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  1. Article ; Online: Black swans or red herrings - Inflammatory derangement after cardiac arrest.

    Kernan, Kate F / Kochanek, Patrick M

    Resuscitation

    2021  Volume 171, Page(s) 100–102

    MeSH term(s) Heart Arrest/therapy ; Humans
    Language English
    Publishing date 2021-12-14
    Publishing country Ireland
    Document type Editorial ; Research Support, N.I.H., Extramural ; Comment
    ZDB-ID 189901-6
    ISSN 1873-1570 ; 0300-9572
    ISSN (online) 1873-1570
    ISSN 0300-9572
    DOI 10.1016/j.resuscitation.2021.12.002
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  2. Article ; Online: Should COVID-19 take advice from rheumatologists?

    Kernan, Kate F / Canna, Scott W

    The Lancet. Rheumatology

    2020  Volume 2, Issue 6, Page(s) e310–e311

    Keywords covid19
    Language English
    Publishing date 2020-05-07
    Publishing country England
    Document type Journal Article
    ISSN 2665-9913
    ISSN (online) 2665-9913
    DOI 10.1016/S2665-9913(20)30129-6
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  3. Article ; Online: Should COVID-19 take advice from rheumatologists?

    Kernan, Kate F / Canna, Scott W

    The Lancet Rheumatology

    2020  Volume 2, Issue 6, Page(s) e310–e311

    Keywords covid19
    Language English
    Publisher Elsevier BV
    Publishing country us
    Document type Article ; Online
    ISSN 2665-9913
    DOI 10.1016/s2665-9913(20)30129-6
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Subtypes and Mimics of Sepsis.

    Kellum, John A / Formeck, Cassandra L / Kernan, Kate F / Gómez, Hernando / Carcillo, Joseph A

    Critical care clinics

    2022  Volume 38, Issue 2, Page(s) 195–211

    Abstract: Sepsis is a heterogenous and imprecise syndrome that includes multiple phenotypes, some of which are amenable to specific therapies. Developing new therapies for sepsis will require focusing on subsets of patients. Key to improving care is evaluating ... ...

    Abstract Sepsis is a heterogenous and imprecise syndrome that includes multiple phenotypes, some of which are amenable to specific therapies. Developing new therapies for sepsis will require focusing on subsets of patients. Key to improving care is evaluating patients for sepsis mimics and treatable diseases whose manifestations lead to a clinical classification of sepsis. Because sepsis is common, it is easy to overlook unusual causes of organ failure and succumb to confirmation bias about the nature of an illness. Careful attention to medical and family histories, focused diagnostic testing, and subspecialty input can help identify potentially treatable diseases masquerading as typical sepsis.
    MeSH term(s) Humans ; Sepsis/diagnosis ; Sepsis/therapy
    Language English
    Publishing date 2022-04-04
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 1006423-0
    ISSN 1557-8232 ; 0749-0704
    ISSN (online) 1557-8232
    ISSN 0749-0704
    DOI 10.1016/j.ccc.2021.11.013
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  6. Article: Refining empiric subgroups of pediatric sepsis using machine-learning techniques on observational data.

    Qin, Yidi / Caldino Bohn, Rebecca I / Sriram, Aditya / Kernan, Kate F / Carcillo, Joseph A / Kim, Soyeon / Park, Hyun Jung

    Frontiers in pediatrics

    2023  Volume 11, Page(s) 1035576

    Abstract: Sepsis contributes to 1 of every 5 deaths globally with 3 million per year occurring in children. To improve clinical outcomes in pediatric sepsis, it is critical to avoid "one-size-fits-all" approaches and to employ a precision medicine approach. To ... ...

    Abstract Sepsis contributes to 1 of every 5 deaths globally with 3 million per year occurring in children. To improve clinical outcomes in pediatric sepsis, it is critical to avoid "one-size-fits-all" approaches and to employ a precision medicine approach. To advance a precision medicine approach to pediatric sepsis treatments, this review provides a summary of two phenotyping strategies, empiric and machine-learning-based phenotyping based on multifaceted data underlying the complex pediatric sepsis pathobiology. Although empiric and machine-learning-based phenotypes help clinicians accelerate the diagnosis and treatments, neither empiric nor machine-learning-based phenotypes fully encapsulate all aspects of pediatric sepsis heterogeneity. To facilitate accurate delineations of pediatric sepsis phenotypes for precision medicine approach, methodological steps and challenges are further highlighted.
    Language English
    Publishing date 2023-01-30
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2711999-3
    ISSN 2296-2360
    ISSN 2296-2360
    DOI 10.3389/fped.2023.1035576
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  7. Article ; Online: Genetic variation in genes of inborn errors of immunity in children with unexplained encephalitis.

    Malik, Devesh / Simon, Dennis W / Thakkar, Kavita / Rajan, Deepa S / Kernan, Kate F

    Genes and immunity

    2022  Volume 23, Issue 7, Page(s) 235–239

    Abstract: Pediatric encephalitis has significant morbidity and mortality, yet 50% of cases are unexplained. Host genetics plays a role in encephalitis' development; however, the contributing variants are poorly understood. One child with anti-NMDA receptor ... ...

    Abstract Pediatric encephalitis has significant morbidity and mortality, yet 50% of cases are unexplained. Host genetics plays a role in encephalitis' development; however, the contributing variants are poorly understood. One child with anti-NMDA receptor encephalitis and ten with unexplained encephalitis underwent whole genome sequencing to identify rare candidate variants in genes known to cause monogenic immunologic and neurologic disorders, and polymorphisms associated with increased disease risk. Using the professional Human Genetic Mutation Database (Qiagen), we divided the candidate variants into three categories: monogenic deleterious or potentially deleterious variants (1) in a disease-consistent inheritance pattern; (2) in carrier states; and (3) disease-related polymorphisms. Six patients (55%) had a deleterious or potentially deleterious variant in a disease-consistent inheritance pattern, five (45%) were heterozygous carriers for an autosomal recessive condition, and six (55%) carried a disease-related polymorphism. Finally, seven (64%) had more than one variant, suggesting possible polygenetic risk. Among variants identified were those implicated in atypical hemolytic uremic syndrome, common variable immunodeficiency, hemophagocytic lymphohistiocytosis, and systemic lupus erythematosus. This preliminary study shows genetic variation related to inborn errors of immunity in acute pediatric encephalitis. Future research is needed to determine if these variants play a functional role in the development of unexplained encephalitis.
    MeSH term(s) Humans ; Child ; Mutation ; Heterozygote ; Polymorphism, Genetic ; Lymphohistiocytosis, Hemophagocytic ; Encephalitis/genetics ; Genetic Variation
    Language English
    Publishing date 2022-10-05
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
    ZDB-ID 2060566-3
    ISSN 1476-5470 ; 1466-4879
    ISSN (online) 1476-5470
    ISSN 1466-4879
    DOI 10.1038/s41435-022-00185-5
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    Zs.A 5592: Show issues Location:
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  8. Article ; Online: Deep neural networks with knockoff features identify nonlinear causal relations and estimate effect sizes in complex biological systems.

    Fan, Zhenjiang / Kernan, Kate F / Sriram, Aditya / Benos, Panayiotis V / Canna, Scott W / Carcillo, Joseph A / Kim, Soyeon / Park, Hyun Jung

    GigaScience

    2023  Volume 12

    Abstract: Background: Learning the causal structure helps identify risk factors, disease mechanisms, and candidate therapeutics for complex diseases. However, although complex biological systems are characterized by nonlinear associations, existing bioinformatic ... ...

