Mass Defect Research Articles

Nontargeted screening of aldehydes and ketones by chemical isotope labeling combined with ultra-high performance liquid chromatography-high resolution mass spectrometry followed by hybrid filtering of features

Aldehydes and ketones are important carbonyl compounds that are widely present in foodstuffs, biological organisms and human living environment. However, it is still challenging to comprehensively detect and capture them using liquid chromatography – mass spectrometry. In this work, a chemical isotope labeling (CIL) coupled with ultra-high performance liquid chromatography - high resolution mass spectrometry (UHPLC–HRMS) strategy was developed for the capture and detection of this class of compounds. 2,4-Dinitrophenylhydrazine (DNPH) and isotope-labeled DNPH (DNPH-d3) were utilized to selectively label the target analytes. To address the difficulties in processing UHPLC–HRMS data, a post-acquisition data processing method called MSFilter was proposed to facilitate the screening and identification aldehydes and ketones in complex matrices. The MSFilter consists of four independent filters, namely statistical characteristic-based filtering, mass defect filtering, CIL paired peaks filtering, and diagnostic fragmentation ion filtering. These filters can be used individually or in combination to eliminate unrelated interfering MS features and efficiently detect DNPH-labeled aldehydes and ketones. The results of a mixture containing 48 model compounds showed that although all individual filtering methods could significantly reduce more than 95% of the raw MS features with acceptable recall rates above 85%, but they had relatively high false positive ratios of over 90%. In comparison, the hybrid filtering method combining four filters is able to eliminate massive interfering features (> 99.5%) with a high recall rate of 81.25% and a much lower false positive ratio of 15.22%. By implementing the hybrid filtering method in MSFilter, a total of 154 features were identified as potential signals of CCs from the original 45,961 features of real tobacco samples, of which 70 were annotated. We believe that the proposed strategy is promising to analyze the potential CCs in complex samples by UHPLC–HRMS.

Clinical Outcomes of Isobar TTL System with Isthmic Bone Grafting and Pedicle Screw-Vertebral Plate Hook with Direct Repair of Defect for Lumbar Spondylolysis: A Matched-Pair Case Control Study.

Although direct isthmic repair, such as PSVPH, did not affect the mobility of the fixed segment and adjacent segment, it has a relatively low rate of isthmic fusion compared with conventional fusion. The Isobar TTL dynamic internal fixation system has been widely used in clinical practice and has achieved satisfactory clinical results. However, the use of the Isobar TTL system in combination with direct isthmic repair for lumbar spondylolysis has rarely been reported. The aim of this study was to compare the clinical and radiologic outcomes between patients who underwent Isobar TTL system and PSVPH with direct repair of defect for lumbar spondylolysis. Stepwise propensity score matching (PSM) for age and sex were performed to keep comparable clinical data between groups in this retrospective and matched-pair case control study. A total of 50 patients diagnosed with lumbar spondylolysis underwent surgical implantation of the Isobar TTL group (n = 25) or PSVPH group (n = 25) from June 2009 to June 2016. Clinical outcomes were assessed using the Oswestry disability index (ODI), and visual analog score (VAS). Radiographic evaluations included range of motion (ROM) and the disc heights of stabilized segment and adjacent segment, adjacent segment degeneration (ASD) and bony fusion. Three-dimensional reconstruction of lumbar CT scan was obtained to evaluate bone fusion of the isthmic at final follow-up. The independent Student's t test and chi-square test were applied to compare the differences between groups. A total of 25 patients from TTL group were matched to 25 patients in PSVPH group for age, sex, body mass index (BMI), defect side, spondylolisthesis meyerding, and follow-up duration. The intervertebral space height (IH) of stabilized segment at postoperative 1 week and final follow-up in the TTL group was higher than those in the PSVPH group, respectively (P = 0.030; P = 0.013). The ROM of stabilized segment at final follow-up in the TTL group was significantly lower than that in the PSVPH group (P < 0.001). The bony fusion rate at the final follow-up was 88.0% (22/25 cages) in the TTL group and 80.0% (20/25 cages) in the PSVPH group. The ODI score at final follow-up in the TTL group was significantly lower than that in the PSVPH group (P = 0.007). Overall, our data suggest that the Isobar TTL system outcomes are comparable to those in the PSVPH, with a similar high bony fusion rate as PSVPH, especially its wider indications as a new surgery.

