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Tissier, R.

Publications and source records attributed to Tissier, R..

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{-}CardiOvascular examination in awake Orangutans (Pongo pygmaeus pygmaeus): Low-stress Echocardiography including Speckle Tracking imaging (the COOLEST method)

IntroductionCardiovascular diseases have been identified as a major cause of mortality and morbidity in Borneo orangutans (Pongo pygmaeus pygmaeus). Transthoracic echocardiography is usually performed under anesthesia in great apes, which may be stressful and risky in cardiac animals. The aim of the present pilot study was hence to develop a quick and non-stressful echocardiographic method (i.e., the COOLEST method) in awake Borneo orangutans (CardiOvascular examination in awake Orangutans: Low-stress Echocardiography including Speckle Tracking imaging) and assess the variability of corresponding variables. Materials and MethodsFour adult Borneo orangutans trained to present their chest to the trainers were involved. A total of 96 TTE examinations were performed on 4 different days by a trained observer examining each orangutans 6 times per day. Each examination included four two-dimensional views, with offline assessment of 28 variables (i.e., two-dimensional (n=12), M-mode and anatomic M-mode (n=6), Doppler (n=7), and speckle tracking imaging (n=3)), representing a total of 2,688 measurements. A general linear model was used to determine the within-day and between-day coefficients of variation. ResultsMean{+/-}SD (minimum-maximum) images acquisition duration was 3.8{+/-}1.6 minutes (1.3-6.3). All within-day and between-day coefficients of variation but one (n=55/56, 98%) were <15%, and most (51/56, 91%) were <10% including those of speckle tracking systolic strain variables (2.7% to 5.4%). DiscussionHeart morphology as well as global and regional myocardial function can be assessed in awake orangutans with good to excellent repeatability and reproducibility. ConclusionsThis non-stressful method may be used for longitudinal cardiac follow-up in awake orangutans.

zoology

'Range': A gain and dynamic range independent quantification of spread aiding in panel design

In conventional flowcytometry one detector (primary) is dedicated for one fluorochrome. However, photons usually end up in other detectors too (fluorescence spillover). Compensation is a process that corrects the spillover signal from all detectors except the primary detector. Post compensation, the photon counting error of spillover signals become evident as spreading of the data. The spreading induced by spillover impairs the ability to resolve stained cell population from the unstained one, potentially reducing or completely losing cell populations. For successful multi-color panel design, it is important to know the expected spillover to maximize the data resolution. The Spillover Spreading Matrix (SSM) can be used to estimate the spread, but the outcome is dependent on detector sensitivity. Simply, the same single stained sample produces different spillover spread values when detector(s) sensitivity is altered. Many researchers mistakenly use this artifact to "reduce" the spread by decreasing detector sensitivity. This can result in diminished capacity to resolve dimly expressing cell populations. Here, we introduce SQI (Spread Quantification Index), that can quantify the spillover spread independent of detector sensitivity and independent of dynamic range. This allows users to compare spillover spread between instruments having different types of detectors, which is not possible using SSM.

immunology