LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 5 of total 5

Search options

  1. Article ; Online: Identifying susceptibility of children and adolescents to the Omicron variant (B.1.1.529)

    June Young Chun / Hwichang Jeong / Yongdai Kim

    BMC Medicine, Vol 20, Iss 1, Pp 1-

    2022  Volume 9

    Abstract: Abstract Background The Omicron variant (B.1.1.529) is estimated to be more transmissible than previous strains of SARS-CoV-2 especially among children, potentially resulting in croup which is a characteristic disease in children. Current coronavirus ... ...

    Abstract Abstract Background The Omicron variant (B.1.1.529) is estimated to be more transmissible than previous strains of SARS-CoV-2 especially among children, potentially resulting in croup which is a characteristic disease in children. Current coronavirus disease 2019 (COVID-19) cases among children might be higher because (i) school-aged children have higher contact rates and (ii) the COVID-19 vaccination strategy prioritizes the elderly in most countries. However, there have been no reports confirming the age-varying susceptibility to the Omicron variant to date. Methods We developed an age-structured compartmental model, combining age-specific contact matrix in South Korea and observed distribution of periods between each stage of infection in the national epidemiological investigation. A Bayesian inference method was used to estimate the age-specific force of infection and, accordingly, age-specific susceptibility, given epidemic data during the third (pre-Delta), fourth (Delta driven), and fifth (Omicron driven) waves in South Korea. As vaccine uptake increased, individuals who were vaccinated were excluded from the susceptible population in accordance with vaccine effectiveness against the Delta and Omicron variants, respectively. Results A significant difference between the age-specific susceptibility to the Omicron and that to the pre-Omicron variants was found in the younger age group. The rise in susceptibility to the Omicron/pre-Delta variant was highest in the 10–15 years age group (5.28 times [95% CI, 4.94–5.60]), and the rise in susceptibility to the Omicron/Delta variant was highest in the 15–19 years age group (3.21 times [95% CI, 3.12–3.31]), whereas in those aged 50 years or more, the susceptibility to the Omicron/pre-Omicron remained stable at approximately twofold. Conclusions Even after adjusting for contact pattern, vaccination status, and waning of vaccine effectiveness, the Omicron variant of SARS-CoV-2 tends to propagate more easily among children than the pre-Omicron strains.
    Keywords SARS-CoV-2 ; COVID-19 ; B.1.1.529 SARS-CoV-2 variant ; Mathematical model ; Bayesian analysis ; Child ; Medicine ; R
    Language English
    Publishing date 2022-11-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  2. Article ; Online: Smooth Function Approximation by Deep Neural Networks with General Activation Functions

    Ilsang Ohn / Yongdai Kim

    Entropy, Vol 21, Iss 7, p

    2019  Volume 627

    Abstract: There has been a growing interest in expressivity of deep neural networks. However, most of the existing work about this topic focuses only on the specific activation function such as ReLU or sigmoid. In this paper, we investigate the approximation ... ...

    Abstract There has been a growing interest in expressivity of deep neural networks. However, most of the existing work about this topic focuses only on the specific activation function such as ReLU or sigmoid. In this paper, we investigate the approximation ability of deep neural networks with a broad class of activation functions. This class of activation functions includes most of frequently used activation functions. We derive the required depth, width and sparsity of a deep neural network to approximate any Hölder smooth function upto a given approximation error for the large class of activation functions. Based on our approximation error analysis, we derive the minimax optimality of the deep neural network estimators with the general activation functions in both regression and classification problems.
    Keywords function approximation ; deep neural networks ; activation functions ; Hölder continuity ; convergence rates ; Science ; Q ; Astrophysics ; QB460-466 ; Physics ; QC1-999
    Subject code 518
    Language English
    Publishing date 2019-06-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  3. Article ; Online: Transmission onset distribution of COVID-19

    June Young Chun / Gyuseung Baek / Yongdai Kim

    International Journal of Infectious Diseases, Vol 99, Iss , Pp 403-

    2020  Volume 407

    Abstract: Objectives: The distribution of the transmission onset of COVID-19 relative to the symptom onset is a key parameter for infection control. It is often not easy to study the transmission onset time, as it is difficult to know who infected whom exactly ... ...