Failure mode of parallel-fractured rock-like sample with different inclinations

Parallel fractures, a kind of common geological defect in natural rock mass, show a variety of failure mechanism and increases the difficulty in the timely warning of geological disasters such as landslide. Therefore, studying the mechanical properties and failure mechanism of parallel-fractured rock mass occupies a vital position in the stability analysis and warning technology of disaster precursor. In response to this, the laboratorial efforts on micro fracture mode and macro strength prediction of parallel-fractured rock-like samples with different inclinations were made in this paper. Firstly, the parallel-fractured samples were prepared by changing the fracture parameters, and the uniaxial compression test was then carried out. According to the mechanical parameter variations of samples during axial loading, the multiple indexes affecting the uniaxial compressive strength of parallel-fractured samples was clarified, and the specific influence of fracture inclination was quantified by mathematical method. Finally, the progressive failure mechanism of samples was analyzed through strain field evolution in virtue of digital image correlation (DIC) technique, and the main failure modes of parallel-fractured samples were summarized. Meanwhile, the acoustic emission (AE) signals were collected and processed to further reveal the failure characteristics of parallel-fractured samples with different inclinations in a microscopical perspective.

Characterization of Base Oil and Additive Oxidation Products from Formulated Lubricant by Ultra-High Resolution Mass Spectrometry

Automotive formulated lubricants are high value products composed of 80% base oil and 20% various additives. During their life service, lubricants are exposed to several factors that will cause degradation over time, such as high temperature, shear, and oxidation. Base oil is a complex combination of hydrocarbons that are relatively sensitive to oxidation. During the initiation phase of oxidation, free radicals are formed, leading to the production of hydroperoxide ROOH and an alkyl radical R•. These compounds will react with the base oil molecules to form aldehydes, ketones, and carboxylic acids in the termination phase. Owing to the molecular complexity of these mixtures, Fourier transform mass spectrometry seems to be the most appropriate tool to cover their wide range of compounds due to its ultra-high resolving power and mass accuracy. In this study, a native formulated lubricant and its different oxidized states at 140 °C under air flow (3, 5, 7, 8, and 9 days of oxidation) were analyzed by FTICR MS. The combination of atmospheric pressure chemical ionization (APCI) was used to achieve a non-selective ionization of molecules, including base oils, while Electrospray ionization (ESI) was used to selectively ionize acidic molecules. Apparent Kendrick mass defect (aKMD) plots were used to separate homologous series of molecules on different horizontal lines on the basis of the CH2 repetition unit. Aging of lubricants was mainly characterized by a rapid consumption of certain additive families, such as molybdenum dithiocarbamates (MoDTCs) and zinc dithiophosphate (ZnDTPs), but also by the emergence of many oxidation products. Thus, the presence of aldehydes, ketones, and acids was characterized in the early stage of aging while larger products from polymerization were observed in a more advanced stage of aging. Interaction products between peroxy radicals and hindered phenols/alkyl diphenylamines (ADPAs) antioxidations were elucidated toward the high m/z. The formation of such products can be explained by trapping mechanisms of these additives at high temperature (&gt;120 °C). Other types of interaction products were observed with the formation of antioxidant complexes. Additive degradation products were also characterized. For instance, polyisobutenyl succinimide dispersant oxidation products were clearly evidenced on the aKMD plots due to the gaps of 56 Da between each point. Overall, this study demonstrated the efficiency of the aKMD approach, and the use of ESI/APCI to characterize base oil and additive oxidation products.

