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dc.contributor.authorAdler, Gail K.
dc.contributor.authorKlerman, Elizabeth B.
dc.contributor.authorFaghih, Rose Taj
dc.contributor.authorDahleh, Munther A
dc.contributor.authorBrown, Emery Neal
dc.date.accessioned2016-10-24T21:31:13Z
dc.date.available2016-10-24T21:31:13Z
dc.date.issued2015-10
dc.identifier.issn0018-9294
dc.identifier.issn1558-2531
dc.identifier.urihttp://hdl.handle.net/1721.1/104966
dc.description.abstractPulsatile release of cortisol from the adrenal glands is governed by pulsatile release of adrenocorticotropic hormone (ACTH) from the anterior pituitary. In return, cortisol has a negative feedback effect on ACTH release. Simultaneous recording of ACTH and cortisol is not typical, and determining the number, timing, and amplitudes of pulsatile events from simultaneously recorded data is challenging because of several factors: 1) stimulator ACTH pulse activity, 2) kinematics of ACTH and cortisol, 3) the sampling interval, and 4) the measurement error. We model ACTH and cortisol secretion simultaneously using a linear differential equations model with Gaussian errors and sparse pulsatile events as inputs to the model. We propose a novel framework for recovering pulses and parameters underlying the interactions between ACTH and cortisol. We recover the timing and amplitudes of pulses using compressed sensing and employ generalized cross validation for determining the number of pulses. We analyze serum ACTH and cortisol levels sampled at 10-min intervals over 24 h from ten healthy women. We recover physiologically plausible timing and amplitudes for these pulses and model the feedback effect of cortisol. We recover 15 to 18 pulses over 24 h, which is highly consistent with the results of another cortisol data analysis approach. Modeling the interactions between ACTH and cortisol allows for accurate quantification of pulsatile events, and normal and pathological states. This could lay the basis for a more physiologically-based approach for administering cortisol therapeutically. The proposed approach can be adapted to deconvolve other pairs of hormones with similar interactions.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant DP1 OD003646)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Grant 0836720)en_US
dc.description.sponsorshipNational Science Foundation (U.S.). Office of Emerging Frontiers in Research and Innovation (Grant 0735956)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Graduate Research Fellowship)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant R01GM 53559)en_US
dc.description.sponsorshipNational Space Biomedical Research Institute (Grant NCC9-58)en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/tbme.2015.2427745en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcePMCen_US
dc.titleQuantifying Pituitary-Adrenal Dynamics and Deconvolution of Concurrent Cortisol and Adrenocorticotropic Hormone Data by Compressed Sensingen_US
dc.typeArticleen_US
dc.identifier.citationFaghih, Rose T. et al. “Quantifying Pituitary-Adrenal Dynamics and Deconvolution of Concurrent Cortisol and Adrenocorticotropic Hormone Data by Compressed Sensing.” IEEE Transactions on Biomedical Engineering 62.10 (2015): 2379–2388.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Data, Systems, and Societyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Medical Engineering & Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Divisionen_US
dc.contributor.departmentPicower Institute for Learning and Memoryen_US
dc.contributor.mitauthorFaghih, Rose Taj
dc.contributor.mitauthorDahleh, Munther A
dc.contributor.mitauthorBrown, Emery Neal
dc.relation.journalIEEE Transactions on Biomedical Engineeringen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsFaghih, Rose T.; Dahleh, Munther A.; Adler, Gail K.; Klerman, Elizabeth B.; Brown, Emery N.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-9959-8422
dc.identifier.orcidhttps://orcid.org/0000-0002-1470-2148
dc.identifier.orcidhttps://orcid.org/0000-0003-2668-7819
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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