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Systematic Process for the Identification of “Known Unknowns” in Commercial Products by GC-MS and LC-MS

Note: Details on other subjects are found in “My Topics” tab under sailboat picture above or on the sidebar links to the right..

Introduction:  In the last 34 years, we have developed a systematic process for the identification of “known unknowns” by GC-MS and LC-MS in commercial products.  We define “known unknowns” as non-targeted species which are known in the chemical literature or mass spectrometry reference databases, but unknown to the investigator.  The process is shown in the following simplified flowchart:

This process is described in detail in the February 2013 copy of LCGC, “MS-The Practical Art.”  The article is entitled:  “Identifying “Known Unknowns” in Commercial Products by Mass Spectrometry.”  A copy with associated ads is shown below:

LCGC PDF with Advertisements

or the direct link to the Chromatography Online Website:

LCGC Article On-Line Link

which can be printed using the instructions in this link.  The article originated from work presented at Pittcon in 2012.

NIST Search of EI and CID Spectra:  The initial step in our process utilizes computer searches of EI (GC-MS) or CID (LC-MS) spectra against reference databases using the NIST MS search.  The computer EI searches normally work better than CID ones, but the latter are still very useful.  We employ both purchased, in-house, and internet databases:

We use the NIST and Wiley commercial databases, but there are many other specialty databases that others might find useful.

The NIST search interfaces easily with a wide variety of manufacturers’ data processing and structural drawing programs:

“Spectra-Less” Database Searching:  If the NIST search is not successful, then accurate mass data is used to obtain a molecular formula (MF), a monoisotopic mass, or an average molecular weight.  This data is used to search very large databases such as the CAS Registry (>70 million entries) or ChemSpider (>28 million entries) via web interfaces.  We define them as “spectra-less” databases because they contain no computer-searchable mass spectral data.  We had originally used this approach to search the TSCA database or our Eastman Chemical plant material listing.

The candidate structures from the CAS Registry or ChemSpider searches are prioritized by either the number of associated references or key words.  Other ancillary information such as mass spectral fragments in EI or CID spectra; isotopic abundances, UV spectra; types of ion adducts; CI data; number of exchangeable protons;  etc. are used to narrow the list to one structure.  This website has many screenshots (SciFinder1, SciFinder2, ChemSpider) that illustrate these approaches with many examples.

Model EI and CID Spectra from NIST Structure Search:  The NIST MS Search program ranks model compounds employing structural searching of both our commercial and in-house databases.  This is particularly valuable for finding model compounds for a proposed structure found in searches of “spectra-less” databases such as the CAS Registry and ChemSpider.

As noted in the table above, there are ~800,000 structures associated with the EI spectra and 100,000 structures with CID mass spectra in our computer-searchable databases.  We use the NIST MS Interpreter  program to automatically correlate fragment ions in the EI and CID spectra with the component’s substructure.

“No Results” from Process:  There will be non-targeted species in the sample which are “unknown unknowns”, those not found in any reference libraries or “spectra-less” databases.  A few thoughts on their identification are discussed in another section.

Future Improvements Needed:  The approach works well for the majority of our samples which are fairly simple and contain components with molecular weights <500 daltons.  On the other hand, improvements are needed for complex samples and components with molecular weights >500 daltons.

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Eastman employs four different”in silico” software programs for processing MS/MS (CID) and EI spectra in our identification efforts.  The results are definitely not as useful as searching or examining experimentally acquired CID spectra.  Nevertheless, the use of in silico software programs and their associated spectra can definitely assist in shortening the time it takes to manually interpret and prioritize substructural information for candidate species.  In addition ABSciex has some interesting in silico capabilities and a section of a recent review article discusses the topic.

The software programs we use are listed below.

1.  Use of NIST MS Interpreter for EI and MS/MS Spectra

We routinely use NIST MS Interpreter to understand EI and MS/MS (APCI, electrospray) spectra.  It is critical part of entering compounds into both our EI and MS/MS libraries.  It quickly allows us to determine if all the major fragments in our spectrum are consistent with the proposed structure.  In addition, it can also be used to correlate fragment ions in a model compound’s spectrum to its substructure in the NIST and Wiley EI and MS/MS libraries and our in-house libraries.

