Large-Scale, Wavelet-Based Analysis of Lysosomal Trajectories and Co-Movements of Lysosomes with Nanoparticle Cargos

Lysosomes—that is, acidic organelles known for degradation/recycling—move through the cytoplasm alternating between bursts of active transport and short, diffusive motions or even pauses. While their mobility is essential for lysosomes’ fusogenic and non-fusogenic interactions with target organelles, their movements have not been characterized in adequate detail. Here, large-scale statistical analysis of lysosomal movement trajectories reveals that lysosome trajectories in all examined cell types—both cancer and noncancerous ones—are superdiffusive and characterized by heavy-tailed distributions of run and flight lengths. Consideration of Akaike weights for various potential models (lognormal, power law, truncated power law, stretched exponential, and exponential) indicates that the experimental data are best described by the lognormal distribution, which, in turn, can be related to one of the space-search strategies particularly effective when “thorough” search needs to balance search for rare target(s) (organelles). In addition, automated, wavelet-based analysis allows for co-tracking the motions of lysosomes and the cargos they carry—particularly the nanoparticle aggregates known to cause selective lysosome disruption in cancerous cells. The methods we describe here could help study nanoparticle assemblies, viruses, and other objects transported inside various vesicle types, as well as coordinated movements of organelles/particles in the cytoplasm. Custom-written code that includes integrated workflow for our analyses is made available for academic use.

Strain specific motility patterns and surface adhesion of virulent and probiotic Escherichia coli

Bacterial motility provides the ability for bacterial dissemination and surface exploration, apart from a choice between surface colonisation and further motion. In this study, we characterised the movement trajectories of pathogenic and probiotic Escherichia coli strains (ATCC43890 and M17, respectively) at the landing stage (i.e., leaving the bulk and approaching the surface) and its correlation with adhesion patterns and efficiency. A poorly motile strain JM109 was used as a control. Using specially designed and manufactured microfluidic chambers, we found that the motion behaviour near surfaces drastically varied between the strains, correlating with adhesion patterns. We consider two bacterial strategies for effective surface colonisation: horizontal and vertical, based on the obtained results. The horizontal strategy demonstrated by the M17 strain is characterised by collective directed movements within the horizontal layer during a relatively long period and non-uniform adhesion patterns, suggesting co-dependence of bacteria in the course of adhesion. The vertical strategy demonstrated by the pathogenic ATCC43890 strain implies the individual movement of bacteria mainly in the vertical direction, a faster transition from bulk to near-surface swimming, and independent bacterial behaviour during adhesion, providing a uniform distribution over the surface.

Joint Simon effect in movement trajectories

In joint action literature it is often assumed that acting together is driven by pervasive and automatic process of co-representation, that is, representing the co-actor’s part of the task in addition to one’s own. Much of this research employs joint stimulus-response compatibility tasks varying the stimuli employed or the physical and social relations between participants. In this study we test the robustness of co-representation effects by focusing instead on variation in response modality. Specifically, we implement a mouse-tracking version of a Joint Simon Task in which participants respond by producing continuous movements with a computer mouse rather than pushing discrete buttons. We have three key findings. First, in a replication of an earlier study we show that in a classical individual Simon Task movement trajectories show greater curvature on incongruent trials, paralleling longer response times. Second, this effect largely disappears in a Go-NoGo Simon Task, in which participants respond to only one of the cues and refrain from responding to the other. Third, contrary to previous studies that use button pressing responses, we observe no overall effect in the joint variants of the task. However, we also detect a notable diversity in movement strategies adopted by the participants, with some participants showing the effect on the individual level. Our study casts doubt on the pervasiveness of co-representation, highlights the usefulness of mouse-tracking methodology and emphasizes the need for looking at individual variation in task performance.

Clustering analysis of movement kinematics in reinforcement learning

Reinforcement learning has been used as an experimental model of motor skill acquisition, where at times movements are successful and thus reinforced. One fundamental problem is to understand how humans select exploration over exploitation during learning. The decision could be influenced by factors such as task demands and reward availability. In this study, we applied a clustering algorithm to examine how a change in the accuracy requirements of a task affected the choice of exploration over exploitation. Participants made reaching movements to an unseen target using a planar robot arm and received reward after each successful movement. For one group of participants, the width of the hidden target decreased after every other training block. For a second group, it remained constant. The clustering algorithm was applied to the kinematic data to characterize motor learning on a trial-to-trial basis as a sequence of movements, each belonging to one of the identified clusters. By the end of learning, movement trajectories across all participants converged primarily to a single cluster with the greatest number of successful trials. Within this analysis framework, we defined exploration and exploitation as types of behaviour in which two successive trajectories belong to different or similar clusters, respectively. The frequency of each mode of behaviour was evaluated over the course learning. It was found that by reducing the target width, participants used a greater variety of different clusters and displayed more exploration than exploitation. Excessive exploration relative to exploitation was found to be detrimental to subsequent motor learning.

Professional Mobility as a Model for Overcoming Maladaptive Forms of a Person’s Psychological Defence in Conditions of Professional Development Crises

The article deals with the results of the analysis of the person’s professional mobility as a comprehensive tool for overcoming the professional crises. It also determines the existence of many unascertained psychological problems in its structure. One of these problems is the problem of overcoming maladaptive forms of a person’s psychological defence based on his professional mobility in stressful conditions of the professional development crises. Stressful uncertainty in the professional crisis and the high ambivalent tension, which the person is experiencing, characterize the specialist’s maladaptive development according to the “catastrophic” scenario. In the conditions of the professional development crisis a specialist cannot leave it adaptively and flexibly due to a limited number of rigidly patterned professional barriers and behaviour models. Such maladaptive patterned movement of a specialist towards the disintegrational destruction of the whole system of his professional development can be overcome constructively on the basis of his professional mobility model, selection and realization of the further professional movement vector. We consider the interactive strategy of a specialist’s behaviour for constructive overcoming professional crises in the system of his professional development, based on the development of the ability of directed transitions to new professional movement trajectories in the points of the system bifurcation, as the professional mobility.

Multivariate functional additive mixed models

Multivariate functional data can be intrinsically multivariate like movement trajectories in 2D or complementary such as precipitation, temperature and wind speeds over time at a given weather station. We propose a multivariate functional additive mixed model (multiFAMM) and show its application to both data situations using examples from sports science (movement trajectories of snooker players) and phonetic science (acoustic signals and articulation of consonants). The approach includes linear and nonlinear covariate effects and models the dependency structure between the dimensions of the responses using multivariate functional principal component analysis. Multivariate functional random intercepts capture both the auto-correlation within a given function and cross-correlations between the multivariate functional dimensions. They also allow us to model between-function correlations as induced by, for example, repeated measurements or crossed study designs. Modelling the dependency structure between the dimensions can generate additional insight into the properties of the multivariate functional process, improves the estimation of random effects, and yields corrected confidence bands for covariate effects. Extensive simulation studies indicate that a multivariate modelling approach is more parsimonious than fitting independent univariate models to the data while maintaining or improving model fit.

The Control Concept for Upper Limb Exoskeleton

Robotic exoskeletons inspired by the animal’s external covering are wearable systems that enhance human power, motor skills, or support the movement. The main difficulty, apart from the mechanical structure design, is the development of an exoskeleton control system, as it should recognize the movement intended by the user and assist in its execution. This work is devoted to the exoskeleton of the upper limbs that supports movement. The method of controlling the exoskeleton by means of electromyograms (EMG) was presented. EMG is a technique for recording and assessing the electrical activity produced by skeletal muscles. The main advantage of EMG based control is the ability to forecast intended motion, even if the user is unable to generate it. This work aims to define strategies for controlling the exoskeleton of the upper limb in children suffering from neuromuscular diseases. Such diseases gradually reduce the mobility of the lower and upper limbs. These children are wheelchair bound, so it was assumed that the upper limb exoskeleton could be attached to a wheelchair. EMG signals are recorded, amplified and filtered. An artificial neural network using fuzzy logic to process EMG was used. This network predicts movement trajectories. Using this forecast and taking into account the feedback information, the control system generates the appropriate drive torques.

Flying In-formation: A computational method for the classification of host seeking mosquito flight patterns using path segmentation and unsupervised machine learning

The rational design of effective vector control tools requires detailed knowledge of vector behaviour. Yet, behavioural observations, interpretations, evaluations and definitions by even the most experienced researcher are constrained by subjectivity and perceptual limits. Seeking an objective alternative to ‘expertise’, we developed and tested an unsupervised method for the automatic identification of videotracked mosquito flight behaviour. This method unites path-segmentation and unsupervised machine learning in an innovative workflow and is implemented using a combination of R and python. The workflow (1) records movement trajectories; (2) applies path-segmentation; (3) clusters path segments using unsupervised learning; and (4) interprets results. Analysis of the flight patterns of An. gambiae s.s., responding to human-baited insecticide-treated bednets (ITNs), by the new method identified four distinct behaviour modes: with ‘swooping’ and ‘approaching’ modes predominant at ITNs; increased ‘walking’ behaviours at untreated nets; similar rates of 'reacting' at both nets; and higher overall activity at treated nets. The method’s validity was tested by comparing these findings with those from a similar setting using an expertise-based method. The level of correspondence found between the studies validated the accuracy of the new method. While researcher-defined behaviours are inherently subjective, and prone to corollary shortcomings, the new approach’s mathematical method is objective, automatic, repeatable and a validated alternative for analysing complex vector behaviour. This method provides a novel and adaptable analytical tool and is freely available to vector biologists, ethologists and behavioural ecologists.