Semi-analytic method for slow light photonic crystal waveguide design

We present a semi-analytic method to calculate the dispersion curves and the group velocity of photonic crystal waveguide modes in two-dimensional geometries. We model the waveguide as a homogenous strip, surrounded by photonic crystal acting as diffracting mirrors. Following conventional guided-wave optics, the properties of the photonic crystal waveguide may be calculated from the phase upon propagation over the strip and the phase upon reflection. The cases of interest require a theory including the specular order and one other diffracted reflected order. The computational advantages let us scan a large parameter space, allowing us to find novel types of solutions.Comment: Accepted by Photonics and Nanostructures - Fundamentals and Application

Progress toward curing HIV infection with hematopoietic cell transplantation.

HIV-1 infection afflicts more than 35 million people worldwide, according to 2014 estimates from the World Health Organization. For those individuals who have access to antiretroviral therapy, these drugs can effectively suppress, but not cure, HIV-1 infection. Indeed, the only documented case for an HIV/AIDS cure was a patient with HIV-1 and acute myeloid leukemia who received allogeneic hematopoietic cell transplantation (HCT) from a graft that carried the HIV-resistant CCR5-∆32/∆32 mutation. Other attempts to establish a cure for HIV/AIDS using HCT in patients with HIV-1 and malignancy have yielded mixed results, as encouraging evidence for virus eradication in a few cases has been offset by poor clinical outcomes due to the underlying cancer or other complications. Such clinical strategies have relied on HIV-resistant hematopoietic stem and progenitor cells that harbor the natural CCR5-∆32/∆32 mutation or that have been genetically modified for HIV-resistance. Nevertheless, HCT with HIV-resistant cord blood remains a promising option, particularly with inventories of CCR5-∆32/∆32 units or with genetically modified, human leukocyte antigen-matched cord blood

Incidence and prognostic significance of hypoxemia in fibrotic interstitial lung disease: an international cohort study.

BACKGROUND Hypoxemia is a cardinal feature of fibrotic interstitial lung disease (ILD). The incidence, progression, and prognostic significance of hypoxemia in patients with fibrotic ILD is currently unknown. RESEARCH QUESTION What are the epidemiology of hypoxemia and its additive prognostic value in current risk prediction model in fibrotic ILD? METHODS We identified 848 patients with fibrotic ILD (258 with idiopathic pulmonary fibrosis (IPF)) in five prospective ILD registries from Australia, Canada, and Switzerland. Cumulative incidence of exertional and resting hypoxemia from the time of diagnosis was estimated at 1-year intervals in patients with baseline 6-minute walk tests, adjusted for competing risks of death and lung transplantation. Likelihood ratio tests were used to determine the prognostic significance of exertional and resting hypoxemia for 1-year mortality/transplantation when added to the ILD-GAP model. The cohort was divided into derivation and validation subsets to evaluate performance characteristics of the extended model (the "ILD-GAP-O2" model), which included oxygenation status as a predictor. RESULTS The 1-, 2-, and 5-year overall cumulative incidence was 6.1%, 17.3%, and 40.1% for exertional hypoxemia, and 2.4%, 5.6%, and 16.5% for resting hypoxemia, which were significantly higher in IPF patients compared to non-IPF patients (p<0.001 for both). Addition of exertional or resting hypoxemia to the ILD-GAP model improved 1-year mortality/transplantation prediction (p<0.001 for both). The ILD-GAP-O2 model had improved discrimination (C-index of 0.80 vs 0.75) and model fit (Akaike information criteria of 400 vs 422) in the validation cohort, with comparable calibration. INTERPRETATION IPF patients have higher cumulative incidence of exertional and resting hypoxemia than non-IPF patients. The extended ILD-GAP-O2 model provides additional risk stratification for 1-year prognosis in fibrotic ILD

