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1.
Journal of Business and Industrial Marketing ; 2022.
Article in English | Scopus | ID: covidwho-1961333

ABSTRACT

Purpose: Leveraging theory from the dynamic capability literature, this study aims to explore how information technology (IT) capability influences firm agility and subsequently translates into firm performance. Design/methodology/approach: This study examines the proposed relationships by using survey data from a sample of 296 Chinese retail firms. Structural equation modeling is used to test this study’s hypotheses. Findings: The following results are produced: the direct effect of IT capability on firm agility is confirmed;firm agility has a direct impact on firm performance;and the indirect effect of IT capability on firm performance via firm agility is demonstrated (i.e. partial mediation). Originality/value: The catastrophic outbreak of the COVID-19 pandemic has heightened the importance of firm agility more than ever. Although the traumatic event is painful, however, there is nothing like a crisis to offer a tremendous business opportunity. In response to the pandemic circumstance, firms are required to operate their business by reacting to unpredictable and dynamic market changes quickly and efficiently. This study sheds light on why firms should develop their IT capability and how it affects firm performance via firm agility during the COVID-19 outbreak. © 2022, Emerald Publishing Limited.

2.
PLoS One ; 17(7): e0271381, 2022.
Article in English | MEDLINE | ID: covidwho-1933385

ABSTRACT

OBJECTIVE: We used SARS-CoV-2 whole-genome sequencing (WGS) and electronic health record (EHR) data to investigate the associations between viral genomes and clinical characteristics and severe outcomes among hospitalized COVID-19 patients. METHODS: We conducted a case-control study of severe COVID-19 infection among patients hospitalized at a large academic referral hospital between March 2020 and May 2021. SARS-CoV-2 WGS was performed, and demographic and clinical characteristics were obtained from the EHR. Severe COVID-19 (case patients) was defined as having one or more of the following: requirement for supplemental oxygen, mechanical ventilation, or death during hospital admission. Controls were hospitalized patients diagnosed with COVID-19 who did not meet the criteria for severe infection. We constructed predictive models incorporating clinical and demographic variables as well as WGS data including lineage, clade, and SARS-CoV-2 SNP/GWAS data for severe COVID-19 using multiple logistic regression. RESULTS: Of 1,802 hospitalized SARS-CoV-2-positive patients, we performed WGS on samples collected from 590 patients, of whom 396 were case patients and 194 were controls. Age (p = 0.001), BMI (p = 0.032), test positive time period (p = 0.001), Charlson comorbidity index (p = 0.001), history of chronic heart failure (p = 0.003), atrial fibrillation (p = 0.002), or diabetes (p = 0.007) were significantly associated with case-control status. SARS-CoV-2 WGS data did not appreciably change the results of the above risk factor analysis, though infection with clade 20A was associated with a higher risk of severe disease, after adjusting for confounder variables (p = 0.024, OR = 3.25; 95%CI: 1.31-8.06). CONCLUSIONS: Among people hospitalized with COVID-19, older age, higher BMI, earlier test positive period, history of chronic heart failure, atrial fibrillation, or diabetes, and infection with clade 20A SARS-CoV-2 strains can predict severe COVID-19.


Subject(s)
Atrial Fibrillation , COVID-19 , Heart Failure , COVID-19/epidemiology , Case-Control Studies , Electronic Health Records , Heart Failure/epidemiology , Heart Failure/genetics , Humans , SARS-CoV-2/genetics
3.
American Journal of Respiratory and Critical Care Medicine ; 205(1), 2022.
Article in English | EMBASE | ID: covidwho-1927807

