Clinical-pathological study on β-APP, IL-1β, GFAP, NFL, Spectrin II, 8OHdG, TUNEL, miR-21, miR-16, miR-92 expressions to verify DAI-diagnosis, grade and prognosis

Traumatic brain injury (TBI) is one of the most important death and disability cause, involving substantial costs, also in economic terms, when considering the young age of the involved subject. Aim of this paper is to report a series of patients treated at our institutions, to verify neurological results at six months or survival; in fatal cases we searched for βAPP, GFAP, IL-1β, NFL, Spectrin II, TUNEL and miR-21, miR-16, and miR-92 expressions in brain samples, to verify DAI diagnosis and grade as strong predictor of survival and inflammatory response. Concentrations of 8OHdG as measurement of oxidative stress was performed. Immunoreaction of β-APP, IL-1β, GFAP, NFL, Spectrin II and 8OHdG were significantly increased in the TBI group with respect to control group subjects. Cell apoptosis, measured by TUNEL assay, were significantly higher in the study group than control cases. Results indicated that miR-21, miR-92 and miR-16 have a high predictive power in discriminating trauma brain cases from controls and could represent promising biomarkers as strong predictor of survival, and for the diagnosis of postmortem traumatic brain injury

A Simple and Sensitive Method for Measuring Tumor-Specific T Cell Cytotoxicity

A simple and sensitive method to quantitatively measure the cytolytic effect of tumor-specific T killer cells is highly desirable for basic and clinical studies. Chromium (51Cr) release assay has been the “gold standard” for quantifying cytolytic activities of cytotoxic T lymphocytes (CTLs) against target cells and this method is still being used in many laboratories. However, a major drawback of this method is the use of radioactive materials, which is inconvenient to handle because of environmental safety concerns and expensive due to the short half-life of the isotope. Consequently, several nonradioactive methods have been reported recently. Here we report a new method that we recently developed for quantifying antigen-specific cytolytic activity of CTLs. This method fully exploits the high sensitivity and the relative simplicity of luciferase quantitative assay. We initially expected the released luciferase in the supernatant to be the adequate source for monitoring cell death. However, to our total surprise, incubation of these killer T cells with the tumor cell targets did not result in significant release of luciferase in the culture medium. Instead, we found that the remaining luciferase inside the cells could accurately reflect the overall cell viability

Regulation of Classical Cadherin Membrane Expression and F-Actin Assembly by Alpha-Catenins, during Xenopus Embryogenesis

Alpha (α)-E-catenin is a component of the cadherin complex, and has long been thought to provide a link between cell surface cadherins and the actin skeleton. More recently, it has also been implicated in mechano-sensing, and in the control of tissue size. Here we use the early Xenopus embryos to explore functional differences between two α-catenin family members, α-E- and α-N-catenin, and their interactions with the different classical cadherins that appear as tissues of the embryo become segregated from each other. We show that they play both cadherin-specific and context-specific roles in the emerging tissues of the embryo. α-E-catenin interacts with both C- and E-cadherin. It is specifically required for junctional localization of C-cadherin, but not of E-cadherin or N-cadherin at the neurula stage. α-N-cadherin interacts only with, and is specifically required for junctional localization of, N-cadherin. In addition, α -E-catenin is essential for normal tissue size control in the non-neural ectoderm, but not in the neural ectoderm or the blastula. We also show context specificity in cadherin/ α-catenin interactions. E-cadherin requires α-E-catenin for junctional localization in some tissues, but not in others, during early development. These specific functional cadherin/alpha-catenin interactions may explain the basis of cadherin specificity of actin assembly and morphogenetic movements seen previously in the neural and non-neural ectoderm

Small Molecule, Non-Peptide p75NTR Ligands Inhibit Aβ-Induced Neurodegeneration and Synaptic Impairment

The p75 neurotrophin receptor (p75NTR) is expressed by neurons particularly vulnerable in Alzheimer's disease (AD). We tested the hypothesis that non-peptide, small molecule p75NTR ligands found to promote survival signaling might prevent Aβ-induced degeneration and synaptic dysfunction. These ligands inhibited Aβ-induced neuritic dystrophy, death of cultured neurons and Aβ-induced death of pyramidal neurons in hippocampal slice cultures. Moreover, ligands inhibited Aβ-induced activation of molecules involved in AD pathology including calpain/cdk5, GSK3β and c-Jun, and tau phosphorylation, and prevented Aβ-induced inactivation of AKT and CREB. Finally, a p75NTR ligand blocked Aβ-induced hippocampal LTP impairment. These studies support an extensive intersection between p75NTR signaling and Aβ pathogenic mechanisms, and introduce a class of specific small molecule ligands with the unique ability to block multiple fundamental AD-related signaling pathways, reverse synaptic impairment and inhibit Aβ-induced neuronal dystrophy and death

