PBX1 is dispensable for neural commitment of RA-treated murine ES cells

Experimentation with PBX1 knockout mice has shown that PBX1 is necessary for early embryogenesis. Despite broad insight into PBX1 function, little is known about the underlying target gene regulation. Utilizing the Cre–loxP system, we targeted a functionally important part of the homeodomain of PBX1 through homozygous deletion of exon-6 and flanking intronic regions leading to exon 7 skipping in embryonic stem (ES) cells. We induced in vitro differentiation of wild-type and PBX1 mutant ES cells by aggregation and retinoic acid (RA) treatment and compared their profiles of gene expression at the ninth day post-reattachment to adhesive media. Our results indicate that PBX1 interactions with HOX proteins and DNA are dispensable for RA-induced ability of ES to express neural genes and point to a possible involvement of PBX1 in the regulation of imprinted genes

Development and testing of a pyro-driven launcher for harpoon-based comet sample acquisition

The CORSAIR (COmet Rendezvous, Sample Acquisition, Investigation, and Return) mission is a proposal for the fourth NASA New Frontiers program. It belongs to the Comet Surface Sample Return mission theme which focuses on acquiring and returning to Earth a macroscopic sample from the surface of a comet nucleus. CORSAIR uses a harpoon-based Sample Acquisition System (SAS) with the spacecraft hovering several meters above the comet surface. This stand-off strategy overcomes disadvantages of systems using drills or shovels. Since comets are low gravity objects, these techniques would require anchoring before sampling, which is not necessary here. Moreover, the harpoon-based system allows for acquiring several samples from different locations on the comet maximizing the scientifc output of the mission. Each SAS assembly consists of a pyro-driven launcher, a Sample Acquisition and Retrieval Projectile (SARP) and a retraction system using a deployable composite boom structure. In order to collect enough cometary material, the launcher has to provide the required kinetic energy to the SARP. Due to high energy densities, pyrotechnically actuated devices ultimately reduce the overall system mass and dimensions. Here, an overview of the development, design and testing of the launcher is given. Furthermore, the launcher theory is introduced explaining the entire reaction chain: initiation -> gas dynamics -> SARP motion

Optically switchable transistors comprising a hybrid photochromic molecule/n-type organic active layer

Organic semiconductors can be easily combined with other molecular building blocks in order to fabricate multifunctional devices, in which each component conveys a specific (opto)electronic function. We have fabricated photoswitchable hybrid thin-film transistors based on an active bi-component material, consisting of an n-type fullerene derivative and a photochromic diarylethene that possesses light-tunable energy levels. The devices can be gated in two independent ways by either using an electrical stimulus via the application of a voltage to the gate electrode or an optical stimulus causing interconversion of the diarylethene molecules between their two isomers. Fine control over the device output current is achieved by engineering the diarylethenes' LUMO that can act as an intra-gap state controlled by a distinct wavelength in the UV or in the visible range. Importantly, the devices based on a mixed diarylethene/fullerene active layer preserve the high mobility of the pristine semiconductor

The contact system proteases play disparate roles in streptococcal sepsis

Sepsis causes an activation of the human contact system, an inflammatory response mechanism against foreign surfaces, proteins and pathogens. The serine proteases of the contact system, factor XII and plasma kallikrein, are decreased in plasma of septic patients, which was previously associated with an unfavorable outcome. However, the precise mechanisms and roles of contact system factors in bacterial sepsis are poorly understood. We, therefore, studied the physiological relevance of factor XII and plasma kallikrein in a mouse model of experimental sepsis. We show that decreased plasma kallikrein concentration in septic mice is a result of reduced mRNA expression plasma prekallikrein gene, indicating that plasma kallikrein belong to negative acute phase proteins. Investigations regarding the pathophysiological function of contact system proteases during sepsis revealed different roles for factor XII and plasma kallikrein. In vitro, factor XII decelerated bacteria induced fibrinolysis, whereas plasma kallikrein supported it. Remarkably, depletion of plasma kallikrein (but not factor XII) by treatment with antisense-oligonucleotides, dampens bacterial dissemination and growth in multiple organs in the mouse sepsis model. These findings identify plasma kallikrein as a novel host pathogenicity factor in Streptococcus pyogenes sepsis

Natriuretic peptides and integrated risk assessment for cardiovascular disease. an individual-participant-data meta-analysis

