Adolescence As Risk Factor for Adverse Pregnancy Outcome in Central Africa – A Cross-Sectional Study

BACKGROUND: Sub-Saharan Africa has the highest rates of maternal and neonatal mortality worldwide. Young maternal age at delivery has been proposed as risk factor for adverse pregnancy outcome, yet there is insufficient data from Sub-Saharan Africa. The present study aimed to investigate the influence of maternal adolescence on pregnancy outcomes in the Central African country Gabon. METHODOLOGY AND PRINCIPAL FINDINGS: Data on maternal age, parity, birth weight, gestational age, maternal Plasmodium falciparum infection, use of bednets, and intake of intermittent preventive treatment of malaria in pregnancy were collected in a cross-sectional survey in 775 women giving birth in three mother-child health centers in Gabon. Adolescent women (≤16 years of age) had a significantly increased risk to deliver a baby with low birth weight in univariable analysis (22.8%, 13/57, vs. 9.3%, 67/718, OR: 2.9, 95% CI: 1.5-5.6) and young maternal age showed a statistically significant association with the risk for low birth weight in multivariable regression analysis after correction for established risk factors (OR: 2.7; 95% CI: 1.1-6.5). In further analysis adolescent women were shown to attend significantly less antenatal care visits than adult mothers (3.3±1.9 versus 4.4±1.9 mean visits, p<0.01, n = 356) and this difference accounted at least for part of the excess risk for low birth weight in adolescents. CONCLUSION: Our data demonstrate the importance of adolescent age as risk factor for adverse pregnancy outcome. Antenatal care programs specifically tailored for the needs of adolescents may be necessary to improve the frequency of antenatal care visits and pregnancy outcomes in this risk group in Central Africa

Alternative and complementary therapies in osteoarthritis and cartilage repair

Osteoarthritis (OA) is the most common joint condition and, with a burgeoning ageing population, is due to increase in prevalence. Beyond conventional medical and surgical interventions, there are an increasing number of ‘alternative’ therapies. These alternative therapies may have a limited evidence base and, for this reason, are often only afforded brief reference (or completely excluded) from current OA guidelines. Thus, the aim of this review was to synthesize the current evidence regarding autologous chondrocyte implantation (ACI), mesenchymal stem cell (MSC) therapy, platelet-rich plasma (PRP), vitamin D and other alternative therapies. The majority of studies were in knee OA or chondral defects. Matrix-assisted ACI has demonstrated exceedingly limited, symptomatic improvements in the treatment of cartilage defects of the knee and is not supported for the treatment of knee OA. There is some evidence to suggest symptomatic improvement with MSC injection in knee OA, with the suggestion of minimal structural improvement demonstrated on MRI and there are positive signals that PRP may also lead to symptomatic improvement, though variation in preparation makes inter-study comparison difficult. There is variability in findings with vitamin D supplementation in OA, and the only recommendation which can be made, at this time, is for replacement when vitamin D is deplete. Other alternative therapies reviewed have some evidence (though from small, poor-quality studies) to support improvement in symptoms and again there is often a wide variation in dosage and regimens. For all these therapeutic modalities, although controlled studies have been undertaken to evaluate effectiveness in OA, these have often been of small size, limited statistical power, uncertain blindness and using various methodologies. These deficiencies must leave the question as to whether they have been validated as effective therapies in OA (or chondral defects). The conclusions of this review are that all alternative interventions definitely require clinical trials with robust methodology, to assess their efficacy and safety in the treatment of OA beyond contextual and placebo effects

IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads

The drug discovery process currently employed in the pharmaceutical industry typically requires about 10 years and $2–3 billion to deliver one new drug. This is both too expensive and too slow, especially in emergencies like the COVID-19 pandemic. In silico methodologies need to be improved both to select better lead compounds, so as to improve the efficiency of later stages in the drug discovery protocol, and to identify those lead compounds more quickly. No known methodological approach can deliver this combination of higher quality and speed. Here, we describe an Integrated Modeling PipEline for COVID Cure by Assessing Better LEads (IMPECCABLE) that employs multiple methodological innovations to overcome this fundamental limitation. We also describe the computational framework that we have developed to support these innovations at scale, and characterize the performance of this framework in terms of throughput, peak performance, and scientific results. We show that individual workflow components deliver 100 × to 1000 × improvement over traditional methods, and that the integration of methods, supported by scalable infrastructure, speeds up drug discovery by orders of magnitudes. IMPECCABLE has screened ∼ 1011 ligands and has been used to discover a promising drug candidate. These capabilities have been used by the US DOE National Virtual Biotechnology Laboratory and the EU Centre of Excellence in Computational Biomedicine

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Spike pattern recognition by supervised classification in low dimensional embedding space

© The Author(s) 2016. This article is published with open access at Springerlink.com under the terms of the Creative Commons Attribution License 4.0, (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.Epileptiform discharges in interictal electroencephalography (EEG) form the mainstay of epilepsy diagnosis and localization of seizure onset. Visual analysis is rater-dependent and time consuming, especially for long-term recordings, while computerized methods can provide efficiency in reviewing long EEG recordings. This paper presents a machine learning approach for automated detection of epileptiform discharges (spikes). The proposed method first detects spike patterns by calculating similarity to a coarse shape model of a spike waveform and then refines the results by identifying subtle differences between actual spikes and false detections. Pattern classification is performed using support vector machines in a low dimensional space on which the original waveforms are embedded by locality preserving projections. The automatic detection results are compared to experts’ manual annotations (101 spikes) on a whole-night sleep EEG recording. The high sensitivity (97 %) and the low false positive rate (0.1 min−1), calculated by intra-patient cross-validation, highlight the potential of the method for automated interictal EEG assessment.Peer reviewedFinal Published versio

Expression of the embryonic stem cell marker SOX2 in early-stage breast carcinoma

<p>Abstract</p> <p>Background</p> <p>The SRY-related HMG-box family of transcription factors member <it>SOX2 </it>has been mainly studied in embryonic stem cells as well as early foregut and neural development. More recently, SOX2 was shown to participate in reprogramming of adult somatic cells to a pluripotent stem cell state and implicated in tumorigenesis in various organs. In breast cancer, SOX2 expression was reported as a feature of basal-like tumors. In this study, we assessed SOX2 expression in 95 primary tumors of postmenopausal breast cancer patients.</p> <p>Methods</p> <p>Samples from 95 patients diagnosed and treated at the University of Tuebingen Institute of Pathology and Women's Hospital were analyzed by immunohistochemistry for SOX2 expression in the primary tumor samples and in corresponding lymph node metastasis, where present. Furthermore, SOX2 amplification status was assessed by FISH in representative samples. In addition, eighteen fresh frozen samples were analyzed for <it>SOX2</it>, <it>NANOG </it>and <it>OCT4 </it>gene expression by real-time PCR.</p> <p>Results</p> <p>SOX2 expression was detected in 28% of invasive breast carcinoma as well as in 44% of ductal carcinoma in situ (DCIS) lesions. A score of SOX2 expression (score 0 to 3) was defined in order to distinguish SOX2 negative (score 0) from SOX2 positive samples (score 1-3) and among latter the subgroup of SOX2 high expressors (score 3 > 50% positive cells). Overall, the incidence of SOX2 expression (score 1-3) was higher than previously reported in a cohort of lymph node negative patients (28% versus 16.7%). SOX2 expression was detected across different breast cancer subtypes and did not correlate with tumor grading. However, high SOX2 expression (score 3) was associated with larger tumor size (p = 0.047) and positive lymph node status (0.018). Corresponding metastatic lymph nodes showed higher SOX2 expression and were significantly more often SOX2 positive than primary tumors (p = 0.0432).</p> <p>Conclusions</p> <p>In this report, we show that the embryonic stem cell factor SOX2 is expressed in a variety of early stage postmenopausal breast carcinomas and metastatic lymph nodes. Our data suggest that SOX2 plays an early role in breast carcinogenesis and high expression may promote metastatic potential. Further studies are needed to explore whether SOX2 can predict metastatic potential at an early tumor stage.</p

