Predicting effect of anti-PD-1/PD-L1 inhibitors therapy for hepatocellular carcinoma by detecting plasma metabolite based on UHPLC-MS.

Introduction: Anti-PD-1/PD-L1 inhibitors therapy has become a promising treatment for hepatocellular carcinoma (HCC), while the therapeutic efficacy varies significantly among effects for individual patients are significant difference. Unfortunately, specific predictive biomarkers indicating the degree of benefit for patients and thus guiding the selection of suitable candidates for immune therapy remain elusive.no specific predictive biomarkers are available indicating the degree of benefit for patients and thus screening the preferred population suitable for the immune therapy. Methods: Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) considered is an important method for analyzing biological samples, since it has the advantages of high rapid, high sensitivity, and high specificity. Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) has emerged as a pivotal method for analyzing biological samples due to its inherent advantages of rapidity, sensitivity, and specificity. In this study, potential metabolite biomarkers that can predict the therapeutic effect of HCC patients receiving immune therapy were identified by UHPLC-MS. Results: A partial least-squares discriminant analysis (PLS-DA) model was established using 14 glycerophospholipid metabolites mentioned above, and good prediction parameters (R2 = 0.823, Q2 = 0.615, prediction accuracy = 0.880 and p < 0.001) were obtained. The relative abundance of glycerophospholipid metabolite ions is closely related to the survival benefit of HCC patients who received immune therapy. Discussion: This study reveals that glycerophospholipid metabolites play a crucial role in predicting the efficacy of immune therapy for HCC.

Intercropping with maize and sorghum-induced saikosaponin accumulation in Bupleurum chinense DC. by liquid chromatography-mass spectrometry-based metabolomics.

Bupleuri Radix is an important medicinal plant, which has been used in China and other Asian countries for thousands of years. Cultivated Bupleurum chinense DC. (B. chinense) is the main commodity of Bupleuri Radix. The benefits of intercropping with various crops for B. chinense have been recognized; however, the influence of intercropping on the chemical composition of B. chinense is still unclear yet. In this study, intercropping with sorghum and maize exhibited little effect on the root length, root diameter, and single root mass of B. chinense. Only the intercropping with sorghum increased the root length of B. chinense slightly compared to the monocropping. In addition, 200 compounds were identified by UHPLC-Q-TOF-MS, and metabolomic combined with the Venn diagram and heatmap analysis showed apparent separation between the intercropped and monocropped B. chinense samples. Intercropping with sorghum and maize could both increase the saikosaponins, fatty acyls, and organic acids in B. chinense while decreasing the phospholipids. The influence of intercropping on the saikosaponin biosynthesis was probably related with the light intensity and hormone levels in B. chinense. Moreover, we found intercropping increased the anti-inflammatory activity of B. chinense. This study provides a scientific reference for the beneficial effect of intercropping mode of B. chinense.

Impact of extraction method on the lipids of Himalayan marmot oil with ultrahigh-performance liquid chromatography Q-Exactive Orbitrap mass spectrometry analysis.

RATIONALE: Himalayan marmot oil (SPO) has been used for pharmaceutical purposes for centuries, but its composition is still unclear. The bioactivity of SPO highly depends on the techniques used for its processing. This study focused on the comprehensive lipidomics of SPO, especially on the ones derived from dry rendering, wet rendering, cold pressing, and ultrasound-assisted solvent extraction. METHODS: We performed lipid profiling of SPO acquired by different extraction methods using ultrahigh-performance liquid chromatography Q-Exactive Orbitrap mass spectrometry, and 17 classes of lipids (2 BMPs, 12 LysoPCs, 9 LysoPEs, 41 PCs, 24 PEs, 23 Plasmenyl-PCs, 10 Plasmenyl-PEs, 10 MGs, 63 DGs, 187 TGs, 2 MGDGs, 3 Cer[NDS]s, 22 Cer[NS]s, 2 GlcCer[NS]s, 14 SMs, 14 CEs, and 6 AcylCarnitines) were characterized. RESULTS: Fifty-five lipids were differentially altered (VIP > 1.5, p < 0.05) between the extraction techniques, which can be used as potential biomarkers to differentiate SPO extracted by various methods. Additionally, the contents of oleic acid and arachidic acid were abundant in all samples that may suggest their medicinal values and are conducive to in-depth research. CONCLUSIONS: These findings reveal the alterations of lipid profile and free fatty acid composition in SPO obtained with different extraction methods, providing a theoretical foundation for investigating its important components as functional factors in medicines and cosmetics.

