Use of inert gas jets to measure the forces required for mechanical gene transfection

Background

Abnormal blood glucose (BG) concentrations have been associated with increased morbidity and mortality in both critically ill adults and infants. Furthermore, hypoglycaemia and glycaemic variability have both been independently linked to mortality in these patients. Continuous Glucose Monitoring (CGM) devices have the potential to improve detection and diagnosis of these glycaemic abnormalities. However, sensor noise is a trade-off of the high measurement rate and must be managed effectively if CGMs are going to be used to monitor, diagnose and potentially help treat glycaemic abnormalities.

Aim

To develop a tool that will aid clinicians in identifying unusual CGM behaviour and highlight CGM data that potentially need to be interpreted with care.

Methods

CGM data and BG measurements from 50 infants at risk of hypoglycaemia were used. Unusual CGM measurements were classified using a stochastic model based on the kernel density method and historical CGM measurements from the cohort. CGM traces were colour coded with very unusual measurements coloured red, highlighting areas to be interpreted with care. A 5-fold validation of the model was Monte Carlo simulated 25 times to ensure an adequate model fit.

Results

The stochastic model was generated using ~67,000 CGM measurements, spread across the glycaemic range ~2-10?mmol/L. A 5-fold validation showed a good model fit: the model 80% confidence interval (CI) captured 83% of clinical CGM data, the model 90% CI captured 91% of clinical CGM data, and the model 99% CI captured 99% of clinical CGM data. Three patient examples show the stochastic classification method in use with 1) A stable, low variability patient which shows no unusual CGM measurements, 2) A patient with a very sudden, short hypoglycaemic event (classified as unusual), and, 3) A patient with very high, potentially un-physiological, glycaemic variability after day 3 of monitoring (classified as very unusual).

Conclusions

This study has produced a stochastic model and classification method capable of highlighting unusual CGM behaviour. This method has the potential to classify important glycaemic events (e.g. hypoglycaemia) as true clinical events or sensor noise, and to help identify possible sensor degradation. Colour coded CGM traces convey the information quickly and efficiently, while remaining computationally light enough to be used retrospectively or in real-time.     

Ionic Relations of Garden Orache, A triplex hortensis L.: Growth and Ion Distribution at Moderate Salinity and the Function of Bladder Hairs

The growth of garden orache, A triplex hortensis was studiedunder conditions of mild NaCl or Na₂SO₄ salinity. Growth, drymatter production and leaf size were substantially stimulatedat 10 mM and 50 mM Na⁺ salts. Increased growth, however, appearedto be due to a K⁺-sparing effect of Na⁺ rather than to salinityper se. The distribution of K⁺ and Na⁺ in the plant revealeda remarkable preference for K+ in the roots and the hypocotyl.In the shoot the K/Na ratio decreased strongly with leaf age.However, the inverse changes in K⁺ and Na⁺ content with leafage were dependent on the presence of bladder hairs, which removedalmost all of the Na⁺ from the young leaf lamina. Measurementsof net fluxes of K⁺ and Na⁺ into roots and shoots of growingAtriplex plants showed a higher K/Na selectivity of the netion flux to the root compared to the shoot. With increasingsalinity the selectivity ratio S_{K, Na}^* of net ion fluxes tothe roots and to the shoots was increased. The data suggestthat recirculation of K⁺ from leaves to roots is an importantlink in establishing the K/Na selectivity in A. hortensis plants.The importance of K⁺ recirculation and phloem transport forsalt tolerance is discussed. Key words: Atriplex hortensis, Salinity, Potassium, Sodium, K⁺ retranslocation, Bladder hairs, Growth stimulation