Fractal descriptor on holographic images of cervical cells

Abstract Background Segmentation of nuclei in cervical cytology pap smear images is a crucial stage in automated cervical cancer screening. The task itself is challenging due to the presence of cervical cells with spurious edges, overlapping cells, neutrophils, and artifacts. Methods After the initial preprocessing steps of adaptive thresholding, in our approach, the image passes through a convolution filter to filter out some noise. Then, contours from the resultant image are filtered by their distinctive contour properties followed by a nucleus size recovery procedure based on contour average intensity value. Results We evaluate our method on a public (benchmark) dataset collected from ISBI and also a private real dataset. The results show that our algorithm outperforms other state-of-the-art methods in nucleus segmentation on the ISBI dataset with a precision of 0.978 and recall of 0.933. A promising precision of 0.770 and a formidable recall of 0.886 on the private real dataset indicate that our algorithm can effectively detect and segment nuclei on real cervical cytology images. Tuning various parameters, the precision could be increased to as high as 0.949 with an acceptable decrease of recall to 0.759. Our method also managed an Aggregated Jaccard Index of 0.681 outperforming other state-of-the-art methods on the real dataset. Conclusion We have proposed a contour property-based approach for segmentation of nuclei. Our algorithm has several tunable parameters and is flexible enough to adapt to real practical scenarios and requirements.

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Chloroquine and Sulfadoxine Derivatives Inhibit ZIKV Replication in Cervical Cells

Viruses ◽

10.3390/v13010036 ◽

2020 ◽

Vol 13 (1) ◽

pp. 36

Author(s):

Audrien Alves Andrade de Souza ◽

Lauana Ribas Torres ◽

Lyana Rodrigues Pinto Lima Capobianco ◽

Vanessa Salete de Paula ◽

Cynthia Machado Cascabulho ◽

...

Keyword(s):

Antiviral Activity ◽

Specific Treatment ◽

Vero Cells ◽

Vehicle Control ◽

Therapeutic Window ◽

Chemical Structures ◽

Hybrid Compounds ◽

Cervical Cells ◽

Zika Fever

Despite the severe morbidity caused by Zika fever, its specific treatment is still a challenge for public health. Several research groups have investigated the drug repurposing of chloroquine. However, the highly toxic side effect induced by chloroquine paves the way for the improvement of this drug for use in Zika fever clinics. Our aim is to evaluate the anti-Zika virus (ZIKV) effect of hybrid compounds derived from chloroquine and sulfadoxine antimalarial drugs. The antiviral activity of hybrid compounds (C-Sd1 to C-Sd7) was assessed in an in-vitro model of human cervical and Vero cell lines infected with a Brazilian (BR) ZIKV strain. First, we evaluated the cytotoxic effect on cultures treated with up to 200 µM of C-Sds and observed CC50 values that ranged from 112.0 ± 1.8 to >200 µM in cervical cells and 43.2 ± 0.4 to 143.0 ± 1.3 µM in Vero cells. Then, the cultures were ZIKV-infected and treated with up to 25 µM of C-Sds for 48 h. The treatment of cervical cells with C-Sds at 12 µM induced a reduction of 79.8% ± 4.2% to 90.7% ± 1.5% of ZIKV–envelope glycoprotein expression in infected cells as compared to 36.8% ± 2.9% of infection in vehicle control. The viral load was also investigated and revealed a reduction of 2- to 3-logs of ZIKV genome copies/mL in culture supernatants compared to 6.7 ± 0.7 × 108 copies/mL in vehicle control. The dose–response curve by plaque-forming reduction (PFR) in cervical cells revealed a potent dose-dependent activity of C-Sds in inhibiting ZIKV replication, with PFR above 50% and 90% at 6 and 12 µM, respectively, while 25 µM inhibited 100% of viral progeny. The treatment of Vero cells at 12 µM led to 100% PFR, confirming the C-Sds activity in another cell type. Regarding effective concentration in cervical cells, the EC50 values ranged from 3.2 ± 0.1 to 5.0 ± 0.2 µM, and the EC90 values ranged from 7.2 ± 0.1 to 11.6 ± 0.1 µM, with selectivity index above 40 for most C-Sds, showing a good therapeutic window. Here, our aim is to investigate the anti-ZIKV activity of new hybrid compounds that show highly potent efficacy as inhibitors of ZIKV in-vitro infection. However, further studies will be needed to investigate whether these new chemical structures can lead to the improvement of chloroquine antiviral activity.

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Competing Endogenous RNAs in Cervical Carcinogenesis: A New Layer of Complexity

Processes ◽

10.3390/pr9060991 ◽

2021 ◽

Vol 9 (6) ◽

pp. 991

Author(s):

Fernanda Costa Brandão Berti ◽

Sara Cristina Lobo-Alves ◽

Camila de Freitas Oliveira-Toré ◽

Amanda Salviano-Silva ◽

Karen Brajão de Oliveira ◽

...