Tear Proteomics in Infants at Risk of Retinopathy of Prematurity: A Feasibility Study.

Purpose: This feasibility study investigated the practicability of collecting and analyzing tear proteins from preterm infants at risk of retinopathy of prematurity (ROP). We sought to identify any tear proteins which might be implicated in the pathophysiology of ROP as well as prognostic markers. Methods: Schirmer's test was used to obtain tear samples from premature babies, scheduled for ROP screening, after parental informed consent. Mass spectrometry was used for proteomic analysis. Results: Samples were collected from 12 infants, which were all adequate for protein analysis. Gestational age ranged from 25 + 6 to 31 + 1 weeks. Postnatal age at sampling ranged from 19 to 66 days. One infant developed self-limiting ROP. Seven hundred one proteins were identified; 261 proteins identified in the majority of tear samples, including several common tear proteins, were used for analyses. Increased risk of ROP as determined by the postnatal growth ROP (G-ROP) criteria was associated with an increase in lactate dehydrogenase B chain in tears. Older infants demonstrated increased concentration of immunoglobulin complexes within their tear samples and two sets of twins in the cohort showed exceptionally similar proteomes, supporting validity of the analysis. Conclusions: Tear sampling by Schirmer test strips and subsequent proteomic analysis by mass spectrometry in preterm infants is feasible. A larger study is required to investigate the potential use of tear proteomics in identification of ROP. Translational Relevance: Tear sampling and subsequent mass spectrometry in preterm infants is feasible. Investigation of the premature tear proteome may increase our understanding of retinal development and provide noninvasive biomarkers for identification of treatment-warranted ROP.

Rapid detection of IDH mutations in gliomas by intraoperative mass spectrometry.

The development and performance of two mass spectrometry (MS) workflows for the intraoperative diagnosis of isocitrate dehydrogenase (IDH) mutations in glioma is implemented by independent teams at Mayo Clinic, Jacksonville, and Huashan Hospital, Shanghai. The infiltrative nature of gliomas makes rapid diagnosis necessary to guide the extent of surgical resection of central nervous system (CNS) tumors. The combination of tissue biopsy and MS analysis used here satisfies this requirement. The key feature of both described methods is the use of tandem MS to measure the oncometabolite 2-hydroxyglutarate (2HG) relative to endogenous glutamate (Glu) to characterize the presence of mutant tumor. The experiments i) provide IDH mutation status for individual patients and ii) demonstrate a strong correlation of 2HG signals with tumor infiltration. The measured ratio of 2HG to Glu correlates with IDH-mutant (IDH-mut) glioma (P < 0.0001) in the tumor core data of both teams. Despite using different ionization methods and different mass spectrometers, comparable performance in determining IDH mutations from core tumor biopsies was achieved with sensitivities, specificities, and accuracies all at 100%. None of the 31 patients at Mayo Clinic or the 74 patients at Huashan Hospital were misclassified when analyzing tumor core biopsies. Robustness of the methodology was evaluated by postoperative re-examination of samples. Both teams noted the presence of high concentrations of 2HG at surgical margins, supporting future use of intraoperative MS to monitor for clean surgical margins. The power of MS diagnostics is shown in resolving contradictory clinical features, e.g., in distinguishing gliosis from IDH-mut glioma.

Comprehensive profiling of the chemical constituents in Dayuanyin decoction using UPLC-QTOF-MS combined with molecular networking.

