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3 Stricker Learning Span criterion validity: remote self-administration of a computer adaptive word list memory test shows similar ability to differentiate PET-defined biomarker groups as in-person Rey Auditory Verbal Learning Test performance in cognitively unimpaired individuals on the Alzheimer’s continuum
- Nikki H. Stricker, John L. Stricker, Aimee J. Karstens, Jay S. Patel, Teresa J. Christianson, Winnie Z. Fan, Sabrina M. Albertson, Ryan D. Frank, Mary M. Machulda, Walter K. Kremers, Julie A. Fields, Jonathan Graff-Radford, Clifford R. Jack, Jr, David S. Knopman, Michelle M. Mielke, Ronald C. Petersen
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 407-408
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Objective:
The Stricker Learning Span (SLS) is a computer-adaptive word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). Given recent evidence suggesting the prominence of learning impairment in preclinical Alzheimer’s disease (AD), the SLS places greater emphasis on learning than delayed memory compared to traditional word list memory tests (see Stricker et al., Neuropsychology in press for review and test details). The primary study aim was to establish criterion validity of the SLS by comparing the ability of the remotely-administered SLS and inperson administered Rey Auditory Verbal Learning Test (AVLT) to differentiate biomarkerdefined groups in cognitively unimpaired (CU) individuals on the Alzheimer’s continuum.
Participants and Methods:Mayo Clinic Study of Aging CU participants (N=319; mean age=71, SD=11; mean education=16, SD=2; 47% female) completed a brief remote cognitive assessment (∼0.5 months from in-person visit). Brain amyloid and brain tau PET scans were available within 3 years. Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (A+, n=110) or not (A-, n=209), and for 2) those with biological AD (A+T+, n=43) vs no evidence of AD pathology (A-T-, n=181). Primary neuropsychological outcome variables were sum of trials for both the SLS and AVLT. Secondary outcome variables examined comparability of learning (1-5 total) and delay performances. Linear model ANOVAs were used to investigate biomarker subgroup differences and Hedge’s G effect sizes were derived, with and without adjusting for demographic variables (age, education, sex).
Results:Both SLS and AVLT performances were worse in the biomarker positive relative to biomarker negative groups (unadjusted p’s<.05). Because biomarker positive groups were significantly older than biomarker negative groups, group differences were attenuated after adjusting for demographic variables, but SLS remained significant for A+ vs A- and for A+T+ vs A-T- comparisons (adjusted p’s<.05) and AVLT approached significance (p’s .05-.10). The effect sizes for the SLS were slightly better (qualitatively, no statistical comparison) for separating biomarker-defined CU groups in comparison to AVLT. For A+ vs A- and A+T+ vs A-T- comparisons, unadjusted effect sizes for SLS were -0.53 and -0.81 and for AVLT were -0.47 and -0.61, respectively; adjusted effect sizes for SLS were -0.25 and -0.42 and for AVLT were -0.19 and -0.26, respectively. In secondary analyses, learning and delay variables were similar in terms of ability to separate biomarker groups. For example, unadjusted effect sizes for SLS learning (-.80) was similar to SLS delay (.76), and AVLT learning (-.58) was similar to AVLT 30-minute delay (-.55) for the A+T+ vs AT- comparison.
Conclusions:Remotely administered SLS performed similarly to the in-person-administered AVLT in its ability to separate biomarker-defined groups in CU individuals, providing evidence of criterion validity. The SLS showed significantly worse performance in A+ and A+T+ groups (relative to A- and A-T-groups) in this CU sample after demographic adjustment, suggesting potential sensitivity to detecting transitional cognitive decline in preclinical AD. Measures emphasizing learning should be given equal consideration as measures of delayed memory in AD-focused studies, particularly in the preclinical phase.
65 Mayo Test Drive raw composite criterion validity: a brief remote self-administered digital cognitive composite shows similar ability to differentiate PET-defined biomarker groups as a global composite from a person-administered neuropsychological battery in cognitively unimpaired individuals on the Alzheimer’s continuum
- Nikki H. Stricker, Aimee J. Karstens, Teresa J. Christianson, John L. Stricker, Winnie Z. Fan, Sabrina M. Albertson, Ryan D. Frank, Mary M. Machulda, Walter K. Kremers, Jason Hassenstab, Julie A. Fields, Jonathan Graff-Radford, Clifford R. Jack, Jr., David S. Knopman, Michelle M. Mielke, Ronald C. Petersen
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 371-372
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Objective:
Mayo Test Drive (MTD): Test Development through Rapid Iteration, Validation and Expansion, is a web-based multi-device (smartphone, tablet, personal computer) platform optimized for remote self-administered cognitive assessment that includes a computer-adaptive word list memory test (Stricker Learning Span; SLS; Stricker et al., 2022; Stricker et al., in press) and a measure of processing speed (Symbols Test: Wilks et al., 2021). Study aims were to determine criterion validity of MTD by comparing the ability of the MTD raw composite and in-person administered cognitive measures to differentiate biomarkerdefined groups in cognitively unimpaired (CU) individuals on the Alzheimer’s continuum.
Participants and Methods:Mayo Clinic Study of Aging CU participants (N=319; mean age=71, SD=11, range=37-94; mean education=16, SD=2, range=6-20; 47% female) completed a brief remote cognitive assessment (∼0.5 months from in-person visit). Brain amyloid and brain tau PET scans were available within 3 years. Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (A+, n=110) or not (A-, n=209), and for 2) those with biological AD (A+T+, n=43) or with no evidence of AD pathology (A-T-, n=181). Primary outcome variables were MTD raw composite (SLS sum of trials + an accuracy-weighted Symbols response time measure), Global-z (average of 9 in-person neuropsychological measures) and an in-person screening measure (Kokmen Short Test of Mental Status, STMS; which is like the MMSE). Linear model ANOVAs were used to investigate biomarker subgroup differences and Hedge’s G effect sizes were derived, with and without adjusting for demographic variables (age, education, sex).
Results:Remotely administered MTD raw composite showed comparable to slightly larger effect sizes compared to Global-z. Unadjusted effect sizes for MTD raw composite for differentiating A+ vs. A- and A+T+ vs. A-T- groups, respectively, were -0.57 and -0.84 and effect sizes for Global-z were -0.54 and -0.73 (all p’s<.05). Because biomarker positive groups were significantly older than biomarker negative groups, group differences were attenuated after adjusting for demographic variables, but MTD raw composite remained significant for A+T+ vs A-T- (adjusted effect size -0.35, p=.007); Global-z did not reach significance for A+T+ vs A-T- (adjusted effect size -0.19, p=.08). Neither composite reached significance for adjusted analyses for the A+ vs A- comparison (MTD raw composite adjusted effect size= -.22, p=.06; Global-z adjusted effect size= -.08, p=.47). Results were the same for an alternative MTD composite using traditional z-score averaging methods, but the raw score method is preferred for comparability to other screening measures. The STMS screening measure did not differentiate biomarker groups in any analyses (unadjusted and adjusted p’s>.05; d’s -0.23 to 0.05).
