Volatile organic compounds in headspace characterize isolated bacterial strains independent of growth medium or antibiotic sensitivity.

Introduction: Early and reliable determination of bacterial strain specificity and antibiotic resistance is critical to improve sepsis treatment. Previous research demonstrated the potential of headspace analysis of volatile organic compounds (VOCs) to differentiate between various microorganisms associated with pulmonary infections in vitro. This study evaluates whether VOC analysis can also discriminate antibiotic sensitive from resistant bacterial strains when cultured on varying growth media.

Constructing bi-plots for random forest: Tutorial.

Current technological developments have allowed for a significant increase and availability of data. Consequently, this has opened enormous opportunities for the machine learning and data science field, translating into the development of new algorithms in a wide range of applications in medical, biomedical, daily-life, and national security areas. Ensemble techniques are among the pillars of the machine learning field, and they can be defined as approaches in which multiple, complex, independent/uncorrelated, predictive models are subsequently combined by either averaging or voting to yield a higher model performance.

Impact of rescanning and normalization on convolutional neural network performance in multi-center, whole-slide classification of prostate cancer.

Algorithms can improve the objectivity and efficiency of histopathologic slide analysis. In this paper, we investigated the impact of scanning systems (scanners) and cycle-GAN-based normalization on algorithm performance, by comparing different deep learning models to automatically detect prostate cancer in whole-slide images. Specifically, we compare U-Net, DenseNet and EfficientNet.

Identification of Mycobacterium tuberculosis using volatile biomarkers in culture and exhaled breath.

In this pilot study, volatile molecules produced by cultures of Mycobacterium tuberculosis were evaluated to determine whether they could be used to discriminate between uninfected and M. tuberculosis-infected macaques. Thirty seven of the culture biomarkers were detectable in macaque breath and were shown to discriminate between uninfected and infected animals with an area under the curve (AUC) of 87%.

Volatile metabolites in breath strongly correlate with gut microbiome in CD patients.

Microbiota composition and its metabolic capacity are very important for host health. Evidence suggests that gut microbiome is involved in the metabolites production by host-microbiome interaction. These metabolites can be absorbed in blood and excreted in exhaled air.

A new method to evaluate macaque health using exhaled breath: A case study of in a BSL-3 setting.

Breath is hypothesized to contain clinically relevant information, useful for the diagnosis and monitoring of disease, as well as understanding underlying pathogenesis. Nonhuman primates, such as the cynomolgus macaque, serve as an important model for the study of human disease, including over 70 different human infections. In this feasibility study, exhaled breath was successfully collected in less than 5 min under Biosafety Level 3 conditions from five anesthetized, intubated cynomolgus and rhesus macaques, before and after lung infection with The breath was subsequently analyzed using comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry.

Data Fusion in Metabolomics and Proteomics for Biomarker Discovery.

Proteomics and metabolomics provide key insights into status and dynamics of biological systems. These molecular studies reveal the complex mechanisms involved in disease or aging processes. Invaluable information can be obtained using various analytical techniques such as nuclear magnetic resonance, liquid chromatography, or gas chromatography coupled to mass spectrometry.

Increased mitochondrial ATP production capacity in brain of healthy mice and a mouse model of isolated complex I deficiency after isoflurane anesthesia.

We reported before that the minimal alveolar concentration (MAC) of isoflurane is decreased in complex I-deficient mice lacking the NDUFS4 subunit of the respiratory chain (RC) (1.55 and 0.81% at postnatal (PN) 22-25 days and 1.

Toward high-content screening of mitochondrial morphology and membrane potential in living cells.

Mitochondria are double membrane organelles involved in various key cellular processes. Governed by dedicated protein machinery, mitochondria move and continuously fuse and divide. These "mitochondrial dynamics" are bi-directionally linked to mitochondrial and cell functional state in space and time.

Quantifying small molecule phenotypic effects using mitochondrial morpho-functional fingerprinting and machine learning.

In primary fibroblasts from Leigh Syndrome (LS) patients, isolated mitochondrial complex I deficiency is associated with increased reactive oxygen species levels and mitochondrial morpho-functional changes. Empirical evidence suggests these aberrations constitute linked therapeutic targets for small chemical molecules. However, the latter generally induce multiple subtle effects, meaning that in vitro potency analysis or single-parameter high-throughput cell screening are of limited use to identify these molecules.

Photo-induction and automated quantification of reversible mitochondrial permeability transition pore opening in primary mouse myotubes.

Opening of the mitochondrial permeability transition pore (mPTP) is involved in various cellular processes including apoptosis induction. Two distinct states of mPTP opening have been identified allowing the transfer of molecules with a molecular weight <1500 Da or <300 Da. The latter state is considered to be reversible and suggested to play a role in normal cell physiology.

Towards the disease biomarker in an individual patient using statistical health monitoring.

In metabolomics, identification of complex diseases is often based on application of (multivariate) statistical techniques to the data. Commonly, each disease requires its own specific diagnostic model, separating healthy and diseased individuals, which is not very practical in a diagnostic setting. Additionally, for orphan diseases such models cannot be constructed due to a lack of available data.

Breath acetone to monitor life style interventions in field conditions: an exploratory study.

Objective: To assess whether breath acetone concentration can be used to monitor the effects of a prolonged physical activity on whole body lipolysis and hepatic ketogenesis in field conditions.