BACKGROUND: Guidelines for primary prevention of cardiovascular diseases focus on prediction of coronary heart disease and stroke. We assessed whether or not measurement of N-terminal-pro-B-type natriuretic peptide (NT-proBNP) concentration could enable a more integrated approach than at present by predicting heart failure and enhancing coronary heart disease and stroke risk assessment. METHODS: In this individual-participant-data meta-analysis, we generated and harmonised individual-participant data from relevant prospective studies via both de-novo NT-proBNP concentration measurement of stored samples and collection of data from studies identified through a systematic search of the literature (PubMed, Scientific Citation Index Expanded, and Embase) for articles published up to Sept 4, 2014, using search terms related to natriuretic peptide family members and the primary outcomes, with no language restrictions. We calculated risk ratios and measures of risk discrimination and reclassification across predicted 10 year risk categories (ie, <5%, 5% to <7·5%, and ≥7·5%), adding assessment of NT-proBNP concentration to that of conventional risk factors (ie, age, sex, smoking status, systolic blood pressure, history of diabetes, and total and HDL cholesterol concentrations). Primary outcomes were the combination of coronary heart disease and stroke, and the combination of coronary heart disease, stroke, and heart failure. FINDINGS: We recorded 5500 coronary heart disease, 4002 stroke, and 2212 heart failure outcomes among 95 617 participants without a history of cardiovascular disease in 40 prospective studies. Risk ratios (for a comparison of the top third vs bottom third of NT-proBNP concentrations, adjusted for conventional risk factors) were 1·76 (95% CI 1·56-1·98) for the combination of coronary heart disease and stroke and 2·00 (1·77-2·26) for the combination of coronary heart disease, stroke, and heart failure. Addition of information about NT-proBNP concentration to a model containing conventional risk factors was associated with a C-index increase of 0·012 (0·010-0·014) and a net reclassification improvement of 0·027 (0·019-0·036) for the combination of coronary heart disease and stroke and a C-index increase of 0·019 (0·016-0·022) and a net reclassification improvement of 0·028 (0·019-0·038) for the combination of coronary heart disease, stroke, and heart failure. INTERPRETATION: In people without baseline cardiovascular disease, NT-proBNP concentration assessment strongly predicted first-onset heart failure and augmented coronary heart disease and stroke prediction, suggesting that NT-proBNP concentration assessment could be used to integrate heart failure into cardiovascular disease primary prevention

Composite transcriptome assembly of RNA-seq data in a sheep model for delayed bone healing

<p>Abstract</p> <p>Background</p> <p>The sheep is an important model organism for many types of medically relevant research, but molecular genetic experiments in the sheep have been limited by the lack of knowledge about ovine gene sequences.</p> <p>Results</p> <p>Prior to our study, mRNA sequences for only 1,556 partial or complete ovine genes were publicly available. Therefore, we developed a composite <it>de novo </it>transcriptome assembly method for next-generation sequence data to combine known ovine mRNA and EST sequences, mRNA sequences from mouse and cow, and sequences assembled <it>de novo </it>from short read RNA-Seq data into a composite reference transcriptome, and identified transcripts from over 12 thousand previously undescribed ovine genes. Gene expression analysis based on these data revealed substantially different expression profiles in standard versus delayed bone healing in an ovine tibial osteotomy model. Hundreds of transcripts were differentially expressed between standard and delayed healing and between the time points of the standard and delayed healing groups. We used the sheep sequences to design quantitative RT-PCR assays with which we validated the differential expression of 26 genes that had been identified by RNA-seq analysis. A number of clusters of characteristic expression profiles could be identified, some of which showed striking differences between the standard and delayed healing groups. Gene Ontology (GO) analysis showed that the differentially expressed genes were enriched in terms including <it>extracellular matrix</it>, <it>cartilage development</it>, <it>contractile fiber</it>, and <it>chemokine activity</it>.</p> <p>Conclusions</p> <p>Our results provide a first atlas of gene expression profiles and differentially expressed genes in standard and delayed bone healing in a large-animal model and provide a number of clues as to the shifts in gene expression that underlie delayed bone healing. In the course of our study, we identified transcripts of 13,987 ovine genes, including 12,431 genes for which no sequence information was previously available. This information will provide a basis for future molecular research involving the sheep as a model organism.</p

