Developmental and Lactational Exposure to Dieldrin Alters Mammary Tumorigenesis in Her2/neu Transgenic Mice

Breast cancer is the most common cancer in Western women and while its precise etiology is unknown, environmental factors are thought to play a role. The organochlorine pesticide dieldrin is a persistent environmental toxicant thought to increase the risk of breast cancer and reduce survival in the human population. The objective of this study was to define the effect of developmental exposure to environmentally relevant concentrations of dieldrin, on mammary tumor development in the offspring. Sexually mature FVB-MMTV/neu female mice were treated with vehicle (corn oil), or dieldrin (0.45, 2.25, and 4.5 µg/g body weight) daily by gavage for 5 days prior to mating and then once weekly throughout gestation and lactation until weaning. Dieldrin concentrations were selected to produce serum levels representative of human background body burdens, occupational exposure, and overt toxicity. Treatment had no effect on litter size, birth weight or the number of pups surviving to weaning. The highest dose of dieldrin significantly increased the total tumor burden and the volume and number of tumors found in the thoracic mammary glands. Increased mRNA and protein expression of the neurotrophin BDNF and its receptor TrkB was increased in tumors from the offspring of dieldrin treated dams. This study indicates that developmental exposure to the environmental contaminant dieldrin causes increased tumor burden in genetically predisposed mice. Dieldrin exposure also altered the expression of BNDF and TrkB, novel modulators of cancer pathogenesis

oA novel nonparametric approach for estimating cut-offs in continuous risk indicators with application to diabetes epidemiology

<p>Abstract</p> <p>Background</p> <p>Epidemiological and clinical studies, often including anthropometric measures, have established obesity as a major risk factor for the development of type 2 diabetes. Appropriate cut-off values for anthropometric parameters are necessary for prediction or decision purposes. The cut-off corresponding to the Youden-Index is often applied in epidemiology and biomedical literature for dichotomizing a continuous risk indicator.</p> <p>Methods</p> <p>Using data from a representative large multistage longitudinal epidemiological study in a primary care setting in Germany, this paper explores a novel approach for estimating optimal cut-offs of anthropomorphic parameters for predicting type 2 diabetes based on a discontinuity of a regression function in a nonparametric regression framework.</p> <p>Results</p> <p>The resulting cut-off corresponded to values obtained by the Youden Index (maximum of the sum of sensitivity and specificity, minus one), often considered the optimal cut-off in epidemiological and biomedical research. The nonparametric regression based estimator was compared to results obtained by the established methods of the Receiver Operating Characteristic plot in various simulation scenarios and based on bias and root mean square error, yielded excellent finite sample properties.</p> <p>Conclusion</p> <p>It is thus recommended that this nonparametric regression approach be considered as valuable alternative when a continuous indicator has to be dichotomized at the Youden Index for prediction or decision purposes.</p

A short history of the 5-HT2C receptor: from the choroid plexus to depression, obesity and addiction treatment

This paper is a personal account on the discovery and characterization of the 5-HT2C receptor (first known as the 5- HT1C receptor) over 30 years ago and how it translated into a number of unsuspected features for a G protein-coupled receptor (GPCR) and a diversity of clinical applications. The 5-HT2C receptor is one of the most intriguing members of the GPCR superfamily. Initially referred to as 5-HT1CR, the 5-HT2CR was discovered while studying the pharmacological features and the distribution of [3H]mesulergine-labelled sites, primarily in the brain using radioligand binding and slice autoradiography. Mesulergine (SDZ CU-085), was, at the time, best defined as a ligand with serotonergic and dopaminergic properties. Autoradiographic studies showed remarkably strong [3H]mesulergine-labelling to the rat choroid plexus. [3H]mesulergine-labelled sites had pharmacological properties different from, at the time, known or purported 5-HT receptors. In spite of similarities with 5-HT2 binding, the new binding site was called 5-HT1C because of its very high affinity for 5-HT itself. Within the following 10 years, the 5-HT1CR (later named 5- HT2C) was extensively characterised pharmacologically, anatomically and functionally: it was one of the first 5-HT receptors to be sequenced and cloned. The 5-HT2CR is a GPCR, with a very complex gene structure. It constitutes a rarity in theGPCR family: many 5-HT2CR variants exist, especially in humans, due to RNA editing, in addition to a few 5-HT2CR splice variants. Intense research led to therapeutically active 5-HT2C receptor ligands, both antagonists (or inverse agonists) and agonists: keeping in mind that a number of antidepressants and antipsychotics are 5- HT2CR antagonists/inverse agonists. Agomelatine, a 5-HT2CR antagonist is registered for the treatment of major depression. The agonist Lorcaserin is registered for the treatment of aspects of obesity and has further potential in addiction, especially nicotine/ smoking. There is good evidence that the 5-HT2CR is involved in spinal cord injury-induced spasms of the lower limbs, which can be treated with 5-HT2CR antagonists/inverse agonists such as cyproheptadine or SB206553. The 5-HT2CR may play a role in schizophrenia and epilepsy. Vabicaserin, a 5-HT2CR agonist has been in development for the treatment of schizophrenia and obesity, but was stopped. As is common, there is potential for further indications for 5-HT2CR ligands, as suggested by a number of preclinical and/or genome-wide association studies (GWAS) on depression, suicide, sexual dysfunction, addictions and obesity. The 5-HT2CR is clearly affected by a number of established antidepressants/antipsychotics and may be one of the culprits in antipsychotic-induced weight gain

Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons

An important open problem of computational neuroscience is the generic organization of computations in networks of neurons in the brain. We show here through rigorous theoretical analysis that inherent stochastic features of spiking neurons, in combination with simple nonlinear computational operations in specific network motifs and dendritic arbors, enable networks of spiking neurons to carry out probabilistic inference through sampling in general graphical models. In particular, it enables them to carry out probabilistic inference in Bayesian networks with converging arrows (“explaining away”) and with undirected loops, that occur in many real-world tasks. Ubiquitous stochastic features of networks of spiking neurons, such as trial-to-trial variability and spontaneous activity, are necessary ingredients of the underlying computational organization. We demonstrate through computer simulations that this approach can be scaled up to neural emulations of probabilistic inference in fairly large graphical models, yielding some of the most complex computations that have been carried out so far in networks of spiking neurons

Is the beck anxiety inventory a good tool to assess the severity of anxiety? A primary care study in The Netherlands study of depression and anxiety (NESDA)

<p>Abstract</p> <p>Background</p> <p>Appropriate management of anxiety disorders in primary care requires clinical assessment and monitoring of the severity of the anxiety. This study focuses on the Beck Anxiety Inventory (BAI) as a severity indicator for anxiety in primary care patients with different anxiety disorders (social phobia, panic disorder with or without agoraphobia, agoraphobia or generalized anxiety disorder), depressive disorders or no disorder (controls).</p> <p>Methods</p> <p>Participants were 1601 primary care patients participating in the Netherlands Study of Depression and Anxiety (NESDA). Regression analyses were used to compare the mean BAI scores of the different diagnostic groups and to correct for age and gender.</p> <p>Results</p> <p>Patients with any anxiety disorder had a significantly higher mean score than the controls. A significantly higher score was found for patients with panic disorder and agoraphobia compared to patients with agoraphobia only or social phobia only. BAI scores in patients with an anxiety disorder with a co-morbid anxiety disorder and in patients with an anxiety disorder with a co-morbid depressive disorder were significantly higher than BAI scores in patients with an anxiety disorder alone or patients with a depressive disorder alone. Depressed and anxious patients did not differ significantly in their mean scores.</p> <p>Conclusions</p> <p>The results suggest that the BAI may be used as a severity indicator of anxiety in primary care patients with different anxiety disorders. However, because the instrument seems to reflect the severity of depression as well, it is not a suitable instrument to discriminate between anxiety and depression in a primary care population.</p

Bayesian Integration and Non-Linear Feedback Control in a Full-Body Motor Task

A large number of experiments have asked to what degree human reaching movements can be understood as being close to optimal in a statistical sense. However, little is known about whether these principles are relevant for other classes of movements. Here we analyzed movement in a task that is similar to surfing or snowboarding. Human subjects stand on a force plate that measures their center of pressure. This center of pressure affects the acceleration of a cursor that is displayed in a noisy fashion (as a cloud of dots) on a projection screen while the subject is incentivized to keep the cursor close to a fixed position. We find that salient aspects of observed behavior are well-described by optimal control models where a Bayesian estimation model (Kalman filter) is combined with an optimal controller (either a Linear-Quadratic-Regulator or Bang-bang controller). We find evidence that subjects integrate information over time taking into account uncertainty. However, behavior in this continuous steering task appears to be a highly non-linear function of the visual feedback. While the nervous system appears to implement Bayes-like mechanisms for a full-body, dynamic task, it may additionally take into account the specific costs and constraints of the task

Emergence of Visual Saliency from Natural Scenes via Context-Mediated Probability Distributions Coding