Methods: Twenty-three non-diabetic, 11 type 1 diabetic, and 17 type 2 diabetic subjects provided breath and blood samples for this study. Samples were collected during the International Four Days Marches, in the Netherlands.

NMR and pattern recognition methods in metabolomics: from data acquisition to biomarker discovery: a review.

Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms.

Confirmation of brand identity of a Trappist beer by mid-infrared spectroscopy coupled with multivariate data analysis.

Authentication of foods is of importance both to consumers and producers for e.g. confidence in label descriptions and brand protection, respectively.

Interpretation and visualization of non-linear data fusion in kernel space: study on metabolomic characterization of progression of multiple sclerosis.

Background: In the last decade data fusion has become widespread in the field of metabolomics. Linear data fusion is performed most commonly. However, many data display non-linear parameter dependences.

Simultaneous analysis of plasma and CSF by NMR and hierarchical models fusion.

Because cerebrospinal fluid (CSF) is the biofluid which interacts most closely with the central nervous system, it holds promise as a reporter of neurological disease, for example multiple sclerosis (MScl). To characterize the metabolomics profile of neuroinflammatory aspects of this disease we studied an animal model of MScl-experimental autoimmune/allergic encephalomyelitis (EAE). Because CSF also exchanges metabolites with blood via the blood-brain barrier, malfunctions occurring in the CNS may be reflected in the biochemical composition of blood plasma.

Isolated mitochondrial complex I deficiency: explorative data analysis of patient cell parameters.

Mitochondrial dysfunction has been implicated in many human diseases and off-target drug effects. Isolated deficiency of mitochondrial complex I (CI), the first complex of the oxidative phosphorylation (OXPHOS) system, can arise from mutations in nuclear DNA (nDNA)-encoded subunits. In humans, these mutations are generally associated with neurodegenerative disorders like Leigh or Leigh-like syndrome with onset in early childhood.

NMR and pattern recognition can distinguish neuroinflammation and peripheral inflammation.

Multiple Sclerosis (MScl) is a neurodegenerative disease of the CNS, associated with chronic neuroinflammation. Cerebrospinal fluid (CSF), being in closest interaction with CNS, was used to profile neuroinflammation to discover disease-specific markers. We used the commonly accepted animal model for the neuroinflammatory aspect of MScl: the experimental autoimmune/allergic encephalomyelitis (EAE).

Fusion of metabolomics and proteomics data for biomarkers discovery: case study on the experimental autoimmune encephalomyelitis.

Background: Analysis of Cerebrospinal Fluid (CSF) samples holds great promise to diagnose neurological pathologies and gain insight into the molecular background of these pathologies. Proteomics and metabolomics methods provide invaluable information on the biomolecular content of CSF and thereby on the possible status of the central nervous system, including neurological pathologies. The combined information provides a more complete description of CSF content.

Ubiquinol formation in isolated photosynthetic reaction centres monitored by time-resolved differential FTIR in combination with 2D correlation spectroscopy and multivariate curve resolution.

Two-dimensional correlation analysis was carried out in combination with multivariate curve resolution-alternating least squares (MCR-ALS) to analyse time-resolved infrared (IR) difference spectra probing photoinduced ubiquinol formation in detergent-isolated reaction centres from Rhodobacter sphaeroides. The dynamic 2D IR correlation spectra have not only allowed the determination of the concomitance or non-concomitance of different chemical events through known marker bands but also have helped identify new vibrational bands related to the complex series of photochemical and redox reactions. In particular, a strong positive band located at 1565 cm⁻¹ was found to be synchronous with the process of ubiquinol formation.

Chemometrics description of measurement error structure: study of an ultrafast absorption spectroscopy experiment.

The error structure inherent to a transient absorption spectroscopy kinetic experiment is described through the examination of the related measurement error covariance matrices in the time and the spectral direction. The systematic approach proposed by Wentzell's group to characterize the measurement error covariance matrices is used for this purpose. The goals of this study are identifying and modelling the factors contributing to the error measurement and proposing a weighting error-based scheme that can be generally used when analysing data coming from this experimental setup.

Monitoring and interpretation of photoinduced biochemical processes by rapid-scan FTIR difference spectroscopy and hybrid hard and soft modeling.

Natural photochemical processes often require special instrumentation to monitor them at a suitable time scale. Rapid-scan FTIR difference spectroscopy is one of the preferred techniques to obtain rich structural information in the scale of milliseconds about photochemical processes of complex natural systems. The difference spectra obtained by this technique enhance the fine spectroscopic changes undergone during the process but require powerful data analysis methodologies to take full advantage of the information provided.

The benzophenone S1(n,pi*) --> T1(n,pi*) states intersystem crossing reinvestigated by ultrafast absorption spectroscopy and multivariate curve resolution.

The well-known benzophenone intersystem crossing from S(1)(n,pi*) to T(1)(n,pi*) states, for which direct transition is forbidden by El-Sayed rules, is reinvestigated by subpicosecond time-resolved absorption spectroscopy and effective data analysis for various excitation wavelengths and solvents. Multivariate curve resolution alternating least-squares analysis is used to perform bilinear decomposition of the time-resolved spectra into pure spectra of overlapping transient species and their associated time-dependent concentrations. The results suggest the implication of an intermediate (IS) in the relaxation process of the S(1) state.