Optical absorption parameters of amorphous carbon films from Forouhi–Bloomer and Tauc–Lorentz models: a comparative study

International audienceParametrization models of optical constants, namely Tauc-Lorentz (TL), Forouhi-Bloomer (FB) and modified FB models, were applied to the interband absorption of amorphous carbon films. The optical constants were determined by means of transmittance and reflectance measurements in the visible range. The studied films were prepared by rf sputtering and characterized for their chemical properties. The analytical models were also applied to other optical data published in the literature pertaining to films produced by various deposition techniques. The different approaches used to determine important physical parameters of the interband transition yielded different results. A figure-of-merit was introduced to check the applicability of the models and the results showed that FB modified for an energy dependence of the dipole matrix element adequately represents the interband transition in the amorphous carbons. Further, the modified FB model shows a relative superiority over the TL ones for concerning the determination of the band gap energy, as it is the only one to be validated by an independent, though indirect, gap measurement by x-ray photoelectron spectroscopy. Finally, the application of the modified FB model allowed us to establish some important correlations between film structure and optical absorption properties

Messenger RNA expression of transporter and ion channel genes in undifferentiated and differentiated Caco-2 cells compared to human intestines.

PURPOSE: The purpose of this work was to study the influence of cell differentiation on the mRNA expression of transporters and channels in Caco-2 cells and to assess Caco-2 cells as a model for carrier-mediated drug transport in the intestines. METHOD: Gene mRNA expression was measured using a custom-designed microarray chip with 750 deoxyoligonucleotide probes (70mers). Each oligomer was printed four times on poly-lysine-coated glass slides. Expression profiles were expressed as ratio values between fluorescence intensities of Cy3 and Cy5 dye-labeled cDNA derived from poly(A) + RNA samples of Caco-2 cells and total RNA of human intestines. RESULTS: Significant differences in the mRNA expression profile of transporters and channels were observed upon differentiation of Caco-2 cells from 5 days to 2 weeks in culture, including changes for MAT8, S-protein, and Nramp2. Comparing Caco-2 cells of different passage number revealed few changes in mRNAs except for GLUT3, which was down-regulated 2.4-fold within 13 passage numbers. Caco-2 cells had a similar expression profile when either cultured in flasks or on filters but differed more strongly from human small and large intestine, regardless of the differentiation state of Caco-2 cells. Expression of several genes highly transcribed in small or large intestines differed fourfold or more in Caco-2 cells. CONCLUSIONS: Although Caco-2 cells have proven a suitable model for studying carrier-mediated transport in human intestines, the expression of specific transporter and ion channel genes may differ substantially

Gradual not sudden change: multiple sites of functional transition across the microvascular bed

In understanding the role of the neurovascular unit as both a biomarker and target for disease interventions, it is vital to appreciate how the function of different components of this unit change along the vascular tree. The cells of the neurovascular unit together perform an array of vital functions, protecting the brain from circulating toxins and infection, while providing nutrients and clearing away waste products. To do so, the brain’s microvasculature dilates to direct energy substrates to active neurons, regulates access to circulating immune cells, and promotes angiogenesis in response to decreased blood supply, as well as pulsating to help clear waste products and maintain the oxygen supply. Different parts of the cerebrovascular tree contribute differently to various aspects of these functions, and previously, it has been assumed that there are discrete types of vessel along the vascular network that mediate different functions. Another option, however, is that the multiple transitions in function that occur across the vascular network do so at many locations, such that vascular function changes gradually, rather than in sharp steps between clearly distinct vessel types. Here, by reference to new data as well as by reviewing historical and recent literature, we argue that this latter scenario is likely the case and that vascular function gradually changes across the network without clear transition points between arteriole, precapillary arteriole and capillary. This is because classically localized functions are in fact performed by wide swathes of the vasculature, and different functional markers start and stop being expressed at different points along the vascular tree. Furthermore, vascular branch points show alterations in their mural cell morphology that suggest functional specializations irrespective of their position within the network. Together this work emphasizes the need for studies to consider where transitions of different functions occur, and the importance of defining these locations, in order to better understand the vascular network and how to target it to treat disease

Suppression of experimental arthritis by gene transfer of interleukin 1 receptor antagonist cDNA.