Rapid Chemical Screening of Microplastics and Nanoplastics by Thermal Desorption and Pyrolysis Mass Spectrometry with Unsupervised Fuzzy Clustering.

The transport and chemical identification of microplastics and nanoplastics (MNPs) are critical to the concerns over plastic accumulation in the environment. Chemically and physically transient MNP species present unique challenges for isolation and analysis due to many factors such as their size, color, surface properties, morphology, and potential for chemical change. These factors contribute to the eventual environmental and toxicological impact of MNPs. As analytical methods and instrumentation continue to be developed for this application, analytical test materials will play an important role. Here, a direct mass spectrometry screening method was developed to rapidly characterize manufactured and weathered MNPs, complementing lengthy pyrolysis-gas chromatography-mass spectrometry analysis. The chromatography-free measurements took advantage of Kendrick mass defect analysis, in-source collision-induced dissociation, and advancements in machine learning approaches for the data analysis of complex mass spectra. In this study, we applied Gaussian mixture models and fuzzy c-means clustering for the unsupervised analysis of MNP sample spectra, incorporating clustering stability and information criterion measurements to determine latent dimensionality. These models provided insight into the composition of mixed and weathered MNP samples. The multiparametric data acquisition and machine learning approach presented improved confidence in polymer identification and differentiation.

Integrated strategy facilitates rapid in-depth chemome characterization of traditional Chinese medicine prescriptions: Shengbai oral liquid as a case.

Chemome characterization is the prerequisite for either therapeutic mechanism clarification or quality control of traditional Chinese medicine prescriptions (TCMPs). Liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) currently serves as the most popular analytical tool; however, chemome characterization is still challenged by MS/MS spectral acquisition and post-acquisition data processing. Here, an integrated strategy was proposed for in-depth chemome clarification of Shengbai oral liquid (SBOL). Gas phase ion fractionation with staggered mass ranges was demonstrated to be the superior acquisition method regarding MS2 spectrum coverage in this study, and narrower mass range further advanced coverage. To facilitate information extraction, all ingredient materials were measured in parallel to form an in-house library, where each MS1 -MS2 item generated a square mass-to-charge ratio (m/z) frame to capture the tagged identity and each chemical family produced a pentagon frame for mass defect features to accomplish chemical analogs-targeted quasi-molecular ion extraction. Square m/z frame imprinting captured 355 identities, while mass defect frames extracted 275 compounds. Attributing to comprehensive MS2 spectrum acquisition and efficient data processing, 355 components were captured and tentatively identified, resulting in a clarified chemical composition for SBOL. Therefore, the proposed strategy should be meaningful for the chemome characterization of TCMPs.

New Insights into the Role of Natural Organic Matter in Fe-Cr Coprecipitation: Importance of Molecular Selectivity.

Coprecipitation of Fe/Cr hydroxides with natural organic matter (NOM) is an important pathway for Cr immobilization. However, the role of NOM in coprecipitation is still controversial due to its molecular heterogeneity and diversity. This study focused on the molecular selectivity of NOM toward Fe/Cr coprecipitates to uncover the fate of Cr via Fourier transform-ion cyclotron resonance-mass spectrometry (FT-ICR-MS). The results showed that the significant effects of Suwannee River NOM (SRNOM) on Cr immobilization and stability of the Fe/Cr coprecipitates did not merely depend on the adsorption of SRNOM on Fe/Cr hydroxides. FT-ICR-MS spectra suggested that two pathways of molecular selectivity of SRNOM in the coprecipitation affected Cr immobilization. Polycyclic aromatics and polyphenolic compounds in SRNOM preferentially adsorbed on the Fe/Cr hydroxide nanoparticles, which provided extra binding sites and promoted the aggregation. Notably, some specific compounds (i.e., polyphenolic compounds and highly unsaturated phenolic compounds), less unsaturated and more oxygenated than those adsorbed on Fe/Cr hydroxide nanoparticles, were preferentially incorporated into the insoluble Cr-organic complexes in the coprecipitates. Kendrick mass defect analysis revealed that the insoluble Cr-organic complexes contained fewer carbonylated homologous compounds. More importantly, the spatial distribution of insoluble Cr-organic complexes was strongly related to Cr immobilization and stability of the Fe/Cr-NOM coprecipitates. The molecular information of the Fe/Cr-NOM coprecipitates would be beneficial for a better understanding of the transport and fate of Cr and exploration of the related remediation strategy.

