Fragmentation Patterns Research Articles

A New Paradigm for Assessing Detailed Dynamics of Forest Landscape Fragmentation

There is an urgent need for a thorough assessment of forest landscape fragmentation to inform forest protection and restoration, and reforestation policies. However, there is currently a lack of an effective comprehensive index for forest landscape fragmentation, and detailed knowledge of the forest landscape fragmentation dynamics remains insufficient. Here, taking Putian City of Fujian Province in Southeastern China as a case, we employed a forest fragmentation comprehensive index (FFCI) to capture key features of forest landscape fragmentation, such as patch size, number, and distribution. Then, bivariate spatial autocorrelation analysis was employed to identify the spatial associations between the static forest landscape fragmentation (FFCI) and the dynamic forest landscape fragmentation (ΔFFCI), and the spatial coupling modes among the three individual components of FFCI (mean patch area, MPA; aggregation index, AI; patch density, PD) were identified to explore the detail process of forest landscape fragmentation. Finally, the random forest model was applied to observe the impact factors of forest landscape fragmentation dynamics. The findings showed that forest landscapes with different degrees of fragmentation exhibited more noticeable changes at both ends (i.e., either high or lower-level fragmentation), with the intermediate level remaining consistent from 2000 to 2020. Around 18.3% of forest landscapes experienced a decrease in fragmentation, particularly in the northern part of the study area, while approximately 81.7% of forest landscapes exhibited an increasing trend in fragmentation. The bivariate spatial autocorrelation analysis indicated that the proportion of Low–High-type grids was the highest at 17.3%, followed by the High–High type at 7.0%. We also identified eight forest landscape fragmentation modes, which indicate the most significant forest landscape fragmentation pattern is a decrease in MPA and an increase in PD. Moreover, the anthropogenic factors (e.g., population density and night light intensity) were found to dominate the FFCI dynamics during 2000–2020. This study offers an efficient research paradigm for the dynamics of forest landscape fragmentation. The outcomes are conducive to an in-depth comprehension of the detailed dynamic information of forest landscape fragmentation, and supply a scientific foundation for enhancing the overall ecological service function of the forest.

Morphomolecular Correlation and Clinicopathologic Analysis in Endometrial Carcinoma.

Research groups have identified 4 groups [polymerase epsilon (POLE) mutant, mismatch repair-deficient, p53-abnormal, and no specific molecular profile)] reflecting the Tumor Cancer Genomic Atlas Research Network subgroups in endometrial carcinomas, improving the clinical applicability of molecular classification. We have analyzed the histopathologic and prognostic characteristics of our cases based on the ProMisE classification, supported by growing data on recommended treatment regimens. The study included 118 cases of endometrial carcinoma diagnosed between 2016 and 2020, which underwent mismatch repair and p53 immunohistochemistry. Next-generation sequencing was performed for POLE mutation analysis, dividing the cases into 4 subgroups. The histopathologic and clinical characteristics of these groups were then analyzed statistically. Four cases(3.4%) were classified as POLE mutant, 31 (26.3%) as mismatch repair-deficient, 22 (18.6%) as p53 mutant, and 61 (51.7%) as no specific molecular profile. We categorized 118 patients with endometrial carcinoma into low (n=43), intermediate (n=28), high-intermediate (n=21), high (n=22), and advanced metastatic (n=4) risk groups regardless of the molecular subtypes of their disease. When we reclassified all cases according to the molecular subtypes of endometrial carcinoma only the risk group of 3 (2.5%) cases changed. Using the new algorithm we designed, after narrowing down the number of patients, the microcystic, elongated, and fragmented pattern of invasion was revealed as an independent prognostic factor that reduces overall survival time (hazard ratio: 16.395, 95% CI: 2.140-125.606, P =0.007). In conclusion, using the new algorithm we have designed, and by identifying patients for whom molecular classification could alter risk groups, we observed that molecular tests can be utilized more efficiently in populations with limited economic resources and, in doing so, we discovered a new morphologic marker with prognostic significance.

Exploring the time axis within medium-modified jets

In this manuscript, we illustrate how to use the newly proposed τ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ au $$\\end{document} re-clustering algorithm to select jets with different degrees of quenching without biasing their initial transverse momentum spectrum. Our study is based on Z+jet simulated events using the JEWEL Monte Carlo event generator to account for jet quenching effects. We apply the τ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ au $$\\end{document} re-clustering algorithm to extract a proxy for a time axis (formation time) within the evolving medium. This information allows us to label jets according to their fragmentation pattern and select populations with enhanced sensitivity to quenching effects. Our results illustrate the potential of jets as precision tools for QGP tomography. Further, we show that the discussed method minimizes the biases stemming from pT\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p_{T}$$\\end{document}-, ΔR\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Delta R$$\\end{document}- or mass-based jet selection.

Metabolic profiling of a new synthetic cannabinoid receptor agonist, ADMB-FUBIATA, with human liver microsomes, human primary hepatocytes and human recombinant CYP450 enzymes using LC-quadrupole-orbitrap MS

A novel synthetic cannabinoid receptor agonist (SCRA), ADMB-FUBIATA, featuring an acetamide-linked structure, has emerged on the illicit drug market. To provide dependable verification of its consumption and identify reliable biomarkers, we investigated an in vitro metabolism study of ADMB-FUBIATA incubated with human primary hepatocytes (HPHs) for the first time and correlated our findings with those from human liver microsomes (HLMs). In this work, ADMB-FUBIATA (10 μM) was incubated with HLM and HPH for 1 and 5 h, respectively, and then subjected to LC-quadrupole-orbitrap MS. A total of 25 metabolites across 8 metabolic pathways were identified after incubation with HLM and HPH, respectively. Monohydroxylation and N-dealkylation were the major metabolic pathways, and formation to ketone was first identified. In addition, the metabolism of ADMB-FUBIATA were found to be mediated by multiple CYP450 enzymes, predominantly CYP2C19, 2D6, and 3A4. This research also initially characterized the fragmentation patterns of the metabolites of ADMB-FUBIATA, elaborating on their structural relationship with ADMB-FUBIATA analogs. To effectively monitor ADMB-FUBIATA abuse, metabolites M4 and M1 were proposed as reliable biomarkers by cross-validating the HLM and HPH incubation results.

