Untargeted metabolomic analysis of Rat neuroblastoma cells as a model system to study the biochemical effects of the acute administration of methamphetamine

Methamphetamine is an illicit psychostimulant drug that is linked to a number of diseases of the nervous system. The downstream biochemical effects of its primary mechanisms are not well understood, and the objective of this study was to investigate whether untargeted metabolomic analysis of an in vitro model could generate data relevant to what is already known about this drug. Rat B50 neuroblastoma cells were treated with 1 mM methamphetamine for 48 h, and both intracellular and extracellular metabolites were profiled using gas chromatography–mass spectrometry. Principal component analysis of the data identified 35 metabolites that contributed most to the difference in metabolite profiles. Of these metabolites, the most notable changes were in amino acids, with significant increases observed in glutamate, aspartate and methionine, and decreases in phenylalanine and serine. The data demonstrated that glutamate release and, subsequently, excitotoxicity and oxidative stress were important in the response of the neuronal cell to methamphetamine. Following this, the cells appeared to engage amino acid-based mechanisms to reduce glutamate levels. The potential of untargeted metabolomic analysis has been highlighted, as it has generated biochemically relevant data and identified pathways significantly affected by methamphetamine. This combination of technologies has clear uses as a model for the study of neuronal toxicology

Are the black hole masses in Narrow Line Seyfert 1 galaxies actually small?

Narrow Line Seyfert 1 galaxies (NLS1s) are generally considered peculiar objects among the broad class of Type 1 active galactic nuclei, due to the relatively small width of the broad lines, strong X-ray variability, soft X-ray continua, weak [OIII], and strong FeII line intensities. The mass M_BH of the central massive black hole (MBH) is claimed to be lighter than expected from known MBH-host galaxy scaling relations, while the accretion rate onto the MBH larger than the average value appropriate to Seyfert 1 galaxies. In this Letter, we show that NLS1 peculiar M_BH and L/L_Edd turn out to be fairly standard, provided that the broad line region is allowed to have a disc-like, rather than isotropic, geometry. Assuming that NLS1s are rather ``normal'' Seyfert 1 objects seen along the disc axis, we could estimate the typical inclination angles from the fraction of Seyfert 1 classified as NLS1s, and compute the geometrical factor relating the observed FWHM of broad lines to the virial mass of the MBH. We show that the geometrical factor can fully account for the "black hole mass deficit" observed in NLS1s, and that L/L_Edd is (on average) comparable to the value of the more common broad line Seyfert 1 galaxies.Comment: 5 pages, 3 figures. Accepted for publication in MNRAS Letters. Wrong version was uploaded! Check for the correct one in the replacemen

Providing contexts for classification of transients in a wide-area sky survey: An application of noise-induced cluster ensemble

With new sensor systems that capture sky survey at high quality level, analyzing the resulting data within a limited time frame appears to be the next challenge. Specific to the GOTO project, this task proves to be crucial to discover new transients from a pool of large candidates. Initial works based on the feature-based approach design this detection as imbalance classification, where a data-level method can be used to resolve the difference in cardinality between classes. This paper presents a context generation framework to complement the previously proposed model. In particular, samples are clustered to form data contexts to which different learning strategies may be applied. To ensure the quality of data clustering, a noise-induced cluster ensemble technique that has been recently introduced in the literature is employed here. The results with simulated data and algorithms of NB, C4.5 and KNN have shown that the proposed framework can filter out some negative samples quickly, while making classification of the rest more effective. In particular, it enhances predictive performance of basic classifiers by lifting F1 scores from less than 0.1 to around 0.3–0.5. Besides, parameter analysis is also given as a guideline for its application

Electrochemical Characterization of Self-Assembled Monolayers on Gold Substrates Derived from Thermal Decomposition of Monolayer-Protected Cluster Films

