Rapid and accurate method for estimating molecular weights of organic compounds from low resolution mass spectra

1992 ◽  
Vol 16 (3) ◽  
pp. 193-202 ◽  
Author(s):  
Donald R. Scott
Keyword(s):  
Organic Compounds ◽  
Mass Spectra ◽  
Accurate Method ◽  
Low Resolution ◽  
Molecular Weights ◽  
Resolution Mass

Diazabenzenes. I. Synthesis of some t-butylpyrazines and their N-oxides

1972 ◽  
Vol 25 (12) ◽  
pp. 2671 ◽  
Author(s):  
RF Evans ◽  
KN Mewett
Keyword(s):  
Steric Hindrance ◽  
Mass Spectra ◽  
Ammonium Acetate ◽  
Spectroscopic Properties ◽  
Iron Pentacarbonyl ◽  
Membered Ring ◽  
Low Resolution ◽  
Butyl Lithium ◽  
Pyrazine Ring ◽  
Resolution Mass

Steric hindrance prevented formation of tetra-t-butylpyrazine either when pivaloin was heated with ammonium acetate or when pivalil monooxime was reduced with zinc and alkali. Diminution of the steric hindrance of the t-butyl groups by masking them by incorporation into a seven-membered ring containing sulphur was of no avail. 2,5-Di-t- butylpyrazine resulted from the analogous reduction of t-butyl-glyoxal dioxime and could be converted into its N-oxide and N,N?-dioxide. t- Butyl-lithium reacted with the pyrazine and the mono-N-oxide to give a mixture of products including 2,3,5-tri-t-butylpyrazine whose spectroscopic properties suggested a buckling of the pyrazine ring. Benzonitrile and diphenylacetylene reacted independently in the presence of iron pentacarbonyl and gave, inter alia, 2,4,6-triphenyl- 1,3,5-triazine and hexaphenylbenzene respectively. ��� The most prominent features of the low resolution mass spectra of these pyrazines and some of their precursors are discussed and rationalized.

Influence of errors and matching criteria upon the retrieval of binary coded low resolution mass spectra

1979 ◽  
Vol 51 (3) ◽  
pp. 420-423 ◽  
Author(s):  
Geert. Van Marlen ◽  
Auke. Dijkstra ◽  
Henk A. Van't Klooster
Keyword(s):  
Mass Spectra ◽  
Low Resolution ◽  
Matching Criteria ◽  
Resolution Mass

scholarly journals High-resolution serum proteomic features for ovarian cancer detection.

2004 ◽  
Vol 11 (2) ◽  
pp. 163-178 ◽  
Author(s):  
T P Conrads ◽  
V A Fusaro ◽  
S Ross ◽  
D Johann ◽  
V Rajapakse ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
High Resolution ◽  
Sensitivity And Specificity ◽  
Mass Spectra ◽  
Spectral Feature ◽  
Low Resolution ◽  
Mass Spectral ◽  
High Resolution Mass ◽  
Process Error ◽  
Resolution Mass

Serum proteomic pattern diagnostics is an emerging paradigm employing low-resolution mass spectrometry (MS) to generate a set of biomarker classifiers. In the present study, we utilized a well-controlled ovarian cancer serum study set to compare the sensitivity and specificity of serum proteomic diagnostic patterns acquired using a high-resolution versus a low-resolution MS platform. In blinded testing sets, the high-resolution mass spectral data contained multiple diagnostic signatures that were superior to the low-resolution spectra in terms of sensitivity and specificity (P<0.00001) throughout the range of modeling conditions. Four mass spectral feature set patterns acquired from data obtained exclusively with the high-resolution mass spectrometer were 100% specific and sensitive in their diagnosis of serum samples as being acquired from either unaffected patients or those suffering from ovarian cancer. Important to the future of proteomic pattern diagnostics is the ability to recognize inferior spectra statistically, so that those resulting from a specific process error are recognized prior to their potentially incorrect (and damaging) diagnosis. To meet this need, we have developed a series of quality-assurance and in-process control procedures to (a) globally evaluate sources of sample variability, (b) identify outlying mass spectra, and (c) develop quality-control release specifications. From these quality-assurance and control (QA/QC) specifications, we identified 32 mass spectra out of the total 248 that showed statistically significant differences from the norm. Hence, 216 of the initial 248 high-resolution mass spectra were determined to be of high quality and were remodeled by pattern-recognition analysis. Again, we obtained four mass spectral feature set patterns that also exhibited 100% sensitivity and specificity in blinded validation tests (68/68 cancer: including 18/18 stage I, and 43/43 healthy). We conclude that (a) the use of high-resolution MS yields superior classification patterns as compared with those obtained with lower resolution instrumentation; (b) although the process error that we discovered did not have a deleterious impact on the present results obtained from proteomic pattern analysis, the major source of spectral variability emanated from mass spectral acquisition, and not bias at the clinical collection site; (c) this variability can be reduced and monitored through the use of QA/QC statistical procedures; (d) multiple and distinct proteomic patterns, comprising low molecular weight biomarkers, detected by high-resolution MS achieve accuracies surpassing individual biomarkers, warranting validation in a large clinical study.

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