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4. Body Map of Droplet Distributions During Oropharyngeal Suction to Protect Health Care Workers From Airborne Diseases.

Author

Park, Jiyeon, Su, Min-Ying, Kang, Keum, Kim, Ae, Ahn, Jin, Cho, Eunah, Lee, Jun-Ho, and Kim, Young

Subjects
body mapping gown, contamination, droplets, suction, Humans, Suction, Aerosols, Intubation, Intratracheal, Health Personnel
Abstract

PURPOSE: Health care workers (HCWs), and in particular anesthesia providers, often must perform aerosol-generating medical procedures (AGMPs). However, no studies have analyzed droplet distributions on the bodies of HCWs during AGMPs. Therefore, the purpose of this study was to assess and analyze droplet distributions on the bodies of HCWs during suction of oral cavities with and without oral airways and during extubations. DESIGN: Using a quasi-experiemental design, we assumed the HCWs perform suction and extubation on intubated patients, and we prepared an intubated mannequin mimicking a patient. This study performed the oral suction and extubation on the intubated mannequin (with or without oral airways in place) and analyzed the droplet distributions. METHODS: We prepared a mannequin intubated with an 8.0 mm endotracheal tube, assuming the situation of general anesthesia. We designed the body mapping gown, and divided it into 10 areas including the head, neck, chest, abdomen, upper arms, forearms, and hands. We classified experiments into group O when suctions were performed on the mannequin with an oral airway, and into group X when the suctions were performed on the mannequin without an oral airway. An experienced board-certified anesthesiologist performed 10 oral suctions on each mannequin, and 10 extubations. We counted the droplets on the anesthesiologists gown according to the divided areas after each procedure. FINDINGS: The mean droplet count after suction was 6.20 ± 2.201 in group O and 13.6 ± 4.300 in group X, with a significant difference between the two groups (P < .001). The right and left hands were the most contaminated areas in group O (2.8 ± 1.033 droplets and 2.0 ± 0.943 droplets, respectively). The abdomen, right hand, left forearm, and left hand showed many droplets in group X. (1.3 ± 1.337 droplets, 3.1 ± 1.792 droplets, 3.2 ± 3.910 droplets, and 4.3 ± 2.214 droplets, respectively). The chest, abdomen, and left hand presented significantly more droplets in group X than in group O. The trunk area (chest and abdomen) was exposed to more droplets during extubations than during suctions. CONCLUSIONS: During suctions, more droplets are splattered from mannequins without oral airways than from those with oral airways. The right and left hands were the most contaminated areas in group O. Moreover, the abdomen, right hand, left forearm, and left hand presented a lot of droplets in group X. In addition, extubations contaminate wider areas (the head, neck, chest and abdomen) of an HCW than suctions.

Published
2023

5. CFTR regulates brown adipocyte thermogenesis via the cAMP/PKA signaling pathway

Author

Choi, Kyung-Mi, Cho, Sung-Hee, Kim, Jung Hak, Kim, Ae-Rhee Lilian, Kong, Xiangmudong, and Yoon, John C

Subjects
Medical Physiology, Biomedical and Clinical Sciences, Nutrition, Lung, Obesity, Rare Diseases, Cystic Fibrosis, 2.1 Biological and endogenous factors, Congenital, Metabolic and endocrine, Animals, Mice, Adipocytes, Brown, Cystic Fibrosis Transmembrane Conductance Regulator, Energy Metabolism, Signal Transduction, Thermogenesis, Cyclic AMP-Dependent Protein Kinases, CFTR, thermogenesis, brown adipocyte, cAMP-PKA pathway, Clinical Sciences, Respiratory System, Clinical sciences
Abstract

