Multiple Instance Learning for Heterogeneous Images: Training a CNN for Histopathology

Multiple instance (MI) learning with a convolutional neural network enables end-to-end training in the presence of weak image-level labels. We propose a new method for aggregating predictions from smaller regions of the image into an image-level classification by using the quantile function. The quantile function provides a more complete description of the heterogeneity within each image, improving image-level classification. We also adapt image augmentation to the MI framework by randomly selecting cropped regions on which to apply MI aggregation during each epoch of training. This provides a mechanism to study the importance of MI learning. We validate our method on five different classification tasks for breast tumor histology and provide a visualization method for interpreting local image classifications that could lead to future insights into tumor heterogeneity

Epstein-Barr virus proteins EBNA3A and EBNA3C together induce expression of the oncogenic microRNA cluster miR-221/miR-222 and ablate expression of its target p57KIP2.

We show that two host-encoded primary RNAs (pri-miRs) and the corresponding microRNA (miR) clusters--widely reported to have cell transformation-associated activity--are regulated by EBNA3A and EBNA3C. Utilising a variety of EBV-transformed lymphoblastoid cell lines (LCLs) carrying knockout-, revertant- or conditional-EBV recombinants, it was possible to demonstrate unambiguously that EBNA3A and EBNA3C are both required for transactivation of the oncogenic miR-221/miR-222 cluster that is expressed at high levels in multiple human tumours--including lymphoma/leukemia. ChIP, ChIP-seq, and chromosome conformation capture analyses indicate that this activation results from direct targeting of both EBV proteins to chromatin at the miR-221/miR-222 genomic locus and activation via a long-range interaction between enhancer elements and the transcription start site of a long non-coding pri-miR located 28 kb upstream of the miR sequences. Reduced levels of miR-221/miR-222 produced by inactivation or deletion of EBNA3A or EBNA3C resulted in increased expression of the cyclin-dependent kinase inhibitor p57KIP2, a well-established target of miR-221/miR-222. MiR blocking experiments confirmed that miR-221/miR-222 target p57KIP2 expression in LCLs. In contrast, EBNA3A and EBNA3C are necessary to silence the tumour suppressor cluster miR-143/miR-145, but here ChIP-seq suggests that repression is probably indirect. This miR cluster is frequently down-regulated or deleted in human cancer, however, the targets in B cells are unknown. Together these data indicate that EBNA3A and EBNA3C contribute to B cell transformation by inhibiting multiple tumour suppressor proteins, not only by direct repression of protein-encoding genes, but also by the manipulation of host long non-coding pri-miRs and miRs

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

Chiral Modulations in Curved Space I: Formalism

The goal of this paper is to present a formalism that allows to handle four-fermion effective theories at finite temperature and density in curved space. The formalism is based on the use of the effective action and zeta function regularization, supports the inclusion of inhomogeneous and anisotropic phases. One of the key points of the method is the use of a non-perturbative ansatz for the heat-kernel that returns the effective action in partially resummed form, providing a way to go beyond the approximations based on the Ginzburg-Landau expansion for the partition function. The effective action for the case of ultra-static Riemannian spacetimes with compact spatial section is discussed in general and a series representation, valid when the chemical potential satisfies a certain constraint, is derived. To see the formalism at work, we consider the case of static Einstein spaces at zero chemical potential. Although in this case we expect inhomogeneous phases to occur only as meta-stable states, the problem is complex enough and allows to illustrate how to implement numerical studies of inhomogeneous phases in curved space. Finally, we extend the formalism to include arbitrary chemical potentials and obtain the analytical continuation of the effective action in curved space.Comment: 22 pages, 3 figures; version to appear in JHE

Upregulation of the cell-cycle regulator RGC-32 in Epstein-Barr virus-immortalized cells

Epstein-Barr virus (EBV) is implicated in the pathogenesis of multiple human tumours of lymphoid and epithelial origin. The virus infects and immortalizes B cells establishing a persistent latent infection characterized by varying patterns of EBV latent gene expression (latency 0, I, II and III). The CDK1 activator, Response Gene to Complement-32 (RGC-32, C13ORF15), is overexpressed in colon, breast and ovarian cancer tissues and we have detected selective high-level RGC-32 protein expression in EBV-immortalized latency III cells. Significantly, we show that overexpression of RGC-32 in B cells is sufficient to disrupt G2 cell-cycle arrest consistent with activation of CDK1, implicating RGC-32 in the EBV transformation process. Surprisingly, RGC-32 mRNA is expressed at high levels in latency I Burkitt's lymphoma (BL) cells and in some EBV-negative BL cell-lines, although RGC-32 protein expression is not detectable. We show that RGC-32 mRNA expression is elevated in latency I cells due to transcriptional activation by high levels of the differentially expressed RUNX1c transcription factor. We found that proteosomal degradation or blocked cytoplasmic export of the RGC-32 message were not responsible for the lack of RGC-32 protein expression in latency I cells. Significantly, analysis of the ribosomal association of the RGC-32 mRNA in latency I and latency III cells revealed that RGC-32 transcripts were associated with multiple ribosomes in both cell-types implicating post-initiation translational repression mechanisms in the block to RGC-32 protein production in latency I cells. In summary, our results are the first to demonstrate RGC-32 protein upregulation in cells transformed by a human tumour virus and to identify post-initiation translational mechanisms as an expression control point for this key cell-cycle regulator