    Abstract Objectives: The distribution of the transmission onset of COVID-19 relative to the symptom onset is a key parameter for infection control. It is often not easy to study the transmission onset time, as it is difficult to know who infected whom exactly when. Methods: We inferred transmission onset time from 72 infector-infectee pairs in South Korea, either with known or inferred contact dates, utilizing the incubation period. Combining this data with known information of the infector's symptom onset, we could generate the transmission onset distribution of COVID-19, using Bayesian methods. Serial interval distribution could be automatically estimated from our data. Results: We estimated the median transmission onset to be 1.31 days (standard deviation, 2.64 days) after symptom onset with a peak at 0.72 days before symptom onset. The pre-symptomatic transmission proportion was 37% (95% credible interval [CI], 16–52%). The median incubation period was estimated to be 2.87 days (95% CI, 2.33–3.50 days), and the median serial interval to be 3.56 days (95% CI, 2.72–4.44 days). Conclusions: Considering that the transmission onset distribution peaked with the symptom onset and the pre-symptomatic transmission proportion is substantial, the usual preventive measures might be too late to prevent SARS-CoV-2 transmission.
    Keywords COVID-19 ; SARS-CoV-2 ; Infectious disease transmission ; Infectious disease incubation period ; Infectious and parasitic diseases ; RC109-216 ; covid19
    Subject code 535
    Language English
    Publishing date 2020-10-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  4. Article ; Online: Generalizing uncertainty decomposition theory in climate change impact assessments

    Yongdai Kim / Ilsang Ohn / Jae-Kyoung Lee / Young-Oh Kim

    Journal of Hydrology X, Vol 3, Iss , Pp - (2019)

    2019  

    Abstract: Most studies of the uncertainties in climate change impact assessments focus on each stage independently without considering correlations between stages. Therefore, it is difficult to quantify the relative contribution of each stage to the total ... ...

    Abstract Most studies of the uncertainties in climate change impact assessments focus on each stage independently without considering correlations between stages. Therefore, it is difficult to quantify the relative contribution of each stage to the total uncertainty and to identify how uncertainties are propagated as the stages proceed. In this study, we propose a new method for decomposing total uncertainty to components from individual stages. The proposed method is more theoretically sound compared to existing methods because the sum of the uncertainties from individual stages is always equal to the total uncertainty. In addition, the results of real data analysis indicate that our proposed method provides reasonable uncertainty decomposition. Keywords: Climate change impacts, Downscaling, Emission scenario, GCM, Hydrological model, Total uncertainty, Uncertainty decomposition
    Keywords Environmental engineering ; TA170-171 ; Environmental sciences ; GE1-350
    Subject code 550
    Language English
    Publishing date 2019-04-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  5. Article: Meta-markers for the differential diagnosis of lung cancer and lung disease

    Kim, Yong-In / Hye-Jin Sung / Jaesung Hwang / Je-Yoel Cho / Jung-Mo Ahn / Sang-Su Na / Yongdai Kim

    Journal of proteomics. 2016 Oct. 04, v. 148

    2016  

    Abstract: Misdiagnosis of lung cancer remains a serious problem due to the difficulty of distinguishing lung cancer from other respiratory lung diseases. As a result, the development of serum-based differential diagnostic biomarkers is in high demand. In this ... ...

    Abstract Misdiagnosis of lung cancer remains a serious problem due to the difficulty of distinguishing lung cancer from other respiratory lung diseases. As a result, the development of serum-based differential diagnostic biomarkers is in high demand. In this study, 198 clinical serum samples from non-cancer lung disease and lung cancer patients were analyzed using nLC-MRM-MS for the levels of seven lung cancer biomarker candidates. When the candidates were assessed individually, only SERPINEA4 showed statistically significant changes in the serum levels. The MRM results and clinical information were analyzed using a logistic regression analysis to select model for the best ‘meta-marker’, or combination of biomarkers for differential diagnosis. Also, under consideration of statistical interaction, variables having low significance as a single factor but statistically influencing on meta-marker model were selected. Using this probabilistic classification, the best meta-marker was determined to be made up of two proteins SERPINA4 and PON1 with age factor. This meta-marker showed an enhanced differential diagnostic capability (AUC=0.915) for distinguishing the two patient groups. Our results suggest that a statistical model can determine optimal meta-markers, which may have better specificity and sensitivity than a single biomarker and thus improve the differential diagnosis of lung cancer and lung disease patients.Diagnosing lung cancer commonly involves the use of radiographic methods. However, an imaging-based diagnosis may fail to differentiate lung cancer from non-cancerous lung disease. In this study, we examined several serum proteins in the sera of 198 lung cancer and non-cancerous lung disease patients by multiple-reaction monitoring. We then used a combination of variables to generate a meta-marker model that is useful as a differential diagnostic biomarker.
    Keywords biomarkers ; blood proteins ; blood serum ; lung neoplasms ; monitoring ; patients ; radiography ; regression analysis ; statistical models
    Language English
    Dates of publication 2016-1004
    Size p. 36-43.
    Publishing place Elsevier B.V.
    Document type Article
    ZDB-ID 2400835-7
    ISSN 1876-7737 ; 1874-3919
    ISSN (online) 1876-7737
    ISSN 1874-3919
    DOI 10.1016/j.jprot.2016.04.052
    Database NAL-Catalogue (AGRICOLA)

    Full text online

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

To top