Diabetic Peripheral Neuropathy

Diabetic autonomic neuropathies (DAN) are clinical syndromes resulting from impairments of the autonomic nervous system in patients with diabetes mellitus. Since the autonomic nervous system innervates most body organs, any or all of those organs may be affected by DAN. A high index of suspicion is the best diagnostic tool. Proper management, with patient and family education in its center, improves the quality of life of persons with DAN. Undiagnosed and ignored, DAN could cause severe disability and even death.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68591/2/10.1177_014572178701300208.pd

Search algorithms as a framework for the optimization of drug combinations

Combination therapies are often needed for effective clinical outcomes in the management of complex diseases, but presently they are generally based on empirical clinical experience. Here we suggest a novel application of search algorithms, originally developed for digital communication, modified to optimize combinations of therapeutic interventions. In biological experiments measuring the restoration of the decline with age in heart function and exercise capacity in Drosophila melanogaster, we found that search algorithms correctly identified optimal combinations of four drugs with only one third of the tests performed in a fully factorial search. In experiments identifying combinations of three doses of up to six drugs for selective killing of human cancer cells, search algorithms resulted in a highly significant enrichment of selective combinations compared with random searches. In simulations using a network model of cell death, we found that the search algorithms identified the optimal combinations of 6-9 interventions in 80-90% of tests, compared with 15-30% for an equivalent random search. These findings suggest that modified search algorithms from information theory have the potential to enhance the discovery of novel therapeutic drug combinations. This report also helps to frame a biomedical problem that will benefit from an interdisciplinary effort and suggests a general strategy for its solution.Comment: 36 pages, 10 figures, revised versio

MultiMetEval: comparative and multi-objective analysis of genome-scale metabolic models

Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEv​al/downloads

Wide-Scale Analysis of Human Functional Transcription Factor Binding Reveals a Strong Bias towards the Transcription Start Site

We introduce a novel method to screen the promoters of a set of genes with shared biological function, against a precompiled library of motifs, and find those motifs which are statistically over-represented in the gene set. The gene sets were obtained from the functional Gene Ontology (GO) classification; for each set and motif we optimized the sequence similarity score threshold, independently for every location window (measured with respect to the TSS), taking into account the location dependent nucleotide heterogeneity along the promoters of the target genes. We performed a high throughput analysis, searching the promoters (from 200bp downstream to 1000bp upstream the TSS), of more than 8000 human and 23,000 mouse genes, for 134 functional Gene Ontology classes and for 412 known DNA motifs. When combined with binding site and location conservation between human and mouse, the method identifies with high probability functional binding sites that regulate groups of biologically related genes. We found many location-sensitive functional binding events and showed that they clustered close to the TSS. Our method and findings were put to several experimental tests. By allowing a "flexible" threshold and combining our functional class and location specific search method with conservation between human and mouse, we are able to identify reliably functional TF binding sites. This is an essential step towards constructing regulatory networks and elucidating the design principles that govern transcriptional regulation of expression. The promoter region proximal to the TSS appears to be of central importance for regulation of transcription in human and mouse, just as it is in bacteria and yeast.Comment: 31 pages, including Supplementary Information and figure

MHC Class I Endosomal and Lysosomal Trafficking Coincides with Exogenous Antigen Loading in Dendritic Cells

BACKGROUND: Cross-presentation by dendritic cells (DCs) is a crucial prerequisite for effective priming of cytotoxic T-cell responses against bacterial, viral and tumor antigens; however, this antigen presentation pathway remains poorly defined. METHODOLOGY/PRINCIPAL FINDINGS: In order to develop a comprehensive understanding of this process, we tested the hypothesis that the internalization of MHC class I molecules (MHC-I) from the cell surface is directly involved in cross-presentation pathway and the loading of antigenic peptides. Here we provide the first examination of the internalization of MHC-I in DCs and we demonstrate that the cytoplasmic domain of MHC-I appears to act as an addressin domain to route MHC-I to both endosomal and lysosomal compartments of DCs, where it is demonstrated that loading of peptides derived from exogenously-derived proteins occurs. Furthermore, by chasing MHC-I from the cell surface of normal and transgenic DCs expressing mutant forms of MHC-I, we observe that a tyrosine-based endocytic trafficking motif is required for the constitutive internalization of MHC-I molecules from the cell surface into early endosomes and subsequently deep into lysosomal peptide-loading compartments. Finally, our data support the concept that multiple pathways of peptide loading of cross-presented antigens may exist depending on the chemical nature and size of the antigen requiring processing. CONCLUSIONS/SIGNIFICANCE: We conclude that DCs have 'hijacked' and adapted a common vacuolar/endocytic intracellular trafficking pathway to facilitate MHC I access to the endosomal and lysosomal compartments where antigen processing and loading and antigen cross-presentation takes place

