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Acker L, Wong MK, Wright MC, Reese M, Giattino CM, Roberts KC, Au S, Colon-Emeric C, Lipsitz LA, Devinney MJ, Browndyke J, Eleswarpu S, Moretti E, Whitson HE, Berger M, Woldorff MG. Preoperative electroencephalographic alpha-power changes with eyes opening are associated with postoperative attention impairment and inattention-related delirium severity. Br J Anaesth 2024; 132:154-163. [PMID: 38087743 PMCID: PMC10797508 DOI: 10.1016/j.bja.2023.10.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 10/11/2023] [Accepted: 10/13/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND In the eyes-closed, awake condition, EEG oscillatory power in the alpha band (7-13 Hz) dominates human spectral activity. With eyes open, however, EEG alpha power substantially decreases. Less alpha attenuation with eyes opening has been associated with inattention; thus, we analysed whether reduced preoperative alpha attenuation with eyes opening is associated with postoperative inattention, a delirium-defining feature. METHODS Preoperative awake 32-channel EEG was recorded with eyes open and eyes closed in 71 non-neurological, noncardiac surgery patients aged ≥ 60 years. Inattention and other delirium features were assessed before surgery and twice daily after surgery until discharge. Eyes-opening EEG alpha-attenuation magnitude was analysed for associations with postoperative inattention, primarily, and with delirium severity, secondarily, using multivariate age- and Mini-Mental Status Examination (MMSE)-adjusted logistic and proportional-odds regression analyses. RESULTS Preoperative alpha attenuation with eyes opening was inversely associated with postoperative inattention (odds ratio [OR] 0.73, 95% confidence interval [CI]: 0.57, 0.94; P=0.038). Sensitivity analyses showed an inverse relationship between alpha-attenuation magnitude and inattention chronicity, defined as 'never', 'newly', or 'chronically' inattentive (OR 0.76, 95% CI: 0.62, 0.93; P=0.019). In addition, preoperative alpha-attenuation magnitude was inversely associated with postoperative delirium severity (OR 0.79, 95% CI: 0.65, 0.95; P=0.040), predominantly as a result of the inattention feature. CONCLUSIONS Preoperative awake, resting, EEG alpha attenuation with eyes opening might represent a neural biomarker for risk of postoperative attentional impairment. Further, eyes-opening alpha attenuation could provide insight into the neural mechanisms underlying postoperative inattention risk.
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Affiliation(s)
- Leah Acker
- Department of Anaesthesiology, Duke University School of Medicine, Durham, NC, USA; Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC, USA; Duke-UNC Alzheimer's Disease Research Center, Durham, NC, USA.
| | - Megan K Wong
- Department of Anaesthesiology, Duke University School of Medicine, Durham, NC, USA
| | - Mary C Wright
- Department of Anaesthesiology, Duke University School of Medicine, Durham, NC, USA
| | - Melody Reese
- Department of Anaesthesiology, Duke University School of Medicine, Durham, NC, USA; Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, USA
| | | | | | - Sandra Au
- Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, USA
| | - Cathleen Colon-Emeric
- Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, USA; Duke-UNC Alzheimer's Disease Research Center, Durham, NC, USA; Division of Geriatric Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Lewis A Lipsitz
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Harvard Medical School, Boston, MA, USA; Division of Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Michael J Devinney
- Department of Anaesthesiology, Duke University School of Medicine, Durham, NC, USA
| | - Jeffrey Browndyke
- Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC, USA; Geriatrics Research Education and Clinical Center, Durham VA Medical Center, Durham, NC, USA
| | - Sarada Eleswarpu
- Department of Anaesthesiology, Duke University School of Medicine, Durham, NC, USA
| | - Eugene Moretti
- Department of Anaesthesiology, Duke University School of Medicine, Durham, NC, USA
| | - Heather E Whitson
- Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, USA; Duke-UNC Alzheimer's Disease Research Center, Durham, NC, USA; Division of Geriatric Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA; Geriatrics Research Education and Clinical Center, Durham VA Medical Center, Durham, NC, USA
| | - Miles Berger
- Department of Anaesthesiology, Duke University School of Medicine, Durham, NC, USA; Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC, USA; Duke-UNC Alzheimer's Disease Research Center, Durham, NC, USA
| | - Marty G Woldorff
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA; Division of Behavioural Medicine & Neurosciences, Department of Psychiatry & Behavioural Sciences, Duke University Medical Center, Durham, NC, USA; Department of Psychology & Neuroscience, Duke University, Durham, NC, USA
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Reese M, Christensen S, Anolick H, Roberts KC, Wong MK, Wright MC, Acker L, Browndyke JN, Woldorff MG, Berger M. EEG pre-burst suppression: characterization and inverse association with preoperative cognitive function in older adults. Front Aging Neurosci 2023; 15:1229081. [PMID: 37711992 PMCID: PMC10499509 DOI: 10.3389/fnagi.2023.1229081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 08/01/2023] [Indexed: 09/16/2023] Open
Abstract
The most common complication in older surgical patients is postoperative delirium (POD). POD is associated with preoperative cognitive impairment and longer durations of intraoperative burst suppression (BSup) - electroencephalography (EEG) with repeated periods of suppression (very low-voltage brain activity). However, BSup has modest sensitivity for predicting POD. We hypothesized that a brain state of lowered EEG power immediately precedes BSup, which we have termed "pre-burst suppression" (preBSup). Further, we hypothesized that even patients without BSup experience these preBSup transient reductions in EEG power, and that preBSup (like BSup) would be associated with preoperative cognitive function and delirium risk. Data included 83 32-channel intraoperative EEG recordings of the first hour of surgery from 2 prospective cohort studies of patients ≥age 60 scheduled for ≥2-h non-cardiac, non-neurologic surgery under general anesthesia (maintained with a potent inhaled anesthetic or a propofol infusion). Among patients with BSup, we defined preBSup as the difference in 3-35 Hz power (dB) during the 1-s preceding BSup relative to the average 3-35 Hz power of their intraoperative EEG recording. We then recorded the percentage of time that each patient spent in preBSup, including those without BSup. Next, we characterized the association between percentage of time in preBSup and (1) percentage of time in BSup, (2) preoperative cognitive function, and (3) POD incidence. The percentage of time in preBSup and BSup were correlated (Spearman's ρ [95% CI]: 0.52 [0.34, 0.66], p < 0.001). The percentage of time in BSup, preBSup, or their combination were each inversely associated with preoperative cognitive function (β [95% CI]: -0.10 [-0.19, -0.01], p = 0.024; -0.04 [-0.06, -0.01], p = 0.009; -0.04 [-0.06, -0.01], p = 0.003, respectively). Consistent with prior literature, BSup was significantly associated with POD (odds ratio [95% CI]: 1.34 [1.01, 1.78], p = 0.043), though this association did not hold for preBSup (odds ratio [95% CI]: 1.04 [0.95, 1.14], p = 0.421). While all patients had ≥1 preBSup instance, only 20.5% of patients had ≥1 BSup instance. These exploratory findings suggest that future studies are warranted to further study the extent to which preBSup, even in the absence of BSup, can identify patients with impaired preoperative cognition and/or POD risk.
