Electricity Generating Authority Of Thailand Research Articles

The association between interdental cleaning and periodontitis in an urban Thai adult cohort: a cross-sectional study.

Plaque biofilm is a major etiologic factor of periodontitis, and its effective removal prevents or ameliorates the disease. However, toothbrushing alone does not sufficiently clean the interdental area, and additional interdental cleaning is required to completely remove the plaque from this locale. This cross-sectional study aimed to assess the association of interdental cleaning on the prevalence of periodontitis in a large urban Thai adult cohort. Interdental cleaning data were retrieved from a dental survey of 1,743 employees of the Electricity Generating Authority of Thailand (EGAT) in 2019. The Centers for Disease Control and Prevention/American Association of Periodontology (CDC/AAP) periodontal case definitions were applied. The participants were subdivided into two groups as those with or without periodontitis depending on their oral health status assessed by calibrated professional examiners. The proportion of subjects who performed interdental cleaning was assessed through a self-reported questionnaire by frequency (daily/ ≥ 1 per week/ none) and profile (correct/ incorrect) of interdental cleaning. Then, the association between interdental cleaning and periodontitis was calculated using logistic regression analysis controlling for the common risk factors of periodontitis such as age, sex, education, smoking, and diabetes. Participants who performed interdental cleaning on a daily basis and ≥ 1 per week were 27.5% (95% CI: 25.4, 29.6) and 29.1% (95% CI: 27.0, 31.3), respectively while the remainder did not practice. Of those who used interdental cleaning, about one-half focused on sites with food impaction. There was a significant 44% lower prevalence of periodontitis (adjusted odds ratio of 0.56 (95%CI: 0.40, 0.79) in the cohort with a frequent and correct group. Our data indicate an inverse association between interdental cleaning and periodontitis, particularly in those who routinely adhered to it. Regular interdental cleaning is likely to have a salutary effect on oral health. The study was registered retrospectively in Thai Clinical Trials Registry, Registration number: TCTR20240817005, on 17 Aug 2024 ( https://www.thaiclinicaltrials.org ).

A comprehensive Thai pharmacogenomics database (TPGxD-1): Phenotype prediction and variants identification in 942 whole-genome sequencing data.

Computational methods analyze genomic data to identify genetic variants linked to drug responses, thereby guiding personalized medicine. This study analyzed 942 whole-genome sequences from the Electricity Generating Authority of Thailand (EGAT) cohort to establish a population-specific pharmacogenomic database (TPGxD-1) in the Thai population. Sentieon (version 201808.08) implemented the GATK best workflow practice for variant calling. We then annotated variant call format (VCF) files using Golden Helix VarSeq 2.5.0 and employed Stargazer v2.0.2 for star allele analysis. The analysis of 63 very important pharmacogenes (VIPGx) reveals 85,566 variants, including 13,532 novel discoveries. Notably, we identified 464 known PGx variants and 275 clinically relevant novel variants. The phenotypic prediction of 15 VIPGx demonstrated a varied metabolic profile for the Thai population. Genes like CYP2C9 (9%), CYP3A5 (45.2%), CYP2B6 (9.4%), NUDT15 (15%), CYP2D6 (47%) and CYP2C19 (43%) showed a high number of intermediate metabolizers; CYP3A5 (41%), and CYP2C19 (9.9%) showed more poor metabolizers. CYP1A2 (52.7%) and CYP2B6 (7.6%) were found to have a higher number of ultra-metabolizers. The functional prediction of the remaining 10 VIPGx genes reveals a high frequency of decreased functional alleles in SULT1A1 (12%), NAT2 (84%), and G6PD (12%). SLCO1B1 reports 20% poor functional alleles, while PTGIS (42%), SLCO1B1 (4%), and TPMT (5.96%) showed increased functional alleles. This study discovered new variants and alleles in the 63 VIPGx genes among the Thai population, offering insights into advancing clinical pharmacogenomics (PGx). However, further validation is needed using other computational and genotyping methods.

