Developing a multi-center clinical data mart of ACEI and ARB for real-world evidence (RWE)

Background Randomized controlled trials can be expensive and time-consuming, leading to medical researchers utilizing real-world evidence (RWE) based on already-collected data. We aimed to conduct various RWE studies on angiotensin-converting enzyme inhibitors (ACEI) and angiotensin II receptor blocker (ARB), commonly used as first-line therapy for blood pressure, and to develop a multi-center clinical data mart (CDM) of ACEI/ARB for various clinical purposes. Methods Data from electronic medical records of St. Marys Hospital and the Seoul National University Hospital were collected. We obtained blood and urine test results of patients within the 30 days prior to their first prescription of ACEI or ARB, as well as the first date of diagnosis and presence of various chronic and cardiovascular diseases using the International Classification of Diseases-10 classification. One researcher managed data quality and collation for each hospital in order to facilitate patient anonymity. When results were unclear, the responsible investigator for each hospital attempted to resolve ambiguities by direct chart review. Results A total of 102,333 patients who were prescribed ACEI or ARB for the first time were included (21,481 ACEI, 80,551 ARB, and 301 both). Our ACEI/ARB-CDM included short-term studies (within 12 months) to observe changes in various blood or urinary laboratory test values after the initial prescription of ACEI or ARB and long-term studies to confirm the incidence of various diseases. Conclusion We established a CDM of RWE for ACEI/ARB prescription, which included various clinical studies. As we accumulate experience in this process, we expect that the use of RWE research will grow and develop.The research was supported by funding from the Korean Society of Hypertension (2018)

Maternal Psychosocial Factors that Affect Breastfeeding Adaptation and Immune Substances in Human Milk

PURPOSE: This study was to identify relationships of maternal psychosocial factors including mother's mood state, childcare stress, social support and sleep satisfaction with breastfeeding adaptation and immune substances in breast milk, especially secretory immunoglobulin A (sIgA) and transforming growth factor-beta 2 (TGF-beta2). METHODS: Data were collected from 84 mothers who delivered full-term infants by natural childbirth. Structured questionnaires and breast milk were collected at 2~4 days and 6 weeks postpartum. Data were analyzed using descriptive statistics, Pearson's correlation, multiple linear regression, and generalized estimating equation (GEE). RESULTS: Scores for the breastfeeding adaptation scale were significantly related with child care stress, mood state and social support. Mother's anger was positively correlated with the level of sIgA in colostrum (p<.01). Immune substances of breastmilk was significantly influenced by time for milk collection (p<.001) and the type of breastfeeding (sIgA, p<.001, TGF-beta2, p=.003). Regression analysis showed that breastfeeding adaptation could be explained 59.1% by the type of breastfeeding, childcare stress, the Profile of Mood States, emotional support and sleep quality (F=16.67, p<.001). CONCLUSION: The findings from this study provide important concepts of breastfeeding adaptation program and explanation of psychosocial factors by immune substances in breast milk. Future research, specially, bio-maker research on breast milk should focus on the ways to improve breastfeeding adaptation

Pairwise Feature Learning for Unseen Plant Disease Recognition

With the advent of Deep Learning, people have begun to use it with computer vision approaches to identify plant diseases on a large scale targeting multiple crops and diseases. However, this requires a large amount of plant disease data, which is often not readily available, and the cost of acquiring disease images is high. Thus, developing a generalized model for recognizing unseen classes is very important and remains a major challenge to date. Existing methods solve the problem with general supervised recognition tasks based on the seen composition of the crop and the disease. However, ignoring the composition of unseen classes during model training can lead to a reduction in model generalisation. Therefore, in this work, we propose a new approach that leverages the visual features of crop and disease from the seen composition, using them to learn the features of unseen crop-disease composition classes. We show that our proposed method can improve the classification performance of these unseen classes and outperform the state-of-the-art in the identification of multiple crop-diseases

Risk Factors and Control Strategies for the Rapidly Rising Rate of Breast Cancer in Korea