BackgroundCystic fibrosis (CF) is characterized by reduced growth and lower body weight, which are multifactorial. CF mouse models lack key disease characteristics that predispose to a negative energy balance, such as pulmonary infections or exocrine pancreatic insufficiency, and yet they still exhibit a growth defect and an abnormally increased energy expenditure. Whether adipocyte thermogenesis contributes to the elevated resting energy expenditure in CF mice is unknown.MethodsWe examined the expression of CFTR in thermogenic brown adipose tissue (BAT) and investigated a functional role for CFTR using BAT-specific CFTR null mice (CFTRBATKO).ResultsThe CFTR protein is expressed in mouse BAT at levels comparable to those in the lungs. BAT-specific inactivation of CFTR in mice increases whole-body energy expenditure associated with sympathetic stimulation by cold exposure. Weight gain on a high-fat diet is attenuated in these mice. However, CFTR-deficient brown adipocytes themselves have impaired, rather than enhanced, thermogenic responses. These cells feature decreased lipolysis and blunted activation of the cAMP/PKA signaling pathway in response to adrenergic stimulation. This suggests that compensatory heat production in other tissues likely accounts for the increased systemic energy expenditure seen in CFTRBATKO mice.ConclusionsOur data reveal a new role for CFTR in the regulation of adipocyte thermogenesis.

Published
2023

15. Comparison of the Oral Calcimimetics Evocalcet and Cinacalcet in East Asian Patients on Hemodialysis with Secondary Hyperparathyroidism

