Evernin
* Please be kindly noted products are not for therapeutic use. We do not sell to patients.
| Category | Others |
| Catalog number | BBF-05494 |
| CAS | 61631-65-0 |
| Molecular Weight | 360.36 |
| Molecular Formula | C19H20O7 |
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Specification
| Synonyms | 2-Hydroxy-4-[(2-hydroxy-4-methoxy-6-methylbenzoyl)oxy]-3,6-dimethylbenzoic acid methyl ester; Benzoic acid, 2-hydroxy-4-[(2-hydroxy-4-methoxy-6-methylbenzoyl)oxy]-3,6-dimethyl-, methyl ester |
| IUPAC Name | methyl 2-hydroxy-4-(2-hydroxy-4-methoxy-6-methylbenzoyl)oxy-3,6-dimethylbenzoate |
| Canonical SMILES | CC1=CC(=CC(=C1C(=O)OC2=C(C(=C(C(=C2)C)C(=O)OC)O)C)O)OC |
| InChI | InChI=1S/C19H20O7/c1-9-6-12(24-4)8-13(20)15(9)19(23)26-14-7-10(2)16(18(22)25-5)17(21)11(14)3/h6-8,20-21H,1-5H3 |
| InChI Key | SAFYHKBNYXIGKB-UHFFFAOYSA-N |
Reference Reading
1. Incidence of first-ever transient ischemic attack in Eastern Finland
Tiina Komulainen, Anne Koivisto, Pekka Jäkälä Acta Neurol Scand. 2022 Nov;146(5):615-622. doi: 10.1111/ane.13689. Epub 2022 Aug 27.
Objectives: The incidence of stroke has been declining in Finland, as well as in Europe. However, it is unclear whether the incidence of transient ischemic attack (TIA) is also decreasing. In fact, the TIA incidence in the Finnish population has never been reported. Therefore, here we investigated the incidence of TIA in the Eastern Finnish population in 2017. Materials and methods: All patients with suspected TIA, from a defined catchment area, were referred to a neurological emergency unit at Kuopio University Hospital (KUH) in the Northern Savonia region of Eastern Finland, which had a population of 246,653 in 2017. The original study population comprised TIA patients diagnosed based on the WHO TIA criteria in 2017. Incidence rates were calculated by dividing the number of TIA cases by the number of people in different age groups. Results: Among 432 patients with a suspected TIA referred to the neurological emergency unit at Kuopio University Hospital in 2017, 293 were living in Northern Savonia and were ultimately diagnosed with TIA after neurological examinations. The number of first-ever TIAs was 211. The crude incidence of all TIA was 122/100,000 inhabitants, and of first-ever TIA was 86/100,000. The age-standardized incidence (European population 2010) of the first-ever TIA was calculated to be 64/100,000. The mean age of first-ever TIA patients was 70 years: 72 years for women versus 68 years for men. Conclusions: We found a high incidence of TIA in Eastern Finland.
2. Sociodemographic, personal, peer, and familial predictors of e-cigarette ever use in ESPAD Ireland: A forward stepwise logistic regression model
Joan Hanafin, Salome Sunday, Luke Clancy Tob Induc Dis. 2022 Feb 2;20:12. doi: 10.18332/tid/144234. eCollection 2022.
