there was a unique patient with a history of daily exposure to fenpropathrin for 6 months prior to developing Parkinsonian symptoms progressively. Since whether fenpropathrin is related to any dopaminergic degeneration was unknown, we aimed in this study to evaluate the neurotoxic effects of fenpropathrin on the dopaminergic system and associated mechanisms in vitro and in vivo. In cultured SH-SY5Y cells, fenpropathrin caused cell death, reactive oxygen species generation, Lewy body-associated proteins aggregation, and Lewy body-like intracytoplasmic inclusions formation. In rodent animals, two different injections of fenpropathrin were used for administrations, intraperitoneal (i.p), or stereotaxical (ST). The rats exhibited lower number of pokes 60 days after first i.p injection, while the rats in ST group showed a significant upregulation of apomorphine-evoked rotations 60 days after first injection. Decreased tyrosine hydroxylase (TH) and vesicular monoamine transporter 2 (VMAT2) immunoreactivity, while increased dopamine transporter (DAT) immunoreactivity were observed in rats of either i.p or ST group 60 days after the last exposure to fenpropathrin. However, the number of TH-positive cells in the substantia nigra was more reduced 120 days after the first i.p injection than those of 60 days. Our data demonstrated that exposure to fenpropathrin could mimic the pathologic and pathogenetic features of PD especially in late onset cases. These results imply fenpropathrin as a DA neurotoxin and a possible environmental risk factor for PD.
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