Fast Optimal Transport Averaging of Neuroimaging Data

Knowing how the Human brain is anatomically and functionally organized at the level of a group of healthy individuals or patients is the primary goal of neuroimaging research. Yet computing an average of brain imaging data defined over a voxel grid or a triangulation remains a challenge. Data are large, the geometry of the brain is complex and the between subjects variability leads to spatially or temporally non-overlapping effects of interest. To address the problem of variability, data are commonly smoothed before group linear averaging. In this work we build on ideas originally introduced by Kantorovich to propose a new algorithm that can average efficiently non-normalized data defined over arbitrary discrete domains using transportation metrics. We show how Kantorovich means can be linked to Wasserstein barycenters in order to take advantage of an entropic smoothing approach. It leads to a smooth convex optimization problem and an algorithm with strong convergence guarantees. We illustrate the versatility of this tool and its empirical behavior on functional neuroimaging data, functional MRI and magnetoencephalography (MEG) source estimates, defined on voxel grids and triangulations of the folded cortical surface.Comment: Information Processing in Medical Imaging (IPMI), Jun 2015, Isle of Skye, United Kingdom. Springer, 201

In Vitro Interaction of Lithium on Phospholipids in Human Erythrocytes

Lithium salts are used in the treatment of mania and as prophylaxis against manic depressive disorder. The aim of these studies was the in vitro investigation of the effect of lithium on phospholipids of human erythrocyte membranes. Erythrocytes were treated with lithium for 1 h. Phospholipids phosphatidylinositol (PI), phosphatidylserine (PS), phosphatidylethanolamine (PE), and phosphatidylocholine (PC) were separated from erythrocyte ghosts and determined by HPLC. Blood samples from healthy adults were investigated. A very strong decrease in PC content in erythrocyte membranes due to lithium in vitro treatment was found, as well as a statistically significant increase in PI content

Transgenerational Stress Memory Is Not a General Response in Arabidopsis

Adverse conditions can trigger DNA damage as well as DNA repair responses in plants. A variety of stress factors are known to stimulate homologous recombination, the most accurate repair pathway, by increasing the concentration of necessary enzymatic components and the frequency of events. This effect has been reported to last into subsequent generations not exposed to the stress. To establish a basis for a genetic analysis of this transgenerational stress memory, a broad range of treatments was tested for quantitative effects on homologous recombination in the progeny. Several Arabidopsis lines, transgenic for well-established recombination traps, were exposed to 10 different physical and chemical stress treatments, and scored for the number of somatic homologous recombination (SHR) events in the treated generation as well as in the two subsequent generations that were not treated. These numbers were related to the expression level of genes involved in homologous recombination and repair. SHR was enhanced after the majority of treatments, confirming previous data and adding new effective stress types, especially interference with chromatin. Compounds that directly modify DNA stimulated SHR to values exceeding previously described induction rates, concomitant with an induction of genes involved in SHR. In spite of the significant stimulation in the stressed generations, the two subsequent non-treated generations only showed a low and stochastic increase in SHR that did not correlate with the degree of stimulation in the parental plants. Transcripts coding for SHR enzymes generally returned to pre-treatment levels in the progeny. Thus, transgenerational effects on SHR frequency are not a general response to abiotic stress in Arabidopsis and may require special conditions

Evolutionary Rate Covariation Identifies New Members of a Protein Network Required for Drosophila melanogaster Female Post-Mating Responses

