Evaluation of cell-free DNA approaches for multi-cancer early detection.

In the Circulating Cell-free Genome Atlas (NCT02889978) substudy 1, we evaluate several approaches for a circulating cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test by defining clinical limit of detection (LOD) based on circulating tumor allele fraction (cTAF), enabling performance comparisons. Among 10 machine-learning classifiers trained on the same samples and independently validated, when evaluated at 98% specificity, those using whole-genome (WG) methylation, single nucleotide variants with paired white blood cell background removal, and combined scores from classifiers evaluated in this study show the highest cancer signal detection sensitivities. Compared with clinical stage and tumor type, cTAF is a more significant predictor of classifier performance and may more closely reflect tumor biology. Clinical LODs mirror relative sensitivities for all approaches. The WG methylation feature best predicts cancer signal origin. WG methylation is the most promising technology for MCED and informs development of a targeted methylation MCED test.

Genome-wide characteristics of de novo mutations in autism.

De novo mutations (DNMs) are important in Autism Spectrum Disorder (ASD), but so far analyses have mainly been on the ~1.5% of the genome encoding genes. Here, we performed whole genome sequencing (WGS) of 200 ASD parent-child trios and characterized germline and somatic DNMs. We confirmed that the majority of germline DNMs (75.6%) originated from the father, and these increased significantly with paternal age only (p=4.2×10-10). However, when clustered DNMs (those within 20kb) were found in ASD, not only did they mostly originate from the mother (p=7.7×10-13), but they could also be found adjacent to de novo copy number variations (CNVs) where the mutation rate was significantly elevated (p=2.4×10-24). By comparing DNMs detected in controls, we found a significant enrichment of predicted damaging DNMs in ASD cases (p=8.0×10-9; OR=1.84), of which 15.6% (p=4.3×10-3) and 22.5% (p=7.0×10-5) were in the non-coding or genic non-coding, respectively. The non-coding elements most enriched for DNM were untranslated regions of genes, boundaries involved in exon-skipping and DNase I hypersensitive regions. Using microarrays and a novel outlier detection test, we also found aberrant methylation profiles in 2/185 (1.1%) of ASD cases. These same individuals carried independently identified DNMs in the ASD risk- and epigenetic- genes DNMT3A and ADNP. Our data begins to characterize different genome-wide DNMs, and highlight the contribution of non-coding variants, to the etiology of ASD.

Data Shared Lasso: A Novel Tool to Discover Uplift.

A model is presented for the supervised learning problem where the observations come from a fixed number of pre-specified groups, and the regression coefficients may vary sparsely between groups. The model spans the continuum between individual models for each group and one model for all groups. The resulting algorithm is designed with a high dimensional framework in mind. The approach is applied to a sentiment analysis dataset to show its efficacy and interpretability. One particularly useful application is for finding sub-populations in a randomized trial for which an intervention (treatment) is beneficial, often called the uplift problem. Some new concepts are introduced that are useful for uplift analysis. The value is demonstrated in an application to a real world credit card promotion dataset. In this example, although sending the promotion has a very small average effect, by targeting a particular subgroup with the promotion one can obtain a 15% increase in the proportion of people who purchase the new credit card.

Collaborative regression.

We consider the scenario where one observes an outcome variable and sets of features from multiple assays, all measured on the same set of samples. One approach that has been proposed for dealing with these type of data is "sparse multiple canonical correlation analysis" (sparse mCCA). All of the current sparse mCCA techniques are biconvex and thus have no guarantees about reaching a global optimum. We propose a method for performing sparse supervised canonical correlation analysis (sparse sCCA), a specific case of sparse mCCA when one of the datasets is a vector. Our proposal for sparse sCCA is convex and thus does not face the same difficulties as the other methods. We derive efficient algorithms for this problem that can be implemented with off the shelf solvers, and illustrate their use on simulated and real data.

Rate of false conviction of criminal defendants who are sentenced to death.

The rate of erroneous conviction of innocent criminal defendants is often described as not merely unknown but unknowable. There is no systematic method to determine the accuracy of a criminal conviction; if there were, these errors would not occur in the first place. As a result, very few false convictions are ever discovered, and those that are discovered are not representative of the group as a whole. In the United States, however, a high proportion of false convictions that do come to light and produce exonerations are concentrated among the tiny minority of cases in which defendants are sentenced to death. This makes it possible to use data on death row exonerations to estimate the overall rate of false conviction among death sentences. The high rate of exoneration among death-sentenced defendants appears to be driven by the threat of execution, but most death-sentenced defendants are removed from death row and resentenced to life imprisonment, after which the likelihood of exoneration drops sharply. We use survival analysis to model this effect, and estimate that if all death-sentenced defendants remained under sentence of death indefinitely, at least 4.1% would be exonerated. We conclude that this is a conservative estimate of the proportion of false conviction among death sentences in the United States.

Automated cellular annotation for high-resolution images of adult Caenorhabditis elegans.

