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  1. Article ; Online: In silico

    Lee, Chloe H / Koohy, Hashem

    F1000Research

    2020  Volume 9, Page(s) 145

    Abstract: Background: ...

    Abstract Background:
    MeSH term(s) Humans ; Betacoronavirus/immunology ; China ; Computer Simulation ; Coronavirus Infections/immunology ; Coronavirus Infections/prevention & control ; Coronavirus Nucleocapsid Proteins ; COVID-19 ; COVID-19 Vaccines ; Databases, Protein ; Epitopes/immunology ; Nucleocapsid Proteins/immunology ; Pandemics/prevention & control ; Peptides/immunology ; Pneumonia, Viral/prevention & control ; SARS-CoV-2 ; Spike Glycoprotein, Coronavirus/immunology ; T-Lymphocytes/immunology ; Viral Vaccines/immunology
    Chemical Substances Coronavirus Nucleocapsid Proteins ; COVID-19 Vaccines ; Epitopes ; Nucleocapsid Proteins ; Peptides ; Spike Glycoprotein, Coronavirus ; spike protein, SARS-CoV-2 ; Viral Vaccines
    Keywords covid19
    Language English
    Publishing date 2020-02-25
    Publishing country England
    Document type Journal Article
    ZDB-ID 2699932-8
    ISSN 2046-1402 ; 2046-1402
    ISSN (online) 2046-1402
    ISSN 2046-1402
    DOI 10.12688/f1000research.22507.2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: In silico identification of vaccine targets for 2019-nCoV [version 2; peer review

    Chloe H. Lee / Hashem Koohy

    F1000Research, Vol

    3 approved]

    2020  Volume 9

    Abstract: Background: The newly identified coronavirus known as 2019-nCoV has posed a serious global health threat. According to the latest report (18-February-2020), it has infected more than 72,000 people globally and led to deaths of more than 1,016 people in ... ...

    Abstract Background: The newly identified coronavirus known as 2019-nCoV has posed a serious global health threat. According to the latest report (18-February-2020), it has infected more than 72,000 people globally and led to deaths of more than 1,016 people in China. Methods: The 2019 novel coronavirus proteome was aligned to a curated database of viral immunogenic peptides. The immunogenicity of detected peptides and their binding potential to HLA alleles was predicted by immunogenicity predictive models and NetMHCpan 4.0. Results: We report in silico identification of a comprehensive list of immunogenic peptides that can be used as potential targets for 2019 novel coronavirus (2019-nCoV) vaccine development. First, we found 28 nCoV peptides identical to Severe acute respiratory syndrome-related coronavirus (SARS CoV) that have previously been characterized immunogenic by T cell assays. Second, we identified 48 nCoV peptides having a high degree of similarity with immunogenic peptides deposited in The Immune Epitope Database (IEDB). Lastly, we conducted a de novo search of 2019-nCoV 9-mer peptides that i) bind to common HLA alleles in Chinese and European population and ii) have T Cell Receptor (TCR) recognition potential by positional weight matrices and a recently developed immunogenicity algorithm, iPred, and identified in total 63 peptides with a high immunogenicity potential. Conclusions: Given the limited time and resources to develop vaccine and treatments for 2019-nCoV, our work provides a shortlist of candidates for experimental validation and thus can accelerate development pipeline.
    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2020-04-01T00:00:00Z
    Publisher F1000 Research Ltd
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: A systems approach evaluating the impact of SARS-CoV-2 variant of concern mutations on CD8+ T cell responses.

    Buckley, Paul R / Lee, Chloe H / Antanaviciute, Agne / Simmons, Alison / Koohy, Hashem

    Immunotherapy advances

    2023  Volume 3, Issue 1, Page(s) ltad005

    Abstract: T cell recognition of SARS-CoV-2 antigens after vaccination and/or natural infection has played a central role in resolving SARS-CoV-2 infections and generating adaptive immune memory. However, the clinical impact of SARS-CoV-2-specific T cell responses ... ...

