Insights into the evolution of Darwin's finches from comparative analysis of the Geospiza magnirostris genome sequence

Background: A classical example of repeated speciation coupled with ecological diversification is the evolution of 14 closely related species of Darwin's (Galápagos) finches (Thraupidae, Passeriformes). Their adaptive radiation in the Galápagos archipelago took place in the last 2-3 million years and some of the molecular mechanisms that led to their diversification are now being elucidated. Here we report evolutionary analyses of genome of the large ground finch, Geospiza magnirostris.Results: 13,291 protein-coding genes were predicted from a 991.0 Mb G. magnirostris genome assembly. We then defined gene orthology relationships and constructed whole genome alignments between the G. magnirostris and other vertebrate genomes. We estimate that 15% of genomic sequence is functionally constrained between G. magnirostris and zebra finch. Genic evolutionary rate comparisons indicate that similar selective pressures acted along the G. magnirostris and zebra finch lineages suggesting that historical effective population size values have been similar in both lineages. 21 otherwise highly conserved genes were identified that each show evidence for positive selection on amino acid changes in the Darwin's finch lineage. Two of these genes (Igf2r and Pou1f1) have been implicated in beak morphology changes in Darwin's finches. Five of 47 genes showing evidence of positive selection in early passerine evolution have cilia related functions, and may be examples of adaptively evolving reproductive proteins.Conclusions: These results provide insights into past evolutionary processes that have shaped G. magnirostris genes and its genome, and provide the necessary foundation upon which to build population genomics resources that will shed light on more contemporaneous adaptive and non-adaptive processes that have contributed to the evolution of the Darwin's finches. © 2013 Rands et al.; licensee BioMed Central Ltd

Factors associated with optimal pharmacy refill adherence for antiretroviral medications and plasma HIV RNA non-detectability among HIV-positive crack cocaine users: a prospective cohort study

BACKGROUND: Crack cocaine use is known to contribute to poor adherence to antiretroviral medications; however, little is known about facilitators of or barriers to effective HIV treatment use among HIV-infected crack cocaine users. We sought to identify correlates of optimal pharmacy refill adherence for antiretroviral medications and plasma HIV RNA viral load (pVL) suppression among this population. METHODS: Data from a prospective cohort of HIV-positive people who use illicit drugs in Vancouver, Canada, were linked to comprehensive HIV clinical monitoring and pharmacy dispensation records. We used multivariable generalized linear mixed-effects modelling to longitudinally identify factors associated with ≥95 % adherence to pharmacy refills for antiretroviral medications and pVL <50 copies/mL among crack cocaine users exposed to highly-active antiretroviral therapy (HAART). RESULTS: Among 438 HAART-exposed crack cocaine users between 2005 and 2013, 240 (54.8 %) had ≥95 % pharmacy refill adherence in the previous 6 months at baseline. In multivariable analyses, homelessness (adjusted odds ratio [AOR]: 0.58), ≥daily crack cocaine smoking (AOR: 0.64), and ≥ daily heroin use (AOR: 0.43) were independently associated with optimal pharmacy refill adherence (all p < 0.05). The results for pVL non-detectability were consistent with those of medication adherence, except that longer history of HAART (AOR: 1.06), receiving a single tablet-per-day regimen (AOR: 3.02) and participation in opioid substitution therapies was independently associated with pVL non-detectability (AOR: 1.55) (all p < 0.05). CONCLUSIONS: Homelessness, and daily crack cocaine and/or heroin use were independently and negatively associated with optimal HAART-related outcomes. With the exception of opioid substitution therapies, no addiction treatment modalities assessed appeared to facilitate medication adherence or viral suppression. Evidence-based treatment options for crack cocaine use that also confer benefits to HAART need to be developed

Intraepithelial leukocytes of the intestinal mucosa in normal man and in Whipple's disease

Intraepithelial lymphocytes (IEL) of the intestinal mucosa of normal man and of patients with Whipple's disease were studied by light microscopy of 1-μm-thick sections, and by electron microscopy of thin sections. IEL in normal human intestine tend to be elongated in outline, have few cytoplasmic organelles, have compact nuclei, and are unattached to epithelial cells. IEL in Whipple's disease are more likely to be activated in appearance, ie, to be larger and to contain more cytoplasmic organelles than IEL of normal intestine. The number of IEL/100 intestinal epithelial cells is similar in normal man and in patients with Whipple's disease. Other intraepithelial (IE) cells found in normal intestine include eosinophils and mast cells, and we note for the first time the presence of IE macrophages. There are no “globule leukocytes” in the intestine of normal man or of patients with Whipple's disease. Other IE cells found in the intestine in Whipple's disease include eosinophils, polymorphonuclear (PMN) leukocytes, and macrophages in untreated disease and intraepithelial macrophages in treated disease. These IE cells may be involved in the acute and chronic immune responses of the intestine.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44392/1/10620_2005_Article_BF01296750.pd

The development and validation of a prognostic model to PREDICT Relapse of depression in adult patients in primary care: protocol for the PREDICTR study.

BACKGROUND: Most patients who present with depression are treated in primary care by general practitioners (GPs). Relapse of depression is common (at least 50% of patients treated for depression will relapse after a single episode) and leads to considerable morbidity and decreased quality of life for patients. The majority of patients will relapse within 6 months, and those with a history of relapse are more likely to relapse in the future than those with no such history. GPs see a largely undifferentiated case-mix of patients, and once patients with depression reach remission, there is limited guidance to help GPs stratify patients according to risk of relapse. We aim to develop a prognostic model to predict an individual's risk of relapse within 6-8 months of entering remission. The long-term objective is to inform the clinical management of depression after the acute phase. METHODS: We will develop a prognostic model using secondary analysis of individual participant data drawn from seven RCTs and one longitudinal cohort study in primary or community care settings. We will use logistic regression to predict the outcome of relapse of depression within 6-8 months. We plan to include the following established relapse predictors in the model: residual depressive symptoms, number of previous depressive episodes, co-morbid anxiety and severity of index episode. We will use a "full model" development approach, including all available predictors. Performance statistics (optimism-adjusted C-statistic, calibration-in-the-large, calibration slope) and calibration plots (with smoothed calibration curves) will be calculated. Generalisability of predictive performance will be assessed through internal-external cross-validation. Clinical utility will be explored through net benefit analysis. DISCUSSION: We will derive a statistical model to predict relapse of depression in remitted depressed patients in primary care. Assuming the model has sufficient predictive performance, we outline the next steps including independent external validation and further assessment of clinical utility and impact. STUDY REGISTRATION: ClinicalTrials.gov ID: NCT04666662