It is supplied free of charge with the NIST Version 2.0 Software.  I have included screenshots of the MS Interpreter and a poster presented by NIST:

ms_interpreter_screenshots (2 pages)

ms_interpreter_NIST_poster

2.  MetFrag with SciFinder and ChemSpider

MetFrag looks very interesting.  It allows me to use an automated connection to ChemSpider and a manual connection to SciFinder to obtain candidate structures.  In silico CID spectra are generated for all the candidate structures which are then compared to my acquired accurate mass CID spectrum.  The best results appear to be obtained in my examples by sorting by the “# of Explained Peaks” instead of “Score” in many cases.

I have shown the results for the approach with both ChemSpider and SciFinder for trazodone:

trazodone_example

Their web links are:

MetFusion_link

MetFrag_link

If you want to try the trazodone example, the following link contains the mass spec data and the SDF file needed for the MetFrag query:

test_files_metfrag

3.  Identifying “Known Unknowns” Using ChemSpider and Automated MS/MS Structure Correlation

A poster session was given at the 2012 ASMS conference in Vancouver.  The work was done as a collaborative effort between Agilent, ChemSpider (RSC), and Eastman Chemical Company.  The approach is described below with a link to the poster session in PDF format:

• Accurate mass data acquired by LC/MS in data-dependent MS/MS mode
• Agilent MassHunter Qualitative Analysis software used to find compounds and generate molecular formulas using monoisotopic mass, isotope abundance, and isotope spacing, as well as look for matching formulas for each fragment ion and its neutral loss from the precursor
• Prototype Agilent MassHunter Molecular Structure Correlator software uses ChemSpider interface to obtain candidate structures for a target molecular formula and associated number of references for candidate structures
• Calculation of correlation scores to explain MS/MS fragmentation pattern for each candidate structure using a “systematic bond-breaking” approach
• Results sorted by number of references and/or correlation score to evaluate structure candidates for identification of components

asms_2012_poster_agilent_chemspider

3.   MathSpec

MathSpec, Inc. is a privately held company based in the Chicago area. The founder, Dr. Daniel L. Sweeney, believes that mass spectral fragmentation data can best be interpreted by viewing small molecules as mathematical partitions of the molecular weight. Dan has been doing LC-MS and interpreting MS/MS data for over twenty years.

It seems to work well and he is also modifying to find similar compounds.  He added the capability to sort by number of associated synonyms which is similar to the concept of sorting by the number of references in other programs.

MathSpec_link

Also see his You Tube videos describing his new software including add-ins in Excel.  Just search with Google for “MathSpec You Tube.”

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I presented a paper at PittCon 2012 describing the identification of “known unknowns.”  The name of the session was “Accurate Mass and Novel Applications of Mass Spectrometry for Unknown Environmental Analyses Symposium” which was arranged by Michael Thurman and Imma Ferrer, University of Colorado.

My presentation summarized the approaches we employ at Eastman for the identification of unknowns including searching mass spectral databases (EI, CID) and  “spectra-less” databases such as the CAS Registry and ChemSpider.

Here is a link to the talk:

pittcon_known_unknown_talk

Links to related articles on ChemSpider and CAS Registry (SciFinder/STN Express) can be found on the side bar of my webpage.  Also additional information on creating, using, and distributing personal libraries in NIST format is found in those links.

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NIST has greatly facilitated the utilization of the NIST Version 2 library search software package with a wide variety of other data processing and structural drawing packages.

The NIST software includes a data processing program:

AMDIS

We use AMDIS, but also use the NIST search with a variety of other data processing programs.  I have included some links with instructions to setting up several of these programs below.

David Sparkman indicated that sometimes problems are noted in transferring spectra from a manufacturer’s data processing to the NIST search for processing.  This can often be fixed by deleting the AUTOIMP.MSD file found in the same directory as the installed NIST search software.  The file will then be created correctly when starting the transfer of the spectrum from the manufacturer’s program to the NIST search.

Agilent MassHunter:

NIST_agilent_masshunter

MassLynx:

NIST_waters_masslynx

I occasionally had problems getting MassLynx to work, see attached fix:

NIST_waters_masslynx_possible_problem

Xcalibur:

NIST_thermo_xcalibur

Various Structural Drawing Packages:

NIST_various_structure_programs

Agilent LC-MSD software:

NIST_agilent_msd_chemstation

ACD Software:

NIST_acd

Wsearch: This program exports spectra to NIST search and supports many different file formats.