Conclusions:Remotely administered MTD raw composite shows at least similar ability to separate biomarker-defined groups in CU individuals as a Global-z for person-administered measures within a neuropsychological battery, providing evidence of criterion validity. Both the MTD raw composite and Global-z showed greater ability to separate biomarker positive from negative CU groups compared to a typical screening measure (STMS) that was unable to differentiate these groups. MTD may be useful as a screening measure to aid early detection of Alzheimer’s pathological changes.
Mayo normative studies: regression-based normative data for ages 30–91 years with a focus on the Boston Naming Test, Trail Making Test and Category Fluency
- Aimee J. Karstens, Teresa J. Christianson, Emily S. Lundt, Mary M. Machulda, Michelle M. Mielke, Julie A. Fields, Walter K. Kremers, Jonathan Graff-Radford, Prashanthi Vemuri, Clifford R. Jack, Jr., David S. Knopman, Ronald C. Petersen, Nikki H. Stricker
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- Journal:
- Journal of the International Neuropsychological Society / Volume 30 / Issue 4 / May 2024
- Published online by Cambridge University Press:
- 28 November 2023, pp. 389-401
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Objective:
Normative neuropsychological data are essential for interpretation of test performance in the context of demographic factors. The Mayo Normative Studies (MNS) aim to provide updated normative data for neuropsychological measures administered in the Mayo Clinic Study of Aging (MCSA), a population-based study of aging that randomly samples residents of Olmsted County, Minnesota, from age- and sex-stratified groups. We examined demographic effects on neuropsychological measures and validated the regression-based norms in comparison to existing normative data developed in a similar sample.
Method:The MNS includes cognitively unimpaired adults ≥30 years of age (n = 4,428) participating in the MCSA. Multivariable linear regressions were used to determine demographic effects on test performance. Regression-based normative formulas were developed by first converting raw scores to normalized scaled scores and then regressing on age, age2, sex, and education. Total and sex-stratified base rates of low scores (T < 40) were examined in an older adult validation sample and compared with Mayo’s Older Americans Normative Studies (MOANS) norms.
Results:Independent linear regressions revealed variable patterns of linear and/or quadratic effects of age (r2 = 6–27% variance explained), sex (0–13%), and education (2–10%) across measures. MNS norms improved base rates of low performance in the older adult validation sample overall and in sex-specific patterns relative to MOANS.
Conclusions:Our results demonstrate the need for updated norms that consider complex demographic associations on test performance and that specifically exclude participants with mild cognitive impairment from the normative sample.
Stricker Learning Span criterion validity: a remote self-administered multi-device compatible digital word list memory measure shows similar ability to differentiate amyloid and tau PET-defined biomarker groups as in-person Auditory Verbal Learning Test
- Nikki H. Stricker, John L. Stricker, Ryan D. Frank, Winnie Z. Fan, Teresa J. Christianson, Jay S. Patel, Aimee J. Karstens, Walter K. Kremers, Mary M. Machulda, Julie A. Fields, Jonathan Graff-Radford, Clifford R. Jack, Jr., David S. Knopman, Michelle M. Mielke, Ronald C. Petersen
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- Journal:
- Journal of the International Neuropsychological Society / Volume 30 / Issue 2 / February 2024
- Published online by Cambridge University Press:
- 30 June 2023, pp. 138-151
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Objective:
The Stricker Learning Span (SLS) is a computer-adaptive digital word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). We aimed to establish criterion validity of the SLS by comparing its ability to differentiate biomarker-defined groups to the person-administered Rey’s Auditory Verbal Learning Test (AVLT).
Method:Participants (N = 353; mean age = 71, SD = 11; 93% cognitively unimpaired [CU]) completed the AVLT during an in-person visit, the SLS remotely (within 3 months) and had brain amyloid and tau PET scans available (within 3 years). Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (amyloid PET positive, A+, n = 125) or not (A-, n = 228), and those with biological AD (amyloid and tau PET positive, A+T+, n = 55) vs no evidence of AD pathology (A−T−, n = 195). Analyses were repeated among CU participants only.
Results:The SLS and AVLT showed similar ability to differentiate biomarker-defined groups when comparing AUROCs (p’s > .05). In logistic regression models, SLS contributed significantly to predicting biomarker group beyond age, education, and sex, including when limited to CU participants. Medium (A− vs A+) to large (A−T− vs A+T+) unadjusted effect sizes were observed for both SLS and AVLT. Learning and delay variables were similar in terms of ability to separate biomarker groups.
Conclusions:Remotely administered SLS performed similarly to in-person-administered AVLT in its ability to separate biomarker-defined groups, providing evidence of criterion validity. Results suggest the SLS may be sensitive to detecting subtle objective cognitive decline in preclinical AD.
Absolute risks of self-harm and interpersonal violence by diagnostic category following first discharge from inpatient psychiatric care
- P. L. H. Mok, F. Walter, M. J. Carr, S. Antonsen, N. Kapur, S. Steeg, J. Shaw, C. B. Pedersen, R. T. Webb
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- Journal:
- European Psychiatry / Volume 66 / Issue 1 / 2023
- Published online by Cambridge University Press:
- 18 January 2023, e13
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Background
Persons discharged from inpatient psychiatric services are at greatly elevated risk of harming themselves or inflicting violence on others, but no studies have reported gender-specific absolute risks for these two outcomes across the spectrum of psychiatric diagnoses. We aimed to estimate absolute risks for self-harm and interpersonal violence post-discharge according to gender and diagnostic category.
MethodsDanish national registry data were utilized to investigate 62,922 discharged inpatients, born 1967–2000. An age and gender matched cohort study was conducted to examine risks for self-harm and interpersonal violence at 1 year and at 10 years post-discharge. Absolute risks were estimated as cumulative incidence percentage values.
ResultsPatients diagnosed with substance misuse disorders were at especially elevated risk, with the absolute risks for either self-harm or interpersonal violence being 15.6% (95% CI 14.9, 16.3%) of males and 16.8% (15.6, 18.1%) of females at 1 year post-discharge, rising to 45.7% (44.5, 46.8%) and 39.0% (37.1, 40.8%), respectively, within 10 years. Diagnoses of personality disorders and early onset behavioral and emotional disorders were also associated with particularly high absolute risks, whilst risks linked with schizophrenia and related disorders, mood disorders, and anxiety/somatoform disorders, were considerably lower.
ConclusionsPatients diagnosed with substance misuse disorders, personality disorders and early onset behavioral and emotional disorders are at especially high risk for internally and externally directed violence. It is crucial, however, that these already marginalized individuals are not further stigmatized. Enhanced care at discharge and during the challenging transition back to life in the community is needed.
Brain morphometric features predict medication response in youth with bipolar disorder: a prospective randomized clinical trial
- Du Lei, Kun Qin, Wenbin Li, Walter H. L. Pinaya, Maxwell J. Tallman, L. Rodrigo Patino, Jeffrey R. Strawn, David Fleck, Christina C. Klein, Su Lui, Qiyong Gong, Caleb M. Adler, Andrea Mechelli, John A. Sweeney, Melissa P. DelBello
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- Journal:
- Psychological Medicine / Volume 53 / Issue 9 / July 2023
- Published online by Cambridge University Press:
- 08 April 2022, pp. 4083-4093
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Background
Identification of treatment-specific predictors of drug therapies for bipolar disorder (BD) is important because only about half of individuals respond to any specific medication. However, medication response in pediatric BD is variable and not well predicted by clinical characteristics.