A Deep Learning Approach for Short-Term Electricity Demand Forecasting: Analysis of Thailand Data

Accurate electricity demand forecasting serves as a vital planning tool, enhancing the reliability of management decisions. Apart from that, achieving these aims, particularly in managing peak demand, faces challenges due to the industry’s volatility and the ongoing increase in residential energy use. Our research suggests that employing deep learning algorithms, such as recurrent neural networks (RNN), long short-term memory (LSTM), and gated recurrent units (GRU), holds promise for the accurate forecasting of electrical energy demand in time series data. This paper presents the construction and testing of three deep learning models across three separate scenarios. Scenario 1 involves utilizing data from all-day demand. In Scenario 2, only weekday data are considered. Scenario 3 uses data from non-working days (Saturdays, Sundays, and holidays). The models underwent training and testing across a wide range of alternative hyperparameters to determine the optimal configuration. The proposed model’s validation involved utilizing a dataset comprising half-hourly electrical energy demand data spanning seven years from the Electricity Generating Authority of Thailand (EGAT). In terms of model performance, we determined that the RNN-GRU model performed better when the dataset was substantial, especially in scenarios 1 and 2. On the other hand, the RNN-LSTM model is excellent in Scenario 3. Specifically, the RNN-GRU model achieved an MAE (mean absolute error) of 214.79 MW and an MAPE (mean absolute percentage error) of 2.08% for Scenario 1, and an MAE of 181.63 MW and MAPE of 1.89% for Scenario 2. Conversely, the RNN-LSTM model obtained an MAE of 226.76 MW and an MAPE of 2.13% for Scenario 3. Furthermore, given the expanded dataset in Scenario 3, we can anticipate even higher precision in the results.

Economic Pricing in Peer-to-Peer Electrical Trading for a Sustainable Electricity Supply Chain Industry in Thailand

The state-owned power Electricity Generating Authority of Thailand (EGAT), a monopoly market in charge of producing, distributing, and wholesaling power, is the focal point of Thailand’s electricity market. Although the government has encouraged people to install on-grid solar panels to sell electricity as producers and retail consumers, the price mechanism, i.e., purchasing price and selling prices, is still unilaterally determined by the government. Therefore, we are interested in studying the case where blockchain can be used as a free trading platform. Without involving buying or selling from the government, this research presents a model of fully traded price mechanisms. Based on the study results of the double auction system, data on buying and selling prices of electrical energy in Thailand were used as the initial data for the electricity peer-to-peer free-trading model. Then, information was obtained to analyze the trading price trends by using the law of demand and supply in addition to the principle of the bipartite graph. The price trend results agree well with those of price equilibrium equations. Therefore, we firmly believe that the model we offer can be traded in a closed system of free-trade platforms. In addition, the players in the system can help to determine the price trend that will occur according to various parameters and will cause true fairness in the sustainable electricity supply chain industry in Thailand.

DECARBONIZING A THAI COAL POWER PLANT: EFFECT OF FLUE GAS LOADS ON CARBON CAPTURE PERFORMANCE AND ECONOMICS

Abstract: The objectives of this study are to evaluate the technical and cost implications of retrofitting post-combustion Carbon Capture and Storage (CCS) in existing coal-fired power plants in Thailand, with a special focus on the Mae Moh plant managed by the Electricity Generating Authority of Thailand (EGAT). We undertake a detailed analysis using AspenPlus simulation models to determine the optimum capture cost per ton of CO2 and to examine the effects of various flue gas loads on CO2 capture performance and cost-effectiveness. The research reveals a key operational insight: as the flow rate of flue gas increases, the cost to capture a ton of CO2 decreases, indicating economies of scale in CCS operations. Furthermore, the study explores the potential for integrating solar photovoltaic (PV) technology as a renewable energy source, which shows promise in lowering Thailand's power sector emissions and operational costs. By comparing the levelized cost of electricity (LCOE) for solar PV against conventional coal-fired power generation and considering the country's favorable geographic and climatic conditions, solar PV emerges as an economically viable and environmentally sustainable alternative. The findings of this research aim to inform strategic energy policy decisions in Thailand, advocating for a transition to more sustainable energy systems and emphasizing the balance between environmental responsibility and economic feasibility.

