Fabrication of p-type porous GaN on silicon and epitaxial GaN

Abstract : Porous GaN layers are grown on silicon from gold or platinum catalyst seed layers, and self-catalyzed on epitaxial GaN films on sapphire. Using a Mg-based precursor, we demonstrate p-type doping of the porous GaN. Electrical measurements for p-type GaN on Si show Ohmic and Schottky behavior from gold and platinum seeded GaN, respectively. Ohmicity is attributed to the formation of a Ga2Au intermetallic. Porous p-type GaN was also achieved on epitaxial n-GaN on sapphire, and transport measurements confirm a p-n junction commensurate with a doping density of 1018 cm 3. Photoluminescence and cathodoluminescence confirm emission from Mg-acceptors in porous p-type GaN

Translation of tissue-based artificial intelligence into clinical practice: from discovery to adoption.

Digital pathology (DP), or the digitization of pathology images, has transformed oncology research and cancer diagnostics. The application of artificial intelligence (AI) and other forms of machine learning (ML) to these images allows for better interpretation of morphology, improved quantitation of biomarkers, introduction of novel concepts to discovery and diagnostics (such as spatial distribution of cellular elements), and the promise of a new paradigm of cancer biomarkers. The application of AI to tissue analysis can take several conceptual approaches, within the domains of language modelling and image analysis, such as Deep Learning Convolutional Neural Networks, Multiple Instance Learning approaches, or the modelling of risk scores and their application to ML. The use of different approaches solves different problems within pathology workflows, including assistive applications for the detection and grading of tumours, quantification of biomarkers, and the delivery of established and new image-based biomarkers for treatment prediction and prognostic purposes. All these AI formats, applied to digital tissue images, are also beginning to transform our approach to clinical trials. In parallel, the novelty of DP/AI devices and the related computational science pipeline introduces new requirements for manufacturers to build into their design, development, regulatory and post-market processes, which may need to be taken into account when using AI applied to tissues in cancer discovery. Finally, DP/AI represents challenge to the way we accredit new diagnostic tools with clinical applicability, the understanding of which will allow cancer patients to have access to a new generation of complex biomarkers

Desipramine treatment in normal subjects. Effects on neuroendocrine responses to tryptophan and on platelet serotonin (5-HT)-related receptors.

Normal subjects took the tricyclic antidepressant, desipramine hydrochloride, for 16 days. Following treatment there was an increase in the number of specific binding sites on the platelet for both tritiated imipramine and tritiated LSD, the latter site probably representing a platelet serotonin (5-HT) receptor. During desipramine treatment the prolactin response to tryptophan (L-tryptophan) was enhanced, and this enhancement correlated with the increase in platelet LSD binding. The results confirm previous observations that desipramine administration increases certain 5-HT-mediated neuroendocrine responses. Our findings further indicate that desipramine may alter both 5-HT uptake and 5-HT receptor sensitivity, and suggest that the platelet LSD receptor may in certain conditions provide a useful model of 5-HT receptors in the brain