Precision oncology in neurofibromatosis type 1: quantification of differential sensitivity to selumetinib in plexiform neurofibromas using single-cell RNA sequencing.

Purpose: Selumetinib is an FDA-approved targeted therapy for plexiform neurofibromas in neurofibromatosis type 1(NF1) with durable response rates seen in most, but not all patients. In this proof-of-concept study, we demonstrate single-cell RNA sequencing(scRNAseq) as a technique for quantifying drug response to selumetinib at the single cell level.

Methods: scRNAseq data from neurofibroma biopsies was obtained from a public genomics repository.

Emergent Applications of Machine Learning for Diagnosing and Managing Appendicitis: A State-of-the-Art Review.

Appendicitis is an inflammatory condition that requires timely and effective intervention. Despite being one of the most common surgically treated diseases, the condition is difficult to diagnose because of atypical presentations. Ultrasound and computed tomography (CT) imaging improve the sensitivity and specificity of diagnoses, yet these tools bear the drawbacks of high operator dependency and radiation exposure, respectively.

Racial disparities in complications following elective colon cancer resection: Impact of laparoscopic versus robotic approaches.

Background: We sought to examine differences in outcomes for Black and White patients undergoing robotic or laparoscopic colectomy to assess the potential impact of technological advancement.

Methods: We queried the ACS-NSQIP database for elective robotic (RC) and laparoscopic (LC) colectomy for cancer from 2012 to 2020. Outcomes included 30-day mortality and complications.

Microfluidic 'brain-on chip' systems to supplement neurological practice: development, applications and considerations.

Among the greatest general challenges in bioengineering is to mimic human physiology. Advanced efforts in tissue engineering have led to sophisticated 'brain-on-chip' (BoC) microfluidic devices that can mimic structural and functional aspects of brain tissue. BoC may be used to understand the biochemical pathways of neurolgical pathologies and assess promising therapeutic agents for facilitating regenerative medicine.

Smartphone-Based Light Detection and Ranging for Remote Patient Evaluation and Monitoring.

LIDAR (from "light detection and ranging" or "laser imaging, detection, and ranging") is an evolving three-dimensional scanning technology with historical applications in various fields. However, the applicability of LIDAR in the field of medicine has mostly not been examined thus far. Here, we review the basic principles governing LIDAR and its potential to be used in three notable use cases in the context of remote patient monitoring: geriatric fall prevention, postoperative recovery monitoring, and home safety assessment.

Astrocyte Heterogeneity in Multiple Sclerosis: Current Understanding and Technical Challenges.

The emergence of single cell technologies provides the opportunity to characterize complex immune/central nervous system cell assemblies in multiple sclerosis (MS) and to study their cell population structures, network activation and dynamics at unprecedented depths. In this review, we summarize the current knowledge of astrocyte subpopulations in MS tissue and discuss the challenges associated with resolving astrocyte heterogeneity with single-nucleus RNA-sequencing (snRNA-seq). We further discuss multiplexed imaging techniques as tools for defining population clusters within a spatial context.