    Abstract T cell recognition of SARS-CoV-2 antigens after vaccination and/or natural infection has played a central role in resolving SARS-CoV-2 infections and generating adaptive immune memory. However, the clinical impact of SARS-CoV-2-specific T cell responses is variable and the mechanisms underlying T cell interaction with target antigens are not fully understood. This is especially true given the virus' rapid evolution, which leads to new variants with immune escape capacity. In this study, we used the Omicron variant as a model organism and took a systems approach to evaluate the impact of mutations on CD8+ T cell immunogenicity. We computed an immunogenicity potential score for each SARS-CoV-2 peptide antigen from the ancestral strain and Omicron, capturing both antigen presentation and T cell recognition probabilities. By comparing ancestral vs. Omicron immunogenicity scores, we reveal a divergent and heterogeneous landscape of impact for CD8+ T cell recognition of mutated targets in Omicron variants. While T cell recognition of Omicron peptides is broadly preserved, we observed mutated peptides with deteriorated immunogenicity that may assist breakthrough infection in some individuals. We then combined our scoring scheme with an
    Language English
    Publishing date 2023-03-15
    Publishing country England
    Document type Journal Article
    ISSN 2732-4303
    ISSN (online) 2732-4303
    DOI 10.1093/immadv/ltad005
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Pediatrician-Reported Injury Prevention Anticipatory Guidance by Patient Age Group.

    Burr, William H / Lee, Lois K / Hoffman, Benjamin D / Somberg, Chloe / Zonfrillo, Mark R

    Academic pediatrics

    2023  Volume 23, Issue 3, Page(s) 610–615

    Abstract: Objective: Unintentional injuries remain a leading cause of death for children and adolescents older than 1 year. Injury prevention has long been a cornerstone of anticipatory guidance. Previous studies have established the sustained efficacy of injury ... ...

    Abstract Objective: Unintentional injuries remain a leading cause of death for children and adolescents older than 1 year. Injury prevention has long been a cornerstone of anticipatory guidance. Previous studies have established the sustained efficacy of injury prevention anticipatory guidance in pediatric primary care. This study examines the topical emphasis of injury prevention anticipatory guidance by patient age, with special attention given to the rate of water safety anticipatory guidance across 4 patient age groups.
    Methods: A nationwide, random sample of AAP member pediatricians was surveyed on their experiences, attitudes, and practices related to injury prevention anticipatory guidance, including barriers to delivering anticipatory guidance.
    Results: Of the respondents who reported providing direct patient care, 92% considered injury prevention anticipatory guidance a priority issue. The content of that injury prevention guidance varied considerably by patient age. Roughly half (53%) reported counseling families with adolescents on water safety/drowning prevention, which represents a statistically significant decrease relative to other patient age groups.
    Conclusions: Reported injury prevention anticipatory guidance is high across different mechanisms of injury. However, fewer pediatricians deliver drowning prevention anticipatory guidance to adolescents than to younger patients. Targeted outreach and education to increase injury prevention anticipatory guidance, especially for adolescent patients, should be part of a multipronged approach to decrease drowning and other injury deaths.
    MeSH term(s) Adolescent ; Child ; Humans ; Drowning/prevention & control ; Counseling ; Surveys and Questionnaires ; Attitude ; Water
    Chemical Substances Water (059QF0KO0R)
    Language English
    Publishing date 2023-01-20
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2483385-X
    ISSN 1876-2867 ; 1876-2859
    ISSN (online) 1876-2867
    ISSN 1876-2859
    DOI 10.1016/j.acap.2023.01.008
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 5914: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  5. Article: Programmed Cell Death Modifies Neural Circuits and Tunes Intrinsic Behavior.

    Kochersberger, Alison / Torkashvand, Mohammad Mahdi / Lee, Dongyeop / Baskoylu, Saba / Sengupta, Titas / Koonce, Noelle / Emerson, Chloe E / Patel, Nandan V / Colón-Ramos, Daniel / Flavell, Steven / Horvitz, H Robert / Venkatachalam, Vivek / Hammarlund, Marc

    bioRxiv : the preprint server for biology

    2023  

    Abstract: Programmed cell death is a common feature of animal development. During development of ... ...

    Abstract Programmed cell death is a common feature of animal development. During development of the
    Language English
    Publishing date 2023-09-25
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.09.11.557249
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Comparative Analysis of Metabolic Syndrome Diagnostic Criteria and Its Effects on Prevalence in a Multiethnic Population.

    Asato, Chloe B H / Nelson-Hurwitz, Denise C / Lee, Thomas / Grandinetti, Andrew

    Metabolic syndrome and related disorders

    2021  Volume 19, Issue 6, Page(s) 347–351

    Abstract: Background: ...