245-OR: Impaired Mitochondrial Respiration in Peripheral Blood Mononuclear Cells Is Associated with Increased Obesity Classified by Waist-to-Hip Ratio in Nondiabetes EGAT Population

This study aimed to determine the impact of waist-to-hip ratio (WHR)-classified obesity and diabetes (DM) status on mitochondrial respiration in peripheral blood mononuclear cells (PBMCs) using a large cohort from the Electricity Generation Authority of Thailand (EGAT) during 2017-2018. The 1954 participants were included in this study with an average age of 67.1±7.7 years old. The mitochondrial respiration in PBMCs obtained from fresh blood samples was analyzed by the Seahorse Flux Analyzer. The participants were classified based on DM status and WHR including 1) non-DM non-obese, 2) non-DM obese, 3) DM non-obese and 4) DM obese. We found that the non-DM obese group had lower basal respiration (BR), maximal respiration, spare respiratory capacity (SRC), and proton leak (PL), compared to those of the non-DM non-obese group (Figure 1). The BR, SRC, and PL of non-DM obese group were not significantly different from those of the DM group with or without adjusting with age. All of these findings suggest that WHR-classified obesity in people with non-DM is associated with impaired mitochondrial respiration in PBMCs at a level comparable to that in people with DM. Thus, not only DM, but also obesity, may play an important role on impaired mitochondrial respiration in PBMCs. Disclosure T.Attachaipanich: None. S.C.Chattipakorn: None. S.Sriwichaiin: None. N.Apaijai: None. S.Kerdphoo: None. N.Thongmung: None. P.Vathesatogkit: None. C.Kitiyakara: None. P.Sritara: None. N.Chattipakorn: None.

Residential greenness and kidney function: A cohort study of Thai employees.

Higher residential greenness is associated with a lower risk of chronic kidney disease, but evidence on the association between greenness exposure and kidney function has not been conducted. Using cohort data from Electricity Generating Authority of Thailand (EGAT) employees, we investigated the association between long-term exposure to greenness and kidney function using estimated glomerular filtration rate (eGFR) in Bangkok Metropolitan Region (BMR), Thailand. We analyzed data from 2022 EGAT workers (aged 25-55 years at baseline) from 2009 to 2019. The level of greenness was calculated using the satellite-derived Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI). From 2008 to 2019, the average concentration of each air pollutant (PM10, O3, NO2, SO2, and CO) at the sub-district level in BMR was generated using the Kriging method. Long-term exposure for each participant was defined as the 1-year average concentrations before the date of the physical examination in 2009, 2014, and 2019. We employed linear mixed effects models to evaluate associations of NDVI and EVI with eGFR. The robustness of the results was also tested by including air pollutants in the models. After relevant confounders were controlled, the interquartile range increase in NDVI was associated with higher eGFR [1.03% (95%CI: 0.33, 1.74)]. After PM10 and SO2 were included in the models, the associations between NDVI and eGFR became weaker. The additions of O3, NO2, and CO strengthened the associations between them. In contrast, we did not find any association between EVI and eGFR. In conclusion, there was a positive association between NDVI and eGFR, but not for EVI. Air pollutants had a significant impact on the relationship between NDVI and eGFR. Additional research is needed to duplicate this result in various settings and populations to confirm our findings.

A phase diagram approach to the detection and location of faulty capacitor units in A 115-kV capacitor bank based on unbalanced current arguments

The protection of traditional high voltage capacitor banks relies on an unbalance relay which operates when an internal fuse is blown. However, the unbalance relay cannot indicate cause or position of the fault. Thus, an operator wastes time and human resources investigating the fault issues. To address this issue, a method to locate the fault position in a capacitor bank is developed in this study. The study was simulated by using PSCAD software and modeled on the 115-kV system of the Electricity Generating Authority of Thailand (EGAT). Case studies involving faults with varied phases, side and branch connections, row connections, and inception angles were considered. Moreover, the magnitude and argument of the current phase and unbalanced current were analyzed to identify the fault location in a capacitor bank. The performance of the proposed method was verified via comparison with that of traditional methods and the results of laboratory experiments. In addition, various voltage systems were observed to verify the flexibility and accuracy of the proposed method. The results demonstrate that the proposed method was more efficient than traditional methods at locating the fault position in a capacitor bank.

Long-term associations of air pollution exposure with liver enzymes among adult employees of the Electricity Generating Authority of Thailand: A longitudinal cohort study

Exposure to particulate air pollution may induce hepatotoxic effects via low-grade inflammation. However, only a few longitudinal epidemiological studies have investigated the long-term effects of air pollution on liver enzyme levels. The present study examined associations between long-term air pollution exposure and serum liver enzymes [alkaline phosphatase (ALP), aspartate aminotransferase (AST), alanine aminotransferase (ALT)] in employees of the Electricity Generating Authority of Thailand (EGAT) in Thailand's Bangkok Metropolitan Region (BMR). We conducted secondary analyses using the data obtained from 2022 subjects (mean age, 41.2 years as of 2009) of the EGAT3 cohort study (2009–2019). The daily mean concentration of each air pollutant (PM10, O3, NO2, SO2, and CO) was estimated at the sub-district level in BMR from 2008 to 2019 using the Kriging approach. Long-term exposure for each subject was defined as the 1-year average concentrations before the date of the physical examination in 2009, 2014, and 2019. We used linear mixed effects models to assess associations between air pollution and serum liver enzymes. Interquartile range increases in PM10 and O3 were related to decreased ALP [-2.4% (95%CI: -3.0, −1.9) and −6.6% (−7.3, −5.9), respectively] after potential confounders were adjusted. Positive associations between NO2, SO2, and CO with ALP were found [5.7% (4.8, 6.5), 4.5% (4.0, 5.0), and 0.8 (0.3, 1.4), respectively]. Elevated AST was also associated with higher PM10 [1.7% (0.8, 2.5)] and O3 [5.7% (4.5, 6.9)]. However, AST was negatively associated with NO2 [-2.9% (−4.0, −1.8)] and SO2 [-1.7% (−2.3, −1.1)]. In contrast to other air pollutants, we only observed a positive association between O3 and ALT [3.4% (1.5, 5.3)]. The alteration in liver enzyme levels was significantly associated with long-term exposure to air pollution, which may raise the possibility of hepatocellular damage.

Association of body mass index and dietary intake with mild cognitive impairment and dementia: a retrospective cohort study

BackgroundThe prevalence of cognitive impairment in older adults is gradually increasing, and this is leading to many adverse outcomes. Common causes of cognitive impairment in advancing age are mild cognitive impairment (MCI) and dementia. However, how the nutritional status and nutrient intake are related to MCI and dementia is controversial. Therefore, we aimed to evaluate the association of body mass index (BMI) and dietary intake with the risk of MCI and dementia.MethodsThis retrospective cohort study involved 821 participants aged ≥ 50 years from a previous population-based cohort study: the Electricity Generating Authority of Thailand (EGAT) study in 2013–2014 (baseline) and 2018–2019 (follow-up). Dietary intake was recorded using a 12-month self-reported food frequency questionnaire. MCI and dementia were diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria using the Montreal Cognitive Assessment with ADL and the Kessler Psychological Distress Scale (K10) at study entry and at the 5-year follow-up.ResultsAmong the 821 participants, the mean age was 60.0 ± 4.3 years, and the incidence rate of MCI and dementia was 42.5 and 11.2 per 1,000 person-years, respectively. The rate of MCI and dementia was higher in participants aged ≥ 60 years and with an education level of < 7 years. The rate of MCI was also higher in those with a BMI of ≥ 25 kg/m2 and type 2 diabetes. Compared to BMI 18.5–22.9 kg/m2, BMI of ≥ 25 kg/m2 (odds ratio 1.91 [95% confidence interval, 1.12–3.26], p < 0.001) was associated with an increased risk of MCI after adjusted for age, education level, and type 2 diabetes. Regarding dietary intake, fresh red meat consumption was inversely associated with the risk of MCI (p = 0.037) and dementia (p = 0.011) after adjusting for age, education level, type 2 diabetes, and BMI.ConclusionObesity was associated with a greater risk of MCI. Moreover, low consumption of fresh red meat could be a risk factor for MCI and dementia. Further studies are required to confirm and explain these findings.

