Parallel Reactions Research Articles

DIA proteomic and PRM validation through human granulose cells profiles screen suitable biomarkers for polycystic ovary syndrome patients

The aim of this study is to identify differentially expressed proteins (DEPs) in granulose cells (GCs) from women with or withoutpolycystic ovary syndrome (PCOS) via data independent acquisition (DIA) proteomic analysis.A total of 63 women were recruited for this study, 34 PCOS patients as experimental group (P), and 29 women without PCOS as Normal group (NP). DIA-based proteomic analysis was performed to identify DEPs in GCs between the P and NP samples. Certain typical DEPs were further validated by Parallel reaction monitoring (PRM), and correlation analysis was performed between these DEPs and the clinical characteristics.Cell vitality was measured by CCK-8 assay. DIA analysis revealed 174 significantly DEPs, of which 7 were upregulated and 167 downregulated. Bioinformatics analysis was performed to analysis the significantly DEPs. The PRM experiment confirmed TOP2A and SPHKAP were upregulated significantly in P by comparing to NP, while GM2A, MRPS16, APOA2 and FGF2 were downregulated significantly. Most notably, Correlation analysis revealed that TOP2A, SPHKAP, MRPS16 and FGF2were positively correlated with TG, AMH and Age, but negatively correlated with Menarche age, DBIL, FT3, Basal serum FSH and LH.Meanwhile, CCK-8 assay has shown that downregulation of FGF2 could weaken cell viability. Finally, a panel of DEPs were identified in the GCs of patients with PCOS, of which certain significant DEPs might play essential roles in the pathogenesis of PCOS, could be regarded as candidate biomarkers for PCOS.

Insoluble Proteomics Analysis of Acute Intracranial Large Vessel Occlusive Thrombus.

Acute large vessel occlusion (LVO) stroke is highly prevalent and severe. Despite thrombolytic therapy, many patients experience substantial complications. Understanding the origins, constituents, and pathological processes involved in thrombus formation in acute intracranial large artery occlusion is crucial. To identify the characteristics of insoluble proteins from different sources of cerebral thrombus. This study included 13 patients with cardiogenic embolic thrombus (CE) and 15 with large artery atherosclerosis thrombus (LAA). High-performance liquid chromatography and liquid chromatography-tandem mass spectrometry were used to analyze insoluble proteins in thrombi. Bioinformatics analyses explored differential proteins and associated functional pathways. Least Absolute Shrinkage and Selection Operator and Random Forest identified biomarkers for diagnosing thrombus sources, validated by parallel reaction monitoring. We constructed an insoluble protein atlas of cerebral thrombi, identifying 6975 insoluble proteins, including 143 extracellular matrix (ECM)-related proteins. The enrichment pathways considerably varied between thrombi from different sources. Inflammation-related pathways, such as "acute inflammatory response," along with ECM-related pathways such as "laminin interactions," were notably upregulated in LAA compared to CE. Additionally, two biomarkers (IDH2, HSPG2) exhibited strong diagnostic performance (AUC = 1) and robustness. In the insoluble Proteomics of thrombus, we highlighted the crucial roles of immune responses and ECM proteins in thrombus formation, providing new insights into its mechanisms and potential drug development. Additionally, we identified two biomarkers that offer new methods for determining thrombus sources in patients with LVO.

Artificial intelligence-enabled multipurpose smart detection in active-matrix electrowetting-on-dielectric digital microfluidics

An active-matrix electrowetting-on-dielectric (AM-EWOD) system integrates hundreds of thousands of active electrodes for sample droplet manipulation, which can enable simultaneous, automatic, and parallel on-chip biochemical reactions. A smart detection system is essential for ensuring a fully automatic workflow and online programming for the subsequent experimental steps. In this work, we demonstrated an artificial intelligence (AI)-enabled multipurpose smart detection method in an AM-EWOD system for different tasks. We employed the U-Net model to quantitatively evaluate the uniformity of the applied droplet-splitting methods. We used the YOLOv8 model to monitor the droplet-splitting process online. A 97.76% splitting success rate was observed with 18 different AM-EWOD chips. A 99.982% model precision rate and a 99.980% model recall rate were manually verified. We employed an improved YOLOv8 model to detect single-cell samples in nanolitre droplets. Compared with manual verification, the model achieved 99.260% and 99.193% precision and recall rates, respectively. In addition, single-cell droplet sorting and routing experiments were demonstrated. With an AI-based smart detection system, AM-EWOD has shown great potential for use as a ubiquitous platform for implementing true lab-on-a-chip applications.