CONTEXT: Dayuanyin decoction is a traditional Chinese medicine formulation that is commonly used in modern clinical practice to treat viral infections such as viral pneumonia, viral fever, influenza, and hepatitis. Although the usage rate of Dayuanyin decoction is gradually increasing in clinical practice, its pharmacological constituents are still unclear. OBJECTIVE: This study comprehensively characterized the chemical constituents in Dayuanyin decoction using ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) and molecular networking. MATERIALS AND METHODS: The overall strategy involved retrieving structural information, such as fragment ions and precursor ion masses, from self-built databases to identify the target constituents of the Dayuanyin decoction extract. The identification of non-targeted constituents was achieved by analyzing different categories, fragment pathways, mass spectrometry data, and the relationships between clusters of structures in molecular networking. Unannotated constituents were inferred from secondary mass spectrometry similarity and molecular weight differences and annotated constituents in the same constituent cluster. A few predicted constituents were selected and validated by comparing them to reference standards under identical mass spectrometry conditions. RESULTS: This study preliminarily identified 216 constituents, including flavonoids, amino acids, alkaloids, triterpenes, steroidal saponins, phenylpropanoids, and other constituents. CONCLUSIONS: This integrated strategy using UPLC-QTOF-MS and molecular networking lays the foundation for clinical research on pharmacologically active substances in Dayuanyin decoction and could be popularized for the comprehensive profiling of chemical constituents of other traditional Chinese medicines.

Rapid evaporative ionization mass spectrometry: A survey through 15 years of applications.

Rapid evaporative ionization mass spectrometry (REIMS) is a relatively recent MS technique explored in many application fields, demonstrating high versatility in the detection of a wide range of chemicals, from small molecules (phenols, amino acids, di- and tripeptides, organic acids, and sugars) to larger biomolecules, that is, phospholipids and triacylglycerols. Different sampling devices were used depending on the analyzed matrix (liquid or solid), resulting in distinct performances in terms of automation, reproducibility, and sensitivity. The absence of laborious and time-consuming sample preparation procedures and chromatographic separations was highlighted as a major advantage compared to chromatographic methods. REIMS was successfully used to achieve a comprehensive sample profiling according to a metabolomics untargeted analysis. Moreover, when a multitude of samples were available, the combination with chemometrics allowed rapid sample differentiation and the identification of discriminant features. The present review aims to provide a survey of literature reports based on the use of such analytical technology, highlighting its mode of operation in different application areas, ranging from clinical research, mostly focused on cancer diagnosis for the accurate identification of tumor margins, to the agri-food sector aiming at the safeguard of food quality and security.

Discrimination of three commercial tuna species through species-specific peptides: From high-resolution mass spectrometry discovery to MRM validation.

The risk of tuna adulteration is high driven by economic benefits. The authenticity of tuna is required to protect both consumers and tuna stocks. Given this, the study is designed to identify species-specific peptides for distinguishing three commercial tropical tuna species. The peptides derived from trypsin digestion were separated and detected using ultrahigh-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UPLC-Q-TOF/MS) in data-dependent acquisition (DDA) mode. Venn analysis showed that there were differences in peptide composition among the three tested tuna species. The biological specificity screening through the National Center for Biotechnology Information's Basic Local Alignment Search Tool (NCBI BLAST) revealed that 93 peptides could serve as potential species-specific peptides. Finally, the detection specificity of species-specific peptides of raw meats and processed products was carried out by multiple reaction monitoring (MRM) mode based on a Q-Trap mass spectrometer. The results showed that three, one and two peptides of Katsuwonus pelamis, Thunnus obesus and Thunnus albacores, respectively could serve as species-specific peptides.

Alkylresorcinol detection and identification in archaeological pottery using ultra-high-performance liquid chromatography-quadrupole/Orbitrap mass spectrometry.

RATIONALE: Alkylresorcinols (AR) are cereal-specific biomarkers and have recently been found in archaeological pots. However, their low concentrations and high susceptibility to degradation make them difficult to detect using conventional gas chromatography mass spectrometry (GC/MS). Here we describe the development of a more sensitive liquid chromatography mass spectrometry (LC/MS) method to detect these compounds. METHOD: A method based on the use of ultra-high-performance liquid chromatography (UHPLC) coupled to an Orbitrap mass analyser was established and validated for the detection of low-concentration ARs in pottery. During the preliminary experiments, UHPLC-Q/Orbitrap MS (ultra-high-performance liquid chromatography-quadrupole/Orbitrap mass spectrometry) was demonstrated to be more sensitive, and a wide range of AR homologues in cereal extracts were detected, unlike UHPLC-QTOFMS (ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry) and GC/MS. The developed method was utilised to profile AR homologue distribution in modern cereal samples and reanalyse AR-containing pots from the archaeological site of Must Farm. RESULTS: A highly sensitive LC/MS method with a limit of detection (LOD) of 0.02 µg/g and a limit of quantification (LOQ) of 0.06 µg/g was used to profile ARs in five modern cereal grains. The obtained LOD is 250 times lower than that obtained using the conventional GC/MS approach. AR 21:0 was the most abundant homologue in all four Triticum spp.-einkorn, emmer, Khorasan wheat and common wheat. Meanwhile, AR 25:0 was the predominant homologue in barley, potentially enabling differentiation between wheat and barley. The developed LC/MS-based method was successfully used to analyse ARs extracted from Must Farm potsherds and identified the cereal species most likely processed in the pots-emmer wheat. CONCLUSION: The described method offers an alternative and more sensitive approach for detecting and identifying ARs in ancient pottery. It has been successfully utilised to detect AR homologues in archaeological samples and discriminate which cereal species-wheat and barley-were processed in the pots.