Influence of green transformational leadership on the workplace pro-environment behavior

Today, environmental problems are worsening, greenhouse gas emissions are increasing, and natural resources are depleting. Solving these problems requires the efforts of everyone in the organization. This study aims to analyze the impact of green transformational leadership on pro-environmental behavior in the workplace. Specifically, the main hypothesis is that green transformational leadership positively influences workplace pro-environment behavior. Two other pathways are also proposed. The relationship can be mediated through green mindfulness and green self-efficacy. The method used in this study is a questionnaire, and data were collected from 163 respondents who work for the Electricity Generation Authority of Thailand. An integrated model containing the hypothesized structure was then tested with structural equation modeling. The results showed that green transformational leadership positively impacted workplace pro-environment behaviors and that this relationship was mediated by green mindfulness. However, green self-efficacy did not mediate between green transformational leadership and workplace pro-environment behavior as there was no relationship between self-efficacy and workplace pro-environment behavior. Rather, green self-efficacy influences workplace pro-environment behavior through green mindfulness. The revised model provides some practical implications for corporations that intend to promote workplace pro-environment behavior. First, green transformational leadership serves as an important factor as it has both direct and indirect impacts on workplace pro-environment behavior. Second, green mindfulness is an important mediator for two indirect effects upon workplace pro-environment behavior. These two factors are key in motivating staff members to work environmentally.

Validity of Simple Self-Reported Periodontal Status Questions

The aim of this research was to evaluate the validity of the questions developed by Thai periodontists on self-reported periodontal status and symptoms in identifying severe periodontitis amongst adults in Thailand. Registered Electricity Generating Authority of Thailand (EGAT) employees completed medical examinations and full-mouth periodontal examinations. They also were interviewed using a self-reported questionnaire that was developed by Thai periodontists. The questions pertained to their periodontal status and symptoms comprising swollen gums, bad breath, loose teeth, bleeding on brushing, painful gums, and pus or abscesses. The participants were categorised as having nonsevere and severe periodontitis according to the Centers for Disease Control and Prevention in partnership with the American Academy of Periodontology (CDC/AAP) case definitions. Self-reported periodontal status and symptom results were compared with actual periodontal status. The area under the receiver operating characteristic curve (AUROCC), sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated. A total of 1393 EGAT employees participated in this study. The questions on self-reported periodontal status and all symptoms poorly identified patients with severe periodontitis, with an AUROCC of 0.52 to 0.60. The sensitivity was 5.0% to 40.2%; however, the specificity was good, at 73.2% to 99.1%. The validity of the self-reported questions was comparable amongst the sex, education, and income subgroups. This study demonstrated that self-reported periodontal status and symptoms were inadequate in identifying patients with severe periodontal disease.

