Daegu Catholic University

Multicollinearity represents a high degree of linear intercorrelation between explanatory variables in a multiple regression model and leads to incorrect results of regression analyses. Diagnostic tools of multicollinearity include the variance inflation factor (VIF), condition index and condition number, and variance decomposition proportion (VDP). The multicollinearity can be expressed by the coefficient of determination (Rh2) of a multiple regression model with one explanatory variable (Xh) as the model's response variable and the others (Xi [i ≠ h]) as its explanatory variables. The variance (σh2) of the regression coefficients constituting the final regression model are proportional to the VIF. Hence, an increase in Rh2 (strong multicollinearity) increases σh2. The larger σh2 produces unreliable probability values and confidence intervals of the regression coefficients. The square root of the ratio of the maximum eigenvalue to each eigenvalue from the correlation matrix of standardized explanatory variables is referred to as the condition index. The condition number is the maximum condition index. Multicollinearity is present when the VIF is higher than 5 to 10 or the condition indices are higher than 10 to 30. However, they cannot indicate multicollinear explanatory variables. VDPs obtained from the eigenvectors can identify the multicollinear variables by showing the extent of the inflation of σh2 according to each condition index. When two or more VDPs, which correspond to a common condition index higher than 10 to 30, are higher than 0.8 to 0.9, their associated explanatory variables are multicollinear. Excluding multicollinear explanatory variables leads to statistically stable multiple regression models.

, distribute normally with mean, µ, and variance, [Formula: see text]. Using the central limit theorem, a variety of parametric tests have been developed under assumptions about the parameters that determine the population probability distribution. Compared to non-parametric tests, which do not require any assumptions about the population probability distribution, parametric tests produce more accurate and precise estimates with higher statistical powers. However, many medical researchers use parametric tests to present their data without knowledge of the contribution of the central limit theorem to the development of such tests. Thus, this review presents the basic concepts of the central limit theorem and its role in binomial distributions and the Student's t-test, and provides an example of the sampling distributions of small populations. A proof of the central limit theorem is also described with the mathematical concepts required for its near-complete understanding.

BACKGROUND/AIMS: Ginseng regulates gastrointestinal (GI) motor activity but the underlying components and molecular mechanisms are unknown. We investigated the effect of gintonin, a novel ginseng-derived G protein-coupled lysophosphatidic acid (LPA) receptor ligand, on the pacemaker activity of the interstitial cells of Cajal (ICC) in murine small intestine and GI motility. MATERIALS AND METHODS: Enzymatic digestion was used to dissociate ICC from mouse small intestines. The whole-cell patch-clamp configuration was used to record pacemaker potentials and currents from cultured ICC in the absence or presence of gintonin. In vivo effects of gintonin on gastrointestinal (GI) motility were investigated by measuring the intestinal transit rate (ITR) of Evans blue in normal and streptozotocin (STZ)-induced diabetic mice. RESULTS: We investigated the effects of gintonin on pacemaker potentials and currents in cultured ICC from mouse small intestine. Gintonin caused membrane depolarization in current clamp mode but this action was blocked by Ki16425, an LPA1/3 receptor antagonist, and by the addition of GDPβS, a GTP-binding protein inhibitor, into the ICC. To study the gintonin signaling pathway, we examined the effects of U-73122, an active PLC inhibitor, and chelerythrine and calphostin, which inhibit PKC. All inhibitors blocked gintonin actions on pacemaker potentials, but not completely. Gintonin-mediated depolarization was lower in Ca(2+)-free than in Ca(2+)-containing external solutions and was blocked by thapsigargin. We found that, in ICC, gintonin also activated Ca(2+)-activated Cl(-) channels (TMEM16A, ANO1), but not TRPM7 channels. In vivo, gintonin (10-100 mg/kg, p.o.) not only significantly increased the ITR in normal mice but also ameliorated STZ-induced diabetic GI motility retardation in a dose-dependent manner. CONCLUSIONS: Gintonin-mediated membrane depolarization of pacemaker activity and ANO1 activation are coupled to the stimulation of GI contractility through LPA1/3 receptor signaling pathways in cultured murine ICC. Gintonin might be a ingredient responsible for ginseng-mediated GI tract modulations, and could be a novel candidate for development as a prokinetic agent that may prevent or alleviate GI motility dysfunctions in human patients.

Chitosan is a modified, natural biopolymer derived by deacetylation of chitin, a major component of the shells of crustacean. Recently, chitosan has received increased attention for its commercial applications in the biomedical, food, and chemical industries. Use of chitosan in food industry is readily seen due to its several distinctive biological activities and functional properties. The antimicrobial activity and film-forming property of chitosan make it a potential source of food preservative or coating material of natural origin. This review focuses on the applications of chitosan for improvement of quality and shelf life of various foods from agriculture, poultry, and seafood origin.

Abstract Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities 1,2 . This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity 3–6 . Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017—and more than 80% in some low- and middle-income regions—was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing—and in some countries reversal—of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.

Federated learning (FL) is a method used for training artificial intelligence models with data from multiple sources while maintaining data anonymity, thus removing many barriers to data sharing. Here we used data from 20 institutes across the globe to train a FL model, called EXAM (electronic medical record (EMR) chest X-ray AI model), that predicts the future oxygen requirements of symptomatic patients with COVID-19 using inputs of vital signs, laboratory data and chest X-rays. EXAM achieved an average area under the curve (AUC) >0.92 for predicting outcomes at 24 and 72 h from the time of initial presentation to the emergency room, and it provided 16% improvement in average AUC measured across all participating sites and an average increase in generalizability of 38% when compared with models trained at a single site using that site's data. For prediction of mechanical ventilation treatment or death at 24 h at the largest independent test site, EXAM achieved a sensitivity of 0.950 and specificity of 0.882. In this study, FL facilitated rapid data science collaboration without data exchange and generated a model that generalized across heterogeneous, unharmonized datasets for prediction of clinical outcomes in patients with COVID-19, setting the stage for the broader use of FL in healthcare.

Missing values and outliers are frequently encountered while collecting data. The presence of missing values reduces the data available to be analyzed, compromising the statistical power of the study, and eventually the reliability of its results. In addition, it causes a significant bias in the results and degrades the efficiency of the data. Outliers significantly affect the process of estimating statistics (e.g., the average and standard deviation of a sample), resulting in overestimated or underestimated values. Therefore, the results of data analysis are considerably dependent on the ways in which the missing values and outliers are processed. In this regard, this review discusses the types of missing values, ways of identifying outliers, and dealing with the two.

Low-cost, high-yield production of graphene nanosheets (GNs) is essential for practical applications. We have achieved high yield of edge-selectively carboxylated graphite (ECG) by a simple ball milling of pristine graphite in the presence of dry ice. The resultant ECG is highly dispersable in various solvents to self-exfoliate into single- and few-layer (≤ 5 layers) GNs. These stable ECG (or GN) dispersions have been used for solution processing, coupled with thermal decarboxylation, to produce large-area GN films for many potential applications ranging from electronic materials to chemical catalysts. The electrical conductivity of a thermally decarboxylated ECG film was found to be as high as 1214 S/cm, which is superior to its GO counterparts. Ball milling can thus provide simple, but efficient and versatile, and eco-friendly (CO(2)-capturing) approaches to low-cost mass production of high-quality GNs for applications where GOs have been exploited and beyond.

BACKGROUND: Simulation-based nursing education is an increasingly popular pedagogical approach. It provides students with opportunities to practice their clinical and decision-making skills through various real-life situational experiences. However, simulation approaches fall along a continuum ranging from low-fidelity to high-fidelity simulation. The purpose of this study was to determine the effect size of simulation-based educational interventions in nursing and compare effect sizes according to the fidelity level of the simulators through a meta-analysis. METHOD: This study explores the quantitative evidence published in the electronic databases EBSCO, Medline, ScienceDirect, ERIC, RISS, and the National Assembly Library of Korea database. Using a search strategy including the search terms "nursing," "simulation," "human patient," and "simulator," we identified 2279 potentially relevant articles. Forty studies met the inclusion criteria and were retained in the analysis. RESULTS: This meta-analysis showed that simulation-based nursing education was effective in various learning domains, with a pooled random-effects standardized mean difference of 0.70. Subgroup analysis revealed that effect sizes were larger for high-fidelity simulation (0.86), medium-fidelity simulation (1.03), and standardized patients (0.86) than they were for low-fidelity and hybrid simulations. In terms of cognitive outcomes, the effect size was the largest for high-fidelity simulation (0.50). Regarding affective outcome, high-fidelity simulation (0.80) and standardized patients (0.73) had the largest effect sizes. CONCLUSIONS: These results suggest that simulation-based nursing educational interventions have strong educational effects, with particularly large effects in the psychomotor domain. Since the effect is not proportional to fidelity level, it is important to use a variety of educational interventions to meet all of the educational goals.

