scholarly journals Estimation of three-dimensional chromatin morphology for nuclear classification and characterisation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Priyanka Rana ◽  
Arcot Sowmya ◽  
Erik Meijering ◽  
Yang Song
Keyword(s):  
Morphological Changes ◽  
Three Dimensional ◽  
Texture Feature ◽  
Genetic Alterations ◽  
Diagnosis And Prognosis ◽  
Chromatin Configuration ◽  
Nuclear Organisation ◽  
Phenotypic State ◽  
Chromatin Patterns ◽  
Nuclear Texture

AbstractClassification and characterisation of cellular morphological states are vital for understanding cell differentiation, development, proliferation and diverse pathological conditions. As the onset of morphological changes transpires following genetic alterations in the chromatin configuration inside the nucleus, the nuclear texture as one of the low-level properties if detected and quantified accurately has the potential to provide insights on nuclear organisation and enable early diagnosis and prognosis. This study presents a three dimensional (3D) nuclear texture description method for cell nucleus classification and variation measurement in chromatin patterns on the transition to another phenotypic state. The proposed approach includes third plane information using hyperplanes into the design of the Sorted Random Projections (SRP) texture feature and is evaluated on publicly available 3D image datasets of human fibroblast and human prostate cancer cell lines obtained from the Statistics Online Computational Resource. Results show that 3D SRP and 3D Local Binary Pattern provide better classification results than other feature descriptors. In addition, the proposed metrics based on 3D SRP validate the change in intensity and aggregation of heterochromatin on transition to another state and characterise the intermediate and ultimate phenotypic states.

scholarly journals Estimation of Three-Dimensional Chromatin Morphology for Nuclear Classification and Characterisation

2020 ◽  
Author(s):  
Priyanka Rana ◽  
Arcot Sowmya ◽  
Erik Meijering ◽  
Yang Song
Keyword(s):  
Prostate Cancer ◽  
Early Diagnosis ◽  
Human Fibroblast ◽  
Prostate Cancer Cell ◽  
Three Dimensional ◽  
Human Prostate Cancer ◽  
3D Image ◽  
Human Prostate Cancer Cell ◽  
Phenotypic State ◽  
Nuclear Texture

AbstractClassification and characterisation of cellular morphological states are vital for understanding cell differentiation, development, proliferation and diverse pathological conditions. As the onset of morphological changes transpires following genetic alterations in the chromatin configuration inside the nucleus, the nuclear texture as one of the low-level properties if detected and quantified accurately has the potential to provide insights on nuclear organisation and enable early diagnosis and prognosis. This study presents a three dimensional (3D) nuclear texture description method for cell nucleus classification and variation measurement in chromatin patterns on the transition to another phenotypic state. The proposed approach includes third plane information using hyperplanes into the design of the Sorted Random Projections (SRP) texture feature. The significance of including third plane information for low-resolution volumetric images is investigated by comparing the performance of 3D texture descriptor with its respective pseudo 3D form that ignores the interslice intensity correlations. Following classification, changes in chromatin pattern are estimated by computing the ratio of heterochromatin and euchromatin corresponding to their respective intensities and image gradient obtained by 3D SRP. The proposed method is evaluated on two publicly available 3D image datasets of human fibroblast and human prostate cancer cell lines in two phenotypic states obtained from the public Statistics Online Computational Resource. Experimental results show that 3D SRP and 3D Local Binary Pattern provide better results than other utilised handcrafted descriptors and deep learning features extracted using a pre-trained model. The results also show the advantage of utilising 3D feature descriptor for classification over its corresponding pseudo version. In addition, the proposed method validates that as the cell passes to another phenotypic state, there is a change in intensity and aggregation of heterochromatin.Author SummaryAutomated classification and measurement of cellular phenotypic traits can significantly impact clinical decision making. Early detection of diseases requires an accurate description of low-level cellular features to detect small-scale abnormalities in the few abnormal cells in the tissue microenvironment. The challenge is the development of a computational approach for 3D textural feature description that can capture the heterogeneous information in multiple dimensions and characterise the cells in their ultimate and intermediate phenotypic states effectively. Our work has proposed the method and metrics to measure chromatin condensation pattern and classify the phenotypic states. Experimental evaluation on the 3D image set of human fibroblast and human prostate cancer cell collections validates the proposed method for the classification of cell states. Results also signify the credibility of proposed metrics to characterise the cellular phenotypic states and contributes to studies related to early diagnosis, prognosis and drug resistance.

