Developing and Standardizing a Protocol for Quantitative Proton Nuclear Magnetic Resonance ( ¹ H NMR) Spectroscopy of Saliva

Metabolic profiling by ¹H NMR spectroscopy is an underutilized technology in salivary research, although preliminary studies have identified promising results in multiple fields (diagnostics, nutrition, sports physiology). Translation of preliminary findings into validated, clinically approved knowledge is hindered by variability in protocol for the collection, storage, preparation, and analysis of saliva. This study aims to evaluate the effects of differing sample pretreatments on the ¹H NMR metabolic profile of saliva. Protocol considerations are highly varied in the current literature base, including centrifugation, freeze–thaw cycles, and different NMR quantification methods. Our findings suggest that the ¹H NMR metabolite profile of saliva is resilient to any change resulting from freezing, including freezing of saliva prior to centrifuging. However, centrifugation was necessary to remove an unidentified broad peak between 1.24 and 1.3 ppm, the intensity of which correlated strongly with saliva cellular content. This peak obscured the methyl peak from lactate and significantly affected quantification. Metabolite quantification was similar for saliva centrifuged between 750<i>g</i> to 15 000<i>g</i>. Quantification of salivary metabolites was similar whether quantified using internal phosphate-buffered sodium trimethylsilyl-[2,2,3,3-²H₄]-propionate (TSP) or external TSP in a coaxial NMR tube placed inside the NMR tube containing the saliva sample. Our results suggest that the existing literature on salivary ¹H NMR will not have been adversely affected by variations of the common protocol; however, use of TSP as an internal standard without a buffered medium appears to affect metabolite quantification, notably for acetate and methanol. We include protocol recommendations to facilitate future NMR-based studies of saliva

Determining bacterial and host contributions to the human salivary metabolome

BACKGROUND: Salivary metabolomics is rapidly advancing. AIM AND METHODS: To determine the extent to which salivary metabolites reflects host or microbial metabolic activity whole-mouth saliva (WMS), parotid saliva (PS) and plasma collected contemporaneously from healthy volunteers were analysed by (1)H-NMR spectroscopy. Spectra underwent principal component analysis and k-means cluster analysis and metabolite quantification. WMS samples were cultured on both sucrose and peptide-enriched media. Correlation between metabolite concentration and bacterial load was assessed. RESULTS: WMS contained abundant short-chain fatty acids (SCFAs), which were minimal in PS and plasma. WMS spectral exhibited greater inter-individual variation than those of PS or plasma (6.7 and 3.6 fold, respectively), likely reflecting diversity of microbial metabolomes. WMS bacterial load correlated strongly with SCFA levels. Additional WMS metabolites including amines, amino acids and organic acids were positively correlated with bacterial load. Lactate, urea and citrate appeared to enter WMS via PS and the circulation. Urea correlated inversely with WMS bacterial load. CONCLUSIONS: Oral microbiota contribute significantly to the WMS metabolome. Several WMS metabolites (lactate, urea and citrate) are derived from the host circulation. WMS may be particularly useful to aid diagnosis of conditions reflective of dysbiosis. WMS could also complement other gastrointestinal fluids in future metabolomic studies

Effect of whole-body irradiation on Michaelis-Menten constants of microsomal enzyme systems of rat liver

A new methodology to analyze non-linear components in perturbative transport experiments is introduced. The methodology has been experimentally validated in the Large Helical Device for the electron heat transport channel. Electron cyclotron resonance heating with different modulation frequencies by two gyrotrons has been used to directly quantify the amplitude of the non-linear component at the inter-modulation frequencies. The measurements show significant quadratic non-linear contributions and also the absence of cubic and higher order components. The non-linear component is analyzed using the Volterra series, which is the non-linear generalization of transfer functions. This allows us to study the radial distribution of the non-linearity of the plasma and to reconstruct linear profiles where the measurements were not distorted by non-linearities. The reconstructed linear profiles are significantly different from the measured profiles, demonstrating the significant impact that non-linearity can have

Crash dieting: The effects of eating and drinking on driving performance

Previous research suggests that compared to mobile phone use, eating and drinking while driving is more common and is seen as lower risk by drivers. Nevertheless, snacking at the wheel can affect vehicle control to a similar extent as using a hands-free phone, and is actually a causal factor in more crashes. So far, though, there has not been a controlled empirical study of this problem. In an effort to fill this gap in the literature, we used the Brunel University Driving Simulator to test participants on a typical urban scenario. At designated points on the drive, which coincided with instructions to eat or drink, a critical incident was simulated by programming a pedestrian to walk in front of the car. Whilst the driving performance variables measured were relatively unaffected by eating and drinking, perceived driver workload was significantly higher and there were more crashes in the critical incident when compared to driving normally. Despite some methodological limitations of the study, when taken together with previous research, the evidence suggests that the physical demands of eating and drinking while driving can increase the risk of a crash

Predicting the Availability of Hematopoietic Stem Cell Donors Using Machine Learning