Rapid and accurate identification of adulterated ingredients in lotus root powder based on liquid chromatography-high resolution mass spectrometry and MS-IDF

Although lotus root powder has high nutritional value and good therapeutic effects, there is still few reports on quality analysis of lotus root powder. In this study, we have established a novel method to identify the source and level of adulteration in lotus root powder, based on self-developed derivatization reagents and narrow range mass loss filtration technology. By using this approach, 80 species of oligosaccharides have been identified in lotus root powder, and 18 of them are characteristic and common oligosaccharides for lotus root powder from different places, which might be helpful to distinguish between oligosaccharides and their common adulterants. More importantly, in combination with multivariate statistical methods, the composition proportion of adulterants can also be effectively determined (from 5% to 95%). Furthermore, it is worthy to be mentioned that it is a pioneer report of using narrow range quality loss filtering technology towards successful detection and identification of food ingredients, which achieves rapid detection of adulterated components and their proportions in lotus root powder. In short, the approach of using mass defect filter is effective in sugar spectra analysis, which might be promising for simple, sensitive, and accurate food quality control.

Oleanolic acid and moderate drinking increase the pancreatic GLP-1R expression of the β-cell mass deficiency induced hyperglycemia.

Oleanolic acid (OA) and moderate drinking have been reported to attenuate diabetes. However, the underlying mechanism of OA and moderate drinking alone or in combination on the islet β-cell deficiency induced diabetes is not fully elucidated. Male Sprague Dawley (SD) rats were intraperitoneally injected with 55 mg/kg streptozotocin (STZ) to induce β-cell deficiency. OA, 5% ethanol (EtOH), or a mixture of OA in 5% ethanol (OA+EtOH) were applied to three treatment groups of hyperglycemia rats for 6 weeks. STZ caused the increase of fast blood glucose (FBG) level.OA and EtOH treatment alone or in combination decreased the STZ increased FBG level during the 6 weeks of treatment. In addition, OA treatment also significantly increased the β-cell to total islet cell ratio. Both EtOH and OA+EtOH treatments promoted the increase of total islet cell number and α-cell to β-cell ratio when compared to OA group. STZ induced hyperglycemia dramatically reduced the glucagon-like peptide-1 receptor (GLP-1R) positive cells in islets, all the three treatments significantly increased the pancreatic GLP-1R positive cell number. In the meantime, STZ induced hyperglycemia suppressed the insulin mRNA expression and boosted the glucagon mRNA expression. EtOH and OA+EtOH treatments increased the insulin mRNA expression, but none of the 3 treatments altered the elevated glucagon level. GLP-1R positive cell ratio in islets is crucial for the blood glucose level of diabetes. OA and 5% ethanol alone or in combination suppresses the blood glucose level of β-cell deficiency induced diabetes by increasing islet GLP-1R expression.

Clinical-functional and nutritional-metabolic features of the comorbid phenotype of vibration disease in combination with arterial hypertension

