Genome‐wide tests for introgression between cactophilic Drosophila implicate a role of inversions during speciation

Models of speciation‐with‐gene‐flow have shown that the reduction in recombination between alternative chromosome arrangements can facilitate the fixation of locally adaptive genes in the face of gene flow and contribute to speciation. However, it has proven frustratingly difficult to show empirically that inversions have reduced gene flow and arose during or shortly after the onset of species divergence rather than represent ancestral polymorphisms. Here, we present an analysis of whole genome data from a pair of cactophilic fruit flies, Drosophila mojavensis and D. arizonae, which are reproductively isolated in the wild and differ by several large inversions on three chromosomes. We found an increase in divergence at rearranged compared to colinear chromosomes. Using the density of divergent sites in short sequence blocks we fit a series of explicit models of species divergence in which gene flow is restricted to an initial period after divergence and may differ between colinear and rearranged parts of the genome. These analyses show that D. mojavensis and D. arizonae have experienced postdivergence gene flow that ceased around 270 KY ago and was significantly reduced in chromosomes with fixed inversions. Moreover, we show that these inversions most likely originated around the time of species divergence which is compatible with theoretical models that posit a role of inversions in speciation with gene flow.     

Reduced D2/D3 Receptor Binding of Extrastriatal and Striatal Regions in Temporal Lobe Epilepsy

Objective

Dopamine is an endogenous neuromodulator in cortical circuits and the basal ganglia. In animal models of temporal lobe epilepsy (TLE), seizure threshold is modulated to some extent by dopamine, with D1-receptors having a pro- and D2-receptors an anticonvulsant effect. We aimed to extend our previously reported results on decreased D2/D3 receptor binding in the lateral epileptogenic temporal lobe and to correlate them with demographic and seizure variables to gain a more comprehensive understanding of the underlying involvement of the dopaminergic system in the epileptogenesis of TLE.

Methods

To quantify D2/D3 receptor binding, we studied 21 patients with TLE and hippocampal sclerosis (13 left- and eight right-sided) and 18 controls using PET with the high-affinity dopamine D2/D3-receptor ligand ¹⁸F-Fallypride to image striatal and extrastriatal binding. TLE was defined by interictal and ictal video-EEG, MRI and ¹⁸F-Fluorodeoxyglucose PET. Voxel-based statistical and regions-of-interest analyses were performed.

Results

¹⁸F-Fallypride binding potential was significantly reduced in the affected temporal lobe and bilateral putamen. A positive correlation between age at onset of epilepsy and [¹⁸F]FP BP_nd (binding potential non-displaceable) in temporal regions on the epileptogenic side was found, as well as a negative correlation between epilepsy duration and [¹⁸F]FP BP_nd in the temporal pole on the epileptogenic side and a positive correlation between the estimated number of lifetime GTCS and [¹⁸F]FP BP_nd in the hippocampus on the epileptogenic side.

Significance

The areas of reduced D2/D3 receptor availability correspond to “the irritative zone” surrounding the epileptogenic area. Moreover, reduced D2/D3 receptor availability was detectable in the basal ganglia, which are suspected to be involved in a control circuit for epileptic seizures. The correlational analysis additionally suggests that increased epilepsy duration leads to increasing impairment of the dopaminergic system.     

Axial Length Measurement Failure Rates with the IOLMaster and Lenstar LS 900 in Eyes with Cataract

Purpose

To evaluate axial length (AL) measurement failure rate with the IOLMaster (Carl Zeiss AG, Germany) and Lenstar LS 900 (Haag-Streit AG, Switzerland) in eyes with cataract.

Methods

Two hundred and ninety-six eyes of 170 patients with cataract were enrolled. Cataract type and severity were graded using the Lens Opacities Classification System III (LOCS III) and AL measurements were attempted with IOLMaster (version 5.4) and Lenstar LS 900 (version 1.1). Chi-squared analysis was used to assess if the difference in AL measurement acquisition rate was statistically significant between the two devices. The association of the different cataract types and severity with the AL measurement acquisition rate was evaluated with logistic regression analysis.