MOTIVATION: Advances in high-resolution microscopy have recently made possible the analysis of gene expression at the level of individual cells. The fixed lineage of cells in the adult worm Caenorhabditis elegans makes this organism an ideal model for studying complex biological processes like development and aging. However, annotating individual cells in images of adult C.elegans typically requires expertise and significant manual effort. Automation of this task is therefore critical to enabling high-resolution studies of a large number of genes. RESULTS: In this article, we describe an automated method for annotating a subset of 154 cells (including various muscle, intestinal and hypodermal cells) in high-resolution images of adult C.elegans. We formulate the task of labeling cells within an image as a combinatorial optimization problem, where the goal is to minimize a scoring function that compares cells in a test input image with cells from a training atlas of manually annotated worms according to various spatial and morphological characteristics. We propose an approach for solving this problem based on reduction to minimum-cost maximum-flow and apply a cross-entropy-based learning algorithm to tune the weights of our scoring function. We achieve 84% median accuracy across a set of 154 cell labels in this highly variable system. These results demonstrate the feasibility of the automatic annotation of microscopy-based images in adult C.elegans.

CONTRAST: a discriminative, phylogeny-free approach to multiple informant de novo gene prediction.

We describe CONTRAST, a gene predictor which directly incorporates information from multiple alignments rather than employing phylogenetic models. This is accomplished through the use of discriminative machine learning techniques, including a novel training algorithm. We use a two-stage approach, in which a set of binary classifiers designed to recognize coding region boundaries is combined with a global model of gene structure. CONTRAST predicts exact coding region structures for 65% more human genes than the previous state-of-the-art method, misses 46% fewer exons and displays comparable gains in specificity.

Gangliocytic paraganglioma: case report and review of the literature.

Gangliocytic paraganglioma is a rare tumor, which occurs nearly exclusively in the second portion of the duodenum. Generally, this tumor has a benign clinical course, although rarely, it may recur or metastasize to regional lymph nodes. Only one case with distant metastasis has been reported. We present a case of duodenal gangliocytic paraganglioma treated first by local resection followed by pylorus-preserving pancreaticoduodenectomy. Examination of the first specimen revealed focal nuclear pleomorphism and mitotic activity, in addition to the presence of three characteristic histologic components: epithelioid, ganglion, and spindle cell. In the subsequent pancreaticoduodenectomy specimen, there was no residual tumor identified in the periampullary area, but metastatic gangliocytic paraganglioma was present in two of seven lymph nodes. This case report confirms the malignant potential of this tumor. We review the published literature on gangliocytic paragangliomas pursuing a malignant course. We conclude that surgical therapy of these neoplasms should not be limited to local resection, as disease recurrence, lymph node involvement, and rarely distant metastasis may occur.

Using multiple alignments to improve gene prediction.

The multiple species de novo gene prediction problem can be stated as follows: given an alignment of genomic sequences from two or more organisms, predict the location and structure of all protein-coding genes in one or more of the sequences. Here, we present a new system, N-SCAN (a.k.a. TWINSCAN 3.0), for addressing this problem. N-SCAN can model the phylogenetic relationships between the aligned genome sequences, context dependent substitution rates, and insertions and deletions. An implementation of N-SCAN was created and used to generate predictions for the entire human genome and the genome of the fruit fly Drosophila melanogaster. Analyses of the predictions reveal that N-SCAN's accuracy in both human and fly exceeds that of all previously published whole-genome de novo gene predictors.

Survey of parents, nurses, and school principals on their perceptions of the controversial role of schools in health promotion.

BACKGROUND: The aim of this paper was to study the perceptions of parents, nurses, and school principals of the role of the health services in elementary schools. METHODS: A questionnaire was distributed to the heads of parents' committees, school nurses, and school principals of 35 randomly selected elementary public schools in Israel. Respondents were asked to qualify the degree of importance of the traditional and contemporary roles of the school health-care team. RESULTS: Response rates were 80.0% for parents, 100% for nurses, and 97.1% for principals. All respondents agreed that both the traditional and new roles are very important. Nurses rated three interconnected roles significantly lower than parents and school principals: 'Evaluation of students with behavioral problems', 'Evaluation of students with low academic performance', and 'Follow up and care of students with behavioral problems and low performance'. CONCLUSIONS: Nurses, parents and school principals in Israel agree that the traditional roles of health teams in elementary schools, that is, providing first aid and ensuring school hygiene, are very important. Most are ready to accept a move from an illness-based to a social-based model, with less time spent on screening and surveillance and more on identifying and managing special needs of children and staff.

Pediatrician attitudes to exclusion of ill children from child-care centers in Israel: pressure on ambulatory practices.

