icenReg: Regression Models for Interval Censored Data in R

The non-parametric maximum likelihood estimator and semi-parametric regression models are fundamental estimators for interval censored data, along with standard fullyparametric regression models. The R package icenReg is introduced which contains fast, reliable algorithms for fitting these models. In addition, the package contains functions for imputation of the censored response variables and diagnostics of both regression effects and baseline distribution

Physiological and Cognitive Factors Related to Human Performance During the Grand Canyon Rim-to-Rim Hike

Exposure to extreme environments is both mentally and physically taxing, leading to suboptimal performance and even life-threatening emergencies. Physiological and cognitive monitoring could provide the earliest indicator of performance decline and inform appropriate therapeutic intervention, yet little research has explored the relationship between these markers in strenuous settings. The Rim-to-Rim Wearables at the Canyon for Health (R2RWATCH) study is a research project at Sandia National Laboratories funded by the Defense Threat Reduction Agency to identify which physiological and cognitive phenomena collected by non-invasive wearable devices are the most related to performance in extreme environments. In a pilot study, data were collected from civilians and military warfighters hiking the Rim-to-Rim trail at the Grand Canyon. Each participant wore a set of devices collecting physiological, cognitive, and environmental data such as heart rate, memory, ambient temperature, etc. Promising preliminary results found correlates between physiological markers recorded by the wearable devices and decline in cognitive abilities, although further work is required to refine those measurements. Planned follow-up studies will validate these findings and further explore outstanding questions

A fibril-specific, conformation-dependent antibody recognizes a subset of Aβ plaques in Alzheimer disease, Down syndrome and Tg2576 transgenic mouse brain

Beta-amyloid (Aβ) is thought to be a key contributor to the pathogenesis of Alzheimer disease (AD) in the general population and in adults with Down syndrome (DS). Different assembly states of Aβ have been identified that may be neurotoxic. Aβ oligomers can assemble into soluble prefibrillar oligomers, soluble fibrillar oligomers and insoluble fibrils. Using a novel antibody, OC, recognizing fibrils and soluble fibrillar oligomers, we characterized fibrillar Aβ deposits in AD and DS cases. We further compared human specimens to those obtained from the Tg2576 mouse model of AD. Our results show that accumulation of fibrillar immunoreactivity is significantly increased in AD relative to nondemented aged subjects and those with select cognitive impairments (p < 0.0001). Further, there was a significant correlation between the extent of frontal cortex fibrillar deposit accumulation and dementia severity (MMSE r = −0.72). In DS, we observe an early age of onset and age-dependent accumulation of fibrillar OC immunoreactivity with little pathology in similarly aged non-DS individuals. Tg2576 mice show fibrillar accumulation that can be detected as young as 6 months. Interestingly, fibril-specific immunoreactivity was observed in diffuse, thioflavine S-negative Aβ deposits in addition to more mature neuritic plaques. These results suggest that fibrillar deposits are associated with disease in both AD and in adults with DS and their distribution within early Aβ pathology associated with diffuse plaques and correlation with MMSE suggest that these deposits may not be as benign as previously thought

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Quantitative 18F-AV1451 Brain Tau PET Imaging in Cognitively Normal Older Adults, Mild Cognitive Impairment, and Alzheimer's Disease Patients

Recent developments of tau Positron Emission Tomography (PET) allows assessment of regional neurofibrillary tangles (NFTs) deposition in human brain. Among the tau PET molecular probes, 18F-AV1451 is characterized by high selectivity for pathologic tau aggregates over amyloid plaques, limited non-specific binding in white and gray matter, and confined off-target binding. The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by 18F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and 18F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on 18F-AV1451 brain uptake.Methods: The study included total 115 participants (CN = 49, MCI = 58, and AD = 8) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed 18F-AV1451 PET images, structural MRIs, and demographic and clinical assessments were downloaded from the ADNI database. A reblurred Van Cittertiteration method was used for voxelwise partial volume correction (PVC) on PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. The parametric images of 18F-AV1451 SUVR relative to cerebellum were calculated. The ROI SUVR measurements from PVC and non-PVC SUVR images were compared. The correlation between ROI 18F-AV1451 SUVR and the measurements of MMSE, CSF total tau (t-tau), and phosphorylated tau (p-tau) were also assessed.Results:18F-AV1451 prominently specific binding was found in the amygdala, entorhinal cortex, parahippocampus, fusiform, posterior cingulate, temporal, parietal, and frontal brain regions. Most regional SUVRs showed significantly higher uptake of 18F-AV1451 in AD than MCI and CN participants. SUVRs of small regions like amygdala, entorhinal cortex and parahippocampus were statistically improved by PVC in all groups (p &lt; 0.01). Although there was an increasing tendency of 18F-AV-1451 SUVRs in MCI group compared with CN group, no significant difference of 18F-AV1451 deposition was found between CN and MCI brains with or without PVC (p &gt; 0.05). Declined MMSE score was observed with increasing 18F-AV1451 binding in amygdala, entorhinal cortex, parahippocampus, and fusiform. CSF p-tau was positively correlated with 18F-AV1451 deposition. PVC improved the results of 18F-AV-1451 tau deposition and correlation studies in small brain regions.Conclusion: The typical deposition of 18F-AV1451 tau PET imaging in AD brain was found in amygdala, entorhinal cortex, fusiform and parahippocampus, and these regions were strongly associated with cognitive impairment and CSF biomarkers. Although more deposition was observed in MCI group, the 18F-AV-1451 PET imaging could not differentiate the MCI patients from CN population. More tau deposition related to decreased MMSE score and increased level of CSF p-tau, especially in ROIs of amygdala, entorhinal cortex and parahippocampus. PVC did improve the results of tau deposition and correlation studies in small brain regions and suggest to be routinely used in 18F-AV1451 tau PET quantification

Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease