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9 results for “microcolony”
Consumption of pollen contaminated with field-realistic concentrations of fungicide cause sub-lethal effects in common eastern bumble bee (Bombus impatiens [Hymenoptera]: [Apidae]) microcolonies
<p>Bumble bees are declining across the globe. Causes of this decline have been attributed to a variety of stressors, including pesticides. Fungicides are a type of pesticide that have been understudied in the context of bumble bee health. As a result, fungicides are often applied to flowering plants without consideration of pollinator exposure. Recent work demonstrates that fungicides have sublethal effects in bumble bees, but little is known about how much fungicide it takes to cause these sublethal effects. To address this gap in the literature, we fed microcolonies of the common eastern bumble bee (<em>Bombus impatiens</em>) pollen contaminated with a range of fungicide concentrations. We chose these concentrations based on the range of fungicide concentrations in pollen and nectar that were reported in the literature. Results revealed that later-stage pupae and newly emerged males are potentially sensitive to fungicide exposure, showing smaller size and reduced fat reserves at intermediate levels of contamination. Compared to the control, intermediated levels of fungicide-contaminated pollen led to increased pupal mortality and delayed male emergence. Contrary to expectations, higher fungicide levels did not exhibit a linear relationship with negative impacts, suggesting nuanced effects. Because body size and emergence timing are important aspects of bumble bee reproductive behavior, results have implications for mating success, potentially disrupting colony development.</p>
Consumption of pollen contaminated with field-realistic concentrations of fungicide cause sub-lethal effects in common eastern bumble bee (Bombus impatiens [Hymenoptera]: [Apidae]) microcolonies
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Data from: The presence of bacterial microcolonies on the maxillary sinus ciliary epithelium in healthy young individuals
Objective: The aim of this cross-sectional in vitro study was to evaluate the mucosal surfaces of healthy maxillary sinuses, explore different forms of bacterial microorganism colonies present on the mucous membrane, and determine a mucosal surface area they occupy. Methods: Samples of the maxillary sinus mucosa were collected from 30 healthy patients (M=11; F=19). The material was obtained during the Le Fort I osteotomy performed during corrective jaw surgery. The morphological and morphometric analysis of sinus mucosa and bacterial film that was grown on it was performed using scanning electron microscopy (SEM) as well as imaging software. Results: Scanning electron microscopy analysis showed the presence of different bacterium and bacteria-like structures in all the analyzed samples. In most cases, the bacterial film was mostly composed of diplococci-like and streptococci-like structures on the mucosa of the paranasal sinus. In any case, the mucous layer did not cover the whole lining of the evaluated sample. Each colony consists of more than 20 single bacterial cells, which has grown in aggregates. Conclusions: Under the conditions of normal homeostasis of the body, the maxillary sinuses present diverse bacterial colonization. The bacteria are dispersed or concentrated in single microcolonies of the biofilm on the border of the mucous covering the ciliary epithelium. There is no uniform layer of the biofilm covering the mucosa of the maxillary sinuses. Because the biofilm is detected on healthy individuals sinus mucosa, the clinical question if it may become pathogenic is unclear and require an explanation.
Data from: The presence of bacterial microcolonies on the maxillary sinus ciliary epithelium in healthy young individuals
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Dataset and scripts belonging to "Inferring Bacterial Interspecific Interactions from Microcolony Growth Expansion"
<p>Dataset and corresponding analysis scripts underlying the manuscript</p> <p><strong><span>Inferring Bacterial Interspecific Interactions from Microcolony Growth Expansion</span></strong></p> <p><span>by</span></p> <p><span>Tania Miguel Trabajo<sup>1</sup>, Isaline Guex<sup>1,2</sup>, Manupriyam Dubey<sup>1</sup>, Elvire Sarton-Lohéac<sup>1</sup>, Helena Todorov<sup>1</sup>, Xavier Richard<sup>2</sup>, Christian Mazza<sup>2</sup>, Jan Roelof van der Meer<sup>1*</sup></span></p> <p><span>Department of Fundamental Microbiology, University of Lausanne</span></p> <p><span>Department of Mathematics, University of Fribourg</span></p> <p> </p> <p>Readme - main folder structure</p> <p>This dataset and corresponding scripts has six main folders. Within the main folders are further Readme-files for the content of the subfolders.</p> <p>/Colony_segmentation: <br>Contains the python script and instructions on how to segment a TIF set of images from time lapse, and calculate the colony expansion rates, areas and positions from the segmented .npy stack.</p> <p>/data_processing:<br>Contains the main subfolders for the segmented colonies and derived data from all experiments, the corresponding scripts, output plots or .csv tables with data shown in the paper, and a list per figure, table or supplementary on how those data were derived with the indicated scripts.</p> <p>/flow_cytometry_data:<br>Has the data and the processing of the flow cytometry quantification of cells washed from the surface of the patches for the relevant experiments shown in the paper.</p> <p>/Imaging_data:<br>Has subfolders with the individual experiments used for the paper. Subfolder will contain the .npy segmented stacked files and the derived data plus individualized local scripts.</p> <p>/LCMS_data:<br>Has the data and the processing of the growth of the mono-cultures and the swapped supernatants, and the derived LCMS tables with the peak areas in the different samples, as shown in the paper.</p> <p>/Surface_model:<br>Has the actual surface model script and the results of the various simulations. </p>
Transcriptional analysis of wild-type budding yeast microcolonies encapsulated in alginate particles
GEO Series GSE72092. Saccharomyces cerevisiae. 16 samples. Type: Expression profiling by high throughput sequencing.
Candida albicans Sfl1/Sfl2 regulatory network drives the formation of pathogenic microcolonies.
GEO Series GSE117433. Candida albicans. 6 samples. Type: Expression profiling by high throughput sequencing.
Microcolony formation by the opportunistic pathogen Pseudomonas aeruginosa requires pyruvate and pyruvate fermentation.
GEO Series GSE35286. Pseudomonas aeruginosa. 6 samples. Type: Expression profiling by array.
A new global repressor (bvlR) of pathogenicity and tight microcolony formation in P. aeruginosa
GEO Series GSE51491. Pseudomonas aeruginosa PA14; Pseudomonas aeruginosa. 6 samples. Type: Expression profiling by array.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.