Surface properties of plasma membrane vesicles isolated from melon (Cucumus melo L.) root cells differing in salinity tolerance

The hypotheses that genotypic differences in salinity tolerance may result from (i) differences in global surface charge density or (ii) from differences in global Ca²⁺ binding were tested. An attempt was made to correlate the differing salinity tolerance of four melon cultivars with surface properties of vesicles extracted from the plasma membrane (PM) of their root cells. Surface characterization involved measurements of electrophoretic mobility and sorption of ⁴⁵Ca²⁺ to the vesicles in the presence of varying concentrations of Ca²⁺, Na⁺ and Mg²⁺. Irrespective of salinity tolerance, vesicles from the four cultivars yielded similar ζ potentials under similar conditions, indicating similar global surface charge densities. Sorption studies with vesicles from two cultivars differing in salinity tolerance predicted independently this result of equal surface charge density. The estimated global binding affinities of Ca²⁺, Na⁺ and Mg²⁺ to the PM of both cultivars were the same with binding coefficients of 50, 0.8 and 9 M⁻¹, respectively. Consequently, the hypotheses enumerated above to interpret genotypic differences in salinity toxicity are rejected. However, vesicles from the salt-resistant strain sorbed 19% more Ca²⁺ per given amount of protein in the membrane, indicating the existence of a larger number of negatively charged surface sites per given amount of protein and a smaller amount of protein per given area of membrane. Genotypic differences in site-specific Ca²⁺-binding affinity (e.g. at ion channels) remain a viable hypothesis for genotypic differences in salinity tolerance.     

Bispectral Analysis of Heart Rate Variability to Characterize and Help Diagnose Pediatric Sleep Apnea

Pediatric obstructive sleep apnea (OSA) is a breathing disorder that alters heart rate variability (HRV) dynamics during sleep. HRV in children is commonly assessed through conventional spectral analysis. However, bispectral analysis provides both linearity and stationarity information and has not been applied to the assessment of HRV in pediatric OSA. Here, this work aimed to assess HRV using bispectral analysis in children with OSA for signal characterization and diagnostic purposes in two large pediatric databases (0–13 years). The first database (training set) was composed of 981 overnight ECG recordings obtained during polysomnography. The second database (test set) was a subset of the Childhood Adenotonsillectomy Trial database (757 children). We characterized three bispectral regions based on the classic HRV frequency ranges (very low frequency: 0–0.04 Hz; low frequency: 0.04–0.15 Hz; and high frequency: 0.15–0.40 Hz), as well as three OSA-specific frequency ranges obtained in recent studies (BW1: 0.001–0.005 Hz; BW2: 0.028–0.074 Hz; BWRes: a subject-adaptive respiratory region). In each region, up to 14 bispectral features were computed. The fast correlation-based filter was applied to the features obtained from the classic and OSA-specific regions, showing complementary information regarding OSA alterations in HRV. This information was then used to train multi-layer perceptron (MLP) neural networks aimed at automatically detecting pediatric OSA using three clinically defined severity classifiers. Both classic and OSA-specific MLP models showed high and similar accuracy (Acc) and areas under the receiver operating characteristic curve (AUCs) for moderate (classic regions: Acc = 81.0%, AUC = 0.774; OSA-specific regions: Acc = 81.0%, AUC = 0.791) and severe (classic regions: Acc = 91.7%, AUC = 0.847; OSA-specific regions: Acc = 89.3%, AUC = 0.841) OSA levels. Thus, the current findings highlight the usefulness of bispectral analysis on HRV to characterize and diagnose pediatric OSA.