Predicting synthetic lethal interactions using conserved patterns in protein interaction networks

In response to a need for improved treatments, a number of promising novel targeted cancer therapies are being developed that exploit human synthetic lethal interactions. This is facilitating personalised medicine strategies in cancers where specific tumour suppressors have become inactivated. Mainly due to the constraints of the experimental procedures, relatively few human synthetic lethal interactions have been identified. Here we describe SLant (Synthetic Lethal analysis via Network topology), a computational systems approach to predicting human synthetic lethal interactions that works by identifying and exploiting conserved patterns in protein interaction network topology both within and across species. SLant out-performs previous attempts to classify human SSL interactions and experimental validation of the models predictions suggests it may provide useful guidance for future SSL screenings and ultimately aid targeted cancer therapy development

Design and rationale of the B-lines lung ultrasound guided emergency department management of acute heart failure (BLUSHED-AHF) pilot trial

Background Medical treatment for acute heart failure (AHF) has not changed substantially over the last four decades. Emergency department (ED)-based evidence for treatment is limited. Outcomes remain poor, with a 25% mortality or re-admission rate within 30 days post discharge. Targeting pulmonary congestion, which can be objectively assessed using lung ultrasound (LUS), may be associated with improved outcomes. Methods BLUSHED-AHF is a multicenter, randomized, pilot trial designed to test whether a strategy of care that utilizes a LUS-driven treatment protocol outperforms usual care for reducing pulmonary congestion in the ED. We will randomize 130 ED patients with AHF across five sites to, a) a structured treatment strategy guided by LUS vs. b) a structured treatment strategy guided by usual care. LUS-guided care will continue until there are ≤15 B-lines on LUS or 6h post enrollment. The primary outcome is the proportion of patients with B-lines ≤ 15 at the conclusion of 6 h of management. Patients will continue to undergo serial LUS exams during hospitalization, to better understand the time course of pulmonary congestion. Follow up will occur through 90 days, exploring days-alive-and-out-of-hospital between the two arms. The study is registered on ClinicalTrials.gov (NCT03136198). Conclusion If successful, this pilot study will inform future, larger trial design on LUS driven therapy aimed at guiding treatment and improving outcomes in patients with AHF

Handoffs and Transitions in Critical Care (HATRICC): Protocol for a Mixed Methods Study of Operating Room to Intensive Care Unit Handoffs

Background: Operating room to intensive care unit handoffs are high-risk events for critically ill patients. Studies in selected patient populations show that standardizing operating room to intensive care unit handoffs improves information exchange and decreases errors. To adapt these findings to mixed surgical populations, we propose to study the implementation of a standardized operating room to intensive care unit handoff process in two intensive care units currently without an existing standard process. Methods/Design: The Handoffs and Transitions in Critical Care (HATRICC) study is a hybrid effectiveness- implementation trial of operating room to intensive care unit handoffs. We will use mixed methods to conduct a needs assessment of the current handoff process, adapt published handoff processes, and implement a new standardized handoff process in two academic intensive care units. Needs assessment: We will use non-participant observation to observe the current handoff process. Focus groups, interviews, and surveys of clinicians will elicit participants’ impressions about the current process. Adaptation and implementation: We will adapt published standardized handoff processes using the needs assessment findings. We will use small group simulation to test the new process’ feasibility. After simulation, we will incorporate the new handoff process into the clinical work of all providers in the study units. Evaluation: Using the same methods employed in the needs assessment phase, we will evaluate use of the new handoff process. Data analysis: The primary effectiveness outcome is the number of information omissions per handoff episode as compared to the pre-intervention period. Additional intervention outcomes include patient intensive care unit length of stay and intensive care unit mortality. The primary implementation outcome is acceptability of the new process. Additional implementation outcomes include feasibility, fidelity and sustainability. Discussion: The HATRICC study will examine the effectiveness and implementation of a standardized operating room to intensive care unit handoff process. Findings from this study have the potential to improve healthcare communication and outcomes for critically ill patients. Trial registration: ClinicalTrials.gov identifier: NCT02267174. Date of registration October 16, 2014

Darwin -— an experimental astronomy mission to search for extrasolar planets

As a response to ESA call for mission concepts for its Cosmic Vision 2015–2025 plan, we propose a mission called Darwin. Its primary goal is the study of terrestrial extrasolar planets and the search for life on them. In this paper, we describe different characteristics of the instrument

Bostonia: The Boston University Alumni Magazine. Volume 10

Founded in 1900, Bostonia magazine is Boston University's main alumni publication, which covers alumni and student life, as well as university activities, events, and programs

Fibroblasts from Distinct Pancreatic Pathologies Exhibit Disease-Specific Properties.

