A transfer-learning approach to feature extraction from cancer transcriptomes with deep autoencoders

Publicado en Lecture Notes in Computer Science.The diagnosis and prognosis of cancer are among the more challenging tasks that oncology medicine deals with. With the main aim of fitting the more appropriate treatments, current personalized medicine focuses on using data from heterogeneous sources to estimate the evolu- tion of a given disease for the particular case of a certain patient. In recent years, next-generation sequencing data have boosted cancer prediction by supplying gene-expression information that has allowed diverse machine learning algorithms to supply valuable solutions to the problem of cancer subtype classification, which has surely contributed to better estimation of patient’s response to diverse treatments. However, the efficacy of these models is seriously affected by the existing imbalance between the high dimensionality of the gene expression feature sets and the number of sam- ples available for a particular cancer type. To counteract what is known as the curse of dimensionality, feature selection and extraction methods have been traditionally applied to reduce the number of input variables present in gene expression datasets. Although these techniques work by scaling down the input feature space, the prediction performance of tradi- tional machine learning pipelines using these feature reduction strategies remains moderate. In this work, we propose the use of the Pan-Cancer dataset to pre-train deep autoencoder architectures on a subset com- posed of thousands of gene expression samples of very diverse tumor types. The resulting architectures are subsequently fine-tuned on a col- lection of specific breast cancer samples. This transfer-learning approach aims at combining supervised and unsupervised deep learning models with traditional machine learning classification algorithms to tackle the problem of breast tumor intrinsic-subtype classification.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

First Results from Sentinel-1A InSAR over Australia: Application to the Perth Basin

Past ground-based geodetic measurements in the Perth Basin, Australia, record small-magnitude subsidence (up to 7 mm/y), but are limited to discrete points or traverses across parts of the metropolitan area. Here, we investigate deformation over a much larger region by performing the first application of Sentinel-1A InSAR data to Australia. The duration of the study is short (0.7 y), as dictated by the availability of Sentinel-1A data. Despite this limited observation period, verification of Sentinel-1A with continuous GPS and independent TerraSAR-X provides new insights into the deformation field of the Perth Basin. The displacements recorded by each satellite are in agreement, identifying broad (>5 km wide) areas of subsidence at rates up to 15 mm/y. Subsidence at rates greater than 20 mm/y over smaller regions ( 2 km wide) is coincident with wetland areas, where displacements are temporally correlated with changes in groundwater levels in the unconfined aquifer. Longer InSAR time series are required to determine whether these measured displacements are representative of long-term deformation or (more likely) seasonal variations. However, the agreement between datasets demonstrates the ability of Sentinel-1A to detect small-magnitude deformation over different spatial scales (from 2 km–10 s of km) in the Perth Basin. We suggest that, even over short time periods, these data are useful as a reconnaissance tool to identify regions for subsequent targeted studies, particularly given the large swath size of radar acquisitions, which facilitates analysis of a broader portion of the deformation field than ground-based methods or single scenes of TerraSAR-X

Reach-scale bankfull channel types can exist independently of catchment hydrology

© 2020 John Wiley & Sons, Ltd. Reach-scale morphological channel classifications are underpinned by the theory that each channel type is related to an assemblage of reach- and catchment-scale hydrologic, topographic, and sediment supply drivers. However, the relative importance of each driver on reach morphology is unclear, as is the possibility that different driver assemblages yield the same reach morphology. Reach-scale classifications have never needed to be predicated on hydrology, yet hydrology controls discharge and thus sediment transport capacity. The scientific question is: do two or more regions with quantifiable differences in hydrologic setting end up with different reach-scale channel types, or do channel types transcend hydrologic setting because hydrologic setting is not a dominant control at the reach scale? This study answered this question by isolating hydrologic metrics as potential dominant controls of channel type. Three steps were applied in a large test basin with diverse hydrologic settings (Sacramento River, California) to: (1) create a reach-scale channel classification based on local site surveys, (2) categorize sites by flood magnitude, dimensionless flood magnitude, and annual hydrologic regime type, and (3) statistically analyze two hydrogeomorphic linkages. Statistical tests assessed the spatial distribution of channel types and the dependence of channel type morphological attributes by hydrologic setting. Results yielded 10 channel types. Nearly all types existed across all hydrologic settings, which is perhaps a surprising development for hydrogeomorphology. Downstream hydraulic geometry relationships were statistically significant. In addition, cobble-dominated uniform streams showed a consistent inverse relationship between slope and dimensionless flood magnitude, an indication of dynamic equilibrium between transport capacity and sediment supply. However, most morphological attributes showed no sorting by hydrologic setting. This study suggests that median hydraulic geometry relations persist across basins and within channel types, but hydrologic influence on geomorphic variability is likely due to local influences rather than catchment-scale drivers. © 2020 John Wiley & Sons, Ltd

Temperature-dependent transformation of the magnetic excitation spectrum on approaching superconductivity in Fe1-x (Ni/Cu)x Te0.5 Se0.5

Spin excitations are one of the top candidates for mediating electron pairing in unconventional superconductors. Their coupling to superconductivity is evident in a large number of systems, by the observation of an abrupt redistribution of magnetic spectral weight at the superconducting transition temperature, Tc, for energies comparable to the superconducting gap. Here we report inelastic neutron scattering measurements on Fe-based superconductors, Fe1-x (Ni/Cu)x Te0.5 Se0.5, that emphasize an additional signature. The overall shape of the low energy magnetic dispersion changes from two incommensurate vertical columns at T >> Tc to a distinctly different U-shaped dispersion at low temperature. Importantly, this spectral reconstruction is apparent for temperature up to ~3Tc. If the magnetic excitations are involved in the pairing mechanism, their surprising modification on the approach to Tc demonstrates that strong interactions are involved