MethodsA total of 121 youth with early course BD (acute manic/mixed episode) were prospectively recruited and randomized to 6 weeks of double-blind treatment with quetiapine (n = 71) or lithium (n = 50). Participants completed structural magnetic resonance imaging (MRI) at baseline before treatment and 1 week after treatment initiation, and brain morphometric features were extracted for each individual based on MRI scans. Positive antimanic treatment response at week 6 was defined as an over 50% reduction of Young Mania Rating Scale scores from baseline. Two-stage deep learning prediction model was established to distinguish responders and non-responders based on different feature sets.
ResultsPre-treatment morphometry and morphometric changes occurring during the first week can both independently predict treatment outcome of quetiapine and lithium with balanced accuracy over 75% (all p < 0.05). Combining brain morphometry at baseline and week 1 allows prediction with the highest balanced accuracy (quetiapine: 83.2% and lithium: 83.5%). Predictions in the quetiapine and lithium group were found to be driven by different morphometric patterns.
ConclusionsThese findings demonstrate that pre-treatment morphometric measures and acute brain morphometric changes can serve as medication response predictors in pediatric BD. Brain morphometric features may provide promising biomarkers for developing biologically-informed treatment outcome prediction and patient stratification tools for BD treatment development.
Investigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder
- Emma C. Johnson, Manav Kapoor, Alexander S. Hatoum, Hang Zhou, Renato Polimanti, Frank R. Wendt, Raymond K. Walters, Dongbing Lai, Rachel L. Kember, Sarah Hartz, Jacquelyn L. Meyers, Roseann E. Peterson, Stephan Ripke, Tim B. Bigdeli, Ayman H. Fanous, Carlos N. Pato, Michele T. Pato, Alison M. Goate, Henry R. Kranzler, Michael C. O'Donovan, James T.R. Walters, Joel Gelernter, Howard J. Edenberg, Arpana Agrawal
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- Psychological Medicine / Volume 53 / Issue 4 / March 2023
- Published online by Cambridge University Press:
- 07 July 2021, pp. 1196-1204
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Background
Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders.
MethodsWe used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific.
ResultsWe identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001).
ConclusionsOur findings provide further evidence that SCZ shares meaningful genetic overlap with AUD.
Mayo Normative Studies: Regression-Based Normative Data for the Auditory Verbal Learning Test for Ages 30–91 Years and the Importance of Adjusting for Sex
- Nikki H. Stricker, Teresa J. Christianson, Emily S. Lundt, Eva C. Alden, Mary M. Machulda, Julie A. Fields, Walter K. Kremers, Clifford R. Jack, Jr., David S. Knopman, Michelle M. Mielke, Ronald C. Petersen
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- Journal:
- Journal of the International Neuropsychological Society / Volume 27 / Issue 3 / March 2021
- Published online by Cambridge University Press:
- 20 August 2020, pp. 211-226
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Objective:
Rey’s Auditory Verbal Learning Test (AVLT) is a widely used word list memory test. We update normative data to include adjustment for verbal memory performance differences between men and women and illustrate the effect of this sex adjustment and the importance of excluding participants with mild cognitive impairment (MCI) from normative samples.
Method:This study advances the Mayo’s Older Americans Normative Studies (MOANS) by using a new population-based sample through the Mayo Clinic Study of Aging, which randomly samples residents of Olmsted County, Minnesota, from age- and sex-stratified groups. Regression-based normative T-score formulas were derived from 4428 cognitively unimpaired adults aged 30–91 years. Fully adjusted T-scores correct for age, sex, and education. We also derived T-scores that correct for (1) age or (2) age and sex. Test-retest reliability data are provided.
Results:From raw score analyses, sex explained a significant amount of variance in performance above and beyond age (8–10%). Applying original age-adjusted MOANS norms to the current sample resulted in significantly fewer-than-expected participants with low delayed recall performance, particularly in women. After application of new T-scores adjusted only for age, even in normative data derived from this sample, these age-adjusted T-scores showed scores <40 T occurred more frequently among men and less frequently among women relative to T-scores that also adjusted for sex.
Conclusions:Our findings highlight the importance of using normative data that adjust for sex with measures of verbal memory and provide new normative data that allow for this adjustment for the AVLT.
Examining pathways between genetic liability for schizophrenia and patterns of tobacco and cannabis use in adolescence
- Hannah J. Jones, Gemma Hammerton, Tayla McCloud, Lindsey A. Hines, Caroline Wright, Suzanne H. Gage, Peter Holmans, Peter B Jones, George Davey Smith, David E. J. Linden, Michael C. O'Donovan, Michael J. Owen, James T. Walters, Marcus R. Munafò, Jon Heron, Stanley Zammit
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- Psychological Medicine / Volume 52 / Issue 1 / January 2022
- Published online by Cambridge University Press:
- 09 June 2020, pp. 132-139
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Background
It is not clear to what extent associations between schizophrenia, cannabis use and cigarette use are due to a shared genetic etiology. We, therefore, examined whether schizophrenia genetic risk associates with longitudinal patterns of cigarette and cannabis use in adolescence and mediating pathways for any association to inform potential reduction strategies.
MethodsAssociations between schizophrenia polygenic scores and longitudinal latent classes of cigarette and cannabis use from ages 14 to 19 years were investigated in up to 3925 individuals in the Avon Longitudinal Study of Parents and Children. Mediation models were estimated to assess the potential mediating effects of a range of cognitive, emotional, and behavioral phenotypes.
ResultsThe schizophrenia polygenic score, based on single nucleotide polymorphisms meeting a training-set p threshold of 0.05, was associated with late-onset cannabis use (OR = 1.23; 95% CI = 1.08,1.41), but not with cigarette or early-onset cannabis use classes. This association was not mediated through lower IQ, victimization, emotional difficulties, antisocial behavior, impulsivity, or poorer social relationships during childhood. Sensitivity analyses adjusting for genetic liability to cannabis or cigarette use, using polygenic scores excluding the CHRNA5-A3-B4 gene cluster, or basing scores on a 0.5 training-set p threshold, provided results consistent with our main analyses.
ConclusionsOur study provides evidence that genetic risk for schizophrenia is associated with patterns of cannabis use during adolescence. Investigation of pathways other than the cognitive, emotional, and behavioral phenotypes examined here is required to identify modifiable targets to reduce the public health burden of cannabis use in the population.
How Can Pharmacogenomics Biomarkers Be Translated into Patient Benefit
- D. Collier, E. Achilla, G. Breen, S. Curran, D. Dima, R. Flanagan, J. Frank, S. Frangou, C. Gasse, I. Giegling, M. Rietschel, D. Rujescu, J. Maccabe, P. McCrone, J. Mill, E. Sigurdsson, H. Stefansson, J. Walters, M. Verbelen, M. Helthuis
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- European Psychiatry / Volume 30 / Issue S1 / March 2015
- Published online by Cambridge University Press:
- 15 April 2020, p. 1
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Treatment resistant schizophrenia (TRS) is one of the most disabling of psychiatric disorders, affecting about 1/3 of patients. First-line treatments include both atypical and typical antipsychotics. The original atypical, clozapine, is a final option, and although it has been shown to be the only effective treatment for TRS, many patients do not respond well to clozapine. Clozapine use is related to adverse events, most notably agranulocytosis, a potentially fatal blood disorder which affects about 1% of those prescribed clozapine and requires regular blood monitoring. This as a barrier to prescription and there is a long delay in access for TRS patients, of five or more years, from first antipsychotic prescription. Better tools to predict treatment resistance and to identify risk of adverse events would allow faster and safer access to clozapine for patients who are likely to benefit from it. The CRESTAR project (www.crestar-project.eu) is a European Framework 7 collaborative project that aims to develop tools to predict i) treatment response, particularly patients who are less likely to respond to usual antipsychotics, indicating treatment with clozapine as early as possible, ii) patients who are at high or low risk of adverse events and side effects, iii) extreme TRS patients so that they can be stratified in clinical trials for novel treatments. CRESTAR has addressed these questions by examining genome-wide association data, genome sequence, epigenetic biomarkers and epidemiological data in European patient cohorts characterized for treatment response, and adverse drug reaction using data from clozapine therapeutic drug monitoring and linked National population medical and pharmacy databases, to identify predictive factors. In parallel CRESTAR will perform health economic research on potential benefits, and ethics and patient-centred research with stakeholders.
5 - Diamonds and the Mantle Geodynamics of Carbon
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- By Steven B. Shirey, Karen V. Smit, D. Graham Pearson, Michael J. Walter, Sonja Aulbach, Frank E. Brenker, Hélène Bureau, Antony D. Burnham, Pierre Cartigny, Thomas Chacko, Daniel J. Frost, Erik H. Hauri, Dorrit E. Jacob, Steven D. Jacobsen, Simon C. Kohn, Robert W. Luth, Sami Mikhail, Oded Navon, Fabrizio Nestola, Paolo Nimis, Mederic Palot, Evan M. Smith, Thomas Stachel, Vincenzo Stagno, Andrew Steele, Richard A. Stern, Emilie Thomassot, Andrew R. Thomson, Yaakov Weiss
- Edited by Beth N. Orcutt, Isabelle Daniel, Université Claude-Bernard Lyon I, Rajdeep Dasgupta, Rice University, Houston
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- Deep Carbon
- Published online:
- 03 October 2019
- Print publication:
- 17 October 2019, pp 89-128
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Summary
The science of studying diamond inclusions for understanding Earth history has developed significantly over the past decades, with new instrumentation and techniques applied to diamond sample archives revealing the stories contained within diamond inclusions. This chapter reviews what diamonds can tell us about the deep carbon cycle over the course of Earth’s history. It reviews how the geochemistry of diamonds and their inclusions inform us about the deep carbon cycle, the origin of the diamonds in Earth’s mantle, and the evolution of diamonds through time.
Subfossil lemur discoveries from the Beanka Protected Area in western Madagascar
- David A. Burney, Haingoson Andriamialison, Radosoa A. Andrianaivoarivelo, Steven Bourne, Brooke E. Crowley, Erik J. de Boer, Laurie R. Godfrey, Steven M. Goodman, Christine Griffiths, Owen Griffiths, Julian P. Hume, Walter G. Joyce, William L. Jungers, Stephanie Marciniak, Gregory J. Middleton, Kathleen M. Muldoon, Eliette Noromalala, Ventura R. Pérez, George H. Perry, Roger Randalana, Henry T. Wright
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- Quaternary Research / Volume 93 / January 2020
- Published online by Cambridge University Press:
- 02 October 2019, pp. 187-203
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A new fossil site in a previously unexplored part of western Madagascar (the Beanka Protected Area) has yielded remains of many recently extinct vertebrates, including giant lemurs (Babakotia radofilai, Palaeopropithecus kelyus, Pachylemur sp., and Archaeolemur edwardsi), carnivores (Cryptoprocta spelea), the aardvark-like Plesiorycteropus sp., and giant ground cuckoos (Coua). Many of these represent considerable range extensions. Extant species that were extirpated from the region (e.g., Prolemur simus) are also present. Calibrated radiocarbon ages for 10 bones from extinct primates span the last three millennia. The largely undisturbed taphonomy of bone deposits supports the interpretation that many specimens fell in from a rock ledge above the entrance. Some primates and other mammals may have been prey items of avian predators, but human predation is also evident. Strontium isotope ratios (87Sr/86Sr) suggest that fossils were local to the area. Pottery sherds and bones of extinct and extant vertebrates with cut and chop marks indicate human activity in previous centuries. Scarcity of charcoal and human artifacts suggests only occasional visitation to the site by humans. The fossil assemblage from this site is unusual in that, while it contains many sloth lemurs, it lacks ratites, hippopotami, and crocodiles typical of nearly all other Holocene subfossil sites on Madagascar.
Genetic influences on eight psychiatric disorders based on family data of 4 408 646 full and half-siblings, and genetic data of 333 748 cases and controls – CORRIGENDUM
- E. Pettersson, P. Lichtenstein, H. Larsson, J. Song, Attention Deficit/Hyperactivity Disorder Working Group of the iPSYCH-Broad-PGC Consortium, Autism Spectrum Disorder Working Group of the iPSYCH-Broad-PGC Consortium, Bipolar Disorder Working Group of the PGC, Eating Disorder Working Group of the PGC, Major Depressive Disorder Working Group of the PGC, Obsessive Compulsive Disorders and Tourette Syndrome Working Group of the PGC, Schizophrenia CLOZUK, Substance Use Disorder Working Group of the PGC, A. Agrawal, A. D. Børglum, C. M. Bulik, M. J. Daly, L. K. Davis, D. Demontis, H. J. Edenberg, J. Grove, J. Gelernter, B. M. Neale, A. F. Pardiñas, E. Stahl, J. T. R. Walters, R. Walters, P. F. Sullivan, D. Posthuma, T. J. C. Polderman
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- Journal:
- Psychological Medicine / Volume 49 / Issue 2 / January 2019
- Published online by Cambridge University Press:
- 18 October 2018, p. 351
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Genetic influences on eight psychiatric disorders based on family data of 4 408 646 full and half-siblings, and genetic data of 333 748 cases and controls
- E. Pettersson, P. Lichtenstein, H. Larsson, J. Song, Attention Deficit/Hyperactivity Disorder Working Group of the iPSYCH-Broad-PGC Consortium, Autism Spectrum Disorder Working Group of the iPSYCH-Broad-PGC Consortium, Bipolar Disorder Working Group of the PGC, Eating Disorder Working Group of the PGC, Major Depressive Disorder Working Group of the PGC, Obsessive Compulsive Disorders and Tourette Syndrome Working Group of the PGC, Schizophrenia CLOZUK, Substance Use Disorder Working Group of the PGC, A. Agrawal, A. D. Børglum, C. M. Bulik, M. J. Daly, L. K. Davis, D. Demontis, H. J. Edenberg, J. Grove, J. Gelernter, B. M. Neale, A. F. Pardiñas, E. Stahl, J. T. R. Walters, R. Walters, P. F. Sullivan, D. Posthuma, T. J. C. Polderman
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- Journal:
- Psychological Medicine / Volume 49 / Issue 7 / May 2019
- Published online by Cambridge University Press:
- 17 September 2018, pp. 1166-1173
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Background
Most studies underline the contribution of heritable factors for psychiatric disorders. However, heritability estimates depend on the population under study, diagnostic instruments, and study designs that each has its inherent assumptions, strengths, and biases. We aim to test the homogeneity in heritability estimates between two powerful, and state of the art study designs for eight psychiatric disorders.
MethodsWe assessed heritability based on data of Swedish siblings (N = 4 408 646 full and maternal half-siblings), and based on summary data of eight samples with measured genotypes (N = 125 533 cases and 208 215 controls). All data were based on standard diagnostic criteria. Eight psychiatric disorders were studied: (1) alcohol dependence (AD), (2) anorexia nervosa, (3) attention deficit/hyperactivity disorder (ADHD), (4) autism spectrum disorder, (5) bipolar disorder, (6) major depressive disorder, (7) obsessive-compulsive disorder (OCD), and (8) schizophrenia.
ResultsHeritability estimates from sibling data varied from 0.30 for Major Depression to 0.80 for ADHD. The estimates based on the measured genotypes were lower, ranging from 0.10 for AD to 0.28 for OCD, but were significant, and correlated positively (0.19) with national sibling-based estimates. When removing OCD from the data the correlation increased to 0.50.
ConclusionsGiven the unique character of each study design, the convergent findings for these eight psychiatric conditions suggest that heritability estimates are robust across different methods. The findings also highlight large differences in genetic and environmental influences between psychiatric disorders, providing future directions for etiological psychiatric research.
Nomenclature for congenital and paediatric cardiac disease: the International Paediatric and Congenital Cardiac Code (IPCCC) and the Eleventh Iteration of the International Classification of Diseases (ICD-11)*
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- Rodney C. G. Franklin, Marie J. Béland, Steven D. Colan, Henry L. Walters III, Vera D. Aiello, Robert H. Anderson, Frédérique Bailliard, Jeffrey R. Boris, Meryl S. Cohen, J. William Gaynor, Kristine J. Guleserian, Lucile Houyel, Marshall L. Jacobs, Amy L. Juraszek, Otto N. Krogmann, Hiromi Kurosawa, Leo Lopez, Bohdan J. Maruszewski, James D. St. Louis, Stephen P. Seslar, Shubhika Srivastava, Giovanni Stellin, Christo I. Tchervenkov, Paul M. Weinberg, Jeffrey P. Jacobs
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- Journal:
- Cardiology in the Young / Volume 27 / Issue 10 / December 2017
- Published online by Cambridge University Press:
- 29 December 2017, pp. 1872-1938
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An internationally approved and globally used classification scheme for the diagnosis of CHD has long been sought. The International Paediatric and Congenital Cardiac Code (IPCCC), which was produced and has been maintained by the International Society for Nomenclature of Paediatric and Congenital Heart Disease (the International Nomenclature Society), is used widely, but has spawned many “short list” versions that differ in content depending on the user. Thus, efforts to have a uniform identification of patients with CHD using a single up-to-date and coordinated nomenclature system continue to be thwarted, even if a common nomenclature has been used as a basis for composing various “short lists”. In an attempt to solve this problem, the International Nomenclature Society has linked its efforts with those of the World Health Organization to obtain a globally accepted nomenclature tree for CHD within the 11th iteration of the International Classification of Diseases (ICD-11). The International Nomenclature Society has submitted a hierarchical nomenclature tree for CHD to the World Health Organization that is expected to serve increasingly as the “short list” for all communities interested in coding for congenital cardiology. This article reviews the history of the International Classification of Diseases and of the IPCCC, and outlines the process used in developing the ICD-11 congenital cardiac disease diagnostic list and the definitions for each term on the list. An overview of the content of the congenital heart anomaly section of the Foundation Component of ICD-11, published herein in its entirety, is also included. Future plans for the International Nomenclature Society include linking again with the World Health Organization to tackle procedural nomenclature as it relates to cardiac malformations. By doing so, the Society will continue its role in standardising nomenclature for CHD across the globe, thereby promoting research and better outcomes for fetuses, children, and adults with congenital heart anomalies.
Optical Parameters of Leaves of Seven Weed Species
- H. W. Gausman, R. M. Menges, A. J. Richardson, H. Walter, R. R. Rodriguez, S. Tamez
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- Weed Science / Volume 29 / Issue 1 / January 1981
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- 12 June 2017, pp. 24-26
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Absorption coefficient (k), infinite reflectance (Ri), and scattering coefficient (s) were tabulated for five wavelengths and analyzed for statistical differences for seven weed species. The wavelengths were: 0.55 μm, 0.65 μm, 0.85 μm, 1.65 μm, and 2.20 μm. The Ri of common lambsquarters (Chenopodium album L.), johnsongrass [Sorghum halepense (L.) Pers.], and annual sowthistle (Sonchus oleraceus L.) leaves at the 0.85-μm wavelength were significantly (p = 0.05) higher than for sunflower (Helianthus annuus L.), ragweed parthenium (Parthenium hysterophorus L.), or London rocket (Sisymbrium irio L.). Annual sowthistle had the largest k value, and Palmer amaranth (Amaranthus palmeri S. Wats.) had the smallest k value at the 0.65-μm chlorophyll absorption wavelength. In general, johnsongrass, ragweed parthenium, or London rocket had the largest s values among the five wavelengths, whereas annual sowthistle and Palmer amaranth were usually lowest.