BACKGROUND: The exclusion of ill children from child-care centers may be associated with high social, economic and medical costs. OBJECTIVE: To assess the opinions of pediatricians working in an outpatient setting in Israel on the exclusion/return of children in child-care centers. METHODS: A questionnaire on practices of exclusion/return of children in child-care centers, in general and according to specific signs and symptoms, was administered to a random computer-selected cross-sectional sample of 192 primary care community pediatricians in Israel. RESULTS: One hundred and seventy-three pediatricians completed the questionnaires, for a response rate of 90%; 147 were board-certified and 26 were not. About half the pediatricians felt pressured by parents requesting antibiotic therapy to accelerate the return of their sick child to the child-care center. The majority also believed their practice was overloaded by often unnecessary demands for medical notes by the child-care centers before children could return. More than half based their decision to exclude children on "common sense" and the remainder, on accepted guidelines. Except for scabies and lice, there were no significant correlations between the physicians' stipulation for a note on return of the child and the specific illness guidelines. CONCLUSIONS: This study shows that a high proportion of pediatricians based their exclusion practices on "common sense" and personal understanding instead of established guidelines, and that the guidelines did not affect their opinion on the duration of illness that warrant a note. Furthermore, half were subjected to parental pressure to employ inappropriate practices. These findings, combined with our earlier survey of child-care centers staff, indicate that better education of parents and day-care staff about ill child-care-center-exclusion policy in Israel would increase their common understanding with pediatricians.

Begin at the beginning: predicting genes with 5' UTRs.

The retrainable, comparative gene predictor N-SCAN integrates multigenome modeling and 5' untranslated region (5' UTR) modeling. In this article, we evaluate N-SCAN's transcription-start site (TSS) and first exon predictions both computationally and experimentally. The computational results indicate that N-SCAN is more accurate than any of the other tools we tested at predicting the TSS and the complete first exon. It is the only one of these tools that can predict complete gene structures together with 5' UTRs. Experimental evaluation shows that N-SCAN can be used to validate novel UTR introns in human gene predictions that do not overlap any RefSeq gene and even to correct RefSeq mRNAs by adding validated UTR exons that are missing from RefSeq.

Exclusion of ill children from child-care centers in Israel.

The aim of the study was to examine criteria for ill children in child-care centers. A questionnaire on practices of exclusion/return of children according to specific signs and symptoms was mailed to the directors of care centers in central Israel. Thirty-six of the 60 questionnaires (60%) were returned by mail and the reminded were completed in personal visits to the CCCs achieving a response rate of 100%. About half (51.7%) used "common sense" and "personal feelings" to exclude children and to allow their return, and 29 (48.3%) used the guidelines of the Ministries of Education and Health or other authorities. The percentage of centers excluding children by signs/symptoms was as follows: high fever (>38 degrees C), 100%; low-grade fever, 76.7%; asthma exacerbation, 80.0%; heavy cough, 75.0%; eye discharge or conjunctivitis, 83.3%; diarrhea and vomiting more than twice per day, 100%; rash, 72.3%; otalgia, 46.7%; and infected skin lesion, 66.7%. Only four centers excluded children with head lice. Most centers required a physician's note on return of a child after high fever (76.7%), eye discharge or conjunctivitis (48.3%), and from 75 to 80%, respectively, for frequent vomiting and bloody or mucinous diarrhea. The results show that exclusion practices among child-care centers (CCCs) vary widely, suggesting the need for the establishment of a uniform exclusion and return policy in Israel, with distribution of clear, up-to-date guidelines on the prevention and control of communicable diseases to all day-care centers. In a simple way, this study identified attitudes concerning the exclusion/return of sick children in CCCs and was useful for the discussion of the related policy with CCCs responsible and national health and educational authorities.

Feasibility of diffusion-NMR surface-to-volume measurements tested by calculations and computer simulations.

It has been demonstrated previously that the surface-to-volume ratio S/V can be determined from the derivative of the time-dependent diffusion coefficient D(t), in the limit t --> 0. Several questions arise concerning the practicality of determining S/V by NMR. In particular, how large are the errors generated by (1) working outside the t --> 0 limit and (2) measuring D outside the b --> 0 limit, both for narrow and full-width gradient pulses? Here b is gamma2G2delta2Delta for narrow pulses and gamma2G2t3/12 for broad pulses. These questions are addressed by random-walk computer simulations and numerical calculations in geometries relevant to small-airways of lung. The results demonstrate that one can work well outside the t --> 0 and b --> 0 limits, provided 10-20% accuracy in the measured S/V is sufficient. Emphasis is placed on the useful range of times t for which NMR determinations of lung S/V are feasible.

Adverse reactions to accidental forearm injection of Bacille Calmette-Guerin vaccine in schoolchildren: 12-month cohort follow-up.

This study examined the natural history of reaction after accidental intradermal administration of bacille Calmette-Guerin (BCG) vaccine instead of purified protein derivative (PPD) in 226 schoolchildren. At 18 days after vaccination, a local reaction with a diameter of 4.5-14 mm was found in 62% of the students, and ulceration with discharge was found in 26.6%; corresponding rates at 120 days were 72.3% and 38% and at 281 days were 73% and 6%. At 345 days, 85% of the students had a dry scar measuring 5-14 mm in diameter, and none had ulceration or discharge.