Analysis of HubP-dependent cell pole protein targeting in Vibrio cholerae uncovers novel motility regulators

In rod-shaped bacteria, the emergence and maintenance of long-axis cell polarity is involved in key cellular processes such as cell cycle, division, environmental sensing and flagellar motility among others. Many bacteria achieve cell pole differentiation through the use of polar landmark proteins acting as scaffolds for the recruitment of functional macromolecular assemblies. In Vibrio cholerae a large membrane-tethered protein, HubP, specifically interacts with proteins involved in chromosome segregation, chemotaxis and flagellar biosynthesis. Here we used comparative proteomics, genetic and imaging approaches to identify additional HubP partners and demonstrate that at least six more proteins are subject to HubP-dependent polar localization. These include a cell-wall remodeling enzyme (DacB), a likely chemotaxis sensory protein (HlyB), two presumably cytosolic proteins of unknown function (VC1210 and VC1380) and two membrane-bound proteins, named here MotV and MotW, that exhibit distinct effects on chemotactic motility. We show that while both ΔmotW and ΔmotV mutants retain monotrichous flagellation, they present significant to severe motility defects when grown in soft agar. Video-tracking experiments further reveal that ΔmotV cells can swim in liquid environments but are unable to tumble or penetrate a semisolid matrix, whereas a motW deletion affects both tumbling frequency and swimming speed. Motility suppressors and gene co-occurrence analyses reveal co-evolutionary linkages between MotV, a subset of non-canonical CheV proteins and flagellar C-ring components FliG and FliM, whereas MotW regulatory inputs appear to intersect with specific c-di-GMP signaling pathways. Together, these results reveal an ever more versatile role for the landmark cell pole organizer HubP and identify novel mechanisms of motility regulation.

Research on Care Workers Physical Exercise Video Tracking based on Deep Neural Network

Most nursing workers have a positive cognitive attitude towards physical exercise, but their exercise behavior lags behind. There are significant differences in the frequency, time, experience and load of physical exercise among nurses of different ages. Care workers’ union organizations should try their best to provide health assistance to medical staff to meet their needs for physical exercise, so as to ensure their physical and mental health. Aiming at the problem of target tracking in motion video, this paper proposes a method of tracking motion video of nursing staff based on deep neural network (DNN). The effectiveness and adaptability of this method are verified by an example. This method can not only track and estimate the position of the target effectively, but also describe the shape of the target well, thus solving the problem that the shape of the target is complex and difficult to track in motion video.

Behavioral Effects of Buspirone in Juvenile Zebrafish of Two Different Genetic Backgrounds

Anxiety continues to represent a major unmet medical need. Despite the availability of numerous anxiolytic drugs, a large proportion of patients do not respond well to current pharmacotherapy, or their response diminishes with chronic drug application. To discover novel compounds and to investigate the mode of action of anxiolytic drugs, animal models have been proposed. The zebrafish is a novel animal model in this research. It is particularly appropriate, as it has evolutionarily conserved features, and drug administration can be employed in a non-invasive manner by immersing the fish into the drug solution. The first step in the analysis of anxiolytic drugs with zebrafish is to test reference compounds. Here, we investigate the effects of buspirone hydrochloride, an anxiolytic drug often employed in the human clinic. We utilize two genetically distinct populations of zebrafish, ABSK, derived from the quasi-inbred AB strain, and WT, a genetically heterogeneous wild-type population. We placed juvenile (10–13-day, post-fertilization, old) zebrafish singly in petri dishes containing one of four buspirone concentrations (0 mg/L control, 5 mg/L, 20 mg/L or 80 mg/L) for 1 h, with each fish receiving a single exposure to one concentration, a between subject experimental design. Subsequently, we recorded the behavior of the zebrafish for 30 min using video-tracking. Buspirone decreased distance moved, number of immobility episodes and thigmotaxis, and it increased immobility duration and turn angle in a quasi-linear dose dependent but genotype independent manner. Although it is unclear whether these changes represent anxiolysis in zebrafish, the results demonstrate that behavioral analysis of juvenile zebrafish may be a sensitive and simple way to quantify the effects of human anxiolytic drugs.

Tweezepy: A Python package for calibrating forces in single-molecule video-tracking experiments

Single-molecule force spectroscopy (SMFS) instruments (e.g., magnetic and optical tweezers) often use video tracking to measure the three-dimensional position of micron-scale beads under an applied force. The force in these experiments is calibrated by comparing the bead trajectory to a thermal motion-based model with the drag coefficient, γ, and trap spring constant, κ, as parameters. Estimating accurate parameters is complicated by systematic biases from spectral distortions, the camera exposure time, parasitic noise, and least-squares fitting methods. However, while robust calibration methods exist that correct for these biases, they are not always used because they can be complex to implement computationally. To address this barrier, we present Tweezepy: a Python package for calibrating forces in SMFS video-tracking experiments. Tweezepy uses maximum likelihood estimation (MLE) to estimate parameters and their uncertainties from a single bead trajectory via the power spectral density (PSD) and Allan variance (AV). It is well-documented, fast, easy to use, and accounts for most common sources of biases in SMFS video-tracking experiments. Here, we provide a comprehensive overview of Tweezepy’s calibration scheme, including a review of the theory underlying thermal motion-based parameter estimates, a discussion of the PSD, AV, and MLE, and an explanation of their implementation.