ABSTRACT

Rationale: In 2019, the clinical manifestations of an outbreak of e-cigarette, or vaping, product useassociated lung injury (EVALI) in the United States was described and linked to vitamin E acetate, an additive used to dilute tetrahydrocanninol (THC). It is unknown whether access to vape shops influence adolescent e-cigarette literacy and increase the risk for EVALI. This study aims to elucidate associations between adolescent EVALI cases and neighborhood vape shop density. Methods: ZIP codes of EVALI cases in adolescents hospitalized at Children's Health Medical Center Dallas from December 2018 - June 2021 were retrospectively identified using the Centers for Disease Control and Prevention case definition. ZIP codes without EVALI cases were identified through the American Community Survey 2019 data and matched to the EVALI ZIP codes 2:1 using population size and age distribution. Vape shop locations were obtained by cross-referencing search results from Google Maps and Yelp. Vape shop density was mapped per ZIP code using ESRI ArcMap geospatial processing software. Hotspots were identified using graduated symbols. Data distribution of vape shop density was assessed with the Shapiro Wilk test for normality. Differences in vape shop density by ZIP code group (EVALI/no EVALI) was assessed with the Wilcoxon Rank Sum test. Results: The mean age of adolescents with EVALI (n=41) was 16.3 years (SD=1.1) (66% male;61% Hispanic, 39% non-Hispanic white). There were 34 corresponding ZIP codes, with five containing two EVALI cases and one containing three cases. 64% of our cohort were identified after the World Health Organization's declaration that COVID-19 was a pandemic, 66% obtained their vaping products from informal sources, 95% smoked primarily THC containing products, and 15% smoked “Dank” vapes. No significant difference in vape shop density was found between the 130 ZIP codes without EVALI cases (0.30 shops/mi2, SD=0.48) and the 34 ZIP codes with at least one EVALI case (0.24 shops/mi2, SD=0.24, p=0.98). Conclusions: Findings here show no association between ZIP code-level vape shop density and EVALI cases, suggesting that interventions should not be focused on regulating vape shops alone. This lack of association may be due to decreased vape shop accessibility during the COVID-19 pandemic and/or the origin of ecigarettes mainly from informal sources. Further research should investigate the association between other neighborhood characteristics and EVALI with the goal of implementing targeted prevention programs in at-risk neighborhoods to mitigate the impact of this new epidemic.

5.
6.
Clinical Pediatric Endocrinology ; 31(2):81-86, 2022.
Article in English | EMBASE | ID: covidwho-1883580

ABSTRACT

Diabetic ketoacidosis (DKA) and hyperglycemic hyperosmolar state (HHS) are diabetic emergencies. Some patients with a hyperglycemic crisis can present with an overlap of DKA and HHS. The coexistence of DKA and HHS is associated with higher mortality than in isolated DKA and HHS. In addition, electrolyte derangements caused by global electrolyte imbalance are associated with potentially life-threatening complications. Here, we describe three cases of mixed DKA and HHS with severe hypernatremia at the onset of type 2 diabetes mellitus. All patients had extreme hyperglycemia and hyperosmolarity with acidosis at the onset of diabetes mellitus. They consumed 2 to 3 L/d of high-carbohydrate drinks prior to admission to relieve thirst. They showed severe hypernatremia with renal impairment. Two patients recovered completely without any complications, while one died. Severe hypernatremia with mixed DKA and HHS is rare. However, it may be associated with excess carbohydrate beverage consumption. Reduced physical activity during the COVID19 pandemic and unhealthy eating behaviors worsened the initial presentation of diabetes mellitus. We highlight the impact of lifestyle factors on mixed DKA and HHS.

