Colorectal surveillance outcomes from an institutional longitudinal cohort of lynch syndrome carriers.

Objective: Lynch Syndrome (LS) carriers have a significantly increased risk of developing colorectal cancer (CRC) during their lifetimes. Further stratification of this patient population may help in identifying additional risk factors that predispose to colorectal carcinogenesis. In most LS patients CRC may arise from adenomas, although an alternative non-polypoid carcinogenesis pathway has been proposed for carriers.

Future Exploration of the Outer Heliosphere and Very Local Interstellar Medium by Interstellar Probe.

A detailed overview of the knowledge gaps in our understanding of the heliospheric interaction with the largely unexplored Very Local Interstellar Medium (VLISM) are provided along with predictions of with the scientific discoveries that await. The new measurements required to make progress in this expanding frontier of space physics are discussed and include in-situ plasma and pick-up ion measurements throughout the heliosheath, direct sampling of the VLISM properties such as elemental and isotopic composition, densities, flows, and temperatures of neutral gas, dust and plasma, and remote energetic neutral atom (ENA) and Lyman-alpha (LYA) imaging from vantage points that can uniquely discern the heliospheric shape and bring new information on the interaction with interstellar hydrogen. The implementation of a pragmatic Interstellar Probe mission with a nominal design life to reach 375 Astronomical Units (au) with likely operation out to 550 au are reported as a result of a 4-year NASA funded mission study.

An integrative Bayesian approach to matrix-based analysis in neuroimaging.

Understanding the correlation structure associated with brain regions is a central goal in neuroscience, as it informs about interregional relationships and network organization. Correlation structure can be conveniently captured in a matrix that indicates the relationships among brain regions, which could involve electroencephalogram sensors, electrophysiology recordings, calcium imaging data, or functional magnetic resonance imaging (FMRI) data-We call this type of analysis matrix-based analysis, or MBA. Although different methods have been developed to summarize such matrices across subjects, including univariate general linear models (GLMs), the available modeling strategies tend to disregard the interrelationships among the regions, leading to "inefficient" statistical inference.

Publisher Correction: Flexible Learning-Free Segmentation and Reconstruction of Neural Volumes.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Flexible Learning-Free Segmentation and Reconstruction of Neural Volumes.

Imaging is a dominant strategy for data collection in neuroscience, yielding stacks of images that often scale to gigabytes of data for a single experiment. Machine learning algorithms from computer vision can serve as a pair of virtual eyes that tirelessly processes these images, automatically detecting and identifying microstructures. Unlike learning methods, our Flexible Learning-free Reconstruction of Imaged Neural volumes (FLoRIN) pipeline exploits structure-specific contextual clues and requires no training.