Immunohistochemical determination of estrogen receptor-α in canine vaginal biopsies throughout proestrus,estrus, and early diestrus

The aim of this study was to describe the presence of estrogen receptor-α (ERα) in several vaginal histological compartments in healthy adult bitches throughout three estrous cycle stages (proestrus, estrus, and early diestrus) and to relate ERα presence with serum progesterone and estradiol-17β concentrations. For this purpose, serial blood samples and vaginal biopsies were taken from five bitches every 48 hours, starting at the clinical onset of proestrus, marked by the beginning of serosanguineous vaginal secretion. Serum progesterone and estradiol-17β concentrations were determined by RIA, whereas detection of steroid receptors was carried out through immunohistochemistry. Subjective image analysis was conducted by two independent observers in the following histological compartments: superficial, intermediate, and deep epithelia and superficial (loose) and deep (dense) stroma (connective tissue). Nuclear ERα immunoreactivity was detected in every histological compartment and estrous cycle stage studied. ERα expression varied among histological compartments and during stages of the cycle. Receptor expression was associated with estradiol-17β and progesterone serum profiles. Most relevant cyclic changes were detected in the superficial and deep epithelia and in the dense connective tissue. The highest ERα expression was detected during diestrus, although each compartment had a different pattern throughout the other cycle stages. Thus, vaginal ERα expression in the bitch varied throughout proestrus, estrus, and early diestrus according to the histological compartment involved.     

Integrating across neuroimaging modalities boosts prediction accuracy of cognitive ability

Variation in cognitive ability arises from subtle differences in underlying neural architecture. Understanding and predicting individual variability in cognition from the differences in brain networks requires harnessing the unique variance captured by different neuroimaging modalities. Here we adopted a multi-level machine learning approach that combines diffusion, functional, and structural MRI data from the Human Connectome Project (N = 1050) to provide unitary prediction models of various cognitive abilities: global cognitive function, fluid intelligence, crystallized intelligence, impulsivity, spatial orientation, verbal episodic memory and sustained attention. Out-of-sample predictions of each cognitive score were first generated using a sparsity-constrained principal component regression on individual neuroimaging modalities. These individual predictions were then aggregated and submitted to a LASSO estimator that removed redundant variability across channels. This stacked prediction led to a significant improvement in accuracy, relative to the best single modality predictions (approximately 1% to more than 3% boost in variance explained), across a majority of the cognitive abilities tested. Further analysis found that diffusion and brain surface properties contribute the most to the predictive power. Our findings establish a lower bound to predict individual differences in cognition using multiple neuroimaging measures of brain architecture, both structural and functional, quantify the relative predictive power of the different imaging modalities, and reveal how each modality provides unique and complementary information about individual differences in cognitive function.     

The causes of epistasis in genetic networks

Epistasis refers to the nonadditive interactions between genes in determining phenotypes. Considerable efforts have shown that, even for a given organism, epistasis may vary both in intensity and sign. Recent comparative studies supported that the overall sign of epistasis switches from positive to negative as the complexity of an organism increases, and it has been hypothesized that this change shall be a consequence of the underlying gene network properties. Why should this be the case? What characteristics of genetic networks determine the sign of epistasis? Here we show, by evolving genetic networks that differ in their complexity and robustness against perturbations but that perform the same tasks, that robustness increased with complexity and that epistasis was positive for small nonrobust networks but negative for large robust ones. Our results indicate that robustness and negative epistasis emerge as a consequence of the existence of redundant elements in regulatory structures of genetic networks and that the correlation between complexity and epistasis is a byproduct of such redundancy, allowing for the decoupling of epistasis from the underlying network complexity.     

Assessing the short‐term effects of capture,handling and tagging of sandgrouse

Capturing and marking free‐living birds permits the study of important aspects of their biology but may have undesirable effects. Bird welfare should be a primary concern, so it is necessary to evaluate and minimize any adverse effects of procedures used. We assess short‐term effects associated with the capture, handling and tagging with backpack‐mounted transmitters of Pin‐tailed Pterocles alchata and Black‐bellied Pterocles orientalis Sandgrouse, steppe birds of conservation concern. There was a significantly higher mortality (15%) during the first week after capture than during the following weeks (< 2.5%) in Pin‐tailed Sandgrouse, but no significant temporal mortality pattern in Black‐bellied Sandgrouse. In Pin‐tailed Sandgrouse, mortality rate during the first week increased with increasing relative transmitter and harness weight regardless of season, and with increasing handling time during the breeding season. There were no significant differences in mortality rate between study areas, type of tag, sex or age or an effect of restraint time. These results suggest the use of lighter transmitters (< 3% of the bird's weight) and a reduction of handling time (< 20 min), particularly during the breeding season, as essential improvements in procedure to reduce the mortality risk associated with the capture, handling and tagging of these vulnerable species.     

Dynamic emergence of the mesenchymal CD44CD24 phenotype in HER2-gene amplified breast cancer cells with de novo resistance to trastuzumab (Herceptin)

Evidence is mounting that the occurrence of the CD44^pos/CD24^neg/low cell population, which contains potential breast cancer (BC) stem cells, could explain BC clinical resistance to HER2-targeted therapies. We investigated whether de novo refractoriness to the anti-HER2 monoclonal antibody trastuzumab (Tzb; Herceptin) may relate to the dynamic regulation of the mesenchymal CD44^pos/CD24^neg/low phenotype in HER2-positive BC. We observed that the subpopulation of Tzb-refractory JIMT-1 BC cells exhibiting CD44^pos/CD24^neg/low-surface markers switched with time. Low-passage JIMT-1 cell cultures were found to spontaneously contain ∼10% of cells bearing the CD44^pos/CD24^neg/low immunophenotype. Late-passage (>60) JIMT-1 cultures accumulated ∼80% of CD44^pos/CD24^neg/low cells and closely resembled the CD44^pos/CD24^neg/low-enriched (∼85%) cell population constitutively occurring in HER2-negative MDA-MB-231 mesenchymal BC cells. Dynamic expression of mesenchymal markers was not limited to CD44/CD24 because high-passages of JIMT-1 cells exhibited also reduced expression of the HER2 protein and over-secretion of pro-invasive/metastatic chemokines and metalloproteases. Accordingly, late-passage JIMT-1 cells displayed an exacerbated migratogenic phenotype in plastic, collagen, and fibronectin substrates. Intrinsic genetic plasticity to efficiently drive the emergence of the CD44^pos/CD24^neg/low mesenchymal phenotype may account for de novo resistance to HER2 targeting therapies in basal-like BC carrying HER2 gene amplification.     

The metallo-beta-lactamase GOB is a mono-Zn(II) enzyme with a novel active site

Metallo-beta-lactamases (MbetaLs) are zinc-dependent enzymes able to hydrolyze and inactivate most beta-lactam antibiotics. The large diversity of active site structures and metal content among MbetaLs from different sources has limited the design of a pan-MbetaL inhibitor. Here we report the biochemical and biophysical characterization of a novel MbetaL, GOB-18, from a clinical isolate of a Gram-negative opportunistic pathogen, Elizabethkingia meningoseptica. Different spectroscopic techniques, three-dimensional modeling, and mutagenesis experiments, reveal that the Zn(II) ion is bound to Asp120, His121, His263, and a solvent molecule, i.e. in the canonical Zn2 site of dinuclear MbetaLs. Contrasting all other related MbetaLs, GOB-18 is fully active against a broad range of beta-lactam substrates using a single Zn(II) ion in this site. These data further enlarge the structural diversity of MbetaLs.     

A consolidated approach to analyzing data from high-throughput protein microarrays with an application to immune response profiling in humans.

Motivation: DNA microarrays are a well-known and established technology in biological and pharmaceutical research providing a wealth of information essential for understanding biological processes and aiding drug development. Protein microarrays are quickly emerging as a follow-up technology, which will also begin to experience rapid growth as the challenges in protein to spot methodologies are overcome. Like DNA microarrays, their protein counterparts produce large amounts of data that must be suitably analyzed in order to yield meaningful information that should eventually lead to novel drug targets and biomarkers. Although the statistical management of DNA microarray data has been well described, there is no available report that offers a successful consolidated approach to the analysis of high-throughput protein microarray data. We describe the novel application of a statistical methodology to analyze the data from an immune response profiling assay using human protein microarray with over 5000 proteins on each chip.     

A Tolerant Behavior in Salt-Sensitive Tomato Plants can be Mimicked by Chemical Stimuli

Lycopersicon esculentum plants exhibit increased salt stress tolerance following treatment with adipic acid monoethylester and 1,3-diaminepropane (DAAME), known as an inducer of resistance against biotic stress in tomato and pepper. For an efficient water and nutrient uptake, plants should adapt their water potential to compensate a decrease in water soil potential produced by salt stress. DAAME-treated plants showed a faster and stronger water potential reduction and an enhanced proline accumulation. Salinity-induced oxidative stress was also ameliorated by DAAME treatments. Oxidative membrane damage and ethylene emission were both reduced in DAAME-treated plants. This effect is probably a consequence of an increase of both non-enzymatic antioxidant activity as well as peroxidase activity. DAAME-mediated tolerance resulted in an unaltered photosynthetic rate and a stimulation of the decrease in transpiration under stress conditions without a cost in growth due to salt stress. The reduction in transpiration rate was concomitant with a reduction in phytotoxic Na⁺ and Cl⁻ accumulation under saline stress. Interestingly, the ABA deficient tomato mutant sitiens was insensitive to DAAME-induced tolerance following NaCl stress exposure. Additionally, DAAME treatments increased the ABA content of leaves, therefore, an intact ABA signalling pathway seems to be important to express DAAME-induced salt tolerance. Here, we show a possibility of enhance tomato stress tolerance by chemical induction of the major plant defences against salt stress. DAAME-induced tolerance against salt stress could be complementary to or share elements with induced resistance against biotic stress. This might be the reason for the observed wide spectrum of effectiveness of this compound.Key Words: adipic acid monoethyl ester, 1,3-diaminepropane, Lycopersicon esculentum, salt stress, oxidative stress, ethylene, chemical induced tolerance