Quantification of Histone H1 Subtypes Using Targeted Proteomics.

Histone H1 is involved in the regulation of chromatin structure. Human somatic cells express up to seven subtypes. The variability in the proportions of somatic H1s (H1 complement) is one piece of evidence supporting their functional specificity. Alterations in the protein levels of different H1 subtypes have been observed in cancer, suggesting their potential as biomarkers and that they might play a role in disease development. We have developed a mass spectrometry-based (MS) parallel reaction monitoring (PRM) assay suitable for the quantification of H1 subtypes. Our PRM method is based on the quantification of unique peptides for each subtype, providing high specificity. Evaluation of the PRM performance on three human cell lines, HeLa, K562, and T47D, showed high reproducibility and sensitivity. Quantification values agreed with the electrophoretic and Western blot data, indicating the accuracy of the method. We used PRM to quantify the H1 complement in peripheral blood samples of healthy individuals and chronic myeloid leukemia (CML) patients. In CML, the first line of therapy is a tyrosine kinase inhibitor, imatinib. Our preliminary data revealed differences in the H1 complement in CML patients between imatinib responders and non-responders. These results support further research to determine if the H1 content or subtype composition could help predict imatinib response.

Automated High-Throughput Biological Sex Identification from Archeological Human Dental Enamel Using Targeted Proteomics.

Biological sex is key information for archeological and forensic studies, which can be determined by proteomics. However, the lack of a standardized approach for fast and accurate sex identification currently limits the reach of proteomics applications. Here, we introduce a streamlined mass spectrometry (MS)-based workflow for the determination of biological sex using human dental enamel. Our approach builds on a minimally invasive sampling strategy by acid etching, a rapid online liquid chromatography (LC) gradient coupled to a high-resolution parallel reaction monitoring (PRM) assay allowing for a throughput of 200 samples per day (SPD) with high quantitative performance enabling confident identification of both males and females. Additionally, we developed a streamlined data analysis pipeline and integrated it into a Shiny interface for ease of use. The method was first developed and optimized using modern teeth and then validated in an independent set of deciduous teeth of known sex. Finally, the assay was successfully applied to archeological material, enabling the analysis of over 300 individuals. We demonstrate unprecedented performance and scalability, speeding up MS analysis by 10-fold compared to conventional proteomics-based sex identification methods. This work paves the way for large-scale archeological or forensic studies enabling the investigation of entire populations rather than focusing on individual high-profile specimens. Data are available via ProteomeXchange with the identifier PXD049326.

Pseudo Master Curve Analysis of an Infinite Number of Parallel First-Order Reactions: Improved Distributed Activation Energy Model.

The so-called Distributed Activation Energy Model (DAEM) has been used extensively, mainly to analyze pyrolysis reactions of solid reactants. The model expresses many parallel first-order reactions using the distributions of activation energy f(E) and frequency factor k 0(E). Miura and Maki presented a method to estimate both f(E) and k 0(E) in the DAEM in 1998. This model has been used successfully by many researchers. In this paper more general basic equations are derived for describing an infinite number of parallel first-order reactions by extending the basic equations for the finite number of parallel first-order reactions. Revisiting the Miura-Maki method based on the general basic equations, a graphical analysis method that may be called "Pseudo Master Curve Analysis" is presented. The method not only supplements the Miura-Maki method but gives the underlying concept of the Miura-Maki method clearly. It is also shown that the graphical method can be applicable to analyze single reactions and the experimental data obtained using isothermal reaction techniques. Next, a method that improves the estimation accuracy of k 0(E) is presented. Practical examples analyzing several experimental data are also given to show the usefulness and validity of the Miura-Maki method and the graphical method. Through the examination, it is proposed that the DAEM should be renamed, for example, as the Distributed Rate Constant Model (DRCM).