    Abstract Background:
    MeSH term(s) Adult ; Cross-Sectional Studies ; Cultural Diversity ; Ethnicity ; Humans ; Metabolic Syndrome/diagnosis ; Metabolic Syndrome/ethnology ; Prevalence
    Language English
    Publishing date 2021-03-01
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2151220-6
    ISSN 1557-8518 ; 1540-4196
    ISSN (online) 1557-8518
    ISSN 1540-4196
    DOI 10.1089/met.2020.0090
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 5950: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  7. Article ; Online: A robust deep learning workflow to predict CD8 + T-cell epitopes.

    Lee, Chloe H / Huh, Jaesung / Buckley, Paul R / Jang, Myeongjun / Pinho, Mariana Pereira / Fernandes, Ricardo A / Antanaviciute, Agne / Simmons, Alison / Koohy, Hashem

    Genome medicine

    2023  Volume 15, Issue 1, Page(s) 70

    Abstract: Background: T-cells play a crucial role in the adaptive immune system by triggering responses against cancer cells and pathogens, while maintaining tolerance against self-antigens, which has sparked interest in the development of various T-cell-focused ... ...

    Abstract Background: T-cells play a crucial role in the adaptive immune system by triggering responses against cancer cells and pathogens, while maintaining tolerance against self-antigens, which has sparked interest in the development of various T-cell-focused immunotherapies. However, the identification of antigens recognised by T-cells is low-throughput and laborious. To overcome some of these limitations, computational methods for predicting CD8 + T-cell epitopes have emerged. Despite recent developments, most immunogenicity algorithms struggle to learn features of peptide immunogenicity from small datasets, suffer from HLA bias and are unable to reliably predict pathology-specific CD8 + T-cell epitopes.
    Methods: We developed TRAP (T-cell recognition potential of HLA-I presented peptides), a robust deep learning workflow for predicting CD8 + T-cell epitopes from MHC-I presented pathogenic and self-peptides. TRAP uses transfer learning, deep learning architecture and MHC binding information to make context-specific predictions of CD8 + T-cell epitopes. TRAP also detects low-confidence predictions for peptides that differ significantly from those in the training datasets to abstain from making incorrect predictions. To estimate the immunogenicity of pathogenic peptides with low-confidence predictions, we further developed a novel metric, RSAT (relative similarity to autoantigens and tumour-associated antigens), as a complementary to 'dissimilarity to self' from cancer studies.
    Results: TRAP was used to identify epitopes from glioblastoma patients as well as SARS-CoV-2 peptides, and it outperformed other algorithms in both cancer and pathogenic settings. TRAP was especially effective at extracting immunogenicity-associated properties from restricted data of emerging pathogens and translating them onto related species, as well as minimising the loss of likely epitopes in imbalanced datasets. We also demonstrated that the novel metric termed RSAT was able to estimate immunogenic of pathogenic peptides of various lengths and species. TRAP implementation is available at: https://github.com/ChloeHJ/TRAP .
    Conclusions: This study presents a novel computational workflow for accurately predicting CD8 + T-cell epitopes to foster a better understanding of antigen-specific T-cell response and the development of effective clinical therapeutics.
    MeSH term(s) Humans ; Epitopes, T-Lymphocyte ; Deep Learning ; Workflow ; COVID-19 ; SARS-CoV-2 ; CD8-Positive T-Lymphocytes
    Chemical Substances Epitopes, T-Lymphocyte
    Language English
    Publishing date 2023-09-13
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2484394-5
    ISSN 1756-994X ; 1756-994X
    ISSN (online) 1756-994X
    ISSN 1756-994X
    DOI 10.1186/s13073-023-01225-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article: In silico identification of vaccine targets for 2019-nCoV

    Lee, Chloe H / Koohy, Hashem

    F1000Res

    Abstract: Background: The newly identified coronavirus known as 2019-nCoV has posed a serious global health threat. According to the latest report (18-February-2020), it has infected more than 72,000 people globally and led to deaths of more than 1,016 people in ... ...