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Affiliation(s)
- Melody Reese
- Department of Anesthesiology, School of Medicine, Duke University, Durham, NC, United States
- Center for the Study of Aging and Human Development, Duke University Medical Center, Durham, NC, United States
| | | | - Harel Anolick
- Pratt School of Engineering, Duke University, Durham, NC, United States
| | - Kenneth C. Roberts
- Center for Cognitive Neuroscience, Duke University, Durham, NC, United States
| | - Megan K. Wong
- School of Medicine, Duke University, Durham, NC, United States
| | - Mary Cooter Wright
- Department of Anesthesiology, School of Medicine, Duke University, Durham, NC, United States
| | - Leah Acker
- Department of Anesthesiology, School of Medicine, Duke University, Durham, NC, United States
| | | | - Marty G. Woldorff
- Center for Cognitive Neuroscience, Duke University, Durham, NC, United States
- Department of Psychiatry, Duke University, Durham, NC, United States
- Department of Psychology and Neuroscience, Duke University, Durham, NC, United States
| | - Miles Berger
- Department of Anesthesiology, School of Medicine, Duke University, Durham, NC, United States
- Center for the Study of Aging and Human Development, Duke University Medical Center, Durham, NC, United States
- Center for Cognitive Neuroscience, Duke University, Durham, NC, United States
- Alzheimer’s Disease Research Center, Duke University, Durham, NC, United States
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3
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Villalobos D, Reese M, Wright MC, Wong M, Syed A, Park J, Hall A, Browndyke JN, Martucci KT, Devinney MJ, Acker L, Moretti EW, Talbot L, Colin B, Ohlendorf B, Waligorska T, Shaw LM, Whitson HE, Cohen HJ, Mathew JP, Berger M. Perioperative changes in neurocognitive and Alzheimer's disease-related cerebrospinal fluid biomarker in older patients randomised to isoflurane or propofol for anaesthetic maintenance. Br J Anaesth 2023:S0007-0912(23)00194-0. [PMID: 37271721 PMCID: PMC10375507 DOI: 10.1016/j.bja.2023.04.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 04/04/2023] [Accepted: 04/05/2023] [Indexed: 06/06/2023] Open
Abstract
BACKGROUND Animal studies have shown that isoflurane and propofol have differential effects on Alzheimer's disease (AD) pathology and memory, although it is unclear whether this occurs in humans. METHODS This was a nested randomised controlled trial within a prospective cohort study; patients age ≥60 yr undergoing noncardiac/non-neurological surgery were randomised to isoflurane or propofol for anaesthetic maintenance. Cerebrospinal fluid (CSF) was collected via lumbar puncture before, 24 h, and 6 weeks after surgery. Cognitive testing was performed before and 6 weeks after surgery. Nonparametric methods and linear regression were used to evaluate CSF biomarkers and cognitive function, respectively. RESULTS There were 107 subjects (54 randomised to isoflurane and 53 to propofol) who completed the 6-week follow-up and were included in the analysis. There was no significant effect of anaesthetic treatment group, time, or group-by-time interaction for CSF amyloid-beta (Aβ), tau, or phospho-tau181p levels, or on the tau/Aβ or p-tau181p/Aβ ratios (all P>0.05 after Bonferroni correction). In multivariable-adjusted intention-to-treat analyses, there were no significant differences between the isoflurane and propofol groups in 6-week postoperative change in overall cognition (mean difference [95% confidence interval]: 0.01 [-0.12 to 0.13]; P=0.89) or individual cognitive domains (P>0.05 for each). Results remained consistent across as-treated and per-protocol analyses. CONCLUSIONS Intraoperative anaesthetic maintenance with isoflurane vs propofol had no significant effect on postoperative cognition or CSF Alzheimer's disease-related biomarkers within 6 weeks after noncardiac, non-neurological surgery in older adults. CLINICAL TRIAL REGISTRATION NCT01993836.
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Affiliation(s)
| | - Melody Reese
- Department of Anaesthesiology, Duke University Medical Centre, Durham, NC, USA; Center for the Study of Aging and Human Development, Duke University Medical Centre, Durham, NC, USA
| | - Mary Cooter Wright
- Department of Anaesthesiology, Duke University Medical Centre, Durham, NC, USA
| | - Megan Wong
- Duke University School of Medicine, Durham, NC, USA
| | - Ayesha Syed
- Department of Anaesthesiology, Duke University Medical Centre, Durham, NC, USA; Trinity College, Duke University, Durham, NC, USA
| | - John Park
- Duke University School of Medicine, Durham, NC, USA; Department of Anaesthesiology, Duke University Medical Centre, Durham, NC, USA
| | - Ashley Hall
- Department of Anaesthesiology, Duke University Medical Centre, Durham, NC, USA
| | - Jeffrey N Browndyke
- Department of Psychiatry and Behavioural Medicine, Division of Behavioral Medicine & Neurosciences, Duke University Medical Center, Durham, NC, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC, USA; Duke Brain Imaging and Analysis Center, Durham, NC, USA; Duke Institute for Brain Sciences, Durham, NC, USA
| | - Katherine T Martucci
- Department of Anaesthesiology, Duke University Medical Centre, Durham, NC, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC, USA; Duke Brain Imaging and Analysis Center, Durham, NC, USA; Duke Institute for Brain Sciences, Durham, NC, USA
| | - Michael J Devinney
- Department of Anaesthesiology, Duke University Medical Centre, Durham, NC, USA
| | - Leah Acker
- Department of Anaesthesiology, Duke University Medical Centre, Durham, NC, USA
| | - Eugene W Moretti
- Department of Anaesthesiology, Duke University Medical Centre, Durham, NC, USA
| | - Leonard Talbot
- Department of Anaesthesiology, Duke University Medical Centre, Durham, NC, USA
| | - Brian Colin
- Department of Anaesthesiology, Duke University Medical Centre, Durham, NC, USA
| | - Brian Ohlendorf
- Department of Anaesthesiology, Duke University Medical Centre, Durham, NC, USA
| | - Teresa Waligorska
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Heather E Whitson
- Center for the Study of Aging and Human Development, Duke University Medical Centre, Durham, NC, USA; Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | - Harvey J Cohen
- Center for the Study of Aging and Human Development, Duke University Medical Centre, Durham, NC, USA; Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | - Joseph P Mathew
- Department of Anaesthesiology, Duke University Medical Centre, Durham, NC, USA
| | - Miles Berger
- Duke University School of Medicine, Durham, NC, USA; Department of Anaesthesiology, Duke University Medical Centre, Durham, NC, USA; Center for the Study of Aging and Human Development, Duke University Medical Centre, Durham, NC, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC, USA; Duke Institute for Brain Sciences, Durham, NC, USA.
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4
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Vasunilashorn SM, Lunardi N, Newman JC, Crosby G, Acker L, Abel T, Bhatnagar S, Cunningham C, de Cabo R, Dugan L, Hippensteel JA, Ishizawa Y, Lahiri S, Marcantonio ER, Xie Z, Inouye SK, Terrando N, Eckenhoff RG. Preclinical and translational models for delirium: Recommendations for future research from the NIDUS delirium network. Alzheimers Dement 2023; 19:2150-2174. [PMID: 36799408 PMCID: PMC10576242 DOI: 10.1002/alz.12941] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 12/19/2022] [Accepted: 12/20/2022] [Indexed: 02/18/2023]
Abstract
Delirium is a common, morbid, and costly syndrome that is closely linked to Alzheimer's disease (AD) and AD-related dementias (ADRD) as a risk factor and outcome. Human studies of delirium have advanced our knowledge of delirium incidence and prevalence, risk factors, biomarkers, outcomes, prevention, and management. However, understanding of delirium neurobiology remains limited. Preclinical and translational models for delirium, while challenging to develop, could advance our knowledge of delirium neurobiology and inform the development of new prevention and treatment approaches. We discuss the use of preclinical and translational animal models in delirium, focusing on (1) a review of current animal models, (2) challenges and strategies for replicating elements of human delirium in animals, and (3) the utility of biofluid, neurophysiology, and neuroimaging translational markers in animals. We conclude with recommendations for the development and validation of preclinical and translational models for delirium, with the goal of advancing awareness in this important field.
