Morphogenesis of Class IV Neurons in Drosophila melanogaster

The establishment of the neuron\u27s morphology is essential to its function. The class IV neurons of the Drosophila melanogaster larva are two-dimensional sensory neurons that develop a complex dendritic arbor sensitive to mechanical stimuli. The fully-developed dendritic tree results from a multitude of stochastic processes including dendritic tip growth, branching and self-avoidance. However, it is yet unknown how the microscopic dendritic growth processes produce the macroscopic morphology of the class IV neurons. In this study, we aim to bridge this gap by formulating multi-scale models of neuronal dendritic morphogenesis. We begin by analyzing the tip dynamics and branching process of class IV dendritic trees. We find that the tip growth dynamics can be described by a Markov process that transitions between three velocity states: growing, paused and shrinking. Driven by the results of our analysis, we propose two types of model of morphogenesis. First, we use the mean-field approximation to formulate dendritic tree growth as a system of reaction-diffusion equations with two kinds of species, dendrites and tips. This coarse-grained approach predicts that the dendritic tree grows by the propagation of a density wave whose tail stabilizes to a steady-state. Second, we construct an agent-based model of morphogenesis that implements the stochastic rules of microscopic tip growth and branching whose combined effects lead to the development of the dendritic tree. Within the limitations of the model, this more fine-grained approach predicts morphometrics that agree with the measured values. In summary, our results characterize the development of class IV neurons and provide a framework to understand how the large-scale morphology of the class IV neuron dendritic tree emerges from the local stochastic growth of its branches

Analyzing Neuronal Dendritic Trees with Convolutional Neural Networks

In the biological sciences, image analysis software are used to detect, segment or classify a variety of features encountered in living matter. However, the algorithms that accomplish these tasks are often designed for a specific dataset, making them hardly portable to accomplish the same tasks on images of different biological structures. Recently, convolutional neural networks have been used to perform complex image analysis on a multitude of datasets. While applications of these networks abound in the technology industry and computer science, use cases are not as common in the academic sciences. Motivated by the generalizability of neural networks, we aim to develop a machine learning algorithm to detect morphological features in the dendritic trees of Drosophila Melanogaster class IV neurons. Our approach is based on the Single Shot Multibox Detector (Liu et. al.) and our training dataset is synthesized from simulations of dendritic trees that we previously developed. Our preliminary results show that the network performs well on the training set. However, on the test set, it sometimes misses objects of interest, which calls for further improvements

Infrared Dynamics of a Large N QCD Model, the Massless String Sector and Mesonic Spectra

A consistency check for any UV complete model for large N QCD should be, among other things, the existence of a well-defined vector and scalar mesonic spectra. In this paper, we use our UV complete model in type IIB string theory to study the IR dynamics and use this to predict the mesonic spectra in the dual type IIA side. The advantage of this approach is two-fold: not only will this justify the consistency of the supergravity approach, but it will also give us a way to compare the IR spectra and the model with the ones proposed earlier by Sakai and Sugimoto. Interestingly, the spectra coming from the massless stringy sector are independent of the UV physics, although the massive string sector may pose certain subtleties regarding the UV contributions as well as the mappings to actual QCD. Additionally, we find that a component of the string landscape enters the picture: there are points in the landscape where the spectra can be considerably improved over the existing results in the literature. These points in the landscape in-turn also determine certain background supergravity components and fix various pathologies that eventually lead to a consistent low energy description of the theory.Comment: 47 pages, 7 pdf figures, 24 tables, JHEP format; Detailed mathematica file of the computations is available on request; Version 2: Text elaborated, typos corrected, a new appendix added to discuss the regimes of validity, and a word in the abstract changed. Results unchanged. Final version to appear in JHE

Impacts de la modélisation stochastique des apports sur la gestion des ressources hydriques du système de la Romaine

