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  • 1.
    Antti, Henrik
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    Fahlgren, Anna
    Umeå universitet, Medicinska fakulteten, Institutionen för molekylärbiologi (Medicinska fakulteten). Umeå universitet, Medicinska fakulteten, Umeå Centre for Microbial Research (UCMR).
    Näsström, Elin
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    Kouremenos, Konstantinos
    Umeå universitet, Medicinska fakulteten, Institutionen för molekylärbiologi (Medicinska fakulteten). Umeå universitet, Medicinska fakulteten, Molekylär Infektionsmedicin, Sverige (MIMS). Umeå universitet, Medicinska fakulteten, Umeå Centre for Microbial Research (UCMR).
    Sundén-Cullberg, Jonas
    Guo, Yongzhi
    Moritz, Thomas
    Wolf-Watz, Hans
    Umeå universitet, Medicinska fakulteten, Institutionen för molekylärbiologi (Medicinska fakulteten). Umeå universitet, Medicinska fakulteten, Molekylär Infektionsmedicin, Sverige (MIMS). Umeå universitet, Medicinska fakulteten, Umeå Centre for Microbial Research (UCMR).
    Johansson, Anders
    Umeå universitet, Medicinska fakulteten, Institutionen för klinisk mikrobiologi, Infektionssjukdomar.
    Fällman, Maria
    Umeå universitet, Medicinska fakulteten, Institutionen för molekylärbiologi (Medicinska fakulteten). Umeå universitet, Medicinska fakulteten, Molekylär Infektionsmedicin, Sverige (MIMS). Umeå universitet, Medicinska fakulteten, Umeå Centre for Microbial Research (UCMR).
    Metabolic profiling for detection of staphylococcus aureus infection and antibiotic resistance2013Ingår i: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 8, nr 2, artikel-id e56971Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Due to slow diagnostics, physicians must optimize antibiotic therapies based on clinical evaluation of patients without specific information on causative bacteria. We have investigated metabolomic analysis of blood for the detection of acute bacterial infection and early differentiation between ineffective and effective antibiotic treatment. A vital and timely therapeutic difficulty was thereby addressed: the ability to rapidly detect treatment failures because of antibiotic-resistant bacteria. Methicillin-resistant (MRSA) and methicillin-sensitive (MSSA) were used and for infecting mice, while natural MSSA infection was studied in humans. Samples of bacterial growth media, the blood of infected mice and of humans were analyzed with combined Gas Chromatography/Mass Spectrometry. Multivariate data analysis was used to reveal the metabolic profiles of infection and the responses to different antibiotic treatments. experiments resulted in the detection of 256 putative metabolites and mice infection experiments resulted in the detection of 474 putative metabolites. Importantly, ineffective and effective antibiotic treatments were differentiated already two hours after treatment start in both experimental systems. That is, the ineffective treatment of MRSA using cloxacillin and untreated controls produced one metabolic profile while all effective treatment combinations using cloxacillin or vancomycin for MSSA or MRSA produced another profile. For further evaluation of the concept, blood samples of humans admitted to intensive care with severe sepsis were analyzed. One hundred thirty-three putative metabolites differentiated severe MSSA sepsis (n = 6) from severe sepsis (n = 10) and identified treatment responses over time. Combined analysis of human, , and mice samples identified 25 metabolites indicative of effective treatment of sepsis. Taken together, this study provides a proof of concept of the utility of analyzing metabolite patterns in blood for early differentiation between ineffective and effective antibiotic treatment in acute infections.

  • 2.
    Kouremenos, Konstantinos A
    et al.
    Umeå universitet, Medicinska fakulteten, Institutionen för molekylärbiologi (Medicinska fakulteten).
    Johansson, Mikael
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Marriott, Philip J
    Monash University, Victoria, Australia.
    Advances in gas chromatographic methods for the identification of biomarkers in cancer2012Ingår i: Journal of Cancer, ISSN 1837-9664, E-ISSN 1837-9664, Vol. 3, s. 404-420Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Screening complex biological specimens such as exhaled air, tissue, blood and urine to identify biomarkers in different forms of cancer has become increasingly popular over the last decade, mainly due to new instruments and improved bioinformatics. However, despite some progress, the identification of biomarkers has shown to be a difficult task with few new biomarkers (excluding recent genetic markers) being considered for introduction to clinical analysis. This review describes recent advances in gas chromatographic methods for the identification of biomarkers in the detection, diagnosis and treatment of cancer. It presents a general overview of cancer metabolism, the current biomarkers used for cancer diagnosis and treatment, a background to metabolic changes in tumors, an overview of current GC methods, and collectively presents the scope and outlook of GC methods in oncology.

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