Gastric cancer (GC) is the fourth most prevalant cancer and the second leading cause of cancer-related mortality worldwide. As in other cancers gastric carcinogenesis is multifactorial involving environmental, genetic and epigenetic components. Epigenetic silencing due to hypermethylation of tumour suppressor genes is one of the key events in gastric carcinogenesis. This study was aimed to analyse the hypermethylation status of the E-Cadherin (CDH1) gene promoter in GCs in the ethnic Kashmiri population. In this study a total of 80 GC patients were recruited. Hypermethylation in tumour tissue was detected by methylation specific PCR (MS-PCR). Hypermethylation of CDH1 promoter was observed in 52 (65%) of gastric carcinoma cases which was significantly much higher than adjacent normal tissue [$p{\leq}0.0001$]. Further the frequency of CDH1 promoter methylation was significantly different with intestinal and diffuse types of gastric cancer [55.7% vs 82.1%; p<0.05]. Moreover females and cases with lymph node invasion had higher frequencies of CDH1 hypermethylation [$P{\leq}0.05$]. Thus the current data indicate a vital role of epigenetic alteration of CDH1 in the causation and development of gastric cancer, particularly of diffuse type, in our population.
Incident investigation is one of the most important processes among various other safety management methods to prevent industrial accidents. Finding the root causes of accidents, eliminating hazards, and improving safety are the most important purposes of investigating accidents. During the investigation process, root cause analysis (RCA) techniques are used to effectively identify RCA. Over the past few decades, over 30 RCA methods have been developed. These techniques are being widely used in some industries, such as the nuclear and aircraft industries; however, most of the RCA techniques require professional knowledge and special training, making it difficult for safety managers in their respective fields to understand and apply them. Therefore, managers of general industrial sites are rarely present at the scene of actual accident investigations, and they cannot contribute much to the purpose and effectiveness of these investigations. In this study, to address these issues, we developed an RCA technique to facilitate root cause investigation of accidents in real-world industrial sites. To develop new techniques, Systematic Cause Analysis Technique (SCAT), one of the RCA techniques, was used to investigate incidents in the enterprise over three years. We also utilized feature analysis and other papers from existing RCA techniques. To verify its effectiveness, the technique proposed was also applied to the accident case. The technique developed can easily identify and analyze the root cause of an accident and help industrial managers. It can also identify the root cause category where accidents are concentrated and use this data to establish guidelines for preventing future accidents and, thus, focus on prioritizing improvement initiatives.
Objectives The purpose of this study is to provide data for development of the korean medicine (KM) clinical practice guidelines (CPG) for growth disorder (GD) by identifying the awareness and knowledge needs of KM doctors (KMD) through online survey. Methods Survey questionnaire was produced by referring to the previous recognition survey studies for clinical KMDs. The survey questionnaire was composed 18 questions regarding the current status of clinical care for GD, clinician's knowledge level about GD, and other details that clinicians use during practice. The survey was conducted from January 2021 to March 2021. An online survey was conducted on 101 KMDs from the association of pediatrics of KM. Results According to the survey, 96 respondents (40.3%) said the causation of GD without growth hormone deficiency needs to be included in CPG. 96 (23.5%) of the respondents wishes to utilize percentile in diagnosis and evaluation of the growth assessment. 24.7% of the clinicians were using the herbal medicine treatment. Currently, when treating with KM for GD, herbal medicine (100%) is the most widely used, followed by acupuncture (77.6%), and moxibustion (36.7%). In terms of a complex treatment, growth therapy efficacy (26.8%) is shown to be the most important factor to consider and needed to be included in CPG for the complex treatment, and diet (22.3%) is also considered to be important in GD. Conclusions In this study, we were able to understand the clinical KMDs' perception of GD, knowledge level, and the requirements in the CPG. The results of this study will provide the basic data for development of CPG for GD.
