CONLAN-a formal construction method for hardware description languages: language derivation

International audienceA CONLAN document has significance only if it is read by a person or machine. that reader (environment) is required to use available facilities to respond to and interact with the document. It must provide the type checking mechanism. It must record the names of defined and declared items and provide the data base they require. It must record signal values. From such records, it can determine facts of importance to continued document evaluation. `System interfaces' are prescribed environment responses, not formally defined via CONLAN syntax

Prospects for a Statistical Theory of LC/TOFMS Data

The critical importance of employing sound statistical arguments when seeking to draw inferences from inexact measurements is well-established throughout the sciences. Yet fundamental statistical methods such as hypothesis testing can currently be applied to only a small subset of the data analytical problems encountered in LC/MS experiments. The means of inference that are more generally employed are based on a variety of heuristic techniques and a largely qualitative understanding of their behavior. In this article, we attempt to move towards a more formalized approach to the analysis of LC/TOFMS data by establishing some of the core concepts required for a detailed mathematical description of the data. Using arguments that are based on the fundamental workings of the instrument, we derive and validate a probability distribution that approximates that of the empirically obtained data and on the basis of which formal statistical tests can be constructed. Unlike many existing statistical models for MS data, the one presented here aims for rigor rather than generality. Consequently, the model is closely tailored to a particular type of TOF mass spectrometer although the general approach carries over to other instrument designs. Looking ahead, we argue that further improvements in our ability to characterize the data mathematically could enable us to address a wide range of data analytical problems in a statistically rigorous manner

Tandem mass spectrometry data quality assessment by self-convolution

<p>Abstract</p> <p>Background</p> <p>Many algorithms have been developed for deciphering the tandem mass spectrometry (MS) data sets. They can be essentially clustered into two classes. The first performs searches on theoretical mass spectrum database, while the second based itself on <it>de novo </it>sequencing from raw mass spectrometry data. It was noted that the quality of mass spectra affects significantly the protein identification processes in both instances. This prompted the authors to explore ways to measure the quality of MS data sets before subjecting them to the protein identification algorithms, thus allowing for more meaningful searches and increased confidence level of proteins identified.</p> <p>Results</p> <p>The proposed method measures the qualities of MS data sets based on the symmetric property of b- and y-ion peaks present in a MS spectrum. Self-convolution on MS data and its time-reversal copy was employed. Due to the symmetric nature of b-ions and y-ions peaks, the self-convolution result of a good spectrum would produce a highest mid point intensity peak. To reduce processing time, self-convolution was achieved using Fast Fourier Transform and its inverse transform, followed by the removal of the "DC" (Direct Current) component and the normalisation of the data set. The quality score was defined as the ratio of the intensity at the mid point to the remaining peaks of the convolution result. The method was validated using both theoretical mass spectra, with various permutations, and several real MS data sets. The results were encouraging, revealing a high percentage of positive prediction rates for spectra with good quality scores.</p> <p>Conclusion</p> <p>We have demonstrated in this work a method for determining the quality of tandem MS data set. By pre-determining the quality of tandem MS data before subjecting them to protein identification algorithms, spurious protein predictions due to poor tandem MS data are avoided, giving scientists greater confidence in the predicted results. We conclude that the algorithm performs well and could potentially be used as a pre-processing for all mass spectrometry based protein identification tools.</p

Islet-Like Cell Aggregates Generated from Human Adipose Tissue Derived Stem Cells Ameliorate Experimental Diabetes in Mice

BACKGROUND: Type 1 Diabetes Mellitus is caused by auto immune destruction of insulin producing beta cells in the pancreas. Currently available treatments include transplantation of isolated islets from donor pancreas to the patient. However, this method is limited by inadequate means of immuno-suppression to prevent islet rejection and importantly, limited supply of islets for transplantation. Autologous adult stem cells are now considered for cell replacement therapy in diabetes as it has the potential to generate neo-islets which are genetically part of the treated individual. Adopting methods of islet encapsulation in immuno-isolatory devices would eliminate the need for immuno-suppressants. METHODOLOGY/PRINCIPAL FINDINGS: In the present study we explore the potential of human adipose tissue derived adult stem cells (h-ASCs) to differentiate into functional islet like cell aggregates (ICAs). Our stage specific differentiation protocol permit the conversion of mesodermic h-ASCs to definitive endoderm (Hnf3β, TCF2 and Sox17) and to PDX1, Ngn3, NeuroD, Pax4 positive pancreatic endoderm which further matures in vitro to secrete insulin. These ICAs are shown to produce human C-peptide in a glucose dependent manner exhibiting in-vitro functionality. Transplantation of mature ICAs, packed in immuno-isolatory biocompatible capsules to STZ induced diabetic mice restored near normoglycemia within 3-4 weeks. The detection of human C-peptide, 1155±165 pM in blood serum of experimental mice demonstrate the efficacy of our differentiation approach. CONCLUSIONS: h-ASC is an ideal population of personal stem cells for cell replacement therapy, given that they are abundant, easily available and autologous in origin. Our findings present evidence that h-ASCs could be induced to differentiate into physiologically competent functional islet like cell aggregates, which may provide as a source of alternative islets for cell replacement therapy in type 1 diabetes

Sox9-Haploinsufficiency Causes Glucose Intolerance in Mice

The HMG box transcription factor Sox9 plays a critical role in progenitor cell expansion during pancreas organogenesis and is required for proper endocrine cell development in the embryo. Based on in vitro studies it has been suggested that Sox9 controls expression of a network of important developmental regulators, including Tcf2/MODY5, Hnf6, and Foxa2, in pancreatic progenitor cells. Here, we sought to: 1) determine whether Sox9 regulates this transcriptional network in vivo and 2) investigate whether reduced Sox9 gene dosage leads to impaired glucose homeostasis in adult mice. Employing two genetic models of temporally-controlled Sox9 inactivation in pancreatic progenitor cells, we demonstrate that contrary to in vitro findings, Sox9 is not required for Tcf2, Hnf6, or Foxa2 expression in vivo. Moreover, our analysis revealed a novel role for Sox9 in maintaining the expression of Pdx1/MODY4, which is an important transcriptional regulator of beta-cell development. We further show that reduced beta-cell mass in Sox9-haploinsufficient mice leads to glucose intolerance during adulthood. Sox9-haploinsufficient mice displayed 50% reduced beta-cell mass at birth, which recovered partially via a compensatory increase in beta-cell proliferation early postnatally. Endocrine islets from mice with reduced Sox9 gene dosage exhibited normal glucose stimulated insulin secretion. Our findings show Sox9 plays an important role in endocrine development by maintaining Ngn3 and Pdx1 expression. Glucose intolerance in Sox9-haploinsufficient mice suggests that mutations in Sox9 could play a role in diabetes in humans

Matrix-assisted laser desorption ionization hydrogen/deuterium exchange studies to probe peptide conformational changes

AbstractHydrogen/deuterium (H/D) exchange chemistry monitored by matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry is used to study solution phase conformational changes of bradykinin, α-melanocyte stimulating hormone, and melittin as water is added to methanol-d4, acetonitrile, and isopropanol-d8 solutions. The results are interpreted in terms of a preference for the peptides to acquire more compact conformations in organic solvents as compared to the random conformations. Our interpretation is supported by circular dichroism spectra of the peptides in the same solvent systems and by previously published structural data for the peptides. These results demonstrate the utility of MALDI-TOF as a method to monitor the H/D exchange chemistry of peptides and investigations of solution-phase conformations of biomolecules