\end{aligned}$$, $$\begin{aligned} L= RP \times D \end{aligned}$$, $$\begin{aligned} {x}^{Sqr}=[{x}_{0,0}; sort([{x}^{S}_{1,0};{x}^{S}_{1,1};\ldots ;{x}^{S}_{1,p_{1}-1}]);\ldots ;sort([{x}^{S}_{m,0};{x}^{S}_{m,1};\ldots ;{x}^{S}_{m,p_{m}-1}])] \end{aligned}$$, $$\begin{aligned} f_{S}= RP \times {{x}}^{Sqr} \end{aligned}$$, \([f_{G}]_{CP_{yz}}, [f_{C}]_{CP_{yz}}, [f_{S}]_{CP_{yz}}, [f_{A}]_{CP_{yz}}, [f_{R}]_{CP_{yz}}\), $$\begin{aligned} SRP_{CP_{yz}}= [norm([f_{G}]_{CP_{yz}}),norm([f_{C}]_{CP_{yz}}),norm([f_{S}]_{CP_{yz}}),norm([f_{A}]_{CP_{yz}}),norm([f_{R}]_{CP_{yz}})] \end{aligned}$$, $$\begin{aligned} SRP_{CP} = [SRP_{CP_{yz}},SRP_{CP_{xz}},SRP_{CP_{xy}}] \end{aligned}$$, $$\begin{aligned} \frac{HC}{EC} =\frac{sum([f_{G}]_{HC})}{sum([f_{G}]_{Nucleus}) - sum([f_{G}]_{HC})} \end{aligned}$$, $$\begin{aligned} \frac{HC}{EC} =\frac{sum([f_{R,A}]_{HC})}{sum([f_{R,A}]_{Nucleus}) - sum([f_{R,A}]_{HC})} \end{aligned}$$, https://doi.org/10.1038/s41598-021-82985-9. In cross disciplines such as mechanobiology, nuclear morphological quantification has emerged as a promising approach to study the effect of external signals on nuclear morphology and their further impact on enclosed protein organisation. 3b). A number of fluorescent stains are available that label DNA and allow easy visualization of the nucleus in interphase cells and chromosomes in mitotic cells, including Hoechst, 4',6-diamidino-2-phenylindole (DAPI), ethidium bromide, propidium iodide, and acridine orange. The https:// ensures that you are connecting to the In addition, image analysis software was used to estimate the DNA content in the nuclei of Arcellinida and ciliates and to compare them to measurements of well-known model organisms. DAPI staining and DNA content estimation of uncultivable microbial At present single-cell surface marker/RNA sequencing (scRNA-Seq) is the accepted method to identify the intermediate states that occur during EMT in metastasis. Dilute the DAPI stock solution to 30 nM in PBS. 1.54 MB DAPI Colonialism Staining Assays Most recent answer Robert Jackson The University of Arizona This looks like Mycoplasma contamination. Cellular features are extracted and further represented using BOVW to reduce redundant features and obtain a global feature vector to represent each class features. Similar to the proposed 3D method, the obtained results demonstrate a positive shift in HC/EC ratios from PROLIF to SS class and negative shift from EPI to EMT class. Rep. 7, 113 (2017). The proposed 3D approach extends SRP by extracting features from the third plane using hyperplanes built in the cubic patches of the volumetric image (explained in Methods). C-E. Histograms of three sorted nuclear fractions reexamined by cytometry to confirm their relative NeuN staining levels. As illustrated in Fig. Genes Development 29, 238249 (2015). Cell. Med. In this study, we developed protocols for DAPI (4',6-diamidino-2-phenylindole) staining of Arcellinida nuclei and adapted protocols for ciliates. The presented model is evaluated on publicly available 3D image datasets of human fibroblast and human prostate cancer cells. volume11, Articlenumber:3364 (2021) Following this, the maximum value of the concatenated vector ([\(f_{R,A}]_{CP_{i}}\)), is obtained as \({m_i}\). Similar to the 3D approach, the threshold to identify HC in 2D images is also the maximum value of the SRP function vector, and thus the ratios can be computed using Eqs. 18, 176196 (2014). J. Although not as bright as th Leard E, Carmichael RH, Ortmann AC, Jones JL. Rev. DAPI staining (blue) depicts the nucleus with an intranuclear inclusion, which contains the autophagy-associated proteins ubiquitin and p62. An ovol2-zeb1 mutual inhibitory circuit governs bidirectional and multi-step transition between epithelial and mesenchymal states. Changes in the chromatin pattern as implied by results in Table2 are in accordance with other relevant studies2,7,9,17. HC intensity measure HC/EC ratio based on pixel values estimates the fraction of the HC intensity in the nucleus. A. The HC/EC ratio was also computed following the same method with the original pixel values without random projections, and it was observed that the obtained p-value was higher. 