Kevin Bishop on Muck Rack

Kevin Bishop

Falmouth
As seen in: BBC, Color Research & Application, Nature, Wiley Online Library, Rotten Tomatoes, Taylor & Francis Online, ACS Publications, Cell Press, Chief Marketer, Optica and
Journalism & sports lecturer @marjonuni & @falmouthuni. Media man for @MouseholeAFC Senior fellow @jschofieldtrust
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Articles

3D pathology-guided microdissection - Nature Methods

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By Gan Gao, Qinghua Han, David Brenes, Elena Baraznenok, Renao Yan, Robert Serafin, Kevin Bishop, Rui Wang, Eric Q. Konnick, Colin Pritchard, Sandy Figiel, Freddie C. Hamdy, Ian Mills, Nicholas P. Reder, Deepti Reddi, Thomas G. Paulson, William Grady, Jacob Valk, Lawrence D. True, Michael Haffner, Srinivasa Rao, Dan J. Woodcock, Jonathan T. C. Liu, Huai-Ching Hsieh
| Nature Verified
Abstract Traditional micro- and macrodissection techniques enable the extraction of localized regions in thin tissue sections for molecular analysis. Despite the growing use of three-dimensional (3D) microscopy, analogous methods for volumetric microdissection are lacking. Here we have developed a 3D microdissection method based on computer numerical controlled milling integrated with open-top light-sheet microscopy.
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Macrophages Mediate Mesoscale Brain Mechanical Homeostasis

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By Bailey Johnson, Patricia Gordon, Kevin Bishop, Hyeyeon Gong
| Wiley Online Library Verified
1 Introduction Organ homeostasis relies on the dynamic rearrangement, expansion, and remodeling of interconnected tissues. In the brain, this involves the cooperative function of neuronal networks, specialized vascular systems like the blood–brain barrier, meningeal lymphatics, and brain-specific immune cells, such as microglia.[1-4] In particular, microglia play an important role in the developing brain.
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The quantum mechanical potential of mean force: density matrix formulation, estimators, and constrained path integral molecular dynamics integrators

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By Kevin Bishop, Pierre-Nicholas Roy, Dmitri Iouchtchenko
| Taylor & Francis Online
Abstract We obtain a formal expression for the quantum mechanical potential of mean force (PMF) in terms of the reduced density matrix associated with a reaction coordinate. We derive two path integral estimators for the derivative of the quantum mechanical PMF, which may be integrated to yield the PMF. For the first estimator, we perform the differentiation on the exact path integral, and for the second, the differentiation is performed after discretisation.
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