M-Track: A New Software for Automated Detection of Grooming Trajectories in Mice

Grooming is a complex and robust innate behavior, commonly performed by most vertebrate species. In mice, grooming consists of a series of stereotyped patterned strokes, performed along the rostro-caudal axis of the body. The frequency and duration of each grooming episode is sensitive to changes in stress levels, social interactions and pharmacological manipulations, and is therefore used in behavioral studies to gain insights into the function of brain regions that control movement execution and anxiety. Traditional approaches to analyze grooming rely on manually scoring the time of onset and duration of each grooming episode, and are often performed on grooming episodes triggered by stress exposure, which may not be entirely representative of spontaneous grooming in freely-behaving mice. This type of analysis is time-consuming and provides limited information about finer aspects of grooming behaviors, which are important to understand movement stereotypy and bilateral coordination in mice. Currently available commercial and freeware video-tracking software allow automated tracking of the whole body of a mouse or of its head and tail, not of individual forepaws. Here we describe a simple experimental set-up and a novel open-source code, named M-Track, for simultaneously tracking the movement of individual forepaws during spontaneous grooming in multiple freely-behaving mice. This toolbox provides a simple platform to perform trajectory analysis of forepaw movement during distinct grooming episodes. By using M-track we show that, in C57BL/6 wild type mice, the speed and bilateral coordination of the left and right forepaws remain unaltered during the execution of distinct grooming episodes. Stress exposure induces a profound increase in the length of the forepaw grooming trajectories. M-Track provides a valuable and user-friendly interface to streamline the analysis of spontaneous grooming in biomedical research studies

Recurrent geomagnetic storms and relativistic electron enhancements in the outer magnetosphere: ISTP coordinated measurements

New, coordinated measurements from the International Solar-Terrestrial Physics (ISTP) constellation of spacecraft are presented to show the causes and effects of recurrent geomagnetic activity during recent solar minimum conditions. It is found using WIND and POLAR data that even for modest geomagnetic storms, relativistic electron fluxes are strongly and rapidly enhanced within the outer radiation zone of the Earth\u27s magnetosphere. Solar wind data are utilized to identify the drivers of magnetospheric acceleration processes. Yohkoh solar soft X-ray data are also used to identify the solar coronal holes that produce the high-speed solar wind streams which, in turn, cause the recurrent geomagnetic activity. It is concluded that even during extremely quiet solar conditions (sunspot minimum) there are discernible coronal holes and resultant solar wind streams which can produce intense magnetospheric particle acceleration. As a practical consequence of this Sun-Earth connection, it is noted that a long-lasting E\u3e1MeV electron event in late March 1996 appears to have contributed significantly to a major spacecraft (Anik E1) operational failure

Buildup of the ring current during periodic loading‐unloading cycles in the magnetotail driven by steady southward interplanetary magnetic field

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95239/1/jgra18825.pd

Effect of multiple substorms on the buildup of the ring current

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95361/1/jgra17662.pd

Recurrent Geomagnetic Storms and Relativistic Electron Enhancements in the Outer Magnetosphere: ISTP Coordinated Measurements

New, coordinated measurements from the International Solar-Terrestrial Physics (ISTP) constellation of spacecraft are presented to show the causes and effects of recurrent geomagnetic activity during recent solar minimum conditions. It is found using WIND and POLAR data that even for modest geomagnetic storms, relativistic electron fluxes are strongly and rapidly enhanced within the outer radiation zone of the Earth\u27s magnetosphere. Solar wind data are utilized to identify the drivers of magnetospheric acceleration processes. Yohkoh solar soft X-ray data are also used to identify the solar coronal holes that produce the high-speed solar wind streams which, in turn, cause the recurrent geomagnetic activity. It is concluded that even during extremely quiet solar conditions (sunspot minimum) there are discernible coronal holes and resultant solar wind streams which can produce intense magnetospheric particle acceleration. As a practical consequence of this Sun-Earth connection, it is noted that a long-lasting E\u3e1MeV electron event in late March 1996 appears to have contributed significantly to a major spacecraft (Anik E1) operational failure

Nitrate regulates floral induction in Arabidopsis, acting independently of light, gibberellin and autonomous pathways

The transition from vegetative growth to reproduction is a major developmental event in plants. To maximise reproductive success, its timing is determined by complex interactions between environmental cues like the photoperiod, temperature and nutrient availability and internal genetic programs. While the photoperiod- and temperature- and gibberellic acid-signalling pathways have been subjected to extensive analysis, little is known about how nutrients regulate floral induction. This is partly because nutrient supply also has large effects on vegetative growth, making it difficult to distinguish primary and secondary influences on flowering. A growth system using glutamine supplementation was established to allow nitrate to be varied without a large effect on amino acid and protein levels, or the rate of growth. Under nitrate-limiting conditions, flowering was more rapid in neutral (12/12) or short (8/16) day conditions in C24, Col-0 and Laer. Low nitrate still accelerated flowering in late-flowering mutants impaired in the photoperiod, temperature, gibberellic acid and autonomous flowering pathways, in the fca co-2 ga1-3 triple mutant and in the ft-7 soc1-1 double mutant, showing that nitrate acts downstream of other known floral induction pathways. Several other abiotic stresses did not trigger flowering in fca co-2 ga1-3, suggesting that nitrate is not acting via general stress pathways. Low nitrate did not further accelerate flowering in long days (16/8) or in 35S::CO lines, and did override the late-flowering phenotype of 35S::FLC lines. We conclude that low nitrate induces flowering via a novel signalling pathway that acts downstream of, but interacts with, the known floral induction pathways

Antagonistic Roles of SEPALLATA3, FT and FLC Genes as Targets of the Polycomb Group Gene CURLY LEAF

In Arabidopsis, mutations in the Pc-G gene CURLY LEAF (CLF) give early flowering plants with curled leaves. This phenotype is caused by mis-expression of the floral homeotic gene AGAMOUS (AG) in leaves, so that ag mutations largely suppress the clf phenotype. Here, we identify three mutations that suppress clf despite maintaining high AG expression. We show that the suppressors correspond to mutations in FPA and FT, two genes promoting flowering, and in SEPALLATA3 (SEP3) which encodes a co-factor for AG protein. The suppression of the clf phenotype is correlated with low SEP3 expression in all case and reveals that SEP3 has a role in promoting flowering in addition to its role in controlling floral organ identity. Genetic analysis of clf ft mutants indicates that CLF promotes flowering by reducing expression of FLC, a repressor of flowering. We conclude that SEP3 is the key target mediating the clf phenotype, and that the antagonistic effects of CLF target genes masks a role for CLF in promoting flowering

Example of forepaw trajectories during three consecutive grooming episodes.

<p><b>(A)</b> Example of forepaw trajectories detected for the left (top) and right forepaw (bottom) during individual grooming episodes, using M-Track. The color coding of each trajectory represents the speed with which the forepaw is moved. Although the area of the body groomed varies across episodes, the average grooming speed remains similar for the left and right forepaws across grooming episodes. The speed values represent mean ± S.D. <b>(B)</b> Image plots obtained from grooming trajectories for the left (top) and right (bottom) forepaws. The color of the image represents the number of times that the trajectory of the forepaw has moved over a given pixel. <b>(C)</b> x,y-displacements for each forepaw during individual grooming episodes. <b>(D)</b> Frequency count histogram of the frame-to-frame displacements for the left and right forepaws. We observed a high level of correlation for each one of the recorded grooming episodes (Pearson’s correlation coefficient: r = 0.95±0.03 (n = 3)).</p

M-Track analysis of grooming trajectories in mice exposed to 30 min restraint stress.

<p>The M-Track analysis reveals that the grooming trajectory length of the left and right forepaws is significantly increased following exposure to restraint stress (Control: left forepaw 17.2 ± 4.4 mm, right forepaw 20.9 ± 6.4 mm (n = 9); Restraint: left forepaw 935.3 ± 273.3 mm, right forepaw 990.6 ± 229.6 mm (n = 9); left *p = 0.010, right **p = 0.003).</p

Accuracy of M-Track detection of forepaw position using different HSV settings.

<p>The data included in this figure were used to estimate how accurately M-Track detects the position of the forepaws labelled with different colors (Neon green and Neon magenta), using tight and looser limits for the H, S, or V parameters. The data shows the effect that loosening the HSV settings has on the detected position of the forepaws <b>(A)</b>, the correlation coefficient of the forepaw trajectories detected with optimal and offset HSV settings along the x <b>(B)</b> and y dimensions <b>(C)</b>, the number of frames dropped <b>(D)</b> and the length of time for which the frames are dropped <b>(E)</b>. Pixel size: 0.21 mm.</p