Lipidomics random forest algorithm of seminal plasma is a promising method for enhancing the diagnosis of necrozoospermia.

BACKGROUND: Despite the clear clinical diagnostic criteria for necrozoospermia in andrology, the fundamental mechanisms underlying it remain elusive. This study aims to profile the lipid composition in seminal plasma systematically and to ascertain the potential of lipid biomarkers in the accurate diagnosis of necrozoospermia. It also evaluates the efficacy of a lipidomics-based random forest algorithm model in identifying necrozoospermia. METHODS: Seminal plasma samples were collected from patients diagnosed with necrozoospermia (n = 28) and normozoospermia (n = 28). Liquid chromatography-mass spectrometry (LC-MS) was used to perform lipidomic analysis and identify the underlying biomarkers. A lipid functional enrichment analysis was conducted using the LION lipid ontology database. The top 100 differentially significant lipids were subjected to lipid biomarker examination through random forest machine learning model. RESULTS: Lipidomic analysis identified 46 lipid classes comprising 1267 lipid metabolites in seminal plasma. The top five enriched lipid functions as follows: fatty acid (FA) with ≤ 18 carbons, FA with 16-18 carbons, monounsaturated FA, FA with 18 carbons, and FA with 16 carbons. The top 100 differentially significant lipids were subjected to machine learning analysis and identified 20 feature lipids. The random forest model identified lipids with an area under the curve > 0.8, including LPE(20:4) and TG(4:0_14:1_16:0). CONCLUSIONS: LPE(20:4) and TG(4:0_14:1_16:0), were identified as differential lipids for necrozoospermia. Seminal plasma lipidomic analysis could provide valuable biochemical information for the diagnosis of necrozoospermia, and its combination with conventional sperm analysis may improve the accuracy and reliability of the diagnosis.

NMR and LC-MS-based metabolomics to investigate the efficacy of a commercial bio stimulant for the treatment of wheat (Triticum aestivum).

INTRODUCTION: Bio stimulants are substances and/or microorganisms that are used to improve plant growth and crop yields by modulating physiological processes and metabolism of plants. While research has primarily focused on the broad effects of bio stimulants in crops, understanding their cellular and molecular influences in plants, using metabolomic analysis, could elucidate their effectiveness and offer possibilities for fine-tuning their application. One such bio stimulant containing galacturonic acid as elicitor is used in agriculture to improve wheat vigor and strengthen resistance to lodging. OBJECTIVE: However, whether a metabolic response is evolved by plants treated with this bio stimulant and the manner in which the latter might regulate plant metabolism have not been studied. METHOD: Therefore, the present study used 1H-NMR and LC-MS to assess changes in primary and secondary metabolites in the roots, stems, and leaves of wheat (Triticum aestivum) treated with the bio stimulant. Orthogonal partial least squares discriminant analysis effectively distinguished between treated and control samples, confirming a metabolic response to treatment in the roots, stems, and leaves of wheat. RESULTS: Fold-change analysis indicated that treatment with the bio stimulation solution appeared to increase the levels of hydroxycinnamic acid amides, lignin, and flavonoid metabolism in different plant parts, potentially promoting root growth, implantation, and developmental cell wall maturation and lignification. CONCLUSION: These results demonstrate how non-targeted metabolomic approaches can be utilized to investigate and monitor the effects of new agroecological solutions based on systemic responses.

Analytical methods for stable isotope labeling to elucidate rapid auxin kinetics in Arabidopsis thaliana.