Inhibition of the long non-coding RNA MALAT1 downregulates MAP2K1 to suppress the progression of hypopharyngeal squamous cell carcinoma.

This study aimed to explore the role of lncRNA MALAT1 (Long non-coding RNAs metastasis-associated lung adenocarcinoma transcript), and its underlying mechanisms in Hypopharyngeal Squamous Cell Carcinoma (HSCC). Quantitative real-time PCR (qRT-PCR) was employed to measure lncRNA MALAT1 expression in HSCC and adjacent non-cancerous tissues, along with the expression of the downstream target mitogen-activated protein kinase kinase 1 (MAP2K1). The independent prognostic significance of lncRNA MALAT1 was assessed using Cox regression analysis. Potential downstream targets of MALAT1 were identified through PRM analysis and validated using the TCGA-HNSC database, Western blotting, and immunohistochemistry. CCK-8, flow cytometry, and Transwell assays were conducted to assess the effects of the lncRNA MALAT1/MAP2K1 axis on FaDu cells. Additionally, a nude mouse xenograft model was used to confirm the role of lncRNA MALAT1/MAP2K1 in tumor growth. LncRNA MALAT1 was significantly upregulated in HSCC tissues and closely associated with poor prognosis. Bioinformatics analysis, including parallel reaction monitoring (PRM) screening and TCGA-HNSC data, identified FERMT2, CSNK2A2, and MAP2K1 as potential downstream targets of MALAT1. Validation through qPCR, Western blotting, and immunohistochemistry confirmed MAP2K1 as a downstream target. In vitro and in vivo experiments demonstrated that inhibiting lncRNA MALAT1 suppressed cell proliferation, migration, and epithelial-to-mesenchymal transition (EMT) by downregulating MAP2K1 expression. Additionally, it induced apoptosis, affected the cell cycle, and inhibited tumor growth. Our study uniquely demonstrates that targeting MALAT1 significantly impedes HSCC progression by downregulating its novel downstream target, MAP2K1, offering new insights into potential therapeutic strategies.

A Computer Vision Approach toward Verifying CFD Models of Stirred Tank Reactors.

Mixing is one of the most important nonchemical considerations in the design of scalable processes. While noninvasive imaging approaches to deliver a quantifiable understanding of mixing dynamics are well-known, the use of imaging to verify computational fluid dynamics (CFD) models remains in its infancy. Herein, we use colorimetric reactions and our kinetic imaging software, Kineticolor, to explore (i) the correlation of imaging kinetics with pH probe measurements, (ii) feed point sensitivity for Villermaux-Dushman-type competing parallel reactions, and (iii) the use of experimental imaging kinetic data to qualitatively assess CFD models. We report further evidence that the influences of the stirring rate, baffle presence, and feed position on mixing in a tank reactor can be informatively captured with a camcorder and help experimentally verify CFD models. Overall, this work advances scarce little precedent in demonstrating the use of computer vision to verify CFD models of fluid flow in tank reactors.

Identification of daurisoline metabolites in rats via the UHPLC-Q-exactive orbitrap mass spectrometer

Daurisoline, a bisbenzylisoquinoline alkaloid extracted from the rhizomes of Menispermum dauricum, exhibits diverse biological activities, encompassing antiplatelet, anti-inflammatory, neuroprotective, and antitumor properties. However, previous investigations have not comprehensively elucidated the metabolic profile and pathways of daurisoline in vivo. Using Ultra-High-Performance Liquid Chromatography with Q-Exactive Orbitrap Mass Spectrometry technology, we comprehensively investigated the metabolites of daurisoline in Sprague-Dawley rats, following intragastric administration. Data collection and analysis were enhanced through Full Scan MS/dd-MS2, in conjunction with parallel reaction monitoring, extracted ion chromatography, and diagnostic fragment ions. Sixty-three metabolites were detected and characterized, including sixty-two novel metabolites and coclaurine. This investigation elucidated the cleavage patterns and tissue distribution characteristics of the metabolism of daurisoline. Furthermore, in vivo reactions, including dehydrogenation, hydroxylation, methylation, sulfation and glucuronidation, were thoroughly examined. Investigating the metabolites of daurisoline in rats has deepened our understanding of its metabolism in vivo, aiding in elucidating its metabolic and pharmacological actions. This provides a valuable foundation for further research into its therapeutic efficacy.

An integrated strategy for in-depth profiling of N-acylethanolamines in biological samples by UHPLC-HRMS

BackgroundN-acylethanolamines (NAEs) are a class of naturally occurring bioactive lipids that play crucial roles in various physiological processes, particularly exhibiting neuroprotective and anti-inflammatory properties. However, the comprehensive profiling of endogenous NAEs in complex biological matrices is challenging due to their low abundance, structural similarity and the limited availability of commercial standards. Here, we propose an integrated strategy for comprehensive profiling of NAEs that combines chemical derivatization and a three-dimensional (3D) prediction model based on quantitative structure-retention time relationship (QSRR) using liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS). ResultsAfter acetyl chloride (ACC) derivatization, the detection sensitivity of NAEs was significantly improved. We developed a QSRR prediction model to construct an in-house database for 141 NAEs, encompassing information on RT, MS1 (m/z), and MS/MS spectra. Propargylamine-labeled fatty acids were synthesized as RT calibrants across various analytical conditions to enhance the robustness of the RT prediction model. NAEs in biological samples were then in-depth profiled using parallel reaction monitoring (PRM) acquisition. This integrated strategy identified and annotated a total of 50 NAEs across serum, hippocampus and cortex tissues from a 5xFAD mouse model of Alzheimer's disease (AD). Notably, the levels of polyunsaturated NAEs, particularly NAE 20:5 and NAE 22:6, were significantly decreased in 5xFAD mice compared to WT mice, as confirmed by accurate quantitation using ACC-d0/d3 derivatization. SignificanceOur integrated strategy exhibits great potential for the in-depth profiling of NAEs in complex biological samples, facilitating the elucidation of NAE functions in diverse physiological and pathological processes.

Proteomic Analysis Reveals Differential Protein Expression in Placental Tissues of Early-Onset Preeclampsia Patients.

Preeclampsia, a significant cause of maternal and perinatal morbidity and mortality, remains poorly understood, in terms of its pathogenesis. This study aims to uncover novel and effective biomarkers for preeclampsia by conducting a comparative analysis of differential proteins in placentas from early onset preeclampsia (EOPE) and normal pregnancies. Utilizing tandem mass tag (TMT)-based quantitative proteomics, we identified differentially expressed proteins in placental tissues from 15 EOPE patients and 15 normal pregnant women. These proteins were subsequently validated by using parallel reaction monitoring (PRM). Our analysis revealed a total of 59 differentially expressed proteins, with 25 up-regulated and 34 down-regulated proteins in EOPE placental tissues compared to those from normal pregnancies. Validation through PRM confirmed the differential expression of 6 proteins. Our findings suggest these 6 proteins could play crucial roles in the pathogenesis of EOPE, highlighting the potential involvement of the estrogen signaling pathway and dilated cardiomyopathy (DCM) pathway in the development of preeclampsia. The data were deposited with the ProteomeXchange Consortium via the iProX partner repository with the identifier PXD055025.

Quantitation of Host Cell Proteins by Capillary LC/IMS/MS/MS in Combination with Rapid Digestion on Immobilized Trypsin Column Under Native Conditions.

Host cell protein (HCP) impurities are considered a critical quality attribute of biopharmaceuticals because of their potential to compromise safety and efficacy, and LC/MS-based analytical methods have been developed to identify and quantify individual proteins instead of employing enzyme-linked immunosorbent assay to assess total HCP levels. Native digestion enables highly sensitive detection of HCPs but requires overnight incubation to generate peptides, limiting the throughput of sample preparation. In this study, we developed an approach employing native digestion on a trypsin-immobilized column to improve the sensitivity and throughput. We examined suitable databases for the identification of HCPs derived from Chinese hamster ovary (CHO) cells and selected RefSeq's Chinese Hamster as the optimal database. Then, we investigated methods to identify HCPs with greater efficiency than that of denatured in-solution digestion. Native in-column digestion not only reduced the digestion time from overnight to 10 min but also increased the number of quantified HCPs from 154 to 226. In addition to this rapid digestion methodology, we developed high-throughput LC/MS/MS with a monolithic silica column and parallel reaction monitoring-parallel accumulation-serial fragmentation. The optimized system was validated with synthetic peptides derived from high-risk HCPs, confirming excellent linearity, precision, accuracy, and low limit of detection (LOD) and limit of quantification (LOQ) (1-3 ppm). The optimized digestion and analysis method enabled high-throughput quantification of HCPs, and is expected to be useful for quality control and characterization of HCPs in antibody drugs.