Due to the aging population and tremendous changes in life style over the past decades, cancer has been the leading cause of death in Korea. The incidence rate of breast cancer is the second highest in Korea, and it has shown an annual increase of 6.8% for the past 6 years. The major risk factors of breast cancer in Korean women are as follows: Early menarche, late menopause, late full-term pregnancy (FTP), and low numbers of FTP. Height and body mass index increased the risk of breast cancer in postmenopausal women only. There are ethnic variations in breast cancer due to the differences in genetic susceptibility or exposure to etiologic agent. With the epidemiological evidences on the possibility of further increase of breast cancer in Korea, the Korean Government began implementing the National Cancer Screening Program against breast cancer in 2002. Five-year survival rates for female breast cancer have improved significantly from 78.0% in early 1993-1995 to 90.0% in 2004-2008. This data indicate that improvement of the survival rate may be partially due to the early diagnosis of breast cancer as well as the increased public awareness about the significance of early detection and organized cancer screening program. The current primary prevention programs are geared towards strengthening national prevention campaigns. In accordance with the improvement in 5-year survival rate, the overall cancer mortality has started to decrease. However, breast cancer death rate and incidence rates are still increasing, which need further organized effort by the Korean Government

Feasibility of routine lymphadenectomy in clinical stage-I endometrial cancer

BACKGROUND: To determine the accuracy of several preoperative tests in predicting lymph node (LN) metastases and the feasibility of doing a routine lymphadenectomy in clinical stage-I endometrial cancer. MATERIAL/METHODS: We reviewed 132 patients with clinical stage-I endometrial cancer. The preoperative tests used to predict LN metastases were serum CA-125 level, histologic type and grade, LN status assessed by pelvic magnetic resonance image (MRI) or computed tomography (CT), and depth of myometrial invasion assessed only by pelvic MRI. The cutoff value of the serum CA-125 level was determined using receiver operating characteristic curves. Multivariate logistic regression analyses were used to determine which tests are good predictors of LN metastases. RESULTS: Of 132 patients, 13 (9.8%) had LN metastases. On univariate logistic regression analysis, a high CA-125 level and preoperative LN evaluation by pelvic MRI or CT were significant predictors for LN metastases (OR=17.41, 95% CI: 4.36-69.56 and OR=14.30, 95% CI: 4.02-50.63, respectively). However, on multivariate logistic regression analysis adjusted for age and all preoperative tests, a high CA-125 level was the most significant predictor (OR=13.73, 95% CI: 2.03-92.73). Among the 97 patients with no significant predictor of LN metastases, pelvic LN metastases were observed in 3 patients (3.1%) and para-aortic LN metastases were observed in 1 patient (1.1%). Surgical complications were mild (lymphocele, n=9; lymphedema, n=2; wound problem, n=2). CONCLUSIONS: Considering the importance of LN metastases as an indicator of prognosis, and the relatively low surgical risk of lymphadenectomy, clinicians should cautiously consider routine lymphadenectomy in patients with clinical stage-I endometrial cancer

Atopy and House Dust Mite Sensitization as Risk Factors for Asthma in Children

Asthma is commonly described as an atopic disease in childhood, but some cases of this disorder do not fit this description. The aim of this study was to evaluate the frequency of atopy, asthma, and sensitization to house dust mites in children with allergic symptoms. This study was performed at the Severance Hospital of Yonsei University with patients who visited the allergy clinic for evaluation of nonspecific upper respiratory symptoms, typical symptoms of asthma, or a general health workup. The patients were divided into three age groups: 0-3 years (group 1), 4-7 years (group 2), and 8-12 years (group 3). Of the 1,244 children examined, 844 (67.8%) were atopic and 400 (32.2%) were non-atopic. The frequency of atopy and asthma increased with age. Asthma was diagnosed in the same proportion (64%) of atopic and non-atopic children. As risk factors for asthma symptoms, the positive values of house dust mite (HDM) sensitivity were significantly increased in groups 1, 2, and 3 to 53.5%, 68.9%, and 80.2%, respectively. A significant difference between the percentage of asthmatics sensitized to HDM and that of asthmatics not sensitized to HDM was found only in group 3. In conclusion, asthma is related to atopy with increasing age, and house dust mite sensitization seems to be an important determinant of asthma in older children in Korea

