Toward an mHealth Intervention for Smoking Cessation

The prevalence of tobacco dependence in the United States (US) remains alarming. Invariably, smoke-related health problems are the leading preventable causes of death in the US. Research has shown that a culturally tailored cessation counseling program can help reduce smoking and other tobacco usage. In this paper, we present a mobile health (mHealth) solution that leverages the Short Message Service (SMS) or text messaging feature of mobile devices to motivate behavior change among tobacco users. Our approach implements the Theory of Planned Behavior (TPB) and a phase-based framework. We make contributions to improving previous mHealth intervention approaches by delivering personalized and evidence-based motivational SMS messages to participants. Our proposed solution implements machine learning algorithms that take the participant\u27s demographic profile and previous smoking behavior into account. We discuss our preliminary evaluation of the system against a couple of pseudo-scenarios and our observation of the system\u27s performance

Building a Tailored Text Messaging System for Smoking Cessation in Native American Populations

When starting new and healthy habits or encouraging vigilance against returning to poor habits, a simple text message can be beneficial. Text messages also have the advantage of being easily accessible for lower-income populations spread over a rural area, who may not be able to afford smartphones with apps or data plans. Users benefit the most from text messages that are customized for them, but personalization requires time and effort on part of the user and the counselor. However, personalization that focuses on the cultural background of a pool of recipients, in addition to general personal preferences, can be a low-cost method of ensuring the best experience for patients interested in taking up new habits. In this paper, we discuss the development of a system for motivating users to quit smoking designed for Native American users in South Dakota, using text messaging as a daily intervention method for patients. Our results show that focusing on modular message customization options and messages with a conversational tone best helps our goal of providing users with customization options that help motivate them to live happy and healthy lifestyles

Artificial Gravity Partially Protects Space-Induced Neurological Deficits in Drosophila Melanogaster

Spaceflight poses risks to the central nervous system (CNS), and understanding neurological responses is important for future missions. We report CNS changes in Drosophila aboard the International Space Station in response to spaceflight microgravity (SFmg) and artificially simulated Earth gravity (SF1g) via inflight centrifugation as a countermeasure. While inflight behavioral analyses of SFmg exhibit increased activity, postflight analysis displays significant climbing defects, highlighting the sensitivity of behavior to altered gravity. Multiomics analysis shows alterations in metabolic, oxidative stress and synaptic transmission pathways in both SFmg and SF1g; however, neurological changes immediately postflight, including neuronal loss, glial cell count alterations, oxidative damage, and apoptosis, are seen only in SFmg. Additionally, progressive neuronal loss and a glial phenotype in SF1g and SFmg brains, with pronounced phenotypes in SFmg, are seen upon acclimation to Earth conditions. Overall, our results indicate that artificial gravity partially protects the CNS from the adverse effects of spaceflight

Reality Versus Grant Application Research “Plans”

This article describes the implementation of the American Indian mHealth Smoking Dependence Study focusing on the differences between what was written in the grant application compared to what happened in reality. The study was designed to evaluate a multicomponent intervention involving 256 participants randomly assigned to one of 15 groups. Participants received either a minimal or an intense level of four intervention components: (1) nicotine replacement therapy, (2) precessation counseling, (3) cessation counseling, and (4) mHealth text messaging. The project team met via biweekly webinars as well as one to two in-person meetings per year throughout the study. The project team openly shared progress and challenges and collaborated to find proactive solutions to address challenges as compared to what was planned in the original grant application. The project team used multiple strategies to overcome unanticipated intervention issues: (1) cell phone challenges, (2) making difficult staffing decisions, (3) survey lessons, (4) nicotine replacement therapy, (5) mHealth text messages, (6) motivational interviewing counseling sessions, and (7) use of e-cigarettes. Smoking cessation studies should be designed based on the grant plans. However, on the ground reality issues needed to be addressed to assure the scientific rigor and innovativeness of this study