Object Tracking Using HSV Values and OpenCV

This research shows how to use colour and movement to automate the process of recognising and tracking things. Video tracking is a technique for detecting a moving object over a long distance using a camera. The main purpose of video tracking is to connect target objects in subsequent video frames. The connection may be particularly troublesome when things move faster than the frame rate. Using HSV colour space values and OpenCV in different video frames, this study proposes a way to track moving objects in real-time. We begin by calculating the HSV value of an item to be monitored, and then we track the object throughout the testing step. The items were shown to be tracked with 90 percent accuracy. Keywords: HSV, OpenCV, Object tracking, Video frames, GUI

ALGORITHMS FOR OBJECT POSITION MONITORING ON THE SEA SURFACE USING MONOCULAR VIDEO CAMERA

The article proposes new algorithms for estimating the coordinates of objects (both linear and angular) relative to the coordinate system related to the video camera. A two-step algorithm is proposed. At the first stage, the processing of images coming from the camera is performed – the selection of an area be-longing to the sea surface in the image, the detection and video tracking of objects, the determination of azimuth and elevation angles from the obtained images. Our approach is based on the representation of elevation and azimuth angles in the form of non-stationary autoregression models, recurrent estimation of their parameters and subsequent estimation of the object coordinates.

Investigation of the Combined Effects of Rising Temperature and Pesticide Contamination on the Swimming Behaviour of Alpine Chironomids

Some pollutants can be transported through the atmosphere and travel medium–long distances to be deposited in glaciers at high altitude and latitude. The increase in the rate of glacier melting due to global warming can release these pollutants in alpine streams. This study investigated the combined effects of rising temperatures and chlorpyrifos (CPF) contamination on the swimming behaviour of alpine chironomids collected in a shrinking alpine glacier. We assessed the individual and interaction effects of rising temperatures (2–11 °C) and CPF concentrations (0–110 ng L−1) on the swimming behaviour of Diamesa zernyi (Chironomidae) larvae. Distance (mm) and speed (mm s−1) were recorded using a video-tracking system after 24–72 h of treatment. The two stressors caused different effects on distance and speed, with increasing temperature generally causing hyperactivity and CPF from hyperactivity to reduced mobility. Two interactions were detected between stressors when combined: (i) CPF superimposed the effect of temperature on both behavioural endpoints i.e., with 110 ng L−1 of CPF, at 11 °C, larvae moved less; (ii) warming (11 °C) magnified the negative effect of CPF: the smallest distance and slowest speed were recorded at the highest values of the two stressors after 72 h. Our results suggest that water contamination by CPF, even at sub-lethal concentrations, might increase the sensitivity of chironomids to warming, and vice versa, raising concerns about freshwater biodiversity conservation under climate change.

A Non-Invasive Millimetre-Wave Radar Sensor for Automated Behavioural Tracking in Precision Farming—Application to Sheep Husbandry

The automated quantification of the behaviour of freely moving animals is increasingly needed in applied ethology. State-of-the-art approaches often require tags to identify animals, high computational power for data collection and processing, and are sensitive to environmental conditions, which limits their large-scale utilization, for instance in genetic selection programs of animal breeding. Here we introduce a new automated tracking system based on millimetre-wave radars for real time robust and high precision monitoring of untagged animals. In contrast to conventional video tracking systems, radar tracking requires low processing power, is independent on light variations and has more accurate estimations of animal positions due to a lower misdetection rate. To validate our approach, we monitored the movements of 58 sheep in a standard indoor behavioural test used for assessing social motivation. We derived new estimators from the radar data that can be used to improve the behavioural phenotyping of the sheep. We then showed how radars can be used for movement tracking at larger spatial scales, in the field, by adjusting operating frequency and radiated electromagnetic power. Millimetre-wave radars thus hold considerable promises precision farming through high-throughput recording of the behaviour of untagged animals in different types of environments.

An Efficient Real Time Object Tracking Based on HSV Value

This study presents a strategy to automate the process to recognize and track objects using color and motion. Video Tracking is the approach to detect a moving item using a camera across the long distance. The basic goal of video tracking is in successive video frames to link target objects. When objects move quicker in proportion to frame rate, the connection might be particularly difficult. This work develops a method to follow moving objects in real-time utilizing HSV color space values and OpenCV in distinct video frames.. We start by deriving the HSV value of an object to be tracked and then in the testing stage, track the object. It was seen that the objects were tracked with 90% accuracy. Keywords: HSV, OpenCV, Object tracking,