Cushman, Taylor R.;Haque, Waqar;Menon, Hari;Rusthoven, Chad G.;Butler, E. Brian;Teh, Bin S.;Verma, Vivek
Journal of Gynecologic Oncology
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v.29
no.6
/
pp.97.1-97.12
/
2018
Objective: Women with cervical cancer (CC) found to have positive surgical margins, positive lymph nodes, and/or parametrial invasion receive a survival benefit from postoperative chemoradiotherapy (CRT) vs. radiation therapy (RT) alone. However, older women may not benefit to the same extent, as they are at increased risk of death from non-oncologic causes as well as toxicities from oncologic treatments. This study sought to evaluate whether there was a survival benefit of CRT over RT in elderly patients with cervical cancer. Methods: The National Cancer Database was queried for patients ${\geq}70$ years old with newly diagnosed IA2, IB, or IIA CC and positive margins, parametrial invasion, and/or positive nodes on surgical resection. Statistics included logistic regression, Kaplan-Meier overall survival (OS), and Cox proportional hazards modeling analyses. Results: Altogether, 166 patients met inclusion criteria; 62 (37%) underwent postoperative RT and 104 (63%) underwent postoperative CRT. Younger patients and those living in areas of higher income were less likely to receive CRT, while parametrial invasion and nodal involvement were associated with an increased likelihood (p<0.05 for all). There were no OS differences by treatment type. Subgroup analysis by number of risk factors, as well as each of the 3 risk factors separately, also did not reveal any OS differences between cohorts. Conclusion: In the largest such study to date, older women with postoperative risk factor(s) receiving RT alone experienced similar survival as those undergoing CRT. Although causation is not implied, careful patient selection is paramount to balance treatment-related toxicity risks with theoretical outcome benefits.
Journal of the Korea Academia-Industrial cooperation Society
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v.22
no.1
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pp.531-542
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2021
This study was undertaken for identifying ways to positively resolve problems associated with perceived overqualification from the perspective of job crafting, which is highlighted as a social issue in the labor market. We hypothesized the mediating role of job crafting in order to uncover the questions regarding when and how perceived overqualification associates with an employee's organizational commitment. Autoregressive cross-lagged models were applied to the longitudinal data gathered from 263 full-time employees across 3 waves over 9 months. Our results demonstrate positive and significant cross-lagged effect of perceived overqualification on job crafting and organizational commitment. However, the cross-lagged effect of job crafting on perceived overqualification was found to be insignificant, but was significant for organizational commitment. There were no other indications of reverse causation effects. Our data indicates that job crafting longitudinally mediates the relation between perceived overqualification and organizational commitment. These findings offer a meaningful implication that employees who perceive themselves to be overqualified should be given an opportunity to craft their own jobs.
MANSOOR, Abdul;HUSSAIN, Syed Tahir;RAIS, Syed Imran;BASHIR, Malik Fahim;TARIQ, Yasir Bin;KAUSAR, Maria
The Journal of Asian Finance, Economics and Business
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v.9
no.2
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pp.61-69
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2022
The study intends to investigate a short-run and a long-run causality among money, income, and prices in the Keynesian and Monetarists framework. This study emphasizes the importance of unrecorded money, which exists alongside legal monetary assets and plays a dual function in determining economic prosperity. The underground economy, which is a hidden component of aggregate economic activity, is determined using Tanzi's monetary approach (Tanzi, 1980). This research uses a time series of annual data from 1990 to 2019 for this purpose. The data is extracted from the World Bank database for the monetary and development indicators. The study keeping in view the trending nature in data follows a unit root testing followed by the Autoregressive Distributive Lag Model (ARDL) to assess the long and short-run dynamics of causality among the variables. In both the pricing and income equations, the study finds a significant level link among the variables; however, there is no evidence of the presence of a level association in the money equation. The short-run causal relationship provides evidence of bi-directional causation between the supply of money and national income. The outcome of this study advise that though the view point of both the Monetarist and Keynesian school holds in both short and long run, however, in Pakistan only the Monetarists' role of money supply and income holds in Pakistan. This evidence would be of precise interest to the policy-makers.
Purpose: The purpose of this study was verifying factors that affect to intention to use AI financial services and finding a way of building an user oriented AI ecology. Methods: This study used the UTAUT (Unified Theory of Acceptance and Use of Technology) model with independent variables such as performance expectancy, effort expectancy, social influence, facilitating conditions, trust, personal innovativeness and AI understanding as moderating variable. The data was collected through online & offline survey with questionnaire from 330 financial customers. Results: As a result, the analysis suggested that the performance expectancy, social influence, facilitating conditions, personal innovativeness are statistically significant to the intention to use AI. It was also found that AI knowledge of users differently influence the intention to use through the moderating effect on the facilitating conditions. Conclusion: Performance expectancy, social influence, facilitating conditions, personal innovativeness have positive causation to the intention to use in AI financial service. On the facilitating conditions, unlike other variables, it was found that the user's intention to use was different by the level of AI understanding. It means that customers could have the strong intention to use AI even though they don't have enough pieces of knowledge on the factors. Customers seem to be of recognition that the technology has certain benefits for themselves. The facilitating factors are significantly affected by AI understanding and differently effect on the intention to use AI.
This research examined the relation between personal history of residential moves and psychological independence. In particular, this research tested how actual self-importance (vis-a-vis perceived social importance) of values (Study 1) and preference for uniqueness (Study 2) would vary as a function of past experience of moving. The results showed that personal history of residential moves was positively linked to actual self-importance of individualistic values and perceived social importance of collectivistic values. In addition, the results demonstrated that individuals with frequent residential moves generally showed a greater liking for uniqueness. The implications of these results for the direction of causation between residential mobility and psychological independence are discussed and suggestions for future research are made.
Purpose - The purpose of this study is to examine the gravity model commonly used for demand forecasting upon the implementation of new tourist facilities and analyze the main causation of forecasting errors to provide a suggestion on how to improve. Design/methodology/approach - This study first measured the errors in predicted values derived from past feasibility study reports by examining the cases of five national science museums. Next, to improve the predictive accuracy of the gravity model, the study identified the five most likely issues contributing to errors, applied modified values, and recalculated. The potential for improvement was then evaluated through a comparison of forecasting errors. Findings - First, among the five science museums with very similar characteristics, there was no clear indication of a decrease in the number of visitors to existing facilities due to the introduction of new facilities. Second, representing the attractiveness of tourist facilities using the facility size ratio can lead to significant prediction errors. Third, the impact of distance on demand can vary depending on the characteristics of the facility and the conditions of the area where the facility is located. Fourth, if the distance value is below 1, it is necessary to limit the range of that value to avoid having an excessively small value. Fifth, depending on the type of population data used, prediction results may vary, so it is necessary to use population data suitable for each latent market instead of simply using overall population data. Finally, if a clear trend is anticipated in a certain type of tourist behavior, incorporating this trend into the predicted values could help reduce prediction errors. Research implications or Originality - This study identified the key factors causing prediction errors by using national science museums as cases and proposed directions for improvement. Additionally, suggestions were made to apply the model more flexibly to enhance predictive accuracy. Since reducing prediction errors contributes to increased reliability of analytical results, the findings of this study are expected to contribute to policy decisions handled with more accurate information when running feasibility analyses.
The Journal of the Convergence on Culture Technology
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v.10
no.3
/
pp.155-164
/
2024
This study examines whether startup firms start with the resources they already have and expand the resources they can mobilize in the process of business management (Effectuation Model) using public data provided by the government. The results of the study show that the Effectuation Model can partially explain the behavior of early-stage startup firms. Therefore, in terms of policy implications based on these findings, government policies for entrepreneurship should not be based on the selection of companies based on sophisticated business models and hypothetical profit models, but rather on a system that actively supports entrepreneurship in areas that are challenging, even if they seem somewhat reckless at the moment, or that best match the entrepreneur's knowledge. Next, in order to actively spread entrepreneurship, it is necessary to spread business history or entrepreneurial experience. To this end, it is necessary to drastically change the current financial system for startups, where the founder bears all the financial risk, and to more actively consider ways to reduce the risk of startups by allowing society and the financial system to share some of the risk of startups.
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