Author

Xinling, Liang, Shuangxin, Liu, Sijia, Li, Lixia, Xu, Zhiming, Ye, Zhonglin, Feng, Renwei, Huang, Zhilian, Li, Wei, Chen, Xunhua, Zheng, Naya, Huang, Zhen, Ai, Xin, Wang, former PI, Ni, Zhaohui, present PI, Renhua, Lu, Jianxiao, Shen, Yijun, Zhou, Xinghui, Lin, Yuanyuan, Xie, Jiahui, Zhang, Miaolin, Che, Yan, Fang, Huihua, Pang, Xinyu, Su, Leyi, Gu, Wei, Jin, Peipei, Zhao, Yiwei, Shen, Liou, Zao, Wei, Lu, Haidong, Huang, Gang, Ji, Hao, Li, Deguang, Wang, Liang, Yuan, Lihong, Ding, Xuerong, Wang, Huai, Li, Hong, Liu, Fang, Yuan, Panai, Song, An, Zhou, Xiaojun, Chen, Xiejia, Li, Liyu, He, Xia, Tan, Jing, Chen, Minmin, Zhang, Qian, Zhang, Jing, Qian, Yaozhong, Kong, Youyuan, Chen, Wei, Shen, Guanqing, Xiao, Dezhen, Chen, Dao, Li, Aizhen, Hou, Xiaolei, Li, Hanchang, He, Huizhen, Ye, Zhuxing, Sun, Xiran, Zhang, Weiwei, Shan, Jing, Xue, Yong, Chen, Changying, Xing, Li, Li, Xiangbao, Yu, Kang, Liu, Yifei, Ge, Yili, Xu, Zhimin, Huang, Jingjing, Wu, Bicheng, Liu, Yan, Tu, Mingming, Pan, Hongli, Lin, Dapeng, Wang, Qingyang, Meng, Renna, Luo, Guohua, Ding, Ming, Shi, Changjian, Qiu, Xifeng, Lv, Guojuan, Zhang, Liping, Jiang, Ning, Ding, Huiying, Zhao, Shumin, Bao, Shen, Chen, Qiaojing, Liang, Mei, Zhang, Kanfu, Peng, Pan, Xie, Qian, Yuan, Yan, Zhuo, Shaohua, Li, Yonghui, Mao, Ban, Zhao, Songlan, Wang, Xianguang, Chen, Xiaonong, Chen, Chenni, Gao, Haijin, Yu, Qinjie, Weng, Yuanmeng, Jin, Xiaobo, Ma, Ping, Luo, Dan, Gao, Man, Wu, Yonghui, Qi, Ping, Zhang, Xiaoying, Du, Lihui, Qu, Chunping, Xu, Kaixiang, Sheng, Yi, Yang, Song, Wang, Xinkui, Tian, Hongxia, Guo, Wenhan, Bao, Weifeng, Lin, Sijia, Zhou, Zhuan, Cui, Wenling, Yang, Kaijie, Su, Lian, He, Zhihong, Zhou, Yu, Zheng, Shubei, Zheng, Lingwei, Jin, Yan, Chen, Min, Pan, Wu, Chia-Chao, SungShuei-Liong Lin, Chih-Chien, Wu, Ming-Shiou, Huang, Jenq-Wen, Chiang, Wen Chih, Chiang, Chih-Kang, Yang, Shao-Yu, Wu, Vin-Cent, Huang, Tao-Min, Chen, Yi-Ting, Lai, Tai-Shuan, Lai, Chun-Fu, Tarng, Der-Cherng, Ou, Shuo-Ming, Yang, Chih-Yu, Tseng, Wei-Cheng, Lin, Yao-Ping, Sung, Junne-Ming, Kuo, Te-Hui, Chang, Yu-Tzu, Wu, An-Bang, Lin, Wei-Hung, Fang, Hua-Chang, Chen, Hsin-Yu, Hsu, Chih-Yang, Lee, Po-Tsang, Chen, Chien-Liang, Chou, Kang-Ju, Ho, Tzung-Yu, Lee, Chien-Te, Ng, Hwee-Yeong, Lee, Yueh-Ting, Chiu, Yi-Wen, Kuo, Hung-Tien, Hung, Chi-Chih, Kuo, Mei-Chuan, Lee, Jia-Jung, Tsai, Jer-Chia, Chang, Jer-Ming, Lee-Moay, Lim, Hwang, Shang-Jyh, Hwang, Jyh-Chang, Wang, Hsien-Yi, Kan, Wei-Chih, Wu, Chia-Chun, Jiang, Ming-Yan, Chien, Chih-Chiang, Wu, Ming-Ju, Tsai, Shang-Feng, Chen, Cheng-Hsu, Chen, Hsi-Hsien, Kao, Chih-Chin, Lin, Yen-Chung, Wu, Yueh-Lin, Yeh, Shu-Ching, Mao Chan, Daniel Tak, Yee Mok, Maggie Ming, Yuen Kwan, Lorraine Pui, Wang Chan, Gary Chi, Kim, Yong-Lim, Cho, Jang-Hee, Lim, Jeong-Hoon, Jung, Hee-Yeon, Park, Sun-Hee, Kim, Chan-Duck, Kim, Kyu Yeun, Park, Jung Tak, Yoo, Tae-Hyun, Han, Seung Hyeok, Chung, Wookyung, Jung, Ji Yong, Lee, Hyun Hee, Chang, Jae Hyun, Ro, Han, Kim, Ae Jin, Lee, Jong Soo, Park, Jongha, Park, Kyung Sun, Yoo, Kyoung Don, Chang, Tae Ik, Kang, Ea Wha, Park, Kyoung Sook, Jin, Kyubok, Kim, Yaerim, Paek, Jinhyuk, Park, Wooyeong, Han, Seungyeup, Kwon, Ohyun, Park, Sung Bae, Kim, Myung-gyu, Oh, SeWon, Lee, Jung Pyo, Lee, Jeonghwan, Jung, Jihoon, Park, Cheol Whee, Kim, Hyung Duk, Kim, Sunggyun, Song, Youngrim, Joo, Narae, Lee, Hyungsuk, Choi, Bum-Soon, Park, Hoon Suk, Ban, Tae Hyun, Liang, Xinling, Lu, Kuo-Cheng, Chan, Tak Mao, Fukagawa, Masafumi, Kinoshita, Jun, Nagai, Chisato, Kojima, Masahiro, and Yu, Xueqing

Published
2023
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21. Subgrouping of Korean Readers Based on Reading Achievement and the Relation of Cognitive-Linguistic Variables to the Subgroups

