• Environmental Analysis Health and Toxicology
• /
• v.17 no.1
• /
• pp.53-61
• /
• 2002

Histopathological changes and cadmium accumulations in the gills were investigated in crucian carp (Carassius auratus) exposed to 0, 0.01, 0.1, 0.5 mg/1 cadmium (Cd) concentrations for 25 days. After 25 days of exposure. cadmium accumulations increased in each of the different exposure concentrations. Histopathological changes in the gills of curcian carp exposed to cadmium included the acidification of mucous cell, the terminal clubbing of lamellae, the hyperplasia of epitherial cell and the curved of secondary lamellae. The similar histopathological changes were observed once the accumulations of cadmium reached the similar levels found in the present study with the different exposure schemes. Also the acidification of mucous cell in gills appeared when cadmium accumulations reached 5 $\mu\textrm{g}$/g and more. These results suggested that histopathological changes in the gills, an appearance of mucous cell acidification. be used to estimate the relation between toxic effect and cadmium accumulations in the gills.

• Journal of dental hygiene science
• /
• v.22 no.2
• /
• pp.83-89
• /
• 2022

Background: Estrogen deficiency affects the structure and function of the salivary glands in women, leading to a decrease in salivary secretion and a change in the composition of saliva. Previous studies on changes in the salivary glands that cause estrogen deficiency have reported only partial results for the parotid and submandibular glands, and there are few comparative morphological studies of histological changes between the parotid and submandibular glands in ovariectomized rats (OVX) leading to estrogen deficiency. This study aimed to analyze the histopathological and histochemical changes in the parotid and submandibular salivary glands causing estrogen deficiency by using OVX, and to discuss the mechanism on these changes. Methods: The parotid and submandibular glands from sacrificed control and OVX groups were fixed with cold 4% paraformaldehyde in phosphate buffer (pH 7.2). The tissues were dehydrated using a series of graded ethyl alcohol and embedded in paraffin. For histopathological analysis, sections cut to a thickness of 6 to 7 ㎛ were stained with hematoxylin and eosin (H&E). For histochemical analysis, Periodic acid-Schiff (PAS), Alcian blue (AB, pH 2.5), and PAS+AB (pH 2.5 and pH 1) staining was performed. Results: Histopathological analysis of OVX tissue showed that the parotid and submandibular salivary glands were broadly and clearly separated and divided into lobes. In OVX, acinar and ductal cells with condensed polymorphic or pyknotic nucleus, which are presumed to be characteristic of apoptotic cells, and degenerated cells with lipid deposition in cytoplasmic granules and ruptured membranes were increased. Histochemical analysis of OVX, confirmed an increase in the number and acidification of acinar secretory granules. Conclusion: Histopathological and histochemical changes and the effects of estrogen deficiency are more evident in the submandibular salivary gland than in the parotid gland.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.399-401
• /
• 2022

A definitive diagnosis to classify the breast malignancy status may be achieved by microscopic analysis using surgical open biopsy. However, this procedure requires experts in the specializing of histopathological image analysis directing to time-consuming and high cost. To overcome these issues, deep learning is considered practically efficient to categorize breast cancer into benign and malignant from histopathological images in order to assist pathologists. This study presents a pre-trained convolutional neural network model architecture with a 100% fine-tuning scheme and Adagrad optimizer to classify the breast cancer histopathological images into benign and malignant using a 40× magnification BreaKHis dataset. The pre-trained architecture was constructed using the InceptionResNetV2 model to generate a modified InceptionResNetV2 by substituting the last layer with dense and dropout layers. The results by demonstrating training loss of 0.25%, training accuracy of 99.96%, validation loss of 3.10%, validation accuracy of 99.41%, test loss of 8.46%, and test accuracy of 98.75% indicated that the modified InceptionResNetV2 model is reliable to predict the breast malignancy type from histopathological images. Future works are necessary to focus on k-fold cross-validation, optimizer, model, hyperparameter optimization, and classification on 100×, 200×, and 400× magnification.

• Environmental Analysis Health and Toxicology
• /
• v.11 no.3_4
• /
• pp.45-51
• /
• 1996

Histopathological changes of gills and caudal fins isolated from fishes, Cyprinus carpio, Carassius auratus, and Hernibarbus labeo, which were killed by oxygen deficiency or toxic chemicals, were studied. The toxic chemicals were HCl, NaOH, chloroform, benzene, heavy metals(Cu, Cr, Zn, Pb, Hg), and o-dichlorobenzene. The exposure level was enough to kill the fishes within 30 minutes. Oxygen deficient water was prepared by aeration of nitrogen gas and the oxygen concentration was less than l ppm. Cryocutting was used for the rapid preparation of tissue slides and the tissues were stained by hematoxylin/eosin. In the fishes killed by hazardous chemicals, congestion and/or hyperplasia of secondary lamella and erosion of fin were found as the major histopathological changes. Whereas, these characteristics were not observed in gills or caudal fins of fishes killed by oxygen deficiency. These different bioindications appeared in the fishes killed by toxic substances or natural causes, can be used for the rapid identification of the causes of fish kills.

• Journal of Ecology and Environment
• /
• v.38 no.3
• /
• pp.307-318
• /
• 2015

The objectives of this study were to identify multi-level stressors from blood biomarkers to community-level bioindicators and diagnose the stream ecosystem health in polluted streams. Blood chemistry such as total protein ($T_{Pro}$), blood urea nitrogen ($B_{UN}$), total cholesterol ($T_{Cho}$) and $A_{lb}$umin ($A_{lb}$) were analyzed from sentinel fish tissues; the functions of kidney, gill and liver were significantly decreased in the impacted zone ($I_z$), compared to the control zone ($C_z$). Histopathological analysis showed that fish liver tissues were normal in the $C_z$. Fish liver tissues in the $I_z$, however, showed large cell necrosis and degeneration and also had moderate lobular inflammation and inflammatory cell infiltration of lymphocytic histocytes. Species biotic index (SBI) at species level and stream health assessment (SHA) at community level indicated that chemical impacts were evident in the $I_z$ (ecological health; poor - very poor), and this was matched with the blood tissue analysis and histopathological analysis. The impairments of the streams were supported by water chemistry analysis (nitrogen, phosphorus). Tolerance guild analysis and trophic guild analysis of fish were showed significant differences (P < 0.01) between $C_z$ and $I_z$. Overall, multiple parameter analysis from biomarker level (blood tissues) to bioindicator level (community health) showed significantly greater impacts in the $I_z$ than $C_z$. This approach may be effective as a monitoring tool in identifying the multilateral and forthcoming problems related to chemical pollution and habitat degradation of stream ecosystems.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.7
• /
• pp.3071-3074
• /
• 2014

Background: To investigate the related risk factors of postoperative nosocomial pneumonia (POP) in patients withI-IIIa lung cancer. Methods: Medical records of 511 patients who underwent resection for lung cancer between January 2012 to December 2012 were retrospectively reviewed. Risk factors of postoperative pneumonia were identified and evaluated by univariate and multivariate analyses. Results: The incidence of postoperative pneumonia in these lung cancer patients was 2.9% (15 cases). Compared with 496 patients who had no pneumonia infection after operation, older age (>60), histopathological type of squamous cell carcinoma and longer surgery time (>3h) were significant risk factors by univariate analysis. Other potential risk factors such as alcohol consumption, history of smoking, hypersensitivity, hypertension, diabetes mellitus and so on were not showed such significance in this study. Further, the multivariate analysis revealed that old age (>60 years) (OR 5.813, p=0.018) and histopathological type of squamous cell carcinoma (OR 5.831, p<0.001) were also statistically significant independent risk factors for postoperative pneumonia. Conclusions: This study demonstrated that being old aged (>60 years) and having squamous cell carcinoma histopathological type might be important factors in determining the risk of postoperative pneumonia in lung cancer patients after surgery.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2006.02a
• /
• pp.30-36
• /
• 2006

Tissue microarray (TMA) is an array-based technology allowing the examination of hundreds of tissue samples on a single slide. To handle, exchange, and disseminate TMA data, we need standard representations of the methods used, of the data generated, and of the clinical and histopathological information related to TMA data analysis. This study aims to create a comprehensive data model with flexibility that supports diverse experimental designs and with expressivity and extensibility that enables an adequate and comprehensive description of new clinical and histopathological data elements. We designed a Tissue Microarray Object Model (TMA-OM). Both the Array Information and the Experimental Procedure models are created by referring to Microarray Gene Expression Object Model, Minimum Information Specification For In Situ Hybridization and Immunohistochemistry Experiments (MISFISHIE), and the TMA Data Exchange Specifications (TMA DES). The Clinical and Histopathological Information model is created by using CAP Cancer Protocols and National Cancer Institute Common Data Elements (NCI CDEs). MGED Ontology, UMLS and the terms extracted from CAP Cancer Protocols and NCI CDEs are used to create a controlled vocabulary for unambiguous annotation. We implemented a web-based application for TMA-OM, supporting data export in XML format conforming to the TMA DES or the DTD derived from TMA-OM. TMA-OM provides a comprehensive data model for storage, analysis and exchange of TMA data and facilitates model-level integration of other biological models.

• The Korea Journal of Herbology
• /
• v.30 no.6
• /
• pp.47-53
• /
• 2015

Objectives : This study was performed to investigate the anti-diabetic effect of the fruit extract of Lycium chinense Mill(Lycii Fructus, LF) on multiple low-dose streptozotocin-induced diabetic rats.Methods : Male Sprague-Dawley rats were divided into three groups; normal, STZ-control, Lycii Fructus extractorally administrated 300 ㎎/㎏ group (STZ-LF). Diabetes was induced in rats by consecutive injection of streptozotocin (STZ) at doses of 30 ㎎/㎏ for 5 days. After 4 weeks, all rats were sacrificed, Fasting blood glucose, total cholesterol (CHO), triglyceride (TG) and HDL-Cholesterol were measured in sera of rats. Histopathological changes of pancreas, kidney, liver and lung tissues were observed by microscope after H&E, Periodic acid-Schiff (PAS) and Masson's trichrome staining. The changes of body weight, blood glucose, and food and water intake were also measured.Results : There were no differences in body, food intake and water intake in LF-administrated groups compared with STZ control group. However, LF extract significantly decreased the levels of serum glucose, CHO, TG and HDL-Cholesterol in diabetic rats. In histopathological analysis of kidney, liver and lung, LF-administrated groups showed the inhibition of morphological damage.Conclusions : These results suggest that LF have a biological action on multi low-dose STZ-induced diabetes in rats via decreasing the serum glucose, TG and TG levels and may protect the morphological changes of kidney, liver and lung.

• Journal of Multimedia Information System
• /
• v.7 no.1
• /
• pp.1-10
• /
• 2020

The image analysis is an important and predominant task for classifying the different parts of the image. The analysis of complex image analysis like histopathological define a crucial factor in oncology due to its ability to help pathologists for interpretation of images and therefore various feature extraction techniques have been evolved from time to time for such analysis. Although deep reinforcement learning is a new and emerging technique but very less effort has been made to compare the deep learning and deep reinforcement learning for image analysis. The paper highlights how both techniques differ in feature extraction from complex images and discusses the potential pros and cons. The use of Convolution Neural Network (CNN) in image segmentation, detection and diagnosis of tumour, feature extraction is important but there are several challenges that need to be overcome before Deep Learning can be applied to digital pathology. The one being is the availability of sufficient training examples for medical image datasets, feature extraction from whole area of the image, ground truth localized annotations, adversarial effects of input representations and extremely large size of the digital pathological slides (in gigabytes).Even though formulating Histopathological Image Analysis (HIA) as Multi Instance Learning (MIL) problem is a remarkable step where histopathological image is divided into high resolution patches to make predictions for the patch and then combining them for overall slide predictions but it suffers from loss of contextual and spatial information. In such cases the deep reinforcement learning techniques can be used to learn feature from the limited data without losing contextual and spatial information.

• Journal of Veterinary Clinics
• /
• v.33 no.5
• /
• pp.290-294
• /
• 2016

A 13-month-old intact female poodle dog presented with an acute history of circling and seizure episodes. On the basis of the results of neurologic examination combined with magnetic resonance imaging and cerebrospinal fluid analysis (CSF), meningoencephalitis of unknown etiology (MUE) was suspected. Therapy with mycophenolate mofetil plus prednisolone was initiated, following which the clinical signs showed improvement for only one month before gradually worsening again. Acute progression of the clinical disease was observed, and the patient was euthanized 91 days after initial presentation. This case was definitively diagnosed as necrotizing meningoencephalitis (NME) according to the results of post-mortem histopathological examination. This report describes the clinical findings, serial magnetic resonance imaging (MRI) characteristics, and histopathological changes in a case of acute NME.