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- By Mitchell Aboulafia, Frederick Adams, Marilyn McCord Adams, Robert M. Adams, Laird Addis, James W. Allard, David Allison, William P. Alston, Karl Ameriks, C. Anthony Anderson, David Leech Anderson, Lanier Anderson, Roger Ariew, David Armstrong, Denis G. Arnold, E. J. Ashworth, Margaret Atherton, Robin Attfield, Bruce Aune, Edward Wilson Averill, Jody Azzouni, Kent Bach, Andrew Bailey, Lynne Rudder Baker, Thomas R. Baldwin, Jon Barwise, George Bealer, William Bechtel, Lawrence C. Becker, Mark A. Bedau, Ernst Behler, José A. Benardete, Ermanno Bencivenga, Jan Berg, Michael Bergmann, Robert L. Bernasconi, Sven Bernecker, Bernard Berofsky, Rod Bertolet, Charles J. Beyer, Christian Beyer, Joseph Bien, Joseph Bien, Peg Birmingham, Ivan Boh, James Bohman, Daniel Bonevac, Laurence BonJour, William J. Bouwsma, Raymond D. Bradley, Myles Brand, Richard B. Brandt, Michael E. Bratman, Stephen E. Braude, Daniel Breazeale, Angela Breitenbach, Jason Bridges, David O. Brink, Gordon G. Brittan, Justin Broackes, Dan W. Brock, Aaron Bronfman, Jeffrey E. Brower, Bartosz Brozek, Anthony Brueckner, Jeffrey Bub, Lara Buchak, Otavio Bueno, Ann E. Bumpus, Robert W. Burch, John Burgess, Arthur W. Burks, Panayot Butchvarov, Robert E. Butts, Marina Bykova, Patrick Byrne, David Carr, Noël Carroll, Edward S. Casey, Victor Caston, Victor Caston, Albert Casullo, Robert L. Causey, Alan K. L. Chan, Ruth Chang, Deen K. Chatterjee, Andrew Chignell, Roderick M. Chisholm, Kelly J. Clark, E. J. Coffman, Robin Collins, Brian P. Copenhaver, John Corcoran, John Cottingham, Roger Crisp, Frederick J. Crosson, Antonio S. Cua, Phillip D. Cummins, Martin Curd, Adam Cureton, Andrew Cutrofello, Stephen Darwall, Paul Sheldon Davies, Wayne A. Davis, Timothy Joseph Day, Claudio de Almeida, Mario De Caro, Mario De Caro, John Deigh, C. F. Delaney, Daniel C. Dennett, Michael R. DePaul, Michael Detlefsen, Daniel Trent Devereux, Philip E. Devine, John M. Dillon, Martin C. Dillon, Robert DiSalle, Mary Domski, Alan Donagan, Paul Draper, Fred Dretske, Mircea Dumitru, Wilhelm Dupré, Gerald Dworkin, John Earman, Ellery Eells, Catherine Z. Elgin, Berent Enç, Ronald P. Endicott, Edward Erwin, John Etchemendy, C. Stephen Evans, Susan L. Feagin, Solomon Feferman, Richard Feldman, Arthur Fine, Maurice A. Finocchiaro, William FitzPatrick, Richard E. Flathman, Gvozden Flego, Richard Foley, Graeme Forbes, Rainer Forst, Malcolm R. Forster, Daniel Fouke, Patrick Francken, Samuel Freeman, Elizabeth Fricker, Miranda Fricker, Michael Friedman, Michael Fuerstein, Richard A. Fumerton, Alan Gabbey, Pieranna Garavaso, Daniel Garber, Jorge L. A. Garcia, Robert K. Garcia, Don Garrett, Philip Gasper, Gerald Gaus, Berys Gaut, Bernard Gert, Roger F. Gibson, Cody Gilmore, Carl Ginet, Alan H. Goldman, Alvin I. Goldman, Alfonso Gömez-Lobo, Lenn E. Goodman, Robert M. Gordon, Stefan Gosepath, Jorge J. E. Gracia, Daniel W. Graham, George A. Graham, Peter J. Graham, Richard E. Grandy, I. Grattan-Guinness, John Greco, Philip T. Grier, Nicholas Griffin, Nicholas Griffin, David A. Griffiths, Paul J. Griffiths, Stephen R. Grimm, Charles L. Griswold, Charles B. Guignon, Pete A. Y. Gunter, Dimitri Gutas, Gary Gutting, Paul Guyer, Kwame Gyekye, Oscar A. Haac, Raul Hakli, Raul Hakli, Michael Hallett, Edward C. Halper, Jean Hampton, R. James Hankinson, K. R. Hanley, Russell Hardin, Robert M. Harnish, William Harper, David Harrah, Kevin Hart, Ali Hasan, William Hasker, John Haugeland, Roger Hausheer, William Heald, Peter Heath, Richard Heck, John F. Heil, Vincent F. Hendricks, Stephen Hetherington, Francis Heylighen, Kathleen Marie Higgins, Risto Hilpinen, Harold T. Hodes, Joshua Hoffman, Alan Holland, Robert L. Holmes, Richard Holton, Brad W. Hooker, Terence E. Horgan, Tamara Horowitz, Paul Horwich, Vittorio Hösle, Paul Hoβfeld, Daniel Howard-Snyder, Frances Howard-Snyder, Anne Hudson, Deal W. Hudson, Carl A. Huffman, David L. Hull, Patricia Huntington, Thomas Hurka, Paul Hurley, Rosalind Hursthouse, Guillermo Hurtado, Ronald E. Hustwit, Sarah Hutton, Jonathan Jenkins Ichikawa, Harry A. Ide, David Ingram, Philip J. Ivanhoe, Alfred L. Ivry, Frank Jackson, Dale Jacquette, Joseph Jedwab, Richard Jeffrey, David Alan Johnson, Edward Johnson, Mark D. Jordan, Richard Joyce, Hwa Yol Jung, Robert Hillary Kane, Tomis Kapitan, Jacquelyn Ann K. Kegley, James A. Keller, Ralph Kennedy, Sergei Khoruzhii, Jaegwon Kim, Yersu Kim, Nathan L. King, Patricia Kitcher, Peter D. Klein, E. D. Klemke, Virginia Klenk, George L. Kline, Christian Klotz, Simo Knuuttila, Joseph J. Kockelmans, Konstantin Kolenda, Sebastian Tomasz Kołodziejczyk, Isaac Kramnick, Richard Kraut, Fred Kroon, Manfred Kuehn, Steven T. Kuhn, Henry E. Kyburg, John Lachs, Jennifer Lackey, Stephen E. Lahey, Andrea Lavazza, Thomas H. Leahey, Joo Heung Lee, Keith Lehrer, Dorothy Leland, Noah M. Lemos, Ernest LePore, Sarah-Jane Leslie, Isaac Levi, Andrew Levine, Alan E. Lewis, Daniel E. Little, Shu-hsien Liu, Shu-hsien Liu, Alan K. L. Chan, Brian Loar, Lawrence B. Lombard, John Longeway, Dominic McIver Lopes, Michael J. Loux, E. J. Lowe, Steven Luper, Eugene C. Luschei, William G. Lycan, David Lyons, David Macarthur, Danielle Macbeth, Scott MacDonald, Jacob L. Mackey, Louis H. Mackey, Penelope Mackie, Edward H. Madden, Penelope Maddy, G. B. Madison, Bernd Magnus, Pekka Mäkelä, Rudolf A. Makkreel, David Manley, William E. Mann (W.E.M.), Vladimir Marchenkov, Peter Markie, Jean-Pierre Marquis, Ausonio Marras, Mike W. Martin, A. P. Martinich, William L. McBride, David McCabe, Storrs McCall, Hugh J. McCann, Robert N. McCauley, John J. McDermott, Sarah McGrath, Ralph McInerny, Daniel J. McKaughan, Thomas McKay, Michael McKinsey, Brian P. McLaughlin, Ernan McMullin, Anthonie Meijers, Jack W. Meiland, William Jason Melanson, Alfred R. Mele, Joseph R. Mendola, Christopher