Chronic kidney disease (CKD) occurs in more than 15% of the dogs over 10 years of age and causes irreversible renal function deterioration. Therefore, it is important to diagnose CKD early and treat the disease properly. The purpose of this study aimed to to evaluate the clinical utility of urine albumin/creatinine ratio (ACR) using POC (point-of-care) device as an early detection urinary biomarker in CKD dogs and to confirm the correlation between ACR and other known CKD biomarkers. Urine and serum samples were obtained from 50 healthy dogs and 50 dogs with CKD. Serum blood urea nitrogen (BUN), creatinine, and symmetric dimethylarginine (SDMA) concentrations, and urine protein creatinine ratio (UPC) were measured. Urine specific gravity (USG) was evaluated using refractometer, and ACR was measured using an i-SENS A1Care analyzer. The ACR values of dogs with CKD were significantly different from those of healthy dogs (p < 0.001), as with other renal biomarkers. ACR showed significant differences between healthy dogs and dogs with CKD at every IRIS stage (p < 0.005), whereas no significant differences were observed between dogs with CKD IRIS stage I and healthy dogs with UPC. There are significant positive correlation between ACR and BUN (r = 0.611, p < 0.001), creatinine (r = 0.788, p < 0.001), SDMA (r = 0.747, p < 0.001), and UPC (r = 0.784, p < 0.001), and significant negative correlation between ACR and USG (r = -0.700, p < 0.001). In receiver operator characteristic curve analysis, the area under the curve (AUC) was 0.982 (95% CI 0.963-1.000, p < 0.001), with an optimal cut-off value of 64.20 mg/g (94% sensitivity and 94% specificity). Thus, ACR is a useful urinary biomarker for the early diagnosis of proteinuria in CKD and combined use of ACR and other renal biomarkers may be helpful for early diagnosis and prevention of CKD in dogs.
The Journal of the Convergence on Culture Technology
/
v.10
no.1
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pp.403-409
/
2024
In this paper, the guidelines for the design of an Artificial Intelligence(AI) based Integrated Process Safety Management(PSM) system to enhance workplace safety using data from process safety reports submitted by hazardous and risky facility operators in accordance with the Occupational Safety and Health Act is proposed. The system composed of the proposed guidelines is to be implemented separately by individual facility operators and specialized process safety management agencies for single or multiple workplaces. It is structured with key components and stages, including data collection and preprocessing, expansion and segmentation, labeling, and the construction of training datasets. It enables the collection of process operation data and change approval data from various processes, allowing potential fault prediction and maintenance planning through the analysis of all data generated in workplace operations, thereby supporting decision-making during process operation. Moreover, it offers utility and effectiveness in time and cost savings, detection and prediction of various risk factors, including human errors, and continuous model improvement through the use of accurate and reliable training data and specialized datasets. Through this approach, it becomes possible to enhance workplace safety and prevent accidents.
Kim, Keunyong;Kim, Euihyun;Choi, Jun Myoung;Shin, Jisun;Kim, Wonkook;Lee, Kwang-Jae;Son, Young Baek;Ryu, Joo-Hyung
Korean Journal of Remote Sensing
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v.36
no.2_2
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pp.249-261
/
2020
Coastal monitoring using multiple platforms/sensors is a very important tools for accurately understanding the changes in offshore marine environment and disaster with high temporal and spatial resolutions. However, integrated observation studies using multiple platforms and sensors are insufficient, and none of them have been evaluated for efficiency and limitation of convergence. In this study, we aimed to suggest an integrated observation method with multi-remote sensing platform and sensors, and to diagnose the utility and limitation. Integrated in situ surveys were conducted using Rhodamine WT fluorescent dye to simulate various marine disasters. In September 2019, the distribution and movement of RWT dye patches were detected using satellite (Kompsat-2/3/3A, Landsat-8 OLI, Sentinel-3 OLCI and GOCI), unmanned aircraft (Mavic 2 pro and Inspire 2), and manned aircraft platforms after injecting fluorescent dye into the waters of the South Sea-Yeosu Sea. The initial patch size of the RWT dye was 2,600 ㎡ and spread to 62,000 ㎡ about 138 minutes later. The RWT patches gradually moved southwestward from the point where they were first released,similar to the pattern of tidal current flowing southwest as the tides gradually decreased. Unmanned Aerial Vehicles (UAVs) image showed highest resolution in terms of spatial and time resolution, but the coverage area was the narrowest. In the case of satellite images, the coverage area was wide, but there were some limitations compared to other platforms in terms of operability due to the long cycle of revisiting. For Sentinel-3 OLCI and GOCI, the spectral resolution and signal-to-noise ratio (SNR) were the highest, but small fluorescent dye detection was limited in terms of spatial resolution. In the case of hyperspectral sensor mounted on manned aircraft, the spectral resolution was the highest, but this was also somewhat limited in terms of operability. From this simulation approach, multi-platform integrated observation was able to confirm that time,space and spectral resolution could be significantly improved. In the future, if this study results are linked to coastal numerical models, it will be possible to predict the transport and diffusion of contaminants, and it is expected that it can contribute to improving model accuracy by using them as input and verification data of the numerical models.
Although early diagnosis of urinary tract infection is important, the radiologic evaluation is still controversial because of the low sensitivity and the lack of cost-effectiveness. This study was carried out to evaluate the clinical utility of high resolution triple head $^{99m}Tc-DMSA$ SPECT imaging in urinary tract infection. We prospectively performed $^{99m}Tc-DMSA$ planar and SPECT imaging, ultrasound of kidney (US), intravenous pyelography (IVP) and voiding cystourethrography (VCU) in all 60 adult patients with UTI [26 with first episode of acute pyelonephritis (APN), 22 with recurrent APN, and 12 persistent asymptomatic pyuria] and 25 normal persons. To assess reversibility of the renal cortical defect (RCD), $^{99m}Tc-DMSA$ SPECT was repeated 1 to 8 months later in those patients with abnormal initial findings. Overall detection rate of $^{99m}Tc-DMSA$ SPECT imaging was 83% (50/60), but planar, US, IVP and VCU showed abnormal findings in 68%, 28%, 32% and 13%, respectively. 25 out of 27 patients with normal or single RCD were all normal in other radioligic studies. Only two patients showed vesicoureteral reflux (VUR) on VCU (grade I) and mild hydronephrosis on IVP. But, high proportion of those with multiple RCD showed abnormal findings on US (17/33), IVP (18/33), and VCU (7/33): 67% in any of these 3 studies. Especially, 3 out 7 patients with VUR showed multiple RCD on $^{99m}Tc-DMSA$ SPECT without any abnormality on IVP or US. 25 normal persons showed normal findings in all studies except one false positive finding on $^{99m}Tc-DMSA$ SPECT imaging. Follow-up $^{99m}Tc-DMSA$ SPECT was done in 28 patients (13 with single RCD, 15 with multiple RCD). All 13 patients with single RCD showed improvement. Those with multiple RCD presented improvement in 4, no change in 10, and aggravation in 1 on follow-up studies. With these results, we conclude: 1) $^{99m}Tc-DMSA$ SPECT imaging is superior to planar imaging, US, IVP or VCU in detection of renal lesion in urinary tract infection. $^{99m}Tc-DMSA$ SPECT is useful as a initial diagnostic tool in adult patients with urinary tract infection. 2) The multiple RCD on $^{99m}Tc-DMSA$ SPECT represent the high probability of irreversible tissue change and need of extensive urological work-up.
The detectable levels and population fluctuations of phytoplasmas infecting dwarf mulberry trees were investigated using nested-PCR and competitive-PCR methods. Samples of five different types were studied : A. petiole of a leaf that displays dwarf symptoms, B. petiole from apparently healthy leaf residing on a branch also supports a leaf with dwarf symptoms, C. the branch portion that supports a leaf with dwarf symptoms, D. the leaf petiole from healthy appearing leaves on branch with no dwarf symptoms, and branch portion of branch with no dwarf symptoms, E. the rootlets of trees with dwarf symptoms. These 5-parts were collected from each tree during June - April, once in every two months. The phytoplasma was detected from all parts of collected mulberry samples during all seasons using nested-PCR with AS-1/AS-2 primer pairs. The phytoplasma was detected until $10^4$ dilution using direct-PCR method, but it was detected until $10^{13}$ dilution by the nested-PCR method. The density of pytoplasma was found to be $7.94{\times}10^{18}-10^{12}copies/{\mu}L$ in mulberry trees. The density of phytoplasma was observed throughout the year in all samples of mulberry trees. The highest rates of phytoplasma was found in the samples B and C during the early growing season followed by the sample A and D during the dormant season. Samples C and E displayed the highest phytoplasma density followed sample D. The density of phytoplasma appeared stable during all the seasons for samples C and A. The result of the present study demonstrates the utility of nested-PCR and competitive-PCR for detection and determination of population fluctuations of phytoplasmas in plant tissues.
Kim, Kyung Min;Park, Ji Young;Park, Kyoung Un;Sohn, Young Joo;Choi, Youn Young;Han, Mi Seon;Choi, Eun Hwa
Pediatric Infection and Vaccine
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v.28
no.2
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pp.92-100
/
2021
Purpose: Rapid detection of etiologic organisms is crucial for initiating appropriate therapy in patients with central nervous system (CNS) infection. This study aimed to evaluate the diagnostic value of the BioFire® Meningitis/Encephalitis (ME) panel in detecting etiologic organisms in cerebrospinal fluid (CSF) samples from febrile infants. Methods: CSF samples from infants aged <90 days who were evaluated for fever were collected between January 2016 and July 2019 at the Seoul National University Children's Hospital. We performed BioFire® ME panel testing of CSF samples that had been used for CSF analysis and conventional tests (bacterial culture, Xpert® enterovirus assay, and herpes simplex virus-1 and -2 polymerase chain reaction) and stored at -70℃ until further use. Results: In total, 72 (24 pathogen-identified and 48 pathogen-unidentified) CSF samples were included. Using BioFire® ME panel testing, 41 (85.4%) of the 48 pathogen-unidentified CSF samples yielded negative results and 22 (91.7%) of the 24 pathogen-identified CSF samples yielded the same results (enterovirus in 19, Streptococcus agalactiae in 2, and Streptococcus pneumoniae in 1) as those obtained using the conventional tests, thereby resulting in an overall agreement of 87.5% (63/72). Six of the 7 pathogen-unidentified samples were positive for human parechovirus (HPeV) via BioFire® ME panel testing. Conclusions: Compared with the currently available etiologic tests for CNS infection, BioFire® ME panel testing demonstrated a high agreement score for pathogen-identified samples and enabled HPeV detection in young infants. The clinical utility and cost-effectiveness of BioFire® ME panel testing in children must be evaluated for its wider application.
This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.
Ouda, SM;Khairy, AM;Sorour, Ashraf E;Mikhail, Mikhail Nasr
Asian Pacific Journal of Cancer Prevention
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v.16
no.17
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pp.7825-7829
/
2015
Background: Egypt has the highest prevalence of HCV infection in the world (~14.7%). Around 10-15% of HCV-infected persons will advance to cirrhosis within the first 20 years. The incidence of HCC is expected to grow in the next two decades, largely due to HCV related cirrhosis, and detection of HCC at an early stage is critical for a favorable clinical outcome. No simple reliable non-invasive marker has been available till now. B2M, a non-glycosylated polypeptide composed of 99 amino acids, is one of the components of HLA class I molecules on the surfaces of all nucleated cells. It has been reported that the level of serum B2M is elevated in patients with chronic hepatitis C and HCV-related HCC when compared to HCV-negative patients or healthy donors. Determining the clinical utility of serum B2M as a marker for disease progression in Egyptian patients with HCV related chronic hepatitis, cirrhosis and hepatocellular carcinoma was the aim of the present study. Materials and Methods: In this analytical cross sectional study 92 participants were included in 4 equal groups: Group (1) non cirrhotic chronic HCV; Group (2) HCV related liver cirrhosis; Group (3) HCC on top of HCV,; and Group (4) healthy controls. History taking, clinical examination, routine labs and abdominal ultrasound were conducted for all patients, PCR and Metavir scores for group (1) patients, and triphasic CT abdomen and AFP for Group (3) patients. B2M levels were measured in serum with a fully-automated IMX system. Results: The mean serum B2M level of Group (1) was $4.25{\pm}1.48{\mu}g/ml$., Group (2) was $7.48{\pm}3.04$, Group (3) was $6.62{\pm}2.49$ and Group (4) was $1.62{\pm}0.63$. Serum B2M levels were significantly higher in diseased than control group (p<0.01) being significantly higher in cirrhosis ($7.48{\pm}3.04$) and HCC groups ($6.62{\pm}2.49$) than the HCV group ($4.25{\pm}1.48$) (p<0.01). There was a significant correlation between B2M Level and ALK, total and direct bilirubin and INR (p<0.05), and a significant inverse correlation between B2M level and albumin, total proteins, HB andWBCS values (p<0.05). There was no significant correlation between B2M level and viral load or Metavir score, largest tumour size or AFP (p>0.05). The best B2M cut-off for HCV diagnosis was 2.6 with a sensitivity of 100%, a specificity of 92%, a positive predictive value (PPV) of 97% and a negative predictive value (NPV) of 100%. The best B2M cut-off for HCC diagnosis was 4.55 which yielded sensitivity, specificity, positive predictive value, negative predictive values of 74%, 62%, 39.5, 87.8% respectively (p-value <0.01) while best cut-off for cirrhosis was 4.9, with sensitivity 74 % and specificity 74%.The sensitivity for HCC diagnosis increased upon B2M and AFP combined estimation to 91%, specificity to 79%, NPV to 95% and accuracy to 83%. Conclusions: Serum B2M level is elevated in HCV related chronic liver diseases and may be used as a marker for HCV disease progression towards cirrhosis and carcinoma.
Ha, Woo-Seok;Kim, Soo-Mee;Park, Min-Jae;Lee, Dong-Soo;Lee, Jae-Sung
Nuclear Medicine and Molecular Imaging
/
v.43
no.5
/
pp.459-467
/
2009
Purpose: The maximum likelihood-expectation maximization (ML-EM) is the statistical reconstruction algorithm derived from probabilistic model of the emission and detection processes. Although the ML-EM has many advantages in accuracy and utility, the use of the ML-EM is limited due to the computational burden of iterating processing on a CPU (central processing unit). In this study, we developed a parallel computing technique on GPU (graphic processing unit) for ML-EM algorithm. Materials and Methods: Using Geforce 9800 GTX+ graphic card and CUDA (compute unified device architecture) the projection and backprojection in ML-EM algorithm were parallelized by NVIDIA's technology. The time delay on computations for projection, errors between measured and estimated data and backprojection in an iteration were measured. Total time included the latency in data transmission between RAM and GPU memory. Results: The total computation time of the CPU- and GPU-based ML-EM with 32 iterations were 3.83 and 0.26 see, respectively. In this case, the computing speed was improved about 15 times on GPU. When the number of iterations increased into 1024, the CPU- and GPU-based computing took totally 18 min and 8 see, respectively. The improvement was about 135 times and was caused by delay on CPU-based computing after certain iterations. On the other hand, the GPU-based computation provided very small variation on time delay per iteration due to use of shared memory. Conclusion: The GPU-based parallel computation for ML-EM improved significantly the computing speed and stability. The developed GPU-based ML-EM algorithm could be easily modified for some other imaging geometries.
Background : To Investigate the association between bronchial anthracofibrosis (AF) and tuberculosis (TB), and the clinical utility of a polymerase chain reaction (PCR) on bronchial specimens for rapid diagno-sis of active pulmonary TB in patients with bronchial AF. Method : Thirty patients (25 women and 5 men ranging in age from 53 to 88), who were diagnosed with bronchial AF by a bronchoscopic exami-nation, were enrolled in this study. PCR targeting the IS6110 segment of Mycobacterium tuberculosis was performed on the bronchial wash fluid and anthracofibrotic bronchial tissue. The PCR results were compared with the bacteriological, histological, and clinical findings. Results : Eighteen of the 30 patients (60%) were associated with TB, nine of whom were confirmed as having active TB. The remaining 9 had a past history of TB. The sputum or bronchial aspirate AFB smear, culture, and histological findings were positive in 4 (13%), 9 (30%), and 5 (17%) patients, respectively. PCR of the AF tissue and bronchial wash fluid was positive in 5 (17%) and 11 (37%) of the 30 patients, respectively. PCR was more sensitive than the AFB smears for diagnosing pulmonary TB (22 % us 89 %, respectively, p<0.05). All 5 patients with positive AF tissue PCR results also had both histological findings and positive bronchial wash fluid PCR results. Of the 3 patients with positive PCR but negative bacteriological or histological results, 2 of these patients appeared to have active tuberculosis on a clinical basis. Conclusion: Although TB-PCR did not reveal an increased association between bronchial AF and TB compared with traditional methods, PCR on the bronchial wash fluid appears to be useful for the rapid diagnosis of pulmonary TB in patients with bronchial AF. TB-PCR on AF bronchial tissue itself did not yield additional benefits for diagnosing TB, which suggests that an AF lesion itself may not be an active or original site of the infection, but a secondary change of TB.
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