PET imaging using (18)Ffluorodeoxyglucose (FDG) and (11)CPittsburgh compound B (PIB) have been proposed as biomarkers of Alzheimer disease (AD), as have CSF measures of the 42 amino acid beta-amyloid ...protein (Abeta(1-42)) and total and phosphorylated tau (t-tau and p-tau). Relationships between biomarkers and with disease severity are incompletely understood.
Ten subjects with AD, 11 control subjects, and 34 subjects with mild cognitive impairment from the Alzheimer's Disease Neuroimaging Initiative underwent clinical evaluation; CSF measurement of Abeta(1-42), t-tau, and p-tau; and PIB-PET and FDG-PET scanning. Data were analyzed using continuous regression and dichotomous outcomes with subjects classified as "positive" or "negative" for AD based on cutoffs established in patients with AD and controls from other cohorts.
Dichotomous categorization showed substantial agreement between PIB-PET and CSF Abeta(1-42) measures (91% agreement, kappa = 0.74), modest agreement between PIB-PET and p-tau (76% agreement, kappa = 0.50), and minimal agreement for other comparisons (kappa <0.3). Mini-Mental State Examination score was significantly correlated with FDG-PET but not with PIB-PET or CSF Abeta(1-42). Regression models adjusted for diagnosis showed that PIB-PET was significantly correlated with Abeta(1-42), t-tau, and p-tau(181p), whereas FDG-PET was correlated only with Abeta(1-42).
PET and CSF biomarkers of Abeta agree with one another but are not related to cognitive impairment. (18)Ffluorodeoxyglucose-PET is modestly related to other biomarkers but is better related to cognition. Different biomarkers for Alzheimer disease provide different information from one another that is likely to be complementary.
Neuroimaging measures and chemical biomarkers may be important indices of clinical progression in normal aging and mild cognitive impairment (MCI) and need to be evaluated longitudinally.
To ...characterize cross-sectionally and longitudinally clinical measures in normal controls, subjects with MCI, and subjects with mild Alzheimer disease (AD) to enable the assessment of the utility of neuroimaging and chemical biomarker measures.
A total of 819 subjects (229 cognitively normal, 398 with MCI, and 192 with AD) were enrolled at baseline and followed for 12 months using standard cognitive and functional measures typical of clinical trials.
The subjects with MCI were more memory impaired than the cognitively normal subjects but not as impaired as the subjects with AD. Nonmemory cognitive measures were only minimally impaired in the subjects with MCI. The subjects with MCI progressed to dementia in 12 months at a rate of 16.5% per year. Approximately 50% of the subjects with MCI were on antidementia therapies. There was minimal movement on the Alzheimer's Disease Assessment Scale-Cognitive Subscale for the normal control subjects, slight movement for the subjects with MCI of 1.1, and a modest change for the subjects with AD of 4.3. Baseline CSF measures of Abeta-42 separated the 3 groups as expected and successfully predicted the 12-month change in cognitive measures.
The Alzheimer's Disease Neuroimaging Initiative has successfully recruited cohorts of cognitively normal subjects, subjects with mild cognitive impairment (MCI), and subjects with Alzheimer disease with anticipated baseline characteristics. The 12-month progression rate of MCI was as predicted, and the CSF measures heralded progression of clinical measures over 12 months.
The large-scale distribution of neutral hydrogen in the Universe will be luminous through its 21 cm emission. Here, for the first time, we use the auto-power spectrum of 21 cm intensity fluctuations ...to constrain neutral hydrogen fluctuations at z ∼ 0.8. Our data were acquired with the Green Bank Telescope and span the redshift range 0.6 < z < 1 over two fields totalling 41 deg2 and 190 h of radio integration time. The dominant synchrotron foregrounds exceed the signal by ∼103, but have fewer degrees of freedom and can be removed efficiently. Even in the presence of residual foregrounds, the auto-power can still be interpreted as an upper bound on the 21 cm signal. Our previous measurements of the cross-correlation of 21 cm intensity and the WiggleZ galaxy survey provide a lower bound. Through a Bayesian treatment of signal and foregrounds, we can combine both fields in auto- and cross-power into a measurement of ΩHI
bHI
= 0.62+0.23
−0.15 × 10−3 at 68 per cent confidence with 9 per cent systematic calibration uncertainty, where ΩHI
is the neutral hydrogen (H i) fraction and bHI
is the H i bias parameter. We describe observational challenges with the present data set and plans to overcome them.
