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tDDA: A Targeted Data-Dependent Acquisition Mode for Rapid Screening of Targets in Complex Matrices
Ang Li1, Heyuan Jia2, Jie Hong3
1School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China.
Abstract:
Miniaturized mass spectrometers offer significant potential for in situ analysis due to their high specificity and portability. In traditional data-dependent acquisition (DDA) mode, precursor ions for tandem analysis are selected based on the full-scan mass spectrum. However, in situ applications often require the direct analysis of complex samples without extensive sample pretreatment, making them susceptible to chemical noise that can result in false negatives. To address this challenge, we propose a targeted data-dependent acquisition (tDDA) mode that substantially improves the accurate detection of target compounds in complex matrices. Unlike conventional DDA, the tDDA method eliminates reliance on the full-scan mass spectrum, where signals of interest are often obscured by matrix effects. This approach leverages sine amplitude modulation of sinusoidal frequency modulated (SAM-SFM) waveforms technology, which enables the real-time generation of isolated waveforms, allowing tDDA to achieve parallel, high-speed screening. Additionally, targeted automatic gain control (AGC) technology enhances the detection of low-concentration analytes, further reducing the false-negative rate. The tDDA mode was successfully integrated and validated on a modified "Brick" miniaturized ion trap mass spectrometer. Experimental results demonstrated its capability to detect low concentrations of illicit drugs spiked in blood and saliva samples, highlighting its potential for effective in situ screening.
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