Celebrating 70: An Interview with Don Berry

Donald (Don) Arthur Berry, born May 26, 1940 in Southbridge, Massachusetts, earned his A.B. degree in mathematics from Dartmouth College and his M.A. and Ph.D. in statistics from Yale University. He served first on the faculty at the University of Minnesota and subsequently held endowed chair positions at Duke University and The University of Texas M.D. Anderson Center. At the time of the interview he served as Head of the Division of Quantitative Sciences, and Chairman and Professor of the Department of Biostatistics at UT M.D. Anderson Center.Comment: Published in at http://dx.doi.org/10.1214/11-STS366 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

BAYESIAN HYPOTHESIS TEST: Using Surface Integrals to Distribute Prior Information Among the Hypotheses

A solution to the problem of transferring the prior preferences about the paraIlleters of interest to the spaces defined by the hypotheses in test is proposed. We make use of surface (line) integrals to obtain tlus solution

Acute Presentation of Congenital Diaphragmatic Hernia Requiring Damage Control Laparotomy in an Adult Patient

Congenital diaphragmatic hernias constitute an infrequent but potentially serious presentation of bowel obstruction in the adult patient. Herein, we present a rare case of an adult patient with strangulation of colon within a Morgagni\u27s hernia where timely recognition and intervention were life-saving. An 18-year-old female presented with an acute abdomen, respiratory failure, and shock secondary to a strangulated, previously undiagnosed Morgagni hernia requiring emergency laparotomy, reduction of hernia contents and resection of non-viable colon. The patient underwent repair of the hernia with restoration of bowel continuity and reconstruction of her abdominal wall in sequential fashion. Although congenital diaphragmatic hernias have been previously described in the adult population, there are few if any reports of such pathology presenting in such an acute, life-threatening fashion. This case highlights the importance of a high index of suspicion, early recognition, and timely surgical intervention for this rare, potentially fatal condition

Recommendations for the design of small population clinical trials

Background Orphan drug development faces numerous challenges, including low disease prevalence, patient population heterogeneity, and strong presence of paediatric patient populations. Consequently, clinical trials for orphan drugs are often smaller than those of non-orphan drugs, and they require the development of efficient trial designs relevant to small populations to gain the most information from the available data. The International Rare Diseases Research Consortium (IRDiRC) is aimed at promoting international collaboration and advance rare diseases research worldwide, and has as one of its goals to contribute to 1000 new therapies for rare diseases. IRDiRC set up a Small Population Clinical Trials (SPCT) Task Force in order to address the shortcomings of our understanding in carrying out clinical trials in rare diseases. Results The IRDiRC SPCT Task Force met in March 2016 to discuss challenges faced in the design of small studies for rare diseases and present their recommendations, structured around six topics: different study methods/designs and their relation to different characteristics of medical conditions, adequate safety data, multi-arm trial designs, decision analytic approaches and rational approaches to adjusting levels of evidence, extrapolation, and patients’ engagement in study design. Conclusions Recommendations have been issued based on discussions of the Small Population Clinical Trials Task Force that aim to contribute towards successful therapy development and clinical use. While randomised clinical trials are still considered the gold standard, it is recommended to systematically take into consideration alternative trial design options when studying treatments for a rare disease. Combining different sources of safety data is important to give a fuller picture of a therapy’s safety profile. Multi-arm trials should be considered an opportunity for rare diseases therapy development, and funders are encouraged to support such trial design via international networks. Patient engagement is critical in trial design and therapy development, a process which sponsors are encouraged to incorporate when conducting trials and clinical studies. Input from multiple regulatory agencies is recommended early and throughout clinical development. Regulators are often supportive of new clinical trial designs, provided they are well thought through and justified, and they also welcome discussions and questions on this topic. Parallel advice for multiregional development programs should also be considered

Evidence and Credibility: Full Bayesian Significance Test for Precise Hypotheses.

A Bayesian measure of evidence for precise hypotheses is presented. The intention is to give a Bayesian alternative to significance tests or, equivalently, to p-values. In fact, a set is defined in the parameter space and the posterior probability, its credibility, is evaluated. This set is the “Highest Posterior Density Region” that is “tangent” to the set that defines the null hypothesis. Our measure of evidence is the complement of the credibility of the “tangent” region

A Prediction Model to Prioritize Individuals for a SARS-CoV-2 Test Built from National Symptom Surveys

Background: The gold standard for COVID-19 diagnosis is detection of viral RNA through PCR. Due to global limitations in testing capacity, effective prioritization of individuals for testing is essential. Methods: We devised a model estimating the probability of an individual to test positive for COVID-19 based on answers to 9 simple questions that have been associated with SARS-CoV-2 infection. Our model was devised from a subsample of a national symptom survey that was answered over 2 million times in Israel in its first 2 months and a targeted survey distributed to all residents of several cities in Israel. Overall, 43,752 adults were included, from which 498 self-reported as being COVID-19 positive. Findings: Our model was validated on a held-out set of individuals from Israel where it achieved an auROC of 0.737 (CI: 0.712–0.759) and auPR of 0.144 (CI: 0.119–0.177) and demonstrated its applicability outside of Israel in an independently collected symptom survey dataset from the US, UK, and Sweden. Our analyses revealed interactions between several symptoms and age, suggesting variation in the clinical manifestation of the disease in different age groups. Conclusions: Our tool can be used online and without exposure to suspected patients, thus suggesting worldwide utility in combating COVID-19 by better directing the limited testing resources through prioritization of individuals for testing, thereby increasing the rate at which positive individuals can be identified. Moreover, individuals at high risk for a positive test result can be isolated prior to testing. Funding: E.S. is supported by the Crown Human Genome Center, Larson Charitable Foundation New Scientist Fund, Else Kroener Fresenius Foundation, White Rose International Foundation, Ben B. and Joyce E. Eisenberg Foundation, Nissenbaum Family, Marcos Pinheiro de Andrade and Vanessa Buchheim, Lady Michelle Michels, and Aliza Moussaieff and grants funded by the Minerva foundation with funding from the Federal German Ministry for Education and Research and by the European Research Council and the Israel Science Foundation. H.R. is supported by the Israeli Council for Higher Education (CHE) via the Weizmann Data Science Research Center and by a research grant from Madame Olga Klein – Astrachan

Integrating DNA damage repair with the cell cycle

Abstract DNA is labile and constantly subject to damage. In addition to external mutagens, DNA is continuously damaged by the aqueous environment, cellular metabolites and is prone to strand breakage during replication. Cell duplication is orchestrated by the cell division cycle and specific DNA structures are processed differently depending on where in the cell cycle they are detected. This is often because a specific structure is physiological in one context, for example during DNA replication, while indicating a potentially pathological event in another, such as interphase or mitosis. Thus, contextualising the biochemical entity with respect to cell cycle progression provides information necessary to appropriately regulate DNA processing activities. We review the links between DNA repair and cell cycle context, drawing together recent advances

Cross-scale efficient tensor contractions for coupled cluster computations through multiple programming model backends

Coupled-cluster methods provide highly accurate models of molecular structure through explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix–matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts to extend the Libtensor framework to work in the distributed memory environment in a scalable and energy-efficient manner. We achieve up to 240× speedup compared with the optimized shared memory implementation of Libtensor. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures (Cray XC30 and XC40, and IBM Blue Gene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance, tasking and bulk synchronous models. Nevertheless, we preserve a unified interface to both programming models to maintain the productivity of computational quantum chemists

Modeling double strand break susceptibility to interrogate structural variation in cancer

Abstract Background Structural variants (SVs) are known to play important roles in a variety of cancers, but their origins and functional consequences are still poorly understood. Many SVs are thought to emerge from errors in the repair processes following DNA double strand breaks (DSBs). Results We used experimentally quantified DSB frequencies in cell lines with matched chromatin and sequence features to derive the first quantitative genome-wide models of DSB susceptibility. These models are accurate and provide novel insights into the mutational mechanisms generating DSBs. Models trained in one cell type can be successfully applied to others, but a substantial proportion of DSBs appear to reflect cell type-specific processes. Using model predictions as a proxy for susceptibility to DSBs in tumors, many SV-enriched regions appear to be poorly explained by selectively neutral mutational bias alone. A substantial number of these regions show unexpectedly high SV breakpoint frequencies given their predicted susceptibility to mutation and are therefore credible targets of positive selection in tumors. These putatively positively selected SV hotspots are enriched for genes previously shown to be oncogenic. In contrast, several hundred regions across the genome show unexpectedly low levels of SVs, given their relatively high susceptibility to mutation. These novel coldspot regions appear to be subject to purifying selection in tumors and are enriched for active promoters and enhancers. Conclusions We conclude that models of DSB susceptibility offer a rigorous approach to the inference of SVs putatively subject to selection in tumors

α-Synuclein Expression Selectively Affects Tumorigenesis in Mice Modeling Parkinson's Disease

Alpha Synuclein (α-Syn) is a protein implicated in mechanisms of neuronal degeneration in Parkinson's disease (PD). α-Syn is primarily a neuronal protein, however, its expression is found in various tumors including ovarian, colorectal and melanoma tumors. It has been hypothesized that neurodegeneration may share common mechanisms with oncogenesis. We tested whether α-Syn expression affects tumorigenesis of three types of tumors. Specifically, B16 melanoma, E0771 mammary gland adenocarcinoma and D122 Lewis lung carcinoma. For this aim, we utilized transgenic mice expression the human A53T α-Syn form. We found that the in vivo growth of B16 and E0771 but not D122 was enhanced in the A53T α-Syn mice. The effect on tumorigenesis was not detected in age-matched APP/PS1 mice, modeling Alzheimer's disease (AD), suggesting a specific effect for α-Syn- dependent neurodegeneration. Importantly, transgenic α-Syn expression was detected within the three tumor types. We further show uptake of exogenously added, purified α-Syn, by the cultured tumor cells. In accord, with the affected tumorigenesis in the young A53T α-Syn mice, over- expression of α-Syn in cultured B16 and E0771 cells enhanced proliferation, however, had no effect on the proliferation of D122 cells. Based on these results, we suggest that certain forms of α-Syn may selectively accelerate cellular mechanisms leading to cancer