Thermal characterization of ABS-Graphene blended three dimensional printed functional prototypes for electro chemical energy storage

2018 ◽  
Vol 1 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Kamaljit Singh Boparai ◽  
Rupinder Singh
Keyword(s):  
Energy Storage ◽  
Structural Changes ◽  
Fused Deposition Modeling ◽  
Morphological Changes ◽  
Three Dimensional ◽  
Thermal Characterization ◽  
Chemical Energy ◽  
Flow Index ◽  
Fused Deposition

This study highlights the thermal characterization of ABS-Graphene blended three dimensional (3D) printed functional prototypes by fused deposition modeling (FDM) process. These functional prototypes have some applications as electro-chemical energy storage devices (EESD). Initially, the suitability of ABS-Graphene composite material for FDM applications has been examined by melt flow index (MFI) test. After establishing MFI, the feedstock filament for FDM has been prepared by an extrusion process. The fabricated filament has been used for printing 3D functional prototypes for printing of in-house EESD. The differential scanning calorimeter (DSC) analysis was conducted to understand the effect on glass transition temperature with the inclusion of Graphene (Gr) particles. It has been observed that the reinforced Gr particles act as a thermal reservoir (sink) and enhances its thermal/electrical conductivity. Also, FT-IR spectra realized the structural changes with the inclusion of Gr in ABS matrix. The results are supported by scanning electron microscopy (SEM) based micrographs for understanding the morphological changes.

scholarly journals Right Ventricular Global and Regional Remodeling in American-Style Football Athletes: A Longitudinal 3D Echocardiographic Study

2021 ◽  
Vol 11 (8) ◽  
pp. 3357
Author(s):  
Amir Hodzic ◽  
Gabriel Bernardino ◽  
Damien Legallois ◽  
Patrick Gendron ◽  
Hélène Langet ◽  
...  
Keyword(s):  
Right Ventricular ◽  
Morphological Changes ◽  
Three Dimensional ◽  
Computational Method ◽  
Physiological Adaptation ◽  
Volumetric Assessment ◽  
American Style ◽  
Few Data ◽  
The Right ◽  
Field Position

Few data exist concerning the right ventricular (RV) physiological adaptation in American-style football (ASF) athletes. We aimed to analyze the RV global and regional responses among ASF-trained athletes. Fifty-nine (20 linemen and 39 non-linemen) ASF athletes were studied before and after inter-seasonal training. During this period, which lasted 7 months, all athletes were exposed to combined dynamic and static exercises. Cardiac longitudinal changes were examined using three-dimensional transthoracic echocardiography. A computational method based on geodesic distances was applied to volumetrically parcellate the RV into apical, outlet, and inlet regions. RV global and regional end-diastolic volumes increased significantly and similarly in linemen and non-linemen after training, with predominant changes in the apex and outlet regions. RV global and regional ejection fractions were preserved. Morphological changes were uniformly distributed among the four cardiac chambers, and it was independent of the field position. Assessment of RV end-diastolic global, inlet and apical volumes showed low intra-observer (3.3%, 4.1%, and 5.3%, respectively) and inter-observer (7%, 12.2%, and 9%, respectively) variability, whereas the outlet regional volumetric assessment was less reproducible. To conclude, ASF inter-seasonal training was associated with a proportionate biventricular enlargement, regardless of the field position. Regional RV analysis allowed us to quantify the amount of exercise-induced remodeling that was larger in the apical and outlet regions.

scholarly journals Nuclear Morphology Optimized Deep Hybrid Learning (NUMODRIL) For Accurate Diagnosis and Prognosis of Ovarian Cancer

2021 ◽  
Author(s):  
Duhita Sengupta ◽  
Sk Nishan Ali ◽  
Aditya Bhattacharya ◽  
Joy Mustafi ◽  
Asima Mukhopadhyay ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cancer Cells ◽  
Morphological Changes ◽  
Hybrid Learning ◽  
Nuclear Shape ◽  
Machine Learning Techniques ◽  
Serous Carcinoma ◽  
Altered Expression ◽  
Diagnosis And Prognosis ◽  
Wide Range