Author

Kim, Ae-Hwa, Kim, Ui Jung, Kim, Jae Chul, and Vaughn, Sharon

Abstract

The purpose of this study was to classify Korean readers into subgroups based on their reading achievement and to examine the relationships between these subgroups and a set of cognitive-linguistic variables. The reading achievement and cognitive-linguistic skills of 394 elementary school students were measured and the data were analyzed by disaggregating into primary grade level (i.e., Grades 1-3) and intermediate grade level (i.e., Grades 4-6). The main results are summarized as follows. First, three subgroups of readers were found based on the reading achievement for the primary grade level: "very poor word readers and poor comprehenders," "poor readers," and "average readers." Second, four subgroups of readers were found based on the reading achievement for the intermediate grade level: "very significantly poor readers," "very poor readers," "average word readers but poor comprehenders," and "average readers." Third, vocabulary, rapid naming, phonological memory, and phonological awareness were cognitive-linguistic variables that significantly differentiated "very poor readers" and "poor readers" from "average readers" for the primary grade level. Fourth, phonological memory, rapid naming, sentence repetition, and listening comprehension were cognitive-linguistic variables that significantly differentiated "very poor readers" and "poor readers" from "average readers" for the intermediate grade level. This article also discusses the limits of this research and the implications in practice. Finally, this article touches upon the direction of future studies.

Published
2021
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27. Hydroxide-Oxide-Sulfur-Stabilized Bismuth Nanorod Conversion: Selective Induction of the Electrochemical Reduction of CO2 to Formate.

Author

Palanimuthu, Naveenkumar, Santhosh Kumar, Ramasamy, Sidra, Saleem, Kim, Ae Rhan, Kim, Do Hwan, and Yoo, Dong Jin

Abstract

The electrochemical CO2 reduction reaction (e-CO2RR) converts value-added chemicals into formate. Bismuth-based resources exhibit promising potential in the electrochemical reduction of CO2 to formate due to their low toxicity and ability to enhance the *OCHO intermediate reaction pathway. However, there are numerous hurdles to optimizing their activity and applicability. Here, we describe the assembly of structurally stable bismuth hydroxide, oxide, and sulfide nanorods supported by a reduced graphene oxide (rGO) nanosheet through a simple hydrothermal method. The obtained optimized rGO-Bi2S3 nanorods exhibit improved e-CO2RR conversions to formate in H-cell systems compared to hydroxide and oxide electrocatalysts. The rGO-Bi2S3 nanorods maintain high activity within a wide potential window (−0.76 to −1.26 V vs RHE) to obtain overall Faradaic efficiency of formate of ±84% at −1.16 V vs RHE, current density of formate of ±41.50 mA cm–2, and stability for longer than 12 h, with improved Faradaic efficiency greater than ±86% in an H-cell system. Theoretical calculations reveal that the strong interaction between rGO and Bi2S3 stabilizes the adsorption of formate in e-CO2RR. The resulting structural transformation of bismuth nanorods based on sulfur, oxide, and hydroxide provides an encouraging avenue for future energy conversion. [ABSTRACT FROM AUTHOR]

Published
2025
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29. Synthesis and Evaluation of Reduced Graphene Oxide (rGO) Supported on Ni3O4 as Spinel‐Based Cathode Catalyst for the Effective Anion‐Exchange Membrane Fuel Cell Application.

Author

Santhosh Kumar, Ramasamy, Gokulapriyan, Ramasamy, Sakthivel, Venkitesan, Sayfiddinov, Dilmurod, Kim, Ae Rhan, Arunkumar, Iyappan, and Yoo, Dong Jin

Subjects
CHEMICAL bonds, FUEL cell electrolytes, ION-permeable membranes, ALKALINE fuel cells, CHEMICAL structure
Abstract

Oxygen reduction reaction (ORR) stability and catalytic activity in high‐durability anion exchange membrane fuel cells (AEMFCs) can be improved using graphene‐supported spinel‐based Ni3O4 cathode catalysts. Here, we describe a simple and economical hydrothermal method for synthesizing reduced graphene oxide (rGO) supported on Ni3O4. The atomic‐level contribution of the Ni−Ni and Ni−O bonds to the chemical structure of nickel oxide was confirmed by X‐ray photoelectron and absorption spectroscopy studies. Due to the force of the void for oxygen created by nickel atoms, Ni3O4@rGO for the ORR exhibited enhanced stability and catalytic activity (E1/2=0.761 V and over 30,000 CV cycles). A single AEMFC cell achieved the greatest power density and long‐term durability using a Ni3O4@rGO cathode, suggesting improved endurance despite the minimal voltage decrease (power density 29.6 mW cm−2, endurance for 25 h). These findings offer insights and point to opportunities for developing metal oxide–based AEMFCs. [ABSTRACT FROM AUTHOR]

Published
2024
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