AbstractObjectiveTo assess what proportions of studies reported increasing, stable, or declining trends in the incidence of diagnosed diabetes.DesignSystematic review of studies reporting trends of ...diabetes incidence in adults from 1980 to 2017 according to PRISMA guidelines.Data sourcesMedline, Embase, CINAHL, and reference lists of relevant publications.Eligibility criteriaStudies of open population based cohorts, diabetes registries, and administrative and health insurance databases on secular trends in the incidence of total diabetes or type 2 diabetes in adults were included. Poisson regression was used to model data by age group and year.ResultsAmong the 22 833 screened abstracts, 47 studies were included, providing data on 121 separate sex specific or ethnicity specific populations; 42 (89%) of the included studies reported on diagnosed diabetes. In 1960-89, 36% (8/22) of the populations studied had increasing trends in incidence of diabetes, 55% (12/22) had stable trends, and 9% (2/22) had decreasing trends. In 1990-2005, diabetes incidence increased in 66% (33/50) of populations, was stable in 32% (16/50), and decreased in 2% (1/50). In 2006-14, increasing trends were reported in only 33% (11/33) of populations, whereas 30% (10/33) and 36% (12/33) had stable or declining incidence, respectively.ConclusionsThe incidence of clinically diagnosed diabetes has continued to rise in only a minority of populations studied since 2006, with over a third of populations having a fall in incidence in this time period. Preventive strategies could have contributed to the fall in diabetes incidence in recent years. Data are limited in low and middle income countries, where trends in diabetes incidence could be different.Systematic review registrationProspero CRD42018092287.
A variety of measurements have been individually linked to decline in mild cognitive impairment (MCI), but the identification of optimal markers for predicting disease progression remains unresolved. ...The goal of this study was to evaluate the prognostic ability of genetic, CSF, neuroimaging, and cognitive measurements obtained in the same participants.
APOE epsilon4 allele frequency, CSF proteins (Abeta(1-42), total tau, hyperphosphorylated tau p-tau(181p)), glucose metabolism (FDG-PET), hippocampal volume, and episodic memory performance were evaluated at baseline in patients with amnestic MCI (n = 85), using data from a large multisite study (Alzheimer's Disease Neuroimaging Initiative). Patients were classified as normal or abnormal on each predictor variable based on externally derived cutoffs, and then variables were evaluated as predictors of subsequent conversion to Alzheimer disease (AD) and cognitive decline (Alzheimer's Disease Assessment Scale-Cognitive Subscale) during a variable follow-up period (1.9 +/- 0.4 years).
Patients with MCI converted to AD at an annual rate of 17.2%. Subjects with MCI who had abnormal results on both FDG-PET and episodic memory were 11.7 times more likely to convert to AD than subjects who had normal results on both measures (p <or= 0.02). In addition, the CSF ratio p-tau(181p)/Abeta(1-42) (beta = 1.10 +/- 0.53; p = 0.04) and, marginally, FDG-PET predicted cognitive decline.
Baseline FDG-PET and episodic memory predict conversion to AD, whereas p-tau(181p)/Abeta(1-42) and, marginally, FDG-PET predict longitudinal cognitive decline. Complementary information provided by these biomarkers may aid in future selection of patients for clinical trials or identification of patients likely to benefit from a therapeutic intervention.