Link_to_wsearch_program

Using NIST as Corporate Database/Archive:

NIST_Corporate_Database

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David Sparkman and Steve Stein showed me some new exact mass search capabilities introduced with the NIST 11 Library at ASMS conference in Denver.  They thought that these new capabilities might be useful in the identification of “known unknowns.”

An unknown to an investigator, in many cases, is often known in the chemical literature.  We refer to these types of compounds as “known unknowns.”  The term originated from a quote by Donald Rumsfeld:

Rumsfeld_quote

Recent changes in the software allow one to search by accurate mass values with an associated error window.  The results allow one to display and sort the number of synonyms or associated databases.  Often the most likely component would be the one with the highest numbers for these fields.  Steve Stein refers the importance of this type of information in the identification of unknowns as “prior probability.”

I evaluated the software using a group of compounds that I had employed previously to evaluate ChemSpider and CAS.  The results were very encouraging.  I have attached my initial results and some instructions for searching Warfarin’s exact mass.  The approach was very successful for drugs, pesticides, natural products.  However, many polymer antioxidants and UV stabilizers were not found.  Thus, the choice of which database to search, NIST/ChemSpider/or CAS, will be dependent on the user’s needs.

The molecular weight distribution is somewhat lower for the NIST database than either the CAS Registry or Chemspider.  Thus the latter two databases will probably be more useful for higher molecular weight compounds found in LC-MS analyses.

We heavily use NIST for searching both our EI and MS/MS and searching commercial EI and MS/MS databases.  The current version of NIST includes 64,511 MS/MS spectra that can be very useful for identifying “known unknowns.”  Furthermore, we routinely run the same sample by LC-MS and GC-MS and utilize EI spectra in addition to our in-source MS/MS spectra.

Here is a file showing how to use the new NIST exact mass search for identifying a “known unknown” by accurate mass.  Of course, one can also search by molecular formula.

NIST_known_unknown_work

Here are the results from my evaluation with 90 compounds:

NIST_known_unknown_evaluation

Links for our two papers describing our work with CAS and ChemSpider are shown below:

CAS_known_unknown_work

ChemSpider_known_unknown_work

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An unknown to an investigator, in many cases, is often known in the chemical literature.  We refer to these types of non-targeted species as “known unknowns.”  The term originated in a much different context in a quote by Donald Rumsfeld.

ChemSpider is a very valuable source of known substances.  It contains >28 million compounds which can be searched by a variety of parameters and includes valuable links to other web-based resources.

Here is a graph showing the molecular weight distribution of species:

ChemSpider is owned by the Royal Society of Chemistry (RSC) and provided as a free resource to the community.  We refer to this type of database as “spectra-less” because it contains no computer-searchable EI or CID mass spectra.  However, very useful results can be obtained searching this database by molecular formula or monoisotopic mass.

Eastman collaborated in the modification of ChemSpider’s web-based interface to facilitate the entry of monoisotopic molecular weight data and to sort the resulting search results by the number of associated references.  The use of monoisotopic mass does not require subjective limitations of the number of elements, types of elements, double bond equivalents or even the type of ion adduct in obtaining candidate structures.

Eastman had previously demonstrated the utility of using the number of associated references as a useful approach in the identification of unknowns with the CAS Registry.  The resulting candidates are further evaluated by their mass spectral fragmentation and a wide variety of other associated analytical information to arrive at the identification of the “known unknown.”

ChemSpider Prepress Journal Article with Screenshots Illustrating Examples:

ChemSpider_prepress_article

Journal of The American Society for Mass Spectrometry, Volume 23, Number 1, 179-185, DOI: 10.1007/s13361-011-0265-y

I am very impressed in MasterView software developed by Sciex to use ChemSpider in their work flow for the identification of unknowns, see:

Sciex Software Using ChemSpider

MasterView Videos

Link to ASMS Poster at ASMS Conference 2011, Denver, Colorado:

ASMS_poster_2011

Additional Related Information:

A similar approach was previously demonstrated utilizing the CAS Registry which was searched by SciFinder.

CAS_registry_info

NIST offers a similar approach as part of their NIST MS Search Software employing a somewhat smaller collection of compounds.