A Systematic Methodology for the Identification of the Chemical Composition of the Mongolian Drug Erdun-Uril Compound Utilizing UHPLC-Q-Exactive Orbitrap Mass Spectrometry.

The traditional Mongolian medicine Erdun-Uril is a conventional combination of 29 herbs commonly used for the treatment of cerebrovascular ailments. It has the effects of reducing inflammation, counteracting oxidative stress, and averting strokes caused by persistent cerebral hypoperfusion. Prior research on Erdun-Uril has predominantly concentrated on its pharmacodynamics and mechanism of action; however, there has been a lack of systematic and comprehensive investigation into its chemical constituents. Therefore, it is crucial to establish an efficient and rapid method for evaluating the chemical constituents of Erdun-Uril. In this study, Erdun-Uril was investigated using UHPLC-Q-Exactive Orbitrap MS combined with parallel reaction monitoring for the first time. Eventually, a total of 237 compounds, including 76 flavonoids, 68 phenolic compounds, 19 alkaloids, 7 amino acids, etc., were identified based on the chromatographic retention time, bibliography data, MS/MS2 information, neutral loss fragments (NLFs), and diagnostic fragment ions (DFIs). And of these, 225 were reported for the first time in this study. This new discovery of these complex components would provide a reliable theoretical basis for the development of pharmacodynamics and quality standards of the Mongolian medicine Erdun-Uril.

Quantitative proteomics analysis reveals the protective role of S14G-humanin in septic acute kidney injury using 4D-label-free and PRM Approaches

Mitochondrial dysfunction contributes to septic acute kidney injury (S-AKI), making mitochondrial protection a potential therapeutic strategy. This study investigates the effects of S14G-humanin (HNG) in S-AKI, utilizing 4D-label-free and parallel reaction monitoring (PRM) techniques for proteomic analysis. An S-AKI model was created in male C57BL/6 mice using lipopolysaccharide (LPS) injection, followed by HNG administration. After 24 h, kidney tissues were analyzed for histology, biochemistry, mitochondrial function, and proteomics. HNG treatment improved renal function, reduced tubular injury, and decreased pro-inflammatory cytokines and oxidative stress markers. Proteomic analysis identified 5900 proteins, with 5111 quantifiable. HNG altered the expression of 132 proteins, with 18 selected for PRM validation. Ten of these proteins were linked to key pathways, including fatty acid degradation and PPAR signaling. This study is the first to show HNG's protective effects in S-AKI, providing insights into its mechanisms through advanced proteomic techniques.

Parallel reaction monitoring targeted mass spectrometry as a fast and sensitive alternative to antibody-based protein detection

The reliable, accurate and quantitative targeted detection of proteins is a key technology in molecular and cell biology and molecular diagnostics. The current golden standard for targeted protein detection in complex mixtures such as complete cell lysates or body fluids is immunoblotting, a technology that was developed in the late 1970s and has not undergone major changes since. Although widespread, this methodology suffers from several disadvantages, such as the inability to detect low-abundant proteins or specific posttranslational modifications, the requirement for highly specific antibodies, the lack of quantitative power and the often-tedious practical procedures. Mass spectrometry (MS) based targeted protein detection is an alternative technology that could circumvent these caveats. Here, we compare immunoblotting with targeted protein mass spectrometry using a parallel reaction monitoring (PRM) regime on the Orbitrap mass spectrometer. We show that PRM based MS has superior sensitivity and quantitative accuracy over immunoblotting. The limit of detection for proteolytic peptides of a purified target protein was found to be in the mid- to low-attomole range and approximately one order of magnitude higher when embedded in a complex biological matrix. The incorporation of synthetic heavy isotope labeled (AQUA) peptides as internal calibrants into the PRM workflow allows for even higher accuracy for both the relative and absolute quantitation of tryptic target peptides. In conclusion, PRM is a versatile and sensitive technology, which can overcome the shortcomings of immunoblotting. We argue that PRM based MS could become the method of choice for the targeted detection of proteins in complex cellular matrices or body fluids and may eventually replace standard methods such as Western blotting and ELISA in biomedical research and in the clinic.