Abstract Nuclear morphological features are potent determining factors for clinical diagnostic approaches adopted by pathologists to analyse the malignant potential of cancer cells. Considering the structural alteration of nucleus in cancer cells, various groups have developed machine learning techniques based on variation in nuclear morphometric information like nuclear shape, size, nucleus-cytoplasm ratio and various non-parametric methods like deep learning have also been tested for analysing immunohistochemistry images of tissue samples for diagnosing various cancers. Our aim is to study the morphometric distribution of nuclear lamin proteins as a specific parameter in ovarian cancer tissues. Besides being the principal mechanical component of the nucleus, lamins also present a platform for binding of proteins and chromatin thereby serving a wide range of nuclear functions like maintenance of genome stability, chromatin regulation. Altered expression of lamins in different subtypes of cancer is now evident from data across the world. It has already been elucidated that in ovarian cancer, extent of alteration in nuclear shape and morphology can determine degree of genetic changes and thus can be utilized to predict the outcome of low to high form of serous carcinoma. In this work, we have performed exhaustive imaging of ovarian cancer versus normal tissue and introduced a novel Deep Hybrid Learning approach on the basis of the distribution of lamin proteins. Although developed with ovarian cancer datasets in view, this architecture would be of immense importance in accurate and fast diagnosis and prognosis of all types of cancer associated with lamin induced morphological changes and would perform across small/medium to large datasets with equal efficiency.

scholarly journals The new proposed method for texture modification of closed up face image based on image processing using local weighting pattern (LWP) with enhancement technique

2018 ◽  
Vol 7 (2.2) ◽  
pp. 94
Author(s):  
Achmad Fanany Onnilita Gaffar ◽  
Darius Shyafary ◽  
Rony H ◽  
Arief Baramanto Wicaksono Putra
Keyword(s):  
Three Dimensional ◽  
Texture Feature ◽  
Face Image ◽  
Design Element ◽  
Feature Description ◽  
Local Pattern ◽  
Spatial Intensity Distribution ◽  
Texture Modification ◽  
Rgb Image

The texture is a two- and three-dimensional design element that is distinguished by the visual and physical properties perceived. Textured areas in the image can be marked with uniform or varying spatial intensity distribution. There are many techniques and methods from simple to sophisticated which available including machine learning-based methods to modify the texture map. The texture feature description becomes a new challenge in the field of computer vision and pattern recognition since the emergence of the local pattern binary method (LBP). This study proposes a new method called Local Weighting Pattern (LWP) for modifying textures based on the pixel's neighborhood of an RGB image. The results of this study obtained that LWP method produces a texture with a unique and artistic visualization. The Log function has been used to improve the image quality of the LWP method.  

scholarly journals A hybrid fusion of wireless signals and RGB image for indoor positioning

2018 ◽  
Vol 14 (2) ◽  
pp. 155014771875766 ◽  
Author(s):  
Jichao Jiao ◽  
Fei Li ◽  
Weihua Tang ◽  
Zhongliang Deng ◽  
Jichang Cao
Keyword(s):  
Three Dimensional ◽  
Texture Feature ◽  
Local Binary Patterns ◽  
Indoor Positioning ◽  
Location Based Services ◽  
Coarse Grained ◽  
Wireless Data ◽  
Indoor Location ◽  
Matching Process ◽  
Positioning Algorithm

In this article, we propose a new indoor positioning algorithm using smartphones, where wireless signals and images are deeply combined together to improve the positioning performance. Our approach is based on the use of local binary patterns’ feature, which has the advantages of rotation invariance and scale invariance. Moreover, the term “uniform” are fundamental properties of local image textures and their occurrence histogram is proven to be a very powerful texture feature. Besides, the received signal strength acts as a reliable cue on a person’s identity. We first obtain a coarse-grained estimation based on the visualization of wireless signals, which are presented by a vector, making use of fingerprinting methods. Then, we perform a matching process to determine correspondences between two-dimensional pixels and three-dimensional points based on images collected by the smartphone. After being evaluated by experiments, our proposed method demonstrates that the combination of the visual and the wireless data significantly improves the positioning accuracy and robustness. It can be widely applied to smartphones to better analyze human behavior and offer high-accuracy indoor location–based services.

