Journal: Journal of Clinical Medicine

Article Title: Breath Analysis via Gas Chromatography–Mass Spectrometry (GC-MS) in Chronic Coronary Syndrome (CCS): A Proof-of-Concept Study

doi: 10.3390/jcm13195857

Figure Lengend Snippet: Exhaled breath collection and analysis. Each patient provided a single breath sample into a Pneumopipe ® device containing an adsorbing cartridge. Volatile organic compounds (VOCs) from Tenax cartridges were collected in 500 mL Tedlar bags and analyzed using the carboxen solid phase microextraction (SPME) gas chromatography–mass spectrometry (GC-MS) technique. The SPME fiber was thermally desorbed in the GC injector at 280 °C. Data were derived from GC-MS chromatogram analysis, expressed as the ratio of the VOC area to the reference peak area, and analyzed using a partial least square discriminant analysis (PLS-DA) model.

Article Snippet: PLS-DA was performed using the PLS Toolbox software ( https://www.mdpi.com/1424-8220/21/13/4464 , https://www.mdpi.com/2072-4292/13/20/4026 , both accessed on 25 September 2024) (Eigenvector Research Inc., Wenatchee, WA, USA) in the MATLAB environment (The MathWorks Inc., Natick, MA, USA).

Techniques: Solid-phase Microextraction, Gas Chromatography, Mass Spectrometry, Gas Chromatography-Mass Spectrometry, Derivative Assay

Journal: Journal of Clinical Medicine

Article Title: Breath Analysis via Gas Chromatography–Mass Spectrometry (GC-MS) in Chronic Coronary Syndrome (CCS): A Proof-of-Concept Study

doi: 10.3390/jcm13195857

Figure Lengend Snippet: Confusion matrix of the partial least square discriminant analysis (PLS-DA) model among patients with and without the indication of myocardial revascularization.

Article Snippet: PLS-DA was performed using the PLS Toolbox software ( https://www.mdpi.com/1424-8220/21/13/4464 , https://www.mdpi.com/2072-4292/13/20/4026 , both accessed on 25 September 2024) (Eigenvector Research Inc., Wenatchee, WA, USA) in the MATLAB environment (The MathWorks Inc., Natick, MA, USA).

Techniques: Gas Chromatography-Mass Spectrometry

Journal: Journal of Clinical Medicine

Article Title: Breath Analysis via Gas Chromatography–Mass Spectrometry (GC-MS) in Chronic Coronary Syndrome (CCS): A Proof-of-Concept Study

doi: 10.3390/jcm13195857

Figure Lengend Snippet: Confusion matrix of the partial least square discriminant analysis (PLS-DA) model in the subgroup analysis (Group 1 vs. Group 2, 3 vs. Group 4, 5).

Article Snippet: PLS-DA was performed using the PLS Toolbox software ( https://www.mdpi.com/1424-8220/21/13/4464 , https://www.mdpi.com/2072-4292/13/20/4026 , both accessed on 25 September 2024) (Eigenvector Research Inc., Wenatchee, WA, USA) in the MATLAB environment (The MathWorks Inc., Natick, MA, USA).

Techniques: Gas Chromatography-Mass Spectrometry

Journal: Computational and Structural Biotechnology Journal

Article Title: Identification of a metabolic biomarker panel in rats for prediction of acute and idiosyncratic hepatotoxicity

doi: 10.1016/j.csbj.2014.08.001

Figure Lengend Snippet: The scores plot at 6 h (A) and 24 h (B) from the SIMCA PLS training set modeling using the 41 metabolites. VIP plots display the contribution of each metabolite to the modeling at 6 h (C) and 24 h (D). Each dot in the score plots represents one animal labeled as dose compound followed by high dose (H), time point (1 for 6 h and 2 for 24 h) and animal number, for example APAPH14 is animal #4 in the APAP high dose group at 6 h; while APAPH27 is animal #7 in the APAP high dose group at 24 h.

Article Snippet: For the low doses at 6 h, one out of 5 rats dosed with CCl 4 or FEL was classified as hepatotoxic using 6 and 20 metabolites Matlab PLS models, respectively.

Techniques: Labeling

Journal: Computational and Structural Biotechnology Journal

Article Title: Identification of a metabolic biomarker panel in rats for prediction of acute and idiosyncratic hepatotoxicity

doi: 10.1016/j.csbj.2014.08.001

Figure Lengend Snippet: The scores plot from the Simca PLS training set modeling using 6 metabolites at 6 h (A), 7 metabolites at 24 h (B), and 20 metabolites at both 6 h (C) and 24 h (D). The metabolites were chosen based on the VIP value from the Simca PLS modeling ( Fig. 1 C & D). Animal labeling is the same as Fig. 1 .

Article Snippet: For the low doses at 6 h, one out of 5 rats dosed with CCl 4 or FEL was classified as hepatotoxic using 6 and 20 metabolites Matlab PLS models, respectively.

Techniques: Labeling

Journal: Computational and Structural Biotechnology Journal

Article Title: Identification of a metabolic biomarker panel in rats for prediction of acute and idiosyncratic hepatotoxicity

doi: 10.1016/j.csbj.2014.08.001

Figure Lengend Snippet: Matlab PLS model predictions based on the algorithm from Scheme 2 .

Article Snippet: For the low doses at 6 h, one out of 5 rats dosed with CCl 4 or FEL was classified as hepatotoxic using 6 and 20 metabolites Matlab PLS models, respectively.

Techniques: Control