Accurate and High-Resolution Particle Mass Measurement Using a Peak Filtering Algorithm.

Charge detection quadrupole ion trap mass spectrometry (CD-QIT MS) is an effective way of achieving the mass analysis of microparticles with ultrahigh mass. However, its mass accuracy and resolution are still poor. To enhance the performance of CD-QIT MS, the resolution Rpeak of each peak in the mass spectra resulting from an individual particle was assessed, and a peak filtering algorithm that can filter out particle adducts and clusters with a lower Rpeak was proposed. By using this strategy, more accurate mass information about the analyzed particles could be obtained, and the mass resolution of CD-QIT MS was improved by nearly 2-fold, which was demonstrated by using the polystyrene (PS) particle size standards and red blood cells (RBCs). Benefiting from these advantages of the peak filtering algorithm, the baseline separation and relative quantification of 3 and 4 µm PS particles were achieved. To prove the application value of this algorithm in a biological system, the mass of yeast cells harvested at different times was measured, and it was found that the mixed unbudded and budded yeast cells, which otherwise would not be differentiable, were distinguished and quantified with the algorithm.

Desorption Separation Ionization Mass Spectrometry (DSI-MS) for Rapid Analysis of COVID-19.

During the coronavirus disease 2019 (COVID-19) pandemic, which has witnessed over 772 million confirmed cases and over 6 million deaths globally, the outbreak of COVID-19 has emerged as a significant medical challenge affecting both affluent and impoverished nations. Therefore, there is an urgent need to explore the disease mechanism and to implement rapid detection methods. To address this, we employed the desorption separation ionization (DSI) device in conjunction with a mass spectrometer for the efficient detection and screening of COVID-19 urine samples. The study encompassed patients with COVID-19, healthy controls (HC), and patients with other types of pneumonia (OP) to evaluate their urine metabolomic profiles. Subsequently, we identified the differentially expressed metabolites in the COVID-19 patients and recognized amino acid metabolism as the predominant metabolic pathway involved. Furthermore, multiple established machine learning algorithms validated the exceptional performance of the metabolites in discriminating the COVID-19 group from healthy subjects, with an area under the curve of 0.932 in the blind test set. This study collectively suggests that the small-molecule metabolites detected from urine using the DSI device allow for rapid screening of COVID-19, taking just three minutes per sample. This approach has the potential to expand our understanding of the pathophysiological mechanisms of COVID-19 and offers a way to rapidly screen patients with COVID-19 through the utilization of machine learning algorithms.

Recent advances in entirely hand-held ionization sources for mass spectrometry.

Ambient ionization mass spectrometry (AIMS) has been developing explosively since its first debut. The ionization process was hence able to be achieved under atmospheric pressure, facilitating on-site field analysis in a variety of areas, such as clinical diagnosis, metabolic phenotyping, and surface analysis. As part of the ambitious goal of making MS a general device that can be used in everyday life, lots of efforts have been paid to miniaturize the ionization source. This review discusses avant-garde sources that could be entirely hand-held without any accessories. The structure and applications of the devices are described in detail as well. They could be expediently used in real-time and on-site analysis, presenting a great future potential for the routinizing of MS.

Biofluid Metabolic Profiling for Lung Cancer Screening via Reactive Matrix-Assisted Laser Desorption Ionization Mass Spectrometry.

Lung cancer (LC) has the highest mortality rate among various cancer diseases. Developing an early screening method for LC with high classification accuracy is essential. Herein, 2-hydrazinoquinoline (2-HQ) is utilized as a dual-mode reactive matrix for metabolic fingerprint analysis and LC screening via matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS). Metabolites in both positive mode and negative mode can be detected using 2-HQ as the matrix, and derivative analysis of aldehyde and ketone compounds can be achieved simultaneously. Hundreds of serum and urine samples from LC patients and healthy volunteers were analyzed. Combined with machine learning, LC patients and healthy volunteers were successfully distinguished with a high area under the curve value (0.996 for blind serum samples and 0.938 for urine). The MS signal was identified for metabolic profiling, and dysregulated metabolites of the LC group were analyzed. The above results showed that this method has great potential for rapid screening of LC.

Pocket-Size Wireless Nanoelectrospray Ionization Mass Spectrometry for Metabolic Analysis of Salty Biofluids and Single Cells.

