scholarly journals CellCountCV—A Web-Application for Accurate Cell Counting and Automated Batch Processing of Microscopic Images Using Fully Convolutional Neural Networks

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3653
Author(s):  
Denis Antonets ◽  
Nikolai Russkikh ◽  
Antoine Sanchez ◽  
Victoria Kovalenko ◽  
Elvira Bairamova ◽  
...  
Keyword(s):  
Neural Networks ◽  
Endoplasmic Reticulum ◽  
Endoplasmic Reticulum Stress ◽  
Web Application ◽  
Experimental Studies ◽  
Living Cells ◽  
Cell Counting ◽  
Microscopic Images ◽  
Cellular Models ◽  
Cell Counts

In vitro cellular models are promising tools for studying normal and pathological conditions. One of their important applications is the development of genetically engineered biosensor systems to investigate, in real time, the processes occurring in living cells. At present, there are fluorescence, protein-based, sensory systems for detecting various substances in living cells (for example, hydrogen peroxide, ATP, Ca2+ etc.,) or for detecting processes such as endoplasmic reticulum stress. Such systems help to study the mechanisms underlying the pathogenic processes and diseases and to screen for potential therapeutic compounds. It is also necessary to develop new tools for the processing and analysis of obtained microimages. Here, we present our web-application CellCountCV for automation of microscopic cell images analysis, which is based on fully convolutional deep neural networks. This approach can efficiently deal with non-convex overlapping objects, that are virtually inseparable with conventional image processing methods. The cell counts predicted with CellCountCV were very close to expert estimates (the average error rate was < 4%). CellCountCV was used to analyze large series of microscopic images obtained in experimental studies and it was able to demonstrate endoplasmic reticulum stress development and to catch the dose-dependent effect of tunicamycin.

scholarly journals CellCountCV – a web-application for accurate cell counting and automated batch processing of microscopy images using fully-convolutional neural networks

2019 ◽  
Author(s):  
Denis Antonets ◽  
Nikolai Russkikh ◽  
Antoine Sanchez ◽  
Victoria Kovalenko ◽  
Elvira Bairamova ◽  
...  
Keyword(s):  
Neural Networks ◽  
Endoplasmic Reticulum ◽  
Endoplasmic Reticulum Stress ◽  
Web Application ◽  
Experimental Studies ◽  
Living Cells ◽  
Cell Counting ◽  
Cellular Models ◽  
Cell Counts ◽  
Microscopy Images

ABSTRACTThe in vitro cellular models are promising tools for studying normal and pathological conditions. One of their important applications is the development of genetically engineered biosensor systems to investigate the processes occurring in living cells in real time. Today, there are fluorescence protein based sensory systems for detecting various substances in living cells (for example, hydrogen peroxide, ATP, Ca2+ etc.) or for detecting processes such as endoplasmic reticulum stress. Such systems help to study mechanisms underlying the pathogenic processes and diseases and for screening potential therapeutic compounds. It is also necessary to develop new tools for processing and analysis of obtained microimages. Here we present our web-application CellCountCV for automation of microscopy cell images analysis which is based on fully-convolutional deep neural networks. This approach can efficiently deal with non-convex overlapping objects, that are virtually inseparable with conventional image processing methods. The cell counts predicted with CellCountCV were very close to expert estimates (the average error rate was < 4%). CellCountCV was used to analyse large series of microscopy images obtained in experimental studies and it was able to demonstrate the endoplasmic reticulum stress development and to catch the dose-dependent effect of tunicamycin.

scholarly journals Automated Counting of Cancer Cells by Ensembling Deep Features

Cells ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 1019 ◽  
Author(s):  
Liu ◽  
Junker ◽  
Murakami ◽  
Hu
Keyword(s):  
High Throughput ◽  
Pearson Correlation ◽  
Image Features ◽  
Cell Counting ◽  
Single Type ◽  
Imaging Features ◽  
Neural Network Models ◽  
Regression Problem ◽  
Microscopic Images ◽  
Cell Counts

High-content and high-throughput digital microscopes have generated large image sets in biological experiments and clinical practice. Automatic image analysis techniques, such as cell counting, are in high demand. Here, cell counting was treated as a regression problem using image features (phenotypes) extracted by deep learning models. Three deep convolutional neural network models were developed to regress image features to their cell counts in an end-to-end way. Theoretically, ensembling imaging phenotypes should have better representative ability than a single type of imaging phenotype. We implemented this idea by integrating two types of imaging phenotypes (dot density map and foreground mask) extracted by two autoencoders and regressing the ensembled imaging phenotypes to cell counts afterwards. Two publicly available datasets with synthetic microscopic images were used to train and test the proposed models. Root mean square error, mean absolute error, mean absolute percent error, and Pearson correlation were applied to evaluate the models’ performance. The well-trained models were also applied to predict the cancer cell counts of real microscopic images acquired in a biological experiment to evaluate the roles of two colorectal-cancer-related genes. The proposed model by ensembling deep imaging features showed better performance in terms of smaller errors and larger correlations than those based on a single type of imaging feature. Overall, all models’ predictions showed a high correlation with the true cell counts. The ensembling-based model integrated high-level imaging phenotypes to improve the estimation of cell counts from high-content and high-throughput microscopic images.

