Deep-UV (DUV) excitation fluorescence microscopy has potential to provide rapid diagnosis with simple technique comparing to conventional histopathology based on hematoxylin and eosin (H&E) staining. ...We established a fluorescent staining protocol for DUV excitation fluorescence imaging that has enabled clear discrimination of nucleoplasm, nucleolus, and cytoplasm. Fluorescence images of metastasis-positive/-negative lymph nodes of gastric cancer patients were used for patch-based training with a deep neural network (DNN) based on Inception-v3 architecture. The performance on small patches of the fluorescence images was comparable with that of H&E images. Gradient-weighted class activation mapping analysis revealed the areas where the trained model identified metastatic lesions in the images containing cancer cells. We extended the method to large-size image analysis enabling accurate detection of metastatic lesions. We discuss usefulness of DUV excitation fluorescence imaging with the aid of DNN analysis, which is promising for assisting pathologists in assessment of lymph node metastasis.
Altered phosphorylation status of the C-terminal Thr residues of Ezrin/Radixin/Moesin (ERM) is often linked to cell shape change. To determine the role of phophorylated ERM, we modified ...phosphorylation status of ERM and investigated changes in cell adhesion and morphology. Treatment with Calyculin-A (Cal-A), a protein phosphatase inhibitor, dramatically augmented phosphorylated ERM (phospho-ERM). Cal-A-treatment or expression of phospho-mimetic Moesin mutant (Moesin-TD) induced cell rounding in adherent cells. Moreover, reattachment of detached cells to substrate was inhibited by either treatment. Phospho-ERM, Moesin-TD and actin cytoskeleton were observed at the plasma membrane of such round cells. Augmented cell surface rigidity was also observed in both cases.
Meanwhile, non-adherent KG-1 cells were rather rich in phospho-ERM. Treatment with Staurosporine, a protein kinase inhibitor that dephosphorylates phospho-ERM, up-regulated the integrin-dependent adhesion of KG-1 cells to substrate.
These findings strongly suggest the followings: (1) Phospho-ERM inhibit cell adhesion, and therefore, dephosphorylation of ERM proteins is essential for cell adhesion. (2) Phospho-ERM induce formation and/or maintenance of spherical cell shape. (3) ERM are constitutively both phosphorylated and dephosphorylated in cultured adherent and non-adherent cells.
It is known that single or isolated tumor cells enter cancer patients' circulatory systems. These circulating tumor cells (CTCs) are thought to be an effective tool for diagnosing cancer malignancy. ...However, handling CTC samples and evaluating CTC sequence analysis results are challenging. Recently, the convolutional neural network (CNN) model, a type of deep learning model, has been increasingly adopted for medical image analyses. However, it is controversial whether cell characteristics can be identified at the single-cell level by using machine learning methods. This study intends to verify whether an AI system could classify the sensitivity of anticancer drugs, based on cell morphology during culture. We constructed a CNN based on the VGG16 model that could predict the efficiency of antitumor drugs at the single-cell level. The machine learning revealed that our model could identify the effects of antitumor drugs with ~0.80 accuracies. Our results show that, in the future, realizing precision medicine to identify effective antitumor drugs for individual patients may be possible by extracting CTCs from blood and performing classification by using an AI system.
Semantic segmentation with deep learning to extract nerves from label-free endoscopic images obtained using coherent anti-Stokes Raman scattering (CARS) for nerve-sparing surgery is described. We ...developed a CARS rigid endoscope in order to identify the exact location of peripheral nerves in surgery. Myelinated nerves are visualized with a CARS lipid signal in a label-free manner. Because the lipid distribution includes other tissues as well as nerves, nerve segmentation is required to achieve nerve-sparing surgery. We propose using U-Net with a VGG16 encoder as a deep learning model and pre-training with fluorescence images, which visualize the lipid distribution similar to CARS images, before fine-tuning with a small dataset of CARS endoscopy images. For nerve segmentation, we used 24 CARS and 1,818 fluorescence nerve images of three rabbit prostates. We achieved label-free nerve segmentation with a mean accuracy of 0.962 and an F 1 value of 0.860. Pre-training on fluorescence images significantly improved the performance of nerve segmentation in terms of the mean accuracy and F 1 value ( p < 0 . 05 ). Nerve segmentation of label-free endoscopic images will allow for safer endoscopic surgery, while reducing dysfunction and improving prognosis after surgery.
Gaze tracking (GT) systems have attracted the attention of researchers as well as the commercial sector. Commercial systems are readily available, but they are usually fabricated at the same size. In ...this study, we propose a three-dimensional (3-D)-printable frame and an open-source system to fabricate a wearable GT system with low-cost configuration and reasonable performance. A 3-D printer achieves repeatable and adjustable design. The estimated price to make the GT hardware is less than €100, and the system's average accuracy is 2.58°. Our GT system has a 24-Hz sampling rate, which can analyze human interest points. Another contribution of this study is developing the automatic discrimination of interest objects using our proposed GT and machine learning. The output of this combination system is a database that consists of labeled objects. The label with the highest frequency indicates the object of the highest interest for a corresponding user. Our combination system has a 7-Hz sampling rate and a 3.8% classification error.
