scholarly journals Fine-Tuning Motile Cilia and Flagella: Evolution of the Dynein Motor Proteins from Plants to Humans at High Resolution

2016 ◽  
Vol 33 (12) ◽  
pp. 3249-3267 ◽  
Author(s):  
Martin Kollmar
Keyword(s):  
High Resolution ◽  
Motor Proteins ◽  
Fine Tuning ◽  
Dynein Motor ◽  
Motile Cilia ◽  
Cilia And Flagella

scholarly journals Cholesterol sensor ORP1L contacts the ER protein VAP to control Rab7–RILP–p150Glued and late endosome positioning

2009 ◽  
Vol 185 (7) ◽  
pp. 1209-1225 ◽  
Author(s):  
Nuno Rocha ◽  
Coenraad Kuijl ◽  
Rik van der Kant ◽  
Lennert Janssen ◽  
Diane Houben ◽  
...  
Keyword(s):  
Motor Proteins ◽  
Oxysterol Binding Protein ◽  
Membrane Contact Sites ◽  
Cholesterol Levels ◽  
Dynein Motor ◽  
Late Endosomes ◽  
In Trans ◽  
Membrane Contact ◽  
Cholesterol Control ◽  
Niemann Pick

Late endosomes (LEs) have characteristic intracellular distributions determined by their interactions with various motor proteins. Motor proteins associated to the dynactin subunit p150Glued bind to LEs via the Rab7 effector Rab7-interacting lysosomal protein (RILP) in association with the oxysterol-binding protein ORP1L. We found that cholesterol levels in LEs are sensed by ORP1L and are lower in peripheral vesicles. Under low cholesterol conditions, ORP1L conformation induces the formation of endoplasmic reticulum (ER)–LE membrane contact sites. At these sites, the ER protein VAP (VAMP [vesicle-associated membrane protein]-associated ER protein) can interact in trans with the Rab7–RILP complex to remove p150Glued and associated motors. LEs then move to the microtubule plus end. Under high cholesterol conditions, as in Niemann-Pick type C disease, this process is prevented, and LEs accumulate at the microtubule minus end as the result of dynein motor activity. These data explain how the ER and cholesterol control the association of LEs with motor proteins and their positioning in cells.

scholarly journals Ship Classification in High-Resolution SAR Images Using Deep Learning of Small Datasets

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2929 ◽  
Author(s):  
Yuanyuan Wang ◽  
Chao Wang ◽  
Hong Zhang
Keyword(s):  
Deep Learning ◽  
High Resolution ◽  
Classification Accuracy ◽  
Experimental Results ◽  
Fine Tuning ◽  
Classification Model ◽  
Great Success ◽  
Sar Images ◽  
Convolutional Networks ◽  
Ship Classification

With the capability to automatically learn discriminative features, deep learning has experienced great success in natural images but has rarely been explored for ship classification in high-resolution SAR images due to the training bottleneck caused by the small datasets. In this paper, convolutional neural networks (CNNs) are applied to ship classification by using SAR images with the small datasets. First, ship chips are constructed from high-resolution SAR images and split into training and validation datasets. Second, a ship classification model is constructed based on very deep convolutional networks (VGG). Then, VGG is pretrained via ImageNet, and fine tuning is utilized to train our model. Six scenes of COSMO-SkyMed images are used to evaluate our proposed model with regard to the classification accuracy. The experimental results reveal that (1) our proposed ship classification model trained by fine tuning achieves more than 95% average classification accuracy, even with 5-cross validation; (2) compared with other models, the ship classification model based on VGG16 achieves at least 2% higher accuracies for classification. These experimental results reveal the effectiveness of our proposed method.

scholarly journals The mouse ortholog of EFHC1 implicated in juvenile myoclonic epilepsy is an axonemal protein widely conserved among organisms with motile cilia and flagella

