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- Fletcher, John, 1978, et al.
(författare)
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Uncovering new challenges in bio-analysis with ToF-SIMS
- 2008
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Ingår i: Applied Surface Science. - : Elsevier BV. - 0169-4332. ; 255:4, s. 1264-1270
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Konferensbidrag (refereegranskat)abstract
- The introduction of cluster ion beams for routine SIMS analysis has greatly improved the prospects for characterising biological samples. The ultimate quality of the secondary ion image remains limited by the efficiency of the primary beam. Without overcoming the low ionisation probabilities associated with SIMS, the highest lateral resolution available for molecular imaging becomes limited by the statistical probability of any ions being generated from the area of the pixel. C(60)(+) primary ions are currently the most efficient available for routine analysis but although commercial systems have been demonstrated to produce spot sizes under 200 nm, focusing the beam produced in such electron impact sources results in rather low ion currents. The time scale for such high lateral resolution analysis can become impractical on conventional time-of-flight instruments. Molecular depth pro. ling capability has been revealed using SF(5)(+) and C(60)(+) ion beams and recent work has advanced the technique by combining the pro. ling and imaging abilities of these high efficiency projectiles to generate 3D molecular maps of biological systems. In this paper we discuss the challenges associated with 2D and 3D bio-analysis with emphasis on how instrumental advances aid such investigations yet demonstrating the obstacles that need to be overcome using a range of model and real world biological samples. We discuss complications with the biological matrix, challenges in manipulating and visualising the data and look at how instrumental advantages might aid the routine generation of these 3D molecular maps. (C) 2008 Elsevier B. V. All rights reserved.
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| 6. |
- Vaidyanathan, Seetharaman, et al.
(författare)
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Exploratory analysis of TOF-SIMS data from biological surfaces
- 2008
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Ingår i: Applied Surface Science. - : Elsevier BV. - 0169-4332. ; 255:4, s. 1599-1602
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Konferensbidrag (refereegranskat)abstract
- The application of multivariate analytical tools enables simplification of TOF-SIMS datasets so that useful information can be extracted from complex spectra and images, especially those that do not give readily interpretable results. There is however a challenge in understanding the outputs from such analyses. The problem is complicated when analysing images, given the additional dimensions in the dataset. Here we demonstrate how the application of simple pre-processing routines can enable the interpretation of TOF-SIMS spectra and images. For the spectral data, TOF-SIMS spectra used to discriminate bacterial isolates associated with urinary tract infection were studied. Using different criteria for picking peaks before carrying out PC-DFA enabled identification of the discriminatory information with greater certainty. For the image data, an air-dried salt stressed bacterial sample, discussed in another paper by us in this issue, was studied. Exploration of the image datasets with and without normalisation prior to multivariate analysis by PCA or MAF resulted in different regions of the image being highlighted by the techniques. (C) 2008 Elsevier B. V. All rights reserved.
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| 7. |
- Fletcher, John, 1978, et al.
(författare)
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Rapid discrimination of the causal agents of urinary tract infection using ToF-SIMS with chemometric cluster analysis
- 2006
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Ingår i: Applied Surface Science. - : Elsevier BV. - 0169-4332. ; 252:19, s. 6869-6874
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Konferensbidrag (refereegranskat)abstract
- Advances in time of flight secondary ion mass spectrometry (ToF-SIMS) have enabled this technique to become a powerful tool for the analysis of biological samples. Such samples are often very complex and as a result full interpretation of the acquired data can be extremely difficult. To simplify the interpretation of these information rich data, the use of chemometric techniques is becoming widespread in the ToF-SIMS community. Here we discuss the application of principal components-discriminant function analysis (PC-DFA) to the separation and classification of a number of bacterial samples that are known to be major causal agents of urinary tract infection. A large data set has been generated using three biological replicates of each isolate and three machine replicates were acquired from each biological replicate. Ordination plots generated using the PC-DFA are presented demonstrating strain level discrimination of the bacteria. The results are discussed in terms of biological differences between certain species and with reference to FT-IR, Raman spectroscopy and pyrolysis mass spectrometric studies of similar samples. (c) 2006 Elsevier B.V. All rights reserved.
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| 8. |
- Garcia-Closas, Montserrat, et al.
(författare)
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Heterogeneity of breast cancer associations with five susceptibility loci by clinical and pathological characteristics
- 2008
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Ingår i: PLoS genetics. - : Public Library of Science (PLoS). - 1553-7404. ; 4:4, s. e1000054-
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Tidskriftsartikel (refereegranskat)abstract
- A three-stage genome-wide association study recently identified single nucleotide polymorphisms (SNPs) in five loci (fibroblast growth receptor 2 (FGFR2), trinucleotide repeat containing 9 (TNRC9), mitogen-activated protein kinase 3 K1 (MAP3K1), 8q24, and lymphocyte-specific protein 1 (LSP1)) associated with breast cancer risk. We investigated whether the associations between these SNPs and breast cancer risk varied by clinically important tumor characteristics in up to 23,039 invasive breast cancer cases and 26,273 controls from 20 studies. We also evaluated their influence on overall survival in 13,527 cases from 13 studies. All participants were of European or Asian origin. rs2981582 in FGFR2 was more strongly related to ER-positive (per-allele OR (95%CI) = 1.31 (1.27-1.36)) than ER-negative (1.08 (1.03-1.14)) disease (P for heterogeneity = 10(-13)). This SNP was also more strongly related to PR-positive, low grade and node positive tumors (P = 10(-5), 10(-8), 0.013, respectively). The association for rs13281615 in 8q24 was stronger for ER-positive, PR-positive, and low grade tumors (P = 0.001, 0.011 and 10(-4), respectively). The differences in the associations between SNPs in FGFR2 and 8q24 and risk by ER and grade remained significant after permutation adjustment for multiple comparisons and after adjustment for other tumor characteristics. Three SNPs (rs2981582, rs3803662, and rs889312) showed weak but significant associations with ER-negative disease, the strongest association being for rs3803662 in TNRC9 (1.14 (1.09-1.21)). rs13281615 in 8q24 was associated with an improvement in survival after diagnosis (per-allele HR = 0.90 (0.83-0.97). The association was attenuated and non-significant after adjusting for known prognostic factors. Our findings show that common genetic variants influence the pathological subtype of breast cancer and provide further support for the hypothesis that ER-positive and ER-negative disease are biologically distinct. Understanding the etiologic heterogeneity of breast cancer may ultimately result in improvements in prevention, early detection, and treatment.
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