Role of miRNAs in Human T Cell Leukemia Virus Type 1 Induced T Cell Leukemia: A Literature Review and Bioinformatics Approach

Human T cell leukemia virus type 1 (HTLV-1) was identified as the first pathogenic human retrovirus and is estimated to infect 5 to 10 million individuals worldwide. Unlike other retroviruses, there is no effective therapy to prevent the onset of the most alarming diseases caused by HTLV-1, and the more severe cases manifest as the malignant phenotype of adult T cell leukemia (ATL). MicroRNA (miRNA) dysfunction is a common feature of leukemogenesis, and it is no different in ATL cases. Therefore, we sought to analyze studies that reported deregulated miRNA expression in HTLV-1 infected cells and patients’ samples to understand how this deregulation could induce malignancy. Through in silico analysis, we identified 12 miRNAs that stood out in the prediction of targets, and we performed functional annotation of the genes linked to these 12 miRNAs that appeared to have a major biological interaction. A total of 90 genes were enriched in 14 KEGG pathways with significant values, including TP53, WNT, MAPK, TGF-β, and Ras signaling pathways. These miRNAs and gene interactions are discussed in further detail for elucidation of how they may act as probable drivers for ATL onset, and while our data provide solid starting points for comprehension of miRNAs’ roles in HTLV-1 infection, continuous effort in oncologic research is still needed to improve our understanding of HTLV-1 induced leukemia.     

Impact of Ge-Sb-Te compound engineering on the set operation performance in phase-change memories

The phase-change memory (PCM) technology is considered as one of the most attractive non-volatile memory concepts for next generation data storage. It relies on the ability of a chalcogenide material belonging to the Ge-Sb-Te compound system to reversibly change its phase between two stable states, namely the poly-crystalline low-resistive state and the amorphous high-resistive state, allowing the storage of the logical bit. A careful study of the phase-change material properties in terms of the set operation performance, the program window and the electrical switching parameters as a function of composition is very attractive in order to enlarge the possible PCM application spectrum. Concerning the set performance, a crystallization kinetics based interpretation of the observed behavior measured on different Ge-Sb-Te compounds is provided, allowing a physics-based comprehension of the reset-to-set transition.     

Temporal coordination and adaptation to rate change in music performance.

People often coordinate their actions with sequences that exhibit temporal variability and unfold at multiple periodicities. We compared oscillator- and timekeeper-based accounts of temporal coordination by examining musicians' coordination of rhythmic musical sequences with a metronome that gradually changed rate at the end of a musical phrase (Experiment 1) or at the beginning of a phrase (Experiment 2). The rhythms contained events that occurred at the same periodic rate as the metronome and at half the period. Rate change consisted of a linear increase or decrease in intervals between metronome onsets. Musicians coordinated their performances better with a metronome that decreased than increased in tempo (as predicted by an oscillator model), at both beginnings and ends of musical phrases. Model performance was tested with an oscillator period or timekeeper interval set to the same period as the metronome (1:1 coordination) or half the metronome period (2:1 coordination). Only the oscillator model was able to predict musicians' coordination at both periods. These findings suggest that coordination is based on internal neural oscillations that entrain to external sequences. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

An experimental study of factors associated with driver frustration and overtaking intentions

This study examined directly the impact of various factors associated with driving on ‘A-class’ roads in the United Kingdom (specifically length of platoon, proportion of heavy goods vehicles (HGVs), speed and opportunities for overtaking) on self-reported frustration and overtaking intentions. The impact of situational variables (being under time pressure, and time behind a slower moving platoon) were also examined, as was the association between frustration and self-reported overtaking intentions. 183 members of the public from the areas around Perth and Inverness, Scotland took part in the study. Participants viewed simulated ‘driver’s viewpoint’ clips representing all the combinations of the experimental variables (except time pressure, which was a between-groups variable, and time behind platoon, which was examined separately in four specific clips). After each clip, participants responded on a paper questionnaire as to the level of frustration they would feel for a given clip, and the likelihood that at some point during the clip they would have attempted an overtake manoeuvre. The findings show that the links between traffic variables such as speed and platoon length, and behaviourally-relevant variables such as frustration and overtaking intentions, are not simple. Although there are broad and predictable effects of speed and platoon length (lower speeds and longer platoons leading to greater frustration) these are mediated by other variables, and it is not always the case that more frustration leads to more intention to overtake. Analysis of driver attitudes identified three clusters (low, medium and high risk drivers) and suggests that higher risk drivers’ levels of frustration are more affected by situational changes than those of lower risk drivers.     

The principal factors affecting construction project overhead expenses: an exploratory factor analysis approach

Estimation is the first step in the project development process. Information technology provides an efficient platform for estimators to obtain quotations and specifications for their bid estimates. However, in practice, project overhead estimation relies heavily on the professional judgement and intuition of the estimators. This reduces the overall accuracy and reliability of the bid and a better understanding of the factors affecting project overheads is fundamental before any improved estimating methods can be devised. Unfortunately, the published literature on this topic is very limited. Using exploratory factor analysis, we aim to bridge the current knowledge gap by highlighting the principal factors affecting project overheads. Questionnaires detailing 27 variables were sent to quantity surveying managers of large contractors in Hong Kong. Seventy-nine valid responses were analysed by exploratory factor analysis. From the results, eight factors were extracted with their latent properties identified with reference to the expert opinions collected from telephone interviews. The findings clarify some misconceptions about the factors affecting project overheads and provide useful evidence for practitioners and researchers to understand project overheads. Estimators who address the identified factors when assessing future project overhead costs can improve the accuracy of their cost estimates and project budgets.     

A computer filtering method to drive out tiny genes from the yeast genome

The authors of the first yeast chromosome sequence defined a minimum threshold requirement of 100 codons, above which an open reading frame (ORF) is retained as a putative coding sequence. However, at least 58 yeast genes shorter than 100 codons have an assigned protein function. Therefore, the yeast genome may contain other tiny but functionally important genes that are discarded from analyses by this simple filtering rule. We have established discriminant functions from the in-phase hexamer frequencies of functional genes and of simulated ORFs derived from a stationary Markov chain model. Fifty-two out of the 58 genes were recognized as coding ORFs by our discriminating method. The test was also applied to all the small ORFs (36 to 100 codons) found in the intergenic regions of published chromosomes. It retained 140 new potential tiny coding sequences, among which we identified seven new genes by similarity searches. Our method, used conjointly with similarity searches, can also highlight sequencing errors resulting from the disruption of the coding frame of longer ORFs. This method, by its ability to detect potential coding ORFs, can be a very useful tool for functional analysis.     

Pan-Cancer Prediction of Cell-Line Drug Sensitivity Using Network-Based Methods

The development of reliable predictive models for individual cancer cell lines to identify an optimal cancer drug is a crucial step to accelerate personalized medicine, but vast differences in cancer cell lines and drug characteristics make it quite challenging to develop predictive models that result in high predictive power and explain the similarity of cell lines or drugs. Our study proposes a novel network-based methodology that breaks the problem into smaller, more interpretable problems to improve the predictive power of anti-cancer drug responses in cell lines. For the drug-sensitivity study, we used the GDSC database for 915 cell lines and 200 drugs. The theory of optimal mass transport was first used to separately cluster cell lines and drugs, using gene-expression profiles and extensive cheminformatic drug features, represented in a form of data networks. To predict cell-line specific drug responses, random forest regression modeling was separately performed for each cell-line drug cluster pair. Post-modeling biological analysis was further performed to identify potential biological correlates associated with drug responses. The network-based clustering method resulted in 30 distinct cell-line drug cluster pairs. Predictive modeling on each cell-line-drug cluster outperformed alternative computational methods in predicting drug responses. We found that among the four drugs top-ranked with respect to prediction performance, three targeted the PI3K/mTOR signaling pathway. Predictive modeling on clustered subsets of cell lines and drugs improved the prediction accuracy of cell-line specific drug responses. Post-modeling analysis identified plausible biological processes associated with drug responses.     

Interplay between Selenium,Selenoproteins and HIV-1 Replication in Human CD4 T-Lymphocytes

The infection of CD4 T-lymphocytes with human immunodeficiency virus (HIV), the etiological agent of acquired immunodeficiency syndrome (AIDS), disrupts cellular homeostasis, increases oxidative stress and interferes with micronutrient metabolism. Viral replication simultaneously increases the demand for micronutrients and causes their loss, as for selenium (Se). In HIV-infected patients, selenium deficiency was associated with a lower CD4 T-cell count and a shorter life expectancy. Selenium has an important role in antioxidant defense, redox signaling and redox homeostasis, and most of these biological activities are mediated by its incorporation in an essential family of redox enzymes, namely the selenoproteins. Here, we have investigated how selenium and selenoproteins interplay with HIV infection in different cellular models of human CD4 T lymphocytes derived from established cell lines (Jurkat and SupT1) and isolated primary CD4 T cells. First, we characterized the expression of the selenoproteome in various human T-cell models and found it tightly regulated by the selenium level of the culture media, which was in agreement with reports from non-immune cells. Then, we showed that selenium had no significant effect on HIV-1 protein production nor on infectivity, but slightly reduced the percentage of infected cells in a Jurkat cell line and isolated primary CD4 T cells. Finally, in response to HIV-1 infection, the selenoproteome was slightly altered.