Results

AL measurements were obtained in 184 eyes (62.16%) using the IOLMaster and 191 eyes (64.53%) using the Lenstar, which corresponds to a failure rate of 37.84% and 35.47% respectively. Chi-square analysis indicated no significant difference between the Lenstar and IOLMaster for AL measurement failure rate (x² = 0.356, P = 0.550). Logistic regression analysis indicated no association between acquisition rates and cortical or nuclear cataracts with either device. There was a statistically significant association between acquisition rates and increasing severity of posterior subcapsular cataracts with the IOLMaster (β = -1.491, P<0.001) and Lenstar LS 900 (β = -1.507, P<0.001).

Conclusion

The IOLMaster and Lenstar LS 900 have similar AL measurement failure rates (35–38%) for Chinese public hospital cataract patients. Increasing severity of posterior subcapsular cataracts was problematic for both devices.     

Predicting Cognitive Function from Clinical Measures of Physical Function and Health Status in Older Adults

Introduction

Current research suggests that the neuropathology of dementia—including brain changes leading to memory impairment and cognitive decline—is evident years before the onset of this disease. Older adults with cognitive decline have reduced functional independence and quality of life, and are at greater risk for developing dementia. Therefore, identifying biomarkers that can be easily assessed within the clinical setting and predict cognitive decline is important. Early recognition of cognitive decline could promote timely implementation of preventive strategies.

Methods

We included 89 community-dwelling adults aged 70 years and older in our study, and collected 32 measures of physical function, health status and cognitive function at baseline. We utilized an L1–L2 regularized regression model (elastic net) to identify which of the 32 baseline measures were strongly predictive of cognitive function after one year. We built three linear regression models: 1) based on baseline cognitive function, 2) based on variables consistently selected in every cross-validation loop, and 3) a full model based on all the 32 variables. Each of these models was carefully tested with nested cross-validation.

Results

Our model with the six variables consistently selected in every cross-validation loop had a mean squared prediction error of 7.47. This number was smaller than that of the full model (115.33) and the model with baseline cognitive function (7.98). Our model explained 47% of the variance in cognitive function after one year.

Discussion

We built a parsimonious model based on a selected set of six physical function and health status measures strongly predictive of cognitive function after one year. In addition to reducing the complexity of the model without changing the model significantly, our model with the top variables improved the mean prediction error and R-squared. These six physical function and health status measures can be easily implemented in a clinical setting.     

The impact of free or standardized lifestyle and urine sampling protocol on metabolome recognition accuracy

Urine contains a clear individual metabolic signature, although embedded within a large daily variability. Given the potential of metabolomics to monitor disease onset from deviations from the “healthy” metabolic state, we have evaluated the effectiveness of a standardized lifestyle in reducing the “metabolic” noise. Urine was collected from 24 (5 men and 19 women) healthy volunteers over a period of 10 days: phase I, days 1–7 in a real-life situation; phase II, days 8–10 in a standardized diet and day 10 plus exercise program. Data on dietary intake and physical activity have been analyzed by a nation-specific software and monitored by published protocols. Urine samples have been analyzed by ¹H NMR followed by multivariate statistics. The individual fingerprint emerged and consolidated with increasing the number of samples and reaches ~100 % cross-validated accuracy for about 40 samples. Diet standardization reduced both the intra-individual and the interindividual variability; the effect was due to a reduction in the dispersion of the concentration values of several metabolites. Under standardized diet, however, the individual phenotype was still clearly visible, indicating that the individual’s signature was a strong feature of the metabolome. Consequently, cohort studies designed to investigate the relation of individual metabolic traits and nutrition require multiple samples from each participant even under highly standardized lifestyle conditions in order to exploit the analytical potential of metabolomics. We have established criteria to facilitate design of urine metabolomic studies aimed at monitoring the effects of drugs, lifestyle, dietary supplements, and for accurate determination of signatures of diseases.     

