Multiple electron trapping in the fragmentation of strongly driven molecules

We present a theoretical quasiclassical study of the formation, during Coulomb explosion, of two highly excited neutral H atoms (double H$^{*}$) of strongly driven H$_2$. In this process, after the laser field is turned off each electron occupies a Rydberg state of an H atom. We show that two-electron effects are important in order to correctly account for double H$^{*}$ formation. We find that the route to forming two H$^{*}$ atoms is similar to pathway B that was identified in Phys. Rev. A {\bf 85} 011402 (R) as one of the two routes leading to single H$^{*}$ formation. However, instead of one ionization step being "frustrated" as is the case for pathway B, both ionization steps are "frustrated" in double H$^{*}$ formation. Moreover, we compute the screened nuclear charge that drives the explosion of the nuclei during double H$^{*}$ formation.Comment: 4 pages, 6 figure

Molecular heat pump for rotational states

In this work we investigate the theory for three different uni-directional population transfer schemes in trapped multilevel systems which can be utilized to cool molecular ions. The approach we use exploits the laser-induced coupling between the internal and motional degrees of freedom so that the internal state of a molecule can be mapped onto the motion of that molecule in an external trapping potential. By sympathetically cooling the translational motion back into its ground state the mapping process can be employed as part of a cooling scheme for molecular rotational levels. This step is achieved through a common mode involving a laser-cooled atom trapped alongside the molecule. For the coherent mapping we will focus on adiabatic passage techniques which may be expected to provide robust and efficient population transfers. By applying far-detuned chirped adiabatic rapid passage pulses we are able to achieve an efficiency of better than 98% for realistic parameters and including spontaneous emission. Even though our main focus is on cooling molecular states, the analysis of the different adiabatic methods has general features which can be applied to atomic systems

Provenance-Centered Dataset of Drug-Drug Interactions

Over the years several studies have demonstrated the ability to identify potential drug-drug interactions via data mining from the literature (MEDLINE), electronic health records, public databases (Drugbank), etc. While each one of these approaches is properly statistically validated, they do not take into consideration the overlap between them as one of their decision making variables. In this paper we present LInked Drug-Drug Interactions (LIDDI), a public nanopublication-based RDF dataset with trusty URIs that encompasses some of the most cited prediction methods and sources to provide researchers a resource for leveraging the work of others into their prediction methods. As one of the main issues to overcome the usage of external resources is their mappings between drug names and identifiers used, we also provide the set of mappings we curated to be able to compare the multiple sources we aggregate in our dataset.Comment: In Proceedings of the 14th International Semantic Web Conference (ISWC) 201

A Novel Visualization Tool for Evaluating Medication Side-Effects in Multi-drug Regimens

The evaluation and management of medication side-effects is a common and complex task for physicians. Information visualization has the potential to increase the efficiency and reduce the cognitive load involved in this process. We describe the design and development of Rxplore, a novel tool for assessing medication side-effects. Rxplore supports simultaneous lookup of multiple medications and an intuitive visual representation of query results. In a pilot study of Rxplore’s usability and utility, physicians rated the system highly for efficiency, intuitiveness, and clinical value

Dietary and other lifestyle characteristics of Cypriot school children: results from the nationwide CYKIDS study

Dietary and lifestyle behaviors at young ages have been associated with the development of various chronic diseases. Schools are regarded as an excellent setting for lifestyle modification; there is a lack, however, of published dietary data in Cypriot school children. Thus, the objective of this work was to describe lifestyle characteristics of a representative segment of Cypriot school children and provide implications for school health education. Methods. The CYKIDS (Cyprus Kids Study) is a national, cross-sectional study conducted among 1140 school children (10.7 0.98 years). Sampling was stratified and multistage in 24 primary schools of Cyprus. Dietary assessment was based on a 154-item semi-quantitative food-frequency questionnaire and three supplementary questionnaires, assessing dietary patterns and behaviors. Adherence to the Mediterranean diet was evaluated by the KIDMED index (Mediterranean Diet Quality Index for children and adolescents). Physical activity was assessed by a 32-item, semi-quantitative questionnaire. Results. Analysis revealed that 6.7% of the children were classified as high adherers, whereas 37% as low adherers to the Mediterranean diet. About 20% of boys and 25% of girls reported "not having breakfast on most days of the week", while more than 80% of the children reported having meals with the family at least 5 times/week. Some food-related behaviors, such as intake of breakfast, were associated with socio-demographic factors, mostly with gender and the geomorphological characteristics of the living milieu. With respect to physical activity, boys reported higher levels compared to girls, however, one fourth of children did not report any kind of physical activity. Conclusion. A large percentage of Cypriot school children have a diet of low quality and inadequate physical activity. Public health policy makers should urgently focus their attention to primary school children and design school health education programs that target the areas that need attention in order to reduce the future burden of metabolic disorders and chronic diseases

