Using an mHealth approach to collect patient-generated health data for predicting adverse health outcomes among adult survivors of childhood cancer.

Introduction: Cancer therapies predispose childhood cancer survivors to various treatment-related late effects, which contribute to a higher symptom burden, chronic health conditions (CHCs), and premature mortality. Regular monitoring of symptoms between clinic visits is useful for timely medical consultation and interventions that can improve quality of life (QOL). The Health Share Study aims to utilize mHealth to collect patient-generated health data (PGHD; daily symptoms, momentary physical health status) and develop survivor-specific risk prediction scores for mitigating adverse health outcomes including poor QOL and emergency room admissions.

Engineered bacterial swarm patterns as spatial records of environmental inputs.

A diverse array of bacteria species naturally self-organize into durable macroscale patterns on solid surfaces via swarming motility-a highly coordinated and rapid movement of bacteria powered by flagella. Engineering swarming is an untapped opportunity to increase the scale and robustness of coordinated synthetic microbial systems. Here we engineer Proteus mirabilis, which natively forms centimeter-scale bullseye swarm patterns, to 'write' external inputs into visible spatial records.

Total Knee Arthroplasty in Freestanding Ambulatory Surgery Centers: 5-Year Retrospective Chart Review of 90-Day Postsurgical Outcomes and Health Care Resource Utilization.

Introduction: Migration of total knee arthroplasty (TKA) procedures from the inpatient setting to outpatient venues, especially freestanding ambulatory surgery centers (ASCs), requires the use of reliable patient selection algorithms and standardized perioperative pathways to facilitate favorable outcomes for patients.

Methods: This retrospective chart review included consecutive TKA procedures performed over a 5-year period between January 2014 and January 2019 at 2 freestanding ASCs. The patient selection algorithm was developed on the basis of patient comorbidities to minimize the potential for adverse events.

Genome-wide association of implantable cardioverter-defibrillator activation with life-threatening arrhythmias.

Objectives: To identify genetic factors that would be predictive of individuals who require an implantable cardioverter-defibrillator (ICD), we conducted a genome-wide association study among individuals with an ICD who experienced a life-threatening arrhythmia (LTA; cases) vs. those who did not over at least a 3-year period (controls).

Background: Most individuals that receive implantable cardioverter-defibrillators never experience a life-threatening arrhythmia.

Gene expression profiling of human whole blood samples with the Illumina WG-DASL assay.

Background: Microarray-based gene expression analysis of peripheral whole blood is a common strategy in the development of clinically relevant biomarker panels for a variety of human diseases. However, the results of such an analysis are often plagued by decreased sensitivity and reliability due to the effects of relatively high levels of globin mRNA in whole blood. Globin reduction assays have been shown to overcome such effects, but they require large amounts of total RNA and may induce distinct gene expression profiles.

Longitudinal genome-wide association of cardiovascular disease risk factors in the Bogalusa heart study.

Cardiovascular disease (CVD) is the leading cause of death worldwide. Recent genome-wide association (GWA) studies have pinpointed many loci associated with CVD risk factors in adults. It is unclear, however, if these loci predict trait levels at all ages, if they are associated with how a trait develops over time, or if they could be used to screen individuals who are pre-symptomatic to provide the opportunity for preventive measures before disease onset.