Machine learning-based analysis of microfluidic device immobilized C. elegans for automated developmental toxicity testing.

Developmental toxicity (DevTox) tests evaluate the adverse effects of chemical exposures on an organism's development. Although current testing primarily relies on large mammalian models, the emergence of new approach methodologies (NAMs) is encouraging industries and regulatory agencies to evaluate novel assays. C.

vivoBodySeg: Machine learning-based analysis of C. elegans immobilized in vivoChip for automated developmental toxicity testing.

Developmental toxicity (DevTox) tests evaluate the adverse effects of chemical exposures on an organism's development. While large animal tests are currently heavily relied on, the development of new approach methodologies (NAMs) is encouraging industries and regulatory agencies to evaluate these novel assays. Several practical advantages have made useful model for rapid toxicity testing and studying developmental biology.

Femtosecond laser microdissection for isolation of regenerating C. elegans neurons for single-cell RNA sequencing.

Our understanding of nerve regeneration can be enhanced by delineating its underlying molecular activities at single-neuron resolution in model organisms such as Caenorhabditis elegans. Existing cell isolation techniques cannot isolate neurons with specific regeneration phenotypes from C. elegans.

In vivo hamster cheek pouch subepithelial ablation, biomaterial injection, and localization: pilot study.

Significance: The creation of subepithelial voids within scarred vocal folds via ultrafast laser ablation may help in localization of injectable biomaterials toward a clinically viable therapy for vocal fold scarring.

Aim: We aim to prove that subepithelial voids can be created in a live animal model and that the ablation process does not engender additional scar formation. We demonstrate localization and long-term retention of an injectable biomaterial within subepithelial voids.

Planar Laser Activated Neuronal Scanning (PLANS) System for Flow Cytometry.

We present a light-sheet flow cytometer for screening of . A machine learning approach is utilized to enable real-time analysis of protein aggregation models.

Variation in CT Number and Image Noise Uniformity According to Patient Positioning in MDCT.

Objective: Many algorithms for clinical decision making rely on assessment of the CT number (expressed as Hounsfield units); however, to our knowledge, few, if any, studies have addressed how CT numbers change as a function of patient positioning within the scanner.

Materials And Methods: An anthropomorphic phantom underwent imaging with varying amounts of vertical orientation misalignment with respect to isocenter. CT number and noise were measured using ROIs in the upper thorax, mid thorax, and abdomen.

A Wiki Based CT Protocol Management System.

At the University of Wisconsin Madison Department of Radiology, CT protocol management requires maintenance of thousands of parameters for each scanner. Managing CT protocols is further complicated by the unique configurability of each scanner. Due to recent Joint Commission requirements, now all CT protocol changes must be documented and reviewed by a site's CT protocol optimization team.