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Affiliation(s)
- Sarinnapha M. Vasunilashorn
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Nadia Lunardi
- Department of Anesthesiology, University of Virginia, Charlottesville, Virginia, USA
| | - John C. Newman
- Department of Medicine, University of California, San Francisco, California, USA
- Buck Institute for Research on Aging, Novato, California, USA
| | - Gregory Crosby
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Anesthesiology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Leah Acker
- Department of Anesthesiology, Duke University, Durham, Massachusetts, USA
| | - Ted Abel
- Department of Neuroscience and Pharmacology, Carver College of Medicine, University of Iowa, Iowa City, Iowa, USA
| | - Seema Bhatnagar
- Department of Anesthesiology and Critical Care, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Colm Cunningham
- School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - Rafael de Cabo
- Translational Gerontology Branch, Intramural Research Program, National Institute on Aging, Baltimore, Maryland, USA
| | - Laura Dugan
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee, USA
- Division of Geriatric Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- VA Tennessee Valley Geriatric Research, Education, and Clinical Center (GRECC), Nashville, Tennessee, USA
| | - Joseph A. Hippensteel
- Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Yumiko Ishizawa
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Shouri Lahiri
- Department of Neurology, Neurosurgery, and Biomedical Sciences, Cedar-Sinai Medical Center, Los Angeles, California, USA
| | - Edward R. Marcantonio
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, Massachusetts, USA
| | - Zhongcong Xie
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Sharon K. Inouye
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, Massachusetts, USA
| | - Niccolò Terrando
- Department of Anesthesiology, Duke University, Durham, North Carolina, USA
- Department of Cell Biology, Duke University, Durham, North Carolina, USA
- Department of Immunology, Duke University, Durham, North Carolina, USA
- Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, USA
| | - Roderic G. Eckenhoff
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
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5
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David-Bercholz J, Acker L, Caceres AI, Wu PY, Goenka S, Franklin NO, Rodriguiz RM, Wetsel WC, Devinney M, Wright MC, Zetterberg H, Yang T, Berger M, Terrando N. Conserved YKL-40 changes in mice and humans after postoperative delirium. Brain Behav Immun Health 2022; 26:100555. [PMID: 36457825 PMCID: PMC9706140 DOI: 10.1016/j.bbih.2022.100555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 11/11/2022] [Indexed: 11/19/2022] Open
Abstract
Delirium is a common postoperative neurologic complication among older adults. Despite its prevalence (14%-50%) and likely association with inflammation, the exact mechanisms that underpin postoperative delirium are unclear. This project aimed to characterize systemic and central nervous system (CNS) inflammatory changes following surgery in mice and humans. Matched plasma and cerebrospinal fluid (CSF) samples from the "Investigating Neuroinflammation Underlying Postoperative Brain Connectivity Changes, Postoperative Cognitive Dysfunction, Delirium in Older Adults" (INTUIT; NCT03273335) study were compared to murine endpoints. Delirium-like behavior was evaluated in aged mice using the 5-Choice Serial Reaction Time Test (5-CSRTT). Using a well established orthopedic surgical model in the FosTRAP reporter mouse we detected neuronal changes in the prefrontal cortex, an area implicated in attention, but notably not in the hippocampus. In aged mice, plasma interleukin-6 (IL-6), chitinase-3-like protein 1 (YKL-40), and neurofilament light chain (NfL) levels increased after orthopedic surgery, but hippocampal YKL-40 expression was decreased. Given the growing evidence for a YKL-40 role in delirium and other neurodegenerative conditions, we assayed human plasma and CSF samples. Plasma YKL-40 levels were similarly increased after surgery, with a trend toward a greater postoperative plasma YKL-40 increase in patients with delirium. However, YKL-40 levels in CSF decreased following surgery, which paralleled the findings in the mouse brain. Finally, we confirmed changes in the blood-brain barrier (BBB) as early as 9 h after surgery in mice, which warrants more detailed and acute evaluations of BBB integrity following surgery in humans. Together, these results provide a nuanced understanding of neuroimmune interactions underlying postoperative delirium in mice and humans, and highlight translational biomarkers to test potential cellular targets and mechanisms.
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Key Words
- 4-OHT, 4-hydroxytamoxifen
- 5-CSRTT, 5-Choice Serial Reaction Time Test
- AD, Alzheimer’s disease
- Aging
- Attention
- BBB, blood-brain barrier
- Biomarkers
- CAM, Confusion AssessmentMethod
- CNS, central nervous system
- CSF, cerebrospinal fluid
- Delirium
- ELISA, enzyme-linked immunosorbent assay
- GFAP, glial fibrillary acidic protein
- IHC, immunohistochemistry
- IL-6, interleukin-6
- MMSE, mini-mental status exam
- NfL, neurofilament light chain
- PBS, phosphate-buffered saline
- PFA, paraformaldehyde
- PLC, prelimbic cortex
- ROI, regions of interest
- SIMOA, single molecule array
- Surgery
- TRAP, Targeted Recombination in Active Populations
- YKL-40
- YKL-40, chitinase-3-like protein 1
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Affiliation(s)
| | - Leah Acker
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, United States
| | - Ana I. Caceres
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, United States
| | - Pau Yen Wu
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, United States
| | - Saanvi Goenka
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, United States
| | - Nathan O. Franklin
- Department of Psychiatry and Behavioral Sciences, Mouse Behavioral and Neuroendocrine Analysis Core Facility, Duke University Medical Center, Durham, NC, United States
| | - Ramona M. Rodriguiz
- Department of Psychiatry and Behavioral Sciences, Mouse Behavioral and Neuroendocrine Analysis Core Facility, Duke University Medical Center, Durham, NC, United States
| | - William C. Wetsel
- Department of Psychiatry and Behavioral Sciences, Mouse Behavioral and Neuroendocrine Analysis Core Facility, Duke University Medical Center, Durham, NC, United States
- Department of Neurobiology, Duke University Medical Center, Durham, NC, United States
- Department of Cell Biology, Duke University Medical Center, Durham, NC, United States
| | - Michael Devinney
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, United States
| | - Mary Cooter Wright
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, United States
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Ting Yang
- Department of Medicine, Duke University Medical Center, Durham, NC, United States
| | - Miles Berger
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, United States
| | - Niccolò Terrando
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, United States
- Department of Cell Biology, Duke University Medical Center, Durham, NC, United States
- Department of Immunology, Duke University Medical Center, Durham, NC, United States
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6
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Berger M, Browndyke JN, Cooter Wright M, Nobuhara C, Reese M, Acker L, Bullock WM, Colin BJ, Devinney MJ, Moretti EW, Moul JW, Ohlendorf B, Laskowitz DT, Waligorska T, Shaw LM, Whitson HE, Cohen HJ, Mathew JP. Postoperative changes in cognition and cerebrospinal fluid neurodegenerative disease biomarkers. Ann Clin Transl Neurol 2022; 9:155-170. [PMID: 35104057 PMCID: PMC8862419 DOI: 10.1002/acn3.51499] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 12/21/2021] [Indexed: 12/21/2022] Open
Abstract
OBJECTIVE Numerous investigators have theorized that postoperative changes in Alzheimer's disease neuropathology may underlie postoperative neurocognitive disorders. Thus, we determined the relationship between postoperative changes in cognition and cerebrospinal (CSF) tau, p-tau-181p, or Aβ levels after non-cardiac, non-neurologic surgery in older adults. METHODS Participants underwent cognitive testing before and 6 weeks after surgery, and lumbar punctures before, 24 h after, and 6 weeks after surgery. Cognitive scores were combined via factor analysis into an overall cognitive index. In total, 110 patients returned for 6-week postoperative testing and were included in the analysis. RESULTS There was no significant change from before to 24 h or 6 weeks following surgery in CSF tau (median [median absolute deviation] change before to 24 h: 0.00 [4.36] pg/mL, p = 0.853; change before to 6 weeks: -1.21 [3.98] pg/mL, p = 0.827). There were also no significant changes in CSF p-tau-181p or Aβ over this period. There was no change in cognitive index (mean [95% CI] 0.040 [-0.018, 0.098], p = 0.175) from before to 6 weeks after surgery, although there were postoperative declines in verbal memory (-0.346 [-0.523, -0.170], p = 0.003) and improvements in executive function (0.394, [0.310, 0.479], p < 0.001). There were no significant correlations between preoperative to 6-week postoperative changes in cognition and CSF tau, p-tau-181p, or Aβ42 changes over this interval (p > 0.05 for each). INTERPRETATION Neurocognitive changes after non-cardiac, non-neurologic surgery in the majority of cognitively healthy, community-dwelling older adults are unlikely to be related to postoperative changes in AD neuropathology (as assessed by CSF Aβ, tau or p-tau-181p levels or the p-tau-181p/Aβ or tau/Aβ ratios). TRIAL REGISTRATION clinicaltrials.gov (NCT01993836).
