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Accurate and robust brain extraction is a critical step in most neuroimaging analysis pipelines. In particular, for the large-scale multi-site neuroimaging studies involving a significant number of subjects with diverse age and diagnostic groups, accurate and robust extraction of the brain automatically and consistently is highly desirable. In this paper, we introduce population-specific probability maps to guide the brain extraction of diverse subject groups, including both healthy and diseased adult human populations, both developing and aging human populations, as well as non-human primates. Specifically, the proposed method combines an atlas-based approach, for coarse skull-stripping, with a deformable-surface-based approach that is guided by local intensity information and population-specific prior information learned from a set of real brain images for more localized refinement. Comprehensive quantitative evaluations were performed on the diverse large-scale populations of ADNI dataset with over 800 subjects (55∼90 years of age, multi-site, various diagnosis groups), OASIS dataset with over 400 subjects (18∼96 years of age, wide age range, various diagnosis groups), and NIH pediatrics dataset with 150 subjects (5∼18 years of age, multi-site, wide age range as a complementary age group to the adult dataset). The results demonstrate that our method consistently yields the best overall results across almost the entire human life span, with only a single set of parameters. To demonstrate its capability to work on non-human primates, the proposed method is further evaluated using a rhesus macaque dataset with 20 subjects. Quantitative comparisons with popularly used state-of-the-art methods, including BET, Two-pass BET, BET-B, BSE, HWA, ROBEX and AFNI, demonstrate that the proposed method performs favorably with superior performance on all testing datasets, indicating its robustness and effectiveness. [ABSTRACT FROM AUTHOR]

Longitudinal brain image analysis is critical for revealing subtle but complex structural and functional changes of brain during aging or in neurodevelopmental disease. However, even with the rapid increase of clinical research and trials, a software toolbox dedicated for longitudinal image analysis is still lacking publicly. To cater for this increasing need, we have developed a dedicated 4D Adult Brain Extraction and Analysis Toolbox (aBEAT) to provide robust and accurate analysis of the longitudinal adult brain MR images. Specially, a group of image processing tools were integrated into aBEAT, including 4D brain extraction, 4D tissue segmentation, and 4D brain labeling. First, a 4D deformable-surface-based brain extraction algorithm, which can deform serial brain surfaces simultaneously under temporal smoothness constraint, was developed for consistent brain extraction. Second, a level-sets-based 4D tissue segmentation algorithm that incorporates local intensity distribution, spatial cortical-thickness constraint, and temporal cortical-thickness consistency was also included in aBEAT for consistent brain tissue segmentation. Third, a longitudinal groupwise image registration framework was further integrated into aBEAT for consistent ROI labeling by simultaneously warping a pre-labeled brain atlas to the longitudinal brain images. The performance of aBEAT has been extensively evaluated on a large number of longitudinal MR T1 images which include normal and dementia subjects, achieving very promising results. A Linux-based standalone package of aBEAT is now freely available at http://www.nitrc.org/projects/abeat. [ABSTRACT FROM AUTHOR]

Albumin fusion technology, the combination of small molecular proteins or peptides with human serum albumin (HSA), is an effective method for improving the medicinal values of natural small molecular proteins or peptides. However, comparative studies between HSA-fusion proteins or peptides and the parent small molecules in biological and molecular mechanisms are less reported. In this study, we examined the binding property of two novel somatostatin-HSA fusion proteins, (SST14)2-HSA and (SST28)2-HSA, to human SSTRs in stably expressing SSTR1-5 HEK 293 cells; observed the regulation of receptor internalization and internalized receptor recycling; and detected the receptors activation of HSA fusion proteins in stably expressing SSTR2- and SSTR3-EGFP cells. We showed that both somatostatin-HSA fusion proteins had high affinity to all five SSTRs, stimulated the ERK1/2 phosphorylation and persistently inhibited the accumulation of forskolin-stimulated cAMP in SSTR2- and SSTR3-expressing cells; but were less potent than the synthetic somatostatin-14 (SST-14). Our experiments also showed that somatostatin-HSA fusion proteins did not induce the receptors internalization; rather, they accelerated the recycling of the internalized receptors induced by SST-14 to the plasma membrane. Our results indicated that somatostatin-HSA fusion proteins, different from SST-14, exhibit some particular properties in binding, regulating, and activating somatostatin receptors. [ABSTRACT FROM AUTHOR]