RESUMEN

Rules derived from standard Rechtschaffen and Kales criteria were developed to accurately score rodent sleep into wake, rapid eye movement (REM) sleep, and non-REM sleep using movements detected by non-contact electric field (EF) sensors. • Using this method, rodent sleep can be scored using only respiratory and gross body movements as a validated, non-invasive alternative to electrode techniques. • The methodology and rules established for EF sensor-based sleep scoring were easily learned and implemented. • Examples of expert-scored files are included here to help novice scorers self-train to score sleep. Though validated in mice, sleep scoring using respiratory movements has the potential for application in other species and through other movement-based technologies beyond EF sensors.

RESUMEN

STUDY OBJECTIVE: Validate a novel method for sleep-wake staging in mice using noninvasive electric field (EF) sensors. METHODS: Mice were implanted with electroencephalogram (EEG) and electromyogram (EMG) electrodes and housed individually. Noninvasive EF sensors were attached to the exterior of each chamber to record respiration and other movement simultaneously with EEG, EMG, and video. A sleep-wake scoring method based on EF sensor data was developed with reference to EEG/EMG and then validated by three expert scorers. Additionally, novice scorers without sleep-wake scoring experience were self-trained to score sleep using only the EF sensor data, and results were compared to those from expert scorers. Lastly, ability to capture three-state sleep-wake staging with EF sensors attached to traditional mouse home-cages was tested. RESULTS: EF sensors quantified wake, rapid eye movement (REM) sleep, and non-REM sleep with high agreement (>93%) and comparable inter- and intra-scorer error as EEG/EMG. Novice scorers successfully learned sleep-wake scoring using only EF sensor data and scoring criteria, and achieved high agreement with expert scorers (>91%). When applied to traditional home-cages, EF sensors enabled classification of three-state (wake, NREM and REM) sleep-wake independent of EEG/EMG. CONCLUSIONS: EF sensors score three-state sleep-wake architecture with high agreement to conventional EEG/EMG sleep-wake scoring 1) without invasive surgery, 2) from outside the home-cage, and 3) and without requiring specialized training or equipment. EF sensors provide an alternative method to assess rodent sleep for animal models and research laboratories in which EEG/EMG is not possible or where noninvasive approaches are preferred.

Asunto(s)

RESUMEN

OBJECTIVE: In osteoarthritis (OA) models, histology is commonly used to evaluate the severity of joint damage. Unfortunately, semi-quantitative histological grading systems include some level of subjectivity, and quantitative grading systems can be tedious to implement. The objective of this work is to introduce an open source, graphic user interface (GUI) for quantitative grading of knee OA. METHODS: Inspired by the 2010 OARSI histopathology recommendations for the rat, our laboratory has developed a GUI for the evaluation of knee OA, nicknamed GEKO. In this work, descriptions of the quantitative measures acquired by GEKO are presented and measured in 42 histological images from a rat knee OA model. Using these images, across-session and within-session reproducibility for individual graders is evaluated, and inter-grader reliability across different levels of OA severity is also assessed. RESULTS: GEKO allowed histological images to be quantitatively scored in less than 1 min per image. In addition, intra-class coefficients (ICCs) were largely above 0.8 for across-session reproducibility, within-session reproducibility, and inter-grader reliability. These data indicate GEKO aided in the reproducibility and repeatability of quantitative OA grading across graders and grading sessions. CONCLUSIONS: Our data demonstrate GEKO is a reliable and efficient method to calculate quantitative histological measures of knee OA in a rat model. GEKO reduced quantitative grading times relative to manual grading systems and allowed grader reproducibility and repeatability to be easily assessed within a grading session and across time. Moreover, GEKO is being provided as a free, open-source tool for the OA research community.

Asunto(s)

RESUMEN

OBJECTIVE: Parallel measures of osteoarthritis (OA) across species can help evaluate OA models relative to humans. Toward this need, our group recently developed a magnetic nanoparticle-based technology, termed magnetic capture, to analyze biomarkers within a rat knee. The objectives of this study were to directly compare magnetic capture to lavage, and assess c-telopeptide of collagen type II (CTXII) in the rat medial meniscus transection (MMT) model of knee OA. DESIGN: MMT surgery was performed in 30 male Lewis rats (3 months, 250 g). Using lavage or magnetic capture, CTXII was assessed in the OA-affected and contralateral knee at 1 week (n = 6 per group) or 4 weeks (n = 8 per group) after surgery. RESULTS: While lavage detected elevated CTXII concentrations in the OA-affected knee at 1 week (P = 0.002), magnetic capture detected elevated CTXII levels in the OA-affected knee at 4 weeks (P = 0.016). While magnetic capture did not detect significant elevation of CTXII at week 1, five of six rats evaluated with magnetic capture had higher CTXII levels in the OA-affected joint relative to the contralateral limb. Moreover, with magnetic capture, CTXII levels increased from 1 week to 4 weeks, corresponding to histological damage. CTXII concentrations evaluated via lavage were relatively constant across time. CONCLUSIONS: Magnetic capture and lavage evaluate CTXII in different ways: Magnetic capture measures total CTXII in the joint, while lavage measures concentration. Our data indicate magnetic capture may be advantageous at later time points, where CTXII can be diluted by effusions.

Asunto(s)