Keyword(s):

Gene Expression ◽

Fine Tuning ◽

Molecular Networks ◽

Cervical Carcinogenesis ◽

Molecular Changes ◽

Cellular Processes ◽

Target Mrnas ◽

Competing Endogenous Rnas ◽

Cervical Cells ◽

Post Transcriptional Regulation

MicroRNAs (miRNAs) regulate gene expression by binding to complementary sequences within target mRNAs. Apart from working ‘solo’, miRNAs may interact in important molecular networks such as competing endogenous RNA (ceRNA) axes. By competing for a limited pool of miRNAs, transcripts such as long noncoding RNAs (lncRNAs) and mRNAs can regulate each other, fine-tuning gene expression. Several ceRNA networks led by different lncRNAs—described here as lncRNA-mediated ceRNAs—seem to play essential roles in cervical cancer (CC). By conducting an extensive search, we summarized networks involved in CC, highlighting the major impacts of such dynamic molecular changes over multiple cellular processes. Through the sponging of distinct miRNAs, some lncRNAs as HOTAIR, MALAT1, NEAT1, OIP5-AS1, and XIST trigger crucial molecular changes, ultimately increasing cell proliferation, migration, invasion, and inhibiting apoptosis. Likewise, several lncRNAs seem to be a sponge for important tumor-suppressive miRNAs (as miR-140-5p, miR-143-3p, miR-148a-3p, and miR-206), impairing such molecules from exerting a negative post-transcriptional regulation over target mRNAs. Curiously, some of the involved mRNAs code for important proteins such as PTEN, ROCK1, and MAPK1, known to modulate cell growth, proliferation, apoptosis, and adhesion in CC. Overall, we highlight important lncRNA-mediated functional interactions occurring in cervical cells and their closely related impact on cervical carcinogenesis.

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Profiles of Human Papillomavirus Detection of the Multinucleated Cells in Cervical Smears

Microorganisms ◽

10.3390/microorganisms9081575 ◽

2021 ◽

Vol 9 (8) ◽

pp. 1575

Author(s):

Kaori Okayama ◽

Toshiyuki Sasagawa ◽

Koji Teruya ◽

Mizue Oda ◽

Masahiko Fujii ◽

...

Keyword(s):

Pap Smear ◽

Morphological Changes ◽

Human Papillomaviruses ◽

Multinucleated Cells ◽

Hpv Genotypes ◽

Atypical Cells ◽

Intraepithelial Lesion ◽

Liquid Based Cytology ◽

Cervical Cells ◽

High Risk Hpv

Many genotypes of human papillomaviruses (HPVs) may lead to morphological changes in cells, resulting in various atypical cells, such as multinucleated cells (MNCs) and koilocytes, in the cervix. However, the relationships between the profiles of HPV genotypes and MNCs are not exactly known. Thus, this study comprehensively profiles the HPV genotypes in MNCs using a microdissection method. HPV genotypes and MNCs were detected in 651 cases with an abnormal Pap smear by liquid-based cytology. Specific HPV genotypes were also detected, including HPV16, 34, and 56, which might be associated with MNCs. This result suggests that the high-risk HPV genotypes, such as HPV16 and 56, are associated with the atypical changes in MNC morphology from normal cervical cells. The results also show that MNCs may be a predictor of squamous intraepithelial lesion.

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A Hierarchical Feature-Based Methodology to Perform Cervical Cancer Classification

Applied Sciences ◽

10.3390/app11094091 ◽

2021 ◽

Vol 11 (9) ◽

pp. 4091

Author(s):

Débora N. Diniz ◽

Mariana T. Rezende ◽

Andrea G. C. Bianchi ◽

Claudia M. Carneiro ◽

Daniela M. Ushizima ◽

...

Keyword(s):

Cervical Cancer ◽

Pap Smear ◽

Hierarchical Classification ◽

Cell Nuclei ◽

Test Analysis ◽

Pap Smear Test ◽

Microscopy Image ◽

Feature Based ◽

Cervical Cells ◽

Number Of Classes

Prevention of cervical cancer could be performed using Pap smear image analysis. This test screens pre-neoplastic changes in the cervical epithelial cells; accurate screening can reduce deaths caused by the disease. Pap smear test analysis is exhaustive and repetitive work performed visually by a cytopathologist. This article proposes a workload-reducing algorithm for cervical cancer detection based on analysis of cell nuclei features within Pap smear images. We investigate eight traditional machine learning methods to perform a hierarchical classification. We propose a hierarchical classification methodology for computer-aided screening of cell lesions, which can recommend fields of view from the microscopy image based on the nuclei detection of cervical cells. We evaluate the performance of several algorithms against the Herlev and CRIC databases, using a varying number of classes during image classification. Results indicate that the hierarchical classification performed best when using Random Forest as the key classifier, particularly when compared with decision trees, k-NN, and the Ridge methods.

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