• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.2
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• pp.325-330
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• 2009

In Korea, medical diagnostic equipments and biochemical examination can not be used in order for diagnosing sub-healthy state or ante-disease state in oriental medicine clinic. So morphic analogical method used in oriental medicine can be a good tool as a disease-predictable signs in order to enable preventive diagnosis and therapy. Therefore the four geometrical subjects; Essence, Pneuma, Spirit, Blood(四科;精氣紳血) and the four taxonomical species; Pisces, Quadruped, Aves, Carapaces(四類;魚走鳥甲) are chosen as morphic models in this paper. The differences of two classifying methods with four subjects and four species were as follows. The diagnostic category was meta-medical and synthetic against medical specific. The diagnostic object was body in contrast with face. They were able to be applicant in psychology and classification of characteristics against diagnostics and therapeutics directly in oriental medicine. The theoretical basis was basic diagrams of four unit-fluids of body and morphological analogy with four animal species respectively. And the therapeutic aims were systemic pathogenesis following five phase theory against congestion and deficiency of Essence, Pneuma, Spirit, Blood. The four subjects and four species are mixed each other practically in clinic. But it should be used limitedly because of the above reasons described and must divide the principal and secondary factors and follow the pathology of principal shape factor. In order to improve the diagnostic value of ante-disease state, the discriminable standards, measurement methods, limit of interrelating interpretation and the criteria of abnormal disproportion were needed to be defined more clearly in advance.

• Smart Media Journal
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• v.7 no.3
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• pp.22-28
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• 2018

Air pollution problems in Korea are gradually becoming a higher concern due to various reasons such as fine dust, causing anxiety among people with regard to their health. Although various studies have been carried out on the relationship between the influence of fine dust and a certain disease, they are mostly focusing on the analyzation that fine dust is related to specific illnesses such as respiratory and cardiovascular diseases, hypertension and diabetes. In this paper, we utilize the public data of medical history information to extract ten medical care subjects with the highest number of monthly care in 2016, and analyze the relation of fine dust with certain medical subjects using Pearson correlation coefficient. We also subdivide and analyze the correlation between fine dust and the medical subjects according to their gender and age. Middle-aged Female group with the strongest positive correlation between fine dust and the medical subjects is analyzed with the correlation from 2011 to 2015, with its relevance coefficient extracted by regression analysis in order to predict the correlation with the medical subjects according to the fine dust concentration.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.7
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• pp.2601-2611
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• 2015

Prostate cancer, with a lifetime prevalence of one in six men, is the second cause of malignancy-related death and the most prevalent cancer in men in many countries. Nowadays, prostate cancer diagnosis is often based on the use of biomarkers, especially prostate-specific antigen (PSA) which can result in enhanced detection at earlier stage and decreasing in the number of metastatic patients. However, because of the low specificity of PSA, unnecessary biopsies and mistaken diagnoses frequently occur. Prostate cancer has various features so prognosis following diagnosis is greatly variable. There is a requirement for new prognostic biomarkers, particularly to differentiate between inactive and aggressive forms of disease, to improve clinical management of prostate cancer. Research continues into finding additional markers that may allow this goal to be attained. We here selected a group of candidate biomarkers including PSA, PSA velocity, percentage free PSA, $TGF{\beta}1$, AMACR, chromogranin A, IL-6, IGFBPs, PSCA, biomarkers related to cell cycle regulation, apoptosis, PTEN, androgen receptor, cellular adhesion and angiogenesis, and also prognostic biomarkers with Genomic tests for discussion. This provides an outline of biomarkers that are presently of prognostic interest in prostate cancer investigation.

• The Plant Pathology Journal
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• v.37 no.4
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• pp.404-412
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• 2021

Despite the plant microbiota plays an important role in plant health, little is known about the potential interactions of the flower microbiota with pathogens. In this study, we investigated the microbial community of apple blossoms when infected with Erwinia amylovora. The long-read sequencing technology, which significantly increased the genome sequence resolution, thus enabling the characterization of fire blight-induced changes in the flower microbial community. Each sample showed a unique microbial community at the species level. Pantoea agglomerans and P. allii were the most predominant bacteria in healthy flowers, whereas E. amylovora comprised more than 90% of the microbial population in diseased flowers. Furthermore, gene function analysis revealed that glucose and xylose metabolism were enriched in diseased flowers. Overall, our results showed that the microbiome of apple blossoms is rich in specific bacteria, and the nutritional composition of flowers is important for the incidence and spread of bacterial disease.

