2. |
- Limpens, J., et al.
(author)
-
Glasshouse vs field experiments : do they yield ecologically similar results for assessing N impacts on peat mosses?
- 2012
-
In: New Phytologist. - : Wiley. - 0028-646X .- 1469-8137. ; 195:2, s. 408-418
-
Journal article (peer-reviewed)abstract
- Peat bogs have accumulated more atmospheric carbon (C) than any other terrestrial ecosystem today. Most of this C is associated with peat moss (Sphagnum) litter. Atmospheric nitrogen (N) deposition can decrease Sphagnum production, compromising the C sequestration capacity of peat bogs. The mechanisms underlying the reduced production are uncertain, necessitating multifactorial experiments. We investigated whether glasshouse experiments are reliable proxies for field experiments for assessing interactions between N deposition and environment as controls on Sphagnum N concentration and production. We performed a meta-analysis over 115 glasshouse experiments and 107 field experiments. We found that glasshouse and field experiments gave similar qualitative and quantitative estimates of changes in Sphagnum N concentration in response to N application. However, glasshouse-based estimates of changes in production even qualitative assessments diverged from field experiments owing to a stronger N effect on production response in absence of vascular plants in the glasshouse, and a weaker N effect on production response in presence of vascular plants compared to field experiments. Thus, although we need glasshouse experiments to study how interacting environmental factors affect the response of Sphagnum to increased N deposition, we need field experiments to properly quantify these effects.
|
|
3. |
- Jansen, Willemijn J, et al.
(author)
-
Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum.
- 2022
-
In: JAMA neurology. - : American Medical Association (AMA). - 2168-6157 .- 2168-6149. ; 79:3, s. 228-243
-
Journal article (peer-reviewed)abstract
- One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design.To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates.This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria.Alzheimer disease biomarkers detected on PET or in CSF.Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations.Among the 19097 participants (mean [SD] age, 69.1 [9.8] years; 10148 women [53.1%]) included, 10139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P=.04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P=.004), subjective cognitive decline (9%; 95% CI, 3%-15%; P=.005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P=.004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P=.18).This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies.
|
|