BCR and its mutants, the reciprocal t(9;22)-associated ABL/BCR fusion proteins, differentially regulate the cytoskeleton and cell motility

BACKGROUND: The reciprocal (9;22) translocation fuses the bcr (breakpoint cluster region) gene on chromosome 22 to the abl (Abelson-leukemia-virus) gene on chromosome 9. Depending on the breakpoint on chromosome 22 (the Philadelphia chromosome – Ph+) the derivative 9+ encodes either the p40((ABL/BCR) )fusion transcript, detectable in about 65% patients suffering from chronic myeloid leukemia, or the p96((ABL/BCR) )fusion transcript, detectable in 100% of Ph+ acute lymphatic leukemia patients. The ABL/BCRs are N-terminally truncated BCR mutants. The fact that BCR contains Rho-GEF and Rac-GAP functions strongly suggest an important role in cytoskeleton modeling by regulating the activity of Rho-like GTPases, such as Rho, Rac and cdc42. We, therefore, compared the function of the ABL/BCR proteins with that of wild-type BCR. METHODS: We investigated the effects of BCR and ABL/BCRs i.) on the activation status of Rho, Rac and cdc42 in GTPase-activation assays; ii.) on the actin cytoskeleton by direct immunofluorescence; and iii) on cell motility by studying migration into a three-dimensional stroma spheroid model, adhesion on an endothelial cell layer under shear stress in a flow chamber model, and chemotaxis and endothelial transmigration in a transwell model with an SDF-1α gradient. RESULTS: Here we show that both ABL/BCRs lost fundamental functional features of BCR regarding the regulation of small Rho-like GTPases with negative consequences on cell motility, in particular on the capacity to adhere to endothelial cells. CONCLUSION: Our data presented here describe for the first time an analysis of the biological function of the reciprocal t(9;22) ABL/BCR fusion proteins in comparison to their physiological counterpart BCR

Disruption of arterial perivascular drainage of amyloid-β from the brains of mice expressing the human APOE ε4 allele

Failure of elimination of amyloid-β (Aβ) from the brain and vasculature appears to be a key factor in the etiology of sporadic Alzheimer’s disease (AD) and cerebral amyloid angiopathy (CAA). In addition to age, possession of an apolipoprotein E (APOE) ε4 allele is a strong risk factor for the development of sporadic AD. The present study tested the hypothesis that possession of the APOE ε4 allele is associated with disruption of perivascular drainage of Aβ from the brain and with changes in cerebrovascular basement membrane protein levels. Targeted replacement (TR) mice expressing the human APOE3 (TRE3) or APOE4 (TRE4) genes and wildtype mice received intracerebral injections of human Aβ40. Aβ40 aggregated in peri-arterial drainage pathways in TRE4 mice, but not in TRE3 or wildtype mice. The number of Aβ deposits was significantly higher in the hippocampi of TRE4 mice than in the TRE3 mice, at both 3- and 16-months of age, suggesting that clearance of Aβ was disrupted in the brains of TRE4 mice. Immunocytochemical and Western blot analysis of vascular basement membrane proteins demonstrated significantly raised levels of collagen IV in 3-month-old TRE4 mice compared with TRE3 and wild type mice. In 16-month-old mice, collagen IV and laminin levels were unchanged between wild type and TRE3 mice, but were lower in TRE4 mice. The results of this study suggest that APOE4 may increase the risk for AD through disruption and impedance of perivascular drainage of soluble Aβ from the brain. This effect may be mediated, in part, by changes in age-related expression of basement membrane proteins in the cerebral vasculature

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

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration