Modern machine-learning applications in ambient ionization mass spectrometry.

This article provides a comprehensive overview of the applications of methods of machine learning (ML) and artificial intelligence (AI) in ambient ionization mass spectrometry (AIMS). AIMS has emerged as a powerful analytical tool in recent years, allowing for rapid and sensitive analysis of various samples without the need for extensive sample preparation. The integration of ML/AI algorithms with AIMS has further expanded its capabilities, enabling enhanced data analysis. This review discusses ML/AI algorithms applicable to the AIMS data and highlights the key advancements and potential benefits of utilizing ML/AI in the field of mass spectrometry, with a focus on the AIMS community.

Mass spectrometry for neurosurgery: Intraoperative support in decision-making.

Ambient ionization mass spectrometry was proved to be a powerful tool for oncological surgery. Still, it remains a translational technique on the way from laboratory to clinic. Brain surgery is the most sensitive to resection accuracy field since the balance between completeness of resection and minimization of nerve fiber damage determines patient outcome and quality of life. In this review, we summarize efforts made to develop various intraoperative support techniques for oncological neurosurgery and discuss difficulties arising on the way to clinical implementation of mass spectrometry-guided brain surgery.

Spherical Sampler Probes Enhance the Robustness of Ambient Ionization Mass Spectrometry for Rapid Drugs Screening.

Ambient ionization mass spectrometry has become one of the most promising approaches for rapid and high-throughput screening of small molecules in complex biological matrices for emergency medicine, forensics, and food and agriculture applications. The simple procedures for sample collection and ionization without additional pretreatment are vital in these fields. Many efforts have been devoted to modifying various ambient ionization techniques to simplify the procedures and improve the robustness and sensitivity of the methods. Here, we demonstrate the implementation of rigid spherical sampler probes to improve the robustness of touch spray ionization mass spectrometry. The sphericity of the probes increases the stability of the cone-jet mode of electrospray, reduces the requirements for fine positioning of a sampler in the ion source, and decreases the possibility of corona discharge occurrence. The utilization of spherical sampler probes allows fast, non-invasive sampling, followed by rapid analysis for various drugs of different chemical classes in complex biological matrices, such as the whole blood or sebum collected from the skin surface. The linearity of the analytical signal response from drug concentration confirms the possibility of creating a simple semiquantitative method for small molecules monitoring using spherical sampler probes.

Rapid estimation of tumor cell percentage in brain tissue biopsy samples using inline cartridge extraction mass spectrometry.

Tumor cell percentage (TCP) is an essential characteristic of biopsy samples that directly affects the sensitivity of molecular testing in clinical practice. Apart from clarifying diagnoses, rapid evaluation of TCP combined with various neuronavigation systems can be used to support decision making in neurosurgery. It is known that ambient mass spectrometry makes it possible to rapidly distinguish healthy from malignant tissues. In connection with this, here we demonstrate the possibility of using non-imaging ambient mass spectrometry to evaluate TCP in glial tumor tissues with a high degree of confidence. Molecular profiles of histologically annotated human glioblastoma tissue samples were obtained using the inline cartridge extraction ambient mass spectrometry approach. XGBoost regressors were trained to evaluate tumor cell percentage. Using cross-validation, it was estimated that the TCP was determined by the regressors with a precision of approximately 90% using only low-resolution data. This result demonstrates that ambient mass spectrometry provides an accurate method todetermine TCP in dissected tissues even without implementing mass spectrometry imaging. The application of such techniques offers the possibility to automate routine tissue screening and TCP evaluation to boost the throughput of pathology laboratories. Rapid estimation of tumor cell percentage during neurosurgery.

Feature selection algorithm for spray-from-tissue mass spectrometry.

Detection of the brain tumor margins is one of the most significant problems in neurosurgery. Several mass spectrometry-based approaches have been proposed recently for tumor boundary detection. One of them, spray from tissue does not require sample preparation but needs special algorithms for analysis of its spectra. Here we proposed the feature selection algorithm designed for analysis of spray-from-tissue data.

A novel direct spray-from-tissue ionization method for mass spectrometric analysis of human brain tumors.