Global land surface air temperature dynamics since 1880

The geographical extent, magnitude, and uncertainty of global climate change have been widely discussed and have critical policy implications at both global and local scales. In this study, a new analysis of annual mean global land surface air temperature since 1880 was generated, which has greater coverage and lower uncertainty than previous distributions. The Biased Sentinel Hospitals Areal Disease Estimation (BSHADE) method, used in this study, makes a best linear unbiased estimation (BLUE) when a sample is small and biased to a spatially heterogeneous population. For the period of 1901–2010, the warming trend was found to be 0.109 °C decade−1 with 95% confidence intervals between 0.081 °C and 0.137 °C. Additionally, warming exhibited different spatial patterns in different periods. In the early 20th century (1923–1950), warming occurred mainly in the mid-high latitudes of the Northern Hemisphere, whereas in the most recent decades (1977–2014), warming was more spatially extensive across the global land surface. Compared with other common methods, the difference in results appears in the areas with few stations and in the early years, when stations had sparse coverage and were unevenly distributed. Validation, which was performed using real data that simulated the historic situation, showed a smaller error in the BSHADE estimate than in other methods. This study produced a new database with greater coverage and less uncertainty that will improve the understanding of climate dynamics on the Earth since 1880, especially in isolated areas and early periods, and will benefit the assessment of climate-change-related issues, such as the effects of human activities

Filovirus receptor NPC1 contributes to species-specific patterns of ebolavirus susceptibility in bats

Biological factors that influence the host range and spillover of Ebola virus (EBOV) and other filoviruses remain enigmatic. While filoviruses infect diverse mammalian cell lines, we report that cells from African straw-colored fruit bats (Eidolon helvum) are refractory to EBOV infection. This could be explained by a single amino acid change in the filovirus receptor, NPC1, which greatly reduces the affinity of EBOV-NPC1 interaction. We found signatures of positive selection in bat NPC1 concentrated at the virus-receptor interface, with the strongest signal at the same residue that controls EBOV infection in Eidolon helvum cells. Our work identifies NPC1 as a genetic determinant of filovirus susceptibility in bats, and suggests that some NPC1 variations reflect host adaptations to reduce filovirus replication and virulence. A single viral mutation afforded escape from receptor control, revealing a pathway for compensatory viral evolution and a potential avenue for expansion of filovirus host range in nature

Microstructure of conductive binder domain for electrical conduction in next‐generation lithium‐ion batteries

The purpose of this work is to investigate the structure and mechanism of long‐range electronic contacts which are formed by wet mixing and their interaction and relationship with the structure responsible for ion‐transfer within the conductive binder domain of next‐generation LiNi0.6Mn0.2Co0.2O2 lithium‐ion batteries. This paper introduces a novel concept involving an efficient adapted structure model, which includes a bridge structure with two “nested” small and large pore systems, and an effective electrode conduction mechanism involving two “nested” percolation systems. The paper also highlights a limitation in the improvement of the battery performance by percolation systems for electron transfer, which is restricted by pore systems for ion transfer through the ratio of electrical conductivity (σ) and ionic conductivity (κ) as σ/κ = 10. The findings of this paper may provide valuable insight for formulation design and manufacturing of an optimal structure of the conductive binder domain for next‐generation lithium‐ion batteries.This article is protected by copyright. All rights reserved.</jats:p

The Stokes Phenomenon and Quantum Tunneling for de Sitter Radiation in Nonstationary Coordinates

We study quantum tunneling for the de Sitter radiation in the planar coordinates and global coordinates, which are nonstationary coordinates and describe the expanding geometry. Using the phase-integral approximation for the Hamilton-Jacobi action in the complex plane of time, we obtain the particle-production rate in both coordinates and derive the additional sinusoidal factor depending on the dimensionality of spacetime and the quantum number for spherical harmonics in the global coordinates. This approach resolves the factor of two problem in the tunneling method.Comment: LaTex 10 pages, no figur

Paediatric obsessive-compulsive disorder and depressive symptoms: clinical correlates and CBT treatment outcomes.

Depression frequently co-occurs with paediatric obsessive-compulsive disorder (OCD), yet the clinical correlates and impact of depression on CBT outcomes remain unclear. The prevalence and clinical correlates of depression were examined in a paediatric specialist OCD-clinic sample (N = 295; Mean = 15 [7 - 18] years, 42 % female), using both dimensional (Beck Depression Inventory-youth; n = 261) and diagnostic (Development and Wellbeing Assessment; n = 127) measures of depression. The impact of depressive symptoms and suspected disorders on post-treatment OCD severity was examined in a sub-sample who received CBT, with or without SSRI medication (N = 100). Fifty-one per-cent of patients reported moderately or extremely elevated depressive symptoms and 26 % (95 % CI: 18 - 34) met criteria for a suspected depressive disorder. Depressive symptoms and depressive disorders were associated with worse OCD symptom severity and global functioning prior to CBT. Individuals with depression were more likely to be female, have had a psychiatric inpatient admission and less likely to be attending school (ps < 0.01). OCD and depressive symptom severity significantly decreased after CBT. Depressive symptoms and depressive disorders predicted worse post-treatment OCD severity (βs = 0.19 and 0.26, ps < 0.05) but became non-significant when controlling for pre-treatment OCD severity (βs = 0.05 and 0.13, ns). Depression is common in paediatric OCD and is associated with more severe OCD and poorer functioning. However, depression severity decreases over the course of CBT for OCD and is not independently associated with worse outcomes, supporting the recommendation for treatment as usual in the presence of depressive symptoms