2HCl CAS Number: 28718-90-3 Molecular Weight: 350.25 Beilstein: 4894417 EC Number: 249-186-7 MDL number: Since the nucleolus contains very few pixels, we study only the DAPI images. The corresponding null hypothesis is: As shown in Table2, the results from the test verify the statistical significance of the difference in \(HC/EC_{PixelValues}\) and \(HC/EC_{PixelDifferences}\) between two classes and indicate both ratios are higher for SS cells than for PROLIF (normal state) cells, while they are lower for EMT cells than for EPI (normal state) cells. ProLong Gold or. For 3D SRP, as shown in Fig. Mach. The value of a in the dimension of RP is correlated with the patch size of the image. The excitation maximum for DAPI bound to dsDNA is 358 nm, and the emission maximum is 461 nm. sharing sensitive information, make sure youre on a federal Changes in nuclear texture occur in conjunction with other morphological variations such as nuclear and nucleolar size, shape and count at the tissue level and the organisation of protein content, based on which cancerous cells are differentiated from normal ones2,7. EMT cells with their ICS are of high importance in studies related to comprehension of cancer progression and drug resistance. Uhler, C. & Shivashankar, G. Regulation of genome organization and gene expression by nuclear mechanotransduction. Detecting Protein Subcellular Localization by Green Fluorescence Abstract. Use the fixation protocol appropriate for your sample. 2012 Aug 1;2012(8):pdb.prot067363. However, the inference remains the same for the pixel differences approach and no statistical significance in ratio difference is found for the pixel value method. Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article. In the current study, obtained metric values based on texture description are higher than the state-of-the-art (SOTA) works obtained by classification using shape-based features on the same dataset. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. Cell. The presented experiments demonstrate changes in intrinsic texture mainly formed by chromatin. Since this study is not focussed on CNN design, experiments with a pre-trained CNN model are conducted instead. All cell images have three channels showing different fluorophores: DAPI stain for nuclei, fibrillarin antibody (anti-fibrillarin) and ethidium bromide (EtBr) for staining nucleoli. A graph of SSE for each value of k is plotted, which usually takes the shape of an arm, and the value of k corresponding to the elbow of the arm is chosen as an optimal value which represents the least value of k after which SSE scarcely varies. Sci Rep 11, 3364 (2021). Article (7). Implementation details of other handcrafted feature descriptors is provided in Supplementary Information S1. Similar to the intensity measure, the threshold to identify image gradient corresponding to HC is taken as the least \({m_i}\) of all the respective values of the cubic patches of the volumetric image. J. Electron. A comparison of the achieved segmentation results with the SOTA works10,11 on the same dataset is provided in Supplementary Table S1. For most nucleic acid stains, the fluorescent signal is minimal before binding to DNA or RNA, and there is a significant increase in fluorescence intensity after the dye has bound to DNA or RNA. To study the impact of computing third plane information for low resolution, 3D versions of SIFT, LBP, RSurf and SRP was compared with their corresponding pseudo forms that ignores the interslice intensity correlations. It is believed that DAPI associates with the minor groove of double-stranded DNA, with a preference for the adenine-thymine clusters. Although the dye is cell impermeant, higher concentrations will enter a live cell. Mach. Google Scholar. Loss of Nuclear DAPI stain I'm trying to figure out why certain nuclei in a population (in culture) might not be staining with DAPi. Accessibility Mean ranks of 3D handcrafted descriptors and FV-CNN from KruskalWallis test results for fibroblast and PC3 cell collections (a) AUC. However, the z-value (value of the z-statistic) of 0.6341 indicates a negative shift in the median of \(HC/EC_{PixelDifferences}\) from EPI to EMT at 1% significance level. Single-nucleus and bulk RNA sequencing