• Biomedical Science Letters
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• v.29 no.2
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• pp.53-57
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• 2023

The main objective of pathologists is to achieve accurate lesion diagnoses, which has become increasingly challenging due to the growing number of pathological slides that need to be examined. However, using digital technology has made it easier to complete this task compared to older methods. Digital pathology is a specialized field that manages data from digitized specimen slides, utilizing image processing technology to automate and improve analysis. It aims to enhance the precision, reproducibility, and standardization of pathology-based researches, preclinical, and clinical trials through the sophisticated techniques it employs. The advent of whole slide imaging (WSI) technology is revolutionizing the pathology field by replacing glass slides as the primary method of pathology evaluation. Image processing technology that utilizes WSI is being implemented to automate and enhance analysis. Artificial intelligence (AI) algorithms are being developed to assist pathologic diagnosis and detection and segmentation of specific objects. Application of AI-based digital pathology in biomedical researches is classified into four areas: diagnosis and rapid peer review, quantification, prognosis prediction, and education. AI-based digital pathology can result in a higher accuracy rate for lesion diagnosis than using either a pathologist or AI alone. Combining AI with pathologists can enhance and standardize pathology-based investigations, reducing the time and cost required for pathologists to screen tissue slides for abnormalities. And AI-based digital pathology can identify and quantify structures in tissues. Lastly, it can help predict and monitor disease progression and response to therapy, contributing to personalized medicine.

• The Plant Pathology Journal
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• v.40 no.3
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• pp.290-298
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• 2024

K-Maryblyt has been developed for the effective control of secondary fire blight infections on blossoms and the elimination of primary inoculum sources from cankers and newly emerged shoots early in the season for both apple and pear trees. This model facilitates the precise determination of the blossom infection timing and identification of primary inoculum sources, akin to Maryblyt, predicting flower infections and the appearance of symptoms on various plant parts, including cankers, blossoms, and shoots. Nevertheless, K-Maryblyt has undergone significant improvements: Integration of Phenology Models for both apple and pear trees, Adoption of observed or predicted hourly temperatures for Epiphytic Infection Potential (EIP) calculation, incorporation of adjusted equations resulting in reduced mean error with 10.08 degree-hours (DH) for apple and 9.28 DH for pear, introduction of a relative humidity variable for pear EIP calculation, and adaptation of modified degree-day calculation methods for expected symptoms. Since the transition to a model-based control policy in 2022, the system has disseminated 158,440 messages related to blossom control and symptom prediction to farmers and professional managers in its inaugural year. Furthermore, the system has been refined to include control messages that account for the mechanism of action of pesticides distributed to farmers in specific counties, considering flower opening conditions and weather suitability for spraying. Operating as a pivotal module within the Fire Blight Forecasting Information System (FBcastS), K-Maryblyt plays a crucial role in providing essential fire blight information to farmers, professional managers, and policymakers.

• Journal of Preventive Medicine and Public Health
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• v.47 no.4
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• pp.206-215
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• 2014

Objectives: The hospital standardized mortality ratio (HSMR) has been widely used because it allows for robust risk adjustment using administrative data and is important for improving the quality of patient care. Methods: All inpatients discharged from hospitals with more than 700 beds (66 hospitals) in 2008 were eligible for inclusion. Using the claims data, 29 most responsible diagnosis (MRDx), accounting for 80% of all inpatient deaths among these hospitals, were identified, and inpatients with those MRDx were selected. The final study population included 703 571 inpatients including 27 718 (3.9% of all inpatients) in-hospital deaths. Using logistic regression, risk-adjusted models for predicting in-hospital mortality were created for each MRDx. The HSMR of individual hospitals was calculated for each MRDx using the model coefficients. The models included age, gender, income level, urgency of admission, diagnosis codes, disease-specific risk factors, and comorbidities. The Elixhauser comorbidity index was used to adjust for comorbidities. Results: For 26 out of 29 MRDx, the c-statistics of these mortality prediction models were higher than 0.8 indicating excellent discriminative power. The HSMR greatly varied across hospitals and disease groups. The academic status of the hospital was the only factor significantly associated with the HSMR. Conclusions: We found a large variation in HSMR among hospitals; therefore, efforts to reduce these variations including continuous monitoring and regular disclosure of the HSMR are required.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.7
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• pp.3089-3097
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• 2012