New_nist_info

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We don’t have extensive information on the long-term precision and accuracy of our TOF instruments.  However, we have performed some basic studies to understand the limitations of the LCT and GCT.  Our Waters’ instruments are based on TDC (time-to-digital converters), which affects the accuracy and the precision of the instruments.

The TDC approach has two significant limitations:

1)  When two or more ions hit the detector in one flight cycle the TDC counts them as one event.

2)  When two ions hit the detector within a certain time interval, the TDC does not count the second ion (dead time loss)

The LCT and GCT correct for this problem via software.  Our ASMS poster session addresses these limitations and Excel ”program” models the effect.

Deadtime_poster

deadtime_model (Excel)

Here is a good literature reference that discusses the topic:

Chernuschevich, I. V.; Loboda, A. V.; Thomson, B. A. Special Feature Tutorial: An Introduction to Quadrupole-Time-of-Flight Mass Spectrometry. J. Mass Spectrom. 2001, 36, 849-865.

Link to Paper

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Eastman has had a vision for using databases to identify compounds using mass spectral data for the last 35 years.  The approach involves partnerships with many different organizations.  We currently use internal (NIST) and external searches (ChemSpider, CAS Registry) of databases.

The NIST search software offers a very cost effective means of sharing our EI and CID databases within the Eastman Worlwide Corporate Network.  Here is a diagram that outlines its basic attributes:

We use the NIST search with a variety of data processing programs including Xcalibur, WSearch, AMDIS, MassLynx, Agilent MassHunter, and Agilent MSD and with a variety of structural drawing packages.  Here is a link for detailed information on utilizing the NIST search with these other programs:

Using NIST with Other Programs

Automatic Updating of Database Nightly and System Manager Information:

We add new EI and MS/MS spectra with structures to the database daily.  The data base can be searched by mass spectrum, name, MF, MW, structure, etc.   The process employs DOS batch files, some various utilities from NIST, and a Windows scheduler program.  The following document gives details of the process for our automatic nightly update and a general overview of the responsibilities of the system manager:

process_document

Here is a zip files with some of the necessary utility programs:

zip_file_with_executables

Interfacing to Manufacturers’ Data Processing and Drawing Programs:

As I mentioned above, the program can be easily interfaced to an instrument manufacturer’s data system.  I have included below a simple descripition that I wrote and a more detailed one from David Sparkman, a NIST consultant.

simple_instructions

detailed_instructions

User Manuals for Using NIST Search and AMDIS:

NIST has manuals for both AMDIS and the NIST Search.  In addition, I wrote a manual for using the NIST search software for our Eastman users:

Eastman_nist_user_manual

NIST_user_manual

AMDIS_user_manual

New Additions and More Information about NIST Search and AMDIS:

Separation Science

SIS_website

Overview and History of NIST Library:

Steve Stein summarized the strengths and pitfalls of library searching

Stein Paper

Here is an interesting link to the history of library by Steve Heller:

Heller_NIST_history

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51.  “Identifying ‘Known Unknowns’ in Commercial Products by Mass Spectrometry,”  James L. Little, Curtis D. Cleven, Adam S. Howard, Current Trends in Mass Spectrometry, p 24-28, May 2014.

50.  Qualitative Gas Chromatography-Mass Spectrometry Analyses Using Amines as Chemical Ionization Reagent Gases, James L. Little, Adam S. Howard, Journal of the American Society for Mass Spectrometry, DOI:  10.1007/s13361-013-0740-8, December 2013, Volume 24, Issue 12, pp 1913-1918.

49.  “MS the Practical Art:  Identifying “Known Unknowns” in Commercial Products by Mass Spectrometry,”  James L. Little, Curtis D. Cleven, Adam S. Howard, Editor Kate Yu, LCGC Europe, Volume 26, Issue 3, pp. 163-168, March 2013.

48.  “MS the Practical Art:  Identifying “Known Unknowns” in Commercial Products by Mass Spectrometry,”  James L. Little, Curtis D. Cleven, Adam S. Howard, Editor Kate Yu, LCGC North America Volume 31, Number 2, February 2013.

47.  “Isolation and structural identification of the trihydroxamate siderophore vicibactin and its degradative products from Rhizobium Leguminosarum ATCC 14479 bv. trifolii,” William Wright, James Little, Fang Liu, Ranjan Chakraborty, Biometals (2013) 26:271-283, DOI 10.1005/s 10534-013-9609-3.