reveal cellular and - Nature Quantitative analysis of variations in nuclear morphology and protein configuration helps to explain the mechanisms underlying cellular alterations and has opened new avenues for curative models in cancer care2,10,11. Fluorescent vital staining of plant sexual cell nuclei with DNA It has been widely used for objective DNA quantification as the amount of stain seen in the nucleus directly correlates with DNA content . Cellprofiler: Image analysis software for identifying and quantifying cell phenotypes. Leave the cells in ethanol at -20C for 5-15 minutes. From bow to cnn: Two decades of texture representation for texture classification. Although the mean F1 score for FV-CNN is lower than 3D SRP and 3D LBP for fibroblast cell images, statistical results demonstrate their performance to be similar (Fig. According to the obtained results, the proposed metrics based on SRP can be utilised to identify and characterise the ICS in EMT state of human prostate cancer cells. DAPI staining and DNA content estimation of nuclei in uncultivable Pattern Anal. ROC curves: 3D SRP vs Pseudo 3D SRP (a) Fibroblast dataset. It is followed by computing the ratio of HC to EC corresponding to the respective pixel values and pixel differences obtained from SRP functions. The nucleus accumbens revealed very high . However, the structure of the nucleus is unusually variable during the growth of the culture and in some cases may become almost a vesicular one. Nuclear size changes caused by local motion of cell boundaries unfold the nuclear lamina and dilate chromatin and intranuclear bodies. Image segmentation via multi-scale stochastic regional texture appearance models. Performance of 3D SRP is compared with deep learning features (Fisher vector based CNN features (FV-CNN), details in the Methods section) and other handcrafted feature descriptors, which employ distinct approaches for third plane inclusion and are comparatively recent, such as RSurf, and the widely utilised LBP and SIFT texture descriptors. Comput. In Fig. In The Corsini Encyclopedia of Psychology (Wiley, Hoboken, NJ, 2010). Feature learning with component selective encoding for histopathology image classification. 11) and adjacent pixel differences (Eq. Corresponding p-values and z-values characterise cells in \(EMT*\) as being of similar intensity but with slightly decondensed HC than in EPI state and cells in \(EMT^{179}\) as being of lower intensity and highly decondensed HC than in EPI and \(EMT*\) cells (see Supplementary Figs. Bonaccorsi S, Giansanti MG, Cenci G, Gatti M. Cold Spring Harb Protoc. To train the SVM classifier using the outer training set, 100 random samples within the outer training set are used to tune the RBF kernel parameter (gamma) following a heuristic search method47. The length of the line represents the comparison interval, and the extent of overlap of lines implies the range of similarity of corresponding groups. BOVW encoding is applied to the pseudo and non-pseudo versions of SRP, LBP, SIFT and RSurf and the resultant feature dimension is 64. Both DAPI and DAPI dilactate work well in these protocols. Cell Biol. Stoklasa, R. & Majtner, T. Texture analysis of 3d fluorescence microscopy images using rsurf 3d features. Rev. Unlike BOVW where the image is represented by the number of occurrences of the visual word, FV encodes the gradient of the log likelihood of features with respect to the GMM parameters (mean vector, standard deviation vector and mixing weights). in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops 22722280, (2018). As shown in Table1, the mean AUC and F1 score from the 10-fold cross-validation scheme have different standard deviation values for feature descriptors. 2014 Jul;255(1):7-19. doi: 10.1111/jmi.12133. 18, 717727 (2017). Recent developments in confocal microscopy have enabled more effective in-vivo intraoperative studies through 3D fluorescence images, to analyse the heterogeneity of cellular patterns16. Feature functions (\(f_{S}\), \(f_{G}\), \(f_{C}\), \(f_{A}\) and \(f_{R}\)) are obtained and horizontally concatenated to build SRP feature descriptor. Bischl, B., Mersmann, O., Trautmann, H. & Weihs, C. Resampling methods for meta-model validation with recommendations for evolutionary computation. 