Single chamber Mg/Ca analyses of Globigerinoides ruber for paleo-proxy calibration using femtosecond LA-ICP-MS.

Mg/Ca is an independent proxy in paleoceanography to reconstruct past seawater temperature. Femtosecond Laser Ablation Inductively Coupled Plasma Mass Spectrometry (fs-LA-ICP-MS) was employed to determine the Mg/Ca composition of tests (shells) of the planktic foraminifer species Globigerinoides ruber albus (white chromotype) and G. ruber ruber (red/pink chromotype) sampled alive from the temperate to subtropical eastern North Atlantic with the research sailing yacht Eugen Seibold. Mg/Ca data are compared to (i) the measured in-situ temperature of ambient seawater, (ii) average mixed layer temperature, and (iii) sea surface temperature (SST). The pooled mean chamber Mg/Ca from each plankton tow site exhibits a positive relationship with SST. Two chamber-specific calibrations are derived, which are consistent with previous calibration equations for comparable paleo-archives. The results confirm fs-LA-ICP-MS as reliable method for determining Mg/Ca in G. ruber, and both the penultimate and antepenultimate chambers of adult specimens may provide comprehensible Mg/Ca temperatures of the surface ocean.

Recent advances in the application of direct analysis in real time-mass spectrometry (DART-MS) in food analysis.

Direct analysis in real time-mass spectrometry (DART-MS) has evolved as an effective analytical technique for the rapid and accurate analysis of food samples. The current advancements of DART-MS in food analysis are described in this paper. We discussed the DART principles, which include devices, ionization mechanisms, and parameter settings. Numerous applications of DART-MS in the fields of food and food products analysis published during 2018-2023 were reviewed, including contamination detection, food authentication and traceability, and specific analyte analysis in the food matrix. Furthermore, the challenges and limitations of DART-MS, such as matrix effect, isobaric component analysis, cost considerations and accessibility, and compound selectivity and identification, were discussed as well.

Chemical composition analysis of Qingyan dropping pills using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry.

RATIONALE: This study developed a method for the rapid classification and identification of the chemical composition of Qingyan dropping pills (QDP) to provide the theoretical basis and data foundation for further in-depth research on the pharmacological substance basis of the formula and the selection of quality control indexes. METHODS: Ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) and data postprocessing technology were used to analyze the chemical composition of QDP. The fragmentation information on possible characteristic fragments and related neutral losses was summarized based on the literature and was compared with the MS data obtained from the assay, and thus a rapid classification and identification of chemical components in QDP could be achieved. RESULTS: A total of 73 compounds were identified, namely 24 flavonoids, 14 terpenoids, 30 organic acids and their esters, 3 alkaloids, and 2 phenylpropanoids. CONCLUSIONS: In this study, UHPLC-Q-TOF-MS and data postprocessing technology were used to realize the rapid classification and identification of the chemical constituents of QDP, which provided a comprehensive, efficient, and fast qualitative analysis method, a basis for further quality control and safe medication of QDP.

Integrated multicomponent analysis based on ultra-high-performance liquid chromatography coupled with quadrupole-Exactive Orbitrap mass spectrometry and network pharmacology to elucidate the effective constituents and potential mechanism of Zhibai Dihuang pill in treating childhood precocious puberty.

RATIONALE: Childhood precocious puberty (CPP) is a common pediatric endocrine disorder with significant associated risks. Zhibai Dihuang pill (ZBDHP), a classic recipe of the Qing dynasty with its efficacy of nourishing yin and clearing heat, can downregulate the expression of ESR1 in the uterus and ovaries, thereby inhibiting CPP. However, as of now, the main active ingredients and pharmacological mechanisms of ZBDHP remain unclear. METHODS: A comprehensive approach was proposed using ultra-high-performance liquid chromatography coupled with quadrupole-Exactive Orbitrap mass spectrometry (UHPLC-Q-Exactive Orbitrap-MS) and network pharmacology to explore the potentially active constituents of ZBDHP and reveal the underlying mechanisms against CPP. Molecular docking was used to verify the possible mechanisms. RESULTS: A total of 214 constituents derived were identified via UHPLC-Q-Exactive Orbitrap-MS, and 12 of them were definitely characterized using reference standards. Subsequently, compounds tetrahydropalmatine, alisol C, 25-anhydroalisol A 11-acetate, hispidone, cavidine, alisol E, melianone, neogitogenin, denudatin B, and 16ß-hydroperoxyalisol B with related targets PIK3CA, HSD11B1, CYP19A1, AR, PTGS2, CDK2, NR3C1, MMP2, MMP1, and MAPK1 were regarded as key components and targets for ZBDHP treating CPP using the compound-target-pathway network. Besides, the results revealed that the pathways conduced obviously to therapeutic efficacy, including pathways in cancer, neuroactive ligand-receptor interaction, and cyclic adenosine monophosphate（cAMP） signaling pathways. Molecular docking indicated that PIK3CA, HSD11B1, and CYP19A1 exhibited high affinities to corresponding compounds. Overall, the study determined the multicomponent, multitarget, and multipathway mechanisms of ZBDHP against CPP. CONCLUSIONS: This study provided a new method for exploring the chemical constituents and pharmacology mechanism of traditional Chinese medicine.

