Academic literature on the topic 'Time-lapse biological experiment'

Although dragonflies are excellent environmental indicators for monitoring terrestrial water ecosystems, automatic monitoring techniques using digital tools are limited. We designed a novel camera trapping system with an original dragonfly detector based on the hypothesis that perching dragonflies can be automatically detected using inexpensive and energy-saving photosensors built in a perch-like structure. A trial version of the camera trap was developed and evaluated in a case study targeting red dragonflies (Sympetrum spp.) in Japan. During an approximately 2-month period, the detector successfully detected Sympetrum dragonflies while using extremely low power consumption (less than 5 mW). Furthermore, a short-term field experiment using time-lapse cameras for validation at three locations indicated that the detection accuracy was sufficient for practical applications. The frequency of false positive detection ranged from 17 to 51 over an approximately 2-day period. The detection sensitivities were 0.67 and 1.0 at two locations, where a time-lapse camera confirmed that Sympetrum dragonflies perched on the trap more than once. However, the correspondence between the detection frequency by the camera trap and the abundance of Sympetrum dragonflies determined by field observations conducted in parallel was low when the dragonfly density was relatively high. Despite the potential for improvements in our camera trap and its application to the quantitative monitoring of dragonflies, the low cost and low power consumption of the detector make it a promising tool.

The objective of this work was to analyze the effect of water content on the removal of volatile organic compounds (VOCs) in gas phase trickle-bed biofilters. Previous studies revealed that excessive accumulation of biomass in the reactor had a negative effect on contaminant removal efficiency. To solve this problem, periodic backwash was used to remove excess biomass and maintain an effective operation. Results showed that the ether removal efficiency dropped immediately after backwashing and gradually improved to reach the optimal value within about 24 hours. The initial drop in performance can be attributed to biological effects, such as loss of active biomass and the necessity for an adaptation period for the microbial culture. However, mass transfer limitations due to the water retained in the reactor may also be important. To investigate the effect of water content on the biofilter performance, an experiment evaluated the effect of draining after backwashing was conducted. Biofilters were allowed to drain for different periods of time before restarting the reactors. A longer lapse time in draining before the restart resulted in better ether removal efficiency. The improvement of biofilter performance after backwashing was explained with a combination of biological and physical effects. A mathematical model was then used to simulate the performance of the biofilter under these conditions and to support the conclusions obtained. The mathematical model considered a three-phase system (biofilm, water, and gas phase), dunamic processes, non-uniform bacterial population, and one limiting substrate.

Concentrations of airborne chemical and biological agents from a hazardous release are not spread uniformly. Instead, there are regions of higher concentration, in part due to local atmospheric flow conditions which can attract agents. We equipped a ground station and two rotary-wing unmanned aircraft systems (UASs) with ultrasonic anemometers. Flights reported here were conducted 10 to 15 m above ground level (AGL) at the Leach Airfield in the San Luis Valley, Colorado as part of the Lower Atmospheric Process Studies at Elevation—a Remotely-Piloted Aircraft Team Experiment (LAPSE-RATE) campaign in 2018. The ultrasonic anemometers were used to collect simultaneous measurements of wind speed, wind direction, and temperature in a fixed triangle pattern; each sensor was located at one apex of a triangle with ∼100 to 200 m on each side, depending on the experiment. A WRF-LES model was used to determine the wind field across the sampling domain. Data from the ground-based sensors and the two UASs were used to detect attracting regions (also known as Lagrangian Coherent Structures, or LCSs), which have the potential to transport high concentrations of agents. This unique framework for detection of high concentration regions is based on estimates of the horizontal wind gradient tensor. To our knowledge, our work represents the first direct measurement of an LCS indicator in the atmosphere using a team of sensors. Our ultimate goal is to use environmental data from swarms of sensors to drive transport models of hazardous agents that can lead to real-time proper decisions regarding rapid emergency responses. The integration of real-time data from unmanned assets, advanced mathematical techniques for transport analysis, and predictive models can help assist in emergency response decisions in the future.

A variety of biological and pharmaceutical studies, such as for anti-cancer drugs, require the quantification of cell responses over long periods of time. This is performed with time-lapse video microscopy that gives a long sequence of frames. For this purpose, phase contrast imaging is commonly used since it is minimally invasive. The cell responses of interest in this study are the mitotic cell divisions. Their manual measurements are tedious, subjective, and restrictive. This study introduces an automated method for these measurements. The method starts with preprocessing for restoration and reconstruction of the phase contrast time-lapse sequences. The data are first restored from intensity non-uniformities. Subsequently, the circular symmetry of the contour of the mitotic cells in phase contrast images is used by applying a Circle Hough Transform (CHT) to reconstruct the entire cells. The CHT is also enhanced with the ability to “vote” exclusively towards the center of curvature. The CHT image sequence is then registered for misplacements between successive frames. The sequence is subsequently processed to detect cell centroids in individual frames and use them as starting points to form spatiotemporal trajectories of cells along the positive as well as along the negative time directions, that is, anti-causally. The connectivities of different trajectories enhanced by the symmetry of the trajectories of the daughter cells provide as topological by-products the events of cell divisions together with the corresponding entries into mitoses as well as exits from cytokineses. The experiments use several experimental video sequences from three different cell lines with many cells undergoing mitoses and divisions. The quantitative validations of the results of the processing demonstrate the high performance and efficiency of the method.

Microfluidic-based assays have become effective high-throughput approaches to examining replicative aging of budding yeast cells. Deep learning may offer an efficient way to analyze a large number of images collected from microfluidic experiments. Here, we compare three deep learning architectures to classify microfluidic time-lapse images of dividing yeast cells into categories that represent different stages in the yeast replicative aging process. We found that convolutional neural networks outperformed capsule networks in terms of accuracy, precision, and recall. The capsule networks had the most robust performance in detecting one specific category of cell images. An ensemble of three best-fitted single-architecture models achieves the highest overall accuracy, precision, and recall due to complementary performances. In addition, extending classification classes and data augmentation of the training dataset can improve the predictions of the biological categories in our study. This work lays a useful framework for sophisticated deep-learning processing of microfluidic-based assays of yeast replicative aging.

Colorimetric sensing techniques for point(s), linear and areal array(s) were developed using image sensors and novel image processing software for chemical, biological and medical applications. Monitoring and recording of colorimetric information on one or more specimens can be carried out by specially designed image processing software. The colorimetric information on real-time monitoring and recorded images or video clips can be analyzed for point(s), line(s) and area(s) of interest for manual and automatic data collection. Ex situ and in situ colorimetric data can be used as signals for process control, process optimization, safety and security alarms, and inputs for machine learning, including artificial intelligence. As an analytical example, video clips of chromatographic experiments using different colored inks on filter papers dipped in water and randomly blinking light-emitting-diode-based decorative lights were used. The colorimetric information on points, lines and areas, with different sizes from the video clips, were extracted and analyzed as a function of time. The video analysis results were both visualized as time-lapse images and RGB (red, green, blue) color/intensity graphs as a function of time. As a demonstration of the developed colorimetric analysis technique, the colorimetric information was expressed as static and time-series combinations of RGB intensity, HSV (hue, saturation and value) and CIE L*a*b* values. Both static and dynamic colorimetric analysis of photographs and/or video files from image sensors were successfully demonstrated using a novel image processing software.

Neurons, with their long axons and elaborate dendritic arbour, establish the complex circuitry that is essential for the proper functioning of the nervous system. Whereas a catalogue of structural, molecular, and functional differences between axons and dendrites is accumulating, the mechanisms involved in early events of neuronal differentiation, such as neurite initiation and elongation, are less well understood, mainly because the key molecules involved remain elusive. Here we describe the establishment and application of a microscopy-based approach designed to identify novel proteins involved in neurite initiation and/or elongation. We identified 21 proteins that affected neurite outgrowth when ectopically expressed in cells. Complementary time-lapse microscopy allowed us to discriminate between early and late effector proteins. Localization experiments with GFP-tagged proteins in fixed and living cells revealed a further 14 proteins that associated with neurite tips either early or late during neurite outgrowth. Coexpression experiments of the new effector proteins provide a first glimpse on a possible functional relationship of these proteins during neurite outgrowth. Altogether, we demonstrate the potential of the systematic microscope-based screening approaches described here to tackle the complex biological process of neurite outgrowth regulation.

Background: It has been shown that many plant- or microbial-derived oligos and polysaccharides may prompt tissue repair. Among the different extracts that have been studied, the aqueous one of Triticum vulgare (TVE) that was obtained from a whole germinated plant has been proven to have different biological properties that are useful in the process of wound healing. Nevertheless, with the long tradition of its use in pharmaceutical cream and ointments, especially in Italy, a new protocol was recently proposed (and patented) to improve the extraction process. Methods: In a simplified in vitro model, human keratinocyte monolayers were scratched and used to run time lapse experiments by using time lapse video microscopy (TLVM) to quantify reparation rate while considering a dose–response effect. Contemporarily, the molecular mechanisms that are involved in tissue repair were studied. In fact, key biomarkers that are involved in remodeling, such as MMP-2 and MMP-9, and in matrix structure assembly, such as collagen I, elastin, integrin αV and aquaporin 3, were evaluated with gene expression analyses (RT-PCR) and protein quantification in western blotting. Results: All TVE doses tested on the HaCat-supported cell proliferation. TVE also prompted cell migration in respect to the control, correctly modulating the timing of metalloproteases expression toward a consistent and well-assessed matrix remodeling. Furthermore, TVE treatments upregulated and positively modulated the expression of the analyzed biomarkers, thus resulting in a better remodeling of dermal tissue during healing. Conclusions: The in vitro results on the beneficial effects of TVE on tissue elasticity and regeneration may support a better understanding of the action mechanism of TVE as active principles in pharmaceutical preparation in wound treatment.

Despite extensive international acceptance of the critical role of mammalian post-dispersal seed predation in many plant communities, in New Zealand we have limited knowledge of these predators’ influence on plant recruitment in our forests. The principle objective of my thesis was to determine the importance of exotic mammals as post-dispersal seed predators in a New Zealand conifer-broadleaf forest remnant. To address this goal, I used a series of field-based experiments where the actions of different post-dispersal seed predators were separated by wire-mesh exclosures. My study was conducted at Mount Peel Forest Park Scenic Reserve, South Canterbury, New Zealand. Being a human modified conifer forest currently dominated by broadleaf species, it is typical of forest remnants in New Zealand. This presented an opportunity to study a wide range of both potential post-dispersal seed predators and broadleaf tree species. My findings indicate that exotic mammals are not only post-dispersal seed predators at Peel Forest, but are responsible for the majority of post-dispersal predation events observed. Ship rats (Rattus rattus) were the dominant post-dispersal seed predators, while brushtail possums (Trichosurus vulpecula), house mice (Mus musculus) and native invertebrates were also important post-dispersal seed predators for several tree species. Through use of time-lapse video and cafeteria experiments I found that exotic mammalian seed predators, when compared to native invertebrate seed predators, preyed upon larger-seeded plant species and were responsible for considerable seed losses of several tree species. However, exotic mammalian seed predators do share several foraging characteristics with native invertebrate seed predators, as predators foraged in similar habitats and responded in a similar way to changes in seed density. In investigating if post-dispersal seed predation by mammals had a flow-on effect to plant recruitment, I observed natural seedling densities at Peel Forest were significantly higher in the absence of mammalian seed predators, but I found no evidence that the presence of mammals significantly altered the overall species richness. At the community level, I did not find an interaction between habitat and exotic mammals, however I present evidence that for individual plant species a significant mammal : habitat interaction occurred. Consequently, even though my cafeteria experiment implied there was no significant difference in the overall amount of seed preyed upon within different habitats, the less favourable microsite conditions for germination under an intact continuous canopy allows mammals to exacerbate habitat-related patterns of seed mortality and have a noticeable effect on seedling establishment. In an effort to validate the use of manipulative experiments to predict the long-term effect of post-dispersal seed predation on plant dynamics, I attempted to link results of my cafeteria experiment with observed seedling abundance at Peel Forest. Seven tree species were used in this comparison and a strong correlation was observed. This result shows that the level of post-dispersal seed predation determined in the cafeteria experiment provided a good predictor of the effect of mammalian post-dispersal seed predation on seedling establishment. To fully gauge the impact of mammalian post-dispersal seed predators on seedling establishment, the relationship between these seed predators and the type of recruitment limitation experienced by a plant species was also investigated. By using a combination of seed addition, plot manipulations and seed predator exclusion I was able to investigate this relationship. I found evidence that seed limitation at Peel Forest is positively correlated with seed size, and that while mammalian post-dispersal seed predators can further reduce plant recruitment of plant species experiencing seed limitation, the influence of mammals in determining plant recruitment was limited for plant species experiencing microsite limitation. My study has proven that exotic mammals are now the dominant post-dispersal seed predators at Peel Forest, the amount of seed preyed upon varies among plant species, and post-dispersal seed predation by mammalian species can lead to differences in seedling richness and abundance. I proved that the influence of exotic mammals on seedling establishment is also linked to habitat structure and recruitment limitations. When combined these observations suggest that exotic mammalian post-dispersal seed predators may play an important role in determining landscape abundance and distribution of plants at Peel Forest.