46.  Identification of “Known Unknowns” Utilizing Accurate Mass Data and ChemSpider, James L. Little, Antony J. Williams, Alexey Pshenichnov, Valery Tkachenko, Journal of The American Society for Mass Spectrometry, Volume 23, Number 1, 179-185, DOI: 10.1007/s13361-011-0265-y, 2012.

45.  Identifying “Known Unknowns” Using ChemSpider and Automated MS/MS Structure Correlation, J Little, F. Kuhlmann, X. Li, V. Takcheno, J. Zweigenbaum, A. Williams, 2012 61st ASMS Conference, Vancouver BC.

44.  Identification of “known unknowns” utilizing accurate mass data and chemical abstracts service databases, Little James L; Cleven Curtis D; Brown Stacy D, Journal of the American Society for Mass Spectrometry (2011), 22(2), 348-59.

43.  Production of Cyclic Acetals by Reactive Distillation,  D. Terrill, B. McMurray, D. Dillodeaux, James Lon Little, A. Howard, Serial No. 168374, Series Code 13, June 24, 2011.

42.  Production of Cyclic Acetals or Ketals Using Liquid-Phase Acid Catalysts, D. Terrill, B. McMurray, D. Dillodeaux, James Lon Little, A. Howard, Serial No. 168229, Series Code 13, June 24, 2011.

41.  Producdtion of Cyclic Acetals or Ketals Using Solid Acid Catalysts, D. Terrill, B. McMurray, D. Dillodeaux, James Lon Little, A. Howard, Serial No. 168330, Series Code 13, June 24, 2011.

40.  Accurate Mass Measurements:  Identifying “Known Unknowns” Using ChemSpider, J Little, A. Williams, V. Tkachenko, 2011 59th ASMS Conference, Denver, Colorado.

39.  Thermal Decomposition of Pyridine-Substituted Cobaltic Acetate in Acetic Acid, Sumner, Charles E., Jr.; Little, James; Howard, Adam S.; Liang, Weimin C., Inorganic Chemistry (2010), 49(10), 4606-4610.

38.  Accurate Mass Measurements:  Identifying Known Unknowns Using Publicly Accessible Databases, J Little, C. Cleven, S. Brown, 58th ASMS 2010, Salt Lake City, Utah.

37.  Building new drug delivery systems: in vitro and in vivo studies of drug-hydroxybutenyl cyclodextrin complexes, Buchanan, Charles M.; Buchanan, Norma L.; Edgar, Kevin J.; Klein, Sandra; Little, James L.; Ramsey, Michael G.; Ruble, Karen M.; Wacher, Vincent J.; Wempe, Michael F., ACS Symposium Series (2009), 1017(Polysaccharide Materials), 31-64.

36.  Inhibiting efflux with novel non-ionic surfactants: Rational design based on vitamin E TPGS, Wempe, Michael F.; Wright, Charles; Little, James L.; Lightner, Janet W.; Large, Shannon E.; Caflisch, George B.; Buchanan, Charles M.; Rice, Peter J.; Wacher, Vincent J.; Ruble, Karen M.; et al, International Journal of Pharmaceutics (2009), 370(1-2), 93-102.

35.  Pharmacokinetics of Saquinavir After Intravenous and Oral Dosing of Saquinavir: Hydroxybutenyl-β-Cyclodextrin Formulations, Buchanan, Charles M.; Buchanan, Norma L.; Edgar, Kevin J.; Little, James L.; Ramsey, Michael G.; Ruble, Karen M.; Wacher, Vincent J.; Wempe, Michael F., Biomacromolecules (2008), 9(1), 305-313

34.  Factors Affecting the Selectivity of the Oxidation of Methyl p-Toluate by Cobalt (III), Sumner, Charles E., Jr.; Morrill, Kent A.; Howell, Jeff S.; Little, James, Inorganic Chemistry (2008), 47(6), 2190-2195.

33.  Pharmacokinetics of itraconazole after intravenous and oral dosing of itraconazole-cyclodextrin formulations, Buchanan, Charles M.; Buchanan, Norma L.; Edgar, Kevin J.; Klein, Sandra; Little, James L.; Ramsey, Michael G.; Ruble, Karen M.; Wacher, Vincent J.; Wempe, Michael F., Journal of Pharmaceutical Sciences (2007), 96(11), 3100-3116.