7.
Ieee Access ; 10:53027-53042, 2022.
Article in English | English Web of Science | ID: covidwho-1883112

ABSTRACT

As the number of deaths from respiratory diseases due to COVID-19 and infectious diseases increases, early diagnosis is necessary. In general, the diagnosis of diseases is based on imaging devices (e.g., computed tomography and magnetic resonance imaging) as well as the patient's underlying disease information. However, these examinations are time-consuming, incur considerable costs, and in a situation like the ongoing pandemic, face-to-face examinations are difficult to conduct. Therefore, we propose a lung disease classification model based on deep learning using non-contact auscultation. In this study, two respiratory specialists collected normal respiratory sounds and five types of abnormal sounds associated with lung disease, including those associated with four lung lesions in the left and right anterior chest and left and right posterior chest. For preprocessing and feature extraction, the noise was removed using three pass filters (low, band, and high), and respiratory sound features were extracted using the Log-Mel Spectrogram-Mel Frequency Cepstral Coefficient followed by feature stacking. Then, we propose a lung disease classification model of dense lightweight convolutional neural network-bidirectional gated recurrent unit skip connections using depthwise separable convolution based on the extracted respiratory sound information. The performance of the classification model was compared with both the baseline and the lightweight models. The results indicate that the proposed model achieves high performance and has an accuracy of 92.3%, sensitivity of 92.1%, specificity of 98.5%, and f1-score of 91.9%. Using the proposed model, we aim to contribute to the early detection of diseases during the COVID-19 pandemic.

8.
PubMed; 2022.
Preprint in English | PubMed | ID: ppcovidwho-337431

ABSTRACT

Omicron is currently the dominant SARS-CoV-2 variant and several sublineages have emerged. Questions remain about the impact of previous SARS-CoV-2 exposure on cross-variant immune responses elicited by BA.2 infection compared to BA.1. Here we show that without previous history of COVID-19, BA.2 infection induces a reduced immune response against all variants of concern (VOC) compared to BA.1 infection. The absence of ACE2 binding in sera of previously naive BA.1 and BA.2 patients indicates a lack of meaningful neutralization. In contrast, anti-spike antibody levels and neutralizing activity greatly increased in the BA.1 and BA.2 patients with a previous history of COVID-19. Transcriptome analyses of peripheral immune cells showed significant differences in immune response and specific antibody generation between BA.1 and BA.2 patients as well as significant differences in expression of specific immune genes. In summary, prior infection status significantly impacts the innate and adaptive immune response against VOC following BA.2 infection.

9.
Journal of the Korean Society of Clothing and Textiles ; 46(1):116-131, 2022.
Article in English | Scopus | ID: covidwho-1847602

ABSTRACT

This study used text mining to analyze big data to understand consumers’ demand for and perceptions of fashion masks. Based on the text-mining analysis results, a survey was conducted with those living in Korea to investigate the influence of consumers’ mask selection criteria on mask brand awareness and purchase intention for fashion masks. “Fashion mask” and “functional mask” were used as the keywords in a text-mining analysis, and an online survey of 242 respondents was conducted. The analysis results were as follows: First, the text-mining analysis extracted commonly appearing words that had a high frequency and TF-IDF, such as “COVID-19,” “fashion,” “celebrity,” “antibacterial,” and “filter.” This confirmed that during the COVID-19 pandemic, consumers have demanded masks that are both functional and fashionable. Second, among consumers’ mask selection criteria, trend and design had positive effects on face-mask brand awareness. Third, face-mask brand awareness had a positive effect on the purchase intention for both brand and fashion masks, and the purchase intention for brand masks had a positive effect on the purchase intention for fashion masks. © 2022. The Korean Society of Clothing and Textiles. All rights reserved

10.
Journal of the Architectural Institute of Korea ; 37(8):19-29, 2021.
Article in Korean | Scopus | ID: covidwho-1835531

ABSTRACT

Since the 2020 coronavirus pandemic, many elderly people have been infected in elderly care facilities, so there is a very high demand for preventing the spread of infectious diseases in elderly care facilities. In this study, as one of the measures to suppress mass cross-infection in the elderly care facility, it was attempted to derive appropriate area standards for the residents' living space. The study targets the living units of nursing homes for the elderly with 30 or more people, and the study was conducted through domestic and international standards review, infectious disease management guidelines, facility visits, and interviews with related staffs working in elderly care facilities. As a result of the study, it was found that the optimized size of the living unit is 16 people or less, and it is necessary to install an isolation room for each living unit and a special bedroom for each nursing unit. The floor area of the bedroom is 35.4㎡ (8.9㎡/person) for a 4-bed room, 27.7㎡ (9.2㎡/person) for a 3-bed room, 22.2㎡ (11.1㎡/person) for a 2-bed room, and 13.0㎡ for a single bedroom. The common living room is used by all members of the living unit in normal, but when infectious diseases are spread, it is necessary to secure at least 2.3㎡/person on the premise that half of the elderly people in a unit uses this living area simultaneously in consideration of social distancing and density. These area standards were calculated in consideration of the elderly life, provision of nursing care services, and infection control, and can be used to improve the building standards of elderly care facilities. © 2021 Architectural Institute of Korea.

