In vivo manganese-enhanced MRI and diffusion tensor imaging of developing and impaired visual brains

This study explored the feasibility of high-resolution Mn-enhanced MRI (MEMRI) and diffusion tensor imaging (DTI) for in vivo assessments of the development and reorganization of retinal and visual callosal pathways in normal neonatal rodent brains and after early postnatal visual impairments. Using MEMRI, intravitreal Mn 2+ injection into one eye resulted in maximal T1-weighted hyperintensity in neonatal contralateral superior colliculus (SC) 8 hours after administration, whereas in adult contralateral SC signal increase continued at 1 day post-injection. Notably, mild but significant Mn 2+ enhancement was observed in the ipsilateral SC in normal neonatal rats, and in adult rats after neonatal monocular enucleation (ME) but not in normal adult rats. Upon intracortical Mn 2+ injection to the visual cortex, neonatal binocularly-enucleated (BE) rats showed an enhancement of a larger projection area, via the splenium of corpus callosum to the V1/V2 transition zone of the contralateral hemisphere in comparison to normal rats. For DTI, the retinal pathways projected from the enucleated eyes possessed lower fractional anisotropy (FA) 6 weeks after BE and ME. Interestingly, in the optic nerve projected from the remaining eye in ME rats a significantly higher FA was observed compared to normal rats. The results of this study are potentially important for understanding the axonal transport, microstructural reorganization and functional activities in the living visual brain during early postnatal development and plasticity in a global and longitudinal setting. © 2011 IEEE.published_or_final_versionThe 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2011), Boston, MA., 30 August-3 September 2011. In IEEE Engineering in Medicine and Biology Society Conference Proceedings, 2011, p. 7005-700

A Multi-Label Predictor for Identifying the Subcellular Locations of Singleplex and Multiplex Eukaryotic Proteins

Subcellular locations of proteins are important functional attributes. An effective and efficient subcellular localization predictor is necessary for rapidly and reliably annotating subcellular locations of proteins. Most of existing subcellular localization methods are only used to deal with single-location proteins. Actually, proteins may simultaneously exist at, or move between, two or more different subcellular locations. To better reflect characteristics of multiplex proteins, it is highly desired to develop new methods for dealing with them. In this paper, a new predictor, called Euk-ECC-mPLoc, by introducing a powerful multi-label learning approach which exploits correlations between subcellular locations and hybridizing gene ontology with dipeptide composition information, has been developed that can be used to deal with systems containing both singleplex and multiplex eukaryotic proteins. It can be utilized to identify eukaryotic proteins among the following 22 locations: (1) acrosome, (2) cell membrane, (3) cell wall, (4) centrosome, (5) chloroplast, (6) cyanelle, (7) cytoplasm, (8) cytoskeleton, (9) endoplasmic reticulum, (10) endosome, (11) extracellular, (12) Golgi apparatus, (13) hydrogenosome, (14) lysosome, (15) melanosome, (16) microsome, (17) mitochondrion, (18) nucleus, (19) peroxisome, (20) spindle pole body, (21) synapse, and (22) vacuole. Experimental results on a stringent benchmark dataset of eukaryotic proteins by jackknife cross validation test show that the average success rate and overall success rate obtained by Euk-ECC-mPLoc were 69.70% and 81.54%, respectively, indicating that our approach is quite promising. Particularly, the success rates achieved by Euk-ECC-mPLoc for small subsets were remarkably improved, indicating that it holds a high potential for simulating the development of the area. As a user-friendly web-server, Euk-ECC-mPLoc is freely accessible to the public at the website http://levis.tongji.edu.cn:8080/bioinfo/Euk-ECC-mPLoc/. We believe that Euk-ECC-mPLoc may become a useful high-throughput tool, or at least play a complementary role to the existing predictors in identifying subcellular locations of eukaryotic proteins

An efficient algorithm for modelling and dynamic prediction of network traffic

Network node degradation is an important problem in internet of things given the ubiquitous high number of personal computers, tablets, phones and other equipments present nowadays. In order to verify the network traffic degradation as one or multiple nodes in a network fail, this paper proposes one algorithm based on product form results (PRF) for fractionally auto regressive integrated moving average (FARIMA) model, namely PFRF. In this algorithm, the prediction method is established by FARIMA model, through equations for queuing state and average queue length in steady state derived from queuing theory. Experimental simulations were conducted to investigate the relationships between average queue length and service rate. Results demonstrated that, not only it has good adaptability, but has also achieved promising magnitude of 9.87 as standard deviation which shows its high prediction accuracy, given the low-magnitude difference between original value and the algorithm

