Search

Catalpa bungei 'Jinsi', a cultivar of C. bungei C. A. Mey., is valued for its heartwood with good overall mechanical properties, naturally durable and golden-yellow color. Little is known about heartwood formation in C. bungei 'Jinsi' trees. The behavior of starch, water, and nuclei was studied in the xylem tissue of C. bungei 'Jinsi' concerning aging in ray parenchyma cells. Blocks containing heartwood, golden zone, transition zone, and sapwood were collected from the stems of six C. bungei 'Jinsi' trees. The moisture content of the blocks was measured by oven drying. Changes in starch and nuclei in ray parenchyma were investigated in radial profiles from sapwood to heartwood blocks using microscopy and various staining techniques. The nuclear size and starch content gradually decreased to heartwood. While the horizontal distribution of moisture content of C. bungei 'Jinsi' was very varied, with the heartwood and golden zone being lower than sapwood but slightly higher than the transition zone. Starch grains were rare, but nuclei were still present in some ray parenchyma cells in the heartwood and golden zone. The nuclei showed irregular shape and elongation before disintegration. These results suggest that the most apparent change occurs in the transition zone, the critical location involved in forming C. bungei 'Jinsi' heartwood. Water and starch appear to be actively engaged in heartwood formation. The loss of function of ray parenchyma cells results from heartwood formation., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Accurately segmented nuclei are important, not only for cancer classification, but also for predicting treatment effectiveness and other biomedical applications. However, the diversity of cell types, various external factors, and illumination conditions make nucleus segmentation a challenging task. In this work, we present a new deep learning-based method for cell nucleus segmentation. The proposed convolutional blur attention (CBA) network consists of downsampling and upsampling procedures. A blur attention module and a blur pooling operation are used to retain the feature salience and avoid noise generation in the downsampling procedure. A pyramid blur pooling (PBP) module is proposed to capture the multi-scale information in the upsampling procedure. The superiority of the proposed method has been compared with a few prior segmentation models, namely U-Net, ENet, SegNet, LinkNet, and Mask RCNN on the 2018 Data Science Bowl (DSB) challenge dataset and the multi-organ nucleus segmentation (MoNuSeg) at MICCAI 2018. The Dice similarity coefficient and some evaluation matrices, such as F1 score, recall, precision, and average Jaccard index ( AJI ) were used to evaluate the segmentation efficiency of these models. Overall, the proposal method in this paper has the best performance, the AJI indicator on the DSB dataset and MoNuSeg is 0.8429, 0.7985, respectively.

Research on the mechanical properties of brain tissue has gradually deepened recently. Two indentation protocols were used here to characterize the mechanical properties of cortical tissues. Further, histological staining was used to explore the correlation between the mechanical properties and microstructure on the basis of the density of cell nuclei and proteoglycan content. No significant difference was observed in transient contact stiffness between the cerebral cortex and cerebellar cortex at the depth interval of 0-600 μm under the cortical surface; however, the average shear modulus of the cerebral cortex was higher than that of the cerebellar cortex. The cerebral cortex responded more quickly to the change in load and released stress more thoroughly than the cerebellar cortex. In addition, the density of cell nuclei was related to both the transient contact stiffness and second time constant of cortical tissues. Proteoglycan content had a more significant impact on the shear modulus, second time constant, and stress relaxation rate of cortical tissues. Exploring mechanical properties thoroughly will provide more detailed mechanical information for future brain chip implantation. Alternatively, linking the mechanical properties of cortical tissues to the microstructure can provide basic data for the design and manufacture of substitute materials for brain tissue., (Copyright © 2021. Published by Elsevier Ltd.)

Significance: Complementary absorption and fluorescence contrast could prove useful for a wide range of biomedical applications. However, current absorption-based photoacoustic microscopy systems require the ultrasound transducers to physically touch the samples, thereby increasing contamination and limiting strong optical focusing in reflection mode., Aim: We sought to develop an all-optical system for imaging cells and tissues using the three combined imaging modalities: photoacoustic remote sensing (PARS), epifluorescence, and confocal laser scanning microscopy (CLSM)., Approach: A PARS subsystem with ultraviolet excitation was used to obtain label-free absorption-contrast images of nucleic acids in ex vivo tissue samples. Co-integrated epifluorescence and CLSM subsystems were used to verify the 2D and 3D nuclei distribution., Results: Complementary absorption and fluorescence contrast were demonstrated in phantom imaging experiments and subsequent cell and tissue imaging experiments. Lateral and axial resolution of ultraviolet-PARS (UV-PARS) is shown to be 0.39 and 1.6  μm, respectively, with 266-nm light. CLSM lateral and axial resolution was measured as 0.97 and 2.0  μm, respectively. This resolution is sufficient to image individual cell layers with fine optical sectioning. UV-PARS images of cell nuclei are validated in thick tissue using CLSM., Conclusions: Multimodal absorption and fluorescence contrast are obtained with a non-contact all-optical microscopy system for the first time and utilized to obtain images of cells and tissues with subcellular resolution.

Purpose: The main goal of this study was to determine the relationship of cleaved-caspase-3 (C3)-related apoptosis and hepatic proliferation, during the liver repopulation in a living liver donor rat model., Material/methods: Thirty-three animals were randomized into eleven groups and evaluated on postoperative from 3 ​h until 384 ​h after 30%-partial hepatectomy (30%-PHx). Liver sections (5 ​μm) were processed by hematoxylin-eosin, and immunostaining for C3, accompanied by hepatic function test. C3 content and the hepatic lobule enlargement were analyzed by optical density, followed by cell counting., Results: Transient variations of alanine transferase (ALT), aspartate aminotransferase (AST) and lactate dehydrogenase (LDH) were found. Significant increase in the C3 levels, and cell nuclei number, were detected at 12 ​h and 48 ​h after 30%-PHx, evidencing a correlation of p ​= ​-0.3679., Conclusion: In the 30%-PHx rat model, C3-related apoptosis prevents proliferative pathological conditions during the hepatic lobule re-modeling., Competing Interests: Declaration of competing interest The authors declare no conflict of interests., (Copyright © 2021 Medical University of Bialystok. Published by Elsevier B.V. All rights reserved.)

Background: Oral squamous cell carcinoma (OSCC) is the most prevalent form of oral cancer. Very few researches have been carried out for the automatic diagnosis of OSCC using artificial intelligence techniques. Though biopsy is the ultimate test for cancer diagnosis, analyzing a biopsy report is a very much challenging task. To develop computer-assisted software that will diagnose cancerous cells automatically is very important and also a major need of the hour., Aim: To identify OSCC based on morphological and textural features of hand-cropped cell nuclei by traditional machine learning methods., Methods: In this study, a structure for semi-automated detection and classification of oral cancer from microscopic biopsy images of OSCC, using clinically significant and biologically interpretable morphological and textural features, are examined and proposed. Forty biopsy slides were used for the study from which a total of 452 hand-cropped cell nuclei has been considered for morphological and textural feature extraction and further analysis. After making a comparative analysis of commonly used methods in the segmentation technique, a combined technique is proposed. Our proposed methodology achieves the best segmentation of the nuclei. Henceforth the features extracted were fed into five classifiers, support vector machine, logistic regression, linear discriminant, k-nearest neighbors and decision tree classifier. Classifiers were also analyzed by training time. Another contribution of the study is a large indigenous cell level dataset of OSCC biopsy images., Results: We achieved 99.78% accuracy applying decision tree classifier in classifying OSCC using morphological and textural features., Conclusion: It is found that both morphological and textural features play a very important role in OSCC diagnosis. It is hoped that this type of framework will help the clinicians/pathologists in OSCC diagnosis., (© 2020 The Authors. Cancer Reports published by Wiley Periodicals LLC.)

One of the urgent problems arising while carrying out research in the field of scaffold technology is achieving an objective, direct, quantitative analysis of cells cultivated within a scaffold; one which allows characterization of the density distribution of the cells, their viability and their proliferative activity when encapsulated within the scaffold. This problem is associated with the peculiarities of cell cultivation in the three-dimensional structure of scaffolds, including limitations imposed on the possibility of direct cell counting using light microscopy. Also, most scaffolds are opaque, so this generally excludes methods of quantitative analysis using light microscopy. There are methods for the quantitative analysis of cells in a scaffold based on the assessment of their metabolic activity (for example: MTT test). However, these methods are indirect and can result in significant errors. This is due to differences in the metabolic activity of the cells, for example, in different phases of mitosis. Methods based on direct counting of the number of cells isolated from the scaffold are also characterized by a high degree of error that is associated with the loss of cells during the destruction of the scaffold. We describe in detail a method that allows the direct quantitation of cells within a scaffold. Modifications of the method make it possible both to analyze the proliferative activity of cells cultivated in a scaffold and to assess their viability and density distribution in the three-dimensional structure.•Direct rather than indirect analysis of the number of cells in the scaffold by counting the number of nuclei.•Carrying out research without destroying the scaffold structure.•Carrying out research without additional preliminary preparation of samples before staining., Competing Interests: 'The Authors confirm that there are no conflicts of interest., (© 2020 The Author(s).)

Cells respond to physical cues in their microenvironment. These cues result in changes in cell behavior, some of which are transient, and others of which are permanent. Understanding and leveraging permanent alteration of cell behavior induced by mechanical cues, or "mechanical memories," is an important aim in cell and tissue engineering. Herein, this paper reviews the existing literature outlining how cells may store memories of biophysical cues with a specific focus on the nucleus, the storehouse of information in eukaryotic cells. In particular, this review details mechanically driven adaptations in nuclear structure and genome organization and outlines potential mechanisms by which mechanical memories may be encoded within the structure and organization of the nucleus and chromatin., (© 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Extracellular matrix remodeling plays a pivotal role during mesenchyme patterning into different lineages. Tension exerted from cell membrane receptors bound to extracellular matrix ligands is transmitted by the cytoskeleton to the cell nucleus inducing gene expression. Here, we used dendrimer-based arginine-glycine-aspartic acid (RGD) uneven nanopatterns, which allow the control of local surface adhesiveness at the nanoscale, to unveil the adhesive requirements of mesenchymal tenogenic and osteogenic commitments. Cell response was found to depend on the tension resulting from cell-substrate interactions, which affects nuclear morphology and is regulated by focal adhesion size and distribution.

Within this study, we report about the design and biological characterization of novel cell-penetrating peptides (CPPs) with selective suborganelle-targeting properties. The nuclear localization sequence N50, as well as the nucleoli-targeting sequence NrTP, respectively, were fused to a shortened version of the cell-penetrating peptide sC18. We examined cellular uptake, subcellular fate and cytotoxicity of these novel peptides, N50-sC18* and NrTP-sC18*, and found that they are nontoxic up to a concentration of 50 or 100 µM depending on the cell lines used. Moreover, detailed cellular uptake studies revealed that both peptides enter cells via energy-independent uptake, although endocytotic processes cannot completely excluded. However, initial drug delivery studies demonstrated the high versatility of these new peptides as efficient transport vectors targeting specifically nuclei and nucleoli. In future, they could be further explored as parts of newly created peptide-drug conjugates.

Molecular oxygen in living cells is distributed and consumed inhomogeneously, depending on the activity of each organelle. Therefore, tractable methods that can be used to monitor the oxygen status in each organelle are needed to understand cellular function. Here we report the design of a new oxygen-sensing probe for use in the cell nucleus. We prepared "Ru-Hoechsts", each consisting of a phosphorescent ruthenium complex linked to a Hoechst 33258 moiety, and characterized their properties as oxygen sensors. The Hoechst unit shows strong DNA-binding properties in the nucleus, and the ruthenium complex shows oxygen-dependent phosphorescence. Thus, Ru-Hoechsts accumulated in the cell nucleus and showed oxygen-dependent signals that could be monitored. Of the Ru-Hoechsts prepared in this study, Ru-Hoechst b, in which the ruthenium complex and the Hoechst unit were linked through a hexyl chain, showed the most suitable properties for monitoring the oxygen status. Ru-Hoechsts are probes with high potential for visualizing oxygen fluctuations in the nucleus., (© 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

The segmentation of cell nuclei is an important step towards the automated analysis of histological images. The presence of a large number of nuclei in whole-slide images necessitates methods that are computationally tractable in addition to being effective. In this work, a method is developed for the robust segmentation of cell nuclei in histological images based on the principles of persistent homology. More specifically, an abstract simplicial homology approach for image segmentation is established. Essentially, the approach deals with the persistence of disconnected sets in the image, thus identifying salient regions that express patterns of persistence. By introducing an image representation based on topological features, the task of segmentation is less dependent on variations of color or texture. This results in a novel approach that generalizes well and provides stable performance. The method conceptualizes regions of interest (cell nuclei) pertinent to their topological features in a successful manner. The time cost of the proposed approach is lower-bounded by an almost linear behavior and upper-bounded by O(n 2 ) in a worst-case scenario. Time complexity matches a quasilinear behavior which is O(n 1+ɛ ) for ε < 1. Images acquired from histological sections of liver tissue are used as a case study to demonstrate the effectiveness of the approach. The histological landscape consists of hepatocytes and non-parenchymal cells. The accuracy of the proposed methodology is verified against an automated workflow created by the output of a conventional filter bank (validated by experts) and the supervised training of a random forest classifier. The results are obtained on a per-object basis. The proposed workflow successfully detected both hepatocyte and non-parenchymal cell nuclei with an accuracy of 84.6%, and hepatocyte cell nuclei only with an accuracy of 86.2%. A public histological dataset with supplied ground-truth data is also used for evaluating the performance of the proposed approach (accuracy: 94.5%). Further validations are carried out with a publicly available dataset and ground-truth data from the Gland Segmentation in Colon Histology Images Challenge (GlaS) contest. The proposed method is useful for obtaining unsupervised robust initial segmentations that can be further integrated in image/data processing and management pipelines. The development of a fully automated system supporting a human expert provides tangible benefits in the context of clinical decision-making., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Biological sample-preparation procedures have been developed for imaging human chromosomes under cryogenic conditions. A new experimental setup, developed for imaging frozen samples using beamline I13 at Diamond Light Source, is described. This manuscript describes the equipment and experimental procedures as well as the authors' first ptychographic reconstructions using X-rays.

Physical and chemical characteristics of materials are important regulators of cell behavior. In particular, cell elasticity is a fundamental parameter that reflects the state of a cell. Surface topography finely modulates cell fate and function via adhesion mediated signaling and cytoskeleton generated forces. However, how topographies alter cell mechanics is still unclear. In this work we have analyzed the mechanical properties of peripheral and nuclear regions of NIH-3T3 cells on azopolymer substrates with different topographic patterns. Micrometer scale patterns in the form of parallel ridges or square lattices of surface elevations were encoded on light responsive azopolymer films by means of contactless optical methods. Cell mechanics was investigated by atomic force microscopy (AFM). Cells and consequently the cell cytoskeleton were oriented along the linear patterns affecting cytoskeletal structures, e.g., formation of actin stress fibers. Our data demonstrate that topographic substrate patterns are recognized by cells and mechanical information is transferred by the cytoskeleton. Furthermore, cytoskeleton generated forces deform the nucleus, changing its morphology that appears to be related to different mechanical properties in the nuclear region.

Clusters or clumps of cells or nuclei are frequently observed in two dimensional images of thick tissue sections. Correct and accurate segmentation of overlapping cells and nuclei is important for many biological and biomedical applications. Many existing algorithms split clumps through the binarization of the input images; therefore, the intensity information of the original image is lost during this process. In this paper, we present a curvature information, gray scale distance transform, and shortest path splitting line-based algorithm which can make full use of the concavity and image intensity information to find out markers, each of which represents an individual object, and detect accurate splitting lines between objects using shortest path and junction adjustment. The proposed algorithm is tested on both synthetic and real nuclei images. Experiment results show that the performance of the proposed method is better than that of marker-controlled watershed method and ellipse fitting method., (© 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.)

Single-cell gel electrophoresis, or the comet assay, is usually performed with nucleoids prepared after a lysis of either whole cells (more often) or isolated cell nuclei (rarely). Electrophoretic properties of the second type of nucleoids have never been investigated carefully. We measured the kinetics of the DNA exit from nuclei-derived nucleoids in comparison with cell-derived nucleoids. The results show that general organization of the nuclei-derived nucleoids is not changed very much in comparison with nucleoids commonly obtained from whole cells. At the same time, in contrast to the cell-derived nucleoids, for which the exit is stepwise and cooperative, the DNA exit from the nuclei-derived nucleoids can be described by a simple monomolecular kinetics. This difference is probably due to agarose penetration into nuclei (but not into cells) before polymerization of the agarose gel. We suggest that single-nucleus gel electrophoresis may be a way for the comet assay standardization., (© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Background: The cysteine proteinase legumain is highly expressed in cancer. Legumain is a potential biomarker and has been suggested to be utilised for prodrug activation in cancer therapy. However, to define the suitability of legumain for such purposes, detailed knowledge of cell type-specific and subcellular expression together with proteolytic activity patterns in tumour tissue is necessary., Methods: Expression of legumain was examined in a panel of 277 primary tumours from colorectal cancer (CRC) patients using immunohistochemistry. Tumour (cytoplasmic diffuse, cytoplasmic granulated, and nuclear) and stromal cell expression of legumain was quantified, and associations with clinicopathological parameters and outcome were analysed. Additionally, normal colon tissue and spontaneous mouse tumours were stained for legumain., Results: Legumain was highly expressed in tumour and stromal cells. Nuclear legumain was detected in 30% of the tumours. In colon cancer patients, high legumain expression was associated with overall and metastasis-free survival (OS; MFS) in uni- and multivariate analysis. Nuclear legumain was associated with poor OS, but not MFS in the colon cancer subgroup. Cytoplasmic granulated or diffuse expression was not associated with OS or MFS. Normal epithelial cells exhibited granulated legumain mainly at the apical pole, and legumain was highly expressed in CD68 positive macrophages., Conclusions: Legumain is a highly expressed proteinase in CRC and associated with poor outcome in colon cancer. Diversified localisation of legumain expression in tumour and stromal cells suggests multiple functions in CRC, representing both a challenge and an opportunity for use in therapeutic targeting., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

With the rapid development of microscopy for cell imaging, there is a strong and growing demand for image analysis software to quantitatively study cell morphology. Automatic cell segmentation is an important step in image analysis. Despite substantial progress, there is still a need to improve the accuracy, efficiency, and adaptability to different cell morphologies. In this paper, we propose a fully automatic method for segmenting cells in fluorescence images of confluent cell monolayers. This method addresses several challenges through a combination of ideas. 1) It realizes a fully automatic segmentation process by first detecting the cell nuclei as initial seeds and then using a multi-object geometric deformable model (MGDM) for final segmentation. 2) To deal with different defects in the fluorescence images, the cell junctions are enhanced by applying an order-statistic filter and principal curvature based image operator. 3) The final segmentation using MGDM promotes robust and accurate segmentation results, and guarantees no overlaps and gaps between neighboring cells. The automatic segmentation results are compared with manually delineated cells, and the average Dice coefficient over all distinguishable cells is 0.88.