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A stochastic regression model is presented that separates signal from noise in chemical spectra. Spectra are decomposed into additive contributions from signal and from estimated noise. Numerical results on sample spectra are presented and suggest that this strategy offers an effective and computationally efficient framework for comprehensive noise estimation and analysis. From this analysis more effective methods of feature extraction in chemical spectra can be created. [ABSTRACT FROM AUTHOR]

Abstract: Cells are known to sense and respond to the physical properties of their environment and those of tissue scaffolds. Optimizing these cell–material interactions is critical in tissue engineering. In this work, a simple and inexpensive combinatorial platform was developed to rapidly screen three-dimensional (3D) tissue scaffolds and was applied to screen the effect of scaffold properties for tissue engineering of bone. Differentiation of osteoblasts was examined in poly(ethylene glycol) hydrogel gradients spanning a 30-fold range in compressive modulus (≈10 kPa to ≈300 kPa). Results demonstrate that material properties (gel stiffness) of scaffolds can be leveraged to induce cell differentiation in 3D culture as an alternative to biochemical cues such as soluble supplements, immobilized biomolecules and vectors, which are often expensive, labile and potentially carcinogenic. Gel moduli of ≈225 kPa and higher enhanced osteogenesis. Furthermore, it is proposed that material-induced cell differentiation can be modulated to engineer seamless tissue interfaces between mineralized bone tissue and softer tissues such as ligaments and tendons. This work presents a combinatorial method to screen biological response to 3D hydrogel scaffolds that more closely mimics the 3D environment experienced by cells in vivo. [Copyright &y& Elsevier]

Abstract: The interaction of silica and kaolin with dipalmitoylphosphatidylcholine (DPPC) has been studied using 13C and 31P solid state nuclear magnetic resonance spectroscopy. These studies explore the molecular interactions of these respirable dusts with a model lung surfactant species to characterize silica toxicity in mixed systems. The choline head group of DPPC was found to remain mobile when adsorbed on kaolin, in contrast to an immobile head group on silica. Further, glycerol carbon intensities were greatly diminished relative to that of choline carbons, a result attributed to broadening effects. These preliminary findings suggest that silica toxicity may not be related to choline mobility as previously noted [J. Colloid Interface Sci. 172 (1995) 536–538]. [Copyright &y& Elsevier]

A matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) interlaboratory comparison was conducted on mixtures of synthetic polymers having the same repeat unit and closely matching molecular mass distributions but with different end groups. The interlaboratory comparison was designed to see how well the results from a group of experienced laboratories would agree on the mass fraction, and molecular mass distribution, of each polymer in a series of binary mixtures. Polystyrenes of a molecular mass near 9000 u were used. Both polystyrenes were initiated with the same butyl initiator; however, one was tenninated with -H (termed PSH) and the other was terminated with -CH2CH2OH (termed PSOH). End group composition of the individual polymers was checked by MALDI-TOF MS and by nuclear magnetic resonance (NMR). Five mixtures were created gravimetrically with mass ratios between 95:5 and 10:90 PSOH/PSH. Mixture compositions where measured by NMR and by Fourier transform infrared spectrometry (FT-IR). NMR and FT-IR were used to benchmark the performance of these methods in comparison to MALDI-TOF MS. Samples of these mixtures were sent to any institution requesting it. A total of 14 institutions participated. Analysis of variance was used to examine the influences of the independent parameters (participating laboratory, MALDI matrix, instrument manufacturer, TOF mass separation mode) on the measured mass fractions and molecular mass distributions for each polymer in each mixture. Two parameters, participating laboratory and instrument manufacturer, were determined to have a statistically significant influence. MALDI matrix and TOF mass separation mode (linear or reflectron) were found not to have a significant influence. Improper mass calibration, inadequate instrument optimization with respect to high signal-to-noise ratio across the entire mass range, and poor data analysis methods (e.g., baseline subtraction and peak integration) seemed to be the greatest obstacles in the correct application of MALDI-TOF MS to this problem. Each of these problems can be addressed with proper laboratory technique. [ABSTRACT FROM AUTHOR]