The phytohormone auxin plays a critical role in plant growth and development. Despite significant progress in elucidating metabolic pathways of the primary bioactive auxin, indole-3-acetic acid (IAA), over the past few decades, key components such as intermediates and enzymes have not been fully characterized, and the dynamic regulation of IAA metabolism in response to environmental signals has not been completely revealed. In this study, we established a protocol employing a highly sensitive liquid chromatography-mass spectrometry (LC-MS) instrumentation and a rapid stable isotope labeling approach. We treated Arabidopsis seedlings with two stable isotope labeled precursors ([13C6]anthranilate and [13C8, 15N1]indole) and monitored the label incorporation into proposed indolic compounds involved in IAA biosynthetic pathways. This Stable Isotope Labeled Kinetics (SILK) method allowed us to trace the turnover rates of IAA pathway precursors and product concurrently with a time scale of seconds to minutes. By measuring the entire pathways over time and using different isotopic tracer techniques, we demonstrated that these methods offer more detailed information about this complex interacting network of IAA biosynthesis, and should prove to be useful for studying auxin metabolic network in vivo in a variety of plant tissues and under different environmental conditions.

Integrating cryo-OrbiSIMS with computational modelling and metadynamics simulations enhances RNA structure prediction at atomic resolution.

The 3D architecture of RNAs governs their molecular interactions, chemical reactions, and biological functions. However, a large number of RNAs and their protein complexes remain poorly understood due to the limitations of conventional structural biology techniques in deciphering their complex structures and dynamic interactions. To address this limitation, we have benchmarked an integrated approach that combines cryogenic OrbiSIMS, a state-of-the-art solid-state mass spectrometry technique, with computational methods for modelling RNA structures at atomic resolution with enhanced precision. Furthermore, using 7SK RNP as a test case, we have successfully determined the full 3D structure of a native RNA in its apo, native and disease-remodelled states, which offers insights into the structural interactions and plasticity of the 7SK complex within these states. Overall, our study establishes cryo-OrbiSIMS as a valuable tool in the field of RNA structural biology as it enables the study of challenging, native RNA systems.

Proof of concept evidence that stable isotopes of carbon, nitrogen and sulphur may identify individual kittiwakes breeding in different colonies.

RATIONALE: Carbon, nitrogen and sulphur stable isotopes in feathers grown by seabirds while breeding reflect the local isoscape and diet in the vicinity of the colony, so may make it possible to discriminate individual birds from different colonies. METHODS: Black-legged kittiwake Rissa tridactyla inner primary feathers from two colonies about 350 km apart in the North Sea were used to test whether δ13C, δ15N and δ34S differed between individuals from the two colonies. Feather tips cut from breeding birds caught at nests were compared with tips of moulted feathers (grown 1 year earlier) found on the ground. RESULTS: Isotopic compositions showed no overlap between the two colonies in δ13C, δ15N or δ34S in tips of newly-grown feathers sampled from breeding adult kittiwakes. There was some overlap in δ13C, δ15N and δ34S from moulted feathers, but discriminant analysis allowed >90% of individuals to be assigned to their colony. In five of six comparisons, mean isotopic compositions were the same in new and moulted feathers but not for δ34S at one of the two colonies. CONCLUSIONS: This study has demonstrated for the first time that stable isotopes in inner primary feathers of kittiwakes can allow accurate identification of the breeding colony of individual birds from two different colonies within the North Sea. Further research is required to determine if this method can be applied with greater spatial resolution and to a larger number of colonies.

Evaluation of pretreatment methods for filamentous fungal detection.

In order to obtain the best mass spectrometry identification results for using the most appropriate methods in clinical practice, we explore the optimal pretreatment methods for different species and morphologies of filamentous fungi. 98 fungal strains were treated with formic acid sandwich method, dispersion method, extraction method, and other methods using a medium element mass spectrometer (EXS3000) as a platform. Each strain had three targets, and the identification rates and confidence differences under different pre-treatment methods were compared to evaluate the identification effects of these methods. The mass spectrometry identification rates of 98 filamentous fungi obtained after pre-treatment with formic acid sandwich method, dispersion method, and extraction method were 85.71%, 82.65%, and 75.51%, respectively. The identification rate of the formic acid sandwich method was significantly higher than the other two methods (P < 0 005) has the best identification ability and the obtained confidence is also higher than the other two methods. The use of formic acid sandwich method for mass spectrometry identification of filamentous fungi can achieve ideal identification results, which is suitable for mass spectrometry identification of filamentous fungi in conventional laboratories.

Characterization of Human B Cell Hematological Malignancies Using Protein-Based Approaches.

The maturation of B cells is a complex, multi-step process. During B cell differentiation, errors can occur, leading to the emergence of aberrant versions of B cells that, finally, constitute a malignant tumor. These B cell malignancies are classified into three main groups: leukemias, myelomas, and lymphomas, the latter being the most heterogeneous type. Since their discovery, multiple biological studies have been performed to characterize these diseases, aiming to define their specific features and determine potential biomarkers for diagnosis, stratification, and prognosis. The rise of advanced -omics approaches has significantly contributed to this end. Notably, proteomics strategies appear as promising tools to comprehensively profile the final molecular effector of these cells. In this narrative review, we first introduce the main B cell malignancies together with the most relevant proteomics approaches. Then, we describe the core studies conducted in the field and their main findings and, finally, we evaluate the advantages and drawbacks of flow cytometry, mass cytometry, and mass spectrometry for the profiling of human B cell disorders.

Proteomic Profiling of Samples Derived from a Murine Model Following Cryptococcus neoformans Infection.

Proteomic profiling provides in-depth information about the regulation of diverse biological processes, activation of and communication across signaling networks, and alterations to protein production, modifications, and interactions. For infectious disease research, mass spectrometry-based proteomics enables detection of host defenses against infection and mechanisms used by the pathogen to evade such responses. In this chapter, we outline protein extraction from organs, tissues, and fluids collected following intranasal inoculation of a murine model with the human fungal pathogen Cryptococcus neoformans. We describe sample preparation, followed by purification, processing on the mass spectrometer, and a robust bioinformatics analysis. The information gleaned from proteomic profiling of fungal infections supports the detection of novel biomarkers for diagnostic and prognostic purposes.

LC-MS-based metabolomics reveals metabolite dynamic changes of beef after superchilling early post-mortem.

To explore the underlying mechanisms by which superchilling (SC, -3 °C within 5 h of slaughter) improves beef tenderness, an untargeted metabolomics strategy was employed. M. Longissimus lumborum (LL) muscles from twelve beef carcasses were assigned to either SC or very fast chilling (VFC, 0 °C within 5 h of slaughter) treatments, with conventional chilling (CC, 0 âˆ¼ 4 °C until 24 h post-mortem) serving as the control (6 per group). Biochemical properties and metabolites were investigated during the early post-mortem period. The results showed that the degradation of µ-calpain and caspase 3 occurred earlier in SC treated sample, which might be attributed to the accelerated accumulation of free Ca2+. The metabolomic profiles of samples from the SC and CC treatments were clearly distinguished based on partial least squares-discriminant analysis (PLS-DA) at each time point. It is noteworthy that more IMP and 4-hydroxyproline were found in the comparison between SC and CC treatments. According to the results of metabolic pathways analysis and the correlation analysis between traits related to tenderness and metabolites with significant differences (SC vs. CC), it can be suggested that the tenderization effect of the SC treatment may be related to the alteration of arginine and proline metabolism, and purine metabolism in the early post-mortem phase.

Impact of four different extraction methods and three different reconstitution solvents on the untargeted metabolomics analysis of human and rat urine samples.

Unsuitable sample preparation may result in loss of important analytes and consequently affect the outcome of untargeted metabolomics. Due to species differences, different sample preparations may be required within the same biological matrix. The study aimed to compare the in-house sample preparation method for urine with methods from literature and to investigate the transferability of sample preparation from human urine to rat urine. A total of 12 different conditions for protein precipitation were tested, combining four different extraction solvents and three different reconstitution solvents using an untargeted liquid-chromatography high resolution mass spectrometry (LC-HRMS) metabolomics analysis. Evaluation was done based on the impact on feature count, their detectability, as well as the reproducibility of selected compounds. Results showed that a combination of methanol as extraction and acetonitrile/water (75/25) as reconstitution solvent provided improved results at least regarding the total feature count. Additionally, it was found that a higher amount of methanol was most suitable for extraction of rat urine among the tested conditions. In comparison, human urine requires significantly less volume of extraction solvent. Overall, it is recommended to systematically optimize both, the extraction method, and the reconstitution solvent for the used biofluid and the individual analytical settings.

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.