[Study on determination methods and analysis of micronutrients in take-away meals].

OBJECTIVE: To comprehensively analyze the trace nutrient contents in take-away meals, the simultaneous detection method of common vitamins in take-away meals were explored based on the samples' matrix, and the content of trace nutrients in take-away meals was analyzed combined with inductively coupled plasma-mass spectrometry(ICP-MS) detection of common elements. METHODS: Fifty-seven take-away meals were collected randomly and analyzed. Vitamins were determined by high performance liquid chromatography-ultraviolet detector tandem fluorescence detector after pretreatment of samples including enzymatic digestion, hydrolysis and extraction. The separation was performed on a C_(18) column(250 mm×4.6 mm, 5 µm) with ion-pair acid reagents as the mobile phase for water-soluble vitamins and methanol for fat-soluble vitamins. Vitamin B_1, vitamin B_2, nicotinic acid, nicotinamide and vitamin A were detected by ultraviolet detector(UVD), while vitamin B_6 and E by fluorescence detector(FLD). Elemental analysis of calcium, magnesium, sodium, potassium, zinc, selenium and copper in the take-away meals was carried out according to GB 5009.268-2016 by ICP-MS to comprehensively evaluate the contents of micronutrients. RESULTS: Through optimization of chromatography and sample pretreatment conditions, the sensitivity of the established detection method can meet the needs of micronutrient evaluation with the detection limits and quantification limits of vitamins in the range of 0.002-0.098 mg/100 g and 0.007-0.327 mg/100 g, respectively. Good precision was obtained(<10%). The spiked recovery rates were 80.5%-103.8%(n=6). The result showed that the contents of micronutrients in take-away meals were generally low. The detection rates of vitamins ranged from 21.1% to 98.2%. CONCLUSION: The proposed method is simple and sensitive, and the contents of vitamins and elements determined were low in the collected take-away meals.

Extracellular vesicle proteins as breast cancer biomarkers: Mass spectrometry-based analysis.

Extracellular vesicles (EVs) are membrane-surrounded vesicles released by various cell types into the extracellular microenvironment. Although EVs vary in size, biological function, and components, their importance in cancer progression and the potential use of EV molecular species to serve as novel cancer biomarkers have become increasingly evident. Cancer cells actively release EVs into surrounding tissues, which play vital roles in cancer progression and metastasis, including invasion and immune modulation. EVs released by cancer cells are usually chosen as a gateway in the search for biomarkers for cancer. In this review, we mainly focused on molecular profiling of EV protein constituents from breast cancer, emphasizing mass spectrometry (MS)-based proteomic approaches. To further investigate the potential use of EVs as a source of breast cancer biomarkers, we have discussed the use of these proteins as predictive marker candidates. Besides, we have also summarized the key characteristics of EVs as potential therapeutic targets in breast cancer and provided significant information on their implications in breast cancer development and progression. Information provided in this review may help understand the recent progress in understanding EV biology and their potential role as new noninvasive biomarkers as well as emerging therapeutic opportunities and associated challenges.

Thermostability-assisted limited proteolysis-coupled mass spectrometry for capturing drug target proteins and sites.

BACKGROUND: Identifying drug-binding targets and their corresponding sites is crucial for drug discovery and mechanism studies. Limited proteolysis-coupled mass spectrometry (LiP-MS) is a sophisticated method used for the detection of compound and protein interactions. However, in some cases, LiP-MS cannot identify the target proteins due to the small structure changes or the lack of enrichment of low-abundant protein. To overcome this drawback, we developed a thermostability-assisted limited proteolysis-coupled mass spectrometry (TALiP-MS) approach for efficient drug target discovery. RESULTS: We proved that the novel strategy, TALiP-MS, could efficiently identify target proteins of various ligands, including cyclosporin A (a calcineurin inhibitor), geldanamycin (an HSP90 inhibitor), and staurosporine (a kinase inhibitor), with accurately recognizing drug-binding domains. The TALiP protocol increased the number of target peptides detected in LiP-MS experiments by 2- to 8-fold. Meanwhile, the TALiP-MS approach can not only identify both ligand-binding stability and destabilization proteins but also shows high complementarity with the thermal proteome profiling (TPP) and machine learning-based limited proteolysis (LiP-Quant) methods. The developed TALiP-MS approach was applied to identify the target proteins of celastrol (CEL), a natural product known for its strong antioxidant and anti-cancer angiogenesis effect. Among them, four proteins, MTHFD1, UBA1, ACLY, and SND1 were further validated for their strong affinity to CEL by using cellular thermal shift assay. Additionally, the destabilized proteins induced by CEL such as TAGLN2 and CFL1 were also validated. SIGNIFICANCE: Collectively, these findings underscore the efficacy of the TALiP-MS method for identifying drug targets, elucidating binding sites, and even detecting drug-induced conformational changes in target proteins in complex proteomes.