FEBS Letters ◽  
2005 ◽  
Vol 579 (3) ◽  
pp. 819-822 ◽  
Author(s):  
Takashi Ikeda ◽  
Kazuho Ikeda ◽  
Masahiro Enomoto ◽  
Min Kyun Park ◽  
Masafumi Hirono ◽  
...  
Keyword(s):  
Juvenile Myoclonic Epilepsy ◽  
Myoclonic Epilepsy ◽  
Motile Cilia ◽  
Cilia And Flagella

scholarly journals Agricultural Greenhouses Detection in High-Resolution Satellite Images Based on Convolutional Neural Networks: Comparison of Faster R-CNN, YOLO v3 and SSD

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4938
Author(s):  
Min Li ◽  
Zhijie Zhang ◽  
Liping Lei ◽  
Xiaofan Wang ◽  
Xudong Guo
Keyword(s):  
High Resolution ◽  
Visual Inspection ◽  
Satellite Images ◽  
High Spatial Resolution ◽  
Fine Tuning ◽  
Single Shot ◽  
Modern Agriculture ◽  
High Resolution Satellite Images ◽  
Independent Test ◽  
Test Sets

Agricultural greenhouses (AGs) are an important facility for the development of modern agriculture. Accurately and effectively detecting AGs is a necessity for the strategic planning of modern agriculture. With the advent of deep learning algorithms, various convolutional neural network (CNN)-based models have been proposed for object detection with high spatial resolution images. In this paper, we conducted a comparative assessment of the three well-established CNN-based models, which are Faster R-CNN, You Look Only Once-v3 (YOLO v3), and Single Shot Multi-Box Detector (SSD) for detecting AGs. The transfer learning and fine-tuning approaches were implemented to train models. Accuracy and efficiency evaluation results show that YOLO v3 achieved the best performance according to the average precision (mAP), frames per second (FPS) metrics and visual inspection. The SSD demonstrated an advantage in detection speed with an FPS twice higher than Faster R-CNN, although their mAP is close on the test set. The trained models were also applied to two independent test sets, which proved that these models have a certain transability and the higher resolution images are significant for accuracy improvement. Our study suggests YOLO v3 with superiorities in both accuracy and computational efficiency can be applied to detect AGs using high-resolution satellite images operationally.

scholarly journals Mechanisms for focusing mitotic spindle poles by minus end–directed motor proteins

2005 ◽  
Vol 171 (2) ◽  
pp. 229-240 ◽  
Author(s):  
Gohta Goshima ◽  
François Nédélec ◽  
Ronald D. Vale
Keyword(s):  
Rna Interference ◽  
High Resolution ◽  
Computer Modeling ◽  
Mitotic Spindle ◽  
Motor Proteins ◽  
Spindle Pole ◽  
S2 Cells ◽  
Spindle Poles ◽  
Drosophila S2 Cells ◽  
High Resolution Microscopy

During the formation of the metaphase spindle in animal somatic cells, kinetochore microtubule bundles (K fibers) are often disconnected from centrosomes, because they are released from centrosomes or directly generated from chromosomes. To create the tightly focused, diamond-shaped appearance of the bipolar spindle, K fibers need to be interconnected with centrosomal microtubules (C-MTs) by minus end–directed motor proteins. Here, we have characterized the roles of two minus end–directed motors, dynein and Ncd, in such processes in Drosophila S2 cells using RNA interference and high resolution microscopy. Even though these two motors have overlapping functions, we show that Ncd is primarily responsible for focusing K fibers, whereas dynein has a dominant function in transporting K fibers to the centrosomes. We also report a novel localization of Ncd to the growing tips of C-MTs, which we show is mediated by the plus end–tracking protein, EB1. Computer modeling of the K fiber focusing process suggests that the plus end localization of Ncd could facilitate the capture and transport of K fibers along C-MTs. From these results and simulations, we propose a model on how two minus end–directed motors cooperate to ensure spindle pole coalescence during mitosis.

scholarly journals DEEP LEARNING BASED ROOF TYPE CLASSIFICATION USING VERY HIGH RESOLUTION AERIAL IMAGERY

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 55-60
Author(s):  
M. Buyukdemircioglu ◽  
R. Can ◽  
S. Kocaman
Keyword(s):  
Deep Learning ◽  
High Resolution ◽  
Urban Areas ◽  
Image Features ◽  
Training Data ◽  
Fine Tuning ◽  
Computer Hardware ◽  
Geographical Information ◽  
Training Dataset ◽  
Very High