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Affiliation(s)
- Miles Berger
- Department of AnesthesiologyDuke University Medical CenterDurhamNorth CarolinaUSA
- Center for the Study of Aging and Human DevelopmentDuke University Medical CenterDurhamNorth CarolinaUSA
- Center for Cognitive NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
| | - Jeffrey N. Browndyke
- Center for the Study of Aging and Human DevelopmentDuke University Medical CenterDurhamNorth CarolinaUSA
- Center for Cognitive NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
- Division of Geriatric Behavioral Health, Department of Psychiatry and Behavioral MedicineDuke University Medical CenterDurhamNorth CarolinaUSA
- Duke Brain Imaging and Analysis CenterDurhamNorth CarolinaUSA
| | - Mary Cooter Wright
- Department of AnesthesiologyDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Chloe Nobuhara
- Duke University School of MedicineDurhamNorth CarolinaUSA
| | - Melody Reese
- Department of AnesthesiologyDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Leah Acker
- Department of AnesthesiologyDuke University Medical CenterDurhamNorth CarolinaUSA
| | - W. Michael Bullock
- Department of AnesthesiologyDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Brian J. Colin
- Department of AnesthesiologyDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Michael J. Devinney
- Department of AnesthesiologyDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Eugene W. Moretti
- Department of AnesthesiologyDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Judd W. Moul
- Urology Division, Department of SurgeryDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Brian Ohlendorf
- Department of AnesthesiologyDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Daniel T. Laskowitz
- Department of AnesthesiologyDuke University Medical CenterDurhamNorth CarolinaUSA
- Department of NeurologyDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Teresa Waligorska
- Department of Pathology and Lab Medicine, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Leslie M. Shaw
- Department of Pathology and Lab Medicine, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Heather E. Whitson
- Center for the Study of Aging and Human DevelopmentDuke University Medical CenterDurhamNorth CarolinaUSA
- Department of MedicineDuke University Medical CenterDurhamNorth CarolinaUSA
- Geriatrics Research Education and Clinical Center (GRECC)Durham VA Medical CenterDurhamNCUSA
| | - Harvey J. Cohen
- Center for the Study of Aging and Human DevelopmentDuke University Medical CenterDurhamNorth CarolinaUSA
- Department of MedicineDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Joseph P. Mathew
- Department of AnesthesiologyDuke University Medical CenterDurhamNorth CarolinaUSA
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7
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Acker L, Ha C, Zhou J, Manor B, Giattino CM, Roberts K, Berger M, Wright MC, Colon-Emeric C, Devinney M, Au S, Woldorff MG, Lipsitz LA, Whitson HE. Electroencephalogram-Based Complexity Measures as Predictors of Post-operative Neurocognitive Dysfunction. Front Syst Neurosci 2021; 15:718769. [PMID: 34858144 PMCID: PMC8631543 DOI: 10.3389/fnsys.2021.718769] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 10/12/2021] [Indexed: 11/13/2022] Open
Abstract
Physiologic signals such as the electroencephalogram (EEG) demonstrate irregular behaviors due to the interaction of multiple control processes operating over different time scales. The complexity of this behavior can be quantified using multi-scale entropy (MSE). High physiologic complexity denotes health, and a loss of complexity can predict adverse outcomes. Since postoperative delirium is particularly hard to predict, we investigated whether the complexity of preoperative and intraoperative frontal EEG signals could predict postoperative delirium and its endophenotype, inattention. To calculate MSE, the sample entropy of EEG recordings was computed at different time scales, then plotted against scale; complexity is the total area under the curve. MSE of frontal EEG recordings was computed in 50 patients ≥ age 60 before and during surgery. Average MSE was higher intra-operatively than pre-operatively (p = 0.0003). However, intraoperative EEG MSE was lower than preoperative MSE at smaller scales, but higher at larger scales (interaction p < 0.001), creating a crossover point where, by definition, preoperative, and intraoperative MSE curves met. Overall, EEG complexity was not associated with delirium or attention. In 42/50 patients with single crossover points, the scale at which the intraoperative and preoperative entropy curves crossed showed an inverse relationship with delirium-severity score change (Spearman ρ = -0.31, p = 0.054). Thus, average EEG complexity increases intra-operatively in older adults, but is scale dependent. The scale at which preoperative and intraoperative complexity is equal (i.e., the crossover point) may predict delirium. Future studies should assess whether the crossover point represents changes in neural control mechanisms that predispose patients to postoperative delirium.
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Affiliation(s)
- Leah Acker
- Department of Anesthesiology, Duke University School of Medicine, Durham, NC, United States
- Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, United States
| | - Christine Ha
- Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, United States
| | - Junhong Zhou
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew Senior Life and Harvard Medical School, Boston, MA, United States
- Division of Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Brad Manor
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew Senior Life and Harvard Medical School, Boston, MA, United States
- Division of Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Charles M Giattino
- Center for Cognitive Neuroscience, Duke University, Durham, NC, United States
| | - Ken Roberts
- Center for Cognitive Neuroscience, Duke University, Durham, NC, United States
| | - Miles Berger
- Department of Anesthesiology, Duke University School of Medicine, Durham, NC, United States
- Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, United States
- Center for Cognitive Neuroscience, Duke University, Durham, NC, United States
| | - Mary Cooter Wright
- Department of Anesthesiology, Duke University School of Medicine, Durham, NC, United States
| | - Cathleen Colon-Emeric
- Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, United States
- Division of Geriatric Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, United States
| | - Michael Devinney
- Department of Anesthesiology, Duke University School of Medicine, Durham, NC, United States
| | - Sandra Au
- Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, United States
| | - Marty G Woldorff
- Center for Cognitive Neuroscience, Duke University, Durham, NC, United States
- Department of Psychiatry, Duke University, Durham, NC, United States
- Department of Psychology and Neuroscience, Duke University, Durham, NC, United States
| | - Lewis A Lipsitz
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew Senior Life and Harvard Medical School, Boston, MA, United States
- Division of Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Heather E Whitson
- Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, United States
- Division of Geriatric Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, United States
- Geriatrics Research Education and Clinical Center, Durham VA Medical Center, Durham, NC, United States
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8
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VanDusen KW, Li YJ, Cai V, Hall A, Hiles S, Thompson JW, Moseley MA, Cooter M, Acker L, Levy JH, Ghadimi K, Quiñones QJ, Devinney MJ, Chung S, Terrando N, Moretti EW, Browndyke JN, Mathew JP, Berger M. Cerebrospinal Fluid Proteome Changes in Older Non-Cardiac Surgical Patients with Postoperative Cognitive Dysfunction. J Alzheimers Dis 2021; 80:1281-1297. [PMID: 33682719 PMCID: PMC8052629 DOI: 10.3233/jad-201544] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Postoperative cognitive dysfunction (POCD), a syndrome of cognitive deficits occurring 1–12 months after surgery primarily in older patients, is associated with poor postoperative outcomes. POCD is hypothesized to result from neuroinflammation; however, the pathways involved remain unclear. Unbiased proteomic analyses have been used to identify neuroinflammatory pathways in multiple neurologic diseases and syndromes but have not yet been applied to POCD. Objective: To utilize unbiased mass spectrometry-based proteomics to identify potential neuroinflammatory pathways underlying POCD. Methods: Unbiased LC-MS/MS proteomics was performed on immunodepleted cerebrospinal fluid (CSF) samples obtained before, 24 hours after, and 6 weeks after major non-cardiac surgery in older adults who did (n = 8) or did not develop POCD (n = 6). Linear mixed models were used to select peptides and proteins with intensity differences for pathway analysis. Results: Mass spectrometry quantified 8,258 peptides from 1,222 proteins in > 50%of patient samples at all three time points. Twelve peptides from 11 proteins showed differences in expression over time between patients with versus without POCD (q < 0.05), including proteins previously implicated in neurodegenerative disease pathophysiology. Additionally, 283 peptides from 182 proteins were identified with trend-level differences (q < 0.25) in expression over time between these groups. Among these, pathway analysis revealed that 50 were from 17 proteins mapping to complement and coagulation pathways (q = 2.44*10–13). Conclusion: These data demonstrate the feasibility of performing unbiased mass spectrometry on perioperative CSF samples to identify pathways associated with POCD. Additionally, they provide hypothesis-generating evidence for CSF complement and coagulation pathway changes in patients with POCD.
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Affiliation(s)
- Keith W VanDusen
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
| | - Yi-Ju Li
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.,Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
| | - Victor Cai
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
| | - Ashley Hall
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
| | - Sarah Hiles
- Duke Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - J Will Thompson
- Duke Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - M Arthur Moseley
- Duke Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - Mary Cooter
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
| | - Leah Acker
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
| | - Jerrold H Levy
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
| | - Kamrouz Ghadimi
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
| | - Quintin J Quiñones
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
| | - Michael J Devinney
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
| | - Stacey Chung
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
| | - Niccolò Terrando
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
| | - Eugene W Moretti
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
| | - Jeffrey N Browndyke
- Department of Psychiatry & Behavioral Sciences, Division of Geriatric Behavioral Health, Duke University Medical Center, Durham, NC, USA.,Duke Institute for Brain Sciences, Duke University, Durham, NC, USA.,Center for Cognitive Neuroscience, Duke University Medical Center, Durham, NC, USA
| | - Joseph P Mathew
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
| | - Miles Berger
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA.,Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA.,Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA.,Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
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9
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Abstract
Flecainide is a first-line antiarrhythmic drug used to treat atrial arrhythmias and/or supraventricular tachycardia in those without coronary artery disease or structural heart disease. Even though it is an older antiarrhythmic, flecainide accounted for 1.6 million prescriptions in the United States in 2016, and its utilization is generally increasing. Despite its popularity, flecainide may predispose patients to rapid atrial flutter with resultant hemodynamic compromise, particularly in the physiologically stressful perioperative period. This article reviews the pharmacology of flecainide, describes problematic arrhythmias that may arise specifically during flecainide use, and offers recommendations for perioperative flecainide management.