Background and Aims: Vascular endothelial growth factor (VEGF) is a potential prognostic biomarker for patients with resected gastric cancer. However, its role remains controversial. The objective of this study was to conduct a systematic review and meta-analysis of published literature. Methods: Relevant literature was identified using Medline and survival data from published studies were collected following a methodological assessment. Quality assessment of eligible studies and meta-analysis of hazard ratio (HR) were performed to review the correlation of VEGF overexpression with survival and recurrence in patients with gastric cancer. Results: Our meta-analysis included 44 published studies with 4,794 resected patients. VEGF subtype for the prediction of overall survival (OS) included tissue VEGF (HR=2.13, 95% CI 1.71-2.65), circulating VEGF (HR=4.22, 95% CI 2.47-7.18), tissue VEGF-C (HR=2.21, 95% CI 1.58-3.09), tissue VEGF-D (HR=1.73, 95% CI 1.25-2.40). Subgroup analysis showed that HRs of tissue VEGF for OS were, 1.78 (95% CI 0.90-3.51) and 2.31 (95% CI 1.82-2.93) in non-Asians and Asians, respectively. The meta-analysis was also conducted for disease free survival (DFS) and disease specific survival (DSS). Conclusion: Positive expression of tissue VEGF, circulating VEGF, VEGF-C and VEGF-D were all associated with poor prognosis in resected gastric cancer. However, VEGF demonstrated no significant prognostic value for non-Asian populations. Circulating VEGF may be better than tissue VEGF in predicting prognosis.

• The Plant Pathology Journal
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• v.35 no.5
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• pp.508-520
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• 2019

Interplay between Cymbidium mosaic virus (CymMV)/Odontoglossum ringspot virus (ORSV) and its host plant Phalaenopsis equestris remain largely unknown, which led to deficiency of effective measures to control disease of P. equestris caused by infecting viruses. In this study, for the first time, we characterized viral small interfering RNAs (vsiRNAs) profiles in P. equestris co-infected with CymMV and ORSV through small RNA sequencing technology. CymMV and ORSV small interfering RNAs (siRNAs) demonstrated several general and specific/new characteristics. vsiRNAs, with A/U bias at the first nucleotide, were predominantly 21-nt long and they were derived predominantly (90%) from viral positive-strand RNA. 21-nt siRNA duplexes with 0-nt overhangs were the most abundant 21-nt duplexes, followed by 2-nt overhangs and then 1-nt overhangs 21-nt duplexes in infected P. equestris. Continuous but heterogeneous distribution and secondary structures prediction implied that vsiRNAs originate predominantly by direct Dicer-like enzymes cleavage of imperfect duplexes in the most folded regions of the positive strand of both viruses RNA molecular. Furthermore, we totally predicted 54 target genes by vsiRNAs with psRNATarget server, including disease/stress response-related genes, RNA interference core components, cytoskeleton-related genes, photosynthesis or energy supply related genes. Gene Ontology classification showed that a majority of the predicted targets were related to cellular components and cellular processes and performed a certain function. All target genes were down-regulated with different degree by vsiRNAs as shown by real-time reverse transcription polymerase chain reaction. Taken together, CymMV and ORSV siRNAs played important roles in interplay with P. equestris by down modulating the expression levels of endogenous genes in host plant.

• IMMUNE NETWORK
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• v.11 no.1
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• pp.11-41
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• 2011

The discovery of microRNA (miRNA) is one of the major scientific breakthroughs in recent years and has revolutionized current cell biology and medical science. miRNAs are small (19~25nt) noncoding RNA molecules that post-transcriptionally regulate gene expression by targeting the 3' untranslated region (3'UTR) of specific messenger RNAs (mRNAs) for degradation of translation repression. Genetic ablation of the miRNA machinery, as well as loss or degradation of certain individual miRNAs, severely compromises immune development and response, and can lead to immune disorders. Several sophisticated regulatory mechanisms are used to maintain immune homeostasis. Regulatory T (Treg) cells are essential for maintaining peripheral tolerance, preventing autoimmune diseases and limiting chronic inflammatory diseases. Recent publications have provided compelling evidence that miRNAs are highly expressed in Treg cells, that the expression of Foxp3 is controlled by miRNAs and that a range of miRNAs are involved in the regulation of immunity. A large number of studies have reported links between alterations of miRNA homeostasis and pathological conditions such as cancer, cardiovascular disease and diabetes, as well as psychiatric and neurological diseases. Although it is still unclear how miRNA controls Treg cell development and function, recent studies certainly indicate that this topic will be the subject of further research. The specific circulating miRNA species may also be useful for the diagnosis, classification, prognosis of diseases and prediction of the therapeutic response. An explosive literature has focussed on the role of miRNA. In this review, I briefly summarize the current studies about the role of miRNAs in Treg cells and in the regulation of the innate and adaptive immune response. I also review the explosive current studies about clinical application of miRNA.