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  1. Article: Temperature-specific adaptations and genetic requirements in a biofilm formed by

    Bisht, Karishma / Luecke, Alex R / Wakeman, Catherine A

    Frontiers in microbiology

    2023  Volume 13, Page(s) 1032520

    Abstract: Pseudomonas ... ...

    Abstract Pseudomonas aeruginosa
    Language English
    Publishing date 2023-01-06
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2587354-4
    ISSN 1664-302X
    ISSN 1664-302X
    DOI 10.3389/fmicb.2022.1032520
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  2. Article: Interspecies Metabolic Complementation in Cystic Fibrosis Pathogens via Purine Exchange.

    Al Mahmud, Hafij / Baishya, Jiwasmika / Wakeman, Catherine A

    Pathogens (Basel, Switzerland)

    2021  Volume 10, Issue 2

    Abstract: Cystic fibrosis (CF) is a genetic disease frequently associated with chronic lung infections caused by a consortium of pathogens. It is common for auxotrophy (the inability to biosynthesize certain essential metabolites) to develop in clinical isolates ... ...

    Abstract Cystic fibrosis (CF) is a genetic disease frequently associated with chronic lung infections caused by a consortium of pathogens. It is common for auxotrophy (the inability to biosynthesize certain essential metabolites) to develop in clinical isolates of the dominant CF pathogen
    Language English
    Publishing date 2021-02-01
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2695572-6
    ISSN 2076-0817
    ISSN 2076-0817
    DOI 10.3390/pathogens10020146
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  3. Article: Development of a Polymicrobial Checkerboard Assay as a Tool for Determining Combinatorial Antibiotic Effectiveness in Polymicrobial Communities.

    Black, Caroline / Al Mahmud, Hafij / Howle, Victoria / Wilson, Sabrina / Smith, Allie C / Wakeman, Catherine A

    Antibiotics (Basel, Switzerland)

    2023  Volume 12, Issue 7

    Abstract: The checkerboard assay is a well-established tool used to determine the antimicrobial effects of two compounds in combination. Usually, data collected from the checkerboard assay use visible turbidity and optical density as a readout. While helpful in ... ...

    Abstract The checkerboard assay is a well-established tool used to determine the antimicrobial effects of two compounds in combination. Usually, data collected from the checkerboard assay use visible turbidity and optical density as a readout. While helpful in traditional checkerboard assays, these measurements become less useful in a polymicrobial context as they do not enable assessment of the drug effects on the individual members of the community. The methodology described herein allows for the determination of cell viability through selective and differential plating of each individual species in a community while retaining much of the high-throughput nature of a turbidity-based analysis and requiring no specialized equipment. This methodology further improves turbidity-based measurements by providing a distinction between bacteriostatic versus bactericidal concentrations of antibiotics. Herein, we use this method to demonstrate that the clinically used antibiotic combination of ceftazidime and gentamicin works synergistically against
    Language English
    Publishing date 2023-07-20
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2681345-2
    ISSN 2079-6382
    ISSN 2079-6382
    DOI 10.3390/antibiotics12071207
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  4. Article ; Online: In Search of the Truth: Choice of Ground-Truth for Predictive Modeling of Trauma Team Activation in Pediatric Trauma.

    Chacon, Miranda / Liu, Catherine W / Crawford, Loralai / Polydore, Hadassah / Ting, Tiffany / Wakeman, Derek / Wilson, Nicole A

    Journal of the American College of Surgeons

    2024  

    Abstract: Background: Assigning trauma team activation levels for trauma patients is a classification task that machine learning models can help optimize. However, performance is dependent upon the "ground-truth" labels used for training. Our purpose was to ... ...

    Abstract Background: Assigning trauma team activation levels for trauma patients is a classification task that machine learning models can help optimize. However, performance is dependent upon the "ground-truth" labels used for training. Our purpose was to investigate two ground-truths, the Cribari matrix and the Need for Trauma Intervention (NFTI), for labeling training data.
    Study design: Data was retrospectively collected from the institutional trauma registry and electronic medical record, including all pediatric patients (age <18 y) who triggered a trauma team activation (1/2014 - 12/2021). Three ground-truths were used to label training data: 1) Cribari (Injury Severity Score >15 = full activation), 2) NFTI (positive for any of 6 criteria = full activation), and 3) the union of Cribari+NFTI (either positive = full activation).
    Results: Of 1,366 patients triaged by trained staff, 143 (10.47%) were considered under-triaged using Cribari, 210 (15.37%) using NFTI, and 273 (19.99%) using Cribari+NFTI. NFTI and Cribari+NFTI were more sensitive to under-triage in patients with penetrating mechanisms of injury (p = 0.006), specifically stab wounds (p = 0.014), compared to Cribari, but Cribari indicated over-triage in more patients who required prehospital airway management (p < 0.001), CPR (p = 0.017), and who had mean lower GCS scores on presentation (p < 0.001). The mortality rate was higher in the Cribari over-triage group (7.14%, n = 9) compared to NFTI and Cribari+NFTI (0.00%, n = 0, p = 0.005).
    Conclusion: To prioritize patient safety, Cribari+NFTI appears best for training a machine learning algorithm to predict trauma team activation level.
    Language English
    Publishing date 2024-02-15
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1181115-8
    ISSN 1879-1190 ; 1072-7515
    ISSN (online) 1879-1190
    ISSN 1072-7515
    DOI 10.1097/XCS.0000000000001044
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    In stock of ZB MED Cologne/Königswinter

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  5. Article ; Online: Selective pressures during chronic infection drive microbial competition and cooperation.

    Baishya, Jiwasmika / Wakeman, Catherine A

    NPJ biofilms and microbiomes

    2019  Volume 5, Issue 1, Page(s) 16

    Abstract: Chronic infections often contain complex mixtures of pathogenic and commensal microorganisms ranging from aerobic and anaerobic bacteria to fungi and viruses. The microbial communities present in infected tissues are not passively co-existing but rather ... ...

    Abstract Chronic infections often contain complex mixtures of pathogenic and commensal microorganisms ranging from aerobic and anaerobic bacteria to fungi and viruses. The microbial communities present in infected tissues are not passively co-existing but rather actively interacting with each other via a spectrum of competitive and/or cooperative mechanisms. Competition versus cooperation in these microbial interactions can be driven by both the composition of the microbial community as well as the presence of host defense strategies. These interactions are typically mediated via the production of secreted molecules. In this review, we will explore the possibility that microorganisms competing for nutrients at the host-pathogen interface can evolve seemingly cooperative mechanisms by controlling the production of subsets of secreted virulence factors. We will also address interspecies versus intraspecies utilization of community resources and discuss the impact that this phenomenon might have on co-evolution at the host-pathogen interface.
    MeSH term(s) Coinfection/microbiology ; Host-Pathogen Interactions ; Humans ; Microbial Interactions ; Microbiota ; Selection, Genetic
    Language English
    Publishing date 2019-06-07
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Review
    ZDB-ID 2817021-0
    ISSN 2055-5008 ; 2055-5008
    ISSN (online) 2055-5008
    ISSN 2055-5008
    DOI 10.1038/s41522-019-0089-2
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  6. Article: Global stress response in

    Bisht, Karishma / Elmassry, Moamen M / Al Mahmud, Hafij / Bhattacharjee, Shubhra / Deonarine, Amrika / Black, Caroline / San Francisco, Michael J / Hamood, Abdul N / Wakeman, Catherine A

    bioRxiv : the preprint server for biology

    2024  

    Abstract: Versatility in carbon source utilization assists : Importance: Pseudomonas ... ...

    Abstract Versatility in carbon source utilization assists
    Importance: Pseudomonas aeruginosa
    Language English
    Publishing date 2024-03-26
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2024.03.26.586813
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  7. Article ; Online: The Innate Immune Protein Calprotectin Interacts With and Encases Biofilm Communities of

    Baishya, Jiwasmika / Everett, Jake A / Chazin, Walter J / Rumbaugh, Kendra P / Wakeman, Catherine A

    Frontiers in cellular and infection microbiology

    2022  Volume 12, Page(s) 898796

    Abstract: Calprotectin is a transition metal chelating protein of the innate immune response known to exert nutritional immunity upon microbial infection. It is abundantly released during inflammation and is therefore found at sites occupied by pathogens such ... ...

    Abstract Calprotectin is a transition metal chelating protein of the innate immune response known to exert nutritional immunity upon microbial infection. It is abundantly released during inflammation and is therefore found at sites occupied by pathogens such as
    MeSH term(s) Anti-Bacterial Agents/immunology ; Anti-Bacterial Agents/pharmacology ; Biofilms ; Extracellular Polymeric Substance Matrix/genetics ; Extracellular Polymeric Substance Matrix/immunology ; Humans ; Immunity, Innate/genetics ; Immunity, Innate/immunology ; Leukocyte L1 Antigen Complex/genetics ; Leukocyte L1 Antigen Complex/immunology ; Phagocytosis ; Pseudomonas aeruginosa/genetics ; Pseudomonas aeruginosa/immunology ; Staphylococcus aureus/genetics ; Staphylococcus aureus/immunology
    Chemical Substances Anti-Bacterial Agents ; Leukocyte L1 Antigen Complex
    Language English
    Publishing date 2022-07-13
    Publishing country Switzerland
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2619676-1
    ISSN 2235-2988 ; 2235-2988
    ISSN (online) 2235-2988
    ISSN 2235-2988
    DOI 10.3389/fcimb.2022.898796
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  8. Article ; Online: Analyzing genomic data using tensor-based orthogonal polynomials with application to synthetic RNAs.

