Drilling for Admiralty: The OCSLA as a Bar to Maritime Law in OCS Drilling Accidents

Maritime law is ultimately driven by commerce. The seas were—and continue to be—one of the easiest ways to transfer goods over large distances. Yet maritime commerce has a relative newcomer that is not shipping or transportation focused—offshore drilling. Should admiralty and maritime law, intended to protect seamen and keep ships engaged in maritime commerce apply to personal injury claims on drilling rigs on the Outer Continental Shelf? This Note argues that they should not apply for two reasons. In Lozman v. Riviera Beach, the Supreme Court announced that a “vessel” should appear to the reasonable observer as intended to carry a person or things over water. Because a maritime tort requires a “vessel,” and the Lozman definition thereof suggests that drilling rigs are not “vessels,” admiralty and maritime law generally cannot apply to torts on drilling rigs. Moreover, Congress was explicit in the Outer Continental Shelf Lands Act that structures engaged in drilling were to be treated as enclaves of federal law in some “upland state.” Because the OCSLA is clear that it intends federal law such as the Long Shore Harbor Worker Compensation Act to apply to drill platform workers, admiralty and the general maritime law should not apply to drilling-related torts occurring on such rigs

Modeling precision treatment of breast cancer

Background: First-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets. Results: We used least squares-support vector machines and random forest algorithms to identify molecular features associated with responses of a collection of 70 breast cancer cell lines to 90 experimental or approved therapeutic agents. The datasets analyzed included measurements of copy number aberrations, mutations, gene and isoform expression, promoter methylation and protein expression. Transcriptional subtype contributed strongly to response predictors for 25% of compounds, and adding other molecular data types improved prediction for 65%. No single molecular dataset consistently out-performed the others, suggesting that therapeutic response is mediated at multiple levels in the genome. Response predictors were developed and applied to TCGA data, and were found to be present in subsets of those patient samples. Conclusions: These results suggest that matching patients to treatments based on transcriptional subtype will improve response rates, and inclusion of additional features from other profiling data types may provide additional benefit. Further, we suggest a systems biology strategy for guiding clinical trials so that patient cohorts most likely to respond to new therapies may be more efficiently identified

A molecular phylogeny of the cicadas (Hemiptera: Cicadidae) with a review of tribe and subfamily classification:

A molecular phylogeny and a review of family-group classification are presented for 137 species (ca. 125 genera) of the insect family Cicadidae, the true cicadas, plus two species of hairy cicadas (Tettigarctidae) and two outgroup species from Cercopidae. Five genes, two of them mitochondrial, comprise the 4992 base-pair molecular dataset. Maximum-likelihood and Bayesian phylogenetic results are shown, including analyses to address potential base composition bias. Tettigarcta is confirmed as the sister-clade of the Cicadidae and support is found for three subfamilies identified in an earlier morphological cladistic analysis. A set of paraphyletic deep-level clades formed by African genera are together named as Tettigomyiinae n. stat. Taxonomic reassignments of genera and tribes are made where morphological examination confirms incorrect placements suggested by the molecular tree, and 11 new tribes are defined (Arenopsaltriini n. tribe, Durangonini n. tribe, Katoini n. tribe, Lacetasini n. tribe, Macrotristriini n. tribe, Malagasiini n. tribe, Nelcyndanini n. tribe, Pagiphorini n. tribe, Pictilini n. tribe, Psaltodini n. tribe, and Selymbriini n. tribe). Tribe Tacuini n. syn. is synonymized with Cryptotympanini, and Tryellina n. syn. is synonymized with an expanded Tribe Lamotialnini. Tribe Hyantiini n. syn. is synonymized with Fidicinini. Tribe Sinosenini is transferred to Cicadinae from Cicadettinae, Cicadatrini is moved to Cicadettinae from Cicadinae, and Ydiellini and Tettigomyiini are transferred to Tettigomyiinae n. stat from Cicadettinae. While the subfamily Cicadinae, historically defined by the presence of timbal covers, is weakly supported in the molecular tree, high taxonomic rank is not supported for several earlier clades based on unique morphology associated with sound production

