Trade-off between conservation of biological variation and batch effect removal in deep generative modeling for single-cell transcriptomics.

Background: Single-cell RNA sequencing (scRNA-seq) technology has contributed significantly to diverse research areas in biology, from cancer to development. Since scRNA-seq data is high-dimensional, a common strategy is to learn low-dimensional latent representations better to understand overall structure in the data. In this work, we build upon scVI, a powerful deep generative model which can learn biologically meaningful latent representations, but which has limited explicit control of batch effects.

Deep Learning Is Singular, and That's Good.

In singular models, the optimal set of parameters forms an analytic set with singularities, and a classical statistical inference cannot be applied to such models. This is significant for deep learning as neural networks are singular, and thus, "dividing" by the determinant of the Hessian or employing the Laplace approximation is not appropriate. Despite its potential for addressing fundamental issues in deep learning, a singular learning theory appears to have made little inroads into the developing canon of a deep learning theory.

Automating the assessment of biofouling in images using expert agreement as a gold standard.

Biofouling is the accumulation of organisms on surfaces immersed in water. It is of particular concern to the international shipping industry because it increases fuel costs and presents a biosecurity risk by providing a pathway for non-indigenous marine species to establish in new areas. There is growing interest within jurisdictions to strengthen biofouling risk-management regulations, but it is expensive to conduct in-water inspections and assess the collected data to determine the biofouling state of vessel hulls.

Control of Blood Glucose for Type-1 Diabetes by Using Reinforcement Learning with Feedforward Algorithm.

Background: Type-1 diabetes is a condition caused by the lack of insulin hormone, which leads to an excessive increase in blood glucose level. The glucose kinetics process is difficult to control due to its complex and nonlinear nature and with state variables that are difficult to measure.

Methods: This paper proposes a method for automatically calculating the basal and bolus insulin doses for patients with type-1 diabetes using reinforcement learning with feedforward controller.

The Change-Plane Cox Model.

We propose a projection pursuit technique in survival analysis for finding lower-dimensional projections that exhibit differentiated survival outcome. This idea is formally introduced as the change-plane Cox model, a non-regular Cox model with a change-plane in the covariate space dividing the population into two subgroups whose hazards are proportional. The proposed technique offers a potential framework for principled subgroup discovery.

A Low-Cost, Grab-and-Go Breakfast Intervention for Rural High School Students: Changes in School Breakfast Program Participation Among At-Risk Students in Minnesota.

Objective: Evaluate the impact of a grab-and-go component embedded within a larger intervention designed to promote School Breakfast Program (SBP) participation.

Design: Secondary data analysis.

Setting: Rural Minnesota high schools.

School Breakfast Program Participation and Rural Adolescents' Purchasing Behaviors in Food Stores and Restaurants.

Background: Little is known about adolescents' food purchasing behaviors in rural areas. This study examined whether purchasing food at stores/restaurants around schools was related to adolescents' participation in school breakfast programs and overall diet in rural Minnesota.

Methods: Breakfast-skippers enrolled in a group-randomized intervention in 2014 to 2015 (N = 404 from 8 schools) completed 24-hour dietary recalls and pre/post surveys assessing food establishment purchase frequency.

Latent Supervised Learning.

A new machine learning task is introduced, called latent supervised learning, where the goal is to learn a binary classifier from training labels which serve as surrogates for the unobserved class labels. A specific model is investigated where the surrogate variable arises from a two-component Gaussian mixture with unknown means and variances, and the component membership is determined by a hyperplane in the covariate space. The estimation of the separating hyperplane and the Gaussian mixture parameters forms what shall be referred to as the change-line classification problem.

Image and statistical analysis of melanocytic histology.

Aims: We applied digital image analysis techniques to study selected types of melanocytic lesions.

Methods And Results: We used advanced digital image analysis to compare melanocytic lesions as follows: (i) melanoma to nevi, (ii) melanoma subtypes to nevi, (iii) severely dysplastic nevi to other nevi and (iv) melanoma to severely dysplastic nevi. We were successful in differentiating melanoma from nevi [receiver operating characteristic area (ROC) 0.

Hypermethylation of 18S and 28S ribosomal DNAs predicts progression-free survival in patients with ovarian cancer.

Purpose: Repetitive ribosomal DNA (rDNA) genes are GC-rich clusters in the human genome. The aim of the study was to determine the methylation status of two rDNA subunits, the 18S and 28S genes, in ovarian tumors and to correlate methylation levels with clinicopathologic features in a cohort of ovarian cancer patients.

Experimental Design: 18S and 28S rDNA methylation was examined by quantitative methylation-specific PCR in 74 late-stage ovarian cancers, 9 histologically uninvolved, and 11 normal ovarian surface epithelial samples.

Loss of estrogen receptor signaling triggers epigenetic silencing of downstream targets in breast cancer.

Alterations in histones, chromatin-related proteins, and DNA methylation contribute to transcriptional silencing in cancer, but the sequence of these molecular events is not well understood. Here we demonstrate that on disruption of estrogen receptor (ER) alpha signaling by small interfering RNA, polycomb repressors and histone deacetylases are recruited to initiate stable repression of the progesterone receptor (PR) gene, a known ERalpha target, in breast cancer cells. The event is accompanied by acquired DNA methylation of the PR promoter, leaving a stable mark that can be inherited by cancer cell progeny.

Methylation-specific oligonucleotide microarray.

The methylation-specific oligonucleotide (MSO) microarray is a high-throughput approach capable of detecting DNA methylation in genes across several CpG sites. Based on the bisulfite modification of DNA that converts unmethylated cytosines to uracil but leaves the 5'methylcytosine intact, the method utilizes short oligonucleotides corresponding to the methylated and unmethylated alleles as probes affixed on solid support and products amplified from bisulfite-treated DNA as targets for hybridization. MSO is suitable for examining a panel of genes across multiple clinical samples.

Methyl-CpG binding proteins identify novel sites of epigenetic inactivation in human cancer.

Methyl-CpG binding proteins (MBDs) mediate histone deacetylase-dependent transcriptional silencing at methylated CpG islands. Using chromatin immunoprecitation (ChIP) we have found that gene-specific profiles of MBDs exist for hypermethylated promoters of breast cancer cells, whilst a common pattern of histone modifications is shared. This unique distribution of MBDs is also characterized in chromosomes by comparative genomic hybridization of immunoprecipitated DNA and immunolocalization.

Double RNA interference of DNMT3b and DNMT1 enhances DNA demethylation and gene reactivation.

Small interfering RNAs (siRNAs) are newly identified molecules shown to silence genes via targeted mRNA degradation. In this study, we used specific siRNAs as a tool to probe the relationship between two DNA methyltransferase genes, DNMT3b and DNMT1, in the maintenance of DNA methylation patterns in the genome. Levels of DNMT3b or DNMT1 mRNAs and proteins were markedly decreased (up to 80%) on transfecting these siRNAs into the ovarian cancer cell line CP70.

Genetic unmasking of epigenetically silenced tumor suppressor genes in colon cancer cells deficient in DNA methyltransferases.

Hypermethylation associated silencing of the CpG islands of tumor suppressor genes is a common hallmark of human cancer. Here we report a functional search for hypermethylated CpG islands using the colorectal cancer cell line HCT-116, in which two major DNA methyltransferases, DNMT1 and DNMT3b, have been genetically disrupted (DKO cells). Using two molecular screenings for differentially methylated loci [differential methylation hybridization (DMH) and amplification of inter-methylated sites (AIMS)], we found that DKO cells, but not the single DNMT1 or DNMT3b knockouts, have a massive loss of hypermethylated CpG islands that induces the re-activation of the contiguous genes.

Methylation target array for rapid analysis of CpG island hypermethylation in multiple tissue genomes.

Hypermethylation of multiple CpG islands is a common event in cancer. To assess the prognostic values of this epigenetic alteration, we developed Methylation Target Array (MTA), derived from the concept of tissue microarray, for simultaneous analysis of DNA hypermethylation in hundreds of tissue genomes. In MTA, linker-ligated CpG island fragments were digested with methylation-sensitive endonucleases and amplified with flanking primers.

Triple analysis of the cancer epigenome: an integrated microarray system for assessing gene expression, DNA methylation, and histone acetylation.

We developed a novel microarray system to assess gene expression, DNA methylation, and histone acetylation in parallel, and to dissect the complex hierarchy of epigenetic changes in cancer. An integrated microarray panel consisting of 1507 short CpG island tags located at the 5'-end regions (including the first exons) was used to assess effects of epigenetic treatments on a human epithelial ovarian cancer cell line. Treatment with methylation (5-aza-2'-deoxycytidine) or deacetylation (trichostatin A) inhibitors alone resulted in up-regulation of 1.

Aberrant DNA methylation in ovarian cancer: is there an epigenetic predisposition to drug response?

Epigenetic regulation of gene expression has been observed in a variety of tumor types. We have used microarray technology to evaluate the predisposition of drug response by aberrant methylation in ovarian cancer. Results indicate that loss of gene activity due to hypermethylation potentially confers a predisposition in certain cancer types and is an early event in disease progression.

Applications of CpG island microarrays for high-throughput analysis of DNA methylation.

Differential methylation hybridization (DMH) is a high-throughput microarray technique designed to identify changes in DNA methylation patterns commonly observed in cancer and other disease states. The DMH methodology comprises three fundamental components: the arraying of CpG island clones on glass slides, the preparation of the sample amplicons under investigation, and the hybridization of amplicon targets onto the CpG island microarray. Herein, we outline the DMH protocol and illustrate its utility and the validation approaches used in analyzing the hypermethylation profile of breast tumor and normal samples.

Methylation microarray analysis of late-stage ovarian carcinomas distinguishes progression-free survival in patients and identifies candidate epigenetic markers.

Purpose: The purpose of this study was to profile methylation alterations of CpG islands in ovarian tumors and to identify candidate markers for diagnosis and prognosis of the disease.

Experimental Design: A global analysis of DNA methylation using a novel microarray approach called differential methylation hybridization was performed on 19 patients with stage III and IV ovarian carcinomas.

Results: Hierarchical clustering identified two groups of patients with distinct methylation profiles.

Structure and Macromolecular Composition of the Egg and Embryo Jelly Coats of the Anuran Lepidobatrachus laevis: (frog jelly coat/fertilization/glycoprotein).

Eggs and cleavage-stage embryos of the frog Lepidobatrachus laevis are encased by 3 μm thick vitelline/fertilization envelope and two jelly layers, termed J (innermost) and J (outermost). Based on light and transmission electron microscopy, J had a dense reticular appearance whereas J had a laminar structure. Direct dissolution of the jelly coats was accomplished by reduction of disulfide bonds with 0.