scholarly journals Endoplasmic Reticulum Stress Is Involved in Baicalin Protection on Chondrocytes From Patients With Osteoarthritis

Dose-Response ◽  
2018 ◽  
Vol 16 (4) ◽  
pp. 155932581881063 ◽  
Author(s):  
Jiangang Cao ◽  
Yu Zhang ◽  
Tianyi Wang ◽  
Bo Li
Keyword(s):  
Oxidative Stress ◽  
Endoplasmic Reticulum ◽  
Endoplasmic Reticulum Stress ◽  
Cell Viability ◽  
Er Stress ◽  
Messenger Rna ◽  
Cell Counting ◽  
Protective Effects ◽  
Gene Expressions ◽  
Protein Levels

Osteoarthritis (OA) affects elderly population worldwide and endoplasmic reticulum (ER) stress is known to be positively correlated with OA development. Previous reports prove the cytoprotective effects of baicalin on chondrocytes, whereas the mechanisms are hardly reported. Hence, we aimed to investigate the links between OA, ER stress, and baicalin. Chondrocytes from patients with OA were subjected to H2O2 treatment with or without baicalin pretreatment, and cell viability was assessed via Cell Counting Kit-8. Messenger RNA (mRNA) amounts of apoptosis-related genes (Bax, Bcl-2, and Caspase-3), extracellular matrix (ECM)-related genes (Collange I, Collange II, Aggrecan, and Sox9) and ER stress hallmarks (binding immunoglobulin protein [BiP] C/EBP homologous protein [CHOP]) were evaluated via quantitative real-time PCR. Bax, Bcl-2, BiP, and CHOP protein levels were analyzed via Western blot. Baicalin suppressed the changes in cell viability and apoptosis-related gene expressions caused by H2O2. Reactive oxygen species and glutathione/oxidized glutathione assay showed that H2O2 enhanced oxidative stress. Baicalin suppressed H2O2-induced downregulation of mRNA expression of ECM-related genes. Moreover, baicalin reduced H2O2-stimulated increase in oxidative stress and the expression of ER stress hallmarks. Endoplasmic reticulum stress inducer abolished the protective activities, whereas ER stress inhibitor did not exhibit extra protective effects. Baicalin pretreatment protected patient-derived chondrocytes from H2O2 through ER stress inhibition.

scholarly journals Downregulation of ceramide synthase 1 promotes oral cancer through endoplasmic reticulum stress

2020 ◽  
Author(s):  
WEN CHEN ◽  
ZHE LIU ◽  
CHENZHOU WU ◽  
YAFEI CHEN ◽  
LING QIU ◽  
...  
Keyword(s):  
Endoplasmic Reticulum ◽  
Oral Cancer ◽  
Endoplasmic Reticulum Stress ◽  
Er Stress ◽  
Cell Counting ◽  
Luciferase Assay ◽  
Migration And Invasion ◽  
Ceramide Synthase ◽  
Rt Pcr

Abstract Background C18 ceramide (CER) plays an important role in the occurrence and development of oral squamous cell carcinoma (OSCC). However, the function of ceramide synthase 1 (CERS1), a key enzyme in C18 CER synthesis, in OSCC is still unclear. The aim of our study was to investigate the relationship between CERS1 and oral cancer. Methods The expression of CERS1 on 48 pairs of matching OSCC patients’ cancer and normal tissues was determined by quantitative real-time PCR (RT-PCR). A mouse OSCC model induced by 4-nitroquinolin-1-oxide (4NQO) was established on CERS1+/+ and CERS1-/- C57BL/N6 mice. The functions of CERS1 downregulated were accessed by cell counting kit-8 method, colony formation assay, EdU DNA Proliferation in vitro Detection, wound healing test and Annexin V/PI double staining. RT-PCR, Western blot and luciferase assay were performed to explore the molecular mechanisms of CERS1. Results In this study, we found that the expression of CERS1 was downregulated in oral cancer tissues and cell lines. In the mouse OSCC model, CERS1 knockout was associated with the severity of oral malignant transformation. Immunohistochemical studies showed significant upregulation of PCNA, MMP2, MMP9, and BCL2 expression and downregulation of BAX expression in the pathological hyperplastic area. In addition, CERS1 knockdown promoted cell proliferation, migration and invasion in vitro. CERS1 knockdown caused endoplasmic reticulum stress (ER stress) and induced the activating transcription factor 4 (ATF4) pathway. ATF4 upregulated VEGFA transcription to promote tumor growth and metastasis. In addition, mild ER stress caused by CERS1 knockdown could induce cisplatin resistance. Conclusions Our study suggests that CERS1 is downregulated in oral cancer. The downregulation of CERS1 promotes the aggressiveness of OSCC and chemotherapeutic drug resistance by inducing mild ER stress.

scholarly journals ABCC10-Mediated Oxaliplatin Resistance in Colorectal Cancer Was Alleviated by Intense Endoplasmic Reticulum Stress (ERS) / IRE1α

2021 ◽  
Author(s):  
Xiaohui Liu ◽  
Hong Chen ◽  
Haimei Sun ◽  
Xiaoxia Guo ◽  
Bo Wu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Endoplasmic Reticulum ◽  
Endoplasmic Reticulum Stress ◽  
Cell Viability ◽  
High Performance ◽  
Tumor Development ◽  
The Cancer Genome Atlas ◽  
Cell Counting ◽  
Promoting Effect ◽  
Knock Down

Abstract Background: Oxaliplatin resistance is a challenge in treating colorectal cancer (CRC) patients, contributory to the failure in chemotherapy. However, the mechanism of Oxaliplatin resistance has not been completely elucidated. In this study, we explored the key molecule involved in the Oxaliplatin resistance, which could be a candidate therapeutic target to attenuate chemo-resistance in CRC cells.Methods: Microarray screening, western blot and qPCR on clinic CRC samples were conducted to select the target gene ABCC10. The Oncomine Oncology Database and the Cancer Genome Atlas (TCGA) data were analyzed to figure out the correlation between the clinical manifestation and ABCC10. ABCC10 knock-down in CRC cells was conducted to identify its role in the Oxaliplatin resistance. Cell counting kit-8 (CCK-8) assay was conducted to identify the CRC cell viability and Oxaliplatin IC50. Flow cytometry was conducted to detect the cell apoptosis exposed to Oxaliplatin. The intracellular Oxaliplatin accumulation was measured by ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS).Results: ABCC10 transporter was correlated with CRC relapse and metastasis, indicating a CRC-promoting effect of ABCC10. In ABCC10 knock-down CRC cells the Oxaliplatin sensitivity was significantly elevated due to an increase of intracellular Oxaliplatin accumulation resulted from the diminished drug efflux. We next explored a strategy to inhibit ABCC10 in CRC cells, paying a special interest in the endoplasmic reticulum stress (ERS) / unfolded protein response (UPR) that plays a dual role in tumor development. We found that the CRC cell viability was profoundly decreased and the pro-apoptotic factor CHOP and apoptosis were increased by the intense ERS/UPR instead of the inhibited and mild ERS/UPR. Significantly, the Oxaliplatin sensitivity of CRC cells was enhanced in response to the intense ERS, which was blocked by inhibiting IRE1α branch of UPR. Finally, we figured out that the intense ERS/UPR down-regulated ABCC10 via regulated IRE1-dependent decay (RIDD) activity. Conclusion: Oxaliplatin was a substrate of ABCC10. The intense ERS/IRE1α elicited anti-CRC effects through down-regulating ABCC10 so as to increase Oxaliplatin sensitivity, in addition to inducing CHOP. We suggested that introduction of intense ERS/UPR could be a promising strategy to restore chemo-sensitivity when used in combination with Oxaliplatin or other chemotherapeutic drugs pumped out by ABCC10.

X-Ray fluorescence microscopy reveals that rhenium(i) tricarbonyl isonitrile complexes remain intact in vitro

2020 ◽  
Vol 56 (48) ◽  
pp. 6515-6518 ◽  
Author(s):  
Chilaluck C. Konkankit ◽  
James Lovett ◽  
Hugh H. Harris ◽  
Justin J. Wilson
Keyword(s):  
Endoplasmic Reticulum ◽  
Endoplasmic Reticulum Stress ◽  
Fluorescence Microscopy ◽  
Living Cells ◽  
Axial Ligand ◽  
X Ray

An endoplasmic reticulum stress-inducing rhenium isonitrile complex was investigated for its axial ligand stability in living cells using X-ray fluorescence microscopy.

scholarly journals lncRNA AK054386 Functions as a ceRNA to Sequester miR-199 and Induce Sustained Endoplasmic Reticulum Stress in Hepatic Reperfusion Injury

