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Higher Harmonic Generation Imaging for Neuropathology
Published in Francesco S. Pavone, Shy Shoham, Handbook of Neurophotonics, 2020
Nikolay Kuzmin, Sander Idema, Eleonora Aronica, Philip C. de Witt Hamer, Pieter Wesseling, Marie Louise Groot
In Kuzmin et al. [15] THG/SHG imaging was shown provide label-free images of human tumor tissue of histopathological quality, in real time. In the THG tumor images increased cellularity, nuclear pleomorphism, and rarefaction of neuropil in fresh, unstained human brain tissue could be recognized. In Figure 23.7 we show two examples that further illustrate this: In Figure 23.7A a tumor has led to rarefication of the axon matrix (i.e. the intense green “wires”), and an increased number of (tumor) cell nuclei is visible in the resulting open spaces. Areas varying in cellular density can be recognized by an inverse change in THG intensity, because the tumor nuclei give a THG intensity lower than of the axon matrix. Figure 23.7B represents a focus of high-grade glioma in which the axon matrix has completely been replaced by tumor cells associated with vascular proliferation (the latter visible by the red SHG signals from the collagen in the vessel walls). In the high-grade glioma focus, the tumor nuclei can be observed to have a more variable size and shape, consistent with the polymorphism of high-grade glioma cells. Also, the nuclei appear to generate more homogeneously intense THG signal over their whole volume than in the low-grade case, perhaps due to changes in chromatin organization.
Artificial Neural Approach to Analysing the Prognostic Significance of DNA Ploidy and Cell Cycle Distribution of Breast Cancer Aspirate Cells
Published in Raouf N.G. Naguib, Gajanan V. Sherbet, Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management, 2001
The divergence of opinion concerning the prognostic significance of these cellular features could be attributed to the degree of sophistication of statistical techniques employed and the difficulties associated with assigning weighting to individual cellular attributes or dissecting out specific features in order to assess their individual merits as prognostic factors. We demonstrated in previous studies that artificial neural networks (ANNs) are capable of predicting lymph node metastasis in breast cancer patients using measurements relating to the expression of specific markers [15,16]. We previously investigated FNA samples relating to benign conditions as well as carcinomas of the breast using image cytometry (ICM). We showed that cellular features such as DNA ploidy, size of the SPF, cell cycle distribution, and nuclear pleomorphism of breast cancer FNA cells could be analysed using ANNs and successfully used to predict subclinical metastatic disease [17]. In that study, DNA ploidy ranged from 2n to 12.5n, the median being 4n, with a few tumours being hypodiploid. The relative distribution of cells between the G0G1 and G2M phases of the cell cycle, viz. the G0G1/G2M ratio, which is regarded as an aspect of DNA aneuploidy, did not correspond with DNA aneuploidy. Only 25% of samples were aneuploid by this criterion, as compared with 82% that were hyperdiploid as indicated by DNA indices. Nonetheless, by neither criterion did DNA ploidy show any relationship to nodal status. The size of the SPF ranged from 2% to 36%, with a median value of 12%. The nuclear pleomorphism index (NPI) ranged from 0.58 to 1.0.
Corneal Endothelium Regeneration: Basic Concepts
Published in Gilson Khang, Handbook of Intelligent Scaffolds for Tissue Engineering and Regenerative Medicine, 2017
In humans, corneal endothelial cells have limited proliferative capacity in vivo and do not replicate after severe defects, losing corneal endothelial cells significantly.10,17 Innately, there are many dystrophies related to the corneal endothelium, such as Fuchs’ dystrophy, posterior polymorphous dystrophy (PPD), congenital hereditary endothelial dystrophy (CHED), iridocorneal endothelial syndrome (ICE), and intermediate forms (Table 36.1).18,19,20,21–22 These dystrophies needs transplantation for recovery of corneal endothelial cells. Also, some reasons such as aging, accident, trauma, scar, injury, failure of corneal transplantation, contact lens wear, and stress caused by certain systemic diseases such as diabetes, glaucoma, and endothelial dystrophies result in defects in the corneal endothelium and lead to continuous cell loss. Cell loss occurring at a faster rate than normal ones results in endothelial dysfunction years after the original injury.3 Dystrophies and defecting factors induce decreased density of corneal endothelial cells. This reduced cell density is going through increasing size (polymegathism) and changing phenotype of cells (pleomorphism). The excessive corneal endothelial cells loss by diverse causes leads to malfunction of the corneal endothelium.1–3 It means that functions of corneal endothelial cells deteriorate irreversibly when cell density falls below a critical lower threshold, which is presumed to be ~500 cells/mm2.23 This phenomenon can lead to corneal edema due to the stroma’s high capacity to absorb fluid, which impairs corneal transparency and eventually results in corneal blindness.
Antitumor activity of solamargine in mouse melanoma model: relevance to clinical safety
Published in Journal of Toxicology and Environmental Health, Part A, 2022
Ricardo Andrade Furtado, Saulo Duarte Ozelin, Natália Helen Ferreira, Bárbara Ayumi Miura, Silvio Almeida Junior, Geórgia Modé Magalhães, Eduardo José Nassar, Mariza Abreu Miranda, Jairo Kenupp Bastos, Denise Crispim Tavares
Considering that the number of mitoses expresses cell division activity, solamargine treatment reduced cell proliferation and tumor weight being indicative of antitumor activity. The mitosis rate is a strong indicator of proliferation and is an important prognostic factor for malignant melanoma (Massi, Franchi, and Santucci 2002). Further, the antitumor activity of solamargine was evidenced by decrease in pleomorphisms, since cell pleomorphism is linked to the high proliferative rate observed in melanomas (Camargo, Conceição, and Costa 2008).