Real-time feedback about dissected tissue during the neurosurgical procedure is strongly requested. A novel direct ionization mass spectrometric method for identifying pathological differences in tissues is proposed. The method is based on simultaneous extraction of tissue lipids and electrospray ionization which allows mass spectrometric data to be obtained directly from soft tissues. The advantage of this method is the stable flow of solvent, which leads to stable time-dependent spectra. The tissues included necrotized tissues and tumor tissues in different combinations. Capability for direct analysis of samples of dissected tissues during the neurosurgical procedure is demonstrated. Data validation is conducted by compound identification using precise masses from the MS profile, MS/MS, and isotopic distribution structure analysis. The method can be upgraded and applied for real-time identification of tissues during surgery. This paper describes the technique and its application perspective. For these purposes, other methods were compared with the investigated one and the results were shown to be reproducible. Differences in lipid profiles were observed even in tissues from one patient where distinctions between different samples could be poor. The paper presents a proof of concept for the method to be applied in neurosurgery particularly and in tissue analysis generically. The paper also contains preliminary results proving the possibility of observing differences in mass spectra of different tumors.

Incorporation of a Disposable ESI Emitter into Inline Cartridge Extraction Mass Spectrometry Improves Throughput and Spectra Stability.

Rapid and reliable methods for detecting tumor margins are crucial for neuro-oncology. Several mass spectrometry-based methods have been recently proposed to address this problem. Inline Cartridge Extraction (ICE) demonstrates the potential for clinical application, based on ex-vivo analysis of dissected tissues, but requires time-consuming steps to avoid cross-contamination. In this work, a method of incorporating a disposable electrospray emitter into the ICE cartridge by PEEK sleeves melting is developed. It reduces total analysis time and improves throughput. The proposed setup also improves the robustness of the ICE molecular profiling as demonstrated with human glial tumor samples in that stability and reproducibility of the spectra were increased.

Comparison of Dimensionality Reduction Methods in Mass Spectra of Astrocytoma and Glioblastoma Tissues.

Recently developed methods of ambient ionization allow the collection of mass spectrometric datasets for biological and medical applications at an unprecedented pace. One of the areas that could employ such analysis is neurosurgery. The fast in situ identification of dissected tissues could assist the neurosurgery procedure. In this paper tumor tissues of astrocytoma and glioblastoma are compared. The vast majority of the data representation methods are hard to use, as the number of features is high and the amount of samples is limited. Furthermore, the ratio of features and samples number restricts the use of many machine learning methods. The number of features could be reduced through feature selection algorithms or dimensionality reduction methods. Different algorithms of dimensionality reduction are considered along with the traditional noise thresholding for the mass spectra. From our analysis, the Isomap algorithm appears to be the most effective dimensionality reduction algorithm for negative mode, whereas the positive mode could be processed with a simple noise reduction by a threshold. Also, negative and positive mode correspond to different sample properties: negative mode is responsible for the inner variability and the details of the sample, whereas positive mode describes measurement in general.

Assessment of variation of inline cartridge extraction mass spectra.

Recently, mass-spectrometry methods show its utility in tumor boundary location. The effect of differences between research and clinical protocols such as low- and high-resolution measurements and sample storage have to be understood and taken into account to transfer methods from bench to bedside. In this study, we demonstrate a simple way to compare mass spectra obtained by different experimental protocols, assess its quality, and check for the presence of outliers and batch effect in the dataset. We compare the mass spectra of both fresh and frozen-thawed astrocytic brain tumor samples obtained with the inline cartridge extraction prior to electrospray ionization. Our results reveal the importance of both positive and negative ion mode mass spectrometry for getting reliable information about sample diversity. We show that positive mode highlights the difference between protocols of mass spectra measurement, such as fresh and frozen-thawed samples, whereas negative mode better characterizes the histological difference between samples. We also show how the use of similarity spectrum matrix helps to identify the proper choice of the measurement parameters, so data collection would be kept reliable, and analysis would be correct and meaningful.

Relative quantitation of phosphatidylcholines with interfered masses of protonated and sodiated molecules by tandem and Fourier-transform ion cyclotron resonance mass spectrometry.

The present work deals with deconvolution of interfered peaks of protonated and sodiated phosphatidylcholines to solve the problem of relative quantitation of these compounds. The method was developed based on the fact that adducts of phosphatidylcholines with proton and sodium ion give unique characteristic peaks in tandem mass spectrometry. Ultra-high-resolution Fourier-transform ion cyclotron resonance mass spectrometry was used to resolve interfered peaks and thus validate the results of tandem mass spectrometry-based deconvolution. Applicability of the method was tested with synthesized phosphatidylcholines and applied for tissue-spray analysis of the clinical samples and demonstrated good correlation (0.996) between MS/MS and Fourier-transform ion cyclotron resonance mass spectrometry results.