Inflammatory mediators as biomarkers in brain disorders.

Neurodegenerative diseases such as Alzheimer, Parkinson, amyotrophic lateral sclerosis, and Huntington are incurable and debilitating conditions that result in progressive death of the neurons. The definite diagnosis of a neurodegenerative disorder is disadvantaged by the difficulty in obtaining biopsies and thereby to validate the clinical diagnosis with pathological results. Biomarkers are valuable indicators for detecting different phases of a disease such as prevention, early onset, treatment, progression, and monitoring the effect of pharmacological responses to a therapeutic intervention. Inflammation occurs in neurodegenerative diseases, and identification and validation of molecules involved in this process could be a strategy for finding new biomarkers. The ideal inflammatory biomarker needs to be easily measurable, must be reproducible, not subject to wide variation in the population, and unaffected by external factors. Our review summarizes the most important inflammation biomarkers currently available, whose specificity could be utilized for identifying and monitoring distinctive phases of different neurodegenerative diseases

CMB photons shedding light on dark matter

The annihilation or decay of Dark Matter (DM) particles could affect the thermal history of the universe and leave an observable signature in Cosmic Microwave Background (CMB) anisotropies. We update constraints on the annihilation rate of DM particles in the smooth cosmological background, using WMAP7 and recent small-scale CMB data. With a systematic analysis based on the Press-Schechter formalism, we also show that DM annihilation in halos at small redshift may explain entirely the reionization patterns observed in the CMB, under reasonable assumptions concerning the concentration and formation redshift of halos. We find that a mixed reionization model based on DM annihilation in halos as well as star formation at a redshift z~6.5 could simultaneously account for CMB observations and satisfy constraints inferred from the Gunn-Peterson effect. However, these models tend to reheat the inter-galactic medium (IGM) well above observational bounds: by including a realistic prior on the IGM temperature at low redshift, we find stronger cosmological bounds on the annihilation cross-section than with the CMB alone.Comment: 35 pages, 14 figures; version accepted in JCAP after minor revision

The MUSE-Wide Survey: Survey Description and First Data Release

We present the MUSE-Wide survey, a blind, 3D spectroscopic survey in the CANDELS/GOODS-S and CANDELS/COSMOS regions. Each MUSE-Wide pointing has a depth of 1 hour and hence targets more extreme and more luminous objects over 10 times the area of the MUSE-Deep fields (Bacon et al. 2017). The legacy value of MUSE-Wide lies in providing "spectroscopy of everything" without photometric pre-selection. We describe the data reduction, post-processing and PSF characterization of the first 44 CANDELS/GOODS-S MUSE-Wide pointings released with this publication. Using a 3D matched filtering approach we detected 1,602 emission line sources, including 479 Lyman-$\alpha$ (Lya) emitting galaxies with redshifts $2.9 \lesssim z \lesssim 6.3$. We cross-match the emission line sources to existing photometric catalogs, finding almost complete agreement in redshifts and stellar masses for our low redshift (z < 1.5) emitters. At high redshift, we only find ~55% matches to photometric catalogs. We encounter a higher outlier rate and a systematic offset of $\Delta$z$\simeq$0.2 when comparing our MUSE redshifts with photometric redshifts. Cross-matching the emission line sources with X-ray catalogs from the Chandra Deep Field South, we find 127 matches, including 10 objects with no prior spectroscopic identification. Stacking X-ray images centered on our Lya emitters yielded no signal; the Lya population is not dominated by even low luminosity AGN. A total of 9,205 photometrically selected objects from the CANDELS survey lie in the MUSE-Wide footprint, which we provide optimally extracted 1D spectra of. We are able to determine the spectroscopic redshift of 98% of 772 photometrically selected galaxies brighter than 24th F775W magnitude. All the data in the first data release - datacubes, catalogs, extracted spectra, maps - are available on the website https://musewide.aip.de. [abridged]Comment: 25 pages 15+1 figures. Accepted, A&A. Comments welcom

Insulin Resistance as Common Molecular Denominator Linking Obesity to Alzheimer's Disease