99 DIFFERENTIAL GENE REGULATION OF STEROIDOGENIC TRANSCRIPTS AND ESTRADIOL PRODUCTION FOLLOWING IN VITRO PIG EMBRYO ELONGATION IN ALGINATE HYDROGEL THREE-DIMENSIONAL MATRIX

2012 ◽  
Vol 24 (1) ◽  
pp. 162
Author(s):  
J. R. Miles ◽  
C. N. Sargus ◽  
S. A. Plautz ◽  
J. L. Vallet ◽  
A. K. Pannier
Keyword(s):  
Equal Opportunity ◽  
Culture Media ◽  
Morphological Changes ◽  
Three Dimensional ◽  
Differential Gene Regulation ◽  
Alginate Hydrogels ◽  
The Media ◽  
And Control

Between Day 10 and 12 of gestation, the pig embryo elongates from a sphere to a long thin, filament. During this time, the embryo increases the production of oestrogen via an increase in steroidogenic transcripts, which is critical for maternal recognition of pregnancy. To date, attempts to elongate porcine embryos in vitro have been unsuccessful. Therefore, the objective of this study was to utilise alginate hydrogels to establish a culture system that promotes in vitro embryo elongation with a corresponding increase in steroidogenic transcripts and oestradiol production. In 3 replicate collections, White crossbred gilts (n = 15) were bred at Day 0 of the oestrous cycle. At Day 9 of gestation, reproductive tracts were collected and flushed with RPMI-1640 containing antibiotics. Embryos were recovered, grouped according to size and washed with RPMI-1640 containing antibiotics and 10% fetal bovine serum (FBS). Embryos were randomly assigned to be encapsulated using a double encapsulation technique (0.7% sodium alginate and 1.5% calcium chloride solution) or used as controls. Encapsulated and control embryos were cultured for 96 h in CO2 -pretreated RPMI-1640 containing antibiotics and 10% FBS at 38°C, 5% CO2 in air and 100% humidity. Every 24 h, the embryos were imaged and half of the media was replaced. The removed media was stored at –20°C and used to assess oestradiol levels by radioimmunoassay. At the end of culture, a subset of encapsulated and control embryos were snap frozen and used to assess the expression level of steroidogenic transcripts (STAR, CYP11 and CYP19) using quantitative PCR. All data were analysed using general linear model (GLM) procedures for ANOVA. Cell survival, assessed by blastocyst fragmentation and confirmed by live/dead staining in representative embryos, was greater (P = 0.01) for encapsulated embryos (60.1 ± 4.8%) compared with controls (33.3 ± 4.8%). Of encapsulated embryos, 27% had some morphological change (minor flattening and tubal formation) and 14% had significant morphological changes (considerable flattening and tubal formation elongating through the gel), consistent with in vivo embryo elongation. In contrast, the control embryos had no morphological changes observed and remained spherical during culture. The expression levels of STAR, CYP11 and CYP19 were significantly (P < 0.05) greater in encapsulated embryos compared with control embryos. Furthermore, a significant (P < 0.01) time-dependent increase in oestradiol levels in the culture media of encapsulated embryos was identified compared with controls and culture media alone. These results illustrate that cultured pig embryos encapsulated in alginate hydrogels undergo limited morphological changes with increased expression of steroidogenic transcripts and oestrogen production. †USDA is an equal opportunity provider and employer.

Dysregulation of chromatin organization in pediatric and adult brain tumors: oncoepigenomic contributions to tumorigenesis and cancer stem cell properties

Genome ◽  
2020 ◽  
pp. 1-11
Author(s):  
Seungil Paik ◽  
Francesca Maule ◽  
Marco Gallo
Keyword(s):  
Brain Tumors ◽  
Cell Fate ◽  
Three Dimensional ◽  
Genetic Alterations ◽  
Adult Brain ◽  
Post Translational Modifications ◽  
3D Genome ◽  
Differentiated Cells ◽  
Aberrant Dna Methylation ◽  
And Function

The three-dimensional (3D) organization of the genome is a crucial enabler of cell fate, identity, and function. In this review, we will focus on the emerging role of altered 3D genome organization in the etiology of disease, with a special emphasis on brain cancers. We discuss how different genetic alterations can converge to disrupt the epigenome in childhood and adult brain tumors, by causing aberrant DNA methylation and by affecting the amounts and genomic distribution of histone post-translational modifications. We also highlight examples that illustrate how epigenomic alterations have the potential to affect 3D genome architecture in brain tumors. Finally, we will propose the concept of “epigenomic erosion” to explain the transition from stem-like cells to differentiated cells in hierarchically organized brain cancers.

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