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Affiliation(s)
- Leah Acker
- From the Department of Anesthesiology, Duke University School of Medicine, Duke University Medical Center, Durham, North Carolina
| | | | - Colleen Naglee
- From the Department of Anesthesiology, Duke University School of Medicine, Duke University Medical Center, Durham, North Carolina
- Department of Neurology, Duke University School of Medicine, Duke University Medical Center, Durham, North Carolina
| | - Brad Taicher
- From the Department of Anesthesiology, Duke University School of Medicine, Duke University Medical Center, Durham, North Carolina
| | - Yuriy S Bronshteyn
- From the Department of Anesthesiology, Duke University School of Medicine, Duke University Medical Center, Durham, North Carolina
- Durham VA Medical Center, Durham, North Carolina
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10
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Tremblay S, Acker L, Afraz A, Albaugh DL, Amita H, Andrei AR, Angelucci A, Aschner A, Balan PF, Basso MA, Benvenuti G, Bohlen MO, Caiola MJ, Calcedo R, Cavanaugh J, Chen Y, Chen S, Chernov MM, Clark AM, Dai J, Debes SR, Deisseroth K, Desimone R, Dragoi V, Egger SW, Eldridge MAG, El-Nahal HG, Fabbrini F, Federer F, Fetsch CR, Fortuna MG, Friedman RM, Fujii N, Gail A, Galvan A, Ghosh S, Gieselmann MA, Gulli RA, Hikosaka O, Hosseini EA, Hu X, Hüer J, Inoue KI, Janz R, Jazayeri M, Jiang R, Ju N, Kar K, Klein C, Kohn A, Komatsu M, Maeda K, Martinez-Trujillo JC, Matsumoto M, Maunsell JHR, Mendoza-Halliday D, Monosov IE, Muers RS, Nurminen L, Ortiz-Rios M, O'Shea DJ, Palfi S, Petkov CI, Pojoga S, Rajalingham R, Ramakrishnan C, Remington ED, Revsine C, Roe AW, Sabes PN, Saunders RC, Scherberger H, Schmid MC, Schultz W, Seidemann E, Senova YS, Shadlen MN, Sheinberg DL, Siu C, Smith Y, Solomon SS, Sommer MA, Spudich JL, Stauffer WR, Takada M, Tang S, Thiele A, Treue S, Vanduffel W, Vogels R, Whitmire MP, Wichmann T, Wurtz RH, Xu H, Yazdan-Shahmorad A, Shenoy KV, DiCarlo JJ, Platt ML. An Open Resource for Non-human Primate Optogenetics. Neuron 2020; 108:1075-1090.e6. [PMID: 33080229 PMCID: PMC7962465 DOI: 10.1016/j.neuron.2020.09.027] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 07/28/2020] [Accepted: 09/21/2020] [Indexed: 12/26/2022]
Abstract
Optogenetics has revolutionized neuroscience in small laboratory animals, but its effect on animal models more closely related to humans, such as non-human primates (NHPs), has been mixed. To make evidence-based decisions in primate optogenetics, the scientific community would benefit from a centralized database listing all attempts, successful and unsuccessful, of using optogenetics in the primate brain. We contacted members of the community to ask for their contributions to an open science initiative. As of this writing, 45 laboratories around the world contributed more than 1,000 injection experiments, including precise details regarding their methods and outcomes. Of those entries, more than half had not been published. The resource is free for everyone to consult and contribute to on the Open Science Framework website. Here we review some of the insights from this initial release of the database and discuss methodological considerations to improve the success of optogenetic experiments in NHPs.
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Affiliation(s)
- Sébastien Tremblay
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Leah Acker
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Arash Afraz
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Daniel L Albaugh
- Yerkes National Primate Research Center, Morris K. Udall Center of Excellence for Parkinson's Disease, Department of Neurology, Emory University, GA 30329, USA
| | - Hidetoshi Amita
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Ariana R Andrei
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas-Houston, Houston, TX 77030, USA
| | - Alessandra Angelucci
- Department of Ophthalmology, Moran Eye Institute, University of Utah, Salt Lake City, UT 84132, USA
| | - Amir Aschner
- Dominik P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Puiu F Balan
- Laboratory of Neuro- and Psychophysiology, KU Leuven, 3000 Leuven, Belgium
| | - Michele A Basso
- Departments of Psychiatry and Biobehavioral Sciences and Neurobiology, UCLA, Los Angeles, CA 90095, USA
| | - Giacomo Benvenuti
- Departments of Psychology and Neuroscience, Center for Perceptual Systems, University of Texas, Austin, TX 78712, USA
| | - Martin O Bohlen
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Michael J Caiola
- Yerkes National Primate Research Center, Morris K. Udall Center of Excellence for Parkinson's Disease, Department of Neurology, Emory University, GA 30329, USA
| | - Roberto Calcedo
- Gene Therapy Program, Department of Medicine, University of Pennsylvania, Philadelphia, PA 19014, USA
| | - James Cavanaugh
- Laboratory of Sensorimotor Research, National Eye Institute, NIH, Bethesda, MD 20982, USA
| | - Yuzhi Chen
- Departments of Psychology and Neuroscience, Center for Perceptual Systems, University of Texas, Austin, TX 78712, USA
| | - Spencer Chen
- Departments of Psychology and Neuroscience, Center for Perceptual Systems, University of Texas, Austin, TX 78712, USA
| | - Mykyta M Chernov
- Division of Neuroscience, Oregon National Primate Resource Center, Oregon Health and Science University, Beaverton, OR 97006, USA
| | - Andrew M Clark
- Department of Ophthalmology, Moran Eye Institute, University of Utah, Salt Lake City, UT 84132, USA
| | - Ji Dai
- CAS Key Laboratory of Brain Connectome and Manipulation, The Brain Cognition and Brain Disease Institute, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen 518055, China
| | - Samantha R Debes
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas-Houston, Houston, TX 77030, USA
| | - Karl Deisseroth
- Neuroscience Program, Departments of Bioengineering, Psychiatry, and Behavioral Science, Wu Tsai Neurosciences Institute, Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Robert Desimone
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Valentin Dragoi
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas-Houston, Houston, TX 77030, USA
| | - Seth W Egger
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Mark A G Eldridge
- Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20892, USA
| | - Hala G El-Nahal
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Francesco Fabbrini
- Laboratory of Neuro- and Psychophysiology, KU Leuven, 3000 Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000 Leuven, Belgium
| | - Frederick Federer
- Department of Ophthalmology, Moran Eye Institute, University of Utah, Salt Lake City, UT 84132, USA
| | - Christopher R Fetsch
- The Solomon H. Snyder Department of Neuroscience & Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Michal G Fortuna
- German Primate Center - Leibniz Institute for Primate Research, 37077 Göttingen, Germany
| | - Robert M Friedman
- Division of Neuroscience, Oregon National Primate Resource Center, Oregon Health and Science University, Beaverton, OR 97006, USA
| | - Naotaka Fujii
- Laboratory for Adaptive Intelligence, RIKEN Brain Science Institute, Wako, Saitama 351-0198, Japan
| | - Alexander Gail
- German Primate Center - Leibniz Institute for Primate Research, 37077 Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany; Faculty for Biology and Psychology, University of Göttingen, Göttingen, Germany; Leibniz Science Campus Primate Cognition, Göttingen, Germany
| | - Adriana Galvan
- Yerkes National Primate Research Center, Morris K. Udall Center of Excellence for Parkinson's Disease, Department of Neurology, Emory University, GA 30329, USA
| | - Supriya Ghosh
- Department of Neurobiology and Grossman Institute for Neuroscience, Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL 60637, USA
| | - Marc Alwin Gieselmann
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle NE2 4HH, UK
| | - Roberto A Gulli
- Zuckerman Institute, Columbia University, New York, NY 10027, USA; Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, USA
| | - Okihide Hikosaka
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Eghbal A Hosseini
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Xing Hu
- Yerkes National Primate Research Center, Morris K. Udall Center of Excellence for Parkinson's Disease, Department of Neurology, Emory University, GA 30329, USA
| | - Janina Hüer
- German Primate Center - Leibniz Institute for Primate Research, 37077 Göttingen, Germany
| | - Ken-Ichi Inoue
- Systems Neuroscience Section, Primate Research Institute, Kyoto University, Inuyama, Aichi 484-8506, Japan; PRESTO, Japan Science and Technology Agency, Kawaguchi, Saitama 332-0012, Japan
| | - Roger Janz
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas-Houston, Houston, TX 77030, USA
| | - Mehrdad Jazayeri
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Rundong Jiang
- School of Life Sciences, Peking University, Beijing 100871, China
| | - Niansheng Ju
- School of Life Sciences, Peking University, Beijing 100871, China
| | - Kohitij Kar
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Carsten Klein
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Adam Kohn
- Dominik P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461, USA; Department of Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, NY 10461, USA; Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Misako Komatsu
- Laboratory for Adaptive Intelligence, RIKEN Brain Science Institute, Wako, Saitama 351-0198, Japan
| | - Kazutaka Maeda
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Julio C Martinez-Trujillo
- Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada; Brain and Mind Institute, University of Western Ontario, London, ON, Canada
