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Respiratory cilia are important components in the lung defense mechanism. The coordinated beating of cilia cleans the airways of pathogens and foreign particles. We present a large-scale validation dataset of cilia motion for characterizing ciliary function. Ciliary beat frequency (CBF) is provided as benchmark metrics. The video dataset of cilia motion phenotypes contains four categories: temperatures, drugs and ACE2 manipulation. Under each category, mouse trachea samples were treated with different stimuli and imaged with a high-speed video microscope to acquire cilia motion. In addition, we generate ground truth masks labeling ciliary area for image segmentation. This validation dataset can serve as a benchmark for the computer vision community to develop models for analyzing ciliary beat pattern. This video dataset contains 872 videos and their ground-truth masks with the ciliary area labeled. The videos were recorded at 250 frames per second for 1 second. The image size is 800x800. Each pixel is 0.07987 μm. The csv file contains the CBF values of each video.more » « less
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Abstract Background & Aims Cancer metastasis into distant organs is an evolutionarily selective process. A better understanding of the driving forces endowing proliferative plasticity of tumor seeds in distant soils is required to develop and adapt better treatment systems for this lethal stage of the disease. To this end, we aimed to utilize transcript expression profiling features to predict the site-specific metastases of primary tumors and second, to identify the determinants of tissue specific progression. Methods We used statistical machine learning for transcript feature selection to optimize classification and built tree-based classifiers to predict tissue specific sites of metastatic progression. Results We developed a novel machine learning architecture that analyzes 33 types of RNA transcriptome profiles from The Cancer Genome Atlas (TCGA) database. Our classifier identifies the tumor type, derives synthetic instances of primary tumors metastasizing to distant organs and classifies the site-specific metastases in 16 types of cancers metastasizing to 12 locations. Conclusions We have demonstrated that site specific metastatic progression is predictable using transcriptomic profiling data from primary tumors and that the overrepresented biological processes in tumors metastasizing to congruent distant loci are highly overlapping. These results indicate site-specific progression was organotropic and core features of biological signaling pathways are identifiable that may describe proliferative plasticity in distant soils.more » « less
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Abstract Ca2+is a universal intracellular signal that regulates many cellular functions. In
Toxoplasma gondii , the controlled influx of extracellular and intracellular Ca2+into the cytosol initiates a signaling cascade that promotes pathogenic processes like tissue destruction and dissemination. In this work, we studied the role of proton transport in cytosolic Ca2+homeostasis and the initiation of Ca2+signaling. We used aT. gondii mutant of the V‐H+‐ATPase, a pump previously shown to transport protons to the extracellular medium, and to control intracellular pH and membrane potential and we show that proton gradients are important for maintaining resting cytosolic Ca2+at physiological levels and for Ca2+influx. Proton transport was also important for Ca2+storage by acidic stores and, unexpectedly, the endoplasmic reticulum. Proton transport impacted the amount of polyphosphate (polyP), a phosphate polymer that binds Ca2+and concentrates in acidocalcisomes. This was supported by the co‐localization of the vacuolar transporter chaperone 4 (VTC4), the catalytic subunit of the VTC complex that synthesizes polyP, with the V‐ATPase in acidocalcisomes. Our work shows that proton transport regulates plasma membrane Ca2+transport and control acidocalcisome polyP and Ca2+content, impacting Ca2+signaling and downstream stimulation of motility and egress inT. gondii .