Revealing Correlation of Valence State with Nanoporous Structure in Cobalt Catalyst Nanoparticles by in Situ Environmental TEM

Simultaneously probing the electronic structure and morphology of materials at the nanometer or atomic scale while a chemical reaction proceeds is significant for understanding the underlying reaction mechanisms and optimizing a materials design. This is especially important in the study of nanoparticle catalysts, yet such experiments have rarely been achieved. Utilizing an environmental transmission electron microscope (ETEM) equipped with a differentially pumped gas cell, we are able to conduct nanoscopic imaging and electron energy loss spectroscopy (EELS) in situ for cobalt catalysts under reaction conditions. Analysis revealed quantitative correlation of the cobalt valence states to the particles' nanoporous structures. The in situ experiments were performed on nanoporous cobalt particles coated with silica while a 15 mTorr hydrogen environment was maintained at various temperatures (300-600\degreeC). When the nanoporous particles were reduced, the valence state changed from cobalt oxide to metallic cobalt and concurrent structural coarsening was observed. In situ mapping of the valence state and the corresponding nanoporous structures allows quantitatively analysis necessary for understanding and improving the mass activity and lifetime of cobalt-based catalysts, i.e., for Fischer-Tropsch synthesis that converts carbon monoxide and hydrogen into fuels, and uncovering the catalyst optimization mechanisms.Comment: ACS Nano, accepte

Treating asthma with omega-3 fatty acids: where is the evidence? A systematic review

BACKGROUND: Considerable interest exists in the potential therapeutic value of dietary supplementation with the omega-3 fatty acids. Given the interplay between pro-inflammatory omega-6 fatty acids, and the less pro-inflammatory omega-3 fatty acids, it has been thought that the latter could play a key role in treating or preventing asthma. The purpose was to systematically review the scientific-medical literature in order to identify, appraise, and synthesize the evidence for possible treatment effects of omega-3 fatty acids in asthma. METHODS: Medline, Premedline, Embase, Cochrane Central Register of Controlled Trials, CAB Health, and, Dissertation Abstracts were searched to April 2003. We included randomized controlled trials (RCT's) of subjects of any age that used any foods or extracts containing omega-3 fatty acids as treatment or prevention for asthma. Data included all asthma related outcomes, potential covariates, characteristics of the study, design, population, intervention/exposure, comparators, and co interventions. RESULTS: Ten RCT's were found pertinent to the present report. CONCLUSION: Given the largely inconsistent picture within and across respiratory outcomes, it is impossible to determine whether or not omega-3 fatty acids are an efficacious adjuvant or monotherapy for children or adults. Based on this systematic review we recommend a large randomized controlled study of the effects of high-dose encapsulated omega-3 fatty acids on ventilatory and inflammatory measures of asthma controlling diet and other asthma risk factors. This review was limited because Meta-analysis was considered inappropriate due to missing data; poorly or heterogeneously defined populations, interventions, intervention-comparator combinations, and outcomes. In addition, small sample sizes made it impossible to meaningfully assess the impact on clinical outcomes of co-variables. Last, few significant effects were found

RNA-Seq Differentiates Tumour and Host mRNA Expression Changes Induced by Treatment of Human Tumour Xenografts with the VEGFR Tyrosine Kinase Inhibitor Cediranib.

Pre-clinical models of tumour biology often rely on propagating human tumour cells in a mouse. In order to gain insight into the alignment of these models to human disease segments or investigate the effects of different therapeutics, approaches such as PCR or array based expression profiling are often employed despite suffering from biased transcript coverage, and a requirement for specialist experimental protocols to separate tumour and host signals. Here, we describe a computational strategy to profile transcript expression in both the tumour and host compartments of pre-clinical xenograft models from the same RNA sample using RNA-Seq. Key to this strategy is a species-specific mapping approach that removes the need for manipulation of the RNA population, customised sequencing protocols, or prior knowledge of the species component ratio. The method demonstrates comparable performance to species-specific RT-qPCR and a standard microarray platform, and allowed us to quantify gene expression changes in both the tumour and host tissue following treatment with cediranib, a potent vascular endothelial growth factor receptor tyrosine kinase inhibitor, including the reduction of multiple murine transcripts associated with endothelium or vessels, and an increase in genes associated with the inflammatory response in response to cediranib. In the human compartment, we observed a robust induction of hypoxia genes and a reduction in cell cycle associated transcripts. In conclusion, the study establishes that RNA-Seq can be applied to pre-clinical models to gain deeper understanding of model characteristics and compound mechanism of action, and to identify both tumour and host biomarkers

Availability and quality of paraffin blocks identified in pathology archives: A multi-institutional study by the Shared Pathology Informatics Network (SPIN)

BACKGROUND: Shared Pathology Informatics Network (SPIN) is a tissue resource initiative that utilizes clinical reports of the vast amount of paraffin-embedded tissues routinely stored by medical centers. SPIN has an informatics component (sending tissue-related queries to multiple institutions via the internet) and a service component (providing histopathologically annotated tissue specimens for medical research). This paper examines if tissue blocks, identified by localized computer searches at participating institutions, can be retrieved in adequate quantity and quality to support medical researchers. METHODS: Four centers evaluated pathology reports (1990–2005) for common and rare tumors to determine the percentage of cases where suitable tissue blocks with tumor were available. Each site generated a list of 100 common tumor cases (25 cases each of breast adenocarcinoma, colonic adenocarcinoma, lung squamous carcinoma, and prostate adenocarcinoma) and 100 rare tumor cases (25 cases each of adrenal cortical carcinoma, gastro-intestinal stromal tumor [GIST], adenoid cystic carcinoma, and mycosis fungoides) using a combination of Tumor Registry, laboratory information system (LIS) and/or SPIN-related tools. Pathologists identified the slides/blocks with tumor and noted first 3 slides with largest tumor and availability of the corresponding block. RESULTS: Common tumors cases (n = 400), the institutional retrieval rates (all blocks) were 83% (A), 95% (B), 80% (C), and 98% (D). Retrieval rate (tumor blocks) from all centers for common tumors was 73% with mean largest tumor size of 1.49 cm; retrieval (tumor blocks) was highest-lung (84%) and lowest-prostate (54%). Rare tumors cases (n = 400), each institution's retrieval rates (all blocks) were 78% (A), 73% (B), 67% (C), and 84% (D). Retrieval rate (tumor blocks) from all centers for rare tumors was 66% with mean largest tumor size of 1.56 cm; retrieval (tumor blocks) was highest for GIST (72%) and lowest for adenoid cystic carcinoma (58%). CONCLUSION: Assessment shows availability and quality of archival tissue blocks that are retrievable and associated electronic data that can be of value for researchers. This study serves to compliment the data from which uniform use of the SPIN query tools by all four centers will be measured to assure and highlight the usefulness of archival material for obtaining tumor tissues for research

A statistical framework for assessing pharmacological responses and biomarkers using uncertainty estimates

High-throughput testing of drugs across molecular-characterised cell lines can identify candidate treatments and discover biomarkers. However, the cells’ response to a drug is typically quantified by a summary statistic from a best-fit dose-response curve, whilst neglecting the uncertainty of the curve fit and the potential variability in the raw readouts. Here, we model the experimental variance using Gaussian Processes, and subsequently, leverage uncertainty estimates to identify associated biomarkers with a new Bayesian framework. Applied to in vitro screening data on 265 compounds across 1074 cancer cell lines, our models identified 24 clinically established drug-response biomarkers, and provided evidence for six novel biomarkers by accounting for association with low uncertainty. We validated our uncertainty estimates with an additional drug screen of 26 drugs, 10 cell lines with 8 to 9 replicates. Our method is applicable to any dose-response data without replicates, and improves biomarker discovery for precision medicine