Although fibrotic stroma forms an integral component of pancreatic diseases, whether fibroblasts programmed by different types of pancreatic diseases are phenotypically distinct remains unknown. Here, we show that fibroblasts isolated from patients with pancreatic ductal adenocarcinoma (PDAC), chronic pancreatitis (CP), periampullary tumors, and adjacent normal (NA) tissue (N = 34) have distinct mRNA and miRNA profiles. Compared with NA fibroblasts, PDAC-associated fibroblasts were generally less sensitive to an antifibrotic stimulus (NPPB) and more responsive to positive regulators of activation such as TGFβ1 and WNT. Of the disease-associated fibroblasts examined, PDAC- and CP-derived fibroblasts shared greatest similarity, yet PDAC-associated fibroblasts expressed higher levels of tenascin C (TNC), a finding attributable to miR-137, a novel regulator of TNC. TNC protein and transcript levels were higher in PDAC tissue versus CP tissue and were associated with greater levels of stromal activation, and conditioned media from TNC-depleted PDAC-associated fibroblasts modestly increased both PDAC cell proliferation and PDAC cell migration, indicating that stromal TNC may have inhibitory effects on PDAC cells. Finally, circulating TNC levels were higher in patients with PDAC compared with CP. Our characterization of pancreatic fibroblast programming as disease-specific has consequences for therapeutic targeting and for the manner in which fibroblasts are used in research. SIGNIFICANCE: Primary fibroblasts derived from various types of pancreatic diseases possess and retain distinct molecular and functional characteristics in culture, providing a series of cellular models for treatment development and disease-specific research

What is the DSM? Diagnostic manual, cultural icon, political battleground: an overview with suggestions for a critical research agenda

The Diagnostic and Statistical Manual of Mental Disorders of the APA (known as the DSM) is a system for the classification of mental disorders that provides diagnostic criteria used by psychiatrists and experts in related fields. Although classification systems and standards are ubiquitous in social life, they are rarely conspicuous and almost never become an object of public debate. Yet the DSM has attained the status of a ‘cultural icon’ and has been an object of commentary and controversy internationally. This article offers an introduction to the DSM and to the conditions of possibility for its global influence, based on a critical synthesis of historico-sociological approaches to the manual. In the second part of the article, three keywords – polyvalence, ambivalence and participation – are offered to focus on three points for reflection. The first point concerns the reasons for the manual’s continuing prominence and resistance to change since the publication of its third edition in 1980. The second concerns the reasons why, while acknowledging the importance of the DSM, we should neither overestimate it nor take it at face value. The third defines the question of participatory politics as part of a sociological research agenda in relation to the DSM

Evolution and diversity of Rickettsia bacteria

Background: Rickettsia are intracellular symbionts of eukaryotes that are best known for infecting and causing serious diseases in humans and other mammals. All known vertebrate-associated Rickettsia are vectored by arthropods as part of their life-cycle, and many other Rickettsia are found exclusively in arthropods with no known secondary host. However, little is known about the biology of these latter strains. Here, we have identified 20 new strains of Rickettsia from arthropods, and constructed a multi-gene phylogeny of the entire genus which includes these new strains.Results: We show that Rickettsia are primarily arthropod-associated bacteria, and identify several novel groups within the genus. Rickettsia do not co-speciate with their hosts but host shifts most often occur between related arthropods. Rickettsia have evolved adaptations including transmission through vertebrates and killing males in some arthropod hosts. We uncovered one case of horizontal gene transfer among Rickettsia, where a strain is a chimera from two distantly related groups, but multi-gene analysis indicates that different parts of the genome tend to share the same phylogeny.Conclusion: Approximately 150 million years ago, Rickettsia split into two main clades, one of which primarily infects arthropods, and the other infects a diverse range of protists, other eukaryotes and arthropods. There was then a rapid radiation about 50 million years ago, which coincided with the evolution of life history adaptations in a few branches of the phylogeny. Even though Rickettsia are thought to be primarily transmitted vertically, host associations are short lived with frequent switching to new host lineages. Recombination throughout the genus is generally uncommon, although there is evidence of horizontal gene transfer. A better understanding of the evolution of Rickettsia will help in the future to elucidate the mechanisms of pathogenicity, transmission and virulence

Identification of novel loci associated with hip shape:a meta-analysis of genome-wide association studies

