Slow integrin-dependent migration organizes networks of tissue-resident mast cells.

Immune cell locomotion is associated with amoeboid migration, a flexible mode of movement, which depends on rapid cycles of actin polymerization and actomyosin contraction. Many immune cells do not necessarily require integrins, the major family of adhesion receptors in mammals, to move productively through three-dimensional tissue spaces. Instead, they can use alternative strategies to transmit their actin-driven forces to the substrate, explaining their migratory adaptation to changing external environments.

Deep Learning for Synthetic CT from Bone MRI in the Head and Neck.

Background And Purpose: Bone MR imaging techniques enable visualization of cortical bone without the need for ionizing radiation. Automated conversion of bone MR imaging to synthetic CT is highly desirable for downstream image processing and eventual clinical adoption. Given the complex anatomy and pathology of the head and neck, deep learning models are ideally suited for learning such mapping.

The Deterioration Risk Index: Developing and Piloting a Machine Learning Algorithm to Reduce Pediatric Inpatient Deterioration.

Objectives: Develop and deploy a disease cohort-based machine learning algorithm for timely identification of hospitalized pediatric patients at risk for clinical deterioration that outperforms our existing situational awareness program.

Design: Retrospective cohort study.

Setting: Nationwide Children's Hospital, a freestanding, quaternary-care, academic children's hospital in Columbus, OH.

Locating Youth Exposed to Parental Justice Involvement in the Electronic Health Record: Development of a Natural Language Processing Model.

Background: Parental justice involvement (eg, prison, jail, parole, or probation) is an unfortunately common and disruptive household adversity for many US youths, disproportionately affecting families of color and rural families. Data on this adversity has not been captured routinely in pediatric health care settings, and if it is, it is not discrete nor able to be readily analyzed for purposes of research.

Objective: In this study, we outline our process training a state-of-the-art natural language processing model using unstructured clinician notes of one large pediatric health system to identify patients who have experienced a justice-involved parent.

Ultrashort Echo-Time MR Imaging of the Pediatric Head and Neck.

Bone MR imaging techniques use extremely rapid echo times to maximize detection of short-T2 tissues with low water concentrations. The major approaches used in clinical practice are ultrashort echo-time and zero echo-time. Synthetic CT generation is feasible using atlas-based, voxel-based, and deep learning approaches.