3, different colours of the lines indicate different mean ranks and population. 2011 Jan 1;2011(1):pdb.prot5557. In this study, we developed protocols for DAPI (4',6-diamidino-2-phenylindole) staining of Arcellinida nuclei and adapted protocols for ciliates. To obtain 5a, \(x^S_{i,j}\) is the pixel in the ith square ring (S) in jth position, \({x}^{Sqr}\) is the final vector built by concatenating sorted pixels of m concentric squares and \(p_{i}\) is the number of pixels in the ith square. Drain excess buffer from the coverslip and mount. The average dimension of cropped cell objects across all samples is \(64 \times 64\) pixels. IEEE Trans. 5b), options for patch size dimensions are odd numbers as \([(2n+1) \times (2n+1)]\) where n = 2,3,N and depend on the original dimensions of the input image and the level of the desired description. IEEE Trans. Litjens, G. et al. Using it directly for feature extraction does not demand any changes to the architecture by the user and provides robust deep learning features44,45. Why is the nucleolus so important? You are using a browser version with limited support for CSS. Pellet the cells by centrifugation and discard the ethanol. Sign up for the Nature Briefing newsletter what matters in science, free to your inbox daily. Standard SRP functions can be computed from the 2D images following Eqs. Carefully remove the coverslip and rinse the specimen briefly with PBS or dH. Accordingly, the high dimensional data vector D of dimension b is transformed to lower dimensional space L utilising the RP matrix with dimensions \(a \times b\) and simple linear operation: where the resultant dimension of L is a. Oncol. Phys. \(EMT*\) refers to the image set without \(EMT^{179}\). Scientific Reports (Sci Rep) In addition, SRP features offer more robust feature description as these are obtained by encoding intensity distributions of an image patch in square, circular and inter ring structure, while LBP utilises only pixel differences in circular pattern. A simple and robust protocol for immunostaining Arabidopsis pollen Pattern Anal. Corresponding to the high luminance contrast regions in DAPI images, in previous studies HC is identified by applying a threshold equal to the sum of the minimum intensity and sixty per cent of the difference between the maximum and minimum intensities9. Similarly, 3D SRP outperformed 3D LBP on the PC3 data set, as its capability to extract extensive information through hyperplanes was fully utilised for the images with a higher number of slices. 3d cell nuclear morphology: Microscopy imaging dataset and voxel-based morphometry classification results. FV for deep learning features is employed following the work of Song et al.45. Biochem Biophys Rep. 2023 Feb 6;34:101437. doi: 10.1016/j.bbrep.2023.101437. Epub 2012 Jan 31. 38, 113125 (1994). & Hinton, G. E. Imagenet classification with deep convolutional neural networks. Curr. DAPI may be used in flow cytometry systems utilizing UV excitation sources. 3b). (b) PC3 dataset. Thus, these conversions lead to the remodelling of chromatin structure inside the nucleus. DAPI staining carried out following the Hyalosphenia protocol. Commun Med (Lond). A z-stack of the . Dilute the DAPI stock solution to 3 M in staining buffer (100 mM Tris, pH 7.4, 150 mM NaCl, 1 mM CaCl. Han, F. et al. Unable to load your collection due to an error, Unable to load your delegates due to an error. Vision 127, 74109 (2019). The voxel size of all volumetric images from both sets is \(0.1318 \times 0.1318 \times 1\) \(\upmu {\text{ m }}^3\). The results shown in Table1 are obtained via 10-fold cross-validation (explained in Methods). Estandarte, A. K., Botchway, S., Lynch, C., Yusuf, M. & Robinson, I. . in 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 12121216 (IEEE, 2016). PC3 phenotypic states exhibit different and quantifiable nuclear morphological features that are useful in studying prostate cancer progression. Search Thermo Fisher Scientific. ADS & Wong, A. Soft Matter 15, 93109317 (2019). & Shilatifard, A. Chromatin signatures of cancer. the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Note that 3D SRP, 3D LBP and FV-CNN curves are overlapping in (a). Oncol. Sezgin, M. & Sankur, B. As evident from earlier studies10,11 on the same dataset, G0/G1 Serum Starvation Protocol imposes significant changes in cell size and shape, which refer to changes in lamins, the protein primarily responsible for nuclear size and shape. Therefore feature representation techniques such as BOVW15 and FV41,42 encoding are employed which group local feature descriptors into elements of a codebook that encodes many redundant local features into high-level features. McKight, P. E. & Najab, J. KruskalWallis test. This is represented as. Intercellular interactions within a tissue microenvironment take place through diverse mechanical and biochemical signals that control cellular development, differentiation and homeostasis1,2,3,4. Imai, R. et al. DAPI staining and microscoping. DAPI staining of nuclei also allows one to identify the nucleolus, which appears as a black cavity in the nucleus due to a threefold lower concentration of DNA in the nucleolus compared to the surrounding nucleoplasm (excluding centromeres) (Figure 1A; see fluorescence intensity plot). Remove excess liquid from the slide by gently blotting around the sample with an absorbent tissue. 23, R1113R1121 (2013). CAS In this work, the method employed follows Medeiros et al.39 where the RP matrix elements \((rp)^{ij}\) are obtained randomly as. FOIA To extract 3D SRP features, the existing 2D SRP is thus extended and the third plane information is proposed to be accessed using cubic patches and building multiple hyperplanes within the patch. rocyte nucleus, and free merozoites (m) could also be observed. Research on novel handcrafted feature descriptors thus remains active despite the success of deep learning12,13,14,15, as they perform competently for well-defined problems and do not require massive amounts of data for training. P.R. 15, 802812 (2014). Cellular changes at the molecular level can be understood through an adequate feature description capable of capturing low-level details of cells in multi-dimensions. Its blue fluorescence stands out in vivid contrast to green, yellow, or red fluorescent probes of other structures. To overcome high intraclass and low interclass variations, robust texture description is required, alongside compact and efficient representation to make it useful in real life applications. This is because RP achieves compact representation of high dimensional data and preserves its inter-distances when projecting values to a lower dimensional space. Incubate the specimen in the dark for 30 minutes at room temperature. 142, 2336 (2016). The lifetime of DAPI bound to interphase chromosomes within a 3:1 methanol:acetic acid fixed nucleus from the GM18507 lymphocyte cell line was also imaged, as shown in Fig. Biol. Figure 2 demonstrates performance of classification models for all the folds through the ROC plots. Low dimensional representation of fisher vectors for microscopy image classification. Five SRP functions for each hyperplane (\(f_{{G}_{h}}\), \(f_{{C}_{h}}\), \(f_{{S}_{h}}\), \(f_{{A}_{h}}\), \(f_{{R}_{h}}\)) are computed and concatenated across all hyperplanes built along the YZ plane of the cubic patch. Incubate for 15 minutes at room temperature. Internet Explorer). The area of each nucleus was . (a) Represents pixel value in 1st Square ring (S) at j th position. Liu, L., Fieguth, P., Kuang, G. & Zha, H. Sorted random projections for robust texture classification. DAPI as a useful stain for nuclear quantitation - PubMed White circles: cells with lipid . This process is repeated ten times by rotating the sampling of the holdout set, so that the entire dataset are tested with the 10-fold cross-validation. Following classification, heterochromatin intensity and aggregation is measured using the proposed 3D SRP. DAPI can also serve to fluorescently label cells for analysis in multicolor flow cytometry experiments. Genome Biol. (b) Pixel values and differences are extracted in five different patterns from image patch size of \(5 \times 5\) pixels followed by computation of local sorted descriptors (\({x}^{Glob}\), \({x}^{Sqr}\), \({x}^{Circ}\), \(\Delta ^{Ang}\) and \(\Delta ^{Rad}\)) using Eq.
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