Menzel, Michael J. Meyer, Christian B. Miller, David W. Miller, Peter Millican, Robert N. Minor, Phillip Mitsis, James A. Montmarquet, Michael S. Moore, Tim Moore, Benjamin Morison, Donald R. Morrison, Stephen J. Morse, Paul K. Moser, Alexander P. D. Mourelatos, Ian Mueller, James Bernard Murphy, Mark C. Murphy, Steven Nadler, Jan Narveson, Alan Nelson, Jerome Neu, Samuel Newlands, Kai Nielsen, Ilkka Niiniluoto, Carlos G. Noreña, Calvin G. Normore, David Fate Norton, Nikolaj Nottelmann, Donald Nute, David S. Oderberg, Steve Odin, Michael O’Rourke, Willard G. Oxtoby, Heinz Paetzold, George S. Pappas, Anthony J. Parel, Lydia Patton, R. P. Peerenboom, Francis Jeffry Pelletier, Adriaan T. Peperzak, Derk Pereboom, Jaroslav Peregrin, Glen Pettigrove, Philip Pettit, Edmund L. Pincoffs, Andrew Pinsent, Robert B. Pippin, Alvin Plantinga, Louis P. Pojman, Richard H. Popkin, John F. Post, Carl J. Posy, William J. Prior, Richard Purtill, Michael Quante, Philip L. Quinn, Philip L. Quinn, Elizabeth S. Radcliffe, Diana Raffman, Gerard Raulet, Stephen L. Read, Andrews Reath, Andrew Reisner, Nicholas Rescher, Henry S. Richardson, Robert C. Richardson, Thomas Ricketts, Wayne D. Riggs, Mark Roberts, Robert C. Roberts, Luke Robinson, Alexander Rosenberg, Gary Rosenkranz, Bernice Glatzer Rosenthal, Adina L. Roskies, William L. Rowe, T. M. Rudavsky, Michael Ruse, Bruce Russell, Lilly-Marlene Russow, Dan Ryder, R. M. Sainsbury, Joseph Salerno, Nathan Salmon, Wesley C. Salmon, Constantine Sandis, David H. Sanford, Marco Santambrogio, David Sapire, Ruth A. Saunders, Geoffrey Sayre-McCord, Charles Sayward, James P. Scanlan, Richard Schacht, Tamar Schapiro, Frederick F. Schmitt, Jerome B. Schneewind, Calvin O. Schrag, Alan D. Schrift, George F. Schumm, Jean-Loup Seban, David N. Sedley, Kenneth Seeskin, Krister Segerberg, Charlene Haddock Seigfried, Dennis M. Senchuk, James F. Sennett, William Lad Sessions, Stewart Shapiro, Tommie Shelby, Donald W. Sherburne, Christopher Shields, Roger A. Shiner, Sydney Shoemaker, Robert K. Shope, Kwong-loi Shun, Wilfried Sieg, A. John Simmons, Robert L. Simon, Marcus G. Singer, Georgette Sinkler, Walter Sinnott-Armstrong, Matti T. Sintonen, Lawrence Sklar, Brian Skyrms, Robert C. Sleigh, Michael Anthony Slote, Hans Sluga, Barry Smith, Michael Smith, Robin Smith, Robert Sokolowski, Robert C. Solomon, Marta Soniewicka, Philip Soper, Ernest Sosa, Nicholas Southwood, Paul Vincent Spade, T. L. S. Sprigge, Eric O. Springsted, George J. Stack, Rebecca Stangl, Jason Stanley, Florian Steinberger, Sören Stenlund, Christopher Stephens, James P. Sterba, Josef Stern, Matthias Steup, M. A. Stewart, Leopold Stubenberg, Edith Dudley Sulla, Frederick Suppe, Jere Paul Surber, David George Sussman, Sigrún Svavarsdóttir, Zeno G. Swijtink, Richard Swinburne, Charles C. Taliaferro, Robert B. Talisse, John Tasioulas, Paul Teller, Larry S. Temkin, Mark Textor, H. S. Thayer, Peter Thielke, Alan Thomas, Amie L. Thomasson, Katherine Thomson-Jones, Joshua C. Thurow, Vzalerie Tiberius, Terrence N. Tice, Paul Tidman, Mark C. Timmons, William Tolhurst, James E. Tomberlin, Rosemarie Tong, Lawrence Torcello, Kelly Trogdon, J. D. Trout, Robert E. Tully, Raimo Tuomela, John Turri, Martin M. Tweedale, Thomas Uebel, Jennifer Uleman, James Van Cleve, Harry van der Linden, Peter van Inwagen, Bryan W. Van Norden, René van Woudenberg, Donald Phillip Verene, Samantha Vice, Thomas Vinci, Donald Wayne Viney, Barbara Von Eckardt, Peter B. M. Vranas, Steven J. Wagner, William J. Wainwright, Paul E. Walker, Robert E. Wall, Craig Walton, Douglas Walton, Eric Watkins, Richard A. Watson, Michael V. Wedin, Rudolph H. Weingartner, Paul Weirich, Paul J. Weithman, Carl Wellman, Howard Wettstein, Samuel C. Wheeler, Stephen A. White, Jennifer Whiting, Edward R. Wierenga, Michael Williams, Fred Wilson, W. Kent Wilson, Kenneth P. Winkler, John F. Wippel, Jan Woleński, Allan B. Wolter, Nicholas P. Wolterstorff, Rega Wood, W. Jay Wood, Paul Woodruff, Alison Wylie, Gideon Yaffe, Takashi Yagisawa, Yutaka Yamamoto, Keith E. Yandell, Xiaomei Yang, Dean Zimmerman, Günter Zoller, Catherine Zuckert, Michael Zuckert, Jack A. Zupko (J.A.Z.)
- Edited by Robert Audi, University of Notre Dame, Indiana
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- The Cambridge Dictionary of Philosophy
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- 05 August 2015
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- 27 April 2015, pp ix-xxx
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- By Rony A. Adam, Gloria Bachmann, Nichole M. Barker, Randall B. Barnes, John Bennett, Inbar Ben-Shachar, Jonathan S. Berek, Sarah L. Berga, Monica W. Best, Eric J. Bieber, Frank M. Biro, Shan Biscette, Anita K. Blanchard, Candace Brown, Ronald T. Burkman, Joseph Buscema, John E. Buster, Michael Byas-Smith, Sandra Ann Carson, Judy C. Chang, Annie N. Y. Cheung, Mindy S. Christianson, Karishma Circelli, Daniel L. Clarke-Pearson, Larry J. Copeland, Bryan D. Cowan, Navneet Dhillon, Michael P. Diamond, Conception Diaz-Arrastia, Nicole M. Donnellan, Michael L. Eisenberg, Eric Eisenhauer, Sebastian Faro, J. Stuart Ferriss, Lisa C. Flowers, Susan J. Freeman, Leda Gattoc, Claudine Marie Gayle, Timothy M. Geiger, Jennifer S. Gell, Alan N. Gordon, Victoria L. Green, Jon K. Hathaway, Enrique Hernandez, S. Paige Hertweck, Randall S. Hines, Ira R. Horowitz, Fred M. Howard, William W. Hurd, Fidan Israfilbayli, Denise J. Jamieson, Carolyn R. Jaslow, Erika B. Johnston-MacAnanny, Rohna M. Kearney, Namita Khanna, Caroline C. King, Jeremy A. King, Ira J. Kodner, Tamara Kolev, Athena P. Kourtis, S. Robert Kovac, Ertug Kovanci, William H. Kutteh, Eduardo Lara-Torre, Pallavi Latthe, Herschel W. Lawson, Ronald L. Levine, Frank W. Ling, Larry I. Lipshultz, Steven D. McCarus, Robert McLellan, Shruti Malik, Suketu M. Mansuria, Mohamed K. Mehasseb, Pamela J. Murray, Saloney Nazeer, Farr R. Nezhat, Hextan Y. S. Ngan, Gina M. Northington, Peggy A. Norton, Ruth M. O'Regan, Kristiina Parviainen, Resad P. Pasic, Tanja Pejovic, K. Ulrich Petry, Nancy A. Phillips, Ashish Pradhan, Elizabeth E. Puscheck, Suneetha Rachaneni, Devon M. Ramaeker, David B. Redwine, Robert L. Reid, Carla P. Roberts, Walter Romano, Peter G. Rose, Robert L. Rosenfield, Shon P. Rowan, Mack T. Ruffin, Janice M. Rymer, Evis Sala, Ritu Salani, Joseph S. Sanfilippo, Mahmood I. Shafi, Roger P. Smith, Meredith L. Snook, Thomas E. Snyder, Mary D. Stephenson, Thomas G. Stovall, Richard L. Sweet, Philip M. Toozs-Hobson, Togas Tulandi, Elizabeth R. Unger, Denise S. Uyar, Marion S. Verp, Rahi Victory, Tamara J. Vokes, Michelle J. Washington, Katharine O'Connell White, Paul E. Wise, Frank M. Wittmaack, Miya P. Yamamoto, Christine Yu, Howard A. Zacur