Hydro-Québec est le propriétaire et le gestionnaire du complexe hydroélectrique de la rivière Romaine dans le nord-est du Québec, au Canada. Le complexe la Romaine est constitué de quatre réservoirs et parcourt une distance de 192 km entre la centrale Romaine-4 et le Saint-Laurent pour une chute totale de 459 mètres. Pour des fins de modélisation, le réservoir Romaine-1 est considéré comme au fil de l'eau vu son faible volume. Une fois complété en 2020, le système a une puissance installée prévue de 1 550 MW et une production annuelle moyenne de 8 TWh. L'objectif du présent projet est d'évaluer l'avantage d'utiliser la modélisation stochastique des apports dans une procédure de programmation dynamique stochastique pour optimiser la gestion du système hydrique de la rivière Romaine. Des probabilités de transition hebdomadaires sont employées pour la recherche de politiques de gestion optimale des réservoirs du complexe hydroélectrique. Les probabilités de transition sont établies à partir de séries synthétiques générées en utilisant des modèles autorégressifs périodiques de type PARMA: PAR (1), PAR (2), PARMA (1,1), PARMA (2,2). En addition aux modèles PARMA, nous avons utilisé un modèle à moyenne changeante (shifting mean). Les résultats de la modélisation hydrologique stochastique indiquent que parmi les modèles stochastiques mis en œuvre, le modèle PARMA (2,2) a démontré une meilleure performance à reproduire les statistiques des observations historiques. Un ensemble de 100 séries d'une durée de 53 ans (identique aux observations) a été généré. Les séries générées en utilisant le modèle PARMA (2,2) proviennent toutes de distributions statistiquement similaires aux observations, tandis que les autres modèles présentent au moins une série statistiquement différente. Nous utilisons un nouvel algorithme de programmation dynamique stochastique développé dans le cadre du projet Climhydro-2 pour lequel Hydro-Québec est partenaire industriel. Ce dernier utilise une méthode d'approximation de la fonction de Bellman en utilisant une discrétisation adaptative itérative qui permet de réduire le temps de calcul de la solution, tout en minimisant l'erreur d'approximation. Les résultats de la simulation des ensembles de règles de gestion révèlent que l'approche par modélisation stochastique et l'utilisation des observations historiques pour produire les probabilités de transition engendrent une production hydroélectrique totale similaire. Cependant, la gestion des réservoirs est différente selon les modèles et a été démontrée par des volumes de déversements annuels moyens statistiquement différents. Les résultats obtenus montrent que les règles de gestion obtenues avec le modèle PARMA (2,2) permettent de réduire le nombre de violations de la contrainte de débit réservé écologique minimum à la centrale de Romaine-1. Il est nécessaire de respecter un débit minimum à la sortie de la centrale pour la survie du saumon de l'Atlantique qui remonte sur le tronçon entre l'estuaire du Saint-Laurent et la centrale

N-3 polyunsaturated fatty acids stimulate bile acid detoxification in human cell models

Cholestasis is characterized by the accumulation of toxic bile acids (BAs) in liver cells. The present study aimed to evaluate the effects of n-3 polyunsaturated fatty acids (n-3 PUFAs), such as docosahexaenoic (DHA) and eicosapentaenoic (EPA) acids, on BA homeostasis and toxicity in human cell models. The effects of EPA and/or DHA on the expression of genes involved in the maintenance of BA homeostasis were analyzed in human hepatoma (HepG2) and colon carcinoma (Caco-2) cells, as well as in primary culture of human intestinal (InEpC) and renal (RPTEC) cells. Extracellular BA species were quantified in culture media using LC-MS/MS. BA-induced toxicity was evaluated using caspase-3 and flow cytometry assays. Gene expression analyses of HepG2 cells reveal that n-3 PUFAs reduce the expression of genes involved in BA synthesis (CYP7A1, CYP27A1) and uptake (NTCP), while activating genes encoding metabolic enzymes (SULT2A1) and excretion transporters (MRP2, MRP3). N-3 PUFAs also generate a less toxic BA pool and prevent the BA-dependent activation of apoptosis in HepG2 cells. Conclusion. The present study reveals that n-3 PUFAs stimulate BA detoxification