Hematopoietic stem cell transplantation (HSCT) is firmly established as an important curative therapy for patients with hematologic malignancies and other blood disorders. Apart from finding HLA-matched donors during the HSCT process, donor availability remains a key consideration as the time taken from diagnosis to transplant is recognized to adversely affect patient outcome. In this study, we aimed to develop and validate a machine learning approach to predict the availability of stem cell donors. We retrospectively collected a data set containing 10,258 verification typing requests made during the HSCT process in the British Bone Marrow Registry (BBMR) between January 1, 2013, and December 31, 2018. Three machine learning algorithms were implemented and compared, including boosted decision trees (BDTs), logistic regression, and support vector machines. Area under the receiver operating characteristic curve (AUC) was primarily used to assess the algorithms. The experimental results showed that BDTs performed better in predicting the availability of BBMR donors. The overall predictive power of the model, using AUC on the test cohort of 2052 records, was found to be 0.826. Our findings show that machine learning can predict the availability of donors with a high degree of accuracy. We propose the use of the BDT machine learning approach to predict the availability of BBMR donors and use the predictive scores during the HSCT process to ensure patients with blood cancers or disorders receive a transplant at the optimum time

Genome-wide analysis of 53,400 people with irritable bowel syndrome highlights shared genetic pathways with mood and anxiety disorders.

Irritable bowel syndrome (IBS) results from disordered brain-gut interactions. Identifying susceptibility genes could highlight the underlying pathophysiological mechanisms. We designed a digestive health questionnaire for UK Biobank and combined identified cases with IBS with independent cohorts. We conducted a genome-wide association study with 53,400 cases and 433,201 controls and replicated significant associations in a 23andMe panel (205,252 cases and 1,384,055 controls). Our study identified and confirmed six genetic susceptibility loci for IBS. Implicated genes included NCAM1, CADM2, PHF2/FAM120A, DOCK9, CKAP2/TPTE2P3 and BAG6. The first four are associated with mood and anxiety disorders, expressed in the nervous system, or both. Mirroring this, we also found strong genome-wide correlation between the risk of IBS and anxiety, neuroticism and depression (rg > 0.5). Additional analyses suggested this arises due to shared pathogenic pathways rather than, for example, anxiety causing abdominal symptoms. Implicated mechanisms require further exploration to help understand the altered brain-gut interactions underlying IBS

Measurement and Interpretation of Fermion-Pair Production at LEP energies above the Z Resonance

This paper presents DELPHI measurements and interpretations of cross-sections, forward-backward asymmetries, and angular distributions, for the e+e- -> ffbar process for centre-of-mass energies above the Z resonance, from sqrt(s) ~ 130 - 207 GeV at the LEP collider. The measurements are consistent with the predictions of the Standard Model and are used to study a variety of models including the S-Matrix ansatz for e+e- -> ffbar scattering and several models which include physics beyond the Standard Model: the exchange of Z' bosons, contact interactions between fermions, the exchange of gravitons in large extra dimensions and the exchange of sneutrino in R-parity violating supersymmetry.Comment: 79 pages, 16 figures, Accepted by Eur. Phys. J.

A Determination of the Centre-of-Mass Energy at LEP2 using Radiative 2-fermion Events

Using e+e- -> mu+mu-(gamma) and e+e- -> qqbar(gamma) events radiative to the Z pole, DELPHI has determined the centre-of-mass energy, sqrt{s}, using energy and momentum constraint methods. The results are expressed as deviations from the nominal LEP centre-of-mass energy, measured using other techniques. The results are found to be compatible with the LEP Energy Working Group estimates for a combination of the 1997 to 2000 data sets.Comment: 20 pages, 6 figures, Accepted by Eur. Phys. J.

Study of Tau-pair Production in Photon-Photon Collisions at LEP and Limits on the Anomalous Electromagnetic Moments of the Tau Lepton

Tau-pair production in the process e+e- -> e+e-tau+tau- was studied using data collected by the DELPHI experiment at LEP2 during the years 1997 - 2000. The corresponding integrated luminosity is 650 pb^{-1}. The values of the cross-section obtained are found to be in agreement with QED predictions. Limits on the anomalous magnetic and electric dipole moments of the tau lepton are deduced.Comment: 20 pages, 9 figures, Accepted by Eur. Phys. J.

Evidence for an Excess of Soft Photons in Hadronic Decays of Z^0

Soft photons inside hadronic jets converted in front of the DELPHI main tracker (TPC) in events of qqbar disintegrations of the Z^0 were studied in the kinematic range 0.2 < E_gamma < 1 GeV and transverse momentum with respect to the closest jet direction p_T < 80 MeV/c. A clear excess of photons in the experimental data as compared to the Monte Carlo predictions is observed. This excess (uncorrected for the photon detection efficiency) is (1.17 +/- 0.06 +/- 0.27) x 10^{-3} gamma/jet in the specified kinematic region, while the expected level of the inner hadronic bremsstrahlung (which is not included in the Monte Carlo) is (0.340 +/- 0.001 +/- 0.038) x 10^{-3} gamma/jet. The ratio of the excess to the predicted bremsstrahlung rate is then (3.4 +/- 0.2 +/- 0.8), which is similar in strength to the anomalous soft photon signal observed in fixed target experiments with hadronic beams.Comment: 37 pages, 9 figures, Accepted by Eur. Phys. J.