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Binghua Dai ◽  
Liang Qiao ◽  
Mingke Zhang ◽  
Lipeng Cheng ◽  
Ling Zhang ◽  
...  
Keyword(s):  
Endoplasmic Reticulum ◽  
Endoplasmic Reticulum Stress ◽  
Reperfusion Injury ◽  
Ischemia Reperfusion Injury ◽  
Ischemia Reperfusion ◽  
Liver Trauma ◽  
Protective Effects ◽  
Related Factors ◽  
Hepatic Ischemia ◽  
Cellular Models

Hepatic ischemia-reperfusion injury (IRI) is a very complex pathological process that is often associated with liver trauma and surgery, especially liver transplantation surgery. Although endoplasmic reticulum stress (ERS) plays a role in this process, the posttranscriptional regulators and the underlying mechanisms are still unclear. Here, we report that the lncRNA AK054386 was increased in hepatic IRI models. Furthermore, AK054386 can act as a “competing endogenous RNA (ceRNA)” and regulate ERS-related factors by binding and sequestering miR-199, which was shown to inhibit ERS in our previous report. Increased expression of AK054386, which might be mediated by activated NF-κB, resulted in sustained ERS and increased cell apoptosis and death in hepatic IRI mouse and cellular models. In contrast, AK054386 inhibition had protective effects on these models. Our data indicate that AK054386 and miR-199 are critical players in hepatic IRI, and we broadened the scope regarding ceRNA mechanisms. We hope that our results will improve the understanding of hepatic IRI and may provide potential therapeutic targets.

Development of a Neurocomputer Modular Information System for Cancerous Diseases Diagnostics in Animals

2020 ◽  
pp. 75-84 ◽  
Author(s):  
N.A. Staroverova ◽  
M.L. Shustrova ◽  
S.A. Staroverov ◽  
L.A. Dykman
Keyword(s):  
Neural Networks ◽  
Information System ◽  
Web Application ◽  
System Development ◽  
Initial Diagnosis ◽  
Microscopic Images ◽  
Multinucleated Cells ◽  
Cytological Picture ◽  
Characteristic Features ◽  
Cytological Sample

Information system was developed in the form of a web application that makes it possible to identify microscopic images of cytological samples, to establish an initial diagnosis and to provide recommendations for its further confirmation based on additional data. Approaches, assumptions and prerequisites adopted in the information system development are described. It is proposed to use neural networks as the information system element in sample identification and making the initial diagnosis. Patient data, affected area images and microscopic images of cytological samples are planned to be collected in the information system database under creation. Cytological sample images serve as the input data for neural networks operation. Cytological picture assessment is based on the use of the following characteristic features: preparation background, number and location of cells, size and shape of cells, nucleus, presence of multinucleated cells and fission entities (atypical mitoses), etc.

scholarly journals 2-Amino-3-Methylimidazo[4,5-f]quinoline Triggering Liver Damage by Inhibiting Autophagy and Inducing Endoplasmic Reticulum Stress in Zebrafish (Danio rerio)

Toxins ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 826
Author(s):  
Dan Li ◽  
Zhi Li ◽  
Tianchang Zhang ◽  
Bo Peng ◽  
Yan Zhang ◽  
...  
Keyword(s):  
Endoplasmic Reticulum ◽  
Endoplasmic Reticulum Stress ◽  
Protein Expression ◽  
Experimental Studies ◽  
Related Factors ◽  
Potential Harm ◽  
Homologous Protein ◽  
Apoptosis Pathways ◽  
Induced Apoptosis ◽  
Glucose Regulated Protein

It is important to note that 2-Amino-3-methylimidazole[4,5-f]quinoline (IQ) is one of the most common heterocyclic amines (HCAs), which is a class of mutagenic/carcinogenic harmful compounds mainly found in high-protein thermal processed foods and contaminated environments. However, the pre-carcinogenic toxicity of IQ to the liver and its mechanism are poorly understood, further research is needed. In light of this, we exposed zebrafish to IQ (0, 8, 80, and 800 ng/mL) for 35 days, followed by comprehensive experimental studies. Histopathological and ultrastructural analysis showed that hepatocytes were damaged. TUNEL results showed that IQ induced apoptosis of liver cells, the expression of apoptosis factor gene was significantly increased, and the expression of Bcl-2 protein was significantly decreased. In addition, upregulated expression of the 78-kDa glucose-regulated protein (GRP78) and C/EBP homologous protein (CHOP) and endoplasmic reticulum stress (ERS)-related factors transcription levels were elevated obviously, suggesting that IQ induced ERS. Decreased protein expression of autophagy-related 5 (Atg5)-Atg12, Beclin1, and LC3-II, increased protein expression of p62, and autophagy-related factors transcription levels were significantly decreased, suggesting that IQ inhibited autophagy. Overall, our research showed that the potential harm of IQ to the liver before the occurrence of liver cancer was related to ERS and its mediated autophagy and apoptosis pathways.

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