Daisychain Search and Interactive Visualisation of Homologs in Genome Assemblies

Daisychain is an interactive graph visualisation and search tool for custom-built gene homology databases. The main goal of Daisychain is to allow researchers working with specific genes to identify homologs in other annotation releases. The gene-centric representation includes local gene neighborhood to distinguish orthologs and paralogs by local synteny. The software supports genome sequences in FASTA format and GFF3 formatted annotation files, and the process of building the homology database requires a minimum amount of user interaction. Daisychain includes an integrated web viewer that can be used for both data analysis and data publishing. The web interface extends KnetMaps.js and is based on JavaScript

Simulating High-Dimensional Multivariate Data using the bigsimr R Package

It is critical to accurately simulate data when employing Monte Carlo techniques and evaluating statistical methodology. Measurements are often correlated and high dimensional in this era of big data, such as data obtained in high-throughput biomedical experiments. Due to the computational complexity and a lack of user-friendly software available to simulate these massive multivariate constructions, researchers resort to simulation designs that posit independence or perform arbitrary data transformations. To close this gap, we developed the Bigsimr Julia package with R and Python interfaces. This paper focuses on the R interface. These packages empower high-dimensional random vector simulation with arbitrary marginal distributions and dependency via a Pearson, Spearman, or Kendall correlation matrix. bigsimr contains high-performance features, including multi-core and graphical-processing-unit-accelerated algorithms to estimate correlation and compute the nearest correlation matrix. Monte Carlo studies quantify the accuracy and scalability of our approach, up to $d=10,000$. We describe example workflows and apply to a high-dimensional data set -- RNA-sequencing data obtained from breast cancer tumor samples.Comment: 22 pages, 10 figures, https://cran.r-project.org/web/packages/bigsimr/index.htm

Artificial gravity partially protects space-induced neurological deficits in Drosophila melanogaster

Spaceflight poses risks to the central nervous system (CNS), and understanding neurological responses is important for future missions. We report CNS changes in Drosophila aboard the International Space Station in response to spaceflight microgravity (SFμg) and artificially simulated Earth gravity (SF1g) via inflight centrifugation as a countermeasure. While inflight behavioral analyses of SFμg exhibit increased activity, postflight analysis displays significant climbing defects, highlighting the sensitivity of behavior to altered gravity. Multi-omics analysis shows alterations in metabolic, oxidative stress and synaptic transmission pathways in both SFμg and SF1g; however, neurological changes immediately postflight, including neuronal loss, glial cell count alterations, oxidative damage, and apoptosis, are seen only in SFμg. Additionally, progressive neuronal loss and a glial phenotype in SF1g and SFμg brains, with pronounced phenotypes in SFμg, are seen upon acclimation to Earth conditions. Overall, our results indicate that artificial gravity partially protects the CNS from the adverse effects of spaceflight

Interferon β-1a in relapsing multiple sclerosis: four-year extension of the European IFNβ-1a Dose-C omparison Study

Background: Multiple sclerosis (MS) is a chronic disease requiring long-term monitoring of treatment. Objective: To assess the four-year clinical efficacy of intramuscular (IM) IFNb-1a in patients with relapsing MS from the European IFNb-1a Dose-C omparison Study. Methods: Patients who completed 36 months of treatment (Part 1) of the European IFNb-1a Dose-C omparison Study were given the option to continue double-blind treatment with IFNb-1a 30 mcg or 60 mcg IM once weekly (Part 2). Analyses of 48-month data were performed on sustained disability progression, relapses, and neutralizing antibody (NA b) formation. Results: O f 608/802 subjects who completed 36 months of treatment, 493 subjects continued treatment and 446 completed 48 months of treatment and follow-up. IFNb-1a 30 mcg and 60 mcg IM once weekly were equally effective for up to 48 months. There were no significant differences between doses over 48 months on any of the clinical endpoints, including rate of disability progression, cumulative percentage of patients who progressed (48 and 43, respectively), and annual relapse rates; relapses tended to decrease over 48 months. The incidence of patients who were positive for NAbs at any time during the study was low in both treatment groups. Conclusion: C ompared with 60-mcg IM IFNb-1a once weekly, a dose of 30 mcg IM IFNb-1a once weekly maintains the same clinical efficacy over four years