13.
Process Safety and Environmental Protection ; 160:1-12, 2022.
Article in English | Web of Science | ID: covidwho-1805002

ABSTRACT

Owing to the inherent complications in membrane distillation (MD) operations, it has become a challenge to acknowledge swiftly and appropriately to safeguard the quality of effluent, particularly when the processing cost is a prominent concern. Membrane wetting in MD operations is a major concern during longterm performance. In this study, machine learning (ML) methodologies were utilized to overcome the limitations of conventional mechanistic modeling. ML applications have never been explored to investigate how operational factors, such as water flux and salt flux, are affected during long-term MD performance. Furthermore, time-dependent factors were neglected, making it difficult to analyze the relationship between effluent quality and operational factors. Therefore, this study demonstrates a novel ML-based framework designed to enhance the performance of MD. The ML-based framework consists of an autoregressive integrated moving average (ARIMA) and utilizes a unique pathway to explain the impact of time series among operational factors. The accuracy of forecasting has been explored by utilizing 180 h (180 datasets), that was further used and divided into training (165 datasets) and test datasets (15 datasets). Eventually, the ARIMA model demonstrated a highly precise relationship order between the model and experimental data, which can be further used to forecast membrane performance in terms of wetting and fouling. The selected ARIMA model (3,2,1) appears to be an adequate model for water and salt flux data which has been effectively used to capture the course of permeate water and salt flux by producing the smallest forecast RMSE. The RMSE values were observed to be 0.22 and 0.05 for water and salt flux respectively, which can better predict long time series with high frequency. These frameworks can be applied for the early prediction of membrane wetting if ample high-resolution data are available.(c) 2022 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.

14.
PubMed; 2022.
Preprint in English | PubMed | ID: ppcovidwho-334294

ABSTRACT

Type-III CRISPR-Cas systems have recently been adopted for sequence-specific detection of SARS-CoV-2. Here, we make two major advances that simultaneously limit sample handling and significantly enhance the sensitivity of SARS-CoV-2 RNA detection directly from patient samples. First, we repurpose the type III-A CRISPR complex from Thermus thermophilus (TtCsm) for programmable capture and concentration of specific RNAs from complex mixtures. The target bound TtCsm complex primarily generates two cyclic oligoadenylates (i.e., cA3 and cA4) that allosterically activate ancillary nucleases. To improve sensitivity of the diagnostic, we identify and test several ancillary nucleases (i.e., Can1, Can2, and NucC). We show that Can1 and Can2 are activated by both cA3 and cA4, and that different activators trigger changes in the substrate specificity of these nucleases. Finally, we integrate the type III-A CRISPR RNA-guided capture technique with the Can2 nuclease for 90 fM (5x104 copies/ul) detection of SARS-CoV-2 RNA directly from nasopharyngeal swab samples.

15.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-333683

ABSTRACT

Pregnant women appear to be at increased risk for severe outcomes associated with COVID-19, but the pathophysiology underlying this increased morbidity and its potential impact on the developing fetus is not well understood. In this study of pregnant women with and without COVID-19, we assessed viral and immune dynamics at the placenta during maternal SARS-CoV-2 infection. Amongst uninfected women, ACE2 was detected by immunohistochemistry in syncytiotrophoblast cells of the normal placenta during early pregnancy but was rarely seen in healthy placentas at full term. Term placentas from women infected with SARS-CoV-2, however, displayed a significant increase in ACE2 levels. Using immortalized cell lines and primary isolated placental cells, we determined the vulnerability of various placental cell types to direct infection by SARS-CoV-2 in vitro . Yet, despite the susceptibility of placental cells to SARS-CoV-2 infection, viral RNA was detected in the placentas of only a subset (~13%) of women in this cohort. Through single cell transcriptomic analyses, we found that the maternal-fetal interface of SARS-CoV-2-infected women exhibited markers associated with pregnancy complications, such as preeclampsia, and robust immune responses, including increased activation of placental NK and T cells and increased expression of interferon-related genes. Overall, this study suggests that SARS-CoV-2 is associated with immune activation at the maternal-fetal interface even in the absence of detectable local viral invasion. While this likely represents a protective mechanism shielding the placenta from infection, inflammatory changes in the placenta may also contribute to poor pregnancy outcomes and thus warrant further investigation.