Research of 2D-COS with metabolomics modifications through deep learning for traceability of wine.

To tackle the difficulty of extracting features from one-dimensional spectral signals using traditional spectral analysis, a metabolomics analysis method is proposed to locate two-dimensional correlated spectral feature bands and combine it with deep learning classification for wine origin traceability. Metabolomics analysis was performed on 180 wine samples from 6 different wine regions using UPLC-Q-TOF-MS. Indole, Sulfacetamide, and caffeine were selected as the main differential components. By analyzing the molecular structure of these components and referring to the main functional groups on the infrared spectrum, characteristic band regions with wavelengths in the range of 1000-1400 nm and 1500-1800 nm were selected. Draw two-dimensional correlation spectra (2D-COS) separately, generate synchronous correlation spectra and asynchronous correlation spectra, establish convolutional neural network (CNN) classification models, and achieve the purpose of wine origin traceability. The experimental results demonstrate that combining two segments of two-dimensional characteristic spectra determined by metabolomics screening with convolutional neural networks yields optimal classification results. This validates the effectiveness of using metabolomics screening to determine spectral feature regions in tracing wine origin. This approach effectively removes irrelevant variables while retaining crucial chemical information, enhancing spectral resolution. This integrated approach strengthens the classification model's understanding of samples, significantly increasing accuracy.

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.

Native ion mobility-mass spectrometry reveals the binding mechanisms of anti-amyloid therapeutic antibodies.

One of the most important attributes of anti-amyloid antibodies is their selective binding to oligomeric and amyloid aggregates. However, current methods of examining the binding specificities of anti-amyloid ß (Aß) antibodies have limited ability to differentiate between complexes that form between antibodies and monomeric or oligomeric Aß species during the dynamic Aß aggregation process. Here, we present a high-resolution native ion-mobility mass spectrometry (nIM-MS) method to investigate complexes formed between a variety of Aß oligomers and three Aß-specific IgGs, namely two antibodies with relatively high conformational specificity (aducanumab and A34) and one antibody with low conformational specificity (crenezumab). We found that crenezumab primarily binds Aß monomers, while aducanumab preferentially binds Aß monomers and dimers and A34 preferentially binds Aß dimers, trimers, and tetrameters. Through collision induced unfolding (CIU) analysis, our data indicate that antibody stability is increased upon Aß binding and, surprisingly, this stabilization involves the Fc region. Together, we conclude that nIM-MS and CIU enable the identification of Aß antibody binding stoichiometries and provide important details regarding antibody binding mechanisms.

Super-resolution proximity labeling with enhanced direct identification of biotinylation sites.

Promiscuous labeling enzymes, such as APEX2 or TurboID, are commonly used in in situ biotinylation studies of subcellular proteomes or protein-protein interactions. Although the conventional approach of enriching biotinylated proteins is widely implemented, in-depth identification of specific biotinylation sites remains challenging, and current approaches are technically demanding with low yields. A novel method to systematically identify specific biotinylation sites for LC-MS analysis followed by proximity labeling showed excellent performance compared with that of related approaches in terms of identification depth with high enrichment power. The systematic identification of biotinylation sites enabled a simpler and more efficient experimental design to identify subcellular localized proteins within membranous organelles. Applying this method to the processing body (PB), a non-membranous organelle, successfully allowed unbiased identification of PB core proteins, including novel candidates. We anticipate that our newly developed method will replace the conventional method for identifying biotinylated proteins labeled by promiscuous labeling enzymes.

Predicting the age of field Anopheles mosquitoes using mass spectrometry and deep learning.