| | - Masayuki Matsumoto
- Division of Biomedical Science, Faculty of Medicine, University of Tsukuba, Tsukuba, Ibaraki 305-8575, Japan; Transborder Medical Research Center, University of Tsukuba, Tsukuba, Ibaraki 305-8577, Japan
| | - John H R Maunsell
- Department of Neurobiology and Grossman Institute for Neuroscience, Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL 60637, USA
| | - Diego Mendoza-Halliday
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ilya E Monosov
- Department of Neuroscience, Biomedical Engineering, Electrical Engineering, Neurosurgery and Pain Center, Washington University, St. Louis, MO 63110, USA
| | - Ross S Muers
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle NE2 4HH, UK
| | - Lauri Nurminen
- Department of Ophthalmology, Moran Eye Institute, University of Utah, Salt Lake City, UT 84132, USA
| | - Michael Ortiz-Rios
- German Primate Center - Leibniz Institute for Primate Research, 37077 Göttingen, Germany; Leibniz Science Campus Primate Cognition, Göttingen, Germany; Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle NE2 4HH, UK
| | - Daniel J O'Shea
- Department of Electrical Engineering, Wu Tsai Neurosciences Institute, and Bio-X Institute, and Neuroscience Graduate Program, Stanford University, Stanford, CA 94305, USA
| | - Stéphane Palfi
- Department of Neurosurgery, Assistance Publique-Hopitaux de Paris (APHP), U955 INSERM IMRB eq.15, University of Paris 12 UPEC, Faculté de Médecine, Créteil 94010, France
| | - Christopher I Petkov
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle NE2 4HH, UK
| | - Sorin Pojoga
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas-Houston, Houston, TX 77030, USA
| | - Rishi Rajalingham
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Charu Ramakrishnan
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Evan D Remington
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Cambria Revsine
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA 19104, USA; Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20814, USA
| | - Anna W Roe
- Division of Neuroscience, Oregon National Primate Resource Center, Oregon Health and Science University, Beaverton, OR 97006, USA; Interdisciplinary Institute of Neuroscience and Technology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310029, China; Key Laboratory of Biomedical Engineering of the Ministry of Education, Zhejiang University, Hangzhou 310029, China
| | - Philip N Sabes
- Center for Integrative Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Richard C Saunders
- Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20892, USA
| | - Hansjörg Scherberger
- German Primate Center - Leibniz Institute for Primate Research, 37077 Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany; Faculty for Biology and Psychology, University of Göttingen, Göttingen, Germany; Leibniz Science Campus Primate Cognition, Göttingen, Germany
| | - Michael C Schmid
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle NE2 4HH, UK; Department of Neurosciences and Movement Sciences, Faculty of Science and Medicine, University of Fribourg, 1700 Fribourg, Switzerland
| | - Wolfram Schultz
- Department of Physiology, Development of Neuroscience, University of Cambridge, Cambridge CB3 0LT, UK
| | - Eyal Seidemann
- Departments of Psychology and Neuroscience, Center for Perceptual Systems, University of Texas, Austin, TX 78712, USA
| | - Yann-Suhan Senova
- Department of Neurosurgery, Assistance Publique-Hopitaux de Paris (APHP), U955 INSERM IMRB eq.15, University of Paris 12 UPEC, Faculté de Médecine, Créteil 94010, France
| | - Michael N Shadlen
- Department of Neuroscience, Mortimer B. Zuckerman Mind Brain Behavior Institute, The Kavli Institute for Brain Science & Howard Hughes Medical Institute, Columbia University, NY 10027, USA
| | - David L Sheinberg
- Department of Neuroscience and Carney Institute for Brain Science, Brown University, Providence, RI 02912, USA
| | - Caitlin Siu
- Department of Ophthalmology, Moran Eye Institute, University of Utah, Salt Lake City, UT 84132, USA
| | - Yoland Smith
- Yerkes National Primate Research Center, Morris K. Udall Center of Excellence for Parkinson's Disease, Department of Neurology, Emory University, GA 30329, USA
| | - Selina S Solomon
- Dominik P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Marc A Sommer
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - John L Spudich
- Department of Biochemistry and Molecular Biology, McGovern Medical School, The University of Texas-Houston, Houston, TX 77030, USA
| | - William R Stauffer
- Systems Neuroscience Institute, Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Masahiko Takada
- Systems Neuroscience Section, Primate Research Institute, Kyoto University, Inuyama, Aichi 484-8506, Japan
| | - Shiming Tang
- School of Life Sciences, Peking University, Beijing 100871, China
| | - Alexander Thiele
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle NE2 4HH, UK
| | - Stefan Treue
- German Primate Center - Leibniz Institute for Primate Research, 37077 Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany; Faculty for Biology and Psychology, University of Göttingen, Göttingen, Germany; Leibniz Science Campus Primate Cognition, Göttingen, Germany
| | - Wim Vanduffel
- Laboratory of Neuro- and Psychophysiology, KU Leuven, 3000 Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000 Leuven, Belgium; MGH Martinos Center, Charlestown, MA 02129, USA; Harvard Medical School, Boston, MA 02144, USA
| | - Rufin Vogels
- Laboratory of Neuro- and Psychophysiology, KU Leuven, 3000 Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000 Leuven, Belgium
| | - Matthew P Whitmire
- Departments of Psychology and Neuroscience, Center for Perceptual Systems, University of Texas, Austin, TX 78712, USA
| | - Thomas Wichmann
- Yerkes National Primate Research Center, Morris K. Udall Center of Excellence for Parkinson's Disease, Department of Neurology, Emory University, GA 30329, USA
| | - Robert H Wurtz
- Laboratory of Sensorimotor Research, National Eye Institute, NIH, Bethesda, MD 20982, USA
| | - Haoran Xu
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Azadeh Yazdan-Shahmorad
- Center for Integrative Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA; Departments of Bioengineering and Electrical and Computer Engineering, Washington National Primate Research Center, University of Washington, Seattle, WA 98105, USA
| | - Krishna V Shenoy
- Departments of Electrical Engineering, Bioengineering, and Neurobiology, Wu Tsai Neurosciences Institute and Bio-X Institute, Neuroscience Graduate Program, and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - James J DiCarlo
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Michael L Platt
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Marketing, Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA
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11
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Vasunilashorn SM, Devinney MJ, Acker L, Jung Y, Ngo L, Cooter M, Huang R, Marcantonio ER, Berger M. A New Severity Scoring Scale for the 3-Minute Confusion Assessment Method (3D-CAM). J Am Geriatr Soc 2020; 68:1874-1876. [PMID: 32479640 DOI: 10.1111/jgs.16538] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 04/23/2020] [Indexed: 12/17/2022]
Affiliation(s)
- Sarinnapha M Vasunilashorn
- Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Michael J Devinney
- Department of Anesthesiology, Duke University Medical Center, Durham, North Carolina
| | - Leah Acker
- Department of Anesthesiology, Duke University Medical Center, Durham, North Carolina
| | - Yoojin Jung
- Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Long Ngo
- Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts.,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Mary Cooter
- Department of Anesthesiology, Duke University Medical Center, Durham, North Carolina
| | - Richard Huang
- Department of Anesthesiology, Duke University Medical Center, Durham, North Carolina
| | - Edward R Marcantonio
- Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts.,Division of Gerontology, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Miles Berger
- Department of Anesthesiology, Duke University Medical Center, Durham, North Carolina
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12
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Galvan A, Stauffer WR, Acker L, El-Shamayleh Y, Inoue KI, Ohayon S, Schmid MC. Nonhuman Primate Optogenetics: Recent Advances and Future Directions. J Neurosci 2017; 37:10894-10903. [PMID: 29118219 PMCID: PMC5678022 DOI: 10.1523/jneurosci.1839-17.2017] [Citation(s) in RCA: 79] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2017] [Revised: 09/29/2017] [Accepted: 10/02/2017] [Indexed: 12/19/2022] Open
Abstract
Optogenetics is the use of genetically coded, light-gated ion channels or pumps (opsins) for millisecond resolution control of neural activity. By targeting opsin expression to specific cell types and neuronal pathways, optogenetics can expand our understanding of the neural basis of normal and pathological behavior. To maximize the potential of optogenetics to study human cognition and behavior, optogenetics should be applied to the study of nonhuman primates (NHPs). The homology between NHPs and humans makes these animals the best experimental model for understanding human brain function and dysfunction. Moreover, for genetic tools to have translational promise, their use must be demonstrated effectively in large, wild-type animals such as Rhesus macaques. Here, we review recent advances in primate optogenetics. We highlight the technical hurdles that have been cleared, challenges that remain, and summarize how optogenetic experiments are expanding our understanding of primate brain function.