Alleles of human leukocyte antigen (HLA)-A DNAs are classified and expressed graphically by using artificial intelligence “Deep Learning (Stacked autoencoder)”. Nucleotide sequence data corresponding ...to the length of 822 bp, collected from the Immuno Polymorphism Database, were compressed to 2-dimensional representation and were plotted. Profiles of the two-dimensional plots indicate that the alleles can be classified as clusters are formed. The two-dimensional plot of HLA-A DNAs gives a clear outlook for characterizing the various alleles.
Using single-cells time-lapse analysis, we investigated the mechanism of gene expression using nine transfection reagents. Although onset of gene expression occurred after cell division by all ...reagents, 91.6% periods, which depended on onset and cell division, had statistical significance. Evaluation of those periods is useful for elucidating mechanism of transfection.
The mechanical features of individual animal cells have been regarded as indicators of cell type and state. Previously, we investigated the surface mechanics of cancer and normal stromal cells in ...adherent and suspended states using atomic force microscopy. Cancer cells possessed specific mechanical and actin cytoskeleton features that were distinct from normal stromal cells in adherent and suspended states. In this paper, we report the unique mechanical and actin cytoskeletal features of human embryonic kidney HEK293 cells. Unlike normal stromal and cancer cells, the surface stiffness of adherent HEK293 cells was very low, but increased after cell detachment from the culture surface. Induced actin filament depolymerization revealed that the actin cytoskeleton was the underlying source of the stiffness in suspended HEK293 cells. The exclusive mechanical response of HEK293 cells to perturbation of the actin cytoskeleton resembled that of adherent cancer cells and suspended normal stromal cells. Thus, with respect to their special cell-surface mechanical features, HEK293 cells could be categorized into a new class distinct from normal stromal and cancer cells.
Cell proliferation is a key characteristic of eukaryotic cells. During cell proliferation, cells interact with each other. In this study, we developed a cellular automata model to estimate cell-cell ...interactions using experimentally obtained images of cultured cells.
We used four types of cells; HeLa cells, human osteosarcoma (HOS) cells, rat mesenchymal stem cells (MSCs), and rat smooth muscle A7r5 cells. These cells were cultured and stained daily. The obtained cell images were binarized and clipped into squares containing about 10
cells. These cells showed characteristic cell proliferation patterns. The growth curves of these cells were generated from the cell proliferation images and we determined the doubling time of these cells from the growth curves. We developed a simple cellular automata system with an easily accessible graphical user interface. This system has five variable parameters, namely, initial cell number, doubling time, motility, cell-cell adhesion, and cell-cell contact inhibition (of proliferation). Within these parameters, we obtained initial cell numbers and doubling times experimentally. We set the motility at a constant value because the effect of the parameter for our simulation was restricted. Therefore, we simulated cell proliferation behavior with cell-cell adhesion and cell-cell contact inhibition as variables. By comparing growth curves and proliferation cell images, we succeeded in determining the cell-cell interaction properties of each cell. Simulated HeLa and HOS cells exhibited low cell-cell adhesion and weak cell-cell contact inhibition. Simulated MSCs exhibited high cell-cell adhesion and positive cell-cell contact inhibition. Simulated A7r5 cells exhibited low cell-cell adhesion and strong cell-cell contact inhibition. These simulated results correlated with the experimental growth curves and proliferation images.
Our simulation approach is an easy method for evaluating the cell-cell interaction properties of cells.
Abstract We describe a low-invasive gene delivery method that uses an etched atomic force microscopy (AFM) tip or nanoneedle that can be inserted into a cell nucleus without causing cellular damage. ...The nanoneedle is 200 nm in diameter and 6 μm in length and is operated using an AFM system. The probabilities of insertion of the nanoneedle into human mesenchymal stem cells (MSCs) and human embryonic kidney cells (HEK293) were higher than those of typical microinjection capillaries. A plasmid containing the green fluorescent protein (GFP) gene was adsorbed on a poly- l -lysine–modified nanoneedle surface, which was then inserted into primary cultured single human MSCs. A highly efficient gene delivery of over 70% was achieved in human MSCs, which compared very favorably with other major nonviral gene delivery methods (lipofection ~50%, microinjection ~10 %). The single cells expressing GFP were collected and the amount of delivered DNA in each cell was analyzed. The highest rate of expressed GFP per delivered DNA was achieved using the nanoneedle, because the nanoneedle could be inserted into the nucleus directly without causing significant cell damage.
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