Analysis of volume-limited biological samples such as single cells and biofluids not only benefits clinical purposes but also promotes fundamental research in life sciences. Detection of these samples, however, imposes strict requirements on measurement performance because of the minimal volume and concentrated salts of the samples. Herein, we developed a self-cleaning nanoelectrospray ionization device powered by a pocket-size "MasSpec Pointer" (MSP-nanoESI) for metabolic analysis of salty biological samples with limited volume. The self-cleaning effect induced by Maxwell-Wagner electric stress helps with keeping the borosilicate glass capillary tip free from clogging and thus increasing salt tolerance. This device possesses a high sample economy (about 0.1 µL per test) due to its pulsed high voltage supply, sampling method (dipping the nanoESI tip into analyte solution), and contact-free electrospray ionization (ESI) (the electrode does not touch the analyte solution during ESI). High repeatable results could be acquired by the device with a relative standard deviation (RSD) of 1.02% for voltage output and 12.94% for MS signals of caffeine standard. Single MCF-7 cells were metabolically analyzed directly from phosphate buffered saline, and two types of untreated cerebrospinal fluid from hydrocephalus patients were distinguished with 84% accuracy. MSP-nanoESI gets rid of the bulky apparatus and could be held in hand or put into one's pocket for transportation, and it could operate for more than 4 h without recharge. We believe this device will boost scientific research and clinical usage of volume-limited biological samples with high-concentration salts in a low-cost, convenient, and rapid manner.

Screening of hepatocellular carcinoma via machine learning based on atmospheric pressure glow discharge mass spectrometry.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with a high mortality rate. The diagnosis of HCC is currently based on alpha-fetoprotein detection, imaging examinations, and liver biopsy, which are expensive or invasive. Here, we developed a cost-effective, time-saving, and painless method for the screening of HCC via machine learning based on atmospheric pressure glow discharge mass spectrometry (APGD-MS). Ninety urine samples from HCC patients and healthy control (HC) participants were analyzed. The relative quantification data were utilized to train machine learning models. Neural network was chosen as the best classifier with a classification accuracy of 94%. Besides, the levels of eleven urinary carbonyl metabolites were found to be significantly different between HCC and HC, including glycolic acid, pyroglutamic acid, acetic acid, etc. The possible reasons for the regulation were tentatively proposed. This method realizes the screening of HCC via potential urine metabolic biomarkers based on APGD-MS, bringing a hopeful point-of-care diagnosis of HCC in a patient-friendly manner.

Correction: Machine learning encodes urine and serum metabolic patterns for autoimmune disease discrimination, classification and metabolic dysregulation analysis.

Correction for 'Machine learning encodes urine and serum metabolic patterns for autoimmune disease discrimination, classification and metabolic dysregulation analysis' by Qiuyao Du et al., Analyst, 2023, https://doi.org/10.1039/d3an01051a.

Machine learning encodes urine and serum metabolic patterns for autoimmune disease discrimination, classification and metabolic dysregulation analysis.

There is a wide variety of autoimmune diseases (ADs) with complex pathogenesis and their accurate diagnosis is difficult to achieve because of their vague symptoms. Metabolomics has been proven to be an efficient tool in the analysis of metabolic disorders to provide clues about the mechanism and diagnosis of diseases. Previous studies of the metabolomics analysis of ADs were not competent in their discrimination. Herein, a liquid chromatography tandem mass spectrometry (LC-MS) strategy combined with machine learning is proposed for the discrimination and classification of ADs. Urine and serum samples were collected from 267 subjects consisting of 127 healthy controls (HC) and 140 AD patients, including those with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), sicca syndrome (SS), ankylosing spondylitis (AS), systemic scleroderma (SSc) and connective tissue disease (CTD). Machine learning algorithms were encoded for the discrimination and classification of ADs with metabolomic patterns obtained by LC-MS, and satisfactory results were achieved. Notably, urine samples exhibited higher accuracy for disease differentiation and triage than serum samples. Apart from that, differential metabolites were selected and metabolite panels were evaluated to demonstrate their representativeness. Metabolic dysregulations were also investigated to gain more knowledge about the pathogenesis of ADs. This research provides a promising method for the application of metabolomics combined with machine learning in precision medicine.

High Speed Mass Measurement of a Single Metal-Organic Framework Nanocrystal in a Paul Trap.