32.  A Short and Convenient Chemical Route to Optically Pure 2-Methyl Chromanmethanols. Total Asymmetric Synthesis of β-, γ-, and δ-Tocotrienols, Couladouros, Elias A.; Moutsos, Vassilios I.; Lampropoulou, Maria; Little, James L.; Hyatt, John A., Journal of Organic Chemistry (2007), 72(18), 6735-6741.

31.  Pharmacokinetics of tamoxifen after intravenous and oral dosing of tamoxifen-hydroxybutenyl-β-cyclodextrin formulations, Buchanan, Charles M.; Buchanan, Norma L.; Edgar, Kevin J.; Little, James L.; Malcolm, Michael O.; Ruble, Karen M.; Wacher, Vincent J.; Wempe, Michael F., Journal of Pharmaceutical Sciences (2007), 96(3), 644-660.

30.  Light absorbing compositions useful for marking or tagging articles for security identification, Pearson, Jason Clay; Weaver, Max Allen; Dawsey, Timothy Ray; King, Greg Alan; Clark, Mark Dwight; Little, James Lon; Schick, Martin Frederick, U.S. Pat. Appl. Publ. (2007), US 20070287822 A1 20071213

29.  Probing Electrospray Lipid Matrix Ionization Effects in the Analysis of Drugs in Plasma Samples, J Little, M. Wempe, C. Buchanan, 2006  54th ASMS Conference, Seattle, Washington.

28.  Liquid chromatography-mass spectrometry/mass spectrometry method development for drug metabolism studies: Examining lipid matrix ionization effects in plasma, Little, James L.; Wempe, Michael F.; Buchanan, Charles M., Journal of Chromatography, B: Analytical Technologies in the Biomedical and Life Sciences (2006), 833(2), 219-230.

27.  Characterization of ‘Schizokinen’; a dihydroxamate-type siderophore produced by Rhizobium leguminosarum IARI 917, Storey E P; Boghozian R; Little James L; Lowman Douglas W; Chakraborty R, Biometals : an international journal on the role of metal ions in biology, biochemistry, and medicine (2006), 19(6), 637-49.

26.  “Deuterated Ammonia Chemical Ionization: Use in Counting Exchangeable Hydrogen Sites on Organic Compounds,” A. Z Kamzelski, J. L. Little, The Encyclopedia of Mass Spectrometry, Volume 4, Fundamentals of and Applications to Organic (and Organometallic) Compounds, Edited by M Gross et al, p 772-780, D. M Parees, 2005.

25.  Simple Method to Monitor Lysophospholipids and Phospholipids During LC-MS Method Development via In-Source CID, J Little, 2005 53rd ASMS Conference, San Antonio, TX.

24.  Identificaiton of Surfactants by Electrospray Liquid Chromatography-Mass Spectrometry, J Little,  extended abstract from Proceedings of 52nd ASMS Meeting, 2004, Nashville, TN.

23.  Identification of Components in Polycarbonate and Polyester Monomers and Polymers by GC-MS, J Little, extended abstract from Proceedings of 51st ASMS Meeting, 2003, Montreal.

22.  Standard Corporate Approach for Searching Mass Spectral Databases, J Little, extended abstract from Proceedings of 50th ASMS Meeting, 2002, Orlando, FL.

21.  Factors Affecting Mass Measurement Accuracy in a TOF Mass Spectrometer, C. Cleven, J. Little,  extended abstract from Proceedings of 50th ASMS Meeting, 2002, Orlando, FL.

20.  Identifying Unknowns with LC/MS/MS Data Using TSCA Chemical Inventory or SciFinder, J Little, extended abstract from Proceedings of 49th ASMS Meeting, 2001, Chicago, IL.

19.  NIST Search Program:  Standard Corporate Method for Searching EI Databases, J Little, extended abstract from Proceedings of 46th ASMS Meeting, 2000, Long Beach, Fl

18.  Artifacts in trimethylsilyl derivatization reactions and ways to avoid them, J. L. Little J Chromatogr A. 1999 Jun 4;844(1-2):1-22.

17.  Mass Spectral Identification of By-Products Formed in Derivatization Reactions, J Little, A. Spaugh, extended abstract from Proceedings of 45th ASMS Meeting, 1998. Orlando. Fl

16.  ASMS “Terms and Definitioins”-An Opportunity for Participation, J. Bartmess, J. Little, P. Price, R. Voyksner, David, Wang-Iverson, ASMS Measurements and Standards Committee, 1997, Palm Springs, CA.