16.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333613

ABSTRACT

We develop a generalizable AI-driven workflow that leverages heterogeneous HPC resources to explore the time-dependent dynamics of molecular systems. We use this workflow to investigate the mechanisms of infectivity of the SARS-CoV-2 spike protein, the main viral infection machinery. Our workflow enables more efficient investigation of spike dynamics in a variety of complex environments, including within a complete SARS-CoV-2 viral envelope simulation, which contains 305 million atoms and shows strong scaling on ORNL Summit using NAMD. We present several novel scientific discoveries, including the elucidation of the spike's full glycan shield, the role of spike glycans in modulating the infectivity of the virus, and the characterization of the flexible interactions between the spike and the human ACE2 receptor. We also demonstrate how AI can accelerate conformational sampling across different systems and pave the way for the future application of such methods to additional studies in SARS-CoV-2 and other molecular systems. ACM REFERENCE FORMAT: Lorenzo Casalino 1 , Abigail Dommer 1 , Zied Gaieb 1 , Emilia P. Barros 1 , Terra Sztain 1 , Surl-Hee Ahn 1 , Anda Trifan 2,3 , Alexander Brace 2 , Anthony Bogetti 4 , Heng Ma 2 , Hyungro Lee 5 , Matteo Turilli 5 , Syma Khalid 6 , Lillian Chong 4 , Carlos Simmerling 7 , David J. Hardy 3 , Julio D. C. Maia 3 , James C. Phillips 3 , Thorsten Kurth 8 , Abraham Stern 8 , Lei Huang 9 , John McCalpin 9 , Mahidhar Tatineni 10 , Tom Gibbs 8 , John E. Stone 3 , Shantenu Jha 5 , Arvind Ramanathan 2* , Rommie E. Amaro 1* . 2020. AI-Driven Multiscale Simulations Illuminate Mechanisms of SARS-CoV-2 Spike Dynamics. In Supercomputing '20: International Conference for High Performance Computing, Networking, Storage, and Analysis. ACM, New York, NY, USA, 14 pages. https://doi.org/finalDOI.

17.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333592

ABSTRACT

BACKGROUND: The genome of SARS-CoV-2 is susceptible to mutations during viral replication due to the errors generated by RNA-dependent RNA polymerases. These mutations enable the SARS-CoV-2 to evolve into new strains. Viral quasispecies emerge from de novo mutations that occur in individual patients. In combination, these sets of viral mutations provide distinct genetic fingerprints that reveal the patterns of transmission and have utility in contract tracing. METHODS: Leveraging thousands of sequenced SARS-CoV-2 genomes, we performed a viral pangenome analysis to identify conserved genomic sequences. We used a rapid and highly efficient computational approach that relies on k-mers, short tracts of sequence, instead of conventional sequence alignment. Using this method, we annotated viral mutation signatures that were associated with specific strains. Based on these highly conserved viral sequences, we developed a rapid and highly scalable targeted sequencing assay to identify mutations, detect quasispecies and identify mutation signatures from patients. These results were compared to the pangenome genetic fingerprints. RESULTS: We built a k-mer index for thousands of SARS-CoV-2 genomes and identified conserved genomics regions and landscape of mutations across thousands of virus genomes. We delineated mutation profiles spanning common genetic fingerprints (the combination of mutations in a viral assembly) and rare ones that occur in only small fraction of patients. We developed a targeted sequencing assay by selecting primers from the conserved viral genome regions to flank frequent mutations. Using a cohort of SARS-CoV-2 clinical samples, we identified genetic fingerprints consisting of strain-specific mutations seen across populations and de novo quasispecies mutations localized to individual infections. We compared the mutation profiles of viral samples undergoing analysis with the features of the pangenome. CONCLUSIONS: We conducted an analysis for viral mutation profiles that provide the basis of genetic fingerprints. Our study linked pangenome analysis with targeted deep sequenced SARS-CoV-2 clinical samples. We identified quasispecies mutations occurring within individual patients, mutations demarcating dominant species and the prevalence of mutation signatures, of which a significant number were relatively unique. Analysis of these genetic fingerprints may provide a way of conducting molecular contact tracing.