The UCSC cancer genomics browser: update 2011

The UCSC Cancer Genomics Browser (https://genome-cancer.ucsc.edu) comprises a suite of web-based tools to integrate, visualize and analyze cancer genomics and clinical data. The browser displays whole-genome views of genome-wide experimental measurements for multiple samples alongside their associated clinical information. Multiple data sets can be viewed simultaneously as coordinated ‘heatmap tracks’ to compare across studies or different data modalities. Users can order, filter, aggregate, classify and display data interactively based on any given feature set including clinical features, annotated biological pathways and user-contributed collections of genes. Integrated standard statistical tools provide dynamic quantitative analysis within all available data sets. The browser hosts a growing body of publicly available cancer genomics data from a variety of cancer types, including data generated from the Cancer Genome Atlas project. Multiple consortiums use the browser on confidential prepublication data enabled by private installations. Many new features have been added, including the hgMicroscope tumor image viewer, hgSignature for real-time genomic signature evaluation on any browser track, and ‘PARADIGM’ pathway tracks to display integrative pathway activities. The browser is integrated with the UCSC Genome Browser; thus inheriting and integrating the Genome Browser’s rich set of human biology and genetics data that enhances the interpretability of the cancer genomics data

In Vivo, In Vitro, and In Silico Characterization of Peptoids as Antimicrobial Agents

Bacterial resistance to conventional antibiotics is a global threat that has spurred the development of antimicrobial peptides (AMPs) and their mimetics as novel anti-infective agents. While the bioavailability of AMPs is often reduced due to protease activity, the non-natural structure of AMP mimetics renders them robust to proteolytic degradation, thus offering a distinct advantage for their clinical application. We explore the therapeutic potential of N-substituted glycines, or peptoids, as AMP mimics using a multi-faceted approach that includes in silico, in vitro, and in vivo techniques. We report a new QSAR model that we developed based on 27 diverse peptoid sequences, which accurately correlates antimicrobial peptoid structure with antimicrobial activity. We have identified a number of peptoids that have potent, broad-spectrum in vitro activity against multi-drug resistant bacterial strains. Lastly, using a murine model of invasive S. aureus infection, we demonstrate that one of the best candidate peptoids at 4 mg/kg significantly reduces with a two-log order the bacterial counts compared with saline-treated controls. Taken together, our results demonstrate the promising therapeutic potential of peptoids as antimicrobial agents

Remodelling of Cortical Actin Where Lytic Granules Dock at Natural Killer Cell Immune Synapses Revealed by Super-Resolution Microscopy

Super-resolution 3D imaging reveals remodeling of the cortical actin meshwork at the natural killer cell immune synapse, which is likely to be important for secretion of lytic granules

Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma

SummaryWe describe a comprehensive genomic characterization of adrenocortical carcinoma (ACC). Using this dataset, we expand the catalogue of known ACC driver genes to include PRKAR1A, RPL22, TERF2, CCNE1, and NF1. Genome wide DNA copy-number analysis revealed frequent occurrence of massive DNA loss followed by whole-genome doubling (WGD), which was associated with aggressive clinical course, suggesting WGD is a hallmark of disease progression. Corroborating this hypothesis were increased TERT expression, decreased telomere length, and activation of cell-cycle programs. Integrated subtype analysis identified three ACC subtypes with distinct clinical outcome and molecular alterations which could be captured by a 68-CpG probe DNA-methylation signature, proposing a strategy for clinical stratification of patients based on molecular markers

Expression and pharmacological inhibition of TrkB and EGFR in glioblastoma

A member of the Trk family of neurotrophin receptors, tropomyosin receptor kinase B (TrkB, encoded by the NTRK2 gene) is an increasingly important target in various cancer types, including glioblastoma (GBM). EGFR is among the most frequently altered oncogenes in GBM, and EGFR inhibition has been tested as an experimental therapy. Functional interactions between EGFR and TrkB have been demonstrated. In the present study, we investigated the role of TrkB and EGFR, and their interactions, in GBM. Analyses of NTRK2 and EGFR gene expression from The Cancer Genome Atlas (TCGA) datasets showed an increase in NTRK2 expression in the proneural subtype of GBM, and a strong correlation between NTRK2 and EGFR expression in glioma CpG island methylator phenotype (G-CIMP+) samples. We showed that when TrkB and EGFR inhibitors were combined, the inhibitory effect on A172 human GBM cells was more pronounced than when either inhibitor was given alone. When U87MG GBM cells were xenografted into the flank of nude mice, tumor growth was delayed by treatment with TrkB and EGFR inhibitors, given alone or combined, only at specific time points. Intracranial GBM growth in mice was not significantly affected by drug treatments. Our findings indicate that correlations between NTRK2 and EGFR expression occur in specific GBM subgroups. Also, our results using cultured cells suggest for the first time the potential of combining TrkB and EGFR inhibition for the treatment of GBM

The Somatic Genomic Landscape of Glioblastoma

We describe the landscape of somatic genomic alterations based on multi-dimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer