Sparse-Lagrangian PDF Modelling of Silica Synthesis from Silane Jets in Vitiated Co-flows with Varying Inflow Conditions

This paper presents a comparison of experimental and numerical results for a series of turbulent reacting jets where silica nanoparticles are formed and grow due to surface growth and agglomeration. We use large-eddy simulation coupled with a multiple mapping conditioning approach for the solution of the transport equation for the joint probability density function of scalar composition and particulate size distribution. The model considers inception based on finite-rate chemistry, volumetric surface growth and agglomeration. The sub-models adopted for these particulate processes are the standard ones used by the community. Validation follows the “paradigm shift” approach where elastic light scattering signals (that depend on particulate number and size), OH- and SiO-LIF signals are computed from the simulation results and compared with “raw signals” from laser diagnostics. The sensitivity towards variable boundary conditions such as co-flow temperature, Reynolds number and precursor doping of the jet is investigated. Agreement between simulation and experiments is very good for a reference case which is used to calibrate the signals. While keeping the model parameters constant, the sensitivity of the particulate size distribution on co-flow temperature is predicted satisfactorily upstream although quantitative differences with the data exist downstream for the lowest coflow temperature case that is considered. When the precursor concentration is varied, the model predicts the correct direction of the change in signal but notable qualitative and quantitative differences with the data are observed. In particular, the measured signals show a highly non-linear variation while the predictions exhibit a square dependence on precursor doping at best. So, while the results for the reference case appear to be very good, shortcomings in the standard submodels are revealed through variation of the boundary conditions. This demonstrates the importance of testing complex nanoparticle synthesis models on a flame series to ensure that the physical trends are correctly accounted for

Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics.

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography-mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography-mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives

A three-scale domain decomposition method for the 3D analysis of debonding in laminates

The prediction of the quasi-static response of industrial laminate structures requires to use fine descriptions of the material, especially when debonding is involved. Even when modeled at the mesoscale, the computation of these structures results in very large numerical problems. In this paper, the exact mesoscale solution is sought using parallel iterative solvers. The LaTIn-based mixed domain decomposition method makes it very easy to handle the complex description of the structure; moreover the provided multiscale features enable us to deal with numerical difficulties at their natural scale; we present the various enhancements we developed to ensure the scalability of the method. An extension of the method designed to handle instabilities is also presented

Myogenic progenitors contribute to open but not closed fracture repair

<p>Abstract</p> <p>Background</p> <p>Bone repair is dependent on the presence of osteocompetent progenitors that are able to differentiate and generate new bone. Muscle is found in close association with orthopaedic injury, however its capacity to make a cellular contribution to bone repair remains ambiguous. We hypothesized that myogenic cells of the MyoD-lineage are able to contribute to bone repair.</p> <p>Methods</p> <p>We employed a <it>MyoD</it>-Cre⁺:Z/AP⁺conditional reporter mouse in which all cells of the MyoD-lineage are permanently labeled with a <it>human alkaline phosphatase (hAP) </it>reporter. We tracked the contribution of MyoD-lineage cells in mouse models of tibial bone healing.</p> <p>Results</p> <p>In the absence of musculoskeletal trauma, MyoD-expressing cells are limited to skeletal muscle and the presence of reporter-positive cells in non-muscle tissues is negligible. In a closed tibial fracture model, there was no significant contribution of hAP⁺cells to the healing callus. In contrast, open tibial fractures featuring periosteal stripping and muscle fenestration had up to 50% of hAP⁺cells detected in the open fracture callus. At early stages of repair, many hAP⁺cells exhibited a chondrocyte morphology, with lesser numbers of osteoblast-like hAP⁺cells present at the later stages. Serial sections stained for hAP and type II and type I collagen showed that MyoD-lineage cells were surrounded by cartilaginous or bony matrix, suggestive of a functional role in the repair process. To exclude the prospect that osteoprogenitors spontaneously express MyoD during bone repair, we created a metaphyseal drill hole defect in the tibia. No hAP⁺staining was observed in this model suggesting that the expression of MyoD is not a normal event for endogenous osteoprogenitors.</p> <p>Conclusions</p> <p>These data document for the first time that muscle cells can play a significant secondary role in bone repair and this knowledge may lead to important translational applications in orthopaedic surgery.</p> <p>Please see related article: <url>http://www.biomedcentral.com/1741-7015/9/136</url></p

Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry

BACKGROUND: Structure elucidation of unknown small molecules by mass spectrometry is a challenge despite advances in instrumentation. The first crucial step is to obtain correct elemental compositions. In order to automatically constrain the thousands of possible candidate structures, rules need to be developed to select the most likely and chemically correct molecular formulas. RESULTS: An algorithm for filtering molecular formulas is derived from seven heuristic rules: (1) restrictions for the number of elements, (2) LEWIS and SENIOR chemical rules, (3) isotopic patterns, (4) hydrogen/carbon ratios, (5) element ratio of nitrogen, oxygen, phosphor, and sulphur versus carbon, (6) element ratio probabilities and (7) presence of trimethylsilylated compounds. Formulas are ranked according to their isotopic patterns and subsequently constrained by presence in public chemical databases. The seven rules were developed on 68,237 existing molecular formulas and were validated in four experiments. First, 432,968 formulas covering five million PubChem database entries were checked for consistency. Only 0.6% of these compounds did not pass all rules. Next, the rules were shown to effectively reducing the complement all eight billion theoretically possible C, H, N, S, O, P-formulas up to 2000 Da to only 623 million most probable elemental compositions. Thirdly 6,000 pharmaceutical, toxic and natural compounds were selected from DrugBank, TSCA and DNP databases. The correct formulas were retrieved as top hit at 80–99% probability when assuming data acquisition with complete resolution of unique compounds and 5% absolute isotope ratio deviation and 3 ppm mass accuracy. Last, some exemplary compounds were analyzed by Fourier transform ion cyclotron resonance mass spectrometry and by gas chromatography-time of flight mass spectrometry. In each case, the correct formula was ranked as top hit when combining the seven rules with database queries. CONCLUSION: The seven rules enable an automatic exclusion of molecular formulas which are either wrong or which contain unlikely high or low number of elements. The correct molecular formula is assigned with a probability of 98% if the formula exists in a compound database. For truly novel compounds that are not present in databases, the correct formula is found in the first three hits with a probability of 65–81%. Corresponding software and supplemental data are available for downloads from the authors' website

How Large Is the Metabolome? A Critical Analysis of Data Exchange Practices in Chemistry

Calculating the metabolome size of species by genome-guided reconstruction of metabolic pathways misses all products from orphan genes and from enzymes lacking annotated genes. Hence, metabolomes need to be determined experimentally. Annotations by mass spectrometry would greatly benefit if peer-reviewed public databases could be queried to compile target lists of structures that already have been reported for a given species. We detail current obstacles to compile such a knowledge base of metabolites.As an example, results are presented for rice. Two rice (oryza sativa) subspecies have been fully sequenced, oryza japonica and oryza indica. Several major small molecule databases were compared for listing known rice metabolites comprising PubChem, Chemical Abstracts, Beilstein, Patent databases, Dictionary of Natural Products, SetupX/BinBase, KNApSAcK DB, and finally those databases which were obtained by computational approaches, i.e. RiceCyc, KEGG, and Reactome. More than 5,000 small molecules were retrieved when searching these databases. Unfortunately, most often, genuine rice metabolites were retrieved together with non-metabolite database entries such as pesticides. Overlaps from database compound lists were very difficult to compare because structures were either not encoded in machine-readable format or because compound identifiers were not cross-referenced between databases.We conclude that present databases are not capable of comprehensively retrieving all known metabolites. Metabolome lists are yet mostly restricted to genome-reconstructed pathways. We suggest that providers of (bio)chemical databases enrich their database identifiers to PubChem IDs and InChIKeys to enable cross-database queries. In addition, peer-reviewed journal repositories need to mandate submission of structures and spectra in machine readable format to allow automated semantic annotation of articles containing chemical structures. Such changes in publication standards and database architectures will enable researchers to compile current knowledge about the metabolome of species, which may extend to derived information such as spectral libraries, organ-specific metabolites, and cross-study comparisons