Current trends in the cardiovascular clinical trial arena (I)

The existence of effective therapies for most cardiovascular disease states, coupled with increased requirements that potential benefits of new drugs be evaluated on clinical rather than surrogate endpoints, makes it increasingly difficult to substantiate any incremental improvements in efficacy that these new drugs might offer. Compounding the problem is the highly controversial issue of comparing new agents with placebos rather than active pharmaceuticals in drug efficacy trials. Despite the recent consensus that placebos may be used ethically in well-defined, justifiable circumstances, the problem persists, in part because of increased scrutiny by ethics committees but also because of considerable lingering disagreement regarding the propriety and scientific value of placebo-controlled trials (and trials of antihypertensive drugs in particular). The disagreement also substantially affects the most viable alternative to placebo-controlled trials: actively controlled equivalence/noninferiority trials. To a great extent, this situation was prompted by numerous previous trials of this type that were marked by fundamental methodological flaws and consequent false claims, inconsistencies, and potential harm to patients. As the development and use of generic drugs continue to escalate, along with concurrent pressure to control medical costs by substituting less-expensive therapies for established ones, any claim that a new drug, intervention, or therapy is "equivalent" to another should not be accepted without close scrutiny. Adherence to proper methods in conducting studies of equivalence will help investigators to avoid false claims and inconsistencies. These matters will be addressed in the third article of this three-part series

Reversible Keap1 inhibitors are preferential pharmacological tools to modulate cellular mitophagy

Mitophagy orchestrates the autophagic degradation of dysfunctional mitochondria preventing their pathological accumulation and contributing to cellular homeostasis. We previously identified a novel chemical tool (hereafter referred to as PMI), which drives mitochondria into autophagy without collapsing their membrane potential (ΔΨm). PMI is an inhibitor of the protein-protein interaction (PPI) between the transcription factor Nrf2 and its negative regulator, Keap1 and is able to up-regulate the expression of autophagy-associated proteins, including p62/SQSTM1. Here we show that PMI promotes mitochondrial respiration, leading to a superoxide-dependent activation of mitophagy. Structurally distinct Keap1-Nrf2 PPI inhibitors promote mitochondrial turnover, while covalent Keap1 modifiers, including sulforaphane (SFN) and dimethyl fumarate (DMF), are unable to induce a similar response. Additionally, we demonstrate that SFN reverses the effects of PMI in co-treated cells by reducing the accumulation of p62 in mitochondria and subsequently limiting their autophagic degradation. This study highlights the unique features of Keap1-Nrf2 PPI inhibitors as inducers of mitophagy and their potential as pharmacological agents for the treatment of pathological conditions characterized by impaired mitochondrial quality control

Digital biomarker-based individualized prognosis for people at risk of dementia

Background: Research investigating treatments and interventions for cognitive decline fail due to difficulties in accurately recognizing behavioral signatures in the presymptomatic stages of the disease. For this validation study, we took our previously constructed digital biomarker-based prognostic models and focused on generalizability and robustness of the models. Method: We validated prognostic models characterizing subjects using digital biomarkers in a longitudinal, multi-site, 40-month prospective study collecting data in memory clinics, general practitioner offices, and home environments. Results: Our models were able to accurately discriminate between healthy subjects and individuals at risk to progress to dementia within 3 years. The model was also able to differentiate between people with or without amyloid neuropathology and classify fast and slow cognitive decliners with a very good diagnostic performance. Conclusion: Digital biomarker prognostic models can be a useful tool to assist large-scale population screening for the early detection of cognitive impairment and patient monitoring over time