Health Indicators Related to Disease, Death, and Reproduction

One of the primary goals of epidemiology is to quantify various aspects of a population’s health, illness, and death status and the determinants (or risk factors) thereof by calculating health indicators that measure the magnitudes of various conditions. There has been some confusion regarding health indicators, with discrepancies in usage among organizations such as the World Health Organization the, Centers for Disease Control and Prevention (CDC), and the CDC of other countries, and the usage of the relevant terminology may vary across papers. Therefore, in this review, we would like to propose appropriate terminological definitions for health indicators based on the most commonly used meanings and/or the terms used by official agencies, in order to bring clarity to this area of confusion. We have used appropriate examples to make each health indicator easy for the reader to understand. We have included practical exercises for some health indicators to help readers understand the underlying concepts

A switch-on mechanism to activate maize ribosome-inactivating protein for targeting HIV-infected cells

Maize ribosome-inactivating protein (RIP) is a plant toxin that inactivates eukaryotic ribosomes by depurinating a specific adenine residue at the α-sarcin/ricin loop of 28S rRNA. Maize RIP is first produced as a proenzyme with a 25-amino acid internal inactivation region on the protein surface. During germination, proteolytic removal of this internal inactivation region generates the active heterodimeric maize RIP with full N-glycosidase activity. This naturally occurring switch-on mechanism provides an opportunity for targeting the cytotoxin to pathogen-infected cells. Here, we report the addition of HIV-1 protease recognition sequences to the internal inactivation region and the activation of the maize RIP variants by HIV-1 protease in vitro and in HIV-infected cells. Among the variants generated, two were cleaved efficiently by HIV-1 protease. The HIV-1 protease-activated variants showed enhanced N-glycosidase activity in vivo as compared to their un-activated counterparts. They also possessed potent inhibitory effect on p24 antigen production in human T cells infected by two HIV-1 strains. This switch-on strategy for activating the enzymatic activity of maize RIP in target cells provides a platform for combating pathogens with a specific protease

LRP16 Integrates into NF-κB Transcriptional Complex and Is Required for Its Functional Activation

BACKGROUND: Nuclear factor κB (NF-κB)-mediated pathways have been widely implicated in cell survival, development and tumor progression. Although the molecular events of determining NF-κB translocation from cytoplasm to nucleus have been extensively documented, the regulatory mechanisms of NF-κB activity inside the nucleus are still poorly understood. Being a special member of macro domain proteins, LRP16 was previously identified as a coactivator of both estrogen receptor and androgen receptor, and as an interactor of NF-κB coactivator UXT. Here, we investigated the regulatory role of LRP16 on NF-κB activation. METHODOLOGY: GST pull-down and coimmunoprecipitation (CoIP) assays assessed protein-protein interactions. The functional activity of NF-κB was assessed by luciferase assays, changes in expression of its target genes, and its DNA binding ability. Annexin V staining and flow cytometry analysis were used to evaluate cell apoptosis. Immunohistochemical staining of LRP16 and enzyme-linked immunosorbent assay-based evaluation of active NF-κB were performed on primary human gastric carcinoma samples. RESULTS: We demonstrate that LRP16 integrates into NF-κB transcriptional complex through associating with its p65 component. RNA interference knockdown of the endogenous LRP16 in cells leads to impaired NF-κB activity and significantly attenuated NF-κB-dependent gene expression. Mechanistic analysis revealed that knockdown of LRP16 did not affect tumor necrosis factor α (TNF-α)-induced nuclear translocation of NF-κB, but blunted the formation or stabilization of functional NF-κB/p300/CREB-binding protein transcription complex in the nucleus. In addition, knockdown of LRP16 also sensitizes cells to apoptosis induced by TNF-α. Finally, a positive link between LRP16 expression intensity in nuclei of tumor cells and NF-κB activity was preliminarily established in human gastric carcinoma specimens. CONCLUSIONS: Our findings not only indicate that LRP16 is a crucial regulator for NF-κB activation inside the nucleus, but also suggest that LRP16 may be an important contributor to the aberrant activation of NF-κB in tumors