Deep learning for automatic head and neck lymph node level delineation provides expert-level accuracy

Background Deep learning-based head and neck lymph node level (HN_LNL) autodelineation is of high relevance to radiotherapy research and clinical treatment planning but still underinvestigated in academic literature. In particular, there is no publicly available open-source solution for large-scale autosegmentation of HN_LNL in the research setting. Methods An expert-delineated cohort of 35 planning CTs was used for training of an nnU-net 3D-fullres/2D-ensemble model for autosegmentation of 20 different HN_LNL. A second cohort acquired at the same institution later in time served as the test set (n = 20). In a completely blinded evaluation, 3 clinical experts rated the quality of deep learning autosegmentations in a head-to-head comparison with expert-created contours. For a subgroup of 10 cases, intraobserver variability was compared to the average deep learning autosegmentation accuracy on the original and recontoured set of expert segmentations. A postprocessing step to adjust craniocaudal boundaries of level autosegmentations to the CT slice plane was introduced and the effect of autocontour consistency with CT slice plane orientation on geometric accuracy and expert rating was investigated. Results Blinded expert ratings for deep learning segmentations and expert-created contours were not significantly different. Deep learning segmentations with slice plane adjustment were rated numerically higher (mean, 81.0 vs. 79.6, p = 0.185) and deep learning segmentations without slice plane adjustment were rated numerically lower (77.2 vs. 79.6, p = 0.167) than manually drawn contours. In a head-to-head comparison, deep learning segmentations with CT slice plane adjustment were rated significantly better than deep learning contours without slice plane adjustment (81.0 vs. 77.2, p = 0.004). Geometric accuracy of deep learning segmentations was not different from intraobserver variability (mean Dice per level, 0.76 vs. 0.77, p = 0.307). Clinical significance of contour consistency with CT slice plane orientation was not represented by geometric accuracy metrics (volumetric Dice, 0.78 vs. 0.78, p = 0.703). Conclusions We show that a nnU-net 3D-fullres/2D-ensemble model can be used for highly accurate autodelineation of HN_LNL using only a limited training dataset that is ideally suited for large-scale standardized autodelineation of HN_LNL in the research setting. Geometric accuracy metrics are only an imperfect surrogate for blinded expert rating

Diagnostic performance of line-immunoassay based algorithms for incident HIV-1 infection

Background: Serologic testing algorithms for recent HIV seroconversion (STARHS) provide important information for HIV surveillance. We have previously demonstrated that a patient's antibody reaction pattern in a confirmatory line immunoassay (INNO-LIA™ HIV I/II Score) provides information on the duration of infection, which is unaffected by clinical, immunological and viral variables. In this report we have set out to determine the diagnostic performance of Inno-Lia algorithms for identifying incident infections in patients with known duration of infection and evaluated the algorithms in annual cohorts of HIV notifications. Methods: Diagnostic sensitivity was determined in 527 treatment-naive patients infected for up to 12 months. Specificity was determined in 740 patients infected for longer than 12 months. Plasma was tested by Inno-Lia and classified as either incident (< = 12 m) or older infection by 26 different algorithms. Incident infection rates (IIR) were calculated based on diagnostic sensitivity and specificity of each algorithm and the rule that the total of incident results is the sum of true-incident and false-incident results, which can be calculated by means of the pre-determined sensitivity and specificity. Results: The 10 best algorithms had a mean raw sensitivity of 59.4% and a mean specificity of 95.1%. Adjustment for overrepresentation of patients in the first quarter year of infection further reduced the sensitivity. In the preferred model, the mean adjusted sensitivity was 37.4%. Application of the 10 best algorithms to four annual cohorts of HIV-1 notifications totalling 2'595 patients yielded a mean IIR of 0.35 in 2005/6 (baseline) and of 0.45, 0.42 and 0.35 in 2008, 2009 and 2010, respectively. The increase between baseline and 2008 and the ensuing decreases were highly significant. Other adjustment models yielded different absolute IIR, although the relative changes between the cohorts were identical for all models Conclusions: The method can be used for comparing IIR in annual cohorts of HIV notifications. The use of several different algorithms in combination, each with its own sensitivity and specificity to detect incident infection, is advisable as this reduces the impact of individual imperfections stemming primarily from relatively low sensitivities and sampling bias