A protective effect of caffeine on drosophila larvae treated with methyl methanesulfonate.

Lethality induced in larval populations of Drosophila melanogaster was recorded after treatment with (1) caffeine, (2) MMS or (3) caffeine plus MMS. The mixture of caffeine plus MMS was less toxic than expected from the effects observed after treatment with either substance individually. It is postulated that in the combined treatment the caffeine, by inhibiting semiconservative DNA replication, allows for some additional time for repair of alkylated DNA by a repair pathway which is not sensitive to caffeine, possibly excision repair.     

Assessing the faecal source sensitivity and specificity of ruminant and human genetic microbial source tracking markers in the central Ethiopian highlands

This study tested genetic microbial source tracking (MST) methods for identifying ruminant- (BacR) and human-associated (HF183/BacR287, BacHum) bacterial faecal contaminants in Ethiopia in a newly created regional faecal sample bank (n = 173). BacR performed well, and its marker abundance was high (100% sensitivity (Sens), 95% specificity (Spec), median log₁₀ 8·1 marker equivalents (ME) g⁻¹ ruminant faeces). Human-associated markers tested were less abundant in individual human samples (median: log₁₀ 5·4 and 4·2 (ME + 1) g⁻¹) and were not continuously detected (81% Sens, 91% Spec for BacHum; 77% Sens, 91% Spec for HF183/BacR287). Furthermore, the pig-associated Pig2Bac assay was included and performed excellent (100% Sens, 100% Spec). To evaluate the presence of MST targets in the soil microbiome, representative soil samples were tested during a whole seasonal cycle (n = 60). Only BacR could be detected, but was limited to the dry season and to sites of higher anthropogenic influence (log₁₀ 3·0 to 4·9 (ME + 1) g⁻¹ soil). In conclusion, the large differences in marker abundances between target and non-target faecal samples (median distances between distributions ≥log₁₀ 3 to ≥log₁₀ 7) and their absence in pristine soil indicate that all tested assays are suitable candidates for diverse MST applications in the Ethiopian area.     

Poor knowledge of methotrexate associated with older age and limited English-language proficiency in a diverse rheumatoid arthritis cohort

Introduction

Our objective was to determine rheumatoid arthritis (RA) patients’ understanding of methotrexate and assess whether knowledge varies by age, education, English language proficiency, or other disease-related factors.

Methods

Adults with RA (n = 135) who were enrollees of an observational cohort completed a structured telephone interview in their preferred language between August 2007 and July 2009. All subjects who reported taking methotrexate were asked 11 questions about the medication in addition to demographics, education level, and language proficiency. Primary outcome was a total score below the 50^th percentile (considered inadequate methotrexate knowledge). Bivariable and multivariable logistic regressions were performed. Covariates included demographics, language proficiency, education, and disease characteristics.

Results

Of 135 subjects, 83% were female, with a mean age of 55 ± 14 years. The majority spoke English (64%), followed by 22% Spanish and 14% Cantonese or Mandarin. Limited English language proficiency (LEP) was reported in 42%. Mean methotrexate knowledge score was 5.4 ± 2.6 (range, 0 to 10); 73 (54%) had a score lower than 5 (of 10). Age older than 55, less than high school education, LEP, better function, and biologic use were independently associated with poor knowledge.

Conclusions

In a diverse RA cohort, overall methotrexate knowledge was poor. Older age and limited proficiency in English were significant correlates of poor knowledge. Identification of language barriers and improved clinician-patient communication around methotrexate dosing and side effects may lead to improved safety and enhanced benefits of this commonly used RA medication.     

Driving factors of a vegetation shift from Scots pine to pubescent oak in dry Alpine forests

An increasing number of studies have reported on forest declines and vegetation shifts triggered by drought. In the Swiss Rhone valley (Valais), one of the driest inner‐Alpine regions, the species composition in low elevation forests is changing: The sub‐boreal Scots pine (Pinus sylvestris L.) dominating the dry forests is showing high mortality rates. Concurrently the sub‐Mediterranean pubescent oak (Quercus pubescens Willd.) has locally increased in abundance. However, it remains unclear whether this local change in species composition is part of a larger‐scale vegetation shift. To study variability in mortality and regeneration in these dry forests we analysed data from the Swiss national forest inventory (NFI) on a regular grid between 1983 and 2003, and combined it with annual mortality data from a monitoring site. Pine mortality was found to be highest at low elevation (below 1000 m a.s.l.). Annual variation in pine mortality was correlated with a drought index computed for the summer months prior to observed tree death. A generalized linear mixed‐effects model indicated for the NFI data increased pine mortality on dryer sites with high stand competition, particularly for small‐diameter trees. Pine regeneration was low in comparison to its occurrence in the overstorey, whereas oak regeneration was comparably abundant. Although both species regenerated well at dry sites, pine regeneration was favoured at cooler sites at higher altitude and oak regeneration was more frequent at warmer sites, indicating a higher adaptation potential of oaks under future warming. Our results thus suggest that an extended shift in species composition is actually occurring in the pine forests in the Valais. The main driving factors are found to be climatic variability, particularly drought, and variability in stand structure and topography. Thus, pine forests at low elevations are developing into oak forests with unknown consequences for these ecosystems and their goods and services.     

