Molecular survey of pyrethroid resistance mechanisms in Mexican field populations of Rhipicephalus (Boophilus) microplus

Susceptibility to synthetic pyrethroids (SP´s) and the role of two major resistance mechanisms were evaluated in Mexican Rhipicephalus microplus tick populations. Larval packet test (LPT), knock-down (kdr) PCR allele-specific assay (PASA) and esterase activity assays were conducted in tick populations for cypermethrin, flumethrin and deltamethrin. Esterase activity did not have a significant correlation with SP´s resistance. However a significant correlation (p < 0.01) was found between the presence of the sodium channel mutation, and resistance to SP´s as measured by PASA and LPT respectively. Just over half the populations (16/28) were cross-resistant to flumethrin, deltamethrin and cypermethrine, 21.4% of the samples (6/28) were susceptible to all of the three pyrethroids 10.7 of the samples (3/28) were resistant to flumethrin, 3.4 of the samples (1/28) were resistant to deltamethrin only and 7.1% (2/28) were resistant to flumethrin and deltamethrin. The presence of the kdr mutation correlates with resistance to the SP´s as a class. Target site insensitivity is the major mechanism of resistance to SP´s in Mexican R. microplus field strains, involving the presence of a sodium channel mutation, however, esterase-based, other mutations or combination of mechanisms can also occur

Incidence, mechanism and prognostic value of activated AKT in pancreas cancer

When activated, the serine/threonine kinase AKT mediates an antiapoptotic signal implicated in chemoresistance of various cancers. The mechanism(s) of AKT activation are unknown, though overexpression of HER-2/neu has been implicated in breast cancer. Therefore, we determined the incidence of activated AKT in human pancreatic cancer, whether HER-2/neu is involved in AKT activation, and if AKT activation is associated with biologic behaviour. HER-2/neu expression and AKT activation were examined in seven pancreatic cancer cell lines by Western blotting. The in vitro effect of HER-2/neu inhibition on AKT activation was similarly determined. Finally, 78 pancreatic cancer specimens were examined for AKT activation and HER-2/neu overexpression, and correlated with the clinical prognostic variable of histologic grade. HER-2/neu was overexpressed in two of seven cell lines; these two cell lines demonstrated the highest level of AKT activation. Inhibition of HER-2/neu reduced AKT activation in vitro. AKT was activated in 46 out of 78 (59%) of the pancreatic cancers; HER-2/neu overexpression correlated with AKT activation (P=0.015). Furthermore, AKT activation was correlated with higher histologic tumour grade (P=0.047). Thus, it is concluded that AKT is frequently activated in pancreatic cancer; this antiapoptotic signal may be mediated by HER-2/neu overexpression. AKT activation is associated with tumour grade, an important prognostic factor

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

On the automatic identification of unobserved components models

Automatic identi cation of time series models is a necessity once the big data era has come and is staying among us. This has become obvious for many companies and public entities that has passed from a crafted analysis of each individual problem to handle a tsunami of information that has to be processed e ciently, online and in record time. Automatic identi cation tools has never been tried out on Unobserved Components models (UC). This chapter shows how information criteria, such as Akaike's or Schwarz's, are rather useful for model selection within the UC family. The di culty lies, however, on choosing an appropriate and as general as possible set of models to search in. A set too narrow would render poor forecast accuracy, while a set too wide would be highly time consuming. The forecasting results suggest that UC models are powerful potential forecasting competitors to other well-known methods. Though there are several pieces of software available for UC modeling, this is the rst implementation of an automatic algorithm for this class of models, to the best of the authors knowledge

Characterizing Dynamic Changes in the Human Blood Transcriptional Network

Gene expression data generated systematically in a given system over multiple time points provides a source of perturbation that can be leveraged to infer causal relationships among genes explaining network changes. Previously, we showed that food intake has a large impact on blood gene expression patterns and that these responses, either in terms of gene expression level or gene-gene connectivity, are strongly associated with metabolic diseases. In this study, we explored which genes drive the changes of gene expression patterns in response to time and food intake. We applied the Granger causality test and the dynamic Bayesian network to gene expression data generated from blood samples collected at multiple time points during the course of a day. The simulation result shows that combining many short time series together is as powerful to infer Granger causality as using a single long time series. Using the Granger causality test, we identified genes that were supported as the most likely causal candidates for the coordinated temporal changes in the network. These results show that PER1 is a key regulator of the blood transcriptional network, in which multiple biological processes are under circadian rhythm regulation. The fasted and fed dynamic Bayesian networks showed that over 72% of dynamic connections are self links. Finally, we show that different processes such as inflammation and lipid metabolism, which are disconnected in the static network, become dynamically linked in response to food intake, which would suggest that increasing nutritional load leads to coordinate regulation of these biological processes. In conclusion, our results suggest that food intake has a profound impact on the dynamic co-regulation of multiple biological processes, such as metabolism, immune response, apoptosis and circadian rhythm. The results could have broader implications for the design of studies of disease association and drug response in clinical trials

Impact of DNA methylation on trophoblast function

The influence of epigenetics is evident in many fields of medicine today. This is also true in placentology, where versatile epigenetic mechanisms that regulate expression of genes have shown to have important influence on trophoblast implantation and placentation. Such gene regulation can be established in different ways and on different molecular levels, the most common being the DNA methylation. DNA methylation has been shown today as an important predictive component in assessing clinical prognosis of certain malignant tumors; in addition, it opens up new possibilities for non-invasive prenatal diagnosis utilizing cell-free fetal DNA methods. By using a well known demethylating agent 5-azacytidine in pregnant rat model, we have been able to change gene expression and, consequently, the processes of trophoblast differentiation and placental development. In this review, we describe how changes in gene methylation effect trophoblast development and placentation and offer our perspective on use of trophoblast epigenetic research for better understanding of not only placenta development but cancer cell growth and invasion as well

Predictors of Visceral Leishmaniasis Relapse in HIV-Infected Patients: A Systematic Review

Visceral leishmaniasis (VL) is the most serious form of an insect-transmitted parasitic disease prevalent in 70 countries. The disease is caused by species of the L. donovani complex found in different geographical regions. These parasites have substantially different clinical, drug susceptibility and epidemiological characteristics. According to data from the World Health Organization, the areas where HIV-Leishmania co-infection is distributed are extensive. HIV infection increases the risk of developing VL, reduces the likelihood of a therapeutic response, and greatly increases the probability of relapse. A better understanding of the factors promoting relapses is essential; therefore we performed a systematic review of articles involving all articles assessing the predictors of VL relapse in HIV-infected individuals older than 14 years of age. Out of 178 relevant articles, 18 met the inclusion criteria and in total, data from 1017 patients were analyzed. We identified previous episodes of VL relapse, CD4+ lymphocyte count fewer than 100 cells/mL at VL diagnosis, and the absence of an increase in CD4+ counts at follow-up as major factors associated with VL relapse. Knowledge of relapse predictors can help to identify patients with different degrees of risk, facilitate and direct prophylaxis choices, and aid in patient counseling