    Abstract Background: The newly identified coronavirus known as 2019-nCoV has posed a serious global health threat. According to the latest report (18-February-2020), it has infected more than 72,000 people globally and led to deaths of more than 1,016 people in China. Methods: The 2019 novel coronavirus proteome was aligned to a curated database of viral immunogenic peptides. The immunogenicity of detected peptides and their binding potential to HLA alleles was predicted by immunogenicity predictive models and NetMHCpan 4.0. Results: We report in silico identification of a comprehensive list of immunogenic peptides that can be used as potential targets for 2019 novel coronavirus (2019-nCoV) vaccine development. First, we found 28 nCoV peptides identical to Severe acute respiratory syndrome-related coronavirus (SARS CoV) that have previously been characterized immunogenic by T cell assays. Second, we identified 48 nCoV peptides having a high degree of similarity with immunogenic peptides deposited in The Immune Epitope Database (IEDB). Lastly, we conducted a de novo search of 2019-nCoV 9-mer peptides that i) bind to common HLA alleles in Chinese and European population and ii) have T Cell Receptor (TCR) recognition potential by positional weight matrices and a recently developed immunogenicity algorithm, iPred, and identified in total 63 peptides with a high immunogenicity potential. Conclusions: Given the limited time and resources to develop vaccine and treatments for 2019-nCoV, our work provides a shortlist of candidates for experimental validation and thus can accelerate development pipeline.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #32269766
    Database COVID19

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  9. Article ; Online: In silico identification of vaccine targets for 2019-nCoV

    Lee, Chloe H. / Koohy, Hashem

    F1000Research, 9:145

    2020  

    Abstract: BACKGROUND: The newly identified coronavirus known as 2019-nCoV has posed a serious global health threat. According to the latest report (18-February-2020), it has infected more than 72,000 people globally and led to deaths of more than 1,016 people in ... ...

    Abstract BACKGROUND: The newly identified coronavirus known as 2019-nCoV has posed a serious global health threat. According to the latest report (18-February-2020), it has infected more than 72,000 people globally and led to deaths of more than 1,016 people in China. METHODS: The 2019 novel coronavirus proteome was aligned to a curated database of viral immunogenic peptides. The immunogenicity of detected peptides and their binding potential to HLA alleles was predicted by immunogenicity predictive models and NetMHCpan 4.0. RESULTS: We report in silico identification of a comprehensive list of immunogenic peptides that can be used as potential targets for 2019 novel coronavirus (2019-nCoV) vaccine development. First, we found 28 nCoV peptides identical to Severe acute respiratory syndrome-related coronavirus (SARS CoV) that have previously been characterized immunogenic by T cell assays. Second, we identified 48 nCoV peptides having a high degree of similarity with immunogenic peptides deposited in The Immune Epitope Database (IEDB). Lastly, we conducted a de novo search of 2019-nCoV 9-mer peptides that i) bind to common HLA alleles in Chinese and European population and ii) have T Cell Receptor (TCR) recognition potential by positional weight matrices and a recently developed immunogenicity algorithm, iPred, and identified in total 63 peptides with a high immunogenicity potential. CONCLUSIONS: Given the limited time and resources to develop vaccine and treatments for 2019-nCoV, our work provides a shortlist of candidates for experimental validation and thus can accelerate development pipeline.
    Keywords COVID-19 ; vaccine development ; immunogenicity ; T cell cross-reactivity ; adaptive immunity ; Coronavirus ; covid19
    Language English
    Publishing country de
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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  10. Article ; Online: Near-Room-Temperature Magnetoelectric Coupling via Spin Crossover in an Iron(II) Complex.

    Owczarek, Magdalena / Lee, Minseong / Liu, Shuanglong / Blake, Ella R / Taylor, Chloe S / Newman, Georgia A / Eckert, James C / Leal, Juan H / Semelsberger, Troy A / Cheng, Hai-Ping / Nie, Wanyi / Zapf, Vivien S

    Angewandte Chemie (International ed. in English)

    2022  Volume 61, Issue 52, Page(s) e202214335

    Abstract: Magnetoelectric coupling is achieved near room temperature in a spin crossover ... ...

    Abstract Magnetoelectric coupling is achieved near room temperature in a spin crossover Fe
    Language English
    Publishing date 2022-11-23
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 2011836-3
    ISSN 1521-3773 ; 1433-7851
    ISSN (online) 1521-3773
    ISSN 1433-7851
    DOI 10.1002/anie.202214335
    Database MEDical Literature Analysis and Retrieval System OnLINE

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