Glucose intolerance and gestational diabetes risk in relation to sleep duration and snoring during pregnancy: a pilot study

<p>Abstract</p> <p>Background</p> <p>Insufficient sleep and poor sleep quality, considered endemic in modern society, are associated with obesity, impaired glucose tolerance and diabetes. Little, however, is known about the consequences of insufficient sleep and poor sleep quality during pregnancy on glucose tolerance and gestational diabetes.</p> <p>Methods</p> <p>A cohort of 1,290 women was interviewed during early pregnancy. We collected information about sleep duration and snoring during early pregnancy. Results from screening and diagnostic testing for gestational diabetes mellitus (GDM) were abstracted from medical records. Generalized linear models were fitted to derive relative risk (RR) and 95% confidence intervals (95% CIs) of GDM associated with sleep duration and snoring, respectively.</p> <p>Results</p> <p>After adjusting for maternal age and race/ethnicity, GDM risk was increased among women sleeping ≤ 4 hours compared with those sleeping 9 hours per night (RR = 5.56; 95% CI 1.31-23.69). The corresponding RR for lean women (<25 kg/m²) was 3.23 (95% CI 0.34-30.41) and 9.83 (95% CI 1.12-86.32) for overweight women (≥ 25 kg/m²). Overall, snoring was associated with a 1.86-fold increased risk of GDM (RR = 1.86; 95% CI 0.88-3.94). The risk of GDM was particularly elevated among overweight women who snored. Compared with lean women who did not snore, those who were overweight and snored had a 6.9-fold increased risk of GDM (95% CI 2.87-16.6).</p> <p>Conclusions</p> <p>These preliminary findings suggest associations of short sleep duration and snoring with glucose intolerance and GDM. Though consistent with studies of men and non-pregnant women, larger studies that include objective measures of sleep duration, quality and apnea are needed to obtain more precise estimates of observed associations.</p

PI3Kinase signaling in glioblastoma

Glioblastoma (GBM) is the most common primary tumor of the CNS in the adult. It is characterized by exponential growth and diffuse invasiveness. Among many different genetic alterations in GBM, e.g., mutations of PTEN, EGFR, p16/p19 and p53 and their impact on aberrant signaling have been thoroughly characterized. A major barrier to develop a common therapeutic strategy is founded on the fact that each tumor has its individual genetic fingerprint. Nonetheless, the PI3K pathway may represent a common therapeutic target to most GBM due to its central position in the signaling cascade affecting proliferation, apoptosis and migration. The read-out of blocking PI3K alone or in combination with other cancer pathways should mainly focus, besides the cytostatic effect, on cell death induction since sublethal damage may induce selection of more malignant clones. Targeting more than one pathway instead of a single agent approach may be more promising to kill GBM cells

Alignment of the CMS tracker with LHC and cosmic ray data

© CERN 2014 for the benefit of the CMS collaboration, published under the terms of the Creative Commons Attribution 3.0 License by IOP Publishing Ltd and Sissa Medialab srl. Any further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation and DOI.The central component of the CMS detector is the largest silicon tracker ever built. The precise alignment of this complex device is a formidable challenge, and only achievable with a significant extension of the technologies routinely used for tracking detectors in the past. This article describes the full-scale alignment procedure as it is used during LHC operations. Among the specific features of the method are the simultaneous determination of up to 200 000 alignment parameters with tracks, the measurement of individual sensor curvature parameters, the control of systematic misalignment effects, and the implementation of the whole procedure in a multi-processor environment for high execution speed. Overall, the achieved statistical accuracy on the module alignment is found to be significantly better than 10μm

Upper limit map of a background of gravitational waves

We searched for an anisotropic background of gravitational waves using data from the LIGO S4 science run and a method that is optimized for point sources. This is appropriate if, for example, the gravitational wave background is dominated by a small number of distinct astrophysical sources. No signal was seen. Upper limit maps were produced assuming two different power laws for the source strain power spectrum. For an f^-3 power law and using the 50 Hz to 1.8 kHz band the upper limits on the source strain power spectrum vary between 1.2e-48 Hz^-1 (100 Hz/f)^3 and 1.2e-47 Hz^-1 (100 Hz /f)^3, depending on the position in the sky. Similarly, in the case of constant strain power spectrum, the upper limits vary between 8.5e-49 Hz^-1 and 6.1e-48 Hz^-1. As a side product a limit on an isotropic background of gravitational waves was also obtained. All limits are at the 90% confidence level. Finally, as an application, we focused on the direction of Sco-X1, the closest low-mass X-ray binary. We compare the upper limit on strain amplitude obtained by this method to expectations based on the X-ray luminosity of Sco-X1.Comment: 11 pages, 9 figures, 2 table