    Abstract Background: Learning the causal structure helps identify risk factors, disease mechanisms, and candidate therapeutics for complex diseases. However, although complex biological systems are characterized by nonlinear associations, existing bioinformatic methods of causal inference cannot identify the nonlinear relationships and estimate their effect size.
    Results: To overcome these limitations, we developed the first computational method that explicitly learns nonlinear causal relations and estimates the effect size using a deep neural network approach coupled with the knockoff framework, named causal directed acyclic graphs using deep learning variable selection (DAG-deepVASE). Using simulation data of diverse scenarios and identifying known and novel causal relations in molecular and clinical data of various diseases, we demonstrated that DAG-deepVASE consistently outperforms existing methods in identifying true and known causal relations. In the analyses, we also illustrate how identifying nonlinear causal relations and estimating their effect size help understand the complex disease pathobiology, which is not possible using other methods.
    Conclusions: With these advantages, the application of DAG-deepVASE can help identify driver genes and therapeutic agents in biomedical studies and clinical trials.
    MeSH term(s) Neural Networks, Computer ; Computer Simulation ; Causality
    Language English
    Publishing date 2023-05-22
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2708999-X
    ISSN 2047-217X ; 2047-217X
    ISSN (online) 2047-217X
    ISSN 2047-217X
    DOI 10.1093/gigascience/giad044
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  9. Article ; Online: Hyperferritinemia and inflammation.

    Kernan, Kate F / Carcillo, Joseph A

    International immunology

    2017  Volume 29, Issue 9, Page(s) 401–409

    Abstract: Understanding of ferritin biology has traditionally centered on its role in iron storage and homeostasis, with low ferritin levels indicative of deficiency and high levels indicative of primary or secondary hemochromatosis. However, further work has ... ...

    Abstract Understanding of ferritin biology has traditionally centered on its role in iron storage and homeostasis, with low ferritin levels indicative of deficiency and high levels indicative of primary or secondary hemochromatosis. However, further work has shown that iron, redox biology and inflammation are inexorably linked. During infection, increased ferritin levels represent an important host defense mechanism that deprives bacterial growth of iron and protects immune cell function. It may also be protective, limiting the production of free radicals and mediating immunomodulation. Additionally, hyperferritinemia is a key acute-phase reactants, used by clinicians as an indication for therapeutic intervention, aimed at controlling inflammation in high-risk patients. One school of thought maintains that hyperferritinemia is an 'innocent bystander' biomarker of uncontrolled inflammation that can be used to gauge effectiveness of intervention. Other schools of thought maintain that ferritin induction could be a protective negative regulatory loop. Others maintain that ferritin is a key mediator of immune dysregulation, especially in extreme hyperferritinemia, via direct immune-suppressive and pro-inflammatory effects. There is a clear need for further investigation of the role of ferritin in uncontrolled inflammatory conditions both as a biomarker and mediator of disease because its occurrence identifies patients with high mortality risk and its resolution predicts their improved survival.
    MeSH term(s) Acute-Phase Reaction ; Animals ; Cataract/congenital ; Ferritins/metabolism ; Hemochromatosis ; Humans ; Immunity, Innate ; Immunomodulation ; Inflammation ; Iron/metabolism ; Iron Metabolism Disorders/congenital
    Chemical Substances Ferritins (9007-73-2) ; Iron (E1UOL152H7)
    Language English
    Publishing date 2017-05-24
    Publishing country England
    Document type Journal Article ; Review ; Research Support, N.I.H., Extramural
    ZDB-ID 1013745-2
    ISSN 1460-2377 ; 0953-8178
    ISSN (online) 1460-2377
    ISSN 0953-8178
    DOI 10.1093/intimm/dxx031
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  10. Article: Rapid Whole Genome Sequencing and Fulfilling the Promise of Precision Pediatric Critical Care.

    Kernan, Kate F / Ghaloul-Gonzalez, Lina / Vockley, Jerry / Carcillo, Joseph A

    Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies

    2019  Volume 20, Issue 11, Page(s) 1085–1086

    MeSH term(s) Child ; Critical Care ; Humans ; Intensive Care Units, Pediatric ; Whole Genome Sequencing
    Language English
    Publishing date 2019-11-05
    Publishing country United States
    Document type Editorial ; Research Support, N.I.H., Extramural ; Comment
    ZDB-ID 2052349-X
    ISSN 1947-3893 ; 1529-7535
    ISSN (online) 1947-3893
    ISSN 1529-7535
    DOI 10.1097/PCC.0000000000002082
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    Zs.MO 472: Show issues

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