Abstract. Automatic detection, segmentation and reconstruction of buildings in urban areas from Earth Observation (EO) data are still challenging for many researchers. Roof is one of the most important element in a building model. The three-dimensional geographical information system (3D GIS) applications generally require the roof type and roof geometry for performing various analyses on the models, such as energy efficiency. The conventional segmentation and classification methods are often based on features like corners, edges and line segments. In parallel to the developments in computer hardware and artificial intelligence (AI) methods including deep learning (DL), image features can be extracted automatically. As a DL technique, convolutional neural networks (CNNs) can also be used for image classification tasks, but require large amount of high quality training data for obtaining accurate results. The main aim of this study was to generate a roof type dataset from very high-resolution (10 cm) orthophotos of Cesme, Turkey, and to classify the roof types using a shallow CNN architecture. The training dataset consists 10,000 roof images and their labels. Six roof type classes such as flat, hip, half-hip, gable, pyramid and complex roofs were used for the classification in the study area. The prediction performance of the shallow CNN model used here was compared with the results obtained from the fine-tuning of three well-known pre-trained networks, i.e. VGG-16, EfficientNetB4, ResNet-50. The results show that although our CNN has slightly lower performance expressed with the overall accuracy, it is still acceptable for many applications using sparse data.

scholarly journals How signals of calcium ions initiate the beats of cilia and flagella

2019 ◽  
Author(s):  
M. V. Satarić ◽  
T. Nemeš ◽  
D. Sekulić ◽  
J. A. Tuszynski
Keyword(s):  
Atp Hydrolysis ◽  
Cellular Motility ◽  
Cell Organelles ◽  
Ciliary Movement ◽  
Ciliary Function ◽  
Dynein Motor ◽  
Combined Action ◽  
Axonemal Dynein ◽  
Cilia And Flagella

ABSTRACTCilia and flagella are cell organelles serving basic roles in cellular motility. Ciliary movement is performed by a sweeping-like repeated bending motion, which gives rise to a self-propagating “ciliary beat”. The hallmark structure in cilia is the axoneme, a stable architecture of microtubule doublets. The motion of axoneme is powered by the axonemal dynein motor family powered by ATP hydrolysis. It is still unclear how the organized beat of cilium and flagella emerges from the combined action of hundreds of dynein molecules. It has been hypothesized that such coordination is mediated by mechanical stress due to transverse, radial or sliding deformations. The beating asymmetry is crucial for airway ciliary function and it requires tubulin glutamination a unique posttranslational modification of C-termini of constituent microtubules that is highly abundant in cilia and flagella. The exact role of tubulin glutamination in ciliary or flagellar function is still unclear. Here we examine the role of calcium (Ca2+) ions based on the experimental evidences that the flagellar asymmetry can be increased due to the entry of extracellular Ca2+through, for example, nimodipine-sensitive pathway located in the flagella. We propose a new scenario based on the polyelectrolyte properties of cellular microtubules (MTs) such that dynamic influx of Ca2+ions provides the initiation and synchronization of dynein sliding along microtubules. We also point out the possible interplay between tubulin polyglutaminated C-termini and localized pulses of Ca2+ions along microtubules.

scholarly journals Bidirectional intraflagellar transport is restricted to two sets of microtubule doublets in the trypanosome flagellum

2018 ◽  
Author(s):  
Eloïse Bertiaux ◽  
Adeline Mallet ◽  
Cécile Fort ◽  
Thierry Blisnick ◽  
Serge Bonnefoy ◽  
...  
Keyword(s):  
High Resolution ◽  
Focused Ion Beam ◽  
Protein Complexes ◽  
Ion Beam ◽  
Intraflagellar Transport ◽  
Sem Analysis ◽  
Large Individual ◽  
Resolution Electron ◽  
Cilia And Flagella ◽  
Bidirectional Movement

