3D Microstructural Architecture of Muscle Attachments in Extant and Fossil Vertebrates Revealed by Synchrotron Microtomography

Background

Firm attachments binding muscles to skeleton are crucial mechanical components of the vertebrate body. These attachments (entheses) are complex three-dimensional structures, containing distinctive arrangements of cells and fibre systems embedded in the bone, which can be modified during ontogeny. Until recently it has only been possible to obtain 2D surface and thin section images of entheses, leaving their 3D histology largely unstudied except by extrapolation from 2D data. Entheses are frequently preserved in fossil bones, but sectioning is inappropriate for rare or unique fossil material.

Methodology/Principal Findings

Here we present the first non-destructive 3D investigation, by propagation phase contrast synchrotron microtomography (PPC-SRµCT), of enthesis histology in extant and fossil vertebrates. We are able to identify entheses in the humerus of the salamander Desmognathus from the organization of bone-cell lacunae and extrinsic fibres. Statistical analysis of the lacunae differentiates types of attachments, and the orientation of the fibres, reflect the approximate alignment of the muscle. Similar histological structures, including ontogenetically related pattern changes, are perfectly preserved in two 380 million year old fossil vertebrates, the placoderm Compagopiscis croucheri and the sarcopterygian fish Eusthenopteron foordi.

Conclusions/Significance

We are able to determine the position of entheses in fossil vertebrates, the approximate orientation of the attached muscles, and aspects of their ontogenetic histories, from PPC-SRµCT data. Sub-micron microtomography thus provides a powerful tool for studying the structure, development, evolution and palaeobiology of muscle attachments.     

827Spatio-Temporal Quantification of FRET in Living Cells by Fast Time-Domain FLIM: A Comparative Study of Non-Fitting Methods

Förster Resonance Energy Transfer (FRET) measured with Fluorescence Lifetime Imaging Microscopy (FLIM) is a powerful technique to investigate spatio-temporal regulation of protein-protein interactions in living cells. When using standard fitting methods to analyze time domain FLIM, the correct estimation of the FRET parameters requires a high number of photons and therefore long acquisition times which are incompatible with the observation of dynamic protein-protein interactions. Recently, non-fitting strategies have been developed for the analysis of FLIM images: the polar plot or “phasor” and the minimal fraction of interacting donor mf_D. We propose here a novel non-fitting strategy based on the calculation of moments. We then compare the performance of these three methods when shortening the acquisition time: either by reducing the number of counted photons N or the number of temporal channels N_ch, which is particularly adapted for the original fast-FLIM prototype presented in this work that employs the time gated approach. Based on theoretical calculations, Monte Carlo simulations and experimental data, we determine the domain of validity of each method. We thus demonstrate that the polar approach remains accurate for a large range of conditions (low N, N_ch or small fractions of interacting donor f_D). The validity domain of the moments method is more restricted (not applicable when f_D<0.25 or when N_ch = 4) but it is more precise than the polar approach. We also demonstrate that the mf_D is robust in all conditions and it is the most precise strategy; although it does not strictly provide the fraction of interacting donor. We show using the fast-FLIM prototype (with an acquisition rate up to 1 Hz) that these non-fitting strategies are very powerful for on-line analysis on a standard computer and thus for quantifying automatically the spatio-temporal activation of Rac-GTPase in living cells by FRET.     

Widespread Occurrence of Chemical Residues in Beehive Matrices from Apiaries Located in Different Landscapes of Western France

Background

The honey bee, Apis mellifera, is frequently used as a sentinel to monitor environmental pollution. In parallel, general weakening and unprecedented colony losses have been reported in Europe and the USA, and many factors are suspected to play a central role in these problems, including infection by pathogens, nutritional stress and pesticide poisoning. Honey bee, honey and pollen samples collected from eighteen apiaries of western France from four different landscape contexts during four different periods in 2008 and in 2009 were analyzed to evaluate the presence of pesticides and veterinary drug residues.

Methodology/Findings

A multi-residue analysis of 80 compounds was performed using a modified QuEChERS method, followed by GC-ToF and LC−MS/MS. The analysis revealed that 95.7%, 72.3% and 58.6% of the honey, honey bee and pollen samples, respectively, were contaminated by at least one compound. The frequency of detection was higher in the honey samples (n = 28) than in the pollen (n = 23) or honey bee (n = 20) samples, but the highest concentrations were found in pollen. Although most compounds were rarely found, some of the contaminants reached high concentrations that might lead to adverse effects on bee health. The three most frequent residues were the widely used fungicide carbendazim and two acaricides, amitraz and coumaphos, that are used by beekeepers to control Varroa destructor. Apiaries in rural-cultivated landscapes were more contaminated than those in other landscape contexts, but the differences were not significant. The contamination of the different matrices was shown to be higher in early spring than in all other periods.

Conclusions/Significance

Honey bees, honeys and pollens are appropriate sentinels for monitoring pesticide and veterinary drug environmental pollution. This study revealed the widespread occurrence of multiple residues in beehive matrices and suggests a potential issue with the effects of these residues alone or in combination on honey bee health.     

Combined Approaches for Drug Design Points the Way to Novel Proline Racemase Inhibitor Candidates to Fight Chagas’ Disease

Chagas’ disease is caused by Trypanosoma cruzi, a protozoan transmitted to humans by blood-feeding insects, blood transfusion or congenitally. Previous research led us to discover a parasite proline racemase (TcPRAC) and to establish its validity as a target for the design of new chemotherapies against the disease, including its chronic form. A known inhibitor of proline racemases, 2-pyrrolecarboxylic acid (PYC), is water-insoluble. We synthesized soluble pyrazole derivatives, but they proved weak or inactive TcPRAC inhibitors. TcPRAC catalytic site is too small and constrained when bound to PYC to allow efficient search for new inhibitors by virtual screening. Forty-nine intermediate conformations between the opened enzyme structure and the closed liganded one were built by calculating a transition path with a method we developed. A wider range of chemical compounds could dock in the partially opened intermediate active site models in silico. Four models were selected for known substrates and weak inhibitors could dock in them and were used to screen chemical libraries. Two identified soluble compounds, (E)-4-oxopent-2-enoic acid (OxoPA) and its derivative (E)-5-bromo-4-oxopent-2-enoic acid (Br-OxoPA), are irreversible competitive inhibitors that presented stronger activity than PYC on TcPRAC. We show here that increasing doses of OxoPA and Br-OxoPA hamper T. cruzi intracellular differentiation and fate in mammalian host cells. Our data confirm that through to their binding mode, these molecules are interesting and promising as lead compounds for the development of chemotherapies against diseases where active proline racemases play essential roles.     

Plasmonic Enhancement by a Continuous Gold Underlayer: Application to SERS Sensing

Plasmonics - In this paper, we report on an improved enhancement of the surface-enhanced Raman scattering (SERS) effect. Such improvement is obtained by using a continuous gold film (underlayer),...     

Sexual Dimorphism in Circadian Physiology Is Altered in LXRα Deficient Mice

The mammalian circadian timing system coordinates key molecular, cellular and physiological processes along the 24-h cycle. Accumulating evidence suggests that many clock-controlled processes display a sexual dimorphism. In mammals this is well exemplified by the difference between the male and female circadian patterns of glucocorticoid hormone secretion and clock gene expression. Here we show that the non-circadian nuclear receptor and metabolic sensor Liver X Receptor alpha (LXRα) which is known to regulate glucocorticoid production in mice modulates the sex specific circadian pattern of plasma corticosterone. Lxrα^-/- males display a blunted corticosterone profile while females show higher amplitude as compared to wild type animals. Wild type males are significantly slower than females to resynchronize their locomotor activity rhythm after an 8 h phase advance but this difference is abrogated in Lxrα^-/- males which display a female-like phenotype. We also show that circadian expression patterns of liver 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) and Phosphoenolpyruvate carboxykinase (Pepck) differ between sexes and are differentially altered in Lxrα^-/- animals. These changes are associated with a damped profile of plasma glucose oscillation in males but not in females. Sex specific alteration of the insulin and leptin circadian profiles were observed in Lxα^-/- females and could be explained by the change in corticosterone profile. Together this data indicates that LXRα is a determinant of sexually dimorphic circadian patterns of key physiological parameters. The discovery of this unanticipated role for LXRα in circadian physiology underscores the importance of addressing sex differences in chronobiology studies and future LXRα targeted therapies.     

How to Build a Standardized Country-Specific Environmental Food Database for Nutritional Epidemiology Studies

There is a lack of standardized country-specific environmental data to combine with nutritional and dietary data for assessing the environmental impact of individual diets in epidemiology surveys, which are consequently reliant on environmental food datasets based on values retrieved from a heterogeneous literature. The aim of this study was to compare and assess the relative strengths and limits of a database of food greenhouse gas emissions (GHGE) values estimated with a hybrid method combining input/output and LCA approaches, with a dataset of GHGE values retrieved from the literature. France is the geographical perimeter considered in this study, but the methodology could be applied to other countries. The GHGE of 402 foodstuffs, representative of French diet, were estimated using the hybrid method. In parallel, the GHGE of individual foods were collected from existing literature. Median per-food-category GHGE values from the hybrid method and the reviewed literature were found to correlate strongly (Spearman correlation was 0.83), showing similar rankings of food categories. Median values were significantly different for only 5 (out of 29) food categories, including the ruminant meats category for which the hybrid method gave lower estimates than those from existing literature. Analysis also revealed that literature values came from heterogeneous studies that were not always sourced and that were conducted under different LCA modeling hypotheses. In contrast, the hybrid method helps build reliably-sourced, representative national standards for product-based datasets. We anticipate this hybrid method to be a starting point for better environmental impact assessments of diets.     

Rigorous Training of Dogs Leads to High Accuracy in Human Scent Matching-To-Sample Performance

Human scent identification is based on a matching-to-sample task in which trained dogs are required to compare a scent sample collected from an object found at a crime scene to that of a suspect. Based on dogs’ greater olfactory ability to detect and process odours, this method has been used in forensic investigations to identify the odour of a suspect at a crime scene. The excellent reliability and reproducibility of the method largely depend on rigor in dog training. The present study describes the various steps of training that lead to high sensitivity scores, with dogs matching samples with 90% efficiency when the complexity of the scents presented during the task in the sample is similar to that presented in the in lineups, and specificity reaching a ceiling, with no false alarms in human scent matching-to-sample tasks. This high level of accuracy ensures reliable results in judicial human scent identification tests. Also, our data should convince law enforcement authorities to use these results as official forensic evidence when dogs are trained appropriately.     

Where Have All the Rodents Gone? The Effects of Attrition in Experimental Research on Cancer and Stroke

Given small sample sizes, loss of animals in preclinical experiments can dramatically alter results. However, effects of attrition on distortion of results are unknown. We used a simulation study to analyze the effects of random and biased attrition. As expected, random loss of samples decreased statistical power, but biased removal, including that of outliers, dramatically increased probability of false positive results. Next, we performed a meta-analysis of animal reporting and attrition in stroke and cancer. Most papers did not adequately report attrition, and extrapolating from the results of the simulation data, we suggest that their effect sizes were likely overestimated.

Where have all the rodents gone?Ooh ooh, ooh ooh, oohTo non-random attrition, every oneWhen will they ever learn?—with apologies to Pete Seeger, 1955