A fast and sensitive direct extraction (DE) method developed in our group can efficiently extract proteins in 30 min from a 5 cm-long hair strand. Previously, we coupled DE to downstream analysis using gel electrophoresis followed by in-gel digestion, which can be time-consuming. In searching for a better alternative, we found that a combination of DE with a bead-based method (SP3) can lead to significant improvements in protein discovery in human hair. Since SP3 is designed for general applications, we optimized it to process hair proteins following DE and compared it to several other in-solution digestion methods. Of particular concern are genetically variant peptides (GVPs), which can be used for human identification in forensic analysis. Here, we demonstrated improved GVP discovery with the DE and SP3 workflow, which was 3 times faster than the previous in-gel digestion method and required significantly less instrument time depending on the number of gel slices processed. Additionally, it led to an increased number of identified proteins and GVPs. Among the tested in-solution digestion methods, DE combined with SP3 showed the highest sequence coverage, with higher abundances of the identified peptides. This provides a significantly enhanced means for identifying proteins and GVPs in human hair.

The performance of three algorithms for predicting nominal molecular mass from an analyte's electron ionization mass spectrum is presented. The Peak Interpretation Method (PIM) attempts to quantify the likelihood that a molecular ion peak is contained in the mass spectrum, whereas the Simple Search Hitlist Method (SS-HM) and iterative Hybrid Search Hitlist Method (iHS-HM) leverage results from mass spectral library searching. These predictions can be employed in combination (recommended) or independently. The methods were tested on two sets of query mass spectra searched against libraries that did not contain the reference mass spectra of the same compounds: 19,074 spectra of various organic molecules searched against the NIST17 mass spectral library and 162 spectra of small molecule drugs searched against SWGDRUG version 3.3. Individually, each molecular mass prediction method had computed precisions (the fraction of positive predictions that were correct) of 91, 89, and 74%, respectively. The methods become more valuable when predictions are taken together. When all three predictions were identical, which occurred in 33% of the test cases, the predicted molecular mass was almost always correct (>99%).

The standard reference libraries and associated custom software provided by the National Institute of Standards and Technology's Mass Spectrometry Data Center (NIST MSDC) are described with a focus on assisting the seized drug analyst with the identification of fentanyl-related substances (FRS). These tools are particularly useful when encountering novel substances when no certified sample is available. The MSDC provides three standard reference mass spectral libraries, as well as six software packages for mass spectral analysis, reference library searching, data interpretation, and measurement uncertainty estimation. Each of these libraries and software packages are described with references to the original publications provided. Examples of fentanyl identification by gas chromatography-mass spectrometry (GC-MS) and by direct analysis in real-time (DART) mass spectrometry are given. A link to online tutorials is provided., (Published 2023. This article is a U.S. Government work and is in the public domain in the USA.)

This work presents methods for identifying and then creating a mass spectral library for disulfide-linked peptides originating from the NISTmAb, a reference material of the humanized IgG1k monoclonal antibody (RM 8671). Analyses involved both partially reduced and non-reduced samples under neutral and weakly basic conditions followed by nanoflow liquid chromatography tandem mass spectrometry (LC-MS/MS). Spectra of peptides containing disulfide bonds are identified by both MS1 ion and MS2 fragment ion data in order to completely map all the disulfide linkages in the NISTmAb. This led to the detection of 383 distinct disulfide-linked peptide ions, arising from fully tryptic cleavage, missed cleavage, irregular cleavage, complex Met/Trp oxidation mixtures, and metal adducts. Fragmentation features of disulfide bonds under low-energy collision dissociation were examined. These include (1) peptide bond cleavage leaving disulfide bonds intact; (2) disulfide bond cleavage, often leading to extensive fragmentation; and (3) double cleavage products resulting from breakages of two peptide bonds or both peptide and disulfide bonds. Automated annotation of various complex MS/MS fragments enabled the identification of disulfide-linked peptides with high confidence. Peptides containing each of the nine native disulfide bonds were identified along with 86 additional disulfide linkages arising from disulfide bond shuffling. The presence of shuffled disulfides was nearly completely abrogated by refining digest conditions. A curated spectral library of 702 disulfide-linked peptide spectra was created from this analysis and is publicly available for free download. Since all IgG1 antibodies have the same constant regions, the resulting library can be used as a tool for facile identification of "hard-to-find" disulfide-bonded peptides. Moreover, we show that one may identify such peptides originating from IgG1 proteins in human serum, thereby serving as a means of monitoring the completeness of protein reduction in proteomics studies. Data are available via ProteomeXchange with identifier PXD023358.

