5 results on '"Tenebaum, J."'
Search Results
2. A blood-based signature of cerebrospinal fluid A beta(1-42) status
- Author
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Goudey, B., Fung, B.J., Schieber, C., Faux, N.G., Weiner, M.W., Aisen, P., Petersen, R., Jack, C.R., Jagust, W., Trojanowki, J.Q., Toga, A.W., Beckett, L., Green, R.C., Saykin, A.J., Morris, J., Shaw, L.M., Kaye, J., Quinn, J., Silbert, L., Lind, B., Carter, R., Dolen, S., Schneider, L.S., Pawluczyk, S., Beccera, M., Teodoro, L., Spann, B.M., Brewer, J., Vanderswag, H., Fleisher, A., Heidebrink, J.L., Lord, J.L., Mason, S.S., Albers, C.S., Knopman, D., Johnson, K., Doody, R.S., Villanueva-Meyer, J., Chowdhury, M., Rountree, S., Dang, M., Stern, Y., Honig, L.S., Bell, K.L., Ances, B., Morris, J.C., Carroll, M., Creech, M.L., Franklin, E., Mintun, M.A., Schneider, S., Oliver, A., Marson, D., Griffth, R., Clark, D., Geldmacher, D., Brockington, J., Roberson, E., Natelson Love, M., Grossman, H., Mitsis, E., Shah, R.C., deToledo-Morrell, L., Duara, R., Varon, D., Greig, M.T., Roberts, P., Albert, M., Onyike, C., D'Agostino, D., Kielb, S., Galvin, J.E., Cerbone, B., Michel, C.A., Pogorelec, D.M., Rusinek, H., Leon, M.J. de, Glodzik, L., De Santi, S., Doraiswamy, P.M., Petrella, J.R., Borges-Neto, S., Wong, T.Z., Coleman, E., Smith, C.D., Jicha, G., Hardy, P., Sinha, P., Oates, E., Conrad, G., Porsteinsson, A.P., Goldstein, B.S., Martin, K., Makino, K.M., Ismail, M.S., Brand, C., Mulnard, R.A., Thai, G., McAdams-Ortiz, C., Womack, K., Mathews, D., Quiceno, M., Levey, A.I., Lah, J.J., Cellar, J.S., Burns, J.M., Swerdlow, R.H., Brooks, W.M., Apostolova, L., Tingus, K., Woo, E., Silverman, D.H.S., Lu, P.H., Bartzokis, G., Graff-Radford, N.R., Parftt, F., Kendall, T., Johnson, H., Farlow, M.R., Hake, A.M., Matthews, B.R., Brosch, J.R., Herring, S., Hunt, C., Dyck, .H. van, Carson, R.E., MacAvoy, M.G., Varma, P., Chertkow, H., Bergman, H., Hosein, C., Black, S., Stefanovic, B., Caldwell, C., Hsiung, Ging-Yuek Robin, Feldman, H., Mudge, B., Assaly, M., Finger, E., Pasternack, S., Rachisky, I., Trost, D., Kertesz, A., Bernick, C., Munic, D., Mesulam, M.-M., Lipowski, K., Weintraub, S., Bonakdarpour, B., Kerwin, D., Wu, C.-K., Johnson, N., Sadowsky, C., Villena, T., Turner, R.S., Reynolds, B., Sperling, R.A., Johnson, K.A., Marshall, G., Yesavage, J., Taylor, J.L., Lane, B., Rosen, A., Tinklenberg, J., Sabbagh, M.N., Belden, C.M., Jacobson, S.A., Sirrel, S.A., Kowall, N., Killiany, R., Budson, A.E., Norbash, A., Johnson, P.L., Obisesan, T.O., Wolday, S., Allard, J., Lerner, A., Ogrocki, P., Tatsuoka, C., Fatica, P., Fletcher, E., Maillard, P., Olichney, J., DeCarli, C., Carmichael, O., Kittur, S., Borrie, M., Lee, T.-Y., Bartha, R., Johnson, S., Asthana, S., Carlsson, C.M., Potkin, S.G., Preda, A., Nguyen, D., Tariot, P., Burke, A., Trncic, N., Reeder, S., Bates, V., Capote, H., Rainka, M., Scharre, D.W., Kataki, M., Adeli, A., Zimmerman, E.A., Celmins, D., Brown, A.D., Pearlson, G.D., Blank, K., Anderson, K., Flashman, L.A., Seltzer, M., Hynes, M.L., Santulli, R.B., Sink, K.M., Gordineer, L., Williamson, J.D., Garg, P., Watkins, F., Ott, B.R., Querfurth, H., Tremont, G., Salloway, S., Malloy, P., Correia, S., Rosen, H.J., Miller, B.L., Perry, D., Mintzer, J., Spicer, K., Bachman, D., Pomara, N., Hernando, R., Sarrael, A., Relkin, N., Chaing, G., Lin, M., Ravdin, L., Smith, A., Raj, B.A., Fargher, K., Saykin, A., Nho, K., Kling, M., Toledo, J., Shaw, L., Trojanowski, J., Farrer, L., Kastsenmueller, G., Arnold, M., Wishart, D., Wurtz, P., Bhattcharyya, S., Duijin, C. van, Mangravite, L., Han, X., Hankemeier, T., Fiehn, O., Barupal, D., Thiele, I., Heinken, A., Meikle, P., Price, N., Funk, C., Jia, W., Kueider-Paisley, A., Tenebaum, J., Black, C., Moseley, A., Thompson, W., Mahmoudiandehkorki, S., Baillie, R., Welsh-Bohmer, K., Plassman, B., and Epidemiology
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Male ,0301 basic medicine ,Apolipoprotein E ,Oncology ,medicine.medical_specialty ,Amyloid ,Amyloid beta ,lcsh:Medicine ,Article ,03 medical and health sciences ,Apolipoproteins E ,0302 clinical medicine ,Cerebrospinal fluid ,Alzheimer Disease ,Predictive Value of Tests ,Internal medicine ,medicine ,Humans ,Dementia ,Cognitive decline ,lcsh:Science ,Aged ,Aged, 80 and over ,Amyloid beta-Peptides ,Multidisciplinary ,biology ,Chemokine CCL26 ,business.industry ,lcsh:R ,Alzheimer’s Disease Metabolomics Consortium ,Alzheimer’s Disease Neuroimaging Initiative ,medicine.disease ,Peptide Fragments ,3. Good health ,030104 developmental biology ,biology.protein ,Chromogranin A ,Female ,lcsh:Q ,Alzheimer's disease ,business ,Biomarkers ,030217 neurology & neurosurgery ,Alzheimer's Disease Neuroimaging Initiative - Abstract