Clinical significance of undetectable high sensitivity cardiac troponin I (hs-TnI) in Thai individuals with low cardiovascular risk

Abstract Introduction The long term prognosis of individuals who has undetectable hs-TnI is poorly defined in low cardiovascular risk. We aim to examine whether undetectable hs-TnI individuals have better cardiovascular outcomes in low cardiovascular risk population. Methods Data of low cardiovascular risk population (&amp;lt;7.5%) who has no established of atherosclerosis cardiovascular disease (ASCVD) was derived from the Electricity Generating Authority of Thailand (EGAT) study in 2007–2009 survey. High sensitivity cardiac troponin I was measured by using the Abbott ARCHITECT i2000 SR assay. We categorized level of hs-TnI into undetectable hs-TnI (&amp;lt;1.9 ng/L), low hs-TnI, intermediate and more hsTnI by gendered specific cut-off. The low cardiovascular risk population was classified into extremely low risk (&amp;lt;5%) and low risk (5–7.5%). Major cardiovascular event (MACE) and all-cause mortality were collected until 31st December 2019. Survival analysis and subgroup analysis were performed. Results A total of 3,442 participants were eligible. Mean age was 43.6 years-old, 65.5% male, hs-TnI was detected 79.8%, median hs-cTnI was 2.6 ng/L (2,3.6). During median time followed-up 10.3 years, 52 events (1.5%) of MACE and 60 events (1.7%) of all-cause mortality occurred. After adjusted for conventional risk factors, hs-cTnI significantly associated with incidence of MACE (HR 1.03 95% CI 1.02–1.04, p-value &amp;lt;0.001). Compared with intermediate and more hs-TnI group, undetectable hs-TnI and low hs-TnI had 79% and 52% lower incidence of MACE (HR 0.21, 95% CI (0.05–0.79) and HR 0.48, 95% CI (0.23–1.0), p-value for trend 0.04. Subgroup analysis, incidence of MACE remained higher either extremely low or low CV risk compared with those undetectable hs-TnI. (P for interact 0.83) Conclusion Among individuals with low cardiovascular risk, hs-TnI testing can provide risk prognostication. Undetectable hs-TnI could be as a negative risk marker for adverse cardiovascular events. Funding Acknowledgement Type of funding sources: None.

Effects of Conditional Changes on High-Voltage Direct Current Transmission Line Characteristic

The high-voltage direct current (HVDC) transmission system, which links the Gurun Substation of the National Electric Authority of Malaysia (Tenaga Nasional Berhad, TNB) with the Khlong Ngae Station of the Electricity Generating Authority of Thailand (EGAT), has been extensively researched to achieve the highest quality because it is the largest of its kind in Thailand, and there is a plant to expand its transmission power. However, the impact on the whole system is under-researched. To study and develop this system, the HVDC transmission line is modelled with the MATLAB/Simulink program and a laboratory setup to investigate the effect of transmission line distance, load power, and voltage on power loss, voltage drop, and waveform. The HVDC transmission line parameters are calculated from the actual transmission line parameters and converted to the simulation model parameters using the per-unit method. The model is verified and tested by the simulation program before creating the experimental setup. The simulation and experimental results demonstrate the effects of changing system conditions via the three aspects. All the three conditions directly affect the HVDC transmission line; nevertheless, they affect each aspect differently.

Advanced ML-Based Ensemble and Deep Learning Models for Short-Term Load Forecasting: Comparative Analysis Using Feature Engineering

Short-term load forecasting (STLF) plays a pivotal role in the electricity industry because it helps reduce, generate, and operate costs by balancing supply and demand. Recently, the challenge in STLF has been the load variation that occurs in each period, day, and seasonality. This work proposes the bagging ensemble combining two machine learning (ML) models—linear regression (LR) and support vector regression (SVR). For comparative analysis, the performance of the proposed model is evaluated and compared with three advanced deep learning (DL) models, namely, the deep neural network (DNN), long short-term memory (LSTM), and hybrid convolutional neural network (CNN)+LSTM models. These models are trained and tested on the data collected from the Electricity Generating Authority of Thailand (EGAT) with four different input features. The forecasting performance is measured considering mean absolute percentage error (MAPE), mean absolute error (MAE), and mean squared error (MSE) parameters. Using several input features, experimental results show that the integrated model provides better accuracy than others. Therefore, it can be revealed that our approach could improve accuracy using different data in different forecasting fields.

Fuzzy mixed integer linear programming model for national level monthly unit commitment under price-based uncertainty: A case study in Thailand

In large-scale monthly unit commitment (MUC), the generation system is committed to a schedule list of available generating units and available fuel provision for each day in a whole month. Despite challenging numerous operational restrictions, fluctuating factors such as load demand, fuel price affect the decision-making on generating electricity in the uncertain market. A Fuzzy Mixed Integer Linear Programming Model (MILP) focusing on the uncertainty fuel price for the MUC in the national level power system is introduced. The price-based uncertainty is handled by attempting to minimize the fluctuation tolerance of fuel price. Moreover, a solution method for solving Fuzzy MILP is presented. An actual national planning level in Thailand's power system comprises multiple types of generators, and supplied fuels are tested using the proposed technique. The small test case, including a 24-unit system, is used for sensitivity analysis on fuel price. The national-level planning data are from the Electricity Generating Authority of Thailand (EGAT), with a 204-unit system is conducted to demonstrate the efficiency of the proposed Fuzzy MILP model.

Bone Mineral Density and Trabecular Bone Score in Predicting Vertebral Fractures in Male Employees of the Electricity Generating Authority of Thailand.

Purpose Osteoporotic VF is frequently asymptomatic and affects not only women but also men. Identifying patients at risk is essential for early management and prevention. BMD and the TBS are measurements of bone strength and trabecular microarchitecture, respectively. Their role in VF prediction in men is less well-studied. We determined the BMD and TBS predictive ability for osteoporotic VF in men. Methods A total of 115 male participants of the Electricity Generating Authority of Thailand (EGAT) cohorts without a history of VF who completed the baseline BMD and TBS measurements in 2012 and a thoracolumbar spine radiograph in 2017 were recruited. The VF was assessed using the Genant semiquantitative method. Logistic regression analysis was performed to identify factors associated with the fracture. The area under the receiving operator curve (AUC) was analyzed to define VF predictive ability. Results Forty subjects (34.78%) had VFs. The unadjusted relative risks (95% confidence interval) for VF for one standard deviation decrease in the TBS and low TBS were 1.319 (1.157–1.506) and 2.347 (1.496–3.682), respectively, and remained significant after BMD and age adjustment. For VF prediction, combined models had a greater AUC than models predicted from a single variable. The use of low TBS, femoral neck BMD, and age provided the best AUC (0.693). Conclusion BMD and the TBS could predict osteoporotic VF in male EGAT employees. The use of both BMD and the TBS in the VF prediction process improved predictive ability.

Rights to Own and Operate a Hydro Floating Solar Project in Thailand

This paper finds that the current electricity regulatory regime, established by the Energy Industry Act B.E. 2550 (2007), together with the current electricity industry structure—the enhanced single buyer model—serves as a favorable legal basis for a state electricity enterprise, especially the Electricity Generating Authority of Thailand (EGAT), to own and operate a hydro-floating solar project in Thailand. However, it argues that, despite their ability to obtain the relevant licenses under the Energy Industry Act B.E. 2550 (2007) as well as enter into power purchase agreements with state electricity enterprises or private customers, the rights of private hydro-floating solar project operators to own and operate a hydro-floating solar project on the surface of public water resources are undermined by uncertainty pertaining to the possessory right over the water surface of public water resources, as well as unfair or discriminatory practices concerning electricity network access.