    Nafees, Saba / Rice, Sean H / Wakeman, Catherine A

    NAR genomics and bioinformatics

    2020  Volume 2, Issue 4, Page(s) lqaa101

    Abstract: An important goal in molecular biology is to quantify both the patterns across a genomic sequence and the relationship between phenotype and underlying sequence. We propose a multivariate tensor-based orthogonal polynomial approach to characterize ... ...

    Abstract An important goal in molecular biology is to quantify both the patterns across a genomic sequence and the relationship between phenotype and underlying sequence. We propose a multivariate tensor-based orthogonal polynomial approach to characterize nucleotides or amino acids in a given sequence and map corresponding phenotypes onto the sequence space. We have applied this method to a previously published case of small transcription activating RNAs. Covariance patterns along the sequence showcased strong correlations between nucleotides at the ends of the sequence. However, when the phenotype is projected onto the sequence space, this pattern does not emerge. When doing second order analysis and quantifying the functional relationship between the phenotype and pairs of sites along the sequence, we identified sites with high regressions spread across the sequence, indicating potential intramolecular binding. In addition to quantifying interactions between different parts of a sequence, the method quantifies sequence-phenotype interactions at first and higher order levels. We discuss the strengths and constraints of the method and compare it to computational methods such as machine learning approaches. An accompanying command line tool to compute these polynomials is provided. We show proof of concept of this approach and demonstrate its potential application to other biological systems.
    Language English
    Publishing date 2020-12-11
    Publishing country England
    Document type Journal Article
    ISSN 2631-9268
    ISSN (online) 2631-9268
    DOI 10.1093/nargab/lqaa101
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  9. Article ; Online: Pseudomonas aeruginosa polymicrobial interactions during lung infection.

    Bisht, Karishma / Baishya, Jiwasmika / Wakeman, Catherine A

    Current opinion in microbiology

    2020  Volume 53, Page(s) 1–8

    Abstract: Chronic infections often contain complex polymicrobial communities that are recalcitrant to antibiotic treatment. The pathogens associated with these infectious communities are often studied in pure culture for their ability to cause disease. However, ... ...

    Abstract Chronic infections often contain complex polymicrobial communities that are recalcitrant to antibiotic treatment. The pathogens associated with these infectious communities are often studied in pure culture for their ability to cause disease. However, recent studies have begun to focus on the role of polymicrobial interactions in disease outcomes. Pseudomonas aeruginosa can colonize patients with chronic lung diseases for years and sometimes even decades. During these prolonged infections, P. aeruginosa encounters a plethora of other microbes including bacteria, fungi, and viruses. The interactions between these microbes can vary greatly, ranging from antagonistic to synergistic depending on specific host and microbe-associated contexts. These additional layers of complexity associated with chronic P. aeruginosa infections must be considered in future studies in order to fully understand the physiology of infection. Such studies focusing on the entire infectious community rather than individual species may ultimately lead to more effective therapeutic design for persistent polymicrobial infections.
    MeSH term(s) Animals ; Bacteria/classification ; Bacteria/genetics ; Bacteria/isolation & purification ; Humans ; Lung/microbiology ; Lung Diseases/microbiology ; Microbial Interactions ; Microbiota ; Pseudomonas aeruginosa/genetics ; Pseudomonas aeruginosa/growth & development ; Pseudomonas aeruginosa/physiology
    Language English
    Publishing date 2020-02-12
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Review
    ZDB-ID 1418474-6
    ISSN 1879-0364 ; 1369-5274
    ISSN (online) 1879-0364
    ISSN 1369-5274
    DOI 10.1016/j.mib.2020.01.014
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  10. Article ; Online: Selective pressures during chronic infection drive microbial competition and cooperation

    Jiwasmika Baishya / Catherine A. Wakeman

    npj Biofilms and Microbiomes, Vol 5, Iss 1, Pp 1-

    2019  Volume 9

    Abstract: Abstract Chronic infections often contain complex mixtures of pathogenic and commensal microorganisms ranging from aerobic and anaerobic bacteria to fungi and viruses. The microbial communities present in infected tissues are not passively co-existing ... ...

    Abstract Abstract Chronic infections often contain complex mixtures of pathogenic and commensal microorganisms ranging from aerobic and anaerobic bacteria to fungi and viruses. The microbial communities present in infected tissues are not passively co-existing but rather actively interacting with each other via a spectrum of competitive and/or cooperative mechanisms. Competition versus cooperation in these microbial interactions can be driven by both the composition of the microbial community as well as the presence of host defense strategies. These interactions are typically mediated via the production of secreted molecules. In this review, we will explore the possibility that microorganisms competing for nutrients at the host–pathogen interface can evolve seemingly cooperative mechanisms by controlling the production of subsets of secreted virulence factors. We will also address interspecies versus intraspecies utilization of community resources and discuss the impact that this phenomenon might have on co-evolution at the host–pathogen interface.
    Keywords Microbial ecology ; QR100-130
    Subject code 303
    Language English
    Publishing date 2019-06-01T00:00:00Z
    Publisher Nature Publishing Group
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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