Impact of prematurity and perinatal antibiotics on the developing intestinal microbiota: A functional inference study

The microbial colonization of the neonatal gut provides a critical stimulus for normal maturation and development. This process of early microbiota establishment, known to be affected by several factors, constitutes an important determinant for later health. Methods: We studied the establishment of the microbiota in preterm and full-term infants and the impact of perinatal antibiotics upon this process in premature babies. To this end, 16S rRNA gene sequence-based microbiota assessment was performed at phylum level and functional inference analyses were conducted. Moreover, the levels of the main intestinal microbial metabolites, the short-chain fatty acids (SCFA) acetate, propionate and butyrate, were measured by Gas-Chromatography Flame ionization/Mass spectrometry detection. Results: Prematurity affects microbiota composition at phylum level, leading to increases of Proteobacteria and reduction of other intestinal microorganisms. Perinatal antibiotic use further affected the microbiota of the preterm infant. These changes involved a concomitant alteration in the levels of intestinal SCFA. Moreover, functional inference analyses allowed for identifying metabolic pathways potentially affected by prematurity and perinatal antibiotics use. Conclusion: A deficiency or delay in the establishment of normal microbiota function seems to be present in preterm infants. Perinatal antibiotic use, such as intrapartum prophylaxis, affected the early life microbiota establishment in preterm newborns, which may have consequences for later healt

Impact of intrapartum antimicrobial prophylaxis upon the intestinal microbiota and the prevalence of antibiotic resistance genes in vaginally delivered full-term neonates

Background: Disturbances in the early establishment of the intestinal microbiota may produce important implications for the infant's health and for the risk of disease later on. Different perinatal conditions may be affecting the development of the gut microbiota. Some of them, such as delivery mode or feeding habits, have been extensively assessed whereas others remain to be studied, being critical to identify their impact on the microbiota and, if any, to minimize it. Antibiotics are among the drugs most frequently used in early life, the use of intrapartum antimicrobial prophylaxis (IAP), present in over 30% of deliveries, being the most frequent source of exposure. However, our knowledge on the effects of IAP on the microbiota establishment is still limited. The aim of the present work was to evaluate the impact of IAP investigating a cohort of 40 full-term vaginally delivered infants born after an uncomplicated pregnancy, 18 of which were born from mothers receiving IAP. Results: Fecal samples were collected at 2, 10, 30, and 90 days of age. We analyzed the composition of the fecal microbiota during the first 3 months of life by 16S rRNA gene sequencing and quantified fecal short chain fatty acids by gas chromatography. The presence of genes for resistance to antibiotics was determined by PCR in the samples from 1-month-old infants. Our results showed an altered pattern of intestinal microbiota establishment in IAP infants during the first weeks of life, with lower relative proportions of Actinobacteria and Bacteroidetes and increased of Preoteobacteria and Firmicutes. A delay in the increase on the levels of acetate was observed in IAP infants. The analyses of specific antibiotic resistance genes showed a higher occurrence of some beta-lactamase coding genes in infants whose mothers received IAP. Conclusions: Our results indicate an effect of IAP on the establishing early microbiota during the first months of life, which represent a key moment for the development of the microbiota-induced host homeostasis. Understanding the impact of IAP in the gut microbiota development is essential for developing treatments to minimize it, favoring a proper gut microbiota development in IAP-exposed neonates

A scalable monitoring for the CMS Filter Farm based on elasticsearch

A flexible monitoring system has been designed for the CMS File-based Filter Farm making use of modern data mining and analytics components. All the metadata and monitoring information concerning data flow and execution of the HLT are generated locally in the form of small documents using the JSON encoding. These documents are indexed into a hierarchy of elasticsearch (es) clusters along with process and system log information. Elasticsearch is a search server based on Apache Lucene. It provides a distributed, multitenant-capable search and aggregation engine. Since es is schema-free, any new information can be added seamlessly and the unstructured information can be queried in non-predetermined ways. The leaf es clusters consist of the very same nodes that form the Filter Farm thus providing natural horizontal scaling. A separate central" es cluster is used to collect and index aggregated information. The fine-grained information, all the way to individual processes, remains available in the leaf clusters. The central es cluster provides quasi-real-time high-level monitoring information to any kind of client. Historical data can be retrieved to analyse past problems or correlate them with external information. We discuss the design and performance of this system in the context of the CMS DAQ commissioning for LHC Run 2

Probing non-standard interactions at Daya Bay

In this article we consider the presence of neutrino non-standard interactions (NSI) in the production and detection processes of reactor antineutrinos at the Daya Bay experiment. We report for the first time, the new constraints on the flavor non-universal and flavor universal charged-current NSI parameters, estimated using the currently released 621 days of Daya Bay data. New limits are placed assuming that the new physics effects are just inverse of each other in the production and detection processes. With this special choice of the NSI parameters, we observe a shift in the oscillation amplitude without distorting the L/E pattern of the oscillation probability. This shift in the depth of the oscillation dip can be caused by the NSI parameters as well as by theta(13), making it quite difficult to disentangle the NSI effects from the standard oscillations. We explore the correlations between the NSI parameters and theta(13) that may lead to significant deviations in the reported value of the reactor mixing angle with the help of iso-probability surface plots. Finally, we present the limits on electron, muon/tau, and flavor universal (FU) NSI couplings with and without considering the uncertainty in the normalization of the total event rates. Assuming a perfect knowledge of the event rates normalization, we find strong upper bounds similar to 0.1% for the electron and FU cases improving the present limits by one order of magnitude. However, for a conservative error of 5% in the total normalization, these constraints are relaxed by almost one order of magnitude

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 103 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Net1 and Myeov: computationally identified mediators of gastric cancer

Gastric adenocarcinoma (GA) is a significant cause of mortality worldwide. The molecular mechanisms of GA remain poorly characterised. Our aim was to characterise the functional activity of the computationally identified genes, NET 1 and MYEOV in GA. Digital Differential Display was used to identify genes altered expression in GA-derived EST libraries. mRNA levels of a subset of genes were quantitated by qPCR in a panel of cell lines and tumour tissue. The effect of pro- and anti-inflammatory stimuli on gene expression was investigated. Cell proliferation and invasion were measured using in an in-vitro GA model following inhibition of expression using siRNA. In all, 23 genes not previously reported in association with GA were identified. Two genes, Net1 and Myeov, were selected for further analysis and increased expression was detected in GA tissue compared to paired normal tissue using quantitative PCR. siRNA-mediated downregulation of Net1 and Myeov resulted in decreased proliferation and invasion of gastric cancer cells in vitro. These functional studies highlight a putative role for NET1 and Myeov in the development and progression of gastric cancer. These genes may provide important targets for intervention in GA, evidenced by their role in promoting invasion and proliferation, key phenotypic hallmarks of cancer cells