Quantitation of trace polyfunctional thiols in wine by liquid chromatography quadrupole Orbitrap high-resolution mass spectrometry in parallel reaction monitoring

Polyfunctional thiols are key contributors to wine aroma due to their extremely low odor thresholds, and their quantitative analysis remains challenging as a result of their ultratrace concentrations and high reactivity. This work presents the first method based on ultra-high-performance liquid chromatography (UHPLC) coupled to quadrupole Orbitrap high-resolution mass spectrometry (HRMS) in parallel reaction monitoring (PRM) mode for quantifying thiols at nanograms per liter (ng/L) levels in wine. Thiols in wine were derivatized using 4,4′-dithiodipyridine and isolated by liquid-liquid extraction. This protocol allowed rapid sample preparation with minimum labor input and low consumable expenses. Instrumental analysis was conducted using UHPLC–quadrupole Orbitrap HRMS in PRM mode. Twenty thiol analytes, including literature-known, recently identified, and novel thiols were selected and validated by the optimized method in three wine matrices. The overall analytical performances demonstrated by this method were equivalent, and in most cases, greater than many previously developed GC–MS or LC–MS methods. The validated method was applied to analyze a selection of wines in which 12 thiols were quantified.

Synthesis of dihydrocarvone over dendritic ZSM-5 Zeolite: A comprehensive study of experimental, kinetics, and computational insights

This study explores the isomerization of limonene-1,2-epoxide (LE) from kinetic and mechanistic viewpoints, using a dendritic ZSM-5 zeolite (d-ZSM-5) as a highly selective catalyst for the formation of dihydrocarvone (DHC) in the form of diastereoisomers (cis + trans). Ethyl acetate, a green solvent, was used at mild reaction temperatures (50–––70 °C). DHC, which can also be extracted from caraway oil, is widely used as an intermediate for epoxylactone production and as a constituent in flavors and perfumes. Kinetic modeling of LE isomerization was performed using a reaction network with eight parallel reactions and the corresponding rate equations, derived from the assumption of the rate-limiting surface reactions. The large standard errors in the statistical results of some kinetic parameters of the initial data fitting suggested that three of those reactions can be neglected to describe the kinetic model more accurately. This refinement resulted in standard errors in the kinetic parameters lower than ca. 11 %, confirming the statistical reliability of the modified kinetic model. Activation energies of 41.1 and 162 kJ/mol were estimated for the formation of cis-DHC and trans-DHC, respectively. Density Functional Theory (DFT) calculations revealed the preferred pathway for both cis and trans-LE conversion to DHC and carveol. The rate-determining step, carbocation formation (ΔEact = 234 kJ/mol), precedes near-instantaneous dihydrocarvone formation under the studied conditions.

Calibration-Free Analysis with Chronoamperometry at Microelectrodes.

Analytical methods are crucial for monitoring and assessing the concentration of important chemicals, and there is now a growing demand for methodologies that allow miniaturization, require lower sample volumes, and enable real-time analysis in the field. Most electroanalytical techniques depend on calibrations or standards, and this has several limitations, ranging from matrix interference, to stability problems, time required, cost and waste. Therefore, strategies that do not require standards or calibration curves greatly interest the analytical chemistry community. Here, we propose a new quantification method that does not rely on calibration and is only based on a single chronoamperometric curve recorded with a microelectrode. We show that satisfactory analytical information is obtained with just one chronoamperometric experiment that only takes a few seconds. We propose different data treatments to determine the unknown concentration, we consider the experimental conditions and instrument parameters, we report how parallel reactions affect the results, and we recommend procedures to implement the method in autonomous sensors. We also show that the concentration of several species can be derived if their E° values are sufficiently far apart or the sum of all concentrations if the E° values are too close. The proposed method was validated with a model redox system then further evaluated by determining ascorbic acid concentrations in standard solutions and food supplements, and paracetamol in a pain killer. The results for ascorbic acid were compared with those obtained by coulometry, and a good agreement was found, with a maximum deviation ca. 10.8%. The approach was also successfully applied to ascorbic acid quantification in solutions with different viscosity using ethylene glycol as a thickener.