Hippocampal volume change over time, measured with MRI, has huge potential as a marker for Alzheimer's disease. The objectives of this study were: (i) to test if constant and accelerated hippocampal ...loss can be detected in Alzheimer's disease, mild cognitive impairment and normal ageing over short periods, e.g. 6–12 months, with MRI in the large multicentre setting of the Alzheimer's Disease Neuroimaging Initiative (ADNI); (ii) to determine the extent to which the polymorphism of the apolipoprotein E (ApoE) gene modulates hippocampal change; and (iii) to determine if rates of hippocampal loss correlate with cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease, such as the β-amyloid (Aβ1–42) and tau proteins (tau). The MRI multicentre study included 112 cognitive normal elderly individuals, 226 mild cognitive impairment and 96 Alzheimer's disease patients who all had at least three successive MRI scans, involving 47 different imaging centres. The mild cognitive impairment and Alzheimer's disease groups showed hippocampal volume loss over 6 months and accelerated loss over 1 year. Moreover, increased rates of hippocampal loss were associated with presence of the ApoE allele ɛ4 gene in Alzheimer's disease and lower CSF Aβ1–42 in mild cognitive impairment, irrespective of ApoE genotype, whereas relations with tau were only trends. The power to measure hippocampal change was improved by exploiting correlations statistically between successive MRI observations. The demonstration of considerable hippocampal loss in mild cognitive impairment and Alzheimer's disease patients over only 6 months and accelerated loss over 12 months illustrates the power of MRI to track morphological brain changes over time in a large multisite setting. Furthermore, the relations between faster hippocampal loss in the presence of ApoE allele ɛ4 and decreased CSF Aβ1–42 supports the concept that increased hippocampal loss is an indicator of Alzheimer's disease pathology and a potential marker for the efficacy of therapeutic interventions in Alzheimer's disease.
Biomarkers of brain Aβ amyloid deposition can be measured either by cerebrospinal fluid Aβ42 or Pittsburgh compound B positron emission tomography imaging. Our objective was to evaluate the ability ...of Aβ load and neurodegenerative atrophy on magnetic resonance imaging to predict shorter time-to-progression from mild cognitive impairment to Alzheimer’s dementia and to characterize the effect of these biomarkers on the risk of progression as they become increasingly abnormal. A total of 218 subjects with mild cognitive impairment were identified from the Alzheimer’s Disease Neuroimaging Initiative. The primary outcome was time-to-progression to Alzheimer’s dementia. Hippocampal volumes were measured and adjusted for intracranial volume. We used a new method of pooling cerebrospinal fluid Aβ42 and Pittsburgh compound B positron emission tomography measures to produce equivalent measures of brain Aβ load from either source and analysed the results using multiple imputation methods. We performed our analyses in two phases. First, we grouped our subjects into those who were ‘amyloid positive’ (n = 165, with the assumption that Alzheimer's pathology is dominant in this group) and those who were ‘amyloid negative’ (n = 53). In the second phase, we included all 218 subjects with mild cognitive impairment to evaluate the biomarkers in a sample that we assumed to contain a full spectrum of expected pathologies. In a Kaplan–Meier analysis, amyloid positive subjects with mild cognitive impairment were much more likely to progress to dementia within 2 years than amyloid negative subjects with mild cognitive impairment (50 versus 19%). Among amyloid positive subjects with mild cognitive impairment only, hippocampal atrophy predicted shorter time-to-progression (P < 0.001) while Aβ load did not (P = 0.44). In contrast, when all 218 subjects with mild cognitive impairment were combined (amyloid positive and negative), hippocampal atrophy and Aβ load predicted shorter time-to-progression with comparable power (hazard ratio for an inter-quartile difference of 2.6 for both); however, the risk profile was linear throughout the range of hippocampal atrophy values but reached a ceiling at higher values of brain Aβ load. Our results are consistent with a model of Alzheimer’s disease in which Aβ deposition initiates the pathological cascade but is not the direct cause of cognitive impairment as evidenced by the fact that Aβ load severity is decoupled from risk of progression at high levels. In contrast, hippocampal atrophy indicates how far along the neurodegenerative path one is, and hence how close to progressing to dementia. Possible explanations for our finding that many subjects with mild cognitive impairment have intermediate levels of Aβ load include: (i) individual subjects may reach an Aβ load plateau at varying absolute levels; (ii) some subjects may be more biologically susceptible to Aβ than others; and (iii) subjects with mild cognitive impairment with intermediate levels of Aβ may represent individuals with Alzheimer’s disease co-existent with other pathologies.
