Dataset Information

Rapid Development of Improved Data-Dependent Acquisition Strategies.

ABSTRACT: Tandem mass spectrometry (LC-MS/MS) is widely used to identify unknown ions in untargeted metabolomics. Data-dependent acquisition (DDA) chooses which ions to fragment based upon intensities observed in MS1 survey scans and typically only fragments a small subset of the ions present. Despite this inefficiency, relatively little work has addressed the development of new DDA methods, partly due to the high overhead associated with running the many extracts necessary to optimize approaches in busy MS facilities. In this work, we first provide theoretical results that show how much improvement is possible over current DDA strategies. We then describe an in silico framework for fast and cost-efficient development of new DDA strategies using a previously developed virtual metabolomics mass spectrometer (ViMMS). Additional functionality is added to ViMMS to allow methods to be used both in simulation and on real samples via an Instrument Application Programming Interface (IAPI). We demonstrate this framework through the development and optimization of two new DDA methods that introduce new advanced ion prioritization strategies. Upon application of these developed methods to two complex metabolite mixtures, our results show that they are able to fragment more unique ions than standard DDA strategies.

SUBMITTER: Davies V

PROVIDER: S-EPMC8047769 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Rapid Development of Improved Data-Dependent Acquisition Strategies.

Davies Vinny V Wandy Joe J Weidt Stefan S van der Hooft Justin J J JJJ Miller Alice A Daly Rónán R Rogers Simon S

Analytical chemistry 20210330 14

Tandem mass spectrometry (LC-MS/MS) is widely used to identify unknown ions in untargeted metabolomics. Data-dependent acquisition (DDA) chooses which ions to fragment based upon intensities observed in MS1 survey scans and typically only fragments a small subset of the ions present. Despite this inefficiency, relatively little work has addressed the development of new DDA methods, partly due to the high overhead associated with running the many extracts necessary to optimize approaches in busy ...[more]

PMID: 33784814

Similar Datasets

Project description:Rapid health outcome data acquisition using existing questionnaires can greatly facilitate time-sensitive research during or after a wildfire event. We aimed to develop a readily available library of questionnaires for self-reported health outcomes to serve as a centralized platform for wildfire researchers seeking to quickly design instruments tailored to their research aims. In this paper, we describe the methodology used to identify relevant health questionnaires and compile them into a structured library. We first followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2020 checklist and performed a systematic literature review of prior research on wildfire exposure and health and used this to 1) identify health outcome categories associated with wildfire and smoke exposure and 2) extract questionnaires used for self-report of health outcomes related to wildfire exposure. We also performed a secondary search of existing questionnaire repositories to identify additional instruments relevant to health impacts of wildfire exposure. All questionnaires (n=100) were organized by eight health outcome categories (mental health = 60, respiratory health = 19, overall health = 17, sleep = 10, cardiovascular health = 4, allergy = 1, irritation (eye, throat, skin) = 2, and metabolic health = 1). The library (see supplementary information) will be accompanied by a decision-tree framework in development, which will assist future users in building new questionnaires that best fit their study population and research aims. Both the questionnaire library and the forthcoming decision-support framework will be publicly accessible to researchers, public health agencies, and other groups interested in rapid response data collection to characterize the impacts of wildfires. Additionally, this method of creating a wildfire exposure health questionnaire library may serve as a template for rapid collection of questionnaire-based data following other disasters.

Project description:BackgroundDedicated cone-beam breast computed tomography (CBBCT) using short-scan acquisition is being actively investigated to potentially reduce the radiation dose to the breast. This would require determining the optimal x-ray source trajectory for such short-scan acquisition.PurposeTo quantify the projection angle-dependent normalized glandular dose coefficient ( DgNCT$Dg{N^{CT}}$ ) in CBBCT, referred to as angular DgNCT$Dg{N^{CT}}$ , so that the x-ray ray source trajectory that minimizes the radiation dose to the breast for short-scan acquisition can be determined.Materials and methodsA cohort of 75 CBBCT clinical datasets was segmented and used to generate three breast models - (I) patient-specific breast with heterogeneous fibroglandular tissue distribution and real breast shape, (II) patient-specific breast shape with homogeneous tissue distribution and matched fibroglandular weight fraction, and (III) homogeneous semi-ellipsoidal breast with patient-specific breast dimensions and matched fibroglandular weight fraction, which corresponds to the breast model used in current radiation dosimetry protocols. For each clinical dataset, the angular DgNCT$Dg{N^{CT}}$ was obtained at 10 discrete angles, spaced 36° apart, for full-scan, circular, x-ray source trajectory from Monte Carlo simulations. Model III is used for validating the Monte Carlo simulation results. Models II and III are used to determine if breast shape contributes to the observed trends in angular DgNCT$Dg{N^{CT}}$ . A geometry-based theory in conjunction with center-of-mass ( COM$COM$ ) based distribution analysis is used to explain the projection angle-dependent variation in angular DgNCT$Dg{N^{CT}}$ .ResultsThe theoretical model predicted that the angular DgNCT$Dg{N^{CT}}$ will follow a sinusoidal pattern and the amplitude of the sinusoid increases when the center-of-mass of fibroglandular tissue ( COMf$CO{M_f}$ ) is farther from the center-of-mass of the breast ( COMb$CO{M_b}$ ). It also predicted that the angular DgNCT$Dg{N^{CT}}$ will be minimized at x-ray source positions complementary to the COMf$CO{M_f}$ . The COMf$CO{M_f}$ was superior to the COMb$CO{M_b}$ in 80% (60/75) of the breasts. From Monte Carlo simulations and for homogeneous breasts (models II and III), the deviation in breast shape from a semi-ellipsoid had minimal effect on angular DgNCT$Dg{N^{CT}}$ and showed less than 4% variation. From Monte Carlo simulations and for model I, as predicted by our theory, the angular DgNCT$Dg{N^{CT}}$ followed a sinusoidal pattern with maxima and minima at x-ray source positions superior and inferior to the breast, respectively. For model I, the projection angle-dependent variation in angular DgNCT$Dg{N^{CT}}$ was 16.4%.ConclusionThe heterogeneous tissue distribution affected the angular DgNCT$Dg{N^{CT}}$ more than the breast shape. For model I, the angular DgNCT$Dg{N^{CT}}$ was lowest when the x-ray source was inferior to the breast. Hence, for short-scan CBBCT acquisition with COMb$CO{M_b}$ aligned with axis-of-rotation, an x-ray source trajectory inferior to the breast is preferable and such an acquisition spanning 205° can potentially reduce the mean glandular dose by up to 52%.

Dataset Information

Rapid Development of Improved Data-Dependent Acquisition Strategies.

Publications

Rapid Development of Improved Data-Dependent Acquisition Strategies.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets