RhoA Is Essential for Maintaining Normal Megakaryocyte Ploidy and Platelet Generation

RhoA plays a multifaceted role in platelet biology. During platelet development, RhoA has been proposed to regulate endomitosis, proplatelet formation, and platelet release, in addition to having a role in platelet activation. These processes were previously studied using pharmacological inhibitors in vitro, which have potential drawbacks, such as non-specific inhibition or incomplete disruption of the intended target proteins. Therefore, we developed a conditional knockout mouse model utilizing the CRE-LOX strategy to ablate RhoA, specifically in megakaryocytes and in platelets to determine its role in platelet development. We demonstrated that deleting RhoA in megakaryocytes in vivo resulted in significant macrothrombocytopenia. RhoA-null megakaryocytes were larger, had higher mean ploidy, and exhibited stiff membranes with micropipette aspiration. However, in contrast to the results observed in experiments relying upon pharmacologic inhibitors, we did not observe any defects in proplatelet formation in megakaryocytes lacking RhoA. Infused RhoA-null megakaryocytes rapidly released platelets, but platelet levels rapidly plummeted within several hours. Our evidence supports the hypothesis that changes in membrane rheology caused infused RhoA-null megakaryocytes to prematurely release aberrant platelets that were unstable. These platelets were cleared quickly from circulation, which led to the macrothrombocytopenia. These observations demonstrate that RhoA is critical for maintaining normal megakaryocyte development and the production of normal platelets.     

Regulating Emotions during Difficult Multiattribute Decision Making: The Role of Pre-Decisional Coherence Shifting

Almost all real-life decisions entail attribute conflict; every serious choice alternative is better than its competitors on some attribute dimensions but worse on others. In pre-decisional “coherence shifting,” the decision maker gradually softens that conflict psychologically to the point where one alternative is seen as dominant over its competitors, or nearly so. Specifically, weaknesses of the eventually chosen alternative come to be perceived as less severe and less important while its strengths seem more desirable and significant. The research described here demonstrates that difficult multiattribute decision problems are aversive and that pre-decisional coherence shifting aids individuals in regulating that emotional discomfort. Across three studies, attribute conflict was confirmed to be aversive (Study 1), and skin conductance responses and ratings of decision difficulty both decreased in participants who coherence shifted (Study 2). Coherence shifting was also diminished among decision makers who were depleted of regulatory resources, known to be required for common emotion regulation mechanisms. Further, coherence shifting was shown to be relatively common among people who reported strong suppression tendencies in everyday emotion regulation (Study 3). Overall, the data suggest that, at least in part, coherence shifting serves as a tool that helps decision makers manage the pre-decisional discomfort generated by attribute conflict. Theoretical and practical implications are discussed.     

Extreme obesity reduces bone mineral density: complementary evidence from mice and women

Objective: To evaluate the effects of body adiposity on bone mineral density in the presence and absence of ovarian hormones in female mice and postmenopausal women. Research Methods and Procedures: We assessed percentage body fat, serum leptin levels, and bone mineral density in ovariectomized and non‐ovariectomized C57BL/6 female mice that had been fed various calorically dense diets to induce body weight profiles ranging from lean to very obese. Additionally, we assessed percentage body fat and whole body bone mineral density in 37 overweight and extremely obese postmenopausal women from the Women's Contraceptive and Reproductive Experiences study. Results: In mice, higher levels of body adiposity (>40% body fat) were associated with lower bone mineral density in ovariectomized C57BL/6 female mice. A similar trend was observed in a small sample of postmenopausal women. Discussion: The complementary studies in mice and women suggest that extreme obesity in postmenopausal women may be associated with reduced bone mineral density. Thus, extreme obesity (BMI > 40 kg/m²) may increase the risk for osteopenia and osteoporosis. Given the obesity epidemic in the U.S. and in many other countries, and, in particular, the rising number of extremely obese adult women, increased attention should be drawn to the significant and interrelated public health issues of obesity and osteoporosis.     

PHYLOGENETIC RELATIONSHIPS AMONG PAPER WASP SOCIAL PARASITES AND THEIR HOSTS (HYMENOPTERA: VESPIDAE; POLISTINAE)

Abstract— Cladistic analyses of data from allozyme polymorphisms in paper wasp social parasites and their hosts do not support the hypothesis that social parasites are most closely related to their hosts. Electrophoretic data are adduced for nine species of Polistes , including all three known species of social parasites ( Sulcopolistes ) and their hosts. Three different coding methods are investigated; in no case do the social parasites cluster most closely with their hosts. Rather, there is limited evidence that they form a monophyletic group. However, formal taxonomic recognition of Sulcopolistes is not justified, as it renders Polistes sensu stricto paraphyletic. Although the social parasites are not most closely related to their hosts, hosts and parasites belong in the same subgenus and share many characteristics that may have facilitated the exploitation and deception practised by the parasites on the hosts.     

IN SEARCH OF A METHOD FOR CLADISTIC BIOGEOGRAPHY: AN EMPIRICAL COMPARISON OF COMPONENT ANALYSIS, BROOKS PARSIMONY ANALYSIS, AND THREE-AREA STATEMENTS

Abstract— Three quantitative cladistic biogeographic methods, namely, component analysis, Brooks parsimony analysis (BPA), and three-area statements (TAS) have been proposed for obtaining general area cladograms from taxon-area cladograms. Available programs implementing these methods include COMPONENT versions 1.5 and 2.0 for component analysis, TAS for three-area statements, and Hennig86 for analysing matrices for both three-area statements and BPA. Ten different data sets were analysed with these programs and items of error were used to evaluate the general area cladograms obtained. None of the computer implementations of the methods compared proved to be more effective than the others.
"…all methodologies, even the most obvious ones, have their limits…"
Feyerabend (1993:231)     

Predicting drug polypharmacology from cell morphology readouts using variational autoencoder latent space arithmetic

A variational autoencoder (VAE) is a machine learning algorithm, useful for generating a compressed and interpretable latent space. These representations have been generated from various biomedical data types and can be used to produce realistic-looking simulated data. However, standard vanilla VAEs suffer from entangled and uninformative latent spaces, which can be mitigated using other types of VAEs such as β-VAE and MMD-VAE. In this project, we evaluated the ability of VAEs to learn cell morphology characteristics derived from cell images. We trained and evaluated these three VAE variants—Vanilla VAE, β-VAE, and MMD-VAE—on cell morphology readouts and explored the generative capacity of each model to predict compound polypharmacology (the interactions of a drug with more than one target) using an approach called latent space arithmetic (LSA). To test the generalizability of the strategy, we also trained these VAEs using gene expression data of the same compound perturbations and found that gene expression provides complementary information. We found that the β-VAE and MMD-VAE disentangle morphology signals and reveal a more interpretable latent space. We reliably simulated morphology and gene expression readouts from certain compounds thereby predicting cell states perturbed with compounds of known polypharmacology. Inferring cell state for specific drug mechanisms could aid researchers in developing and identifying targeted therapeutics and categorizing off-target effects in the future.