eEF2K Activity Determines Synergy to Cotreatment of Cancer Cells With PI3K and MEK Inhibitors

PI3K-mammalian target of rapamycin and MAPK/ERK kinase (MEK)/mitogen-activated protein kinase (MAPK) are the most frequently dysregulated signaling pathways in cancer. A problem that limits the success of therapies that target individual PI3K-MAPK members is that these pathways converge to regulate downstream functions and often compensate each other, leading to drug resistance and transient responses to therapy. In order to overcome resistance, therapies based on cotreatments with PI3K/AKT and MEK/MAPK inhibitors are now being investigated in clinical trials, but the mechanisms of sensitivity to cotreatment are not fully understood. Using LC-MS/MS-based phosphoproteomics, we found that eukaryotic elongation factor 2 kinase (eEF2K), a key convergence point downstream of MAPK and PI3K pathways, mediates synergism to cotreatment with trametinib plus pictilisib (which target MEK1/2 and PI3Kα/δ, respectively). Inhibition of eEF2K by siRNA or with a small molecule inhibitor reversed the antiproliferative effects of the cotreatment with PI3K plus MEK inhibitors in a cell model–specific manner. Systematic analysis in 12 acute myeloid leukemia cell lines revealed that eEF2K activity was increased in cells for which PI3K plus MEKi cotreatment is synergistic, while PKC potentially mediated resistance to such cotreatment. Together, our study uncovers eEF2K activity as a key mediator of responses to PI3Ki plus MEKi and as a potential biomarker to predict synergy to cotreatment in cancer cells

Experimental tests of hidden variable theories from dBB to Stochastic Electrodynamics

In this paper we present some of our experimental results on testing hidden variable theories, which range from Bell inequalities measurements to a conclusive test of stochastic electrodynamics

Seismic risk in the city of Al Hoceima (north of Morocco) using the vulnerability index method, applied in Risk-UE project

The final publication is available at Springer via http://dx.doi.org/10.1007/s11069-016-2566-8Al Hoceima is one of the most seismic active regions in north of Morocco. It is demonstrated by the large seismic episodes reported in seismic catalogs and research studies. However, seismic risk is relatively high due to vulnerable buildings that are either old or don’t respect seismic standards. Our aim is to present a study about seismic risk and seismic scenarios for the city of Al Hoceima. The seismic vulnerability of the existing residential buildings was evaluated using the vulnerability index method (Risk-UE). It was chosen to be adapted and applied to the Moroccan constructions for its practicality and simple methodology. A visual inspection of 1102 buildings was carried out to assess the vulnerability factors. As for seismic hazard, it was evaluated in terms of macroseismic intensity for two scenarios (a deterministic and probabilistic scenario). The maps of seismic risk are represented by direct damage on buildings, damage to population and economic cost. According to the results, the main vulnerability index of the city is equal to 0.49 and the seismic risk is estimated as Slight (main damage grade equal to 0.9 for the deterministic scenario and 0.7 for the probabilistic scenario). However, Moderate to heavy damage is expected in areas located in the newer extensions, in both the east and west of the city. Important economic losses and damage to the population are expected in these areas as well. The maps elaborated can be a potential guide to the decision making in the field of seismic risk prevention and mitigation strategies in Al Hoceima.Peer ReviewedPostprint (author's final draft

Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs

Artificial intelligence and machine learning (ML) promise to transform cancer therapies by accurately predicting the most appropriate therapies to treat individual patients. Here, we present an approach, named Drug Ranking Using ML (DRUML), which uses omics data to produce ordered lists of >400 drugs based on their anti-proliferative efficacy in cancer cells. To reduce noise and increase predictive robustness, instead of individual features, DRUML uses internally normalized distance metrics of drug response as features for ML model generation. DRUML is trained using in-house proteomics and phosphoproteomics data derived from 48 cell lines, and it is verified with data comprised of 53 cellular models from 12 independent laboratories. We show that DRUML predicts drug responses in independent verification datasets with low error (mean squared error < 0.1 and mean Spearman’s rank 0.7). In addition, we demonstrate that DRUML predictions of cytarabine sensitivity in clinical leukemia samples are prognostic of patient survival (Log rank p < 0.005). Our results indicate that DRUML accurately ranks anti-cancer drugs by their efficacy across a wide range of pathologies

Cumulative regulatory potential of clustered methyl-arginine protein modifications

Systematic analysis of human arginine methylation events bifurcates its signaling mechanism, functioning either in isolation akin to canonical PTM regulation or clustered within disordered protein sequence. Hundreds of proteins contain methyl-arginine clusters and are more prone to mutation and more tightly expression-regulated than dispersed methylation targets. Arginine clusters in the highly methylated RNA binding protein SYNCRIP were experimentally shown to function in concert providing a tunable protein interaction interface. Quantitative immuno-precipitation assays defined two distinct cumulative regulatory mechanisms operating across 18 proximal arginine-glycine motifs in SYNCRIP. Functional binding to the methyl-transferase PRMT1 was promoted by continual arginine stretches while interaction with the methyl-binding protein SMN1 was arginine content dependent irrespective of linear position within the unstructured region. This study highlights how highly repetitive di-amino acid motifs in otherwise low structural complexity regions can provide regulatory potential, and with SYNCRIP as an extreme example how PTMs leverage these disordered sequences to drive cellular functions

Homogeneous Gold Catalysis through Relativistic Effects: Addition of Water to Propyne

In the catalytic addition of water to propyne the Au(III) catalyst is not stable under non-relativistic conditions and dissociates into a Au(I) compound and Cl2. This implies that one link in the chain of events in the catalytic cycle is broken and relativity may well be seen as the reason why Au(III) compounds are effective catalysts.Comment: 12 pages, 3 figures, 1 tabl

Experiences of water immersion during childbirth: a qualitative thematic synthesis

Background The increasing demand for childbirth care based on physiological principles has led official bodies to encourage health centers to provide evidence‑based care aimed at promoting women’s participation in informed decision‑making and avoiding excessive medical intervention during childbirth. One of the goals is to reduce pain and find alternative measures to epidural anesthesia to enhance women’s autonomy and well‑being during child‑ birth. Currently, water immersion is used as a non‑pharmacological method for pain relief. This review aimed to identify and synthesize evidence on women’s and midwives’ experiences, values, and prefer‑ ences regarding water immersion during childbirth. Methods A systematic review and thematic synthesis of qualitative evidence were conducted. Databases were searched and references were checked according to specific criteria. Studies that used qualitative data collection and analysis methods to examine the opinions of women or midwives in the hospital setting were included. Non‑qualita‑ tive studies, mixed‑methods studies that did not separately report qualitative results, and studies in languages other than English or Spanish were excluded. The Critical Appraisal Skills Program Qualitative Research Checklist was used to assess study quality, and results were synthesized using thematic synthesis. Results Thirteen studies met the inclusion criteria and were included in this review. The qualitative studies yielded three key themes: 1) reasons identified by women and midwives for choosing a water birth, 2) benefits experienced in water births, and 3) barriers and facilitators of water immersion during childbirth. Conclusions The evidence from qualitative studies indicates that women report benefits associated with water birth. From the perspective of midwives, ensuring safe water births requires adequate resources, midwives training, and rig‑ orous standardized protocols to ensure that all pregnant women can safely opt for water immersion during childbirth with satisfactory results