Quantification of codon selection for comparative bacterial genomics

<p>Abstract</p> <p>Background</p> <p>Statistics measuring codon selection seek to compare genes by their sensitivity to selection for translational efficiency, but existing statistics lack a model for testing the significance of differences between genes. Here, we introduce a new statistic for measuring codon selection, the Adaptive Codon Enrichment (ACE).</p> <p>Results</p> <p>This statistic represents codon usage bias in terms of a probabilistic distribution, quantifying the extent that preferred codons are over-represented in the gene of interest relative to the mean and variance that would result from stochastic sampling of codons. Expected codon frequencies are derived from the observed codon usage frequencies of a broad set of genes, such that they are likely to reflect nonselective, genome wide influences on codon usage (<it>e.g</it>. mutational biases). The relative adaptiveness of synonymous codons is deduced from the frequency of codon usage in a pre-selected set of genes relative to the expected frequency. The ACE can predict both transcript abundance during rapid growth and the rate of synonymous substitutions, with accuracy comparable to or greater than existing metrics. We further examine how the composition of reference gene sets affects the accuracy of the statistic, and suggest methods for selecting appropriate reference sets for any genome, including bacteriophages. Finally, we demonstrate that the ACE may naturally be extended to quantify the genome-wide influence of codon selection in a manner that is sensitive to a large fraction of codons in the genome. This reveals substantial variation among genomes, correlated with the tRNA gene number, even among groups of bacteria where previously proposed whole-genome measures show little variation.</p> <p>Conclusions</p> <p>The statistical framework of the ACE allows rigorous comparison of the level of codon selection acting on genes, both within a genome and between genomes.</p

Progress toward curing HIV infection with hematopoietic cell transplantation

HIV-1 infection afflicts more than 35 million people worldwide, according to 2014 estimates from the World Health Organization. For those individuals who have access to antiretroviral therapy, these drugs can effectively suppress, but not cure, HIV-1 infection. Indeed, the only documented case for an HIV/AIDS cure was a patient with HIV-1 and acute myeloid leukemia who received allogeneic hematopoietic cell transplantation (HCT) from a graft that carried the HIV-resistant CCR5-∆32/∆32 mutation. Other attempts to establish a cure for HIV/AIDS using HCT in patients with HIV-1 and malignancy have yielded mixed results, as encouraging evidence for virus eradication in a few cases has been offset by poor clinical outcomes due to the underlying cancer or other complications. Such clinical strategies have relied on HIV-resistant hematopoietic stem and progenitor cells that harbor the natural CCR5-∆32/∆32 mutation or that have been genetically modified for HIV-resistance. Nevertheless, HCT with HIV-resistant cord blood remains a promising option, particularly with inventories of CCR5-∆32/∆32 units or with genetically modified, human leukocyte antigen-matched cord blood

Precision medicine driven by cancer systems biology

Molecular insights from genome and systems biology are influencing how cancer is diagnosed and treated. We critically evaluate big data challenges in precision medicine. The melanoma research community has identified distinct subtypes involving chronic sun-induced damage and the mitogen-activated protein kinase driver pathway. In addition, despite low mutation burden, non-genomic mitogen-activated protein kinase melanoma drivers are found in membrane receptors, metabolism, or epigenetic signaling with the ability to bypass central mitogen-activated protein kinase molecules and activating a similar program of mitogenic effectors. Mutation hotspots, structural modeling, UV signature, and genomic as well as non-genomic mechanisms of disease initiation and progression are taken into consideration to identify resistance mutations and novel drug targets. A comprehensive precision medicine profile of a malignant melanoma patient illustrates future rational drug targeting strategies. Network analysis emphasizes an important role of epigenetic and metabolic master regulators in oncogenesis. Co-occurrence of driver mutations in signaling, metabolic, and epigenetic factors highlights how cumulative alterations of our genomes and epigenomes progressively lead to uncontrolled cell proliferation. Precision insights have the ability to identify independent molecular pathways suitable for drug targeting. Synergistic treatment combinations of orthogonal modalities including immunotherapy, mitogen-activated protein kinase inhibitors, epigenetic inhibitors, and metabolic inhibitors have the potential to overcome immune evasion, side effects, and drug resistance

Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas

Summary Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (TP53, ATRX, RB1) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types