SummaryIntraflagellar transport (IFT) is the rapid bidirectional movement of large protein complexes driven by kinesin and dynein motors along microtubule doublets of cilia and flagella. Here we used a combination of high-resolution electron and light microscopy to investigate how and where these IFT trains move within the flagellum of the protist Trypanosoma brucei. Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) analysis of trypanosomes showed that trains are found almost exclusively along two sets of doublets (3-4 and 7-8) and distribute in two categories according to their length. High-resolution live imaging of cells expressing mNeonGreen::IFT81 or GFP::IFT52 revealed for the first time IFT trafficking on two parallel lines within the flagellum. Anterograde and retrograde IFT occur on each of these lines. At the distal end, a large individual anterograde IFT train is converted in several smaller retrograde trains in the space of 3-4 seconds while remaining on the same side of the axoneme.

scholarly journals Multi-strategic RNA-seq analysis reveals a high-resolution transcriptional landscape in cotton

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Kun Wang ◽  
Dehe Wang ◽  
Xiaomin Zheng ◽  
Ai Qin ◽  
Jie Zhou ◽  
...  
Keyword(s):  
High Resolution ◽  
Natural Fiber ◽  
Binding Activity ◽  
Fine Tuning ◽  
Specific Gene ◽  
Rna Seq ◽  
Gene Map ◽  
Dna Binding Activity ◽  
Genomic Studies ◽  
Gene Structures

Abstract Cotton is an important natural fiber crop, however, its comprehensive and high-resolution gene map is lacking. Here we integrate four complementary high-throughput techniques, including Pacbio long read Iso-seq, strand-specific RNA-seq, CAGE-seq, and PolyA-seq, to systematically explore the transcription landscape across 16 tissues or different organ types in Gossypium arboreum. We devise a computational pipeline, named IGIA, to reconstruct accurate gene structures from the integrated data. Our results reveal a dynamic and diverse transcriptional map in cotton: tissue-specific gene expression, alternative usage of TSSs and polyadenylation sites, hotspot of alternative splicing, and transcriptional read-through. These regulated events affect many genes in various aspects such as gain or loss of functional RNA motifs and protein domains, fine-tuning of DNA binding activity, and co-regulation for genes in the same complex or pathway. The methods and findings provide valuable resources for further functional genomic studies such as understanding natural SNP variations for plant community.

Proteomic analysis of microtubule inner proteins (MIPs) in Rib72 null Tetrahymena cells reveals functional MIPs

2020 ◽  
Author(s):  
Amy S. Fabritius ◽  
Brian A. Bayless ◽  
Sam Li ◽  
Daniel Stoddard ◽  
Westley Heydeck ◽  
...  
Keyword(s):  
Proteomic Analysis ◽  
Tetrahymena Thermophila ◽  
Electron Tomography ◽  
Functional Characterization ◽  
Ciliary Beating ◽  
Ciliary Function ◽  
Cryo Electron Tomography ◽  
Motile Cilia ◽  
Cilia And Flagella ◽  
Stable Populations

AbstractMotile cilia and flagella are built from stable populations of doublet microtubules that comprise their axonemes. Their unique stability is brought about, at least in part, by a network of Microtubule Inner Proteins (MIPs) found in the lumen of their doublet microtubules. Rib72A and Rib72B were identified as microtubule inner proteins (MIPs) in the motile cilia of Tetrahymena thermophila. Loss of these proteins leads to ciliary defects and loss of multiple MIPs. We performed mass spectrometry coupled with proteomic analysis and bioinformatics to identify the MIPs lost in RIB72A/B knockout (KO) Tetrahymena cells. From this analysis we identified a number of candidate MIPs and pursued one, Fap115, for functional characterization. We find that loss of Fap115 results in disrupted cell swimming and aberrant ciliary beating. Cryo-electron tomography reveals that Fap115 localizes to MIP6a in the A-tubule of the doublet microtubules. Overall, our results highlight the complex relationship between MIPs, ciliary structure, and ciliary function.

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