Continuous estimates of the oceanic meridional heat transport in the Atlantic are derived from the Rapid Climate Change–Meridional Overturning Circulation (MOC) and Heatflux Array ...(RAPID–MOCHA)observing system deployed along 26.5°N, for the period from April 2004 to October 2007. The basinwide meridional heat transport (MHT) is derived by combining temperature transports (relative to a common reference) from 1) the Gulf Stream in the Straits of Florida; 2) the western boundary region offshore of Abaco, Bahamas; 3) the Ekman layer derived from Quick Scatterometer (QuikSCAT) wind stresses; and 4) the interior ocean monitored by “endpoint” dynamic height moorings. The interior eddy heat transport arising from spatial covariance of the velocity and temperature fields is estimated independently from repeat hydrographic and expendable bathythermograph (XBT) sections and can also be approximated by the array.
The results for the 3.5 yr of data thus far available show a mean MHT of 1.33 ± 0.40 PW for 10-day-averaged estimates, on which time scale a basinwide mass balance can be reasonably assumed. The associated MOC strength and variability is 18.5 ± 4.9 Sv (1 Sv ≡ 10⁶ m³ s−1). The continuous heat transport estimates range from a minimum of 0.2 to a maximum of 2.5 PW, with approximately half of the variance caused by Ekman transport changes and half caused by changes in the geostrophic circulation. The data suggest a seasonal cycle of the MHT with a maximum in summer (July–September) and minimum in late winter (March–April), with an annual range of 0.6 PW. A breakdown of the MHT into “overturning” and “gyre” components shows that the overturning component carries 88% of the total heat transport. The overall uncertainty of the annual mean MHT for the 3.5-yr record is 0.14 PW or about 10% of the mean value.
Unraveling the macroevolutionary history of bryophytes, which arose soon after the origin of land plants but exhibit substantially lower species richness than the more recently derived angiosperms, ...has been challenged by the scarce fossil record. Here we demonstrate that overall estimates of net species diversification are approximately half those reported in ferns and ∼30% those described for angiosperms. Nevertheless, statistical rate analyses on time-calibrated large-scale phylogenies reveal that mosses and liverworts underwent bursts of diversification since the mid-Mesozoic. The diversification rates further increase in specific lineages towards the Cenozoic to reach, in the most recently derived lineages, values that are comparable to those reported in angiosperms. This suggests that low diversification rates do not fully account for current patterns of bryophyte species richness, and we hypothesize that, as in gymnosperms, the low extant bryophyte species richness also results from massive extinctions.
Sedentary behaviour is a public health concern that requires surveillance and epidemiological research. For such large scale studies, self-report tools are a pragmatic measurement solution. A large ...number of self-report tools are currently in use, but few have been validated against an objective measure of sedentary time and there is no comparative information between tools to guide choice or to enable comparison between studies. The aim of this study was to provide a systematic comparison, generalisable to all tools, of the validity of self-report measures of sedentary time against a gold standard sedentary time objective monitor.
Cross sectional data from three cohorts (N = 700) were used in this validation study. Eighteen self-report measures of sedentary time, based on the TAxonomy of Self-report SB Tools (TASST) framework, were compared against an objective measure of postural sitting (activPAL) to provide information, generalizable to all existing tools, on agreement and precision using Bland-Altman statistics, on criterion validity using Pearson correlation, and on data loss.
All self-report measures showed poor accuracy compared with the objective measure of sedentary time, with very wide limits of agreement and poor precision (random error > 2.5 h). Most tools under-reported total sedentary time and demonstrated low correlations with objective data. The type of assessment used by the tool, whether direct, proxy, or a composite measure, influenced the measurement characteristics. Proxy measures (TV time) and single item direct measures using a visual analogue scale to assess the proportion of the day spent sitting, showed the best combination of precision and data loss. The recall period (e.g. previous week) had little influence on measurement characteristics.
Self-report measures of sedentary time result in large bias, poor precision and low correlation with an objective measure of sedentary time. Choice of tool depends on the research context, design and question. Choice can be guided by this systematic comparative validation and, in the case of population surveillance, it recommends to use a visual analog scale and a 7 day recall period. Comparison between studies and improving population estimates of average sedentary time, is possible with the comparative correction factors provided.
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