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2nd International Conference on Biological Engineering and Medical Science, ICBioMed 2022 ; 12611, 2023.
Article in English | Scopus | ID: covidwho-2324523


Research has shown that alopecia including androgen alopecia (AGA), alopecia areata (AA), and telogen effluvium (TE) presents in the majority of patients hospitalized with COVID-19. This study aims to explore the association between age, gender alopecia type, and alopecia level in patients hospitalized with COVID-19, and find which factor has a significant effect on alopecia during COVID-19. In this study, we collected the gender, age, type of alopecia, and alopecia level of patients from four existing studies. A linear regression model and Chi-square test were applied to explore the effect of age and gender on alopecia levels in patients hospitalized with COVID-19. There were 281 patients counted in our study. We examined the data and found a significant correlation between age and androgen alopecia levels in male patients, and we found an association between gender and androgen alopecia prevalence. Our findings might help prevalent other patients with alopecia. © 2023 SPIE.

Transfusion Medicine and Hemotherapy ; 49(Supplement 1):76, 2022.
Article in English | EMBASE | ID: covidwho-2223871
Juridical Tribune Journal = Tribuna Juridica ; 12(4):457-475, 2022.
Article in English | ProQuest Central | ID: covidwho-2217982
2022 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2022 ; 2022-December:1399-1405, 2022.
Article in English | Scopus | ID: covidwho-2213322
2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2213255
Open Forum Infectious Diseases ; 9(Supplement 2):S769, 2022.
Article in English | EMBASE | ID: covidwho-2189956
2nd International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability, ARTIIS 2022 ; 1675 CCIS:524-534, 2022.
Article in English | Scopus | ID: covidwho-2173759
24th International Conference on Human-Computer Interaction, HCII 2022 ; 1655 CCIS:175-183, 2022.
Article in English | Scopus | ID: covidwho-2173726
14th IEEE International Conference of Logistics and Supply Chain Management, LOGISTIQUA 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2161469
Joint 5th International Conference on Applied Informatics Workshops, ICAIW 2022: 3rd International Workshop on Applied Artificial Intelligence, WAAI 2022, 4th International Workshop on Applied Informatics for Economy, Society, and Development, AIESD 2022, 5th International Workshop on Data Engineering and Analytics, WDEA 2022, 1st International Workshop on Intelligent Transportation Systems and Smart Mobility Technology, WITS 2022, 2nd International Workshop on Knowledge Management and Information Technologies, WKMIT 2022 and 1st International Workshop on Systems Modeling, WSSC 2022 ; 3282:206-213, 2022.
Article in English | Scopus | ID: covidwho-2156601
14th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2022 ; : 7-12, 2022.
Article in English | Scopus | ID: covidwho-2136192
8th International Conference on E-Business and Mobile Commerce, ICEMC 2022 ; : 64-71, 2022.
Article in English | Scopus | ID: covidwho-2053353
Int J Mol Sci ; 23(13)2022 Jun 30.
Article in English | MEDLINE | ID: covidwho-1934132


Boesenbergia rotunda (Zingiberaceae), is a high-value culinary and ethno-medicinal plant of Southeast Asia. The rhizomes of this herb have a high flavanone and chalcone content. Here we report the genome analysis of B. rotunda together with a complete genome sequence as a hybrid assembly. B. rotunda has an estimated genome size of 2.4 Gb which is assembled as 27,491 contigs with an N50 size of 12.386 Mb. The highly heterozygous genome encodes 71,072 protein-coding genes and has a 72% repeat content, with class I TEs occupying ~67% of the assembled genome. Fluorescence in situ hybridization of the 18 chromosome pairs at the metaphase showed six sites of 45S rDNA and two sites of 5S rDNA. An SSR analysis identified 238,441 gSSRs and 4604 EST-SSRs with 49 SSR markers common among related species. Genome-wide methylation percentages ranged from 73% CpG, 36% CHG and 34% CHH in the leaf to 53% CpG, 18% CHG and 25% CHH in the embryogenic callus. Panduratin A biosynthetic unigenes were most highly expressed in the watery callus. B rotunda has a relatively large genome with a high heterozygosity and TE content. This assembly and data (PRJNA71294) comprise a source for further research on the functional genomics of B. rotunda, the evolution of the ginger plant family and the potential genetic selection or improvement of gingers.

Ginger , Zingiberaceae , Biosynthetic Pathways , DNA, Ribosomal , Flavonoids , Ginger/genetics , In Situ Hybridization, Fluorescence , Microsatellite Repeats/genetics , Zingiberaceae/genetics
JACC Adv ; 1(2): 100043, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1821317


Background: COVID-19 infection carries significant morbidity and mortality. Current risk prediction for complications in COVID-19 is limited, and existing approaches fail to account for the dynamic course of the disease. Objectives: The purpose of this study was to develop and validate the COVID-HEART predictor, a novel continuously updating risk-prediction technology to forecast adverse events in hospitalized patients with COVID-19. Methods: Retrospective registry data from patients with severe acute respiratory syndrome coronavirus 2 infection admitted to 5 hospitals were used to train COVID-HEART to predict all-cause mortality/cardiac arrest (AM/CA) and imaging-confirmed thromboembolic events (TEs) (n = 2,550 and n = 1,854, respectively). To assess COVID-HEART's performance in the face of rapidly changing clinical treatment guidelines, an additional 1,100 and 796 patients, admitted after the completion of development data collection, were used for testing. Leave-hospital-out validation was performed. Results: Over 20 iterations of temporally divided testing, the mean area under the receiver operating characteristic curve were 0.917 (95% confidence interval [CI]: 0.916-0.919) and 0.757 (95% CI: 0.751-0.763) for prediction of AM/CA and TE, respectively. The interquartile ranges of median early warning times were 14 to 21 hours for AM/CA and 12 to 60 hours for TE. The mean area under the receiver operating characteristic curve for the left-out hospitals were 0.956 (95% CI: 0.936-0.976) and 0.781 (95% CI: 0.642-0.919) for prediction of AM/CA and TE, respectively. Conclusions: The continuously updating, fully interpretable COVID-HEART predictor accurately predicts AM/CA and TE within multiple time windows in hospitalized COVID-19 patients. In its current implementation, the predictor can facilitate practical, meaningful changes in patient triage and resource allocation by providing real-time risk scores for these outcomes. The potential utility of the predictor extends to COVID-19 patients after hospitalization and beyond COVID-19.