Upper limit map of a background of gravitational waves

We searched for an anisotropic background of gravitational waves using data from the LIGO S4 science run and a method that is optimized for point sources. This is appropriate if, for example, the gravitational wave background is dominated by a small number of distinct astrophysical sources. No signal was seen. Upper limit maps were produced assuming two different power laws for the source strain power spectrum. For an f^-3 power law and using the 50 Hz to 1.8 kHz band the upper limits on the source strain power spectrum vary between 1.2e-48 Hz^-1 (100 Hz/f)^3 and 1.2e-47 Hz^-1 (100 Hz /f)^3, depending on the position in the sky. Similarly, in the case of constant strain power spectrum, the upper limits vary between 8.5e-49 Hz^-1 and 6.1e-48 Hz^-1. As a side product a limit on an isotropic background of gravitational waves was also obtained. All limits are at the 90% confidence level. Finally, as an application, we focused on the direction of Sco-X1, the closest low-mass X-ray binary. We compare the upper limit on strain amplitude obtained by this method to expectations based on the X-ray luminosity of Sco-X1.Comment: 11 pages, 9 figures, 2 table

Post-mortem volatiles of vertebrate tissue

Volatile emission during vertebrate decay is a complex process that is understood incompletely. It depends on many factors. The main factor is the metabolism of the microbial species present inside and on the vertebrate. In this review, we combine the results from studies on volatile organic compounds (VOCs) detected during this decay process and those on the biochemical formation of VOCs in order to improve our understanding of the decay process. Micro-organisms are the main producers of VOCs, which are by- or end-products of microbial metabolism. Many microbes are already present inside and on a vertebrate, and these can initiate microbial decay. In addition, micro-organisms from the environment colonize the cadaver. The composition of microbial communities is complex, and communities of different species interact with each other in succession. In comparison to the complexity of the decay process, the resulting volatile pattern does show some consistency. Therefore, the possibility of an existence of a time-dependent core volatile pattern, which could be used for applications in areas such as forensics or food science, is discussed. Possible microbial interactions that might alter the process of decay are highlighted

Identification of regulatory variants associated with genetic susceptibility to meningococcal disease

Non-coding genetic variants play an important role in driving susceptibility to complex diseases but their characterization remains challenging. Here, we employed a novel approach to interrogate the genetic risk of such polymorphisms in a more systematic way by targeting specific regulatory regions relevant for the phenotype studied. We applied this method to meningococcal disease susceptibility, using the DNA binding pattern of RELA - a NF-kB subunit, master regulator of the response to infection - under bacterial stimuli in nasopharyngeal epithelial cells. We designed a custom panel to cover these RELA binding sites and used it for targeted sequencing in cases and controls. Variant calling and association analysis were performed followed by validation of candidate polymorphisms by genotyping in three independent cohorts. We identified two new polymorphisms, rs4823231 and rs11913168, showing signs of association with meningococcal disease susceptibility. In addition, using our genomic data as well as publicly available resources, we found evidences for these SNPs to have potential regulatory effects on ATXN10 and LIF genes respectively. The variants and related candidate genes are relevant for infectious diseases and may have important contribution for meningococcal disease pathology. Finally, we described a novel genetic association approach that could be applied to other phenotypes

PaLM 2 Technical Report

We introduce PaLM 2, a new state-of-the-art language model that has better multilingual and reasoning capabilities and is more compute-efficient than its predecessor PaLM. PaLM 2 is a Transformer-based model trained using a mixture of objectives. Through extensive evaluations on English and multilingual language, and reasoning tasks, we demonstrate that PaLM 2 has significantly improved quality on downstream tasks across different model sizes, while simultaneously exhibiting faster and more efficient inference compared to PaLM. This improved efficiency enables broader deployment while also allowing the model to respond faster, for a more natural pace of interaction. PaLM 2 demonstrates robust reasoning capabilities exemplified by large improvements over PaLM on BIG-Bench and other reasoning tasks. PaLM 2 exhibits stable performance on a suite of responsible AI evaluations, and enables inference-time control over toxicity without additional overhead or impact on other capabilities. Overall, PaLM 2 achieves state-of-the-art performance across a diverse set of tasks and capabilities. When discussing the PaLM 2 family, it is important to distinguish between pre-trained models (of various sizes), fine-tuned variants of these models, and the user-facing products that use these models. In particular, user-facing products typically include additional pre- and post-processing steps. Additionally, the underlying models may evolve over time. Therefore, one should not expect the performance of user-facing products to exactly match the results reported in this report