245 research outputs found

    Lower NPAS3 expression during the later stages of abnormal lung development in rat congenital diaphragmatic hernia

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    Purpose Congenital diaphragmatic hernia (CDH) is characterized by a developmental defect in the diaphragm, pulmonary hypoplasia and pulmonary hypertension. NPAS3 is a PAS domain transcription factor regulating Drosophila tracheogenesis. NPAS3 null mice develop pulmonary hypoplasia in utero and die after birth due to respiratory failure. We aimed to evaluate NPAS3 expres- sion during normal and abnormal lung development due to CDH. Methods CDH was induced by administering 100 mg/ml nitrofen to time-pregnant dams on embryonic day (E) 9 of gestation. Lungs were isolated on E15, E18 and E21 and NPAS3 localization was determined by immunohisto- chemistry and quantified using Western blotting. Results We found that only E21 hypoplastic CDH lungs have reduced expression of NPAS3 in the terminal sac- cules. Western blotting confirmed the down-regulation of NPAS3 protein in the nitrofen-induced hypoplastic lungs. Conclusions We demonstrate for the first time that ni- trofen-induced hypoplastic CDH lungs have reduced NPAS3 expression in the terminal saccules during the later stages of abnormal lung development. Our findings suggest that NPAS3 is associated with pulmonary hypoplasia in CDH.Supported by the Children’s Hospital Research Institute of Manitoba; RK is the recipient of a Career Enhancement Award from the Canadian Child Health Clinician Scientist Program and a New Investigator Salary Award from the Canadian Institutes of Health Research, Manitoba Lung Association and the Children’s Hospital Research Institute

    Search for the glueball candidates f0(1500) and fJ(1710) in gamma gamma collisions

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    Data taken with the ALEPH detector at LEP1 have been used to search for gamma gamma production of the glueball candidates f0(1500) and fJ(1710) via their decay to pi+pi-. No signal is observed and upper limits to the product of gamma gamma width and pi+pi- branching ratio of the f0(1500) and the fJ(1710) have been measured to be Gamma_(gamma gamma -> f0(1500)). BR(f0(1500)->pi+pi-) < 0.31 keV and Gamma_(gamma gamma -> fJ(1710)). BR(fJ(1710)->pi+pi-) < 0.55 keV at 95% confidence level.Comment: 10 pages, 3 figure

    The ves hypothesis and protein misfolding

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    Proteins function by changing conformation. These conformational changes, which involve the concerted motion of a large number of atoms are classical events but, in many cases, the triggers are quantum mechani- cal events such as chemical reactions. Here the initial quantum states after the chemical reaction are assumed to be vibrational excited states, something that has been designated as the VES hypothesis. While the dynamics under classical force fields fail to explain the relatively lower structural stability of the proteins associated with misfolding diseases, the application of the VES hy- pothesis to two cases can provide a new explanation for this phenomenon. This explanation relies on the transfer of vibrational energy from water molecules to proteins, a process whose viability is also examined

    Search for the standard model Higgs boson at LEP

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    Revealing General Patterns of Microbiomes That Transcend Systems: Potential and Challenges of Deep Transfer Learning

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    Special Series: Deciphering the Microbio.A growing body of research has established that the microbiome can mediate the dynamics and functional capacities of diverse biological systems. Yet, we understand little about what governs the response of these microbial communities to host or environmental changes. Most efforts to model microbiomes focus on defining the relationships between the microbiome, host, and environmental features within a specified study system and therefore fail to capture those that may be evident across multiple systems. In parallel with these developments in microbiome research, computer scientists have developed a variety of machine learning tools that can identify subtle, but informative, patterns from complex data. Here, we recommend using deep transfer learning to resolve microbiome patterns that transcend study systems. By leveraging diverse public data sets in an unsupervised way, such models can learn contextual relationships between features and build on those patterns to perform subsequent tasks (e.g., classification) within specific biological contexts.We thank the National Science Foundation for the funding of this work under grant number URoL:MTM2 2025457.Peer reviewe

    Search for R-Parity Violating Decays of Supersymmetric Particles in e+ee^{+}e^{-} Collisions at Centre-of-Mass Energies near 183 GeV

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    Searches for pair-production of supersymmetric particles under the assumption that R-parity is violated via a single dominant LLEˉLL{\bar E}, LQDˉLQ{\bar D} or UˉDˉDˉ{\bar U} {\bar D} {\bar D} coupling are performed using the data collected by the \ALEPH\ collaboration at centre-of-mass energies of 181--184~\gev. The observed candidate events in the data are in agreement with the Standard Model expectations. Upper limits on the production cross-sections and lower limits on the masses of charginos, sleptons, squarks and sneutrinos are de rived
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