It is increasingly recognized that Alzheimer’s disease (AD) exists before dementia is present and that shifts in amyloid beta occur long before clinical symptoms can be detected. Early detection of these molecular changes is a key aspect for the success of interventions aimed at slowing down rates of cognitive decline. Recent evidence indicates that of the two established methods for measuring amyloid, a decrease in cerebrospinal fluid (CSF) amyloid β1−42 (Aβ1−42) may be an earlier indicator of Alzheimer’s disease risk than measures of amyloid obtained from Positron Emission Tomography (PET). However, CSF collection is highly invasive and expensive. In contrast, blood collection is routinely performed, minimally invasive and cheap. In this work, we develop a blood-based signature that can provide a cheap and minimally invasive estimation of an individual’s CSF amyloid status using a machine learning approach. We show that a Random Forest model derived from plasma analytes can accurately predict subjects as having abnormal (low) CSF Aβ1−42 levels indicative of AD risk (0.84 AUC, 0.78 sensitivity, and 0.73 specificity). Refinement of the modeling indicates that only APOEε4 carrier status and four plasma analytes (CGA, Aβ1−42, Eotaxin 3, APOE) are required to achieve a high level of accuracy. Furthermore, we show across an independent validation cohort that individuals with predicted abnormal CSF Aβ1−42 levels transitioned to an AD diagnosis over 120 months significantly faster than those with predicted normal CSF Aβ1−42 levels and that the resulting model also validates reasonably across PET Aβ1−42 status (0.78 AUC). This is the first study to show that a machine learning approach, using plasma protein levels, age and APOEε4 carrier status, is able to predict CSF Aβ1−42 status, the earliest risk indicator for AD, with high accuracy.
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- 2019
3. Lender liability related to credit inquiries
- Author
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Tenebaum, J. Samuel and Treger, Tracy L.
- Subjects
Banking industry -- Management ,Liability for credit information -- Management ,Banking, finance and accounting industries ,Business - Abstract
Banks responding to inquiries about the credit status of their customers expose themselves to liabilities for deliberately misleading an inquirer, unintentionally disclosing incorrect information or providing information against the customer's wishes. Such liabilities can be prevented by reviewing state statutes and case laws, asking for the reasons behind inquiries and disavowing responsibility for responses given to inquirers.
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- 1996
4. CommerceNet Consortium.
- Author
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Tenebaum, J. M., primary
- Published
- 1999
- Full Text
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5. CommerceNet Consortium.
- Author
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COMMERCENET CONSORTIUM PALO ALTO CA, Tenebaum, J. M., COMMERCENET CONSORTIUM PALO ALTO CA, and Tenebaum, J. M.
- Abstract
This report recaps the major activities and accomplishments of CommerceNet during the three years it operated under the TRP grant from April 1994 to April 1997. During that period CommerceNet became the premier industry association for promoting and building electronic commerce solutions on the Internet. CommerceNet's mission is to make electronic commerce easy, trusted and ubiquitous. Launched in Silicon Valley, California, in April 1994 CommerceNet was formed as a non-profit 5OlC6 corporation with support from a United States government TRP grant. The membership grew to over 500 companies and organizations worldwide. They include the leading banks, telecommunications companies, VANs, ISPs, on-line services, software and services companies, as well as major end-users. Together with its members, CommerceNet is transforming the net into a global electronic marketplace.
- Published
- 1999
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