- Edited by Eric J. Bieber, Joseph S. Sanfilippo, University of Pittsburgh, Ira R. Horowitz, Emory University, Atlanta, Mahmood I. Shafi
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- Clinical Gynecology
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- By Federica Agosta, Alberto Albanese, Timothy J. Amrhein, A. M. Barrett, Walter S. Bartynski, Felix Benninger, Thomas Brandt, Andrew G. Burke, Michelle Cameron, Elisa Canu, Louis R. Caplan, Christine M. Carr, Daniel J. A. Connolly, Firouz Daneshgari, John DeLuca, Marianne de Visser, Marianne Dieterich, Antonio E. Elia, Joseph H. Feinberg, Massimo Filippi, Lauren C. Frey, Gaëtan Garraux, Andrea Ginestroni, Peter J. Goadsby, Bronwyn E. Hamilton, Simon J. Hickman, Holly E. Hinson, Jon P. Jennings, Jan Kassubek, Horacio Kaufmann, David M. Kaylie, Joanna Kitley, Vladimir S. Kostic, C. T. Paul Krediet, Megan C. Leary, Farooq H. Maniyar, Ken R. Maravilla, Mario Mascalchi, Rajarshi Mazumder, Priyesh Mehta, Jacqueline A. Palace, Raj M. Paspulati, Christopher A. Potter, Angelo Quattrini, Louis P. Riccelli, Nilo Riva, Maria A. Rocca, Mirabelle B. Sajisevi, Richard Salazar-Montero, Nicholas D. Schiff, Jack H. Simon, Israel Steiner, Carl D. Stevens, Bart P. van de Warrenburg, Judith van Gaalen, William J. Weiner, Jane L. Weissman, Jay Yao, G. Bryan Young
- Edited by Massimo Filippi, Jack H. Simon
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- Imaging Acute Neurologic Disease
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- 05 October 2014
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- 11 September 2014, pp vi-viii
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- By Lenard A. Adler, Pinky Agarwal, Rehan Ahmed, Jagga Rao Alluri, Fawaz Al-Mufti, Samuel Alperin, Michael Amoashiy, Michael Andary, David J. Anschel, Padmaja Aradhya, Vandana Aspen, Esther Baldinger, Jee Bang, George D. Baquis, John J. Barry, Jason J. S. Barton, Julius Bazan, Amanda R. Bedford, Marlene Behrmann, Lourdes Bello-Espinosa, Ajay Berdia, Alan R. Berger, Mark Beyer, Don C. Bienfang, Kevin M. Biglan, Thomas M. Boes, Paul W. Brazis, Jonathan L. Brisman, Jeffrey A. Brown, Scott E. Brown, Ryan R. Byrne, Rina Caprarella, Casey A. Chamberlain, Wan-Tsu W. Chang, Grace M. Charles, Jasvinder Chawla, David Clark, Todd J. Cohen, Joe Colombo, Howard Crystal, Vladimir Dadashev, Sarita B. Dave, Jean Robert Desrouleaux, Richard L. Doty, Robert Duarte, Jeffrey S. Durmer, Christyn M. Edmundson, Eric R. Eggenberger, Steven Ender, Noam Epstein, Alberto J. Espay, Alan B. Ettinger, Niloofar (Nelly) Faghani, Amtul Farheen, Edward Firouztale, Rod Foroozan, Anne L. Foundas, David Elliot Friedman, Deborah I. Friedman, Steven J. Frucht, Oded Gerber, Tal Gilboa, Martin Gizzi, Teneille G. Gofton, Louis J. Goodrich, Malcolm H. Gottesman, Varda Gross-Tsur, Deepak Grover, David A. Gudis, John J. Halperin, Maxim D. Hammer, Andrew R. Harrison, L. Anne Hayman, Galen V. Henderson, Steven Herskovitz, Caitlin Hoffman, Laryssa A. Huryn, Andres M. Kanner, Gary P. Kaplan, Bashar Katirji, Kenneth R. Kaufman, Annie Killoran, Nina Kirz, Gad E. Klein, Danielle G. Koby, Christopher P. Kogut, W. Curt LaFrance, Patrick J.M. Lavin, Susan W. Law, James L. Levenson, Richard B. Lipton, Glenn Lopate, Daniel J. Luciano, Reema Maindiratta, Robert M. Mallery, Georgios Manousakis, Alan Mazurek, Luis J. Mejico, Dragana Micic, Ali Mokhtarzadeh, Walter J. Molofsky, Heather E. Moss, Mark L. Moster, Manpreet Multani, Siddhartha Nadkarni, George C. Newman, Rolla Nuoman, Paul A. Nyquist, Gaia Donata Oggioni, Odi Oguh, Denis Ostrovskiy, Kristina Y. Pao, Juwen Park, Anastas F. Pass, Victoria S. Pelak, Jeffrey Peterson, John Pile-Spellman, Misha L. Pless, Gregory M. Pontone, Aparna M. Prabhu, Michael T. Pulley, Philip Ragone, Prajwal Rajappa, Venkat Ramani, Sindhu Ramchandren, Ritesh A. Ramdhani, Ramses Ribot, Heidi D. Riney, Diana Rojas-Soto, Michael Ronthal, Daniel M. Rosenbaum, David B. Rosenfield, Durga Roy, Michael J. Ruckenstein, Max C. Rudansky, Eva Sahay, Friedhelm Sandbrink, Jade S. Schiffman, Angela Scicutella, Maroun T. Semaan, Robert C. Sergott, Aashit K. Shah, David M. Shaw, Amit M. Shelat, Claire A. Sheldon, Anant M. Shenoy, Yelizaveta Sher, Jessica A. Shields, Tanya Simuni, Rajpaul Singh, Eric E. Smouha, David Solomon, Mehri Songhorian, Steven A. Sparr, Egilius L. H. Spierings, Eve G. Spratt, Beth Stein, S.H. Subramony, Rosa Ana Tang, Cara Tannenbaum, Hakan Tekeli, Amanda J. Thompson, Michael J. Thorpy, Matthew J. Thurtell, Pedro J. Torrico, Ira M. Turner, Scott Uretsky, Ruth H. Walker, Deborah M. Weisbrot, Michael A. Williams, Jacques Winter, Randall J. Wright, Jay Elliot Yasen, Shicong Ye, G. Bryan Young, Huiying Yu, Ryan J. Zehnder
- Edited by Alan B. Ettinger, Albert Einstein College of Medicine, New York, Deborah M. Weisbrot, State University of New York, Stony Brook
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- Neurologic Differential Diagnosis
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