Microtubule-dependent movement is crucial for the spatial organization of endosomes in most eukaryotes, but as yet there has been no systematic analysis of how a particular microtubule motor contributes to early endosome dynamics. Here we tracked early endosomes labeled with GFP-Rab5 on the nanometer scale, and combined this with global, first passage probability (FPP) analysis to provide an unbiased description of how the minus-end microtubule motor, cytoplasmic dynein, supports endosome motility. Dynein contributes to short-range endosome movement, but in particular drives 85–98% of long, inward translocations. For these, it requires an intact dynactin complex to allow membrane-bound p150Glued to activate dynein, since p50 over-expression, which disrupts the dynactin complex, inhibits inward movement even though dynein and p150Glued remain membrane-bound. Long dynein-dependent movements occur via bursts at up to ∼8 µms−1 that are linked by changes in rate or pauses. These peak speeds during rapid inward endosome movement are still seen when cellular dynein levels are 50-fold reduced by RNAi knock-down of dynein heavy chain, while the number of movements is reduced 5-fold. Altogether, these findings identify how dynein helps define the dynamics of early endosomes.

The first-passage-probability can be used as an unbiased method for determining the phases of motion of individual organelles within live cells. Using high speed microscopy, we observe individual lipid droplet tracks and analyze the motor protein driven motion. At short passage lengths (<10(-2)μm), a log-normal distribution in the first-passage-probability as a function of time is observed, which switches to a Gaussian distribution at longer passages due to the running motion of the motor proteins. The mean first-passage times () as a function of the passage length (L), averaged over a number of runs for a single lipid droplet, follow a power law distribution ~L(α), α>2, at short times due to a passive subdiffusive process. This changes to another power law at long times where 1<α<2, corresponding to sub-ballistic superdiffusive motion, an active process. Subdiffusive passive mean square displacements are observed as a function of time, ~t(β), where 0<β<1 at short times again crossing over to an active sub-ballistic superdiffusive result 1<β<2 at longer times. Consecutive runs of the lipid droplets add additional independent Gaussian peaks to a cumulative first-passage-probability distribution indicating that the speeds of sequential phases of motion are independent and biochemically well regulated. As a result we propose a model for motor driven lipid droplets that exhibits a sequential run behavior with occasional pauses.

We show that the transitions which occur between close orders of synchronization in the cardiorespiratory system are mainly due to modulation of the cardiac and respiratory processes by lowfrequency components. The experimental evidence is derived from recordings on healthy subjects at rest and during exercise. Exercise acts as a perturbation of the system that alters the mean cardiac and respiratory frequencies and changes the amount of their modulation by low-frequency oscillations. The conclusion is supported by numerical evidence based on a model of phasecoupled oscillators, with white noise and low-frequency noise. Both the experimental and numerical approaches confirm that low-frequency oscillations play a significant role in the transitional behavior between close orders of synchronization.

Particle tracking experiments with high speed digital microscopy yield the positions and trajectories of lipid droplets inside living cells. Angular correlation analysis shows that the lipid droplets have uncorrelated motion at short time scales (τ < 1 ms) followed by anti-persistent motion for lag times in the range of 1 ⩽ τ ⩽ 10 ms. The angular correlation at longer time scales, τ > 10 ms, becomes persistent, indicating directed movement. The motion at all time scales is associated with the lipid droplets being tethered to and driven along the microtubule network. The point at which the angular correlation changes from anti-persistent to persistent motion corresponds to the cross over between sub-diffusive and super diffusive motion, as observed by mean square displacement analysis. Correct analysis of the angular correlations of the detector noise is found to be crucial in modelling the observed phenomena.

SummaryDepth of anaesthesia monitors usually analyse cerebral function with or without other physiological signals; non‐invasive monitoring of the measured cardiorespiratory signals alone would offer a simple, practical alternative. We aimed to investigate whether such signals, analysed with novel, non‐linear dynamic methods, would distinguish between the awake and anaesthetised states. We recorded ECG, respiration, skin temperature, pulse and skin conductivity before and during general anaesthesia in 27 subjects in good cardiovascular health, randomly allocated to receive propofol or sevoflurane. Mean values, variability and dynamic interactions were determined. Respiratory rate (p = 0.0002), skin conductivity (p = 0.03) and skin temperature (p = 0.00006) changed with sevoflurane, and skin temperature (p = 0.0005) with propofol. Pulse transit time increased by 17% with sevoflurane (p = 0.02) and 11% with propofol (p = 0.007). Sevoflurane reduced the wavelet energy of heart (p = 0.0004) and respiratory (p = 0.02) rate variability at all frequencies, whereas propofol decreased only the heart rate variability below 0.021 Hz (p < 0.05). The phase coherence was reduced by both agents at frequencies below 0.145 Hz (p < 0.05), whereas the cardiorespiratory synchronisation time was increased (p < 0.05). A classification analysis based on an optimal set of discriminatory parameters distinguished with 95% success between the awake and anaesthetised states. We suggest that these results can contribute to the design of new monitors of anaesthetic depth based on cardiovascular signals alone.