Introduction: E-cigarette ever use has risen significantly in recent years in Ireland, similar to trends elsewhere in Europe, the United States, and Asia-Pacific region. Results from ESPAD Ireland (European School Survey Project on Alcohol and other Drugs) show teenage e-cigarette ever use increased from 18% (2015) to 37% (2019). Given this increase, our aim is to profile e-cigarette ever users and never users in this age group; to examine sociodemographic, personal, peer, and familial factors associated with e-cigarette ever use; and to suggest appropriate measures to reduce use. Methods: A nationally representative stratified random sample of 50 ESPAD schools was surveyed in 2019, with 3495 students aged 15-17 years. Bivariate and multivariable logistic regression analyses were performed using Stata version 16. Results: E-cigarette ever use was significantly associated with ever smoking (AOR=4.15; 95% CI: 1.29-13.41), ever cannabis use (AOR=2.21; 95% CI: 1.11-4.41) and ever inhalants use (AOR=2.51; 95% CI: 1.07-5.88). Children of university-educated mothers had significantly higher odds of e-cigarette ever use (AOR=3.46; 95% CI: 1.40-8.54). Associated with reduced AORs were reading books for enjoyment (AOR=0.32; 95% CI: 0.16-0.64), living in households where smoking was regulated (AOR=0.53; 95% CI: 0.30-0.94), and perceiving moderate risk in trying e-cigarettes once or twice (AOR=0.20; 95% CI: 0.07-0.67). Conclusions: E-cigarette ever use is part of a pattern of teenage polysubstance use including cigarette smoking, providing some support for the common liability theory. Regulation of smoking in the home, reading for enjoyment, and perceiving risk from e-cigarette use are associated with decreased likelihood of ever use, and higher parental education with increased likelihood. Thus, health education emphasizing the role of parents and risks of e-cigarette use is indicated to reduce the rise in e-cigarette ever use in teenagers.
3. Risk-stratified Approach for Never- and Ever-Smokers in Lung Cancer Screening: A Prospective Cohort Study in China
Fei Wang, Fengwei Tan, Sipeng Shen, Zheng Wu, Wei Cao, Yiwen Yu, Xuesi Dong, Changfa Xia, Wei Tang, Yongjie Xu, Chao Qin, Meng Zhu, Jibin Li, Zhuoyu Yang, Yadi Zheng, Zilin Luo, Liang Zhao, Jiang Li, Jiansong Ren, Jufang Shi, Yao Huang, Ning Wu, Hongbing Shen, Wanqing Chen, Ni Li, Jie He Am J Respir Crit Care Med. 2023 Jan 1;207(1):77-88. doi: 10.1164/rccm.202204-0727OC.
Rationale: Over 40% of lung cancer cases occurred in never-smokers in China. However, high-risk never-smokers were precluded from benefiting from lung cancer screening as most screening guidelines did not consider them. Objectives: We sought to develop and validate prediction models for 3-year lung cancer risks for never- and ever-smokers, named the China National Cancer Center Lung Cancer models (China NCC-LCm2021 models). Methods: 425,626 never-smokers and 128,952 ever-smokers from the National Lung Cancer Screening program were used as the training cohort and analyzed using multivariable Cox models. Models were validated in two independent prospective cohorts: one included 369,650 never-smokers and 107,678 ever-smokers (841 and 421 lung cancers), and the other included 286,327 never-smokers and 78,469 ever-smokers (503 and 127 lung cancers). Measurements and Main Results: The areas under the receiver operating characteristic curves in the two validation cohorts were 0.698 and 0.673 for never-smokers and 0.728 and 0.752 for ever-smokers. Our models had higher areas under the receiver operating characteristic curves than other existing models and were well calibrated in the validation cohort. The China NCC-LCm2021 ⩾0.47% threshold was suggested for never-smokers and ⩾0.51% for ever-smokers. Moreover, we provided a range of threshold options with corresponding expected screening outcomes, screening targets, and screening efficiency. Conclusion: The construction of the China NCC-LCm2021 models can accurately reflect individual risk of lung cancer, regardless of smoking status. Our models can significantly increase the feasibility of conducting centralized lung cancer screening programs because we provide justified thresholds to define the high-risk population of lung cancer and threshold options to adapt different configurations of medical resources.
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Bio Calculators
* Our calculator is based on the following equation:
Concentration (start) x Volume (start) = Concentration (final) x Volume (final)
It is commonly abbreviated as: C1V1 = C2V2
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Tip: Chemical formula is case sensitive. C22H30N4O √ c22h30n40 ╳
