BAs and boride III-V alloys

Boron arsenide, the typically-ignored member of the III-V arsenide series BAs-AlAs-GaAs-InAs is found to resemble silicon electronically: its Gamma conduction band minimum is p-like (Gamma_15), not s-like (Gamma_1c), it has an X_1c-like indirect band gap, and its bond charge is distributed almost equally on the two atoms in the unit cell, exhibiting nearly perfect covalency. The reasons for these are tracked down to the anomalously low atomic p orbital energy in the boron and to the unusually strong s-s repulsion in BAs relative to most other III-V compounds. We find unexpected valence band offsets of BAs with respect to GaAs and AlAs. The valence band maximum (VBM) of BAs is significantly higher than that of AlAs, despite the much smaller bond length of BAs, and the VBM of GaAs is only slightly higher than in BAs. These effects result from the unusually strong mixing of the cation and anion states at the VBM. For the BAs-GaAs alloys, we find (i) a relatively small (~3.5 eV) and composition-independent band gap bowing. This means that while addition of small amounts of nitrogen to GaAs lowers the gap, addition of small amounts of boron to GaAs raises the gap (ii) boron ``semi-localized'' states in the conduction band (similar to those in GaN-GaAs alloys), and (iii) bulk mixing enthalpies which are smaller than in GaN-GaAs alloys. The unique features of boride III-V alloys offer new opportunities in band gap engineering.Comment: 18 pages, 14 figures, 6 tables, 61 references. Accepted for publication in Phys. Rev. B. Scheduled to appear Oct. 15 200

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Models of peer support to remediate post-intensive care syndrome: A report developed by the SCCM Thrive International Peer Support Collaborative

Objective: Patients and caregivers can experience a range of physical, psychological, and cognitive problems following critical care discharge. The use of peer support has been proposed as an innovative support mechanism. Design: We sought to identify technical, safety and procedural aspects of existing operational models of peer support, among the Society of Critical Care Medicine Thrive Peer Support Collaborative. We also sought to categorize key distinctions between these models and elucidate barriers and facilitators to implementation. Subjects: 17 Thrive sites from the USA, UK, and Australia were represented by a range of healthcare professionals. Interventions: Via an iterative process of in-person and email/conference calls, members of the Collaborative, defined the key areas on which peer support models could be defined and compared; collected detailed self-reports from all sites; reviewed the information and identified clusters of models. Barriers and challenges to implementation of peer support models were also documented. Results: Within the Thrive Collaborative, six general models of peer support were identified: Community based, Psychologist-led outpatient, Models based within ICU follow-up clinics, Online, Groups based within ICU and Peer mentor models. The most common barriers to implementation were: recruitment to groups, personnel input and training: sustainability and funding, risk management and measuring success. Conclusion: A number of different models of peer support are currently being developed to help patients and families recover and grow in the post-critical care setting

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy