• Health Policy and Management
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• v.17 no.2
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• pp.18-32
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• 2007

The purpose of this study was a quantitative analysis for the influence of physician's assistants on national health insurance revenue and number of patients in clinic. The data was derived from the Korean national health insurance. That was complete enumeration. Dependent variables were measured by national health insurance revenue and number of patients. Independent variables were reported physician's assistants that the number of nurse, nurse-aid, technologist of clinical laboratory, physical therapist and radiologist in clinic. Confounding variables were classified by demand(region, number of inhabitants, number of clinics, number of bed per a hundred thousand persons) and supply(sex and age of representative, number of bed, subjective of medical treatment). On the multiple regression analyses, the physician's assistants that nurse, nurse-aid, technologist of clinical laboratory and physical therapist were statistically significant for outputs. But radiologist was statistically significant only for number of patient.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.5
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• pp.1911-1915
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• 2012

Aim: New technologies for the early detection of pancreatic cancer (PC) are urgently needed. The aim of the present study was to screen for the potential protein biomarkers in serum using proteomic fingerprint technology. Methods: Magnetic beads combined with surface-enhanced laser desorption/ionization (SELDI) TOF MS were used to profile and compare the protein spectra of serum samples from 85 patients with pancreatic cancer, 50 patients with acute-on-chronic pancreatitis and 98 healthy blood donors. Proteomic patterns associated with pancreatic cancer were identified with Biomarker Patterns Software. Results: A total of 37 differential m/z peaks were identified that were related to PC (P < 0.01). A tree model of biomarkers was constructed with the software based on the three biomarkers (7762 Da, 8560 Da, 11654 Da), this showing excellent separation between pancreatic cancer and non-cancer., with a sensitivity of 93.3% and a specificity of 95.6%. Blind test data showed a sensitivity of 88% and a specificity of 91.4%. Conclusions: The results suggested that serum biomarkers for pancreatic cancer can be detected using SELDI-TOF-MS combined with magnetic beads. Application of combined biomarkers may provide a powerful and reliable diagnostic method for pancreatic cancer with a high sensitivity and specificity.

• Biomedical Science Letters
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• v.24 no.3
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• pp.270-274
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• 2018

Chlorine dioxide ($ClO_2$) gas is a neutral chlorine compound. $ClO_2$ gas was proven to effectively decontaminate different environments, such as hospital rooms, ambulances, biosafety level 3 laboratories, and cafeterias. In this study, to evaluate the effects of $ClO_2$ gas, bacteria of clinical importance were applied. Staphylococci, Streptococci and Bacillus strains were applied and Klebsiella, and others e.g., Escherichia coli, Shigella, Salmonella, Serratia were also done for the inhibitory analysis. Bacteria plates were applied with a hygiene stick, namely, "FarmeTok (Medistick/Puristic)" to produce $ClO_2$. $ClO_2$-releasing hygiene stick showed the very strong inhibition of bacterial growth but had different inhibitions to the bacteria above 96.7% except for MRSA of 90% inhibition. It is difficult to explain why the MRSA were not inhibited less than others at this point. It can be only suggested that more releasing $ClO_2$ should be essential to kill or inhibit the MRSA. B. subtilis, S. agalactiae, S. pyogenes, E. coli O157:H7, S. typhi (S. enterica serotype typhi) and S. marcesence were inhibited over 99%. This study will provide fundamental data to research growth inhibition by $ClO_2$ gas with bacteria of clinical importance value.

• Journal of Gastric Cancer
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• v.19 no.3
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• pp.254-277
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• 2019

Inflammation can be a causative factor for carcinogenesis or can result from a consequence of cancer progression. Moreover, cancer therapeutic interventions can also induce an inflammatory response. Various inflammatory parameters are used to assess the inflammatory status during cancer treatment. It is important to select the most optimal biomarker among these parameters. Additionally, suitable biomarkers must be examined if there are no known parameters. We briefly reviewed the published literature for the use of inflammatory parameters in the treatment of patients with cancer. Most studies on inflammation evaluated the correlation between host characteristics, effect of interventions, and clinical outcomes. Additionally, the levels of C-reactive protein, albumin, lymphocytes, and platelets were the most commonly used laboratory parameters, either independently or in combination with other laboratory parameters and clinical characteristics. Furthermore, the immune parameters are classically examined using flow cytometry, immunohistochemical staining, and enzyme-linked immunosorbent assay techniques. However, gene expression profiling can aid in assessing the overall peri-interventional immune status. The checklists of guidelines, such as STAndards for Reporting of Diagnostic accuracy and REporting recommendations for tumor MARKer prognostic studies should be considered when designing studies to investigate the inflammatory parameters. Finally, the data should be interpreted after adjusting for clinically important variables, such as age and cancer stage.

• Clinical and Experimental Reproductive Medicine
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• v.49 no.4
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• pp.225-238
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• 2022

The ultimate goal of human assisted reproductive technology is to achieve a healthy pregnancy and birth, ideally from the selection and transfer of a single competent embryo. Recently, techniques for efficiently evaluating the state and quality of preimplantation embryos using time-lapse imaging systems have been applied. Artificial intelligence programs based on deep learning technology and big data analysis of time-lapse monitoring system during in vitro culture of preimplantation embryos have also been rapidly developed. In addition, several molecular markers of the secretome have been successfully analyzed in spent embryo culture media, which could easily be obtained during in vitro embryo culture. It is also possible to analyze small amounts of cell-free nucleic acids, mitochondrial nucleic acids, miRNA, and long non-coding RNA derived from embryos using real-time polymerase chain reaction (PCR) or digital PCR, as well as next-generation sequencing. Various efforts are being made to use non-invasive evaluation of embryo quality (NiEEQ) to select the embryo with the best developmental competence. However, each NiEEQ method has some limitations that should be evaluated case by case. Therefore, an integrated analysis strategy fusing several NiEEQ methods should be urgently developed and confirmed by proper clinical trials.

• Korean Journal of Radiology
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• v.24 no.11
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• pp.1061-1080
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• 2023

Artificial intelligence (AI) in radiology is a rapidly developing field with several prospective clinical studies demonstrating its benefits in clinical practice. In 2022, the Korean Society of Radiology held a forum to discuss the challenges and drawbacks in AI development and implementation. Various barriers hinder the successful application and widespread adoption of AI in radiology, such as limited annotated data, data privacy and security, data heterogeneity, imbalanced data, model interpretability, overfitting, and integration with clinical workflows. In this review, some of the various possible solutions to these challenges are presented and discussed; these include training with longitudinal and multimodal datasets, dense training with multitask learning and multimodal learning, self-supervised contrastive learning, various image modifications and syntheses using generative models, explainable AI, causal learning, federated learning with large data models, and digital twins.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.4
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• pp.1547-1551
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• 2012

Background: Lung cancer is the leading cause of cancer morbidity and mortality. Its management has a significant economic impact on society. Despite a high incidence of cancer, so far, there is no national register for this disease in Morocco. The main goal of this report was to estimate the medical costs of lung cancer in our country. Methods: We first estimated the number of annual new cases according to stage of the disease on the basis of the Grand-Casablanca-Region Cancer Registry data. For each sub-group, the protocol of treatment was described taking into account the international guidelines, and an evaluation of individual costs during the first year following diagnosis was made. Extrapolation of the results to the whole country was used to calculate the total annual cost of treatments for lung cancer in Morocco. Results: Overall approximately 3,500 new cases of lung cancer occur each year in the country. Stages I and II account for only 4% of cases, while 96% are diagnosed at locally advanced or metastatic stages III and IV. The total medical cost of lung cancer in Morocco is estimated to be around USD 12 million. This cost represents approximately 1% of the global budget of the Health Department. According to AROME Guidelines, about 86% of the newly diagnosed lung cancer cases needed palliative treatment while 14% required curative intent therapy. The total cost of early and advanced stages lung cancer management during the first year were estimated to be 4,600 and 3,420 USD, respectively. Conclusion: This study provides health decision-makers with a first estimate of costs and the opportunity to achieve the optimal use of available data to estimate the needs of health facilities in Morocco. A substantial proportion of the burden of lung cancer could be prevented through the application of existing cancer control knowledge and by implementing tobacco control programs.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.4
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• pp.235-243
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• 2023

As next-generation sequencing has been developed and used widely, RNA-sequencing (RNA-seq) has rapidly emerged as the first choice of tools to validate global transcriptome profiling. With the significant advances in RNA-seq, various types of RNA-seq have evolved in conjunction with the progress in bioinformatic tools. On the other hand, it is difficult to interpret the complex data underlying the biological meaning without a general understanding of the types of RNA-seq and bioinformatic approaches. In this regard, this paper discusses the two main sections of RNA-seq. First, two major variants of RNA-seq are described and compared with the standard RNA-seq. This provides insights into which RNA-seq method is most appropriate for their research. Second, the most widely used RNA-seq data analyses are discussed: (1) exploratory data analysis and (2) pathway enrichment analysis. This paper introduces the most widely used exploratory data analysis for RNA-seq, such as principal component analysis, heatmap, and volcano plot, which can provide the overall trends in the dataset. The pathway enrichment analysis section introduces three generations of pathway enrichment analysis and how they generate enriched pathways with the RNA-seq dataset.

• Korean Journal of Radiology
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• v.21 no.6
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• pp.736-745
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• 2020

Objective: To identify the initial chest computed tomography (CT) findings and clinical characteristics associated with the course of coronavirus disease 2019 (COVID-19) pneumonia. Materials and Methods: Baseline CT scans and clinical and laboratory data of 72 patients admitted with COVID-19 pneumonia (39 men, 46.2 ± 15.9 years) were retrospectively analyzed. Baseline CT findings including lobar distribution, presence of ground glass opacities, consolidation, linear opacities, and lung severity score were evaluated. The outcome event was recovery with hospital discharge. The time from symptom onset to discharge or the end of follow-up (for those remained hospitalized) was recorded. Data were censored in events such as death or discharge without recovery. Multivariable Cox proportional hazard regression was used to explore the association between initial CT, clinical or laboratory findings, and discharge with recovery, whereby hazard ratio (HR) values < 1 indicated a lower rate of discharge at four weeks and longer time until discharge. Results: Thirty-two patients recovered and were discharged during the study period with a median length of admission of 16 days (range, 9 to 25 days), while the rest remained hospitalized at the end of this study (median, 17.5 days; range, 4 to 27 days). None died during the study period. After controlling for age, onset time, lesion characteristics, number of lung lobes affected, and bilateral involvement, the lung severity score on baseline CT (> 4 vs. ≤ 4 [reference]: adjusted HR = 0.41 [95% confidence interval, CI = 0.18-0.92], p = 0.031) and initial lymphocyte count (reduced vs. normal or elevated [reference]: adjusted HR = 0.14 [95% CI = 0.03-0.60], p = 0.008) were two significant independent factors that influenced recovery and discharge. Conclusion: Lung severity score > 4 and reduced lymphocyte count at initial evaluation were independently associated with a significantly lower rate of recovery and discharge and extended hospitalization in patients admitted for COVID-19 pneumonia.

• Bioinformatics and Biosystems
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• v.1 no.1
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• pp.28-37
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• 2006

Recent studies in molecular biology and proteomics have identified a significant number of novel diagnostic, prognostic, and therapeutic disease markers. However, validation of these markers in clinical specimens with traditional histopathological techniques involves low throughput and is time consuming and labor intensive. Tissue microarrays (TMAs) offer a means of combining tens to hundreds of specimens of tissue onto a single slide for simultaneous analysis. This capability is particularly pertinent in the field of cancer for target verification of data obtained from cDNA micro arrays and protein expression profiling of tissues, as well as in epidemiology-based investigations using histochemical/immunohistochemical staining or in situ hybridization. In combination with automated image analysis, TMA technology can be used in the global cellular network analysis of tissues. In particular, this potential has generated much excitement in cardiovascular disease research. The following review discusses recent advances in the construction and application of TMAs and the opportunity for developing novel, highly sensitive diagnostic tools for the early detection of cardiovascular disease.