Visual saliency is the perceptual quality that makes some items in visual scenes stand out from their immediate contexts. Visual saliency plays important roles in natural vision in that saliency can direct eye movements, deploy attention, and facilitate tasks like object detection and scene understanding. A central unsolved issue is: What features should be encoded in the early visual cortex for detecting salient features in natural scenes? To explore this important issue, we propose a hypothesis that visual saliency is based on efficient encoding of the probability distributions (PDs) of visual variables in specific contexts in natural scenes, referred to as context-mediated PDs in natural scenes. In this concept, computational units in the model of the early visual system do not act as feature detectors but rather as estimators of the context-mediated PDs of a full range of visual variables in natural scenes, which directly give rise to a measure of visual saliency of any input stimulus. To test this hypothesis, we developed a model of the context-mediated PDs in natural scenes using a modified algorithm for independent component analysis (ICA) and derived a measure of visual saliency based on these PDs estimated from a set of natural scenes. We demonstrated that visual saliency based on the context-mediated PDs in natural scenes effectively predicts human gaze in free-viewing of both static and dynamic natural scenes. This study suggests that the computation based on the context-mediated PDs of visual variables in natural scenes may underlie the neural mechanism in the early visual cortex for detecting salient features in natural scenes

Synaptic Connections of the Neurokinin 1 Receptor-Like Immunoreactive Neurons in the Rat Medullary Dorsal Horn

The synaptic connections between neurokinin 1 (NK1) receptor-like immunoreactive (LI) neurons and γ-aminobutyric acid (GABA)-, glycine (Gly)-, serotonin (5-HT)- or dopamine-β-hydroxylase (DBH, a specific marker for norepinephrinergic neuronal structures)-LI axon terminals in the rat medullary dorsal horn (MDH) were examined under electron microscope by using a pre-embedding immunohistochemical double-staining technique. NK1 receptor-LI neurons were observed principally in laminae I and III, only a few of them were found in lamina II of the MDH. GABA-, Gly-, 5-HT-, or DBH-LI axon terminals were densely encountered in laminae I and II, and sparsely in lamina III of the MDH. Some of these GABA-, Gly-, 5-HT-, or DBH-LI axon terminals were observed to make principally symmetric synapses with NK1 receptor-LI neuronal cell bodies and dendritic processes in laminae I, II and III of the MDH. The present results suggest that neurons expressing NK1 receptor within the MDH might be modulated by GABAergic and glycinergic inhibitory intrinsic neurons located in the MDH and 5-HT- or norepinephrine (NE)-containing descending fibers originated from structures in the brainstem

Nonlinear analysis of EEG signals at different mental states

BACKGROUND: The EEG (Electroencephalogram) is a representative signal containing information about the condition of the brain. The shape of the wave may contain useful information about the state of the brain. However, the human observer can not directly monitor these subtle details. Besides, since bio-signals are highly subjective, the symptoms may appear at random in the time scale. Therefore, the EEG signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. This work discusses the effect on the EEG signal due to music and reflexological stimulation. METHODS: In this work, nonlinear parameters like Correlation Dimension (CD), Largest Lyapunov Exponent (LLE), Hurst Exponent (H) and Approximate Entropy (ApEn) are evaluated from the EEG signals under different mental states. RESULTS: The results obtained show that EEG to become less complex relative to the normal state with a confidence level of more than 85% due to stimulation. CONCLUSIONS: It is found that the measures are significantly lower when the subjects are under sound or reflexologic stimulation as compared to the normal state. The dimension increases with the degree of the cognitive activity. This suggests that when the subjects are under sound or reflexologic stimuli, the number of parallel functional processes active in the brain is less and the brain goes to a more relaxed stat

Hierarchical chemosensory regulation of male-male social interactions in Drosophila

Pheromones regulate male social behaviors in Drosophila, but the identities and behavioral role(s) of these chemosensory signals, and how they interact, are incompletely understood. We found that (z)-7-tricosene, a male-enriched cuticular hydrocarbon that was previously shown to inhibit male-male courtship, was essential for normal levels of aggression. The mechanisms by which (z)-7-tricosene induced aggression and suppressed courtship were independent, but both required the gustatory receptor Gr32a. Sensitivity to (z)-7-tricosene was required for the aggression-promoting effect of 11-cis-vaccenyl acetate (cVA), an olfactory pheromone, but (z)-7-tricosene sensitivity was independent of cVA. (z)-7-tricosene and cVA therefore regulate aggression in a hierarchical manner. Furthermore, the increased courtship caused by depletion of male cuticular hydrocarbons was suppressed by a mutation in the olfactory receptor Or47b. Thus, male social behaviors are controlled by gustatory pheromones that promote aggression and suppress courtship, and whose influences are dominant to olfactory pheromones that enhance these behaviors