Search PubMed⌕ Search

Biomedical subjects

Kunio Doi

Publications and source records attributed to Kunio Doi.

At least 127 records · Page 7Linked to original sources
PubMed2003

Rat strain difference in histology and expression of Th1- and Th2-related cytokines in nasal mucosa after short-term formaldehyde inhalation.

Changes in histology and Th1- and Th2-related cytokines expression in nasal mucosa were examined in Brown Norway (BN) and Fischer 344 (F344) rats after 5-day inhalation of 1% formaldehyde aerosol. In F344 rats, mucosal lesions characterized by degeneration and/or desquamation of epithelial cells with neutrophil infiltration were observed at all levels of nasal cavity and all kinds of mucosal epithelia were involved in such lesions. In BN rats, mucosal lesions were milder and the olfactory epithelium was free from lesions. The levels of Th1-related cytokines (IFN-gamma and IL-2) were significantly depressed and those of Th2-related cytokines (IL-4 and IL-5) also tended to be depressed in BN rats. In F344 rats, similar but much less clear alterations in the levels of Th1- and Th2-related cytokines were observed. Such results of measurement of Th1- and Th2-related cytokines mRNAs seem to be interesting although their significance is still obscure.

Administration, Inhalation↗
PubMed2003

NMDA-induced apoptosis in the developing rat brain.

The N-methyl-D-aspartate receptor (NMDAR), which is one of the glutamate receptors, is considered to have a close relation to synaptic plasticity in the developing brain. In addition, it is also known that the excessive stimulation of NMDARs can trigger neuronal apoptosis. In this study, we examined the expression of neuronal apoptosis in the developing rat brain after the administration of NMDA to pregnant dams or neonates (embryonal days 18 to postnatal days 14). In the NMDA-treated group, the significant increase in nuclei of apoptotic neuronal cells occurred in the dose-dependent manner in the lateral-ventral regions of the fetal cerebral cortex, reaching maximum values at 24 hours after treatment. On the other hand, the induction of apoptosis did not occur in the neonatal brain.

Animals↗
PubMed2003

Effects of granulocyte colony-stimulating factor on the kinetics of inflammatory cells in the peripheral blood and pulmonary lesions during the development of bleomycin-induced lung injury in rats.

We evaluated the effects of granulocyte colony-stimulating factor (G-CSF) on the kinetics of inflammatory cells during the development of inflammation in bleomycin (BLM)-induced lung injury. G-CSF (100 microg/kg/day, s.c.) was administered to rats treated with or without BLM (2 mg/200 microl, intratracheally) for up to 14 days (Day 14) immediately after BLM treatment. In the BLM + G-CSF group, the lung injury score increased on Days 1 and 14, and the score of lung fibrosis on Day 14, respectively. Except for neutrophils, there were no effects of G-CSF on the number of inflammatory cells both in the peripheral blood and in the lung in both BLM-treated and -untreated rats at the acute inflammatory phase. In the G-CSF-treated groups, the number of neutrophil counts in the peripheral blood drastically increased on Day 1, temporally decreased on Day 3, and increased again on Days 7 and 14. The number of neutrophils in the lung markedly increased on Day 1 and then remained at a plateau level until Day 14. The neutrophil alkaline phosphatase score in the lung commenced to increase on Day 1, reached the maximal level on Day 7, and then remained at a plateau level until Day 14. Correlations between the numbers of neutrophils in the lung and the peripheral blood or the lung lesion score were only observed on Day 14. These findings suggest that the exacerbating effect of G-CSF on the lung injury coincided with the increase in the number of alkaline phosphatase-positive neutrophils infiltrating in the pulmonary lesion at the acute inflammatory phase and it lasted to the fibrogenic phase. The exacerbating effect of G-CSF on the severe BLM-induced lung injury seems to be related not only to the pulmonary accumulation of activated neutrophils but also to the severity of lung injury caused by the direct effects of BLM.

Alkaline Phosphatase↗
PubMed2003

Ultrastructural changes in the dorsal skin of Wistar-derived hypotrichotic WBN/ILA-Ht rats following UVA-irradiation.

Ultrastructual characteristics of the dorsal skin responses to a single irradiation of UVA (1100 kJ/m2) were examined in Wistar-derived hypotichotic WBN/ILA-Ht rats (HtRs). In the epidermis, mitochondrial swelling of some keratinocytes and dissociation of keratinocytes due to intercellular edema developed at 3 hours (h) after irradiation and continued to 48 h. At 6 h, in addition to these changes, necrosis of keratinocytes accompanied with infiltration of neutrophils was also observed in some portions, and epidermal hyperplasia with many keratinocytes showing nucleolar hypertrophy and some mitotic keratinocytes was observed at 48 h. In the dermis, mitochondrial swelling and/or partial cytoplasmic destruction in capillary endothelial cells and edema with inflammatory cell infiltration were observed at and after 3 h, and extravasation of erythrocytes was found in some capillaries at 48 h. Mitochondrial swelling was also frequently found in pericytes and fibroblasts. Inflammatory cells were mainly composed of neutrophils throughout the experimental period. Mild degranulation of mast cells which also showed mitochondrial swelling was observed at and after 3 h, and a close special relationship between mast cells and fibroblasts or neutrophils was sometimes observed. In conclusion, the most prominent change in the dorsal skin of HtRs exposed to UVA was degeneration of capillary endothelial cells, resulting in edema and inflammatory cell infiltration, and the most characteristic cytopathic effect of UVA was mitochondrial swelling, and it was common to keratinocytes, capillary endothelial cells, pericytes, mast cells, and fibroblasts.

Animals↗
PubMed2003

Effects of tacrolimus and dexamethasone on tubulointerstitial fibrosis in mercuric chloride treated Brown Norway rats.

We investigated the effects of daily injection of tacrolimus (FK), an immunosuppressor, or dexamethasone (Dx), an antiinflammatory agent, on renal tubulointerstitial fibrosis in mercuric chloride-treated Brown Norway rats. The tubular lesions observed after one time injection of mercuric chloride were reduced in FK-treatment group, but not in Dx-treatment group. Moreover, FK reduced infiltration of mononuclear cells, especially macrophages, and proliferation of myofibroblasts in renal intestitium and also inhibited renal interstitial fibrosis through the reduction of the expressions of fibrosis-related factors, i.e. plasminogen activator inhibitor-1 and transforming growth factor-beta1. On the other hand, Dx reduced lymphocyte infiltraton, but did not inhibit macrophage infiltration. In addition, Dx did not suppress myofibroblast profiferation, upregulation of fibrosis-related factors, and interstitial fibrosis. From these findings, it is suggested that FK may inhibit renal interstitial fibrosis through inhibition of macrophage infiltration, and that macrophages and myofibroblasts are very important fibrogenic factors in the development of mercuric chloride-induced renal tubulointerstitial fibrosis in BN rats.

Animals↗
PubMed2003

Antioxidants suppress nitrofurazone-induced proliferation of hepatocytes.

On administration to rats at a subtoxic dose, the antibiotic nitrofurazone (NF) has been shown to increase hepatocyte DNA synthesis and liver weight in a dose-dependent manner, with no histological or biochemical evidence of cell damage or necrosis. Free radicals are implicated in NF metabolism, as well as in the DNA synthesis or cell proliferation induced by a number of other chemicals. In the present study, NF was given alone or concomitantly with the antioxidants N-acetylcysteine or cyanidanol. Antioxidants prevent the effects of free radicals. Co-administration decreased hepatocyte proliferation to the same level as the control. This suppression of NF-induced hepatocyte proliferation by antioxidants therefore strongly suggests that free radical production is involved in this process.

Acetylcysteine↗
PubMed2003

Computerized scheme for determination of the likelihood measure of malignancy for pulmonary nodules on low-dose CT images.

An automated computerized scheme has been developed for determination of the likelihood measure of malignancy of pulmonary nodules on low-dose helical CT (LDCT) images. Our database consisted of 76 primary lung cancers (147 slices) and 413 benign nodules (576 slices). With this automated computerized scheme, the location of a nodule was first indicated by a radiologist. The outline of the nodule was segmented automatically by use of a dynamic programming technique. Various objective features on the nodules were determined by use of outline analysis and image analysis, and the likelihood measure of malignancy was determined by use of linear discriminant analysis (LDA). The effect of many different combinations of features and the performance of LDA in distinguishing benign nodules from malignant ones were evaluated by means of receiver operating characteristic (ROC) analysis. The Az value (area under the ROC curve) obtained by the computerized scheme in distinguishing benign nodules from malignant ones was 0.828 when a single slice was employed for each of the nodules. However, the Az value was improved to 0.846 when multiple slices were used for determination of the likelihood measure of malignancy. The Az values obtained by the computerized scheme on LDCT images were significantly greater than the Az value of 0.70, which was obtained from our previous observer studies by radiologists in distinguishing benign nodules from malignant ones on LDCT images. The automated computerized scheme for determination of the likelihood measure of malignancy would be useful in assisting radiologists to distinguish between benign and malignant pulmonary nodules on LDCT images.

Algorithms↗
PubMed2003

Automated lung nodule classification following automated nodule detection on CT: a serial approach.

We have evaluated the performance of an automated classifier applied to the task of differentiating malignant and benign lung nodules in low-dose helical computed tomography (CT) scans acquired as part of a lung cancer screening program. The nodules classified in this manner were initially identified by our automated lung nodule detection method, so that the output of automated lung nodule detection was used as input to automated lung nodule classification. This study begins to narrow the distinction between the "detection task" and the "classification task." Automated lung nodule detection is based on two- and three-dimensional analyses of the CT image data. Gray-level-thresholding techniques are used to identify initial lung nodule candidates, for which morphological and gray-level features are computed. A rule-based approach is applied to reduce the number of nodule candidates that correspond to non-nodules, and the features of remaining candidates are merged through linear discriminant analysis to obtain final detection results. Automated lung nodule classification merges the features of the lung nodule candidates identified by the detection algorithm that correspond to actual nodules through another linear discriminant classifier to distinguish between malignant and benign nodules. The automated classification method was applied to the computerized detection results obtained from a database of 393 low-dose thoracic CT scans containing 470 confirmed lung nodules (69 malignant and 401 benign nodules). Receiver operating characteristic (ROC) analysis was used to evaluate the ability of the classifier to differentiate between nodule candidates that correspond to malignant nodules and nodule candidates that correspond to benign lesions. The area under the ROC curve for this classification task attained a value of 0.79 during a leave-one-out evaluation.

Adult↗
PubMed2003

Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose computed tomography.

In this study, we investigated a pattern-recognition technique based on an artificial neural network (ANN), which is called a massive training artificial neural network (MTANN), for reduction of false positives in computerized detection of lung nodules in low-dose computed tomography (CT) images. The MTANN consists of a modified multilayer ANN, which is capable of operating on image data directly. The MTANN is trained by use of a large number of subregions extracted from input images together with the teacher images containing the distribution for the "likelihood of being a nodule." The output image is obtained by scanning an input image with the MTANN. The distinction between a nodule and a non-nodule is made by use of a score which is defined from the output image of the trained MTANN. In order to eliminate various types of non-nodules, we extended the capability of a single MTANN, and developed a multiple MTANN (Multi-MTANN). The Multi-MTANN consists of plural MTANNs that are arranged in parallel. Each MTANN is trained by using the same nodules, but with a different type of non-nodule. Each MTANN acts as an expert for a specific type of non-nodule, e.g., five different MTANNs were trained to distinguish nodules from various-sized vessels; four other MTANNs were applied to eliminate some other opacities. The outputs of the MTANNs were combined by using the logical AND operation such that each of the trained MTANNs eliminated none of the nodules, but removed the specific type of non-nodule with which the MTANN was trained, and thus removed various types of non-nodules. The Multi-MTANN consisting of nine MTANNs was trained with 10 typical nodules and 10 non-nodules representing each of nine different non-nodule types (90 training non-nodules overall) in a training set. The trained Multi-MTANN was applied to the reduction of false positives reported by our current computerized scheme for lung nodule detection based on a database of 63 low-dose CT scans (1765 sections), which contained 71 confirmed nodules including 66 biopsy-confirmed primary cancers, from a lung cancer screening program. The Multi-MTANN was applied to 58 true positives (nodules from 54 patients) and 1726 false positives (non-nodules) reported by our current scheme in a validation test; these were different from the training set. The results indicated that 83% (1424/1726) of non-nodules were removed with a reduction of one true positive (nodule), i.e., a classification sensitivity of 98.3% (57 of 58 nodules). By using the Multi-MTANN, the false-positive rate of our current scheme was improved from 0.98 to 0.18 false positives per section (from 27.4 to 4.8 per patient) at an overall sensitivity of 80.3% (57/71).

Algorithms↗
PubMed2003

Selective enhancement filters for nodules, vessels, and airway walls in two- and three-dimensional CT scans.

Computer-aided diagnostic (CAD) schemes have been developed to assist radiologists in the early detection of lung cancer in radiographs and computed tomography (CT) images. In order to improve sensitivity for nodule detection, many researchers have employed a filter as a preprocessing step for enhancement of nodules. However, these filters enhance not only nodules, but also other anatomic structures such as ribs, blood vessels, and airway walls. Therefore, nodules are often detected together with a large number of false positives caused by these normal anatomic structures. In this study, we developed three selective enhancement filters for dot, line, and plane which can simultaneously enhance objects of a specific shape (for example, dot-like nodules) and suppress objects of other shapes (for example, line-like vessels). Therefore, as preprocessing steps, these filters would be useful for improving the sensitivity of nodule detection and for reducing the number of false positives. We applied our enhancement filters to synthesized images to demonstrate that they can selectively enhance a specific shape and suppress other shapes. We also applied our enhancement filters to real two-dimensional (2D) and three-dimensional (3D) CT images to show their effectiveness in the enhancement of specific objects in real medical images. We believe that the three enhancement filters developed in this study would be useful in the computerized detection of cancer in 2D and 3D medical images.

Databases as Topic↗
PubMed2003

Quantitative computerized analysis of diffuse lung disease in high-resolution computed tomography.

An automated computerized scheme has been developed for the detection and characterization of diffuse lung diseases on high-resolution computed tomography (HRCT) images. Our database consisted of 315 HRCT images selected from 105 patients, which included normal and abnormal slices related to six different patterns, i.e., ground-glass opacities, reticular and linear opacities, nodular opacities, honeycombing, emphysematous change, and consolidation. The areas that included specific diffuse patterns in 315 HRCT images were marked by three radiologists independently on the CRT monitor in the same manner as they commonly describe in their radiologic reports. The areas with a specific pattern, which three radiologists marked independently and consistently as the same patterns, were used as "gold standard" for specific abnormal opacities in this study. The lungs were first segmented from the background in each slice by use of a morphological filter and a thresholding technique, and then divided into many contiguous regions of interest (ROIs) with a 32x32 matrix. Six physical measures which were determined in each ROI included the mean and the standard deviation of the CT value, air density components, nodular components, line components, and multilocular components. Artificial neural networks (ANNs) were employed for distinguishing between seven different patterns which included normals and six patterns associated with diffuse lung disease. The sensitivity of this computerized method for a detection of the six abnormal patterns in each ROI was 99.2% (122/123) for ground-glass opacities, 100% (15/15) for reticular and linear opacities, 88.0% (132/150) for nodular opacities, 100% (98/98) for honeycombing, 95.8% (369/385) for emphysematous change, and 100% (43/43) for consolidation. The specificity in detecting a normal ROI was 88.1% (940/1067). This computerized method may be useful in assisting radiologists in their assessment of diffuse lung disease in HRCT images.

Algorithms↗
PubMed2003

Investigation of new psychophysical measures for evaluation of similar images on thoracic computed tomography for distinction between benign and malignant nodules.

We have been developing a computerized scheme to assist radiologists in improving the diagnostic accuracy for lung cancers on low-dose computed tomography (LDCT) scans by use of similar images for malignant nodules and benign nodules. A database of 415 LDCT scans including 73 cases with 76 confirmed cancers and 342 cases with 413 confirmed benign nodules was first collected in an LDCT screening program for early detection of lung cancers in Nagano, Japan. An observer study by use of receiver operating characteristics analysis was first conducted with five radiologists to demonstrate that presenting similar images for malignant nodules and benign nodules can significantly improve radiologists' performance in the diagnosis of unknown nodules. Another observer study was then conducted for obtaining reliable data on subjective similarity ratings by 10 radiologists. Based on the subjective similarity ratings, three important features were selected from a number of nodule features, and four different techniques for the determination of similarity measures, namely, a feature-based technique, a pixel-value-difference based technique, a cross-correlation-based technique, and a neural-network-based technique, were investigated and evaluated in terms of the correlation coefficient with the subjective similarity ratings. The experimental results in this study indicated that the neural-network-based technique can provide a reliable psychophysical similarity measure which is comparable to the subjective similarity ratings for a single radiologist when evaluated by use of correlation with the average similarity ratings for the other nine radiologists.

Humans↗
PubMed2003

Computer-aided diagnosis to distinguish benign from malignant solitary pulmonary nodules on radiographs: ROC analysis of radiologists' performance--initial experience.

PURPOSE: To evaluate radiologists' performance for determining a distinction between benign and malignant pulmonary nodules on chest radiographs without and with use of a computer-aided diagnosis scheme. MATERIALS AND METHODS: Fifty-three chest radiographs that depicted 31 primary lung cancers and 22 benign nodules were used. The likelihood measure of malignancy for each nodule was determined by using an automated computerized scheme. Sixteen radiologists (nine attending radiologists and seven radiology residents) participated in an observer study in which cases were interpreted first without and then with use of the scheme. The radiologists' performance was evaluated with receiver operating characteristic analysis. RESULTS: The mean area under the best-fit binormal receiver operating characteristic curve plotted in the unit square (Az) values of radiologists who interpreted images without and with the scheme were 0.743 and 0.817, respectively. The performance of radiologists was improved significantly when the scheme was used (P =.002). However, the performance (Az = 0.889) of the computer alone exceeded these results by a substantial margin. The average change in radiologists' confidence level for interpretation without and with the scheme was highly correlated (r = 0.845) with the likelihood measure of malignancy, which was presented as computer output. CONCLUSION: This scheme for computer-aided diagnosis has the potential to improve the accuracy of radiologists' performance in the classification of benign and malignant solitary pulmonary nodules.

Diagnosis, Computer-Assisted↗
PubMed2003

Ganglioglioma in the thalamus of a puppy.

A solitary brain mass of a 4-month-old miniature dachshund showing seizure-like neurological signs was examined histopathologically. At necropsy a white tumor mass, replacing the thalamus, approximately 1.5 cm in diameter, was found. There was cystic space filled with yellowish pale fluid in the central area of the tumor mass. Histopathological examination revealed that the mass consisted of irregularly arranged well-differentiated neuronal and glial cells, and multifocal mineral deposits. The neuronal cells had a large clear nucleus and various amount of Nissl substances in the cytoplasm. Some neural cells were bi-nucleated. Neither mitotic figures nor proliferating cell nuclear antigen (PCNA)-positive nuclei was found in the neuronal cells. Immunostaining for glial fibrillary acidic protein (GFAP) revealed diffuse proliferation of GFAP-positive glial cells and their processes, while these glial cells did not show apparent cellular atypism, mitotic activity, or PCNA-immunoreactivity. Accordingly, the present tumor was diagnosed as ganglioglioma, and hamartomatous histogenesis might be possible.

Animals↗
PubMed2003

D-galactosamine induced hepatocyte apoptosis is inhibited in vivo and in cell culture by a calcium calmodulin antagonist, chlorpromazine, and a calcium channel blocker, verapamil.

Studies were conducted in C57BL/6N Crj male mice and in cultured hepatocytes to clarify the relationship between galactosamine (GaIN) induced apoptosis and [Ca2+]i kinetics. Chlorpromazine (CPZ), a Ca(2+)-calmodulin antagonist, and verapamil (VR), a Ca(2+)-channel blocker each inhibited GaIN-induced DNA fragmentation and the appearance of apoptotic bodies. The kinetics of calcium uptake were evaluated using a calcium analyzer with the acetoxymethyl ester of fura-PE3 (fura-PE3/AM, 2.5 microM) as the calcium reporter. An increase in [Ca2+]i was detected in the cultured hepatocytes within 3 hours after treatment with 20 mM GaIN; this increase was inhibited by pretreatment with either 20 microM CPZ or 30 microM VR. Ca2+ imaging by confocal laser scanning microscopy showed that increase in [Ca2+]i after treatment with GaIN was initially localized around nuclei, while [Ca2+]i signals were later diffuse and observed throughout the cytoplasm. The activities of lactate dehydrogenase (LDH) and serum glutamate-pyruvate transaminase (sGPT), used as indicators of plasma membrane damage and leakage, however, were not reduced by pretreatment with CPZ or VR. From these findings, we infer that the DNA fragmentation in GaIN-induced hepatocyte apoptosis is associated with an elevation in the perinuclear concentration of Ca2+, but GaIN-induced necrotic cell death is triggered through pathway(s) that are insensitive to blockage of Ca2+ influx and therefore appear to occur independently of elevation in [Ca2+]i. These results help to clarify the role of calcium flux in hepatocyte apoptosis and necrosis induced by exposure to hepatotoxins in vivo and in vitro.

Animals↗
PubMed2003

[Development of an automated patient-recognition method for digital chest radiographs using edge-enhanced images].

It is important that all images in a picture archiving and communication system (PACS) environment should be stored in the correct location, e.g., in the proper patient's folder. However, if patient information, such as identification number or patient name, has been entered incorrectly, the image may be stored in the wrong place. We are developing an automated patient recognition method for chest radiographs based on a template-matching technique to prevent such filing errors. To further improve the performance of our method, we investigated the usefulness of a new automated patient-recognition method based on a template-matching technique by using edge-enhanced and smoothed images. We found that the relationship between the correlation values obtained with and without the edge-enhancement technique tended to provide different criteria for identifying correct or incorrect patients. When we combined the two methods to distinguish the images by a rule-based method, 67.1% of wrongly identified patients in our database could be identified as wrongly identified, without any false warnings for correctly identified patients. We consider that this automated method for patient recognition based on edge-enhanced images would be useful in preventing "wrong" images from being stored in a PACS environment.

Databases, Factual↗
PubMed2002

Early death of mice cloned from somatic cells.

Here we report that the lifespan of mice cloned from somatic cells is significantly shorter than that of genotype- and sex-matched controls, most likely due to severe pneumonia and hepatic failure. This finding demonstrates the possibility of long-term deleterious effects of somatic-cell cloning, even after normal birth.

Animals↗