Search results for "Mach"
showing 10 items of 3360 documents
The neuropeptide 26RFa in the human gut and pancreas: potential involvement in glucose homeostasis
2019
Objective Recent studies performed in mice revealed that the neuropeptide 26RFa regulates glucose homeostasis by acting as an incretin and by increasing insulin sensitivity. However, in humans, an association between 26RFa and the regulation of glucose homeostasis is poorly documented. In this study, we have thus investigated in detail the distribution of 26RFa and its receptor, GPR103, in the gut and the pancreas, and determined the response of this peptidergic system to an oral glucose challenge in obese patients. Design and methods Distribution of 26RFa and GPR103 was examined by immunohistochemistry using gut and pancreas tissue sections. Circulating 26RFa was determined using a specif…
Treatment of advanced gastroenteropancreatic neuroendocrine neoplasia, are we on the way to personalised medicine?
2021
Gastroenteropancreatic neuroendocrine neoplasia (GEPNEN) comprises clinically as well as prognostically diverse tumour entities often diagnosed at late stage. Current classification provides a uniform terminology and a Ki67-based grading system, thereby facilitating management. Advances in the study of genomic and epigenetic landscapes have amplified knowledge of tumour biology and enhanced identification of prognostic and potentially predictive treatment subgroups. Translation of this genomic and mechanistic biology into advanced GEPNEN management is limited. ‘Targeted’ treatments such as somatostatin analogues, peptide receptor radiotherapy, tyrosine kinase inhibitors and mammalian target…
Statistical Explorations and Univariate Timeseries Analysis on COVID-19 Datasets to Understand the Trend of Disease Spreading and Death
2020
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Towards identifying drug side effects from social media using active learning and crowd sourcing.
2019
Motivation Social media is a largely untapped source of information on side effects of drugs. Twitter in particular is widely used to report on everyday events and personal ailments. However, labeling this noisy data is a difficult problem because labeled training data is sparse and automatic labeling is error-prone. Crowd sourcing can help in such a scenario to obtain more reliable labels, but is expensive in comparison because workers have to be paid. To remedy this, semi-supervised active learning may reduce the number of labeled data needed and focus the manual labeling process on important information. Results We extracted data from Twitter using the public API. We subsequently use Ama…
Paving the way for synthetic biology-based bioremediation in Europe
2009
Synthetic biology (SB) has a dual definition. It is both the design and construction of new biological parts, devices and systems, and also the re‐design of existing, natural systems for useful purposes. The latter field is maybe one of the major challenges within this discipline, since the promising prospect that biological systems may be used as biomachines will certainly be exploited in the near future. Synthetic biology has challenging conceptual possibilities (Moya et al., 2009a) and impressive progress has already been made in biotechnology following SB approaches (de Lorenzo and Danchin, 2008). Much more is expected in the near future from current efforts aiming to make synthetic gen…
Boosting Signal-to-Noise in Complex Biology: Prior Knowledge Is Power
2011
A major difficulty in the analysis of complex biological systems is dealing with the low signal-to-noise inherent to nearly all large biological datasets. We discuss powerful bioinformatic concepts for boosting signal-to-noise through external knowledge incorporated in processing units we call filters and integrators. These concepts are illustrated in four landmark studies that have provided model implementations of filters, integrators, or both.
Defining classifier regions for WSD ensembles using word space features
2006
Based on recent evaluation of word sense disambiguation (WSD) systems [10], disambiguation methods have reached a standstill. In [10] we showed that it is possible to predict the best system for target word using word features and that using this 'optimal ensembling method' more accurate WSD ensembles can be built (3-5% over Senseval state of the art systems with the same amount of possible potential remaining). In the interest of developing if more accurate ensembles, w e here define the strong regions for three popular and effective classifiers used for WSD task (Naive Bayes – NB, Support Vector Machine – SVM, Decision Rules – D) using word features (word grain, amount of positive and neg…
Building an Optimal WSD Ensemble Using Per-Word Selection of Best System
2006
In Senseval workshops for evaluating WSD systems [1,4,9], no one system or system type (classifier algorithm, type of system ensemble, extracted feature set, lexical knowledge source etc.) has been discovered that resolves all ambiguous words into their senses in a superior way. This paper presents a novel method for selecting the best system for target word based on readily available word features (number of senses, average amount of training per sense, dominant sense ratio). Applied to Senseval-3 and Senseval-2 English lexical sample state-of-art systems, a net gain of approximately 2.5 – 5.0% (respectively) in average precision per word over the best base system is achieved. The method c…
Efficient Online Laplacian Eigenmap Computation for Dimensionality Reduction in Molecular Phylogeny via Optimisation on the Sphere
2019
Reconstructing the phylogeny of large groups of large divergent genomes remains a difficult problem to solve, whatever the methods considered. Methods based on distance matrices are blocked due to the calculation of these matrices that is impossible in practice, when Bayesian inference or maximum likelihood methods presuppose multiple alignment of the genomes, which is itself difficult to achieve if precision is required. In this paper, we propose to calculate new distances for randomly selected couples of species over iterations, and then to map the biological sequences in a space of small dimension based on the partial knowledge of this genome similarity matrix. This mapping is then used …
Sensory methodologies and the taste of water
2009
/WOS: 000285178000010; International audience; Describing the taste of water is a challenge since drinking water is supposed to have almost no taste. In this study, different classical sensory methodologies have been applied in order to assess sensory characteristics of water and have been compared: sensory profiling, Temporal Dominance of Sensations and free sorting task. These methodologies present drawbacks: sensory profile and TDS do not provide an effective discrimination of the taste of water and the free sorting task is efficient but does not enable data aggregation. A new methodology based on comparison with a set of references and named “Polarized Sensory Positioning” (PSP) has bee…