Mosquito-borne diseases like malaria are rising globally, and improved mosquito vector surveillance is needed. Survival of Anopheles mosquitoes is key for epidemiological monitoring of malaria transmission and evaluation of vector control strategies targeting mosquito longevity, as the risk of pathogen transmission increases with mosquito age. However, the available tools to estimate field mosquito age are often approximate and time-consuming. Here, we show a rapid method that combines matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry with deep learning for mosquito age prediction. Using 2763 mass spectra from the head, legs, and thorax of 251 field-collected Anopheles arabiensis mosquitoes, we developed deep learning models that achieved a best mean absolute error of 1.74 days. We also demonstrate consistent performance at two ecological sites in Senegal, supported by age-related protein changes. Our approach is promising for malaria control and the field of vector biology, benefiting other disease vectors like Aedes mosquitoes.

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.

REMEMProt: a resource of membrane-enriched proteome profiles, their disease associations, and biomarker status.

The differential expression of plasma membrane proteins is integrally analyzed for their diagnosis, prognosis, and therapeutic applications in diverse clinical manifestations. Necessarily, distinct membrane protein enrichment methods and mass spectrometry platforms are employed for their global and relative quantitation. First of its kind to explore, we compiled membrane-associated proteomes in human and mouse systems into a database named, Resource of Experimental Membrane-Enriched Mass spectrometry-derived Proteome (REMEMProt). It currently hosts 14,626 proteins (9,507 proteins in Homo sapiens; 5,119 proteins in Mus musculus) with information on their membrane-protein enrichment methods, experimental/physiological context of detection in cells or tissues, transmembrane domain analysis, and their current attribution as biomarkers. Based on these annotations and the transmembrane domain analysis in proteins or their binary/complex protein-protein interactors, REMEMProt facilitates the assessment of the plasma membrane localization potential of proteins through batch query. A cross-study enrichment analysis platform is enabled in REMEMProt for comparative analysis of proteomes using novel/modified membrane enrichment methods and evaluation of methods for targeted enrichment of membrane proteins. REMEMProt data are made freely accessible to explore and download at https://rememprot.ciods.in/.

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.

Application of quantitative protein mass spectrometric data in the early predictive analysis of membrane-bound target engagement by monoclonal antibodies.

Model-informed drug discovery advocates the use of mathematical modeling and simulation for improved efficacy in drug discovery. In the case of monoclonal antibodies (mAbs) against cell membrane antigens, this requires quantitative insight into the target tissue concentration levels. Protein mass spectrometry data are often available but the values are expressed in relative, rather than in molar concentration units that are easier to incorporate into pharmacokinetic models. Here, we present an empirical correlation that converts the parts per million (ppm) concentrations in the PaxDb database to their molar equivalents that are more suitable for pharmacokinetic modeling. We evaluate the insight afforded to target tissue distribution by analyzing the likely tumor-targeting accuracy of mAbs recognizing either epidermal growth factor receptor or its homolog HER2. Surprisingly, the predicted tissue concentrations of both these targets exceed the Kd values of their respective therapeutic mAbs. Physiologically based pharmacokinetic (PBPK) modeling indicates that in these conditions only about 0.05% of the dosed mAb is likely to reach the solid tumor target cells. The rest of the dose is eliminated in healthy tissues via both nonspecific and target-mediated processes. The presented approach allows evaluation of the interplay between the target expression level in different tissues that determines the overall pharmacokinetic properties of the drug and the fraction that reaches the cells of interest. This methodology can help to evaluate the efficacy and safety properties of novel drugs, especially if the off-target cell degradation has cytotoxic outcomes, as in the case of antibody-drug conjugates.

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.

Comparison of Three Widely Employed Extraction Methods for Metabolomic Analysis of Trypanosoma brucei.

Trypanosoma brucei (Tb) is the causative agent of human African trypanosomiasis (HAT), also known as sleeping sickness, which can be fatal if left untreated. An understanding of the parasite's cellular metabolism is vital for the discovery of new antitrypanosomal drugs and for disease eradication. Metabolomics can be used to analyze numerous metabolic pathways described as essential to Tb. brucei but has some limitations linked to the metabolites' physicochemical properties and the extraction process. To develop an optimized method for extracting and analyzing Tb. brucei metabolites, we tested the three most commonly used extraction methods, analyzed the extracts by hydrophilic interaction liquid chromatography high-resolution mass spectrometry (HILIC LC-HRMS), and further evaluated the results using quantitative criteria including the number, intensity, reproducibility, and variability of features, as well as qualitative criteria such as the specific coverage of relevant metabolites. Here, we present the resulting protocols for untargeted metabolomic analysis of Tb. brucei using (HILIC LC-HRMS). © 2024 Wiley Periodicals LLC. Basic Protocol 1: Culture of Trypanosoma brucei brucei parasites Basic Protocol 2: Preparation of samples for metabolomic analysis of Trypanosoma brucei brucei Basic Protocol 3: LC-HRMS-based metabolomic data analysis of Trypanosoma brucei brucei.

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.