Objective comparison of methods to decode anomalous diffusion

Deviations from Brownian motion leading to anomalous diffusion are found in transport dynamics from quantum physics to life sciences. The characterization of anomalous diffusion from the measurement of an individual trajectory is a challenging task, which traditionally relies on calculating the trajectory mean squared displacement. However, this approach breaks down for cases of practical interest, e.g., short or noisy trajectories, heterogeneous behaviour, or non-ergodic processes. Recently, several new approaches have been proposed, mostly building on the ongoing machine-learning revolution. To perform an objective comparison of methods, we gathered the community and organized an open competition, the Anomalous Diffusion challenge (AnDi). Participating teams applied their algorithms to a commonly-defined dataset including diverse conditions. Although no single method performed best across all scenarios, machine-learning-based approaches achieved superior performance for all tasks. The discussion of the challenge results provides practical advice for users and a benchmark for developers

Objective comparison of methods to decode anomalous diffusion

Deviations from Brownian motion leading to anomalous diffusion are found in transport dynamics from quantum physics to life sciences. The characterization of anomalous diffusion from the measurement of an individual trajectory is a challenging task, which traditionally relies on calculating the trajectory mean squared displacement. However, this approach breaks down for cases of practical interest, e.g., short or noisy trajectories, heterogeneous behaviour, or non-ergodic processes. Recently, several new approaches have been proposed, mostly building on the ongoing machine-learning revolution. To perform an objective comparison of methods, we gathered the community and organized an open competition, the Anomalous Diffusion challenge (AnDi). Participating teams applied their algorithms to a commonly-defined dataset including diverse conditions. Although no single method performed best across all scenarios, machine-learning-based approaches achieved superior performance for all tasks. The discussion of the challenge results provides practical advice for users and a benchmark for developers. Deviations from Brownian motion leading to anomalous diffusion are ubiquitously found in transport dynamics but often difficult to characterize. Here the authors compare approaches for single trajectory analysis through an open competition, showing that machine learning methods outperform classical approaches

THE USE OF BULLDOG CLAMP TO CONTROL THE DORSAL VEIN COMPLEX DURING ROBOT ASSISTED RADICAL PROSTATECTOMY

EAU Robotic Urology Section Congress (ERUS) -- SEP 26-28, 2012 -- London, ENGLANDWOS: 000309057300099…EAU Robot Urol Sect (ERUS), NHS Fdn Trust (NHS), Guys & St Thomas, NHS Trust (NHS), E & N Hertfordshire, NHS Fdn Trust (NHS), Heatherwood & Wexham Pk Hosp, Kings Coll London, Soc Robot Surg (SRS), European Grp Robot Urol (EGRU), Intuit Surg, AMS, Johnson & Johnson Co, Ethicon, BK Med, Astellas, Braun, Kings Hlth Partner

Effects of dietary salt on renal Na+ transporter subcellular distribution, abundance, and phosphorylation status

During high-salt (HS) diet the kidney increases urinary Na+ and volume excretion to match intake. We recently reported that HS provokes a redistribution of distal convoluted tubule Na+-Cl− cotransporter (NCC) from apical to subapical vesicles and decreases NCC abundance. This study aimed to test the hypothesis that the other renal Na+ transporters' abundance and or subcellular distribution is decreased by HS diet. Six-week-old Sprague-Dawley rats were fed a normal (NS) 0.4% NaCl diet or a HS 4% NaCl diet for 3 wk or overnight. Kidneys excised from anesthetized rats were fractionated on density gradients or analyzed by microscopy; transporters and associated regulators were detected with specific antibodies. Three-week HS doubled Na+/H+ exchanger (NHE)3 phosphorylation at serine 552 and provoked a redistribution of NHE3, dipeptidyl peptidase IV (DPPIV), myosin VI, Na+-Pi cotransporter (NaPi)-2, ANG II type 2 receptor (AT2R), aminopeptidase N (APN), Na+-K+-2Cl− cotransporter (NKCC2), epithelial Na+ channel (ENaC) β-subunit, and Na+-K+-ATPase (NKA) α1- and β1-subunits from low-density plasma membrane-enriched fractions to higher-density intracellular membrane-enriched fractions. NHE3, myosin VI, and AT2R retraction to the base of the microvilli (MV) during HS was evident by confocal microscopy. HS did not change abundance of NHE3, NKCC, or NKA α1- or β1-subunits but increased ENaC-β in high-density intracellular enriched membranes. Responses to HS were fully apparent after just 18 h. We propose that retraction of NHE3 to the base of the MV, driven by myosin VI and NHE3 phosphorylation and accompanied by redistribution of the NHE3 regulator DPPIV, contributes to a decrease in proximal tubule Na+ reabsorption during HS and that redistribution of transporters out of low-density plasma membrane-enriched fractions in the thick ascending limb of the loop of Henle and distal nephron may also contribute to the homeostatic natriuretic response to HS diet