Investigation of urinary volatile organic metabolites as potential cancer biomarkers by solid-phase microextraction in combination with gas chromatography-mass spectrometry

BACKGROUND: Non-invasive diagnostic strategies aimed at identifying biomarkers of cancer are of great interest for early cancer detection. Urine is potentially a rich source of volatile organic metabolites (VOMs) that can be used as potential cancer biomarkers. Our aim was to develop a generally reliable, rapid, sensitive, and robust analytical method for screening large numbers of urine samples, resulting in a broad spectrum of native VOMs, as a tool to evaluate the potential of these metabolites in the early diagnosis of cancer. METHODS: To investigate urinary volatile metabolites as potential cancer biomarkers, urine samples from 33 cancer patients (oncological group: 14 leukaemia, 12 colorectal and 7 lymphoma) and 21 healthy (control group, cancer-free) individuals were qualitatively and quantitatively analysed. Dynamic solid-phase microextraction in headspace mode (dHS-SPME) using a carboxenpolydimethylsiloxane (CAR/PDMS) sorbent in combination with GC-qMS-based metabolomics was applied to isolate and identify the volatile metabolites. This method provides a potential non-invasive method for early cancer diagnosis as a first approach. To fulfil this objective, three important dHS-SPME experimental parameters that influence extraction efficiency (fibre coating, extraction time and temperature of sampling) were optimised using a univariate optimisation design. The highest extraction efficiency was obtained when sampling was performed at 501C for 60min using samples with high ionic strengths (17% sodium chloride, wv 1) and under agitation. RESULTS: A total of 82 volatile metabolites belonging to distinct chemical classes were identified in the control and oncological groups. Benzene derivatives, terpenoids and phenols were the most common classes for the oncological group, whereas ketones and sulphur compounds were the main classes that were isolated from the urine headspace of healthy subjects. The results demonstrate that compound concentrations were dramatically different between cancer patients and healthy volunteers. The positive rates of 16 patients among the 82 identified were found to be statistically different (Po0.05). A significant increase in the peak area of 2-methyl3-phenyl-2-propenal, p-cymene, anisole, 4-methyl-phenol and 1,2-dihydro-1,1,6-trimethyl-naphthalene in cancer patients was observed. On average, statistically significant lower abundances of dimethyl disulphide were found in cancer patients. CONCLUSIONS: Gas chromatographic peak areas were submitted to multivariate analysis (principal component analysis and supervised linear discriminant analysis) to visualise clusters within cases and to detect the volatile metabolites that are able to differentiate cancer patients from healthy individuals. Very good discrimination within cancer groups and between cancer and control groups was achieved.

The possibility of primordial black hole direct detection

This thesis explores the possibility of directly detecting blackbody emission from Primordial Black Holes (PBHs). A PBH might form when a cosmological density uctuation with wavenumber k, that was once stretched to scales much larger than the Hubble radius during ination, reenters inside the Hubble radius at some later epoch. By modeling these uctuations with a running{tilt power{law spectrum (n(k) = n0 + a1(k)n1 + a2(k)n2 + a3(k)n3; n0 = 0:951; n1 = ????0:055; n2 and n3 unknown) each pair (n2,n3) gives a di erent n(k) curve with a maximum value (n+) located at some instant (t+). The (n+,t+) parameter space [(1:20,10????23 s) to (2:00,109 s)] has t+ = 10????23 s{109 s and n+ = 1:20{2:00 in order to encompass the formation of PBHs in the mass range 1015 g{1010M (from the ones exploding at present to the most massive known). It was evenly sampled: n+ every 0.02; t+ every order of magnitude. We thus have 41 33 = 1353 di erent cases. However, 820 of these ( 61%) are excluded (because they would provide a PBH population large enough to close the Universe) and we are left with 533 cases for further study. Although only sub{stellar PBHs ( 1M ) are hot enough to be detected at large distances we studied PBHs with 1015 g{1010M and determined how many might have formed and still exist in the Universe. Thus, for each of the 533 (n+,t+) pairs we determined the fraction of the Universe going into PBHs at each epoch ( ), the PBH density parameter (PBH), the PBH number density (nPBH), the total number of PBHs in the Universe (N), and the distance to the nearest one (d). As a rst result, 14% of these (72 cases) give, at least, one PBH within the observable Universe, one{third being sub{stellar and the remaining evenly spliting into stellar, intermediate mass and supermassive. Secondly, we found that the nearest stellar mass PBH might be at 32 pc, while the nearest intermediate mass and supermassive PBHs might be 100 and 1000 times farther, respectively. Finally, for 6% of the cases (four in 72) we might have substellar mass PBHs within 1 pc. One of these cases implies a population of 105 PBHs, with a mass of 1018 g(similar to Halley's comet), within the Oort cloud, which means that the nearest PBH might be as close as 103 AU. Such a PBH could be directly detected with a probability of 10????21 (cf. 10????32 for low{energy neutrinos). We speculate in this possibility.

Comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry combined with solid phase microextraction as a powerful tool for quantification of ethyl carbamate in fortified wines. The case study of Madeira wine

An analytical methodology based on headspace solid phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography—time-of-flight mass spectrometry (GC × GC–ToFMS) was developed for the identification and quantification of the toxic contaminant ethyl carbamate (EC) directly in fortified wines. The method performance was assessed for dry/medium dry and sweet/medium sweet model wines, and for quantification purposes, calibration plots were performed for both matrices using the ion extraction chromatography (IEC) mode (m/z 62). Good linearity was obtained with a regression coefficient (r2) higher than 0.981. A good precision was attained (R.S.D. <20%) and low detection limits (LOD) were achieved for dry (4.31 μg/L) and sweet (2.75 μg/L) model wines. The quantification limits (LOQ) and recovery for dry wines were 14.38 μg/L and 88.6%, whereas for sweet wines were 9.16 μg/L and 99.4%, respectively. The higher performance was attainted with sweet model wine, as increasing of glucose content improves the volatile compound in headspace, and a better linearity, recovery and precision were achieved. The analytical methodology was applied to analyse 20 fortified Madeira wines including different types of wine (dry, medium dry, sweet, and medium sweet) obtained from several harvests in Madeira Island (Portugal). The EC levels ranged from 54.1 μg/L (medium dry) to 162.5 μg/L (medium sweet).

Solid phase microextraction, mass spectrometry and metabolomic approaches for detection of potential urinary cancer biomarkers: a powerful strategy for breast cancer diagnosis

A sensitive assay to identify volatile organic metabolites (VOMs) as biomarkers that can accurately diagnose the onset of breast cancer using non-invasively collected clinical specimens is ideal for early detection. Therefore the aim of this study was to establish the urinary metabolomic profile of breast cancer patients and healthy individuals (control group) and to explore the VOMs as potential biomarkers in breast cancer diagnosis at early stage. Solid-phase microextraction (SPME) using CAR/PDMS sorbent combined with gas chromatography–mass spectrometry was applied to obtain metabolomic information patterns of 26 breast cancer patients and 21 healthy individuals (controls). A total of seventy-nine VOMs, belonging to distinct chemical classes, were detected and identified in control and breast cancer groups. Ketones and sulfur compounds were the chemical classes with highest contribution for both groups. Results showed that excretion values of 6 VOMs among the total of 79 detected were found to be statistically different (p < 0.05). A significant increase in the peak area of (−)-4-carene, 3-heptanone, 1,2,4-trimethylbenzene, 2-methoxythiophene and phenol, in VOMs of cancer patients relatively to controls was observed. Statiscally significant lower abundances of dimethyl disulfide were found in cancer patients. Bioanalytical data were submitted to multivariate statistics [principal component analysis (PCA)], in order to visualize clusters of cases and to detect the VOMs that are able to differentiate cancer patients from healthy individuals. Very good discrimination within breast cancer and control groups was achieved. Nevertheless, a deep study using a larger number of patients must be carried out to confirm the results.