Seminal fluid proteins transferred from males to females during copulation are required for full fertility and can exert dramatic effects on female physiology and behavior. In Drosophila melanogaster, the seminal protein sex peptide (SP) affects mated females by increasing egg production and decreasing receptivity to courtship. These behavioral changes persist for several days because SP binds to sperm that are stored in the female. SP is then gradually released, allowing it to interact with its female-expressed receptor. The binding of SP to sperm requires five additional seminal proteins, which act together in a network. Hundreds of uncharacterized male and female proteins have been identified in this species, but individually screening each protein for network function would present a logistical challenge. To prioritize the screening of these proteins for involvement in the SP network, we used a comparative genomic method to identify candidate proteins whose evolutionary rates across the Drosophila phylogeny co-vary with those of the SP network proteins. Subsequent functional testing of 18 co-varying candidates by RNA interference identified three male seminal proteins and three female reproductive tract proteins that are each required for the long-term persistence of SP responses in females. Molecular genetic analysis showed the three new male proteins are required for the transfer of other network proteins to females and for SP to become bound to sperm that are stored in mated females. The three female proteins, in contrast, act downstream of SP binding and sperm storage. These findings expand the number of seminal proteins required for SP's actions in the female and show that multiple female proteins are necessary for the SP response. Furthermore, our functional analyses demonstrate that evolutionary rate covariation is a valuable predictive tool for identifying candidate members of interacting protein networks. © 2014 Findlay et al

Calibration of the LIGO gravitational wave detectors in the fifth science run

The Laser Interferometer Gravitational Wave Observatory (LIGO) is a network of three detectors built to detect local perturbations in the space–time metric from astrophysical sources. These detectors, two in Hanford, WA and one in Livingston, LA, are power-recycled Fabry-Perot Michelson interferometers. In their fifth science run (S5), between November 2005 and October 2007, these detectors accumulated one year of triple coincident data while operating at their designed sensitivity. In this paper, we describe the calibration of the instruments in the S5 data set, including measurement techniques and uncertainty estimation.United States. National Aeronautics and Space AdministrationCarnegie TrustLeverhulme TrustDavid & Lucile Packard FoundationResearch CorporationAlfred P. Sloan Foundatio

An exactly solvable, spatial model of mutation accumulation in cancer

One of the hallmarks of cancer is the accumulation of driver mutations which increase the net reproductive rate of cancer cells and allow them to spread. This process has been studied in mathematical models of well mixed populations, and in computer simulations of three-dimensional spatial models. But the computational complexity of these more realistic, spatial models makes it difficult to simulate realistically large and clinically detectable solid tumours. Here we describe an exactly solvable mathematical model of a tumour featuring replication, mutation and local migration of cancer cells. The model predicts a quasi-exponential growth of large tumours, even if different fragments of the tumour grow sub-exponentially due to nutrient and space limitations. The model reproduces clinically observed tumour growth times using biologically plausible rates for cell birth, death, and migration rates. We also show that the expected number of accumulated driver mutations increases exponentially in time if the average fitness gain per driver is constant, and that it reaches a plateau if the gains decrease over time. We discuss the realism of the underlying assumptions and possible extensions of the model

Phosphoproteomic Analysis Reveals that Dehydrins ERD10 and ERD14 are Phosphorylated by SNF1-related Protein Kinase 2.10 in Response to Osmotic Stress

SNF1-related protein kinases 2 (SnRK2s) regulate the plant responses to abiotic stresses, especially water deficits. They are activated in plants subjected to osmotic stress, and some of them are additionally activated in response to enhanced concentrations of abscisic acid (ABA) in plant cells. The SnRK2s that are activated in response to ABA are key elements of ABA signaling that regulate plant acclimation to environmental stresses and ABA-dependent development. Much less is known about the SnRK2s that are not activated by ABA, albeit several studies have shown that these kinases are also involved in response to osmotic stress. Here, we show that one of the Arabidopsis thaliana ABA-non-activated SnRK2s, SnRK2.10, regulates not only the response to salinity but also the plant sensitivity to dehydration. Several potential SnRK2.10 targets phosphorylated in response to stress were identified by a phosphoproteomic approach, including the dehydrins ERD10 and ERD14. Their phosphorylation by SnRK2.10 was confirmed in vitro. Our data suggest that the phosphorylation of ERD14 within the S-segment is involved in the regulation of dehydrin subcellular localization in response to stress