Effects of altitude on circadian rhythm of adult locomotor activity in Himalayan strains of Drosophila helvetica

BACKGROUND: We recently reported that the altitude of origin altered the photic and thermal sensitivity of the circadian pacemaker controlling eclosion and oviposition rhythms of high altitude Himalayan strains of Drosophila ananassae. The present study was aimed at investigating the effects of altitude of origin on the pacemaker controlling the adult locomotor activity rhythm of D. helvetica. METHODS: Locomotor activity rhythms of the high altitude Himalayan (haH) strain (Hemkund-Sahib, 4,121 m above sea level) and the low altitude Himalayan (laH) strain (Birahi, 1,132 m a.s.l.) of D. helvetica were assayed by two experiments. The first experiment examined the natural entrainment pattern in light-dark (LD) cycles at the breeding site of each strain. The second experiment examined the entrainment parameters in LD 12:12 cycles and the period of free-running rhythm in constant darkness (DD) under controlled laboratory conditions. RESULTS: When entrained by natural or artificial LD cycles, the haH strain had an unimodal activity pattern with a single peak that commenced in the forenoon and continued till evening, while the laH strain had a bimodal activity pattern in which the morning peak occurred before lights-on and was separated by about 4 h from the evening peak. Unimodality of the haH strain was retained in DD; however, bimodality of the laH strain was abolished in DD since the evening peak disappeared immediately after the trasfer from LD 12:12 to DD. The period of the free-running rhythm of the haH strain was ~26.1 h, whereas that of the laH strain was ~21.7 h. CONCLUSION: Parameters of entrainment and free-running rhythm of the adult locomotor activity of the haH strain of D. helvetica were strikingly different from those of the laH strain and were likely due to ecological adaptations to the prevailing environmental conditions at the altitude where the species evolved

Temporal Model Adaptation for Person Re-Identification

Person re-identification is an open and challenging problem in computer vision. Majority of the efforts have been spent either to design the best feature representation or to learn the optimal matching metric. Most approaches have neglected the problem of adapting the selected features or the learned model over time. To address such a problem, we propose a temporal model adaptation scheme with human in the loop. We first introduce a similarity-dissimilarity learning method which can be trained in an incremental fashion by means of a stochastic alternating directions methods of multipliers optimization procedure. Then, to achieve temporal adaptation with limited human effort, we exploit a graph-based approach to present the user only the most informative probe-gallery matches that should be used to update the model. Results on three datasets have shown that our approach performs on par or even better than state-of-the-art approaches while reducing the manual pairwise labeling effort by about 80%

Cosmological Birefringence: an Astrophysical test of Fundamental Physics

We review the methods used to test for the existence of cosmological birefringence, i.e. a rotation of the plane of linear polarization for electromagnetic radiation traveling over cosmological distances, which might arise in a number of important contexts involving the violation of fundamental physical principles. The main methods use: (1) the radio polarization of radio galaxies and quasars, (2) the ultraviolet polarization of radio galaxies, and (3) the cosmic microwave background polarization. We discuss the main results obtained so far, the advantages and disadvantages of each method, and future prospects.Comment: To appear in the Proceedings of the JENAM 2010 Symposium "From Varying Couplings to Fundamental Physics", held in Lisbon, 6-10 Sept. 201

Validating module network learning algorithms using simulated data

In recent years, several authors have used probabilistic graphical models to learn expression modules and their regulatory programs from gene expression data. Here, we demonstrate the use of the synthetic data generator SynTReN for the purpose of testing and comparing module network learning algorithms. We introduce a software package for learning module networks, called LeMoNe, which incorporates a novel strategy for learning regulatory programs. Novelties include the use of a bottom-up Bayesian hierarchical clustering to construct the regulatory programs, and the use of a conditional entropy measure to assign regulators to the regulation program nodes. Using SynTReN data, we test the performance of LeMoNe in a completely controlled situation and assess the effect of the methodological changes we made with respect to an existing software package, namely Genomica. Additionally, we assess the effect of various parameters, such as the size of the data set and the amount of noise, on the inference performance. Overall, application of Genomica and LeMoNe to simulated data sets gave comparable results. However, LeMoNe offers some advantages, one of them being that the learning process is considerably faster for larger data sets. Additionally, we show that the location of the regulators in the LeMoNe regulation programs and their conditional entropy may be used to prioritize regulators for functional validation, and that the combination of the bottom-up clustering strategy with the conditional entropy-based assignment of regulators improves the handling of missing or hidden regulators.Comment: 13 pages, 6 figures + 2 pages, 2 figures supplementary informatio

Volumetric laser endomicroscopy and its application to Barrett's esophagus: results from a 1,000 patient registry.

Volumetric laser endomicroscopy (VLE) uses optical coherence tomography (OCT) for real-time, microscopic cross-sectional imaging. A US-based multi-center registry was constructed to prospectively collect data on patients undergoing upper endoscopy during which a VLE scan was performed. The objective of this registry was to determine usage patterns of VLE in clinical practice and to estimate quantitative and qualitative performance metrics as they are applied to Barrett's esophagus (BE) management. All procedures utilized the NvisionVLE Imaging System (NinePoint Medical, Bedford, MA) which was used by investigators to identify the tissue types present, along with focal areas of concern. Following the VLE procedure, investigators were asked to answer six key questions regarding how VLE impacted each case. Statistical analyses including neoplasia diagnostic yield improvement using VLE was performed. One thousand patients were enrolled across 18 US trial sites from August 2014 through April 2016. In patients with previously diagnosed or suspected BE (894/1000), investigators used VLE and identified areas of concern not seen on white light endoscopy (WLE) in 59% of the procedures. VLE imaging also guided tissue acquisition and treatment in 71% and 54% of procedures, respectively. VLE as an adjunct modality improved the neoplasia diagnostic yield by 55% beyond the standard of care practice. In patients with no prior history of therapy, and without visual findings from other technologies, VLE-guided tissue acquisition increased neoplasia detection over random biopsies by 700%. Registry investigators reported that VLE improved the BE management process when used as an adjunct tissue acquisition and treatment guidance tool. The ability of VLE to image large segments of the esophagus with microscopic cross-sectional detail may provide additional benefits including higher yield biopsies and more efficient tissue acquisition. Clinicaltrials.gov NCT02215291

Detection of regulator genes and eQTLs in gene networks

Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are "expression quantitative trait loci" or eQTLs for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, and to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.Comment: minor revision with typos corrected; review article; 24 pages, 2 figure

Esophageal Granular Cell Tumor and Eosinophilic Esophagitis: Two Interesting Entities Identified in the Same Patient

We illustrate the case of a 41-year-old male with allergic manifestations since childhood. He sought medical attention for intermittent, progressive dysphagia from which he had been suffering for a number of years, having felt the sensation of a retrosternal lump and a self-limited obstruction to the passage of food. Endoscopy detected a submucosal tumor in the upper third of the esophagus, which was typified, via biopsy, as a granular cell tumor with benign characteristics and probably responsible for the symptoms. Two years later, the patient sought medical attention once again as these symptoms had not abated, hence digestive endoscopy was repeated. This revealed stenosis of the junction between the middle and lower thirds of the organ which had not been detected previously but was passable under gentle pressure. Eosinophilic esophagitis was detected after biopsies were taken. Esophageal manometry identified a motor disorder affecting the esophageal body. Following three months of treatment using fluticasone propionate applied topically, the symptoms went into remission, esophageal stenosis disappeared and the esophageal biopsies returned to normal. This is the first documented case of the link between granular cell tumors and Eosinophilic esophagitis, two different disorders which could cause dysphagia in young patients