Networked films of monolayer-protected clusters (MPCs), alkanethiolate-stabilized gold nanoparticles, can be thermally decomposed to form stable gold on glass substrates that are subsequently modified with self-assembled monolayers (SAMs) for use as modified electrodes. Electrochemical assessment of these SAM-modified gold substrates, including double-layer capacitance measurements, linear sweep desorption of the alkanethiolates, and diffusional redox probing, all show that SAMs formed on gold supports formed from thermolysis of MPC films possess substantially higher defect density compared to SAMs formed on traditional evaporated gold. The density of defects in the SAMs on thermolyzed gold is directly related to the strategies used to assemble the MPC film prior to thermolysis. Specifically, gold substrates formed from thermally decomposing MPC films formed with electrostatic bridges between carboxylic acid-modified MPCs and metal ion linkers are particularly sensitive to the degree of metal exposure during the assembly process. While specific metal dependence was observed, metal concentration within the MPC precursor film was determined to be a more significant factor. Specific MPC film linking strategies and pretreatment methods that emphasized lower metal exposure resulted in gold films that supported SAMs of lower defect density. The defect density of a SAM-modified electrode is shown to be critical in certain electrochemical experiments such as protein monolayer electrochemistry of adsorbed cytochrome c. While the thermal decomposition of nanoparticle film assemblies remains a viable and interesting technique for coating both flat and irregular shaped substrates, this study provides electrochemical assessment tools and tactics for determining and controlling SAM defect density on this type of gold structure, a property critical to their effective use in subsequent electrochemical applications

Cell-Cell Interactions and the Regulation of Testis Function

Regulatory interactions have been shown to occur between all the testicular cell types considered. The paracrine factors mediating these interactions generally influence either cellular growth or differentiation. The regulation of cellular growth is essential in the developing testis and is required for the maintenance of spermatogenesis in the adult testis. The rapid rate of germinal cell proliferation and the continuous but slowed growth of the peritubular cells and Leydig cells requires the presence of specific growth factors in the adult. Therefore, cell-cell interactions have evolved that involve growth factors such as IGF, TGF-alpha, TGF-beta and NGF. Other growth factors such as FGF or less characterized components like the seminiferous growth factor (SGF) also may be involved in the paracrine regulation of testis cell growth. An alternate cellular parameter to cell growth to consider is the regulation of cellular function and differentiation. A number of endocrine agents and locally produced paracrine factors have been shown to control and maintain testis cell function and differentiation. Cell-cell interactions mediated by factors such as androgens, POMC peptides, and PModS are all primarily directed at the regulation of cellular differentiation. Therefore, the agents which mediate cell-cell interactions in the testis can generally be categorized into factors that regulate cell growth or those which influence cellular differentiation. The specific cell-cell interactions identified will likely be the first of a large number of cellular interactions yet to be investigated. Although a number of potentially important cell-cell interactions have been identified, future research will require the elucidation of the in vivo physiological significance of these interactions. The existence of different cell types and potential cell-cell interactions in a tissue implies that the actions of an endocrine agent on a tissue will not simply involve a single hormone and single cell. The endocrine regulation of testis function will have effects on cell-cell interactions and be affected by local cell-cell interactions. The ability of LH to influence Leydig cell androgen production promotes a cascade of interactions mediated through several cell types to maintain the process of spermatogenesis. FSH actions on Sertoli cells also promote cell-cell interactions that influence germinal cell development, peritubular myoid cell differentiation and Leydig cell function. Therefore, elucidation of the endocrine regulation of testis function requires an understanding of the local cell-cell interactions in the testis

Determining patterns of student graduation using a bi-level learning framework

The practice of data science, artificial intelligence (AI) in general, has expanded greatly in terms of both theoretical and application domains. Many existing and new problems have been tackled using different reasoning and learning methods. These include the research subject, generally referred to as education data mining (or EDM). Among many issues that have been studied in this EMD community, student performance and achievement provide an interesting, yet useful result to shaping effective learning style and academic consultation. Specific to this work at Mae Fah Luang University, the pattern of students’ graduation is determined based on their profile of performance in different categories of courses. This course-group approach is picked up to generalize the framework for various undergraduation programmes. In that, a bi-level learning method is proposed in order to predict the length of study before graduation. At the first tier, clustering is applied to derive major types of performance profiles, for which classification models can be developed to refine the prediction further. With the experiments on a real data collection, this framework usually provides accurate predictive outcomes, using several conventional classification techniques

Morphological alterations of small intestinal epithelium of calves caused by feeding soybean protein.

The objective of this experiment was to detect alterations of small intestinal mucosa due to incorporation of large amounts of soybean protein in milk replacers and to relate these alterations to calf performance

The X-Ray Star Formation Story as Told by Lyman Break Galaxies in the 4 Ms CDF-S

We present results from deep X-ray stacking of {gt}4000 high-redshift galaxies from z {ap} 1 to 8 using the 4 Ms Chandra Deep Field-South data, the deepest X-ray survey of the extragalactic sky to date. The galaxy samples were selected using the Lyman break technique based primarily on recent Hubble Space Telescope ACS and WFC3 observations. Based on such high specific star formation rates (sSFRs): log SFR/M $_{*}$ {gt} -8.7, we expect that the observed properties of these Lyman break galaxies (LBGs) are dominated by young stellar populations. The X-ray emission in LBGs, eliminating individually detected X-ray sources (potential active galactic nucleus), is expected to be powered by X-ray binaries and hot gas. We find, for the first time, evidence of evolution in the X-ray/SFR relation. Based on X-ray stacking analyses for z {lt} 4 LBGs (covering ~{}90% of the universe's history), we find that the 2-10 keV X-ray luminosity evolves weakly with redshift (z) and SFR as log L $_X$ = 0.93log (1 + z) + 0.65log SFR + 39.80. By comparing our observations with sophisticated X-ray binary population synthesis models, we interpret that the redshift evolution of L $_X$/SFR is driven by metallicity evolution in high mass X-ray binaries, likely the dominant population in these high sSFR galaxies. We also compare these models with our observations of X-ray luminosity density (total 2-10 keV luminosity per Mpc$^{3}$) and find excellent agreement. While there are no significant stacked detections at z {gt}~{} 5, we use our upper limits from 5 {lt}~{} z {lt}~{} 8 LBGs to constrain the supermassive black hole accretion history of the universe around the epoch of reionization

Evidence for feedback in action from the molecular gas content in the z~1.6 outflowing QSO XID2028

Gas outflows are believed to play a pivotal role in shaping galaxies, as they regulate both star formation and black hole growth. Despite their ubiquitous presence, the origin and the acceleration mechanism of such powerful and extended winds is not yet understood. Direct observations of the cold gas component in objects with detected outflows at other wavelengths are needed to assess the impact of the outflow on the host galaxy interstellar medium (ISM). We observed with the Plateau de Bure Interferometer an obscured quasar at z~1.5, XID2028, for which the presence of an ionised outflow has been unambiguously signalled by NIR spectroscopy. The detection of CO(3-2) emission in this source allows us to infer the molecular gas content and compare it to the ISM mass derived from the dust emission. We then analyze the results in the context of recent insights on scaling relations, which describe the gas content of the overall population of star-forming galaxies at a similar redshifts. The Star formation efficiency (~100) and gas mass (M_gas=2.1-9.5x10^{10} M_sun) inferred from the CO(3-2) line depend on the underlying assumptions on the excitation of the transition and the CO-to-H2 conversion factor. However, the combination of this information and the ISM mass estimated from the dust mass suggests that the ISM/gas content of XID2028 is significantly lower than expected for its observed M⋆, sSFR and redshift, based on the most up-to-date calibrations (with gas fraction <20% and depletion time scale <340 Myr). Overall, the constraints we obtain from the far infrared and millimeter data suggest that we are observing QSO feedback able to remove the gas from the host

The transcriptional response of Caenorhabditis elegans to ivermectin exposure identifies novel genes involved in the response to reduced food intake

We have examined the transcriptional response of Caenorhabditis elegans following exposure to the anthelmintic drug ivermectin (IVM) using whole genome microarrays and real-time QPCR. Our original aim was to identify candidate molecules involved in IVM metabolism and/or excretion. For this reason the IVM tolerant strain, DA1316, was used to minimise transcriptomic changes related to the phenotype of drug exposure. However, unlike equivalent work with benzimidazole drugs, very few of the induced genes were members of xenobiotic metabolising enzyme families. Instead, the transcriptional response was dominated by genes associated with fat mobilization and fatty acid metabolism including catalase, esterase, and fatty acid CoA synthetase genes. This is consistent with the reduction in pharyngeal pumping, and consequential reduction in food intake, upon exposure of DA1316 worms to IVM. Genes with the highest fold change in response to IVM exposure, cyp-37B1, mtl-1 and scl-2, were comparably up-regulated in response to short–term food withdrawal (4 hr) independent of IVM exposure, and GFP reporter constructs confirm their expression in tissues associated with fat storage (intestine and hypodermis). These experiments have serendipitously identified novel genes involved in an early response of C. elegans to reduced food intake and may provide insight into similar processes in higher organisms