Xylella fastidiosa gene expression analysis by DNA microarrays

Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE). All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others). The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants

An Intelligent Decision Support System for the Detection of Meat Spoilage using Multispectral Images

In food industry, quality and safety are considered important issues worldwide that are directly related to health and social progress. The use of vision technology for quality testing of food production has the obvious advantage of being able to continuously monitor a production using non-destructive methods, thus increasing the quality and minimizing cost. The performance of an intelligent decision support system has been evaluated in monitoring the spoilage of minced beef stored either aerobically or under modified atmosphere packaging, at different storage temperatures (0, 5, 10, and 15 °C) utilising multispectral imaging information. This paper utilises a neuro-fuzzy model which incorporates a clustering pre-processing stage for the definition of fuzzy rules, while its final fuzzy rule base is determined by competitive learning. Initially, meat samples are classified according to their storage conditions, while identification models are then utilised for the prediction of the Total Viable Counts of bacteria. The innovation of the proposed approach is further extended to the identification of the temperature used for storage, utilizing only imaging spectral information. Results indicated that spectral information in combination with the proposed modelling scheme could be considered as an alternative methodology for the accurate evaluation of meat spoilage

Sustained axon regeneration induced by co-deletion of PTEN and SOCS3

A formidable challenge in neural repair in the adult central nervous system (CNS) is the long distances that regenerating axons often need to travel in order to reconnect with their targets. Thus, a sustained capacity for axon regeneration is critical for achieving functional restoration. Although deletion of either phosphatase and tensin homologue (PTEN), a negative regulator of mammalian target of rapamycin (mTOR), or suppressor of cytokine signalling 3 (SOCS3), a negative regulator of Janus kinase/signal transducers and activators of transcription (JAK/STAT) pathway, in adult retinal ganglion cells (RGCs) individually promoted significant optic nerve regeneration, such regrowth tapered off around 2 weeks after the crush injury. Here we show that, remarkably, simultaneous deletion of both PTEN and SOCS3 enables robust and sustained axon regeneration. We further show that PTEN and SOCS3 regulate two independent pathways that act synergistically to promote enhanced axon regeneration. Gene expression analyses suggest that double deletion not only results in the induction of many growth-related genes, but also allows RGCs to maintain the expression of a repertoire of genes at the physiological level after injury. Our results reveal concurrent activation of mTOR and STAT3 pathways as key for sustaining long-distance axon regeneration in adult CNS, a crucial step towards functional recovery

Metrics for GO based protein semantic similarity: a systematic evaluation

<p>Abstract</p> <p>Background</p> <p>Several semantic similarity measures have been applied to gene products annotated with Gene Ontology terms, providing a basis for their functional comparison. However, it is still unclear which is the best approach to semantic similarity in this context, since there is no conclusive evaluation of the various measures. Another issue, is whether electronic annotations should or not be used in semantic similarity calculations.</p> <p>Results</p> <p>We conducted a systematic evaluation of GO-based semantic similarity measures using the relationship with sequence similarity as a means to quantify their performance, and assessed the influence of electronic annotations by testing the measures in the presence and absence of these annotations. We verified that the relationship between semantic and sequence similarity is not linear, but can be well approximated by a rescaled Normal cumulative distribution function. Given that the majority of the semantic similarity measures capture an identical behaviour, but differ in resolution, we used the latter as the main criterion of evaluation.</p> <p>Conclusions</p> <p>This work has provided a basis for the comparison of several semantic similarity measures, and can aid researchers in choosing the most adequate measure for their work. We have found that the hybrid <it>simGIC</it> was the measure with the best overall performance, followed by Resnik's measure using a best-match average combination approach. We have also found that the average and maximum combination approaches are problematic since both are inherently influenced by the number of terms being combined. We suspect that there may be a direct influence of data circularity in the behaviour of the results including electronic annotations, as a result of functional inference from sequence similarity.</p

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO