• Restorative Dentistry and Endodontics
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• v.18 no.1
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• pp.122-132
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• 1993

The aim of this study was to investigate the level of radiopacity of glass ionomer cements and to determine the optimum level of radiopacity that is the most compatible with the radiographic diagnosis of secondary caries. The experiments were performed in two parts. In the first part, the radiopacities of 9 glass ionomer cements (FI, FII, FI-LC, FII-LC, SI, SII, Vit, B-VLC, AC) and base materials(Ultra-Blend, Zinc phoaphate cements, Cavitec, Dycal) were measured by densitometer. Then all experimental materials were divided into 5 groups based on the level of radiopacity of enamel and dentin. In the second part, class III cavities with or without secondary caries were prepared in extracted anterior teeth. The representative materials of each group with different radiopacities were inserted into each cavity. The radiographs were interpreted by 15 dentists and seconsary caries were diagnosed according to a five-point confidence rating. Sensitivity and ROC analysis were used to compare observer performance. The following results were obtained : 1. The radipacity of glass ionomer cements varied between 1.111mm Al and 6.011mm Al equivalent. 2. Among experimental materials, three materials in group I had lower radiopacity than that of dentin. The radiopacity of two materials in group II slightly exeeded that of dentin. Three materials in group III had slightly lower radiopacity than that on enamel. The radiopacity of one material in group W was slightly higher than that of enamel. Four materals in group V had the radiopacity that exeeded over 2.0mm AI equivalent to that of enamel. 3. The group IV was the highest for sensitivity and the group V was the highest for ROC area. However, no significant differences were obtained among group II, III, IV and V (P<0.05) but only group I was significantly lower(P<0.01). 4. In comparison with the observer performance for the radiographic diagnosis of secondary caries, the group II, III, IV, and V were superior to the group I (P<0.01). And so the optimum level of radiopacity to detect the secondary caries was the radiopacity that is higher than that of dentin.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.77-90
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• 2023

Today, crops face many characteristics/diseases. Insect damage is one of the main characteristics/diseases. Insecticides are not always effective because they can be toxic to some birds. It will also disrupt the natural food chain for animals. A common practice of plant scientists is to visually assess plant damage (leaves, stems) due to disease based on the percentage of disease. Plants suffer from various diseases at any stage of their development. For farmers and agricultural professionals, disease management is a critical issue that requires immediate attention. It requires urgent diagnosis and preventive measures to maintain quality and minimize losses. Many researchers have provided plant disease detection techniques to support rapid disease diagnosis. In this review paper, we mainly focus on artificial intelligence (AI) technology, image processing technology (IP), deep learning technology (DL), vector machine (SVM) technology, the network Convergent neuronal (CNN) content Detailed description of the identification of different types of diseases in tomato and potato plants based on image retrieval technology (CBIR). It also includes the various types of diseases that typically exist in tomato and potato. Content-based Image Retrieval (CBIR) technologies should be used as a supplementary tool to enhance search accuracy by encouraging you to access collections of extra knowledge so that it can be useful. CBIR systems mainly use colour, form, and texture as core features, such that they work on the first level of the lowest level. This is the most sophisticated methods used to diagnose diseases of tomato plants.

• Journal of Internet Computing and Services
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• v.25 no.3
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• pp.19-25
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• 2024

The worldwide aging population trend is causing an increase in the incidence of major retinal diseases that can lead to blindness, including glaucoma, cataract, and macular degeneration. In the field of ophthalmology, there is a focused interest in diagnosing diseases that are difficult to prevent in order to reduce the rate of blindness. This study proposes a deep learning approach to accurately diagnose ocular diseases in fundus photographs using less data than traditional methods. For this, Convolutional Neural Network (CNN) models capable of effective learning with limited data were selected to classify Conventional Fundus Images (CFI) from various ocular disease patients. The chosen CNN models demonstrated exceptional performance, achieving high Accuracy, Precision, Recall, and F1-score values. This approach reduces manual analysis by ophthalmologists, shortens consultation times, and provides consistent diagnostic results, making it an efficient and accurate diagnostic tool in the medical field.

• Journal of Microbiology
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• v.44 no.1
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• pp.42-49
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• 2006

In this study, we describe our newly-developed sensitive two-stage PCR procedure for the detection of 13 common mycoplasmal contaminants (M. arthritidis, M. bovis, M. fermentans, M. genitalium, M. hominis, M. hyorhinis, M. neurolyticum, M. orale, M. pirum, M. pneumoniae, M. pulmonis, M. salivarium, U. urealyticum). For primary amplification, the DNA regions encompassing the 16S and 23S rRNA genes of 13 species were targeted using general mycoplasma primers. The primary PCR products were then subjected to secondary nested PCR, using two different primer pair sets, designed via the multiple alignment of nucleotide sequences obtained from the 13 mycoplasmal species. The nested PCR, which generated DNA fragments of 165-353 bp, was found to be able to detect 1-2 copies of the target DNA, and evidenced no cross-reactivity with the generated DNA of related microorganisms or of human cell lines, thereby confirming the sensitivity and specificity of the primers used. The identification of contaminated species was' achieved via the performance of restriction fragment length polymorphism (RFLP) coupled with Sau3AI digestion. The results obtained in this study furnish evidence suggesting that the employed assay system constitutes an effective tool for the disagnosis of mycoplasmal contamination in cell culture systems.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.6
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• pp.2209-2213
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• 2015

DNA methylation of tumor suppressor gene promoters is the most frequent phenomenon leading to inactivation of function, consequently driving malignant cell transformation. Cyclin D2 is implicated in tumor suppression. In our study, we carried out the MSP assay to evaluation the methylation status at CpG islands in the cyclin D2 promoter in breast cancer cases from the Vietnamese population. The results showed that the frequency of methylation reached 62.1% (59 of 95 breast cancer tumors), but was low in non-cancer specimens at 10% (2 of 20 non-cancer specimens). Additionally, with an RR (relative risk) and OR (odd ratios) of 6.21 and 14.8, DNA hypermethylation of cyclin D2 increased the possibility of malignant transformation. Our results confirmed the cyclin D2 hypermethylation could be used as the potential biomarker which could be applied in prognosis and early diagnosis of Vietnamese breast cancer patients.

• Clinical and Experimental Pediatrics
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• v.46 no.4
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• pp.389-392
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• 2003

Netherton's syndrome is an unusual disorder which consists of triad of ichtyosiform dermatosis, multiple defects of hair shaft and an atopic diathesis. The finding of bamboo hair is pathognomic in Netherton's syndrome and the ichthyosiform dermatosis may consist of either ichtyosis linearis circumflexa or congenital ichthyosiform erythroderma. Often, variability in the clinical features leads to a delay in diagnosis in many cases. We report a case of Netherton's syndrome diagnosed in the neonatal period. The patient presented with severe ichthyosis and confirmed microscopically distinctive bamboo hair.

• Journal of Korean Academy of Nursing Administration
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• v.3 no.1
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• pp.107-118
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• 1997

This study was designed to obtain basic data for development of evaluation tool which would be needed to measure the outcome of general quality nursing care of individual patient. The purpose of this study was to analyze and classify the outcome indicators of quality nursing care. The 29 articles of quality nursing care and outcome measures were selected coveniently, and analyzed to classify the outcome indicators of quality nursing care using open coding method. The results of this study were as follows: 1. Quality nursing care was defined as level of excellence of nursing care to achieve good patient outcome. 2. The 6 domains of which were health status, satisfaction, self care, patient progress and prognosis, and compliance were identified in outcome indicators of quality nursing care 3. Seven indicators of health status domain which were perceived health status, quality of life, well-being, daily activities, physical-physiological status, psychoemotional status, and social role functioning were identified. 4. Two indicators of satifaction domain which were patient satisfaction and family satisfaction were identified. 5. Three indicators of self care domain which were skill, knowledge, and home management were identified. 6. Seven indicators of patient progress and prognosis domain which were change of clinical status, resolution of nursing diagnosis and problem, days of stay, dicahrge state, recovery state, survival were identified. 7. compliance with therapeutic direction compliance was identified as an indicator of compliance domain. 8. It was sugested that studies for development of evaluation tools for outcomes of quality nursing the results of this study could be executed

• Structural Engineering and Mechanics
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• v.31 no.3
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• pp.333-347
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• 2009

Due to structural complicacy, structural health monitoring for civil engineering needs more accurate and effectual methods of damage identification. This study aims to import multi-source information fusion (MSIF) into structural damage diagnosis to improve the validity of damage detection. Firstly, the essential theory and applied mathematic methods of MSIF are introduced. And then, the structural damage identification method based on multi-mode information fusion is put forward. Later, on the basis of a numerical simulation of a concrete continuous box beam bridge, it is obviously indicated that the improved modal strain energy method based on multi-mode information fusion has nicer sensitivity to structural initial damage and favorable robusticity to noise. Compared with the classical modal strain energy method, this damage identification method needs much less modal information to detect structural initial damage. When the noise intensity is less than or equal to 10%, this method can identify structural initial damage well and truly. In a word, this structural damage identification method based on multi-mode information fusion has better effects of structural damage identification and good practicability to actual structures.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.8
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• pp.3997-4000
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• 2012

MicroRNAs (miRNAs) play roles in the clinic, both as diagnostic and therapeutic tools. The identification of relevant microRNAs is critically required for ovarian cancer because of the prevalence of late diagnosis and poor treatment options currently. To identify miRNAs involved in the development or progression of ovarian cancer, we analyzed gene expression profiles downloaded from Gene Expression Omnibus. Comparison of expression patterns between carcinomas and the corresponding normal ovarian tissues enabled us to identify 508 genes that were commonly up-regulated and 1331 genes that were down-regulated in the cancer specimens. Function annotation of these genes showed that most of the up-regulated genes were related to cell cycling, and most of the down-regulated genes were associated with the immune response. When these differentially expressed genes were mapped to MiRTarBase, we obtained a total of 18 key miRNAs which may play important regulatory roles in ovarian cancer. Investigation of these genes and microRNAs should help to disclose the molecular mechanisms of ovarian carcinogenesis and facilitate development of new approaches to therapeutic intervention.

• Advances in pediatric surgery
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• v.6 no.2
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• pp.124-127
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• 2000

Femoral hernia is very rare in children and is easily misdiagnosed. During a period of three years, three children with femoral hernia were treated by one pediatric surgeon at Severance Hospital. Only one case was diagnosed correctly before surgery, and the others were thought to be either an indirect inguinal hernia or groin mass. Curative hernioplasty (McVay hernioplasty) could be done in only one case at the time of first operation. Diagnosis of femoral hernia in children is a challenge because of rarity and similarity of clinical presentation to indirect inguinal hernia. Co-incidental findings of indirect inguinal hernia sac or patent processus vaginalis during surgery can perpetuate the misdiagnosis. In case of absence of expected indirect inguinal hernia or apparent recurrence of indirect inguinal hernia, one should consider the possibility of femoral hernia.