Deciphering the transfer mechanisms for CO2 absorption into binary blended solutions

A thorough understanding of the mechanisms involved in CO2 chemical absorption is crucial for the development of efficient CO2 capture technologies. Due to the insufficient insight into the interaction mechanism of different components in blended solutions, CO2 absorption reactions were often categorized as unidirectional transfer between absorption products. In this study, the CO2 absorption performance of binary blended solutions, including piperazine (PZ)/n-methyldiethanolamine (MDEA), ethanolamine (MEA)/MDEA, ammonia (NH3)/MDEA, PZ/potassium carbonate (K2CO3), and NH3/K2CO3, was investigated using a combination of experimental and computational methods. The CO2 absorption mechanisms of “competitive reaction”, “transfer reaction” and “parallel reaction” in the binary blended solution system were proposed. Kinetic experiments revealed that different blended solutions had varying impacts on the process of CO2 absorption. Among them, PZ/MDEA and MEA/MDEA solutions reduced the absorption rates by an average of 8% and 25%, respectively, compared to PZ or MEA component solutions. NH3/MDEA and PZ/K2CO3 solutions had absorption rates similar to those of single NH3/PZ component solutions. NH3/K2CO3 solutions, on the other hand, exhibited an average increase of 17% in absorption rates compared to NH3 solutions. Quantum mechanical (QM) methods were employed to evaluate of the absorption products and key processes in terms of kinetics and thermodynamics. Quantitative 13C NMR analyses were conducted to further investigate the interactions between components and the pathways of mass transport in blended solutions, which demonstrated proton transfer and CO2/-COO transfer between adsorption products. This study highlights an accurate description of the transfer mechanisms of various blended systems for the enhanced CO2 capture.

Quantification of relevant metabolites in apoptotic bodies from HK-2 cells by targeted metabolomics based on liquid chromatography-tandem mass spectrometry

BackgroundApoptotic bodies play an important role in the cellular communication as a consequence of the great variety of biomolecules they harbor. There is evidence that 1st generation apoptotic bodies from HK-2 cells induced by cisplatin or UV light trigger apoptosis in naïve HK-2 cells whereas 2nd generation apoptotic bodies activate cell proliferation showing an opposite effect. Thus, the development of new analytical strategies to quantify the changes in the involved metabolites is imperative to shed light on the biological mechanisms which trigger apoptosis and cell proliferation. ResultsA LC-(Q-Orbitrap)MS method has been developed to quantify the metabolites unequivocally identified in the apoptotic body fluid from HK-2 cells in our previous works based on untargeted metabolomics. Thus, two different columns and gradients were tested and the HILIC column was selected taking into account the retention times and chromatographic separation. Also, different normal collision energies were tested for each metabolite and the parallel reaction monitoring was chosen to carry out the quantitative analysis. Once the method was optimized, it was evaluated in terms of linearity, limits of detection and quantification, matrix effects, accuracy, and precision, for each metabolite. Limits of detection ranged from 0.02 to 1.4 ng mL−1. A total of 9 relevant metabolites proposed as potential biomarkers to reveal metabolic differences among apoptotic bodies from HK-2 cells were quantified and some insights about the biological relevance were discussed. SignificanceThe first targeted metabolomics methodology enabling the quantification of relevant metabolites in apoptotic bodies from HK-2 cells was developed using LC-(Q-Orbitrap)MS. Pyridoxine, kynurenine, and creatine concentrations were determined in apoptotic bodies from HK-2 cells treated with cisplatin and UV light. Phenylacetylglycine, hippuric acid, butyrylcarnitine, acetylcarnitine, carnitine, and phenylalanine were determined in 1st and 2nd generation apoptotic bodies from HK-2 cells treated with cisplatin. Concentrations determined were useful to establish their biological role in the metabolism.