Volatiles as Chemosystematic Markers for Distinguishing Closely Related Species within the Pinus mugo Complex

Headspace solid‐phase microextraction (HS‐SPME) coupled to GC/MS analysis was used to identify the constituents of pine‐needle volatiles differentiating three closely‐related pine species within the Pinus mugo complex, i.e., P. uncinata Ramond ex DC., P. uliginosa G.E.Neumann ex Wimm ., and P. mugo Turra . Moreover, chemosystematic markers were proposed for the three analyzed pine species. The major constituents of the pine‐needle volatiles were α‐pinene (28.4%) and bornyl acetate (10.8%) for P. uncinata, δ‐car‐3‐ene (21.5%) and α‐pinene (16.1%) for P. uliginosa, and α‐pinene (20%) and δ‐car‐3‐ene (18.1%) for P. mugo. This study is the first report on the application of the composition of pine‐needle volatiles for the reliable identification of closely‐related pine species within the Pinus mugo complex.     

Inhibition of Bone Morphogenetic Protein Signal Transduction Prevents the Medial Vascular Calcification Associated with Matrix Gla Protein Deficiency

Objective

Matrix Gla protein (MGP) is reported to inhibit bone morphogenetic protein (BMP) signal transduction. MGP deficiency is associated with medial calcification of the arterial wall, in a process that involves both osteogenic transdifferentiation of vascular smooth muscle cells (VSMCs) and mesenchymal transition of endothelial cells (EndMT). In this study, we investigated the contribution of BMP signal transduction to the medial calcification that develops in MGP-deficient mice.

Approach and Results

MGP-deficient mice (MGP^-/-) were treated with one of two BMP signaling inhibitors, LDN-193189 or ALK3-Fc, beginning one day after birth. Aortic calcification was assessed in 28-day-old mice by measuring the uptake of a fluorescent bisphosphonate probe and by staining tissue sections with Alizarin red. Aortic calcification was 80% less in MGP^-/- mice treated with LDN-193189 or ALK3-Fc compared with vehicle-treated control animals (P<0.001 for both). LDN-193189-treated MGP^-/- mice survived longer than vehicle-treated MGP^-/- mice. Levels of phosphorylated Smad1/5 and Id1 mRNA (markers of BMP signaling) did not differ in the aortas from MGP^-/- and wild-type mice. Markers of EndMT and osteogenesis were increased in MGP^-/- aortas, an effect that was prevented by LDN-193189. Calcification of isolated VSMCs was also inhibited by LDN-193189.

Conclusions

Inhibition of BMP signaling leads to reduced vascular calcification and improved survival in MGP^-/- mice. The EndMT and osteogenic transdifferentiation associated with MGP deficiency is dependent upon BMP signaling. These results suggest that BMP signal transduction has critical roles in the development of vascular calcification in MGP-deficient mice.     

AUREMOL-RFAC-3D,combination of R-factors and their use for automated quality assessment of protein solution structures

We present here the computer program AUREMOL-RFAC-3D that is a generalization of the previously published program RFAC for the fully automated estimation of residual indices (R-factors) from 2D NOESY spectra. It is part of the larger AUREMOL software package (www.auremol.de). RFAC-3D calculates R-factors directly from two-dimensional homonuclear NOESY spectra as well as from three-dimensional ¹⁵N or ¹³C edited NOESY-HSQC spectra and thus extends the application range to larger proteins. The fully automated method includes automated peak picking and integration, a Bayesian noise and artifact recognition and the use of the complete relaxation matrix formalism. To enhance the reliability of the calculated R-factors the method is also generalized to calculate combined R-factors from a set of 2D and 3D-spectra. For an optimal combination of the information derived from different sources a plausible formalism had to be derived. In addition, we present a novel direct R-factors based measure that correlates an R-factors as defined in this paper to the root mean square deviation of the actual structure from the optimal structure. The new program has been successfully tested on the histidine containing phosphocarrier protein (HPr) from Staphylococcus carnosus and on the Ras-binding domain (RBD) of the Ral guanine-nucleotide dissociation stimulation factor (RalGDS).