Restoration of the impaired balance between pro- and antiinflammatory cytokines should provide effective treatment of rheumatoid arthritis. Gene therapy has been proposed as an approach for delivery of therapeutic proteins to arthritic joints. Here, we examined the efficacy of antiinflammatory gene therapy in bacterial cell wall-induced arthritis in rats. Human secreted interleukin 1 receptor antagonist (sIL-1ra) was expressed in joints of rats with recurrent bacterial cell wall-induced arthritis by using ex vivo gene transfer. To achieve this, primary synoviocytes were transduced in culture with a retroviral vector carrying the sIL-1ra cDNA. Transduced cells were engrafted in ankle joints of animals prior to reactivation of arthritis. Animals in control groups were engrafted with synoviocytes transduced with lacZ and neo marker genes. Cells continued to express transferred genes for at least 9 days after engraftment. We found that gene transfer of sIL-1ra significantly suppressed the severity of recurrence of arthritis, as assessed by measuring joint swelling and by the gross-observation score, and attenuated but did not abolish erosion of cartilage and bone. The effect of intraarticularly expressed sIL-1ra was essentially local, as there was no significant difference in severity of recurrence between unengrafted contralateral joints in control and experimental groups. We estimate that locally expressed sIL-1ra was about four orders of magnitude more therapeutically efficient than systemically administered recombinant sIL-1ra protein. These findings provide experimental evidence for the feasibility of antiinflammatory gene therapy for arthritis

Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics

Timm W, Scherbart A, Boecker S, Kohlbacher O, Nattkemper TW. Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics. BMC Bioinformatics. 2008;9(1):443.Background: Mass spectrometry is a key technique in proteomics and can be used to analyze complex samples quickly. One key problem with the mass spectrometric analysis of peptides and proteins, however, is the fact that absolute quantification is severely hampered by the unclear relationship between the observed peak intensity and the peptide concentration in the sample. While there are numerous approaches to circumvent this problem experimentally (e. g. labeling techniques), reliable prediction of the peak intensities from peptide sequences could provide a peptide-specific correction factor. Thus, it would be a valuable tool towards label-free absolute quantification. Results: In this work we present machine learning techniques for peak intensity prediction for MALDI mass spectra. Features encoding the peptides' physico-chemical properties as well as string-based features were extracted. A feature subset was obtained from multiple forward feature selections on the extracted features. Based on these features, two advanced machine learning methods (support vector regression and local linear maps) are shown to yield good results for this problem (Pearson correlation of 0.68 in a ten-fold cross validation). Conclusion: The techniques presented here are a useful first step going beyond the binary prediction of proteotypic peptides towards a more quantitative prediction of peak intensities. These predictions in turn will turn out to be beneficial for mass spectrometry-based quantitative proteomics

Gene expression profiles in rat mesenteric lymph nodes upon supplementation with Conjugated Linoleic Acid during gestation and suckling

Background Diet plays a role on the development of the immune system, and polyunsaturated fatty acids can modulate the expression of a variety of genes. Human milk contains conjugated linoleic acid (CLA), a fatty acid that seems to contribute to immune development. Indeed, recent studies carried out in our group in suckling animals have shown that the immune function is enhanced after feeding them with an 80:20 isomer mix composed of c9,t11 and t10,c12 CLA. However, little work has been done on the effects of CLA on gene expression, and even less regarding immune system development in early life. Results The expression profile of mesenteric lymph nodes from animals supplemented with CLA during gestation and suckling through dam's milk (Group A) or by oral gavage (Group B), supplemented just during suckling (Group C) and control animals (Group D) was determined with the aid of the specific GeneChip® Rat Genome 230 2.0 (Affymettrix). Bioinformatics analyses were performed using the GeneSpring GX software package v10.0.2 and lead to the identification of 89 genes differentially expressed in all three dietary approaches. Generation of a biological association network evidenced several genes, such as connective tissue growth factor (Ctgf), tissue inhibitor of metalloproteinase 1 (Timp1), galanin (Gal), synaptotagmin 1 (Syt1), growth factor receptor bound protein 2 (Grb2), actin gamma 2 (Actg2) and smooth muscle alpha actin (Acta2), as highly interconnected nodes of the resulting network. Gene underexpression was confirmed by Real-Time RT-PCR. Conclusions Ctgf, Timp1, Gal and Syt1, among others, are genes modulated by CLA supplementation that may have a role on mucosal immune responses in early life