Modelling Blood Flow and Metabolism in the Preclinical Neonatal Brain during and Following Hypoxic-Ischaemia

Hypoxia-ischaemia (HI) is a major cause of neonatal brain injury, often leading to long-term damage or death. In order to improve understanding and test new treatments, piglets are used as preclinical models for human neonates. We have extended an earlier computational model of piglet cerebral physiology for application to multimodal experimental data recorded during episodes of induced HI. The data include monitoring with near-infrared spectroscopy (NIRS) and magnetic resonance spectroscopy (MRS), and the model simulates the circulatory and metabolic processes that give rise to the measured signals. Model extensions include simulation of the carotid arterial occlusion used to induce HI, inclusion of cytoplasmic pH, and loss of metabolic function due to cell death. Model behaviour is compared to data from two piglets, one of which recovered following HI while the other did not. Behaviourally-important model parameters are identified via sensitivity analysis, and these are optimised to simulate the experimental data. For the non-recovering piglet, we investigate several state changes that might explain why some MRS and NIRS signals do not return to their baseline values following the HI insult. We discover that the model can explain this failure better when we include, among other factors such as mitochondrial uncoupling and poor cerebral blood flow restoration, the death of around 40% of the brain tissue. Copyright

PCNA ubiquitylation ensures timely completion of unperturbed DNA replication in fission yeast

PCNA ubiquitylation on lysine 164 is required for DNA damage tolerance. In many organisms PCNA is also ubiquitylated in unchallenged S phase but the significance of this has not been established. Using Schizosaccharomyces pombe, we demonstrate that lysine 164 ubiquitylation of PCNA contributes to efficient DNA replication in the absence of DNA damage. Loss of PCNA ubiquitylation manifests most strongly at late replicating regions and increases the frequency of replication gaps. We show that PCNA ubiquitylation increases the proportion of chromatin associated PCNA and the co-immunoprecipitation of Polymerase δ with PCNA during unperturbed replication and propose that ubiquitylation acts to prolong the chromatin association of these replication proteins to allow the efficient completion of Okazaki fragment synthesis by mediating gap filling

Adiposity is Associated with Regional Cortical Thinning

BACKGROUND: Although obesity is associated with structural changes in brain grey matter, findings have been inconsistent and the precise nature of these changes is unclear. Inconsistencies may partly be due to the use of different volumetric morphometry methods, and the inclusion of participants with comorbidities that exert independent effects on brain structure. The latter concern is particularly critical when sample sizes are modest. The purpose of the current study was to examine the relationship between cortical grey matter and body mass index (BMI), in healthy participants, excluding confounding comorbidities and using a large sample size. SUBJECTS: A total of 202 self-reported healthy volunteers were studied using surface-based morphometry, which permits the measurement of cortical thickness, surface area and cortical folding, independent of each other. RESULTS: Although increasing BMI was not associated with global cortical changes, a more precise, region-based analysis revealed significant thinning of the cortex in two areas: left lateral occipital cortex (LOC) and right ventromedial prefrontal cortex (vmPFC). An analogous region-based analysis failed to find an association between BMI and regional surface area or folding. Participants' age was also found to be negatively associated with cortical thickness of several brain regions; however, there was no overlap between the age- and BMI-related effects on cortical thinning. CONCLUSIONS: Our data suggest that the key effect of increasing BMI on cortical grey matter is a focal thinning in the left LOC and right vmPFC. Consistent implications of the latter region in reward valuation, and goal control of decision and action suggest a possible shift in these processes with increasing BMI.We thank all the participants and the staff of the Wolfson Brain Imaging Centre. This work was supported by the Bernard Wolfe Health Neuroscience Fund (NM, HZ, ISF, PCF), the Wellcome Trust (RGAG/144 to N.M, RGAG/188 to ISF, RNAG/259 to PCF) and the Medical Research Council (G0701497 to KDE).This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/ijo.2016.42