We describe the creation of a mass spectral library of acylcarnitines and conjugated acylcarnitines from the LC-MS/MS analysis of six NIST urine reference materials. To recognize acylcarnitines, we conducted in-depth analyses of fragmentation patterns of acylcarnitines and developed a set of rules, derived from spectra in the NIST17 Tandem MS Library and those identified in urine, using the newly developed hybrid search method. Acylcarnitine tandem spectra were annotated with fragments from carnitine and acyl moieties as well as neutral loss peaks from precursors. Consensus spectra were derived from spectra having similar retention time, fragmentation pattern, and the same precursor m / z and collision energy. The library contains 157 different precursor masses, 586 unique acylcarnitines, and 4 332 acylcarnitine consensus spectra. Furthermore, from spectra that partially satisfied the fragmentation rules of acylcarnitines, we identified 125 conjugated acylcarnitines represented by 987 consensus spectra, which appear to originate from Phase II biotransformation reactions. To our knowledge, this is the first report of conjugated acylcarnitines. The mass spectra provided by this work may be useful for clinical screening of acylcarnitines as well as for studying relationships among fragmentation patterns, collision energies, structures, and retention times of acylcarnitines. Further, these methods are extensible to other classes of metabolites.

A method to discover and correct errors in mass spectral libraries is described. Comparing across a set of highly curated reference libraries compounds that have the same chemical structure quickly identifies entries that are outliers. In cases where three or more entries for the same compound are compared, the outlier as determined by visual inspection was almost always found to contain the error. These errors were either in the spectrum itself or in the chemical descriptors that accompanied it. The method is demonstrated on finding errors in compounds of forensic interest in the NIST/EPA/NIH Mass Spectral Library. The target list of compounds checked was the Scientific Working Group for the Analysis of Seized Drugs (SWGDRUG) mass spectral library. Some examples of errors found are described. A checklist of errors that curators should look for when performing inter-library comparisons is provided. Graphical Abstract ᅟ.

Objective: To investigate the methods of determining aluminum silicate coated on the surface of silica particles and analyze the role of surface occlusion on development of silicosis., Methods: Respirable dust samples were collected on filters using 2 L/min flow in tungsten mines and pottery factories of Jiangxi province, and tin mines of Guanxi province. Dust particles were analyzed by a multiple-voltage scanning electron microscopy-energy dispersive X-ray spectroscopy (MVSEM-EDS) using 20 KeV and 5 KeV electron beam accelerating voltages. Changes in the silicon to aluminum X-ray line intensity ratio between the two voltages are compared particle by particle. This provided an index that distinguishes a silica particle that was homogeneously aluminum-contaminated from a clay coated silica particle., Results: The total of 3,982 dust particles from 47 dust samples of seven pottery factories, three tin mines and three tungsten mines were analyzed in this study. Significant difference of aluminum silicate coated on the surface of silica particle was shown between particles from pottery factories and tin mines. The average sample percentage of respirbale-sized silica particles alumino-silicate occlusion in the pottery factories (45%) was higher than that in the tin mines (18%) and tungsten mines (13%)., Conclusion: Higher percentages silica particles alumino-silicate occlusion is observed in the pottery factories than that in metal mines. These surface analysis results help to understand differences in risk of silicosis when exposure is normalized to cumulative respirable surface silica dust.

The interaction of silica and kaolin with dipalmitoylphosphatidylcholine (DPPC) has been studied using 13C and 31P solid state nuclear magnetic resonance spectroscopy. These studies explore the molecular interactions of these respirable dusts with a model lung surfactant species to characterize silica toxicity in mixed systems. The choline head group of DPPC was found to remain mobile when adsorbed on kaolin, in contrast to an immobile head group on silica. Further, glycerol carbon intensities were greatly diminished relative to that of choline carbons, a result attributed to broadening effects. These preliminary findings suggest that silica toxicity may not be related to choline mobility as previously noted.

A mathematical algorithm is presented that locates and calculates the area beneath peaks from real data using only reproducible mathematical operations and no user-selected parameters. It makes no assumptions about peak shape and requires no smoothing or preprocessing of the data. In fact, it is shown that for matrix-assisted laser desorption time-of-flight mass spectra noise exists at all frequency ranges making the smoothing of data without distortion of peak areas impossible. The algorithm is based on a time-series segmentation routine that reduces the data set to groups of three strategic points where each group defines the beginning, center, and ending of each peak located. The peak areas are found from the strategic points using a commonplace polygonal area calculation routine. Peaks with statistically insignificant height or area are then discarded. The performance of the algorithm is demonstrated on a polystyrene mass spectrum with varying degrees of noise added either mathematically or experimentally. An on-line implementation of the method, termed MassSpectator, for public use can be found at www.nist.gov/maldi.