Introduction. Currently, the occupational etiological factors of vibration disease are well studied, but the management of this group of patients against the background of comorbid pathology, the impact on the quality of life of patients and the long-term prognosis of the disease remains an urgent problem.Aim. Study of nutritional and metabolic status in patients with vibration disease in combination with arterial hypertension.Materials and methods. A survey of 336 patients with vibration disease in combination with arterial hypertension was conducted in the conditions of the regional center of occupational pathology on the basis of a specialized department of occupational pathology. A comprehensive assessment of the clinical, nutritional and metabolic status of patients with vibration disease in combination with hypertension was carried out, including the study of clinical parameters, the daily profile of blood pressure, protein, lipid and carbohydrate metabolism, the component composition of the body of patients and the assessment of the profile of adipokines and cytokines.Results and discussion. Insufficient reduction of pressure at night (non-dippers) was revealed, an increase in fat mass and extracellular fluid was determined against the background of lean mass deficiency and a decrease in phase angle, proatherogenic dyslipidemia, protein deficiency, impaired carbohydrate metabolism, high levels of adipokine and cytokine activity.Conclusion. As a result of the study, additional markers for the diagnosis of nutritional disorders in the combined course of vibration disease and arterial.Conclusions. As an early diagnosis of nutritional and metabolic disorders in vibration disease in combination with arterial hypertension, the most informative integral indicators characterizing nutritional and metabolic disorders in this phenotype were identified – the waist circumference/hip circumference index and active cell mass.

Cracked and shucked: GC-APCI-IMS-HRMS facilitates identification of unknown halogenated organic chemicals in French marine bivalves

High resolution mass spectrometry (HRMS)-based non-target analysis coupled with ion mobility spectrometry (IMS) is gaining momentum due to its ability to provide complementary information which can be useful in the identification of unknown organic chemicals in support of efforts in unraveling the complexity of the chemical exposome. The chemical exposome in the marine environment, though not as well studied as its freshwater counterparts, is not foreign to chemical diversity specially when it comes to potentially bioaccumulative and bioactive polyhalogenated organic contaminants and natural products. In this work we present in detail how we utilized IMS-HRMS coupled with gas chromatographic separation and atmospheric pressure chemical ionization (APCI) to annotate polyhalogenated organic chemicals in French bivalves collected from 25 sites along the French coasts. We describe how we used open cheminformatic tools to exploit isotopologue patterns, isotope ratios, Kendrick mass defect (Cl scale), and collisional cross section (CCS), in order to annotate 157 halogenated features (level 1: 54, level 2: 47, level 3: 50, and level 4: 6). Grouping the features into 11 compound classes was facilitated by a KMD vs CCS plot which showed co-clustering of potentially structurally-related compounds. The features were semi-quantified to gain insight into the distribution of these halogenated features along the French coast, ultimately allowing us to differentiate between sites that are more anthropologically impacted versus sites that are potentially biodiverse.

Evolution of lignin pyrolysis heavy components through the study of representative lignin monomers

Seven typical lignin monomers with different number of methoxyl groups and different 4-substituted patterns were pyrolyzed at 500 °C and 700 °C for 120 s to simulate the secondary polymerization and side chain conversion reactions of primary pyrolytic lignin monomers. The pyrolytic heavy oil components were identified at molecular scale with Fourier transform-ion cyclotron resonance mass spectrometry (FT-ICR-MS) and analyzed with Kendrick mass defect (KMD) and van Krevelen diagrams. The detected heavy components were typically phenolic oligomers formed dominantly through the radical coupling reactions of phenol radicals (C6H4O) and methoxyl radicals (OCH2). Model compounds with CC type 4-substituted groups were prone to produce more phenolic oligomers with more aromatic units. For the CO type model compounds, the number of methoxyl groups have significant influence on the generation of heavy components, thereby affecting the char yields. Rising temperature promotes the generation of heavy components through three main routes, namely the additions of CH2, OCH2 and C6H4O. These routes were mapped on van Krevelen diagrams, shedding light on the evolution patterns of both polymerization and side chain conversion reactions during the secondary pyrolysis of lignin.

Online study of the plasma-accelerated aging process and toxicity of polyethylene terephthalate

Plastic aging occurs in all environmental media and affects their environmental behavior and toxicity. In this study, non-thermal plasma was applied to simulate the aging process of plastics, with polyethylene terephthalate (PET-film) being used as a model. The surface morphology, mass defects, toxicity of aged PET-film and the generation of airborne fine particles were comprehensively characterized. The surface of PET films began to become rough and then gradually became uneven, generating pores, protrusions and cracks. The toxicity of aged PET films was assessed in Caenorhabditis elegans which significantly reduced head thrashing, body bending and brood size. A single particle aerosol mass spectrometry instrument was used to characterize the size distribution and chemical composition of airborne fine particles in real-time. Few particles were observed during the first 90 min, while the generation of particles accelerated significantly after aging time beyond 90 min. For two pieces of PET film with surface area of 5 cm2, during the 180 min, at least 15113 ± 153 fine particles were generated, having a unimodal size distribution with a peak of 0.4 µm. The main components of these particles included metals, inorganic non-metals, and organic components. The results provide useful information on plastic aging and are beneficial in assessing the potential environmental risks.

Harnessing data science to improve molecular structure elucidation from tandem mass spectrometry

Compound structural identification for non-targeted screening of organic molecules in complex mixtures is commonly carried out using liquid chromatography coupled to tandem mass spectrometry (UHPLC-HRMS/MS and related techniques). Instrumental developments in recent years have increased the quality and quantity of data available; however, using current data analysis methods, structures can be assigned to only a small fraction of compounds present in typical mixtures. We present a new data analysis pipeline, “MSEI”, that harnesses data science methodologies to improve structural identification capabilities from tandem mass spectrometry data. In particular, feature vectors for fingerprint calculation are found directly from tandem mass spectra, strongly reducing computational costs, and fingerprint comparison uses an optimised methodology accounting for uncertainty to improve distinction between matching and non-matching compounds. MSEI builds on the identification of a small number of compounds through current state-of-the-art data analysis on UHPLC-HRMS/MS measurements and uses targeted training and tailored molecular fingerprints to focus identification to a particular molecular space of interest. Initial compound identifications are used as training data for a set of random forests which directly predict a custom 75-digit molecular fingerprint from a vectorised MS/MS spectrum. Kendrick mass defects (KMDs) for peaks as well as “lost” fragments removed during fragmentation were found to be useful information for fingerprint prediction. Fingerprints are then compared to potential matches from the PubChem structural database using Euclidean distance, with fingerprint digit weights determined using an SVM to maximise distance between matching and non-matching compounds. Potential matches are additionally filtered for hydrophobicity based on measured retention time, using a newly developed machine learning method for retention time prediction. MSEI was able to correctly assign > 50% of structures in a test dataset and showed > 10% better performance than current state-of-the-art methods, while using an order of magnitude less computational power and a fraction of the training data.

Entropy defect in thermodynamics

This paper describes the physical foundations of the newly discovered “entropy defect” as a basic concept of thermodynamics. The entropy defect quantifies the change in entropy caused by the order induced in a system through the additional correlations among its constituents when two or more subsystems are assembled. This defect is closely analogous to the mass defect that arises when nuclear particle systems are assembled. The entropy defect determines how the entropy of the system compares to its constituent’s entropies and stands on three fundamental properties: each constituent’s entropy must be (i) separable, (ii) symmetric, and (iii) bounded. We show that these properties provide a solid foundation for the entropy defect and for generalizing thermodynamics to describe systems residing out of the classical thermal equilibrium, both in stationary and nonstationary states. In stationary states, the consequent thermodynamics generalizes the classical framework, which was based on the Boltzmann–Gibbs entropy and Maxwell–Boltzmann canonical distribution of particle velocities, into the respective entropy and canonical distribution associated with kappa distributions. In nonstationary states, the entropy defect similarly acts as a negative feedback, or reduction of the increase of entropy, preventing its unbounded growth toward infinity.

Kendrick mass defect analysis - a tool for high-resolution Orbitrap mass spectrometry of native lignin.

Lignin is the second most abundant biopolymer in nature and a promising renewable feedstock for the production of aromatic compounds, composite materials, sorbents, etc. Being a complex mixture of oligomeric molecules with anirregular structure, natural lignin is an extremely difficult object to study. Its molecular level characterization requires advanced analytical techniques among which atmospheric pressure photoionization Orbitrap mass spectrometry holds a promising place. In the present study, Kendrick mass defect (KMD) analysis was proposed to facilitate the visualization and interpretation of Orbitrap mass spectra of the biopolymer on an example of Siberian pine dioxane lignin preparation. The use of the typical guaiacylpropane structure C10H12O4 as a Kendrick base unit made it possible to effectively identify oligomer series with different polymerization degrees and structurally related compounds, as well as to reliably determine the elemental compositions and structures of oligomers with high molecular weights (> 1kDa). For the first time, KMD analysis was applied to the interpretation of the complex tandem mass spectra of lignin oligomers, rapid discrimination of the product ion series, and the establishment of the main collision-induced dissociation pathways. It was demonstrated that especially promising was the use of KMD filtering in the study of broadband fragmentation tandem mass spectra, which allows for the structural characterization of all oligomers with a particular degree of polymerization.

Integration of UHPLC/Q-OrbitrapMS-based metabolomics and activities evaluation to rapidly explore the anti-inflammatory components from lasianthus

Lasianthus, belonging to Rubiaceae, has been verified to improve clinical syndrome in immune diseases (e.g., hepatitis, nephritis, and rheumatoid arthritis). Both the anti-inflammatory function and chemical composition of Lasianthus vary considerably between different species but few studies focus. So essential it is to explore lasianthus and further search for anti-inflammatory substances. The target of this artical is to analyze the anti-inflammatory activity and chemical composition of lasianthus of different species. And the subsequent active compounds were explored. Primary, the anti-inflammatory activity among seven species of lasianthus (e.g., L. fordii., L. wallichii., L. hookeri C., L. verticillatus., L. sikkimensis., L. appressihirtus., and L. hookeri var) were evaluated by vitro experiments (RAW 264.7 cells). Next, UHPLC/Q-Orbitrap-MS-based metabolomics and the mass defect filter (MDF) algorithm were performed to explore metabolites. In addition, principal component analysis (PCA) was to screen out differential compounds in seven species. Finally, the correlation analysis between activities and composition to rapidly discover the active compounds (compounds were verified pharmacologically). Among the 7 species of lasianthus, the L. fordii. and L. hookeri C indicated the best anti-inflammatory activity. Untargeted metabolomics and MDF show 112 compounds, classified into six dominant types (e.g., flavonoids, phenolic acids, alkaloids, iridoids, coumarins, and anthraquinones). Furthermore, 33 differential metabolites were confirmed by PCA. Then according to correlation analysis and pharmacological validation, 7 compounds IC50＜100 (e.g., scopoletin, asperulosidic acid, chlorogenic acid, ferulic acid, betaine, syringic acid, and emodin) were verified as anti-inflammatory compounds and conduct quantitative analysis. Metabolomics integrated with activities evaluation might be a rapid and effective strategy to explore the active compounds from natural products.

Chernaya dyra i temnaya materiya v sinkhronnoy sisteme koordinat

The static state of a black hole in interaction with dark matter is considered in the synchronous coordinate system. Just as in Schwarzschild coordinates, in synchronous coordinates there exists a regular static spherically symmetric solution of the system of Einstein and Klein–Gordon equations that describes the state of matter extremely compressed by its own gravitational field. There is also no constraint on the mass. There also exist two gravitational radii with the boundary conditions at which the solutions are not unique. In contrast to Schwarzschild coordinates, in synchronous coordinates the determinant of the metric tensor and the component g11(r) do not become zero at the gravitational radii. In synchronous coordinates, in contrast to Schwarzschild coordinates, in the spherical layer between the gravitational radii the signature of the metric tensor is not violated. In synchronous coordinates the Einstein and Klein–Gordon equations are reduced to a system of the second (rather than fourth) order. The solutions were obtained analytically, so that no numerical calculations were required. The gravitational mass defect in the λψ4 model was determined. The total mass of matter turns out to be thrice the Schwarzschild mass determined by a remote observer when compared with Newtonian gravity.