Identification of Potent EGFR Inhibitors from TCM Database@Taiwan

Overexpression of epidermal growth factor receptor (EGFR) has been associated with cancer. Targeted inhibition of the EGFR pathway has been shown to limit proliferation of cancerous cells. Hence, we employed Traditional Chinese Medicine Database (TCM Database@Taiwan) (http://tcm.cmu.edu.tw) to identify potential EGFR inhibitor. Multiple Linear Regression (MLR), Support Vector Machine (SVM), Comparative Molecular Field Analysis (CoMFA), and Comparative Molecular Similarities Indices Analysis (CoMSIA) models were generated using a training set of EGFR ligands of known inhibitory activities. The top four TCM candidates based on DockScore were 2-O-caffeoyl tartaric acid, Emitine, Rosmaricine, and 2-O-feruloyl tartaric acid, and all had higher binding affinities than the control Iressa®. The TCM candidates had interactions with Asp855, Lys716, and Lys728, all which are residues of the protein kinase binding site. Validated MLR (r² = 0.7858) and SVM (r² = 0.8754) models predicted good bioactivity for the TCM candidates. In addition, the TCM candidates contoured well to the 3D-Quantitative Structure-Activity Relationship (3D-QSAR) map derived from the CoMFA (q² = 0.721, r² = 0.986) and CoMSIA (q² = 0.662, r² = 0.988) models. The steric field, hydrophobic field, and H-bond of the 3D-QSAR map were well matched by each TCM candidate. Molecular docking indicated that all TCM candidates formed H-bonds within the EGFR protein kinase domain. Based on the different structures, H-bonds were formed at either Asp855 or Lys716/Lys728. The compounds remained stable throughout molecular dynamics (MD) simulation. Based on the results of this study, 2-O-caffeoyl tartaric acid, Emitine, Rosmaricine, and 2-O-feruloyl tartaric acid are suggested to be potential EGFR inhibitors.National Science Council of Taiwan (NSC 99-2221-E-039-013-)Committee on Chinese Medicine and Pharmacy (CCMP100-RD-030)China Medical University (CMU98-TCM)China Medical University (CMU99-TCM)China Medical University (CMU99-S-02)China Medical University (CMU99-ASIA-25)China Medical University (CMU99-ASIA-26)China Medical University (CMU99-ASIA-27)China Medical University (CMU99-ASIA-28)Asia UniversityTaiwan Department of Health. Clinical Trial and Research Center of Excellence (DOH100-TD-B-111-004)Taiwan Department of Health. Cancer Research Center of Excellence (DOH100-TD-C-111-005

Predicting multiplex subcellular localization of proteins using protein-protein interaction network: a comparative study

<p>Abstract</p> <p>Background</p> <p>Proteins that interact in vivo tend to reside within the same or "adjacent" subcellular compartments. This observation provides opportunities to reveal protein subcellular localization in the context of the protein-protein interaction (PPI) network. However, so far, only a few efforts based on heuristic rules have been made in this regard.</p> <p>Results</p> <p>We systematically and quantitatively validate the hypothesis that proteins physically interacting with each other probably share at least one common subcellular localization. With the result, for the first time, four graph-based semi-supervised learning algorithms, Majority, <it>χ</it>²-score, GenMultiCut and FunFlow originally proposed for protein function prediction, are introduced to assign "multiplex localization" to proteins. We analyze these approaches by performing a large-scale cross validation on a <it>Saccharomyces cerevisiae </it>proteome compiled from BioGRID and comparing their predictions for 22 protein subcellular localizations. Furthermore, we build an ensemble classifier to associate 529 unlabeled and 137 ambiguously-annotated proteins with subcellular localizations, most of which have been verified in the previous experimental studies.</p> <p>Conclusions</p> <p>Physical interaction of proteins has actually provided an essential clue for their co-localization. Compared to the local approaches, the global algorithms consistently achieve a superior performance.</p

Do oral aluminium phosphate binders cause accumulation of aluminium to toxic levels?

<p>Abstract</p> <p>Background</p> <p>Aluminium (Al) toxicity was frequent in the 1980s in patients ingesting Al containing phosphate binders (Alucaps) whilst having HD using water potentially contaminated with Al. The aim of this study was to determine the risk of Al toxicity in HD patients receiving Alucaps but never exposed to contaminated dialysate water.</p> <p>Methods</p> <p>HD patients only treated with Reverse Osmosis(RO) treated dialysis water with either current or past exposure to Alucaps were given standardised DFO tests. Post-DFO serum Al level > 3.0 μmol/L was defined to indicate toxic loads based on previous bone biopsy studies.</p> <p>Results</p> <p>39 patients (34 anuric) were studied. Mean dose of Alucap was 3.5 capsules/d over 23.0 months. Pre-DFO Al levels were > 1.0 μmol/L in only 2 patients and none were > 3.0 μmol/L. No patients had a post DFO Al levels > 3.0 μmol/L. There were no correlations between the serum Al concentrations (pre-, post- or the incremental rise after DFO administration) and the total amount of Al ingested.</p> <p>No patients had unexplained EPO resistance or biochemical evidence of adynamic bone.</p> <p>Conclusions</p> <p>Although this is a small study, oral aluminium exposure was considerable. Yet no patients undergoing HD with RO treated water had evidence of Al toxicity despite doses equivalent to 3.5 capsules of Alucap for 2 years. The relationship between the DFO-Al results and the total amount of Al ingested was weak (R²= 0.07) and not statistically significant. In an era of financial prudence, and in view of the recognised risk of excess calcium loading in dialysis patients, perhaps we should re-evaluate the risk of using Al-based phosphate binders in HD patients who remain uric.</p

A compendium and functional characterization of mammalian genes involved in adaptation to Arctic or Antarctic environments

Many mammals are well adapted to surviving in extremely cold environments. These species have likely accumulated genetic changes that help them efficiently cope with low temperatures. It is not known whether the same genes related to cold adaptation in one species would be under selection in another species. The aims of this study therefore were: to create a compendium of mammalian genes related to adaptations to a low temperature environment; to identify genes related to cold tolerance that have been subjected to independent positive selection in several species; to determine promising candidate genes/pathways/organs for further empirical research on cold adaptation in mammals

Longitudinal Assessments of Normal and Perilesional Tissues in Focal Brain Ischemia and Partial Optic Nerve Injury with Manganese-enhanced MRI

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