Quantum state preparation and macroscopic entanglement in gravitational-wave detectors

Long-baseline laser-interferometer gravitational-wave detectors are operating at a factor of 10 (in amplitude) above the standard quantum limit (SQL) within a broad frequency band. Such a low classical noise budget has already allowed the creation of a controlled 2.7 kg macroscopic oscillator with an effective eigenfrequency of 150 Hz and an occupation number of 200. This result, along with the prospect for further improvements, heralds the new possibility of experimentally probing macroscopic quantum mechanics (MQM) - quantum mechanical behavior of objects in the realm of everyday experience - using gravitational-wave detectors. In this paper, we provide the mathematical foundation for the first step of a MQM experiment: the preparation of a macroscopic test mass into a nearly minimum-Heisenberg-limited Gaussian quantum state, which is possible if the interferometer's classical noise beats the SQL in a broad frequency band. Our formalism, based on Wiener filtering, allows a straightforward conversion from the classical noise budget of a laser interferometer, in terms of noise spectra, into the strategy for quantum state preparation, and the quality of the prepared state. Using this formalism, we consider how Gaussian entanglement can be built among two macroscopic test masses, and the performance of the planned Advanced LIGO interferometers in quantum-state preparation

Search for supersymmetry in events with b-quark jets and missing transverse energy in pp collisions at 7 TeV

Results are presented from a search for physics beyond the standard model based on events with large missing transverse energy, at least three jets, and at least one, two, or three b-quark jets. The study is performed using a sample of proton-proton collision data collected at sqrt(s) = 7 TeV with the CMS detector at the LHC in 2011. The integrated luminosity of the sample is 4.98 inverse femtobarns. The observed number of events is found to be consistent with the standard model expectation, which is evaluated using control samples in the data. The results are used to constrain cross sections for the production of supersymmetric particles decaying to b-quark-enriched final states in the context of simplified model spectra.Comment: Submitted to Physical Review

ECRG4 is a candidate tumor suppressor gene frequently hypermethylated in colorectal carcinoma and glioma

<p>Abstract</p> <p>Background</p> <p>Cancer cells display widespread changes in DNA methylation that may lead to genetic instability by global hypomethylation and aberrant silencing of tumor suppressor genes by focal hypermethylation. In turn, altered DNA methylation patterns have been used to identify putative tumor suppressor genes.</p> <p>Methods</p> <p>In a methylation screening approach, we identified <it>ECRG4 </it>as a differentially methylated gene. We analyzed different cancer cells for <it>ECRG4 </it>promoter methylation by COBRA and bisulfite sequencing. Gene expression analysis was carried out by semi-quantitative RT-PCR. The <it>ECRG4 </it>coding region was cloned and transfected into colorectal carcinoma cells. Cell growth was assessed by MTT and BrdU assays. ECRG4 localization was analyzed by fluorescence microscopy and Western blotting after transfection of an <it>ECRG4-eGFP </it>fusion gene.</p> <p>Results</p> <p>We found a high frequency of <it>ECRG4 </it>promoter methylation in various cancer cell lines. Remarkably, aberrant methylation of <it>ECRG4 </it>was also found in primary human tumor tissues, including samples from colorectal carcinoma and from malignant gliomas. <it>ECRG4 </it>hypermethylation associated strongly with transcriptional silencing and its expression could be re-activated <it>in vitro </it>by demethylating treatment with 5-aza-2'-deoxycytidine. Overexpression of <it>ECRG4 </it>in colorectal carcinoma cells led to a significant decrease in cell growth. In transfected cells, ECRG4 protein was detectable within the Golgi secretion machinery as well as in the culture medium.</p> <p>Conclusions</p> <p><it>ECRG4 </it>is silenced via promoter hypermethylation in different types of human cancer cells. Its gene product may act as inhibitor of cell proliferation in colorectal carcinoma cells and may play a role as extracellular signaling molecule.</p