Rare Variants in PLXNA4 and Parkinson’s Disease

Approximately 20% of individuals with Parkinson’s disease (PD) report a positive family history. Yet, a large portion of causal and disease-modifying variants is still unknown. We used exome sequencing in two affected individuals from a family with late-onset familial PD followed by frequency assessment in 975 PD cases and 1014 ethnically-matched controls and linkage analysis to identify potentially causal variants. Based on the predicted penetrance and the frequencies, a variant in PLXNA4 proved to be the best candidate and PLXNA4 was screened for additional variants in 862 PD cases and 940 controls, revealing an excess of rare non-synonymous coding variants in PLXNA4 in individuals with PD. Although we cannot conclude that the variant in PLXNA4 is indeed the causative variant, these findings are interesting in the light of a surfacing role of axonal guidance mechanisms in neurodegenerative disorders but, at the same time, highlight the difficulties encountered in the study of rare variants identified by next-generation sequencing in diseases with autosomal dominant or complex patterns of inheritance.     

Aquaporin 2 Mutations in Trypanosoma brucei gambiense Field Isolates Correlate with Decreased Susceptibility to Pentamidine and Melarsoprol

The predominant mechanism of drug resistance in African trypanosomes is decreased drug uptake due to loss-of-function mutations in the genes for the transporters that mediate drug import. The role of transporters as determinants of drug susceptibility is well documented from laboratory-selected Trypanosoma brucei mutants. But clinical isolates, especially of T. b. gambiense, are less amenable to experimental investigation since they do not readily grow in culture without prior adaptation. Here we analyze a selected panel of 16 T. brucei ssp. field isolates that (i) have been adapted to axenic in vitro cultivation and (ii) mostly stem from treatment-refractory cases. For each isolate, we quantify the sensitivity to melarsoprol, pentamidine, and diminazene, and sequence the genomic loci of the transporter genes TbAT1 and TbAQP2. The former encodes the well-characterized aminopurine permease P2 which transports several trypanocides including melarsoprol, pentamidine, and diminazene. We find that diminazene-resistant field isolates of T. b. brucei and T. b. rhodesiense carry the same set of point mutations in TbAT1 that was previously described from lab mutants. Aquaglyceroporin 2 has only recently been identified as a second transporter involved in melarsoprol/pentamidine cross-resistance. Here we describe two different kinds of TbAQP2 mutations found in T. b. gambiense field isolates: simple loss of TbAQP2, or loss of wild-type TbAQP2 allele combined with the formation of a novel type of TbAQP2/3 chimera. The identified mutant T. b. gambiense are 40- to 50-fold less sensitive to pentamidine and 3- to 5-times less sensitive to melarsoprol than the reference isolates. We thus demonstrate for the first time that rearrangements of the TbAQP2/TbAQP3 locus accompanied by TbAQP2 gene loss also occur in the field, and that the T. b. gambiense carrying such mutations correlate with a significantly reduced susceptibility to pentamidine and melarsoprol.     

Comparison of complex modeling strategies for prediction of a binary outcome based on a few,highly correlated predictors

Motivated by a clinical prediction problem, a simulation study was performed to compare different approaches for building risk prediction models. Robust prediction models for hospital survival in patients with acute heart failure were to be derived from three highly correlated blood parameters measured up to four times, with predictive ability having explicit priority over interpretability. Methods that relied only on the original predictors were compared with methods using an expanded predictor space including transformations and interactions. Predictors were simulated as transformations and combinations of multivariate normal variables which were fitted to the partly skewed and bimodally distributed original data in such a way that the simulated data mimicked the original covariate structure. Different penalized versions of logistic regression as well as random forests and generalized additive models were investigated using classical logistic regression as a benchmark. Their performance was assessed based on measures of predictive accuracy, model discrimination, and model calibration. Three different scenarios using different subsets of the original data with different numbers of observations and events per variable were investigated. In the investigated setting, where a risk prediction model should be based on a small set of highly correlated and interconnected predictors, Elastic Net and also Ridge logistic regression showed good performance compared to their competitors, while other methods did not lead to substantial improvements or even performed worse than standard logistic regression. Our work demonstrates how simulation studies that mimic relevant features of a specific data set can support the choice of a good modeling strategy.