BACKGROUND: The potential benefits and risks of the use of dual antiplatelet therapy beyond a 12-month period in patients receiving drug-eluting stents have not been clearly established. METHODS: In two trials, we randomly assigned a total of 2701 patients who had received drug-eluting stents and had been free of major adverse cardiac or cerebrovascular events and major bleeding for a period of at least 12 months to receive clopidogrel plus aspirin or aspirin alone. The primary end point was a composite of myocardial infarction or death from cardiac causes. Data from the two trials were merged for analysis. RESULTS: The median duration of follow-up was 19.2 months. The cumulative risk of the primary outcome at 2 years was 1.8% with dual antiplatelet therapy, as compared with 1.2% with aspirin monotherapy (hazard ratio, 1.65; 95% confidence interval [CI], 0.80 to 3.36; P=0.17). The individual risks of myocardial infarction, stroke, stent thrombosis, need for repeat revascularization, major bleeding, and death from any cause did not differ significantly between the two groups. However, in the dual-therapy group as compared with the aspirin-alone group, there was a nonsignificant increase in the composite risk of myocardial infarction, stroke, or death from any cause (hazard ratio, 1.73; 95% CI, 0.99 to 3.00; P=0.051) and in the composite risk of myocardial infarction, stroke, or death from cardiac causes (hazard ratio, 1.84; 95% CI, 0.99 to 3.45; P=0.06). CONCLUSIONS: The use of dual antiplatelet therapy for a period longer than 12 months in patients who had received drug-eluting stents was not significantly more effective than aspirin monotherapy in reducing the rate of myocardial infarction or death from cardiac causes. These findings should be confirmed or refuted through larger, randomized clinical trials with longer-term follow-up. (ClinicalTrials.gov numbers, NCT00484926 and NCT00590174.)

Mineral malnutrition stemming from undiversified plant-based diets is a top global challenge. In C3 plants (e.g., rice, wheat), elevated concentrations of atmospheric carbon dioxide (eCO2) reduce protein and nitrogen concentrations, and can increase the total non-structural carbohydrates (TNC; mainly starch, sugars). However, contradictory findings have obscured the effect of eCO2 on the ionome-the mineral and trace-element composition-of plants. Consequently, CO2-induced shifts in plant quality have been ignored in the estimation of the impact of global change on humans. This study shows that eCO2 reduces the overall mineral concentrations (-8%, 95% confidence interval: -9.1 to -6.9, p<0.00001) and increases TNC:minerals > carbon:minerals in C3 plants. The meta-analysis of 7761 observations, including 2264 observations at state of the art FACE centers, covers 130 species/cultivars. The attained statistical power reveals that the shift is systemic and global. Its potential to exacerbate the prevalence of 'hidden hunger' and obesity is discussed.DOI: http://dx.doi.org/10.7554/eLife.02245.001.

Vehicular technology has recently gained increasing popularity, and autonomous driving is a hot topic. To achieve safe and reliable intelligent transportation systems, accurate positioning technologies need to be built to factor in the different types of uncertainties such as pedestrian behavior, random objects, and types of roads and their settings. In this work, we look into the other domains and technologies required to build an autonomous vehicle and conduct a relevant literature analysis. In this work, we look into the current state of research and development in environment detection, pedestrian detection, path planning, motion control, and vehicle cybersecurity for autonomous vehicles. We aim to study the different proposed technologies and compare their approaches. For a car to become fully autonomous, these technologies need to be accurate enough to gain public trust and show immense accuracy in their approach to solving these problems. Public trust and perception of auto vehicles are also explored in this paper. By discussing the opportunities as well as the obstacles of autonomous driving technology, we aim to shed light on future possibilities.

BACKGROUND AND PURPOSE: Although there is some early evidence showing the value of repetitive transcranial magnetic stimulation (rTMS) in stroke rehabilitation, the therapeutic effect of high-frequency rTMS, along with the physiology of rTMS-induced corticomotor excitability supporting motor learning in stroke, has not been established. This study investigated high-frequency rTMS-induced cortical excitability and the associated motor skill acquisition in chronic stroke patients. METHODS: Fifteen patients with chronic hemiparetic stroke (13 men; mean age 53.5 years) practiced a complex, sequential finger motor task using their paretic fingers either after 10 Hz or sham rTMS over the contralateral primary motor cortex (M1). Both the changes in the behavior and corticomotor excitability before and after the intervention were examined by measuring the movement accuracy, the movement time, and the motor-evoked potential (MEP) amplitude. A separate repeated-measures ANOVA and correlation statistics were used to determine the main and interaction effects as well as relationship between the changes in the behavioral and corticomotor excitability. RESULTS: High-frequency rTMS resulted in a significantly larger increase in the MEP amplitude than the sham rTMS (P<0.01), and the plastic change was positively associated with an enhanced motor performance accuracy (P<0.05). CONCLUSIONS: High-frequency rTMS of the affected motor cortex can facilitate practice-dependent plasticity and improve the motor learning performance in chronic stroke victims.

