Coordinates in low-dimensional cell shape-space discriminate migration dynamics from single static cell images

Cell shape has long been used to discern cell phenotypes and states, but the underlying premise has not been quantitatively tested. Here, we show that a single cell image can be used to discriminate its migration behavior by analyzing a large number of cell migration data in vitro. We analyzed a large number of two-dimensional cell migration images over time and found that the cell shape variation space has only six dimensions, and migration behavior can be determined by the coordinates of a single cell image in this 6-dimensional shape-space. We further show that this is possible because persistent cell migration is characterized by spatial-temporally coordinated protrusion and contraction, and a distribution signature in the shape-space. Our findings provide a quantitative underpinning for using cell morphology to differentiate cell dynamical behavior.Comment: 29 pages, 9 figure

Protective Role of Rabbit Nucleotide-Binding Oligomerization Domain-2 (NOD2)-Mediated Signaling Pathway in Resistance to Enterohemorrhagic Escherichia coli Infection

Nucleotide-binding oligomerization domain 2 (NOD2), a member of the NOD-like receptors (NLRs) family that is well-known to play a key role in innate immune responses and is involved in innate antibacterial responses. In this study, rabbit NOD2 (rNOD2) was cloned from rabbit kidney (RK) cells. It was distributed in various tissues, and the highest level of rNod2 was detected in spleen. Moreover, the expression of rNod2 was significantly upregulated in the heart, liver, and spleen induced by enterohemorrhagic Escherichia coli (EHEC). Overexpression of rNOD2 induced the expression of pro-inflammatory cytokine, including Il1β, Il6, Ifn-γ, and Tnf, as well as defensins, including Defb124, Defb125, and Defb128 through the nuclear factor (NF)-κB signaling pathway. Furthermore, overexpression of rNOD2 inhibited the growth of EHEC, and knockdown of rNOD2 or inhibition of the NF-κB pathway promoted its replication. In addition, our results suggest that rNOD2 can significantly activate NF-κB signaling and trigger antibacterial defenses to increase the expression of pro-inflammatory cytokine and defensins after stimulation by EHEC. These findings are useful to further understanding the innate immune system of rabbits and providing a new perspective for the prevention of bacterial diseases in rabbits

SR-POD : sample rotation based on principal-axis orientation distribution for data augmentation in deep object detection

Convolutional neural networks (CNNs) have outperformed most state-of-the-art methods in object detection. However, CNNs suffer the difficulty of detecting objects with rotation, because the dataset used to train the CCNs often does not contain sufficient samples with various angles of orientation. In this paper, we propose a novel data-augmentation approach to handle samples with rotation, which utilizes the distribution of the object's orientation without the time-consuming process of rotating the sample images. Firstly, we present an orientation descriptor, named as "principal-axis orientation" to describe the orientation of the object's principal axis in an image and estimate the distribution of objects’ principal-axis orientations (PODs) of the whole dataset. Secondly, we define a similarity metric to calculate the POD similarity between the training set and an additional dataset, which is built by randomly selecting images from the benchmark ImageNet ILSVRC2012 dataset. Finally, we optimize a cost function to obtain an optimal rotation angle, which indicates the highest POD similarity between the two aforementioned data sets. In order to evaluate our data augmentation method for object detection, experiments, conducted on the benchmark PASCAL VOC2007 dataset, show that with the training set augmented using our method, the average precision (AP) of the Faster RCNN in the TV-monitor is improved by 7.5%. In addition, our experimental results also demonstrate that new samples generated by random rotation are more likely to result in poor performance of object detection

High temperature stability of H-diamond high frequency MOSFET with 300°C grown Al2O3 dielectric

The high frequency H-diamond metal-oxide-semiconductor field effect transistors (MOSFETs) were fabricated on single diamond substrate using 300°C ALD grown Al2O3 as gate dielectric and passivation layer. The devices gate length, gate/drain spacing and dielectric thickness are 100 nm, 2 μm, and 10 nm, respectively. The direct-current and frequency characteristics were investigated. The device shows a maximum saturation drain current of −492.6 mA/mm and gm of 135.2 mS/mm. The device shows good high temperature working performance, and the maximum saturation drain current only has a little decreasing of 7.6%. at 200°C. In addition, the device exhibits a maximum cut-off frequency of 36.2 GHz and maximum oscillation frequency of 70.5 GHz. The transient drain current response measurement indicates that the drain current can follow the changing of gate voltage at the frequency of 1 MHz. These results indicate that the Al2O3 dielectric is suitable for using in high frequency or the high-speed switching devices