Adaptive EAGLE dynamic solution adaptation and grid quality enhancement

In the effort described here, the elliptic grid generation procedure in the EAGLE grid code was separated from the main code into a subroutine, and a new subroutine which evaluates several grid quality measures at each grid point was added. The elliptic grid routine can now be called, either by a computational fluid dynamics (CFD) code to generate a new adaptive grid based on flow variables and quality measures through multiple adaptation, or by the EAGLE main code to generate a grid based on quality measure variables through static adaptation. Arrays of flow variables can be read into the EAGLE grid code for use in static adaptation as well. These major changes in the EAGLE adaptive grid system make it easier to convert any CFD code that operates on a block-structured grid (or single-block grid) into a multiple adaptive code

Transient Expression of Tetrameric Recombinant Human Butyrylcholinesterase in Nicotiana benthamiana.

To optimize the expression, extraction and purification of plant-derived tetrameric recombinant human butyrylcholinesterase (prBChE), we describe the development and use of plant viral amplicon-based gene expression system; Tobacco Mosaic Virus (TMV) RNA-based overexpression vector (TRBO) to express enzymatically active FLAG-tagged plant made recombinant butyrylcholinesterase (rBChE) in Nicotiana benthamiana leaves using transient agroinfiltration. Two gene expression cassettes were designed to express the recombinant protein in either the ER or to the apoplastic compartment. Leaf homogenization was used to isolate ER-retained recombinant butyrylcholinesterase (prBChE-ER) while apoplast-targeted rBChE was isolated by either leaf homogenization (prBChE) or vacuum-extraction of apoplastic wash fluid (prBChE-AWF). rBChE from apoplast wash fluid had a higher specific activity but lower enzyme yield than leaf homogenate. To optimize the isolation and purification of total recombinant protein from leaf homogenates, an acidic extraction buffer was used. The acidic extraction buffer yielded >95% enzymatically active tetrameric rBChE as verified by Coomassie stained and native gel electrophoresis. Furthermore, when compared to human butyrylcholinesterase, the prBChE was found to be similar in terms of tetramerization and enzyme kinetics. The N-linked glycan profile of purified prBChE-ER was found to be mostly high mannose structures while the N-linked glycans on prBChE-AWF were primarily complex. The glycan profile of the prBChE leaf homogenates showed a mixture of high mannose, complex and paucimannose type N-glycans. These findings demonstrate the ability of plants to produce rBChE that is enzymatically active and whose oligomeric state is comparable to mammalian butyrylcholinesterase. The process of plant made rBChE tetramerization and strategies for improving its pharmacokinetics properties are also discussed

Expression, Purification, and Biophysical Characterization of a Secreted Anthrax Decoy Fusion Protein in Nicotiana benthamiana.

Anthrax toxin receptor-mediated drug development for blocking anthrax toxin action has received much attention in recent decades. In this study, we produced a secreted anthrax decoy fusion protein comprised of a portion of the human capillary morphogenesis gene-2 (CMG2) protein fused via a linker to the fragment crystallizable (Fc) domain of human immunoglobulin G1 in Nicotiana benthamiana plants using a transient expression system. Using the Cauliflower Mosaic Virus (CaMV) 35S promoter and co-expression with the p19 gene silencing suppressor, we were able to achieve a high level of recombinant CMG2-Fc-Apo (rCMG2-Fc-Apo) protein accumulation. Production kinetics were observed up to eight days post-infiltration, and maximum production of 826 mg/kg fresh leaf weight was observed on day six. Protein A affinity chromatography purification of the rCMG2-Fc-Apo protein from whole leaf extract and apoplast wash fluid showed the homodimeric form under non-reducing gel electrophoresis and mass spectrometry analysis confirmed the molecular integrity of the secreted protein. The N-glycosylation pattern of purified rCMG2-Fc-Apo protein was analysed; the major portion of N-glycans consists of complex type structures in both protein samples. The most abundant (>50%) N-glycan structure was GlcNAc₂(Xyl)Man₃(Fuc)GlcNAc₂ in rCMG2-Fc-Apo recovered from whole leaf extract and apoplast wash fluid. High mannose N-glycan structures were not detected in the apoplast wash fluid preparation, which confirmed the protein secretion. Altogether, these findings demonstrate that high-level production of rCMG2-Fc-Apo can be achieved by transient production in Nicotiana benthamiana plants with apoplast targeting

Neonatal screening improves sickle cell disease clinical outcome in Belgium.

peer reviewedObjectives To compare the outcomes of sickle cell disease patients diagnosed through neonatal screening with those who were not. Methods In an observational multicenter study in Belgium, 167 screened and 93 unscreened sickle cell disease patients were analyzed for a total of 1116 and 958 patient-years of follow-up, respectively. Both groups were compared with propensity score analysis, with patients matched on three covariates (gender, genotype, and central Africa origin). Bonferroni correction was applied for all comparisons. Results Kaplan-Meier estimates of survival without bacteremia were significantly higher in the screened group than the unscreened group (94.47%; [95% CI, 88.64-97.36%] versus 83.78% [95% CI, 72.27-90.42%]), p = 0.032. Non-significant differences between both groups were reported for survival without acute chest syndrome, acute anemia, cerebral complication, severe infection, and vaso-occlusive crisis. Significantly lower hospitalization rate and days per 100 patient-years were observed in the screened compared with the unscreened group (0.27 vs. 0.63 and 1.25 vs. 2.82, p = 0.0006 and <0.0001). Conclusion These data confirm the benefit of a neonatal screening programme in reducing bacteremia and hospitalization

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

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment