Barriers to Remote Health Interventions for Type 2 Diabetes: A Systematic Review and Proposed Classification Scheme

BACKGROUND: Diabetes self-management involves adherence to healthy daily habits typically involving blood glucose monitoring, medication, exercise, and diet. To support self-management, some providers have begun testing remote interventions for monitoring and assisting patients between clinic visits. Although some studies have shown success, there are barriers to widespread adoption. OBJECTIVE: The objective of our study was to identify and classify barriers to adoption of remote health for management of type 2 diabetes. METHODS: The following 6 electronic databases were searched for articles published from 2010 to 2015: MEDLINE (Ovid), Embase (Ovid), CINAHL, Cochrane Central, Northern Light Life Sciences Conference Abstracts, and Scopus (Elsevier). The search identified studies involving remote technologies for type 2 diabetes self-management. Reviewers worked in teams of 2 to review and extract data from identified papers. Information collected included study characteristics, outcomes, dropout rates, technologies used, and barriers identified. RESULTS: A total of 53 publications on 41 studies met the specified criteria. Lack of data accuracy due to input bias (32%, 13/41), limitations on scalability (24%, 10/41), and technology illiteracy (24%, 10/41) were the most commonly cited barriers. Technology illiteracy was most prominent in low-income populations, whereas limitations on scalability were more prominent in mid-income populations. Barriers identified were applied to a conceptual model of successful remote health, which includes patient engagement, patient technology accessibility, quality of care, system technology cost, and provider productivity. In total, 40.5% (60/148) of identified barrier instances impeded patient engagement, which is manifest in the large dropout rates cited (up to 57%). CONCLUSIONS: The barriers identified represent major challenges in the design of remote health interventions for diabetes. Breakthrough technologies and systems are needed to alleviate the barriers identified so far, particularly those associated with patient engagement. Monitoring devices that provide objective and reliable data streams on medication, exercise, diet, and glucose monitoring will be essential for widespread effectiveness. Additional work is needed to understand root causes of high dropout rates, and new interventions are needed to identify and assist those at the greatest risk of dropout. Finally, future studies must quantify costs and benefits to determine financial sustainability

The complete mitochondrial genome of the foodborne parasitic pathogen Cyclospora cayetanensis

Cyclospora cayetanensis is a human-specific coccidian parasite responsible for several food and water-related outbreaks around the world, including the most recent ones involving over 900 persons in 2013 and 2014 outbreaks in the USA. Multicopy organellar DNA such as mitochondrion genomes have been particularly informative for detection and genetic traceback analysis in other parasites. We sequenced the C. cayetanensis genomic DNA obtained from stool samples from patients infected with Cyclospora in Nepal using the Illumina MiSeq platform. By bioinformatically filtering out the metagenomic reads of non-coccidian origin sequences and concentrating the reads by targeted alignment, we were able to obtain contigs containing Eimeria-like mitochondrial, apicoplastic and some chromosomal genomic fragments. A mitochondrial genomic sequence was assembled and confirmed by cloning and sequencing targeted PCR products amplified from Cyclospora DNA using primers based on our draft assembly sequence. The results show that the C. cayetanensis mitochondrion genome is 6274 bp in length, with 33% GC content, and likely exists in concatemeric arrays as in Eimeria mitochondrial genomes. Phylogenetic analysis of the C. cayetanensis mitochondrial genome places this organism in a tight cluster with Eimeria species. The mitochondrial genome of C. cayetanensis contains three protein coding genes, cytochrome (cytb), cytochrome C oxidase subunit 1 (cox1), and cytochrome C oxidase subunit 3 (cox3), in addition to 14 large subunit (LSU) and nine small subunit (SSU) fragmented rRNA genes

Seminar Users in the Arabic Twitter Sphere

We introduce the notion of "seminar users", who are social media users engaged in propaganda in support of a political entity. We develop a framework that can identify such users with 84.4% precision and 76.1% recall. While our dataset is from the Arab region, omitting language-specific features has only a minor impact on classification performance, and thus, our approach could work for detecting seminar users in other parts of the world and in other languages. We further explored a controversial political topic to observe the prevalence and potential potency of such users. In our case study, we found that 25% of the users engaged in the topic are in fact seminar users and their tweets make nearly a third of the on-topic tweets. Moreover, they are often successful in affecting mainstream discourse with coordinated hashtag campaigns.Comment: to appear in SocInfo 201

A prospective investigation of body size, body fat composition and colorectal cancer risk in the UK biobank

Obesity has been consistently associated with a greater colorectal cancer risk, but this relationship is weaker among women. In the UK Biobank, we investigated the associations between body size (body mass index [BMI], height, waist circumference, and waist-to-hip ratio) and body fat composition (total body fat percentage and trunk fat percentage) measurements with colorectal cancer risk among 472,526 men and women followed for 5.6 years on average. Multivariable hazard ratios (HRs) and 95% confidence intervals (95%CI) for developing colorectal cancer (2,636 incident cases) were estimated using Cox proportional hazards models. Among men, when the highest and lowest fifths were compared, BMI (HR = 1.35, 95%CI: 1.13–1.61; Ptrend < 0.0001), waist circumference (HR = 1.66, 95%CI: 1.39–1.99; Ptrend < 0.0001), waist-to-hip ratio (HR = 1.58, 95%CI: 1.31–1.91; Ptrend < 0.0001), total body fat percentage (HR = 1.27, 95%CI: 1.06–1.53; Ptrend = 0.002), and trunk fat percentage (HR = 1.31, 95%CI: 1.09–1.58; Ptrend = 0.002) were associated with greater colorectal cancer risk. For women, only waist-to-hip ratio (HR for highest versus lowest fifth = 1.33, 95%CI: 1.08–1.65; Ptrend = 0.005) was positively associated with colorectal cancer risk. Greater body size (overall and abdominal adiposity) was positively associated with colorectal cancer development in men. For women, abdominal adiposity, rather than overall body size, was associated with a greater colorectal cancer risk

ELF5 modulates the estrogen receptor cistrome in breast cancer.

Acquired resistance to endocrine therapy is responsible for half of the therapeutic failures in the treatment of breast cancer. Recent findings have implicated increased expression of the ETS transcription factor ELF5 as a potential modulator of estrogen action and driver of endocrine resistance, and here we provide the first insight into the mechanisms by which ELF5 modulates estrogen sensitivity. Using chromatin immunoprecipitation sequencing we found that ELF5 binding overlapped with FOXA1 and ER at super enhancers, enhancers and promoters, and when elevated, caused FOXA1 and ER to bind to new regions of the genome, in a pattern that replicated the alterations to the ER/FOXA1 cistrome caused by the acquisition of resistance to endocrine therapy. RNA sequencing demonstrated that these changes altered estrogen-driven patterns of gene expression, the expression of ER transcription-complex members, and 6 genes known to be involved in driving the acquisition of endocrine resistance. Using rapid immunoprecipitation mass spectrometry of endogenous proteins, and proximity ligation assays, we found that ELF5 interacted physically with members of the ER transcription complex, such as DNA-PKcs. We found 2 cases of endocrine-resistant brain metastases where ELF5 levels were greatly increased and ELF5 patterns of gene expression were enriched, compared to the matched primary tumour. Thus ELF5 alters ER-driven gene expression by modulating the ER/FOXA1 cistrome, by interacting with it, and by modulating the expression of members of the ER transcriptional complex, providing multiple mechanisms by which ELF5 can drive endocrine resistance

Predicting Distribution of Aedes Aegypti and Culex Pipiens Complex, Potential Vectors of Rift Valley Fever Virus in Relation to Disease Epidemics in East Africa.

The East African region has experienced several Rift Valley fever (RVF) outbreaks since the 1930s. The objective of this study was to identify distributions of potential disease vectors in relation to disease epidemics. Understanding disease vector potential distributions is a major concern for disease transmission dynamics. DIVERSE ECOLOGICAL NICHE MODELLING TECHNIQUES HAVE BEEN DEVELOPED FOR THIS PURPOSE: we present a maximum entropy (Maxent) approach for estimating distributions of potential RVF vectors in un-sampled areas in East Africa. We modelled the distribution of two species of mosquitoes (Aedes aegypti and Culex pipiens complex) responsible for potential maintenance and amplification of the virus, respectively. Predicted distributions of environmentally suitable areas in East Africa were based on the presence-only occurrence data derived from our entomological study in Ngorongoro District in northern Tanzania. Our model predicted potential suitable areas with high success rates of 90.9% for A. aegypti and 91.6% for C. pipiens complex. Model performance was statistically significantly better than random for both species. Most suitable sites for the two vectors were predicted in central and northwestern Tanzania with previous disease epidemics. Other important risk areas include western Lake Victoria, northern parts of Lake Malawi, and the Rift Valley region of Kenya. Findings from this study show distributions of vectors had biological and epidemiological significance in relation to disease outbreak hotspots, and hence provide guidance for the selection of sampling areas for RVF vectors during inter-epidemic periods

Gene expression drives the evolution of dominance.

Dominance is a fundamental concept in molecular genetics and has implications for understanding patterns of genetic variation, evolution, and complex traits. However, despite its importance, the degree of dominance in natural populations is poorly quantified. Here, we leverage multiple mating systems in natural populations of Arabidopsis to co-estimate the distribution of fitness effects and dominance coefficients of new amino acid changing mutations. We find that more deleterious mutations are more likely to be recessive than less deleterious mutations. Further, this pattern holds across gene categories, but varies with the connectivity and expression patterns of genes. Our work argues that dominance arises as a consequence of the functional importance of genes and their optimal expression levels