Role of glucuronidation for hepatic detoxification and urinary elimination of toxic bile acids during biliary obstruction

Biliary obstruction, a severe cholestatic condition, results in a huge accumulation of toxic bile acids (BA) in the liver. Glucuronidation, a conjugation reaction, is thought to protect the liver by both reducing hepatic BA toxicity and increasing their urinary elimination. The present study evaluates the contribution of each process in the overall BA detoxification by glucuronidation. Glucuronide (G), glycine, taurine conjugates, and unconjugated BAs were quantified in pre- and post-biliary stenting urine samples from 12 patients with biliary obstruction, using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The same LC-MS/MS procedure was used to quantify intra- and extracellular BA-G in Hepatoma HepG2 cells. Bile acid-induced toxicity in HepG2 cells was evaluated using MTS reduction, caspase-3 and flow cytometry assays. When compared to post-treatment samples, pre-stenting urines were enriched in glucuronide-, taurine- and glycine-conjugated BAs. Biliary stenting increased the relative BA-G abundance in the urinary BA pool, and reduced the proportion of taurine- and glycine-conjugates. Lithocholic, deoxycholic and chenodeoxycholic acids were the most cytotoxic and pro-apoptotic/necrotic BAs for HepG2 cells. Other species, such as the cholic, hyocholic and hyodeoxycholic acids were nontoxic. All BA-G assayed were less toxic and displayed lower pro-apoptotic/necrotic effects than their unconjugated precursors, even if they were able to penetrate into HepG2 cells. Under severe cholestatic conditions, urinary excretion favors the elimination of amidated BAs, while glucuronidation allows the conversion of cytotoxic BAs into nontoxic derivatives

Profiling Circulating and Urinary Bile Acids in Patients with Biliary Obstruction before and after Biliary Stenting

Bile acids are considered as extremely toxic at the high concentrations reached during bile duct obstruction, but each acid displays variable cytotoxic properties. This study investigates how biliary obstruction and restoration of bile flow interferes with urinary and circulating levels of 17 common bile acids. Bile acids (conjugated and unconjugated) were quantified by liquid chromatography coupled with tandem mass spectrometry in serum and urine samples from 17 patients (8 men and 9 women) with biliary obstruction, before and after biliary stenting. Results were compared with serum concentrations measured in 40 age- and sex-paired control donors (20 men and 20 women). The total circulating bile acid concentration increases from 2.7 µM in control donors to 156.9 µM in untreated patients with biliary stenosis. Serum taurocholic and glycocholic acids exhibit 304- and 241-fold accumulations in patients with biliary obstruction compared to controls. The enrichment in chenodeoxycholic acid species reached a maximum of only 39-fold, while all secondary and 6α-hydroxylated species –except taurolithocholic acids – were either unchanged or significantly reduced. Stenting was efficient in restoring an almost normal circulating profile and in reducing urinary bile acids

The Hepatokine TSK does not affect brown fat thermogenic capacity, body weight gain, and glucose homeostasis

Objectives Hepatokines are proteins secreted by the liver that impact the functions of the liver and various tissues through autocrine, paracrine, and endocrine signaling. Recently, Tsukushi (TSK) was identified as a new hepatokine that is induced by obesity and cold exposure. It was proposed that TSK controls sympathetic innervation and thermogenesis in brown adipose tissue (BAT) and that loss of TSK protects against diet-induced obesity and improves glucose homeostasis. Here we report the impact of deleting and/or overexpressing TSK on BAT thermogenic capacity, body weight regulation, and glucose homeostasis. Methods We measured the expression of thermogenic genes and markers of BAT innervation and activation in TSK-null and TSK-overexpressing mice. Body weight, body temperature, and parameters of glucose homeostasis were also assessed in the context of TSK loss and overexpression. Results The loss of TSK did not affect the thermogenic activation of BAT. We found that TSK-null mice were not protected against the development of obesity and did not show improvement in glucose tolerance. The overexpression of TSK also failed to modulate thermogenesis, body weight gain, and glucose homeostasis in mice