15.  Methylamine in Methane:  Improved CI Reagent Gas for Molecular Weight Determinations, J. Little, extended abstract from Proceedings of 44th ASMS Meeting, Portland, OR, 1996.

14.  Andi/Mass Spectrometry Enhances Data Interchange at Eastman Chemical Locations, Jim Little, The Newsletter on Analytical Data Interchange, A Publication of the Analytical Instrument Association, Number Four, Winter 1995.

13.  Sharing Corporate Mass Spectral Data Bases, J Little, W. McSpadden, extended abstract from Proceedings of 43rd ASMS Meeting, Atlanta, GA, 1995.

12.  Network Processing of Mass Spectral Data, J Little, L. Cook, R. Siggins, M. Spence, S. Campbell, J. Hegedus, extended abstract from Proceedings of 42nd ASMS Meeting, Chicago, IL, 1994.

11.  High-Performance Liquid Chromatographic Analysis of Sulfonated Aromatics Using a B-Cyclodextrin-Bonded Phase, Wilder, D. R.; Tindall, G. W.; Cunningham, L. J.; Little, J. L., Journal of Chromatography (1993), 635(2), 221-6.

10.  LC/MS Analysis of Complex Synthetic Organic Molecules Utilizing Electrospray Ionization, K. Johnson, J Little, extended abstract from Proceedings of 40th ASMS Meeting, Washington, DC, 1992.

9.  Preparation of polyester samples for composition analysis, Tindall, G. William; Perry, Randall L.; Little, James L.; Spaugh, Arthur T., Jr., Analytical Chemistry (1991), 63(13), 1251-6.

8.  On the preparation of carbohydrate sulfates by displacement of trifluoromethanesulfonates, Hyatt, John A.; Little, James L., Carbohydrate Research (1991), 220, 215-17.

7.  α-D-Cellooligosaccharide acetates: physical and spectroscopic characterization and evaluation as models for cellulose triacetate, Buchanan, Charles M.; Hyatt, John A.; Kelley, Stephen S.; Little, James L., Macromolecules (1990), 23(16), 3747-55.

6.  Particle-Beam Liquid Secondary Ionization LC/MS Interface, J. Little, L. Cook, R. Perry, G.W. Tindall, M. Vestal, extended abstract from Proceedings of 38th ASMS Meeting, Tuscon, Arizona, 1990.

5.  Heat-Induced Dissociation in LC/MS Analyses, J. Little, J Crawford, D. Wilder, extended abstract from Proceedings of 35th ASMS Meeting, Denver, CO, 1987.

4.  Mass Spectral Identification of Artifacts Formed in Silylation Reactions, J. Little, J. Crawford , extended abstract from Proceedings of 34th ASMS Meeting, 1986, Cincinnati, OH.

3.  Automated Sample Analysis Software for GC/MS, J Little, J. Crawford, G. W. Fields,  extended abstract from Proceedings of 33rd ASMS Meeting, San Diego, CA, 1985.

2.  Preparation of Silica-Supported Diaryl Ketones for Use as Photosensitizers: A Novel Synthetic Application of Silica-Supported Phenyllithium, Hautala, R. R.; King, R. B.; Sweet, E. M.; Little, J. L.; Shields, Audrey W., Journal of Organometallic Chemistry (1981), 216(3), 281-6.

1.  The Use of Functionalized Polymers as Photosensitizers in an Energy Storage Reaction, Hautala, Richard R.; Little, James; Sweet, Edward Solar Energy (1977), 19(5), 503-8.

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This post shares information on our work in the area of matrix effects.  Matrix effects in LCMS can affect sensitivity, precision and accuracy.  We have developed a simple way to monitor phospholipids and lysophospholipids which yield matrix effects.  This approach is easily used in developing MRM LC-MS-MS analyses.

I have attached several links on the internet including:

ASMS Poster Sessions:

Matrix_poster_1

Matrix_poster_2

Prepress of Journal Article:

Matrix_effects_prepress

A published copy of the article can be found at J. L. Little, M. F. Wempe, C. M. Buchanan, Journal of Chromatography B, 833 (2006) 219-230.

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