Gene expression profiles in rat mesenteric lymph nodes upon supplementation with Conjugated Linoleic Acid during gestation and suckling

Background Diet plays a role on the development of the immune system, and polyunsaturated fatty acids can modulate the expression of a variety of genes. Human milk contains conjugated linoleic acid (CLA), a fatty acid that seems to contribute to immune development. Indeed, recent studies carried out in our group in suckling animals have shown that the immune function is enhanced after feeding them with an 80:20 isomer mix composed of c9,t11 and t10,c12 CLA. However, little work has been done on the effects of CLA on gene expression, and even less regarding immune system development in early life. Results The expression profile of mesenteric lymph nodes from animals supplemented with CLA during gestation and suckling through dam's milk (Group A) or by oral gavage (Group B), supplemented just during suckling (Group C) and control animals (Group D) was determined with the aid of the specific GeneChip® Rat Genome 230 2.0 (Affymettrix). Bioinformatics analyses were performed using the GeneSpring GX software package v10.0.2 and lead to the identification of 89 genes differentially expressed in all three dietary approaches. Generation of a biological association network evidenced several genes, such as connective tissue growth factor (Ctgf), tissue inhibitor of metalloproteinase 1 (Timp1), galanin (Gal), synaptotagmin 1 (Syt1), growth factor receptor bound protein 2 (Grb2), actin gamma 2 (Actg2) and smooth muscle alpha actin (Acta2), as highly interconnected nodes of the resulting network. Gene underexpression was confirmed by Real-Time RT-PCR. Conclusions Ctgf, Timp1, Gal and Syt1, among others, are genes modulated by CLA supplementation that may have a role on mucosal immune responses in early life

LC-MSsim – a simulation software for liquid chromatography mass spectrometry data

<p>Abstract</p> <p>Background</p> <p>Mass Spectrometry coupled to Liquid Chromatography (LC-MS) is commonly used to analyze the protein content of biological samples in large scale studies. The data resulting from an LC-MS experiment is huge, highly complex and noisy. Accordingly, it has sparked new developments in Bioinformatics, especially in the fields of algorithm development, statistics and software engineering. In a quantitative label-free mass spectrometry experiment, crucial steps are the detection of peptide features in the mass spectra and the alignment of samples by correcting for shifts in retention time. At the moment, it is difficult to compare the plethora of algorithms for these tasks. So far, curated benchmark data exists only for peptide identification algorithms but no data that represents a ground truth for the evaluation of feature detection, alignment and filtering algorithms.</p> <p>Results</p> <p>We present <it>LC-MSsim</it>, a simulation software for LC-ESI-MS experiments. It simulates ESI spectra on the MS level. It reads a list of proteins from a FASTA file and digests the protein mixture using a user-defined enzyme. The software creates an LC-MS data set using a predictor for the retention time of the peptides and a model for peak shapes and elution profiles of the mass spectral peaks. Our software also offers the possibility to add contaminants, to change the background noise level and includes a model for the detectability of peptides in mass spectra. After the simulation, <it>LC-MSsim </it>writes the simulated data to mzData, a public XML format. The software also stores the positions (monoisotopic m/z and retention time) and ion counts of the simulated ions in separate files.</p> <p>Conclusion</p> <p><it>LC-MSsim </it>generates simulated LC-MS data sets and incorporates models for peak shapes and contaminations. Algorithm developers can match the results of feature detection and alignment algorithms against the simulated ion lists and meaningful error rates can be computed. We anticipate that <it>LC-MSsim </it>will be useful to the wider community to perform benchmark studies and comparisons between computational tools.</p