Mass spectrometry (MS) has emerged as an excellent tool for the characterization of metal-organic frameworks (MOFs) based on the characteristic metal ions and organic ligands. Mass measurement of intact MOF nanocrystals, however, remains a challenge for MS technology. Here, we reported the development of a probe particles based charge detection-quadrupole ion trap mass spectrometry (probe CD-QIT MS) method, where charge detection and mass measurement of a single MOF nanocrystal were achieved under the assistance of probe particles of micrometer size. As a validation of the method, the masses of a series of polystyrene (PS) size standards from 493 nm to 1.6 µm were measured with 3 µm PS particles as probes, and the measured masses were found to match well with their certified masses. Then, charge detections and mass analysis of single ZIF-8 and GOx@ZIF-8 with a size around 600 nm were achieved successfully. The method presented here demonstrates simplicity, high speed, and accuracy. Notably, it allows quantitative measurement of the amount of immobilized GOx enzyme by using the mass difference between ZIF-8 and GOx@ZIF-8. In addition, based on the determined mass, the size analysis of these MOF particles with irregular shape was carried out and demonstrated to be complementary to transmission electron microscopy (TEM).

Development of an Automatic Ultrasonic Matrix Sprayer for Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging.

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) has emerged as a powerful tool for studying the spatial distribution of various types of molecules. Matrix deposition is a critical step for obtaining high-quality imaging data. An automatic device named SoniCoat was fabricated based on an ultrasonic nozzle driven by a pizeoelectric ceramic for matrix coating in the present study. Compared with the minihumidifier developed previously by our group for matrix deposition, SoniCoat realized automation, and the ultrasonic nozzle of this device is easy to clean and less likely to get clogged, indicating a longer life. Compared with commercial and homemade instruments such as the TM-Sprayer and electrospray matrix coating device, our newly developed device achieved a good nebulization effect without the need for high-pressure gas flow and high voltage. Matrix deposition by SoniCoat generated more homogeneous matrix crystals with diameters of about 10 µm and reduced the occurrence of molecular diffusion to a greater extent, compared with the results by TM-Sprayer. Repeatable high-spatial-resolution MS imaging data were obtained with the help of SoniCoat. Furthermore, the newly developed device can also be successfully applied for in situ derivatization.

Biofluids Metabolic Profiling Based on PS@Fe3O4-NH2 Magnetic Beads-Assisted LDI-MS for Liver Cancer Screening.

Liver cancer (LC) is the third frequent cause of death worldwide, so early diagnosis of liver cancer patients is crucial for disease management. Herein, we applied NH2-coated polystyrene@Fe3O4 magnetic beads (PS@Fe3O4-NH2 MBs) as a matrix material in laser desorption/ionization mass spectrometry (LDI-MS). Rapid, sensitive, and selective metabolic profiling of the native biofluids was achieved without any inconvenient enrichment or purification. Then, based on the selected m/z features, LC patients were discriminated from healthy controls (HCs) by machine learning, with the high area under the curve (AUC) values for urine and serum assessments (0.962 and 0.935). Moreover, initial-diagnosed and subsequent-visited LC patients were also differentiated, which indicates potential applications of this method in early diagnosis. Furthermore, among these identified compounds by FT-ICR MS, the expression level of some metabolites changed from HCs to LCs, including 29 and 12 characteristic metabolites in human urine and serum samples, respectively. These results suggest that PS@Fe3O4-NH2 MBs-assisted LDI-MS coupled with machine learning is feasible for LC clinical diagnosis.

Profiling of Urine Carbonyl Metabolic Fingerprints in Bladder Cancer Based on Ambient Ionization Mass Spectrometry.

The diagnosis of bladder cancer (BC) is currently based on cystoscopy, which is invasive and expensive. Here, we describe a noninvasive profiling method for carbonyl metabolic fingerprints in BC, which is based on a desorption, separation, and ionization mass spectrometry (DSI-MS) platform with N,N-dimethylethylenediamine (DMED) as a differential labeling reagent. The DSI-MS platform avoids the interferences from intra- and/or intersamples. Additionally, the DMED derivatization increases detection sensitivity and distinguishes carboxyl, aldehyde, and ketone groups in untreated urine samples. Carbonyl metabolic fingerprints of urine from 41 BC patients and 41 controls were portrayed and 9 potential biomarkers were identified. The mechanisms of the regulations of these biomarkers have been tentatively discussed. A logistic regression (LR) machine learning algorithm was applied to discriminate BC from controls, and an accuracy of 85% was achieved. We believe that the method proposed here may pave the way toward the point-of-care diagnosis of BC in a patient-friendly manner.

Laser Desorption/Ionization Mass Spectrometry Imaging: A New Tool to See through Nanoscale Particles in Biological Systems.

Understanding the fate of nanoscale particles (NPs) in biological systems is significant with the increasing risk for human exposure. Recent research endeavors in laser desorption/ionization mass spectrometry imaging (LDI-MSI) have enriched the toolbox for evaluation of NPs' behavior in biological tissues, especially in aspects including sub-organ bio-distribution, clearance, quantification and surface chemistry variation analysis. In recognition of the potential for advancement in LDI MSI, this concept provides a brief overview of recent research works in LDI MSI for NPs, illustrates new applications that demonstrate the superiority of this technique, and highlights a series of perspectives and directions to move the field forward.

Rapid detection and classification of hongmu by atmospheric pressure ionization mass spectrometry.

Hongmu, a Chinese customary noun representing 29 kinds of wood species such as some Pterocarpus species (abbreviated as spp. hereinafter), Dalbergia spp. and Diospyros spp., is popular among Chinese people due to the furniture made from it. The slow regeneration of hongmu resources led to a decline in production, making hongmu prices high and illegal businesses profit from it. Therefore, it is necessary to identify and distinguish different varieties of hongmu for commercial trade. Herein, a cost-effective and rapid methodology was first developed via atmospheric pressure glow discharge mass spectrometry (APGD-MS) to classify three Dalbergia spp. and three Pterocarpus spp. Meanwhile, principal component analysis (PCA) was further applied to distinguish wood species and six kinds of hongmu extracts were able to be approximately separated into six units. Besides, hongmu could be clearly distinguished from their counterfeits, such as Guibourtia spp., using the method provided here. This method may provide a timely and necessary way for the determination of ingredients and identification of the authenticity of hongmu.

Altered prefrontal neurochemistry in the DJ-1 knockout mouse model of Parkinson's disease: complementary semi-quantitative analyses with in vivo magnetic resonance spectroscopy and MALDI-MSI.

In vivo proton magnetic resonance spectroscopy (1H-MRS) and matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) are two semi-quantitative analytical methods commonly used in neurochemical research. In this study, the two methods were used complementarily, in parallel, to investigate neurochemical perturbations in the medial prefrontal cortex (mPFC) of 9-month-old DJ-1 knockout mice, a well-established transgenic model for Parkinson's diseases. Convergingly, the results obtained with the two methods demonstrated that, compared with the wild-type (WT) mice, the DJ-1 knockout mice had significantly increased glutathione (GSH) level and GSH/glutamate (Glu) ratio in the mPFC, which likely presented an astrocytic compensatory mechanism in response to elevated regional oxidative stress induced by the loss of DJ-1 function. The results from this study also highlighted (1) the need to be cautious when interpreting the in vivo 1H-MRS results obtained from aged transgenic animals, in which the concentration of internal reference, being whether water or total creatine, could no longer be assumed to be the same as that in the age-matched WT animals, and (2) the necessity and importance of complementary analyses with more than one method under such circumstances.

Mass spectrometry for multi-dimensional characterization of natural and synthetic materials at the nanoscale.

Characterization of materials at the nanoscale plays a crucial role in in-depth understanding the nature and processes of the substances. Mass spectrometry (MS) has characterization capabilities for nanomaterials (NMs) and nanostructures by offering reliable multi-dimensional information consisting of accurate mass, isotopic, and molecular structural information. In the last decade, MS has emerged as a powerful nano-characterization technique. This review comprehensively summarizes the capabilities of MS in various aspects of nano-characterization that greatly enrich the toolbox of nano research. Compared with other characterization techniques, MS has unique capabilities for real-time monitoring and tracking reaction intermediates and by-products. Moreover, MS has shown application potential in some novel aspects, such as MS imaging of the biodistribution and fate of NMs in animals and humans, stable isotopic tracing of NMs, and risk assessment of NMs, which deserve update and integration into the current knowledge framework of nano-characterization.

Chiral Primary Amine/Ketone Cooperative Catalysis for Asymmetric α-Hydroxylation with Hydrogen Peroxide.

Carbonyls and amines are yin and yang in organocatalysis as they mutually activate and transform each other. These intrinsically reacting partners tend to condense with each other, thus depleting their individual activity when used together as cocatalysts. Though widely established in many prominent catalytic strategies, aminocatalysis and carbonyl catalysis do not coexist well, and, as such, a cooperative amine/carbonyl dual catalysis remains essentially unknown. Here we report a cooperative primary amine and ketone dual catalytic approach for the asymmetric α-hydroxylation of ß-ketocarbonyls with H2O2. Besides participating in the typical enamine catalytic cycle, the chiral primary amine catalyst was found to work cooperatively with a ketone catalyst to activate H2O2 via an oxaziridine intermediate derived from an in-situ-generated ketimine. Ultimately, this enamine-oxaziridine coupling facilitated the highly controlled α-hydroxylation of several ß-ketocarbonyls in excellent yield and enantioselectivity. Notably, late-stage hydroxylation for peptidyl amide or chiral esters can also be achieved with high stereoselectivity. In addition to its operational simplicity and mild conditions, this cooperative amine/ketone catalytic approach also provides a new strategy for the catalytic activation of H2O2 and expands the domain of typical amine and carbonyl catalysis to include this challenging transformation.

Pocket-Size "MasSpec Pointer" for Ambient Ionization Mass Spectrometry.

Current ambient ionization sources for mass spectrometry (MS) are typically connected to gas cylinders, high-voltage supply, injection pump, and other accessory equipment, which hinder the popularization of MS in the field of on-site detection. Here, we developed a wireless pocket-size "MasSpec Pointer" (weights 65 g) based on arc discharge powered by a 3.7 V polymer Li battery for ambient ionization MS. A high voltage of 5600 V and 20 kHz was generated from the boost coil to penetrate air and form a plasma. The relative standard deviation (RSD) of the high-voltage pulses is 3.8%, leading to a stable discharge and a good quantification performance. A mini diaphragm pump was used to cool the plasma from ∼600 to ∼40 °C and to blow the plasma into a jet, which facilitates sampling. MasSpec Pointer can work well at both positive- and negative-ion modes without any modification and can quickly test gaseous, liquid, or solid samples. The limit of detection of this device for atrazine (an agrochemical) is lower than 0.1 ng/mL. MasSpec Pointer has shown its ability to pinpoint the double-bond location of fatty acid isomers without derivatization reagents or light illumination. Agrochemicals from the surface of an apple and daily chemicals from the surface of a finger were detected successfully using MasSpec Pointer coupled with a miniature mass spectrometer. We believe the "point-and-shoot" device coupled with mini-MS brings the hope for an age of detecting chemicals on-site by nonprofessionals.

Point-of-Care Test Paper for Exhaled Breath Aldehyde Analysis via Mass Spectrometry.

Volatile organic compounds (VOCs) from exhaled breath (EB) are considered to be promising biomarkers for lung diseases. A convenient and sensitive point-of-care (POC) testing method for EB VOCs is essential. Here, we developed a POC test paper for the analysis of EB aldehydes, which are potential biomarkers for lung cancer. A probe molecule, 4-aminothiophenol (4-ATP), was anchored on a paper substrate to specifically capture gas-phase aldehydes through the Schiff base reaction. Meanwhile, thin-film reaction acceleration was utilized to increase capture efficiency. By directly coupling the test paper to a mass spectrometer through paper spray, high sensitivity (0.1 ppt) and a wide quantification linear range (from 10 ppt to 1 ppm) were obtained. Analysis of EB from lung cancer patients with the test paper showed a significant increase in several reported aldehyde markers compared to EB from healthy volunteers, indicating the potential of this method for sensitive, low-cost, and convenient lung cancer screening and diagnosis.

Development of capillary-paper spray for small-molecule analysis in complex samples.

We develop a capillary-paper spray (CPS) ion source which allows for sample separation in the capillary and enables rapid and sensitive paper spray (PS) mass spectrometry (MS) analysis of biofluids. The CPS employs a glass capillary to load liquid analytes, vertically standing at the rear of the PS. To further reduce the matrix effect, a nitrocellulose filter membrane is placed between the glass tube and chromatography paper to absorb proteins and other macromolecules, which is beneficial for the detection of the small molecules. Compared with the normal PS method, the CPS method markedly improves spray stability and prolongs analysis duration, and also generates significantly better signal intensities during the analysis of drugs, thus indicating its potential for clinical use. As a proof of concept, quantitative analysis of drugs (metformin hydrochloride and berberine hydrochloride) in serum is performed.