AMBIsome Therapy Induction OptimisatioN (AMBITION): High dose AmBisome for cryptococcal meningitis induction therapy in sub-Saharan Africa: economic evaluation protocol for a randomised controlled trial-based equivalence study.

INTRODUCTION: Cryptococcal meningitis is responsible for around 15% of all HIV-related deaths globally. Conventional treatment courses with amphotericin B require prolonged hospitalisation and are associated with multiple toxicities and poor outcomes. A phase II study has shown that a single high dose of liposomal amphotericin may be comparable to standard treatment. We propose a phase III clinical endpoint trial comparing single, high-dose liposomal amphotericin with the WHO recommended first-line treatment at six sites across five counties. An economic analysis is essential to support wide-scale implementation. METHODS AND ANALYSIS: Country-specific economic evaluation tools will be developed across the five country settings. Details of patient and household out-of-pocket expenses and any catastrophic healthcare expenditure incurred will be collected via interviews from trial patients. Health service patient costs and related household expenditure in both arms will be compared over the trial period in a probabilistic approach, using Monte Carlo bootstrapping methods. Costing information and number of life-years survived will be used as the input to a decision-analytic model to assess the cost-effectiveness of a single, high-dose liposomal amphotericin to the standard treatment. In addition, these results will be compared with a historical cohort from another clinical trial. ETHICS AND DISSEMINATION: The AMBIsome Therapy Induction OptimisatioN (AMBITION) trial has been evaluated and approved by the London School of Hygiene and Tropical Medicine, University of Botswana, Malawi National Health Sciences, University of Cape Town, Mulago Hospital and Zimbabwe Medical Research Council research ethics committees. All participants will provide written informed consent or if lacking capacity will have consent provided by a proxy. The findings of this economic analysis, part of the AMBITION trial, will be disseminated through peer-reviewed publications and at international and country-level policy meetings. TRIAL REGISTRATION: ISRCTN 7250 9687; Pre-results

Extraction and Inhibition of Enzymatic Activity of Botulinum Neurotoxins/A1, /A2, and /A3 by a Panel of Monoclonal Anti-BoNT/A Antibodies

Botulinum neurotoxins (BoNTs) are extremely potent toxins that are capable of causing death or respiratory failure leading to long-term intensive care. Treatment includes serotype-specific antitoxins, which must be administered early in the course of the intoxication. Rapidly determining human exposure to BoNT is an important public health goal. In previous work, our laboratory focused on developing Endopep-MS, a mass spectrometry-based endopeptidase method for detecting and differentiating BoNT/A–G serotypes in buffer and BoNT/A, /B, /E, and /F in clinical samples. We have previously reported the effectiveness of antibody-capture to purify and concentrate BoNTs from complex matrices, such as clinical samples. Because some antibodies inhibit or neutralize the activity of BoNT, the choice of antibody with which to extract the toxin is critical. In this work, we evaluated a panel of 16 anti-BoNT/A monoclonal antibodies (mAbs) for their ability to inhibit the in vitro activity of BoNT/A1, /A2, and /A3 complex as well as the recombinant LC of A1. We also evaluated the same antibody panel for the ability to extract BoNT/A1, /A2, and /A3. Among the mAbs, there were significant differences in extraction efficiency, ability to extract BoNT/A subtypes, and inhibitory effect on BoNT catalytic activity. The mAbs binding the C-terminal portion of the BoNT/A heavy chain had optimal properties for use in the Endopep-MS assay

The Colorectal cancer disease-specific transcriptome may facilitate the discovery of more biologically and clinically relevant information

<p>Abstract</p> <p>Background</p> <p>To date, there are no clinically reliable predictive markers of response to the current treatment regimens for advanced colorectal cancer. The aim of the current study was to compare and assess the power of transcriptional profiling using a generic microarray and a disease-specific transcriptome-based microarray. We also examined the biological and clinical relevance of the disease-specific transcriptome.</p> <p>Methods</p> <p>DNA microarray profiling was carried out on isogenic sensitive and 5-FU-resistant HCT116 colorectal cancer cell lines using the Affymetrix HG-U133 Plus2.0 array and the Almac Diagnostics Colorectal cancer disease specific Research tool. In addition, DNA microarray profiling was also carried out on pre-treatment metastatic colorectal cancer biopsies using the colorectal cancer disease specific Research tool. The two microarray platforms were compared based on detection of probesets and biological information.</p> <p>Results</p> <p>The results demonstrated that the disease-specific transcriptome-based microarray was able to out-perform the generic genomic-based microarray on a number of levels including detection of transcripts and pathway analysis. In addition, the disease-specific microarray contains a high percentage of antisense transcripts and further analysis demonstrated that a number of these exist in sense:antisense pairs. Comparison between cell line models and metastatic CRC patient biopsies further demonstrated that a number of the identified sense:antisense pairs were also detected in CRC patient biopsies, suggesting potential clinical relevance.</p> <p>Conclusions</p> <p>Analysis from our <it>in vitro </it>and clinical experiments has demonstrated that many transcripts exist in sense:antisense pairs including <it>IGF2BP2</it>, which may have a direct regulatory function in the context of colorectal cancer. While the functional relevance of the antisense transcripts has been established by many studies, their functional role is currently unclear; however, the numbers that have been detected by the disease-specific microarray would suggest that they may be important regulatory transcripts. This study has demonstrated the power of a disease-specific transcriptome-based approach and highlighted the potential novel biologically and clinically relevant information that is gained when using such a methodology.</p

Two-pion Bose-Einstein correlations in central Pb-Pb collisions at sNN\sqrt{s_{\rm NN}} = 2.76 TeV

The first measurement of two-pion Bose-Einstein correlations in central Pb-Pb collisions at $\sqrt{s_{\rm NN}} = 2.76$ TeV at the Large Hadron Collider is presented. We observe a growing trend with energy now not only for the longitudinal and the outward but also for the sideward pion source radius. The pion homogeneity volume and the decoupling time are significantly larger than those measured at RHIC.Comment: 17 pages, 5 captioned figures, 1 table, authors from page 12, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/388

Effective Rheology of Bubbles Moving in a Capillary Tube

We calculate the average volumetric flux versus pressure drop of bubbles moving in a single capillary tube with varying diameter, finding a square-root relation from mapping the flow equations onto that of a driven overdamped pendulum. The calculation is based on a derivation of the equation of motion of a bubble train from considering the capillary forces and the entropy production associated with the viscous flow. We also calculate the configurational probability of the positions of the bubbles.Comment: 4 pages, 1 figur

Chromatin States Accurately Classify Cell Differentiation Stages

Gene expression is controlled by the concerted interactions between transcription factors and chromatin regulators. While recent studies have identified global chromatin state changes across cell-types, it remains unclear to what extent these changes are co-regulated during cell-differentiation. Here we present a comprehensive computational analysis by assembling a large dataset containing genome-wide occupancy information of 5 histone modifications in 27 human cell lines (including 24 normal and 3 cancer cell lines) obtained from the public domain, followed by independent analysis at three different representations. We classified the differentiation stage of a cell-type based on its genome-wide pattern of chromatin states, and found that our method was able to identify normal cell lines with nearly 100% accuracy. We then applied our model to classify the cancer cell lines and found that each can be unequivocally classified as differentiated cells. The differences can be in part explained by the differential activities of three regulatory modules associated with embryonic stem cells. We also found that the “hotspot” genes, whose chromatin states change dynamically in accordance to the differentiation stage, are not randomly distributed across the genome but tend to be embedded in multi-gene chromatin domains, and that specialized gene clusters tend to be embedded in stably occupied domains