Alzheimer's disease (AD) is an aging-related multi-factorial disorder to which metabolic factors contribute at what has canonically been considered a centrally mediated process. Although the exact underlying mechanisms are still unknown, obesity is recognized as a risk factor for AD and the condition of insulin resistance seems to be the link between the two pathologies. Using mice with high fat diet (HFD) obesity we dissected the molecular mechanisms shared by the two disorders. Brains of HFD fed mice showed elevated levels of APP and Aβ40/Aβ42 together with BACE, GSK3β and Tau proteins involved in APP processing and Aβ accumulation. Immunofluorescence, Thioflavin T staining experiments, confirmed increased Aβ generation, deposition in insoluble fraction and plaques formation in both the hippocampus and the cerebral cortex of HFD mice. Presence of Aβ40/Aβ42 in the insoluble fraction was also shown by ELISA assay. Brain insulin resistance was demonstrated by reduced presence of insulin receptor (IRs) and defects in Akt-Foxo3a insulin signaling. We found reduced levels of phospho-Akt and increased levels of Foxo3a in the nuclei of neurons where proapototic genes were activated. Dysregulation of different genes related to insulin resistance, especially those involved in inflammation and adipocytokines synthesis were analyzed by Profiler PCR array. Further, HFD induced oxidative stress, mitochondrial dysfunction and dynamics as demonstrated by expression of biomarkers involved in these processes. Here, we provide evidence that obesity and AD markers besides insulin resistance are associated with inflammation, adipokine dyshomeostasis, oxidative stress and mitochondrial dysfunction, all mechanisms leading to neurodegeneration

Metformin increases APP expression and processing via oxidative stress, mitochondrial dysfunction and NF-κB activation: Use of insulin to attenuate metformin's effect

Clinical and experimental biomedical studies have shown Type 2 diabetes mellitus (T2DM) to be a risk factor for the development of Alzheimer's disease (AD). This study demonstrates the effect of metformin, a therapeutic biguanide administered for T2DM therapy, on β-amyloid precursor protein (APP) metabolism in in vitro, ex vivo and in vivo models. Furthermore, the protective role of insulin against metformin is also demonstrated. In LAN5 neuroblastoma cells, metformin increases APP and presenilin levels, proteins involved in AD. Overexpression of APP and presenilin 1 (Pres 1) increases APP cleavage and intracellular accumulation of β-amyloid peptide (Aβ), which, in turn, promotes aggregation of Aβ. In the experimental conditions utilized the drug causes oxidative stress, mitochondrial damage, decrease of Hexokinase-II levels and cytochrome C release, all of which lead to cell death. Several changes in oxidative stress-related genes following metformin treatment were detected by PCR arrays specific for the oxidative stress pathway. These effects of metformin were found to be antagonized by the addition of insulin, which reduced Aβ levels, oxidative stress, mitochondrial dysfunction and cell death. Similarly, antioxidant molecules, such as ferulic acid and curcumin, are able to revert metformin's effect. Comparable results were obtained using peripheral blood mononuclear cells. Finally, the involvement of NF-κB transcription factor in regulating APP and Pres 1 expression was investigated. Upon metformin treatment, NF-κB is activated and translocates from the cytoplasm to the nucleus, where it induces increased APP and Pres 1 transcription. The use of Bay11-7085 inhibitor suppressed the effect of metformin on APP and Pres 1 expression

Investigating knowledge management factors affecting Chinese ICT firms performance: An integrated KM framework

This is an Author's Accepted Manuscript of an article published in the Journal of Information Systems Management, 28(1), 19 - 29, 2011, copyright Taylor & Francis, available online at: http://www.tandfonline.com/10.1080/10580530.2011.536107.This article sets out to investigate the critical factors of Knowledge Management (KM) which are considered to have an impact on the performance of Chinese information and communication technology (ICT) firms. This study confirms that the cultural environment of an enterprise is central to its success in the context of China. It shows that a collaborated, trusted, and learning environment within ICT firms will have a positive impact on their KM performance

Ontology of core data mining entities

In this article, we present OntoDM-core, an ontology of core data mining entities. OntoDM-core defines themost essential datamining entities in a three-layered ontological structure comprising of a specification, an implementation and an application layer. It provides a representational framework for the description of mining structured data, and in addition provides taxonomies of datasets, data mining tasks, generalizations, data mining algorithms and constraints, based on the type of data. OntoDM-core is designed to support a wide range of applications/use cases, such as semantic annotation of data mining algorithms, datasets and results; annotation of QSAR studies in the context of drug discovery investigations; and disambiguation of terms in text mining. The ontology has been thoroughly assessed following the practices in ontology engineering, is fully interoperable with many domain resources and is easy to extend