18.
Bulletin of the Korean Chemical Society ; 2022.
Article in English | Scopus | ID: covidwho-1787648

ABSTRACT

Peptide purity assignment is necessary for quantification of antibody. Recently, isotope dilution mass spectrometry (IDMS) has been proposed as a primary method for an accurate antibody measurement with traceability. When using the IDMS method, antibodies are measured using their signature peptide as the calibration standard. Therefore, the purity assignments of their signature peptide are essential for the standardization and harmonization of the antibody measurement. In this study, SI-traceable purity assignments of the signature peptides of an antibody were investigated by combining the IDMS and high performance liquid chromatography (HPLC) method. The final purity was calculated from the mass fraction of the total peptide determined by IDMS and the relative fraction of the target peptide determined by HPLC. The uncertainty was evaluated within the 95% confidence range. These peptides with the certified purity value can also be used for the quantification of antibodies for SARS-CoV-2. © 2022 The Authors. Bulletin of the Korean Chemical Society published by Korean Chemical Society and Wiley-VCH GmbH.

19.
Assistive Technology Outcomes and Benefits ; 16(1):1-20, 2022.
Article in English | Scopus | ID: covidwho-1787127

ABSTRACT

This explanatory sequential mixed-methods study sought to describe the implementation process of AT/AAC from school to home during the COVID-19 pandemic, including the extent to which AT/AAC was used, how AT/AAC was used, and what, if any, support the school systems provided. A researcher-designed survey was completed by 104 special educators and 45 parents. Seventeen follow-up interviews were conducted with educators and parent participants. Results of the study demonstrated the importance of clear communication, explicit expectations and procedures for AT/AAC use, and collaboration among stakeholders if AT/AAC implementation is to be as effective as possible. © ATIA 2022.

20.
J Med Entomol ; 59(1): 301-307, 2022 01 12.
Article in English | MEDLINE | ID: covidwho-1784366

ABSTRACT

The efficacy of three groups of insect growth regulators, namely juvenile hormone mimics (methoprene and pyriproxyfen), chitin synthesis inhibitors (diflubenzuron and novaluron), and molting disruptor (cyromazine) was evaluated for the first time, against Aedes albopictus Skuse (Diptera: Culicidae) larvae from 14 districts in Sabah, Malaysia. The results showed that all field populations of Ae. albopictus were susceptible towards methoprene, pyriproxyfen, diflubenzuron, novaluron, and cyromazine, with resistance ratio values ranging from 0.50-0.90, 0.60-1.00, 0.67-1.17, 0.71-1.29, and 0.74-1.07, respectively. Overall, the efficacy assessment of insect growth regulators in this study showed promising outcomes and they could be further explored as an alternative to conventional insecticides.


Subject(s)
Aedes , Juvenile Hormones/pharmacology , Mosquito Control/methods , Aedes/drug effects , Aedes/growth & development , Animals , Diflubenzuron/pharmacology , Insect Vectors/drug effects , Insect Vectors/growth & development , Insecticides/pharmacology , Larva/drug effects , Larva/growth & development , Malaysia , Methoprene/pharmacology , Phenylurea Compounds/pharmacology , Pyridines/pharmacology
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