Our previous studies have clearly shown that the angiogenic enzymes, matrix metalloproteinase (MMP) -2/9, are directly involved in human hepatic tumorigenesis and metastasis and suggest that the MMP-2/9 inhibitors, which have dual inhibitory activities on enzyme activity and transcription, represent the best candidates for achieving tumor regression. Many anti-cancer drugs have strong cellular cytotoxicity and side effects, indicating that strong anti-cancer drugs that have no or minimal cytotoxicity and side effects need to be developed. The specific aim of the present study was to develop powerful anti-cancer drugs with specific tumor regression and anti-metastatic potential having the dual inhibitory activities of specific MMP-2 and -9 enzyme activities and gene transcription at the molecular level. Caffeic acid (CA), a strong and selective MMP-9 activity and transcription inhibitor, was isolated from the plant Euonymus alatus and its derivative, caffeic acid phenethyl ester (CAPE), was synthesized. CA and CAPE selectively inhibited MMP-2 and -9 but not -1, -3, -7, or cathepsin K. Treatment of HepG2 cells with CA (100 microg/mL) and CAPE (5 microg/mL) suppressed phorbol 12-myristate 13-acetate (PMA) -induced MMP-9 expression by inhibiting the function of NF-kappaB, but not AP-1. We confirmed that CA and CAPE suppressed the growth of HepG2 tumor xenografts in nude mice in vivo. The subcutaneous and oral administrations of CA and CAPE significantly reduced the liver metastasis. These results confirm the therapeutic potential of the compounds and suggest that the anti-metastatic and anti-tumor effects of CA and CAPE are mediated through the selective suppression of MMP-9 enzyme activity and transcriptional down-regulation by the dual inhibition of NF-kappaB as well as MMP-9 catalytic activity.

There are many cyclic peptides with diverse biological activities, such as antibacterial activity, immunosuppressive activity, and anti-tumor activity, and so on. Encouraged by natural cyclic peptides with biological activity, efforts have been made to develop cyclic peptides with both genetic and synthetic methods. The genetic methods include phage display, intein-based cyclic peptides, and mRNA display. The synthetic methods involve individual synthesis, parallel synthesis, as well as split-and-pool synthesis. Recent development of cyclic peptide library based on split-and-pool synthesis allows on-bead screening, in-solution screening, and microarray screening of cyclic peptides for biological activity. Cyclic peptides will be useful as receptor agonist/antagonist, RNA binding molecule, enzyme inhibitor and so on, and more cyclic peptides will emerge as therapeutic agents and biochemical tools.

BACKGROUND: Several thyroid ultrasound (TUS) findings have been associated with an increased risk for thyroid cancer; however, there is no consensus as to the format and style for reporting the results of TUS. The objective of this study was to discover the features indicative of malignancy in thyroid nodules based on TUS, generate an equation using these features that would be predictive of malignancy in thyroid nodules, and stratify the results of this equation into TUS categories reflecting the probability of malignancy. METHODS: We obtained odds ratios of TUS findings indicative of malignancy and probability of malignancy for each nodule as determined by logistic regression analysis of ultrasound (US) findings in 1694 patients who had US-guided fine-needle aspiration biopsy. We then generated an equation to predict the probability of malignancy based on TUS and developed categories ranging from lowest to highest probability of malignancy. We evaluated the reliability of this equation and the categories using cytology and histopathology information regarding malignancy in the thyroid nodules. RESULTS: We characterized 12 aspects of thyroid nodules as seen on TUS and developed an equation to predict P(us), the probability of a nodule being malignant based on these US findings. The equation was P(us) = 1/(1 + e(-z)), where e is the mathematical constant 2.71828 and z is the logit of malignant thyroid nodule. P(us) was stratified into five categories based on the probability of a nodule being malignant as indicated by the findings (TUS 1, benign; TUS 2, probably benign; TUS 3, indeterminate; TUS 4, probably malignant; TUS 5, malignant). There was a significant correlation between the cytological category and the TUS 1 through TUS 5 categories (r = 0.491, p < 0.001). CONCLUSIONS: We propose an equation to predict the probability of malignancy in thyroid nodules based on 12 features of thyroid nodules as noted on TUS. This equation, and the stratification of its results into categories, should be useful in reporting the findings of US for thyroid nodules and in guiding management decisions.

Increasing globalization has created tremendous opportunities and challenges for organizations and societies. Consequently, a broad range of information technologies to better support the collaboration of diverse, and increasingly distributed, sets of participants is ever more utilized. Arguably, the success of such technology-mediated collaboration is dependent upon the quality of each individual's contributions; however, although individuals' motivations to do their best could be significantly influenced by the design of a system's human–computer interface, this area has received little attention within the context of group collaboration environments. We fill this gap by integrating research from human–computer interaction, motivation, and technology-supported group work to theoretically derive mechanisms for increasing each individual's motivation within a collective setting. Specifically, we manipulate the interface of a computer-mediated idea generation system (a widely used collaboration tool) to enhance the system's motivational affordance, i.e., the system's properties that fulfill users' motivational needs. Results from two studies demonstrate that by embedding the theoretically derived mechanisms “providing feedback” and “designing for optimal challenge” into the collaboration environment, significant performance gains were realized. The results suggest that even slight manipulations of the human–computer interface can contribute significantly to the successful design of a wide variety of group collaboration environments.

Bo-Yeon Kim, Seon Mee Kang, Jee-Hyun Kang, Seo Young Kang, Kyoung Kon Kim, Kyoung-Bae Kim, Bomtaeck Kim, Seung Jun Kim, Yang-Hyun Kim, Jung-Hwan Kim, Jae Hyun Kim, Eun Mi Kim, Ga Eun Nam, Ji Yeon Park, Jang Won Son, Yun-A Shin, Hye-Jung Shin, Tae Jung Oh, Hyug Lee, Eon-Ju Jeon, Sochung Chung, Yong Hee Hong, Chong Hwa Kim; Committee of Clinical Practice Guidelines, Korean Society for the Study of Obesity (KSSO). J Obes Metab Syndr 2021;30:81-92. https://doi.org/10.7570/jomes21022

Abstract With the increasing advance of computer and information technologies, numerous research papers have been published online as well as offline, and as new research fields have been continuingly created, users have a lot of trouble in finding and categorizing their interesting research papers. In order to overcome the limitations, this paper proposes a research paper classification system that can cluster research papers into the meaningful class in which papers are very likely to have similar subjects. The proposed system extracts representative keywords from the abstracts of each paper and topics by Latent Dirichlet allocation (LDA) scheme. Then, the K-means clustering algorithm is applied to classify the whole papers into research papers with similar subjects, based on the Term frequency-inverse document frequency (TF-IDF) values of each paper.

Bone marrow‐derived mesenchymal stem cell (BM‐MSC) transplantation has been suggested as an effective therapy for liver cirrhosis. The efficacy and safety of autologous BM‐MSC transplantation in the treatment of alcoholic cirrhosis were investigated. Seventy‐two patients with baseline biopsy‐proven alcoholic cirrhosis who had been alcohol‐abstinent for more than 6 months underwent a multicenter, randomized, open‐label, phase 2 trial. Patients were randomly assigned to three groups: one control group and two autologous BM‐MSC groups that underwent either one‐time or two‐time hepatic arterial injections of 5 × 10 7 BM‐MSCs 30 days after BM aspiration. A follow‐up biopsy was performed 6 months after enrollment, and adverse events were monitored for 12 months. The primary endpoint was improvement in fibrosis quantification based on picrosirius red staining. The secondary endpoints included liver function tests, Child‐Pugh score, and Model for End‐stage Liver Disease score. Outcomes were analyzed by per‐protocol analysis. In terms of fibrosis quantification (before versus after), the one‐time and two‐time BM‐MSC groups were associated with 25% (19.5 ± 9.5% versus 14.5 ± 7.1%) and 37% (21.1 ± 8.9% versus 13.2 ± 6.7%) reductions in the proportion of collagen, respectively ( P &lt; 0.001). In the intergroup comparison, two‐time BM‐MSC transplantation in comparison with one‐time BM‐MSC transplantation was not associated with improved results in fibrosis quantification ( P &gt; 0.05). The Child‐Pugh scores of both BM‐MSC groups (one‐time 7.6 ± 1.0 versus 6.3 ± 1.3 and two‐time 7.8 ± 1.2 versus 6.8 ± 1.6) were also significantly improved following BM‐MSC transplantation ( P &lt; 0.05). The proportion of patients with adverse events did not differ among the three groups. Conclusion : Autologous BM‐MSC transplantation safely improved histologic fibrosis and liver function in patients with alcoholic cirrhosis. (H epatology 2016;64:2185‐2197)