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Affiliation(s)
- Adriana Galvan
- Yerkes National Primate Research Center and Department of Neurology, School of Medicine, Emory University, Atlanta, Georgia 30329,
| | - William R Stauffer
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
| | - Leah Acker
- Department of Anesthesiology, Duke University Medical Center, Durham, North Carolina 27710
| | - Yasmine El-Shamayleh
- Department of Physiology and Biophysics, Washington National Primate Research Center, University of Washington, Seattle, Washington 98195
| | - Ken-Ichi Inoue
- Department of Neuroscience, Primate Research Institute, Kyoto University, Inuyama, Aichi 484-8506, Japan
- PRESTO, Japan Science and Technology Agency, Kawaguchi, Saitama 332-0012, Japan
| | - Shay Ohayon
- McGovern Institute for Brain Research, Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, and
| | - Michael C Schmid
- Institute of Neuroscience, Newcastle University, Newcastle, United Kingdom NE2 4HH
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13
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Dykhuizen M, Mitchen JL, Montefiori DC, Thomson J, Acker L, Lardy H, Pauza CD. Determinants of disease in the simian immunodeficiency virus-infected rhesus macaque: characterizing animals with low antibody responses and rapid progression. J Gen Virol 1998; 79 ( Pt 10):2461-7. [PMID: 9780052 DOI: 10.1099/0022-1317-79-10-2461] [Citation(s) in RCA: 57] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Clinical and laboratory markers of simian immunodeficiency virus (SIV) infection were studied during the first 3 months after intravenous inoculation of rhesus macaques. Virus-binding serum antibody titres were correlated strongly with disease progression (P < 0.005) and were predictive of disease outcome by 7 weeks after inoculation. Low virus-binding serum antibody responses to SIV occurred in animals that also showed acute depletion of circulating CD20+ B cells. Acute damage to the CD4+ T cell and CD20+ B cell populations rendered some animals incapable of mounting virus-specific antibody responses and these macaques became the rapidly progressing cases comprising approximately 20-30% of infected animal cohorts.
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Affiliation(s)
- M Dykhuizen
- Wisconsin Regional Primate Research Center, University of Wisconsin, Madison 53715, USA
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14
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Sharma P, He D, Marcus F, Bosnos M, Taylor J, Acker L. The use of bio-battery cell output to predict lesion formation and prevent rapid impedance rise. J Am Coll Cardiol 1998. [DOI: 10.1016/s0735-1097(98)81335-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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15
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Maier HG, Klostermeyer H, Marx F, Lenz H, Siewek F, Thier HP, Kleinau HJ, Kyrein HJ, Burow H, Honikel KO, Kielwein G, Buchberger J, Lechner E, Miller M, Reinefeld E, Frommberger R, Frommberger R, Rohrdanz A, Radler F, Belitz HD, M�rkl H, Wildbrett G, Lechner E, Beliltz HD, Ptz M, Marx F, Acker L, Lechner E, Jung J, Guthy K, Feldheim W, Burow H, Sch�fers FI, W�danger W, Wildbrett G, Pfeilsticker K, Kiermeier F. Book reviews. Eur Food Res Technol 1986. [DOI: 10.1007/bf01142547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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16
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Abstract
A survey on the situation concerning the residues on pesticides in human milk in West Germany is given, based on own investigations. Nearly the whole pattern of chlororganic pesticides - DDT with its metabolites DDE and DDD, hexachlorobenzene (HCB), the different isomeres (alpha-, beta-, gamma-) of benzenehexachloride (BHC) as well as dieldrin and heptachloroepoxid - together with polychlorinated biphenyls (PCB) coming from the environment - were found in all samples of human milk, though in different concentrations. PCB, HCB and beta-BHC had been discovered in human milk only about ten years ago. The residues have decreased in the past years. The concentrations are still so high that the amounts consumed by the suckling exceed the ADI values for the contaminants in question. But in the opinion of the experts the advantages connected with the alimentation with human milk weigh more than the eventual risk by the contamination.
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17
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M�ller G, Dominik J, Reuther R, Malisch R, Schulte E, Acker L, Irion G. Sedimentary record of environmental pollution in the Western Baltic Sea. Naturwissenschaften 1980. [DOI: 10.1007/bf00396539] [Citation(s) in RCA: 44] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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18
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Schulte E, Acker L. [Capillary gas chromatographic separation of residues of chlorohydrocarbons in foods and identification of Mirex in human fat tissue]. Nahrung 1980; 24:577-83. [PMID: 7421984 DOI: 10.1002/food.19800240614] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
The residue analysis of organochloroinsecticides could be substantially improved by using glass capillary columns. The special advantages of the capillary gas chromatography (separation of complex mixtures, simultaneous determination of by-components, improved reliability at the identification, increased sensitivity) can be used with right handling to directly separate the whole mixture of chlorohydrocarbons that are to be met in foods (insecticides, HCB and PCB). The identification is possible even of microgram amounts per kg substance by a direct coupling of GC and MS working without carrier gas separator. In this way the occurrence of Mirex in samples of human fat tissues could be demonstrated.
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19
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Weder J, Piening C, Buchberger J, Pardun H, Kessler HG, Nonnweiler W, B�tticher W, B�rwald G, Hausding D, Kohn RM, Putzien J, Nonnweiler W, Thier HP, Lechner E, Acker L, Kiermeier F, Sterzel W, Bortmes E, Wildbrett G, Buchberger J. Buchbesprechungen. Eur Food Res Technol 1978. [DOI: 10.1007/bf01127659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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20
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Potthast K, Acker L, Hamm R. [Influence of water activity on the enzymatic changes in freeze-dehydrated muscle III. The breakdown of muscle lipids (author's transl)]. Z Lebensm Unters Forsch 1977; 165:15-7. [PMID: 919790 DOI: 10.1007/bf01461045] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
During storage of freeze-dehydrated bovine muscle triglycerides and cholesterolesters are slowly hydrolyzed even at 25% relative humidity (r.h.). The extent of lipid hydrolysis in the tissue increases with rising water activity, the final degree of hydrolysis being dependent on water activity. It has been demonstrated that these changes are due to the effect of muscle enzymes. Phospholipids are not hydrolyzed even at 65% r.h. This might be due to an association of the phospholipids with membranes or to a lack of phospholipase activity in the freeze-dehydrated tissue. The fact that lipids in muscle tissue are hydrolyzed at water activities at which water soluble substrates are not split by hydrolyses agrees well with general ideas about the influence of water activity on the enzymatic breakdown of lipids. Freeze-dehydrated beef should not contain more than 3% moisture in order to prevent undesirable flavour changes caused by lipid changes during storage.
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21
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Potthast K, Hamm R, Acker L. [Influence of water activity on the enzymatic changes in freeze-dehydrated muscle. IV. Change in the activity of glycolytic enzymes during storage (author's transl)]. Z Lebensm Unters Forsch 1977; 165:18-20. [PMID: 144376 DOI: 10.1007/bf01461046] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The influence of water activity (25-65% r.h.) on the changes in activity of glycolytic enzymes during storage (up to 120 days) of freeze-dehydrated bovine muscle was investigated. For this purpose, at different times of storage the decrease of glycogen and the increase in lactate in the rehydrated samples were determined. At 25% r.h. no loss in activity was observed. However, during storage at 40% r.h. and higher the glycolytic activity decreased; this effect increased with rising water activity. The denaturation of the enzyme proteins might be due to Maillard reactions, particularly to the reaction of proteins with the highly reactive glycolytic metabolites glyceraldehyde phosphate and dihydroxyacetone phosphate.
