Development and Validation of a Natural Language Processing Tool to Identify Injuries in Infants Associated With Abuse.

Objectives: Medically minor but clinically important findings associated with physical child abuse, such as bruises in pre-mobile infants, may be identified by frontline clinicians yet the association of these injuries with child abuse is often not recognized, potentially allowing the abuse to continue and even to escalate. An accurate natural language processing (NLP) algorithm to identify high-risk injuries in electronic health record notes could improve detection and awareness of abuse. The objectives were to: 1) develop an NLP algorithm that accurately identifies injuries in infants associated with abuse and 2) determine the accuracy of this algorithm.

17β-estradiol activation of dorsal hippocampal TrkB is independent of increased mature BDNF expression and is required for enhanced memory consolidation in female mice.

The potent estrogen 17β-estradiol (E) is known to enhance hippocampal memory and plasticity, however the molecular mechanisms underlying these effects remain unclear. Brain derived neurotrophic factor (BDNF) and its receptor tropomyosin receptor kinase B (TrkB) are regulated by E, but the potential mechanistic roles of neurotrophic signaling in E-induced enhancement of memory are not well understood. Here, we examined the effects of hippocampal TrkB signaling on E-induced enhancement of memory consolidation in the object placement and recognition tasks.

From ash pond to Riverside Wetlands: Making the business case for engineered natural technologies.

The 2015 announcement of The Dow Chemical Company's (Dow) Valuing Nature Goal, which aims to identify $1 billion in business value from projects that are better for nature, gives nature a spot at the project design table. To support this goal, Dow and The Nature Conservancy have extended their long-standing collaboration and are now working to develop a defensible methodology to support the implementation of the goal. This paper reviews the nature valuation methodology framework developed by the Collaboration in support of the goal.

Estimation of Large Motion in Lung CT by Integrating Regularized Keypoint Correspondences into Dense Deformable Registration.

We present a novel algorithm for the registration of pulmonary CT scans. Our method is designed for large respiratory motion by integrating sparse keypoint correspondences into a dense continuous optimization framework. The detection of keypoint correspondences enables robustness against large deformations by jointly optimizing over a large number of potential discrete displacements, whereas the dense continuous registration achieves subvoxel alignment with smooth transformations.

Patch-Based Nonlinear Image Registration for Gigapixel Whole Slide Images.

Objective: Image registration of whole slide histology images allows the fusion of fine-grained information-like different immunohistochemical stains-from neighboring tissue slides. Traditionally, pathologists fuse this information by looking subsequently at one slide at a time. If the slides are digitized and accurately aligned at cell level, automatic analysis can be used to ease the pathologist's work.