Impaired mitochondrial ATP production, reduced mitochondrial spare respiratory capacity, and increased oxidative stress in PBMCs are associated with aging in adult EGAT population

Aging is associated with the degeneration of several tissues, and that degeneration has an impact on the structure and function of organs. Aging is the most potential risk factor for chronic diseases, particularly dementia. Mitochondrial function is one of the important processes to maintain the metabolism in cells and organs. Mitochondrial function in peripheral blood mononuclear cells (PBMCs) can be a biomarker for several chronic disease. However, the association between aging and mitochondrial function from PBMCs of healthy adult population has not been elusive. Thus, the present study aims to explore the association between aging and mitochondrial function in human PBMCs. The participants were recruited from Electricity Generating Authority of Thailand (EGAT). The demographic data were collected. The basic laboratory parameters were obtained by venipuncture. The PBMCs were also isolated from the venous blood of the participant and then underwent a mitochondrial function test by Seahorse assay. The mitochondrial oxidative stress and mass were assessed by MitoSox and MitoTracker fluorescent dyes and were quantified by flow cytometry. The data of 1,753 participants remained in the final analysis. The associations of age and mitochondrial respiratory parameters were assessed by linear regression analysis. The covariates including underlying diseases of participants and the basic laboratory parameters obtained in this study were used to evaluate the independent associations of age on mitochondrial functions. The general characteristics of the participants in this study were shown in Table 1. The increased age associated with the reduction in mitochondrial ATP production (beta coefficient [95% confident interval] = -0.59 [-0.76,-0.43]) and mitochondrial spare respiratory capacity (-3.30 [-3.65,-2.95]) in PBMCs. Furthermore, the higher age is associated with the higher mitochondrial oxidative stress/mass ratio (0.0045 [0.0040,0.0050]). After adjusted with underlying diseases or basic laboratory parameters, these associations were still in the same direction as univariate analysis. Aging was associated with mitochondrial dysfunction in PBMCs as indicated by the reduction in mitochondrial ATP production and mitochondrial spare respiratory capacity and elevation of mitochondrial oxidative stress/mass ratio. Further investigation on these findings might be useful to develop novel disease interventions or biomarkers for chronic diseases, particularly dementia.

Abstract 13238: Clinical Utility Of Hs-Tni In Healthy Thai Subjects With Intermediate Cardiovascular Risk

Introduction: In European countries, hs-cTnI is approved for risk stratification in general population. Whether this indication can be applied to Thai population is unknown. We test the utility of hs-cTnI as a risk stratification tool for incident cardiovascular disease among Thai subjects with intermediate cardiovascular (CV) risk and without previous cardiovascular disease. Hypothesis: Hs-cTnI can be used as a risk stratification tool in Thai subject who has intermediate cardiovascular risk. Methods: Data were retrieved from 1,757 subjects who had intermediate CV risk (7.5%-19.9%) and had no known CV disease from the electricity generating authority of Thailand (EGAT) study during the year 2007-2009. High-sensitive Troponin I was tested using the Abbot ARCHITECT i2000 SR system. Hs-cTnI was categorized into low, intermediate and high risk using gendered-specific cut-offs points. Major adverse cardiac event (MACE), defined as a composite of CV death, non-fatal myocardial infarction and non-fatal stroke, was collected and confirmed by medical record until 2017-2019. Survival analysis and net reclassification index (NRI) analysis were performed. Results: A total of 1,757 subjects had complete data for analysis. Mean age was 57-year-old, 77% were male. After 10 years, 88 CV event (5%) occurred. Median hs-cTnI was 3 (2.2, 4.1) mg/dL. The event rate was significantly highest in high-risk group of hs-cTnI (14%), followed by intermediate (6.4%) and low risk group (4.3%). Multivariate analysis adjusted for conventional risk factor from Thai CV risk score showed that hs-cTnI is an independent risk factor for MACE (HR 1.02, 95% CI 1.01 to 1.03). For the high-risk group, compared to low risk group, hazard ratio was 3.24, 95% CI 1.73 to 6.07 (p value for trend &lt; 0.001). The addition of hsTnI information to prognostic model yielded an NRI of 0.11 (p-value 0.006). Conclusions: In this intermediate CV risk population, elevation of hs-cTnI is not uncommon. Hs-cTnI is an independent risk factor for cardiovascular death, myocardial infarction and stroke. Hs-cTnI significantly improves the reclassification as shown by NRI. Hs-cTnI can be used as a risk stratification tool in Thai subject who has intermediate cardiovascular risk.