Developing the philosophy of recovery in South African mental health services

The recovery movement has emerged as an important and powerful force in the design and implementation of mental health care in many countries around the world. This involves new and more positive understandings of the concept of recovery, both as an individual outcome and as a goal of services. The basis for these understandings is examined, with particular emphasis on longterm outcomes in schizophrenia, and a brief history of the origins of the recovery movement is given. An argument is made for the implementation of a recovery framework within South African mental health services

Morphologic and Biochemical Changes in Dogs After Portacaval Shunt Plus Bile Fistula or Ileal Bypass: Failure of Bile Fistula or Ileal Bypass to Prevent Hepatocyte Atrophy

External biliary fistula (BF) or ileal bypass (IB) was performed in dogs at the time of or 2 weeks after portacaval shunt (PCS). The pathologic changes in the dog livers 2 to 4 weeks later were compared to those caused by PCS alone. Histopathologic differences between PCS alone vs. PCS plus BF or IB could not be found. Thus, the experiments did not confirm recent observations by others in rats that BF prevents or reverses the hepatic injury of PCS. As estimated by plasma mevalonic acid determinations, the increase in hepatic cholesterol synthesis that is characteristic after BF or IB was suppressed in animals with PCS. BF and IB reduced but did not eliminate the postprandial elevation in serum bile acid that occurs after PCS. The findings have possible relevance in planning the treatment of patients with familial hypercholesterolemia with the combined use of PCS and IB. Copyright © 1983 American Association for the Study of Liver Disease

Chandrasekhar-Kendall functions in astrophysical dynamos

Some of the contributions of Chandrasekhar to the field of magnetohydrodynamics are highlighted. Particular emphasis is placed on the Chandrasekhar-Kendall functions that allow a decomposition of a vector field into right- and left-handed contributions. Magnetic energy spectra of both contributions are shown for a new set of helically forced simulations at resolutions higher than what has been available so far. For a forcing function with positive helicity, these simulations show a forward cascade of the right-handed contributions to the magnetic field and nonlocal inverse transfer for the left-handed contributions. The speed of inverse transfer is shown to decrease with increasing value of the magnetic Reynolds number.Comment: 10 pages, 5 figures, proceedings of the Chandrasekhar Centenary Conference, to be published in PRAMANA - Journal of Physic

The novel mu-opioid antagonist, GSK1521498, reduces ethanol consumption in C57BL/6J mice.

RATIONALE Using the drinking-in-the-dark (DID) model, we compared the effects of a novel mu-opioid receptor antagonist, GSK1521498, with naltrexone, a licensed treatment of alcohol dependence, on ethanol consumption in mice. OBJECTIVE We test the ability of GSK1521498 to reduce alcohol consumption and compare its intrinsic efficacy to that of naltrexone by comparing the two drugs at doses matched for equivalent receptor occupancy. METHODS Thirty-six C57BL/6J mice were tested in a DID procedure. In 2-day cycles, animals experienced one baseline, injection-free session, and one test session when they received two injections, one of test drug and one placebo. All animals received GSK1521498 (0, 0.1, 1 and 3 mg/kg, i.p., 30 min pre-treatment) and naltrexone (0, 0.1, 1 and 3 mg/kg, s.c. 10 min pre-treatment) in a cross-over design. Receptor occupancies following the same doses were determined ex vivo in separate groups by autoradiography, using [3H]DAMGO. Binding in the region of interest was measured integrally by computer-assisted microdensitometry and corrected for non-specific binding. RESULTS Both GSK1521498 and naltrexone dose-dependently decreased ethanol consumption. When drug doses were matched for 70-75 % receptor occupancy, GSK1521498 3 mg/kg, i.p., caused a 2.5-fold greater reduction in alcohol consumption than naltrexone 0.1 mg/kg, s.c. Both GSK1521498 and naltrexone significantly reduced sucrose consumption at a dose of 1 mg/kg but not 0.1 mg/kg. In a test of conditioned taste aversion, GSK1521498 (3 mg/kg) reduced sucrose consumption 24 h following exposure to a conditioning injection. CONCLUSIONS Both opioid receptor antagonists reduced alcohol consumption but GK1521498 has higher intrinsic efficacy than naltrexone

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