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Potthast K, Hamm R, Acker L. [Influence of water activity on the enzymatic changes in freeze-dehydrated muscle. II. Reactions of carbohydrates (author's transl)]. Z Lebensm Unters Forsch 1976; 162:139-48. [PMID: 983345 DOI: 10.1007/bf01274256] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
During storage of prerigor freeze-dried beef, glycogen is not broken down even at 97.5% r.h. (moisture content of the meat about 30%). However, the metabolites of glycogen -- glucose, fructose, and their phosphoric acid esters -- are changed during storage at r.h. greater than 25%, mainly by the effect of glycolytic enzymes. Also nonenzymic reactions of the Maillard type seem to occur. An accelerated breakdown of these carbohydrates with increasing water activity was found. Even though the sugar monophosphates are broken down, no increase in C3 metabolites was found. The reason for this could be that the energy-rich compounds glyceraldehyde phosphate and dihydroxyacetone phosphate form complexes with some proteins. It is suggested that also pyruvate reacts with free amino groups of proteins. The breakdown of carbohydrates increases in uncooked freeze-dried samples above 60% r.h. whereas nonenzymatic reactions of the Maillard type reach a maximum rate at nonenzymatic reactions of the Maillard type reach a maximum rate at 60% r.h. This also shows that the disappearance of carbohydrates during storage of freeze-dried prerigor beef is mainly due to enzymatic processes.
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24
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Acker L, Belitz HD, Vogt K, M�hler K, Gerhardt U, Herrmann K, Schulte E, Seher A, Bay� AW, Baumgart J, Wei� G, Schwerdtfeger E, B�tticher W, Radler F, Rehm HJ, Czaja AT, Nierle W, Nagy M, Eichelsd�rfer D, Feldheim W, Ke�ler HG, Bosch H, Nolte D, Terplan G, Renner E, Kiermeier F, Precht M. Buchbesprechungen. Eur Food Res Technol 1976. [DOI: 10.1007/bf01252670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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25
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Abstract
Phospholipase D (phosphatidylcholine-phosphatidohydrolase, EC 3.1.4.4) hydrolyses lecithin into phosphatidic acid and choline. A review is given on the properties of phospholipase D described in the literature; it deals with the occurrence and distribution of phospholipase D in higher plants, with it's pH and temperature, substrate specifity, activators, inhibitors and with occurrence and properties of bacterial phospholipase D.
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26
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Clauss B, Acker L. [Contamination of milk and milk products with chlorinated hydrocarbons in the Westphalian area. II. Results and discussion]. Z Lebensm Unters Forsch 1975; 159:129-37. [PMID: 1229721 DOI: 10.1007/bf01141862] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
During the time of August 1972 til end of January 1974 samples of butter from 20 dairies from the westfalian area were investigated with regard to their content of chlorinated hydrocarbons. In all samples of milk and butter could be proved: HCB, alpha-, beta-, and gamma-BHC, Heptachlorepoxid (HE), DDT, DDE, DDD, Dieldrin and PCB's, not however, Aldrin, Heptachlor and o,p'-DDT. With HCB, alpha- and gamma-BHC a dependance on the season was observed with maximum values during the winter months. With DDT, DDE and HE the variations were less. With PCB's dependencies on the season or influences of the location were not be recognised. The structure of farming seems to have a significant influence on the contents of HCB. In the course of butter processing the content on chlorinated hydrocarbons related to milk fat is not changed, metabolization does not play a role, either. With the start of lactation the concentration of chlorinated hydrocarbons especially of PCB's are increased as could be shown with single samples.
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27
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Clauss B, Acker L. [On the contamination of milk and milk products with chlorinated hydrocarbons. I. Methods]. Z Lebensm Unters Forsch 1975; 159:79-84. [PMID: 1243868 DOI: 10.1007/bf01135781] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
A method of gaschromatographic determination of chlorinated insecticides in milk and butter in the presence of PCB's is described. The fatty components were extracted from milk after adding sodium oxalate and ethanol with diethyl ether and petrol ether. The clean up of the extracts was carried out according to a modification of the method of Hadorn and Zürcher with propylene carbonate as a selective solvent.
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Abstract
Phospholipase D containing water insoluble fraction was isolated from mature barley; the enzym preparation only had weak phospholipase B activity. The phospholipase D of barley was activated by Ca2+, diethyl ether and sodium dodecyl sulphate (SDS); EDTA inhibited the enzyme to an extent of 10% of the original activity. Diethyl ether and SDS showed and additive effect. Phospholipase D activated by CaC12, diethyl ether and SDS exhibited a sharp optimum at pH 6.6. Lysophosphatidylcholine was hydrolysed much slower than phosphatidylcholine. Diethyl ether and SDS also increased the breakdown of the lysophosphatidylcholine.
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29
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31
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Schulte E, Acker L. Gas-Chromatographie mit Glascapillaren bei Temperaturen bis zu 320�C und ihre Anwendung zur Trennung von Polychlorbiphenylen. ACTA ACUST UNITED AC 1974. [DOI: 10.1007/bf00431299] [Citation(s) in RCA: 44] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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32
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Acker L, Kiermeier F, Fritz A, Reinefeld E, Millies K, Schwerdtfeger E, B�tticher W, Gerstmann E, Thier HP, Wissebach H, K�bler W, Possmann P, Hauck G, Latzko E. Buchbesprechungen. Eur Food Res Technol 1974. [DOI: 10.1007/bf01122892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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33
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Acker L, Kiermeier F, Renner E, Pardun H, Kittner PW, Kiermeier F. Buchbesprechungen. Eur Food Res Technol 1973. [DOI: 10.1007/bf01146559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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34
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35
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36
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37
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Acker L, Becker G. Neuere Untersuchungen über die Lipide der Getreidestärken. Teil II. Die Lipide verschiedener Stärkearten und ihre Bindung an die Amylose. STARCH-STARKE 1971. [DOI: 10.1002/star.19710231202] [Citation(s) in RCA: 51] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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38
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Acker L, Schulte E. [The occurrence of chlorinated biphenyls and hexachlorobenzene along with chlorinated insecticides in human milk and human adipose tissue]. Naturwissenschaften 1970; 57:497. [PMID: 4098200 DOI: 10.1007/bf00593085] [Citation(s) in RCA: 84] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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39
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Acker L, Feldheim W, Dultz G, M�hler K, Winkler S, B�tticher W. Die einzelnen Lebensmittel. Eur Food Res Technol 1970. [DOI: 10.1007/bf01454574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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40
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41
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42
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Nernst C, Lindner AF, Möhler K, Terplan G, Zaadhof KJ, Karg H, Rauch W, Hampel G, Acker L, Hohlfeld W, Baumgart J, Drawert F, Kuchinke E, Lindemann BRFR, v. Ammon, Bucksteeg W, Quentin KE. Die einzelnen Lebensmittel (Chemie, Technologie, Analytik). Eur Food Res Technol 1968. [DOI: 10.1007/bf01884775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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43
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Wildfeuer I, Acker L, Mehner A, Rauch W. Über die Beeinflussung der Dotterfarbe von Hühnereiern durch Zusätze von Carotinoiden zum Futter. ACTA ACUST UNITED AC 1968. [DOI: 10.1007/bf01676986] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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44
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Wildfeuer I, Acker L, Mehner A, Rauch W. �ber die Beeinflussung der Dotterfarbe von H�hnereiern durch Zus�tze von Carotinoiden zum Futter. ACTA ACUST UNITED AC 1968. [DOI: 10.1007/bf01459194] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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45
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46
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Wildfeuer I, Acker L. Über die Beeinflussung der Dotterfarbe von Hühnereiern durch Zusätze von Carotinoiden zum Futter. ACTA ACUST UNITED AC 1967. [DOI: 10.1007/bf02340879] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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47
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48
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Acker L, Schmitz HJ. Über die Lipide der Weizenstärke. III. Mitt. Die übrigen Lipide der Weizenstärke sowie die Lipide anderer Stärkearten. STARCH-STARKE 1967. [DOI: 10.1002/star.19670190901] [Citation(s) in RCA: 46] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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49
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50
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