Polyethylene is one of the most important industrial polymers and is also one of the most challenging polymers to be characterized by mass spectrometry. We have developed a substrate-assisted laser desorption/ionization (LDI) mass spectrometric method for polyethylene analysis. In this method, cobalt, copper, nickel, or iron metal powders are used as a sample substrate and silver nitrate is used as the cationization reagent. Using a conventional UV LDI time-of-flight mass spectrometer, intact oligomer ions having masses up to 5000 u can be detected. Cobalt is found to produce spectra with the highest signal-to-noise ratio and the lowest level of fragmentation. Cobalt powder size is shown to have some effect on the spectra produced. The best results are obtained with the use of cobalt powders with diameters ranging from 30 to 100 microm. Fragmentation cannot be totally eliminated, but the fragment ion peaks can be readily discerned from the intact polyethylene ions in the substrate-assisted LDI spectrum. Thus, the average molecular masses of low-mass polyethylene samples can be determined by using this method. A rapid heating model is used to account for the effectiveness of using the coarse metal powders to assist the analysis of intact polyethylene molecules by LDI.

Unlabelled: A fluorinated analog of proline amino acid, cis-4-[(18)F]fluoro-L-proline (FP), was tested for potential use in PET for detection and evaluation of pulmonary response to respirable crystalline silica. The purpose of the study was to determine whether PET imaging with FP is sensitive for detection of pulmonary fibrosis., Methods: Experimental silicosis was produced in rabbits by airway instillation of 300 mg respirable silica in 0.9% sterile saline; control rabbits received only saline. After 1, 2, 4, or 5 mo, animals were injected with 37 MBq (1 mCi) FP, and imaged in sets of 2 to 3 in a PET scanner using a dynamic scanning protocol over a 3-h period. Each imaging set contained at least 1 control rabbit. FP uptake in each lung was scored from 0 to 5 (PET score) by consensus of 3 readers blinded to animals' exposure status. Animals were humanely killed 2 d after the last imaging, and tissue sections from each lung lobe were graded from 0 to 5 by histopathology examination (histopathology score) for severity and distribution of fibrosis., Results: Silicotic animals had significantly higher (P < 0.05) PET scores at each time point than did control animals. Repeated-measures ANOVA showed significant differences in PET scores between silicotic and control animals for the total lung field, but there were no statistically significant time trends for either group. Presence of fibrosis (i.e., histopathology score > 1) showed a significant association with elevated PET score (i.e., PET score > 1) using Fisher's exact test (P < 0.05). PET scores also showed excellent predictive ability, as all animals (18/18) with fibrosis also had elevated PET scores, and 95% (18/19) of animals with PET scores > 1 showed evidence of fibrosis. Localization of activity to specific lung areas was less exact, perhaps due in part to the small animal size for the resolution of the clinical PET imager used. PET scores were elevated (>1) for 67% (10/15) of silicotic right lungs and 75% (12/16) of silicotic left lungs; fibrosis scores > 1 were measured in 91% (10/11) of right lungs with PET scores > 1, and in 92% (12/13) of such left lungs., Conclusion: The FP tracer provided sensitive and specific identification of silicotic animals in early stages of the disease. This suggests that FP PET imaging has the potential sensitivity to detect active fibrosis in silicosis and other lung diseases. Additional studies are needed to determine the specificity of the FP tracer for fibrosis versus inflammatory processes.

Autocorrelation is shown to be useful in describing the periodic patterns found in high- resolution mass spectra of synthetic polymers. Examples of this usefulness are described for a simple linear homopolymer to demonstrate the method fundamentals, a condensation polymer to demonstrate its utility in understanding complex spectra with multiple repeating patterns on different mass scales, and a condensation copolymer to demonstrate how it can elegantly and efficiently reveal unexpected phenomena. It is shown that using autocorrelation to determine where the signal devolves into noise can be useful in determining molecular mass distributions of synthetic polymers, a primary focus of the NIST synthetic polymer mass spectrometry effort. The appendices describe some of the effects of transformation from time to mass space when time-of-flight mass separation is used, as well as the effects of non-trivial baselines on the autocorrelation function.