Evaluating non-targeted analysis methods for chemical characterization of organic contaminants in different matrices to estimate children's exposure.

Children are vulnerable to environmental exposure of contaminants due to their small size, lack of judgement skills, as well as their proximity to dust, soil, and other environmental sources. A better understanding about the types of contaminants that children are exposed to or how their bodies retain or process these compounds is needed. In this study, we have implemented and optimized a methodology based on non-targeted analysis (NTA) to characterize chemicals in dust, soil, urine, and in the diet (food and drinking water) of infant populations. To evaluate potential toxicological concerns associated with chemical exposure, families with children between 6 months and 6 years of age from underrepresented groups were recruited in the greater Miami area. Samples of soil, indoor dust, food, water, and urine were provided by the caregivers, prepared by different techniques (involving online SPE, ASE, USE, QuEChERs), and analyzed by liquid chromatography-high resolution mass spectrometry (LC-HRMS). Data post-processing was performed using the small molecule structure identification software, Compound Discoverer (CD) 3.3, and identified features were plotted using Kendrick mass defect plot and Van Krevelen diagrams to show unique patterns in different samples and regions of anthropogenic compound classifications. The performance of the NTA workflow was evaluated using quality control standards in terms of accuracy, precision, selectivity, and sensitivity, with an average of 98.2%, 20.3%, 98.4% and 71.1%, respectively. Sample preparation was successfully optimized for soil, dust, water, food, and urine. A total of 30, 78, 103, 20 and 265 annotated features were frequently identified (detection frequency >80%) in the food, dust, soil, water, and urine samples, respectively. Common features detected in each matrix were prioritized and classified, providing insight on children's exposure to organic contaminants of concern and their potential toxicities. Current methods to assess the ingestion of chemicals by children have limitations and are generally restricted by specific classes of targeted organic contaminants of interest. This study offers an innovative approach using non-targeted analysis for the comprehensive screening of organic contaminants that children are exposed to through dust, soil, and diet (drinking water and food).

A mass defect filtering combined background subtraction strategy for rapid screening and identification of metabolites in rat plasma after oral administration of Yindan Xinnaotong soft capsule

The absorbed prototypes and metabolites of traditional Chinese medicines (TCMs) serves an important part in pharmacological action and clinical effects. However, the comprehensive characterization of which is facing actual or possible rigorous challenges due to the lack of data mining methods and the complexity of metabolite samples. Yindan Xinnaotong soft capsule (YDXNT), a typical traditional Chinese medicine prescription consisting of extracts from 8 herbal medicines, is widely used for the treatment of angina pectoris and ischemic stroke in the clinic. This study established a systematic data mining strategy based on ultra-high performance liquid chromatography tandem quadrupole-time-of-fight mass spectrometry (UHPLC-Q-TOF MS) for comprehensive metabolite profiling of YDXNT in rat plasma after oral administration. The multi-level feature ion filtration strategy was primarily conducted through the full scan MS data of plasma samples. All potential metabolites were rapidly fileted out from the endogenous background interference based on the background subtract and the chemical type specifically mass defect filter (MDF) windows including flavonoids, ginkgolides, phenolic acids, saponins, and tanshinones. As the MDF windows of certain types were overlapped, the screened-out potential metabolites were deeply characterized and identified according to their retention times (RT), integrating neutral loss filtering (NLF), diagnostic fragment ions filtering (DFIF), and further confirmed by reference standards. Thus, a total of 122 compounds, consisting of 29 prototype components (16 confirmed with reference standards) and 93 metabolites had been identified. This study provides a rapid and robust metabolite profiling method for researching complicated traditional Chinese medicine prescriptions.