This study was funded by Arthritis Research UK project grant 20244, which also provided salary funding for DB and CVG. LP works in the MRC Integrative Epidemiology Unit, a UK MRC‐funded unit (MC_ UU_ 12013/4 & MC_UU_12013/5). ALSPAC: We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, and nurses. ALSPAC data collection was supported by the Wellcome Trust (grants WT092830M; WT088806; WT102215/2/13/2), UK Medical Research Council (G1001357), and University of Bristol. The UK Medical Research Council and the Wellcome Trust (102215/2/13/2) and the University of Bristol provide core support for ALSPAC. Framingham Heart Study: The Framingham Osteoporosis Study is supported by grants from the National Institute of Arthritis, Musculoskeletal, and Skin Diseases and the National Institute on Aging (R01 AR41398, R01 AR 061162, R01 AR050066, and R01 AR061445). The analyses reflect intellectual input and resource development from the Framingham Heart Study investigators participating in the SNP Health Association Resource project. The Framingham Heart Study of the National Heart, Lung, and Blood Institute of the National Institutes of Health and Boston University School of Medicine were supported by the National Heart, Lung, and Blood Institute's Framingham Heart Study (N01‐HC‐25195) and its contract with Affymetrix, Inc., for genotyping services (N02‐HL‐6‐4278). Analyses reflect intellectual input and resource development from the Framingham Heart Study investigators participating in the SNP Health Association Resource (SHARe) project. A portion of this research was conducted using the Linux Cluster for Genetic Analysis (LinGA‐II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. DK was also supported by Israel Science Foundation grant #1283/14. TDC and DR thank Dr Claire Reardon and the entire Harvard University Bauer Core facility for assistance with ATAC‐seq next generation sequencing. This work was funded in part by the Harvard University Milton Fund, NSF (BCS‐1518596), and NIH NIAMS (1R01AR070139‐01A1) to TDC. MrOS: The Osteoporotic Fractures in Men (MrOS) Study is supported by National Institutes of Health funding. The following institutes provide support: the National Institute on Aging (NIA), the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), the National Center for Advancing Translational Sciences (NCATS), and NIH Roadmap for Medical Research under the following grant numbers: U01 AG027810, U01 AG042124, U01 AG042139, U01 AG042140, U01 AG042143, U01 AG042145, U01 AG042168, U01 AR066160, and UL1 TR000128. The National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) provides funding for the MrOS ancillary study “Replication of candidate gene associations and bone strength phenotype in MrOS” under the grant number R01 AR051124. The National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) provides funding for the MrOS ancillary study “GWAS in MrOS and SOF” under the grant number RC2 AR058973. SOF: The Study of Osteoporotic Fractures (SOF) is supported by National Institutes of Health funding. The National Institute on Aging (NIA) provides support under the following grant numbers: R01 AG005407, R01 AR35582, R01 AR35583, R01 AR35584, R01 AG005394, R01 AG027574, and R01 AG027576. TwinsUK: The study was funded by the Wellcome Trust; European Community's Seventh Framework Programme (FP7/2007‐2013). The study also receives support from the National Institute for Health Research (NIHR)‐funded BioResource, Clinical Research Facility, and Biomedical Research Centre based at Guy's and St Thomas’ NHS Foundation Trust in partnership with King's College London. SNP genotyping was performed by The Wellcome Trust Sanger Institute and National Eye Institute via NIH/CIDR. This study was also supported by the Australian National Health and Medical Research Council (project grants 1048216 and 1127156), the Sir Charles Gairdner Hospital RAC (SGW), and the iVEC/Pawsey Supercomputing Centre (project grants Pawsey0162 and Director2025 [SGW]). The salary of BHM was supported by a Raine Medical Research Foundation Priming Grant. The Umeå Fracture and Osteoporosis Study (UFO) is supported by the Swedish Research Council (K20006‐72X‐20155013), the Swedish Sports Research Council (87/06), the Swedish Society of Medicine, the Kempe‐Foundation (JCK‐1021), and by grants from the Medical Faculty of Umeå Unviersity (ALFVLL:968:22‐2005, ALFVL:‐937‐2006, ALFVLL:223:11‐2007, and ALFVLL:78151‐2009) and from the county council of Västerbotten (Spjutspetsanslag VLL:159:33‐2007). This publication is the work of the authors and does not necessarily reflect the views of any funders. None of the funders had any influence on data collection, analysis, interpretation of the results, or writing of the paper. DB will serve as the guarantor of the paper. Authors’ roles: Study conception and design: DAB, JSG, RMA, LP, DK, and JHT. Data collection: DJ, DPK, ESO, SRC, NEL, BHM, FMKW, JBR, SGW, TDC, BGF, DAL, CO, and UP‐L. Data analysis: DAB, DSE, FKK, JSG, FRS, CVG, RJB, RMA, SGW, EG, TDC, DR, and TB. Data interpretation: JSG, RMA, TDC, DR, DME, LP, DK, and JHT. Drafting manuscript: DAB and JHT. Revising manuscript content: JHT. All authors approved the final version of manuscript. DAB takes responsibility for the integrity of the data analysis.Peer reviewedPublisher PD