Electron Capture vs Transfer Dissociation for Site Determination of Tryptic Peptide Tyrosine Sulfation: Direct Detection of Fibrinogen Sulfation Sites and Identification of Novel Isobaric Interferences.

Tyrosine sulfation, an understudied but crucial post-translational modification, cannot be directly detected in conventional nanoflow liquid chromatography-tandem mass spectrometry (nanoLC-MS/MS) due to the extreme sulfate lability. Here, we report the detection of sulfate-retaining fragments from LC-electron capture dissociation (ECD) and nanoLC-electron transfer higher energy collision dissociation (EThcD). Sulfopeptide candidates were identified by Proteome Discoverer and MSFragger analysis of nanoLC-HCD MS/MS data and added to inclusion lists for LC-ECD or nanoLC-EThcD MS/MS. When this approach failed, targeted LC-ECD with fixed m/z isolation windows was performed. For the plasma protein fibrinogen, the known pyroglutamylated sulfopeptide QFPTDYDEGQDDRPK from the beta chain N-terminus was identified despite a complete lack of sulfate-containing fragment ions. The peptide QVGVEHHVEIEYD from the gamma-B chain C-terminus was also identified as sulfated or phosphorylated. This sulfopeptide is not annotated in Uniprot but was previously reported. MSFragger further identified a cysteine-containing peptide from the middle of the gamma chain as sulfated and deamidated. NanoLC-EThcD and LC-ECD MS/MS confirmed the two former sulfopeptides via sulfate-retaining fragment ions, whereas an unexpected fragmentation pattern was observed for the third sulfopeptide candidate. Manual interpretation of the LC-ECD spectrum revealed two additional isobaric identifications: a trisulfide-linked cysteinyl-glycine or a carbamidomethyl-dithiothreiotol covalent adduct. Synthesis of such adducts confirmed the latter identity.

Chemical Composition and Therapeutic Potential of Syngonium podophyllum L. Leaves against Hypercholesterolemia in Rats: Liver, Kidney, and Heart Crosstalk

Background: One of the main risk factors for atherosclerosis is hypercholesterolemia Objective: This study aimed to assess hypercholesterolemia's effect on the liver, heart, and kidney and the impact of Syngonium podophyllum L. leaves methanolic extract as a treating agent in a rat model. Methods: Flavonoid components were isolated and identified from the methanolic extract of Syngonium podophyllum L. leaves. Total serum leptin, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), aspartate and alanine aminotransferases (AST and ALT), urea, and creatinine levels were all measured as part of the biochemical evaluation. The liver tissue was tested for levels of malondialdehyde (MDA), glutathione (GSH), superoxide dismutase (SOD), and DNA fragmentation. Results: Thirty-nine compounds were identified by GC/MS profiling of the n-hexane fraction of Syngonium podophyllum L leaves. The major volatile constituents were decane, 4-methyl, decane, N-acetyl 3-pentenyl, 1-amine, 2-methyl, 1-hexene, and 3-hydroxy, propanenitrile, while the major phenolic compounds isolated from methanolic extract were luteolin-7- α-L rhamnoside-4'- O-β-glucopyranoside (1), apigenin 6, 8-di-C-β-glucopyranoside (vicenin 2) (2), quercetin-3-Oα-L-rhamnoside (3), quercetin-7-O-β-glucoside compound (4), luteolin-7-O-β-glucoside (5), 5- hydroxy-6,7,8,4'-tetramethoxy flavone (6), gallic acid (7) and quercetin (8). Hypercholesterolemic rats revealed significant alterations (p ≤ 0.05) in the lipid profile, liver and kidney function, DNA fragmentation pattern and antioxidant indices. With oral cholesterol administration of 30 mg/0.3 mL, 0.7% tween/rats fed a high-fat diet for nine weeks, treatment with leaves extract (250 mg/kg body weight) was able to restore all biochemical parameters as well as the architectures of the liver and heart. Conclusion: Due to its abundance in physiologically active phenolic and flavonoid components, the methanolic extract of Syngonium podophyllum L. leaves successfully served as a hypolipidemic, anti-atherosclerotic, and antioxidant therapeutic agent.

Chemical composition analysis of Ganoderma lucidum based on UPLC-Orbitrap-HRMS and virtual screening of FXR activators for treatment of liver fibrosis

The chemical composition of Ganoderma lucidum ethanol extracts was systematically analyzed and identified by ultra-high performance liquid chromatography-quadrupole electrostatic field orbitrap high-resolution mass spectrometry(UPLC-Orbitrap-HRMS). The fragmentation pattern of the representative chemical compounds was summarized, and the potential anti-liver fibrosis active compounds of G. lucidum acting on the farnesoid X receptor(FXR) target were studied to elucidate its pharmacodynamic substance basis. Preliminarily, 95 chemical constituents of G. lucidum ethanol extracts were identified, including 24 ganoderic acids, 9 ganoderenic acids, 13 lucidenic acids, 3 ganolucidic acids, 1 ganoderma lactone, 40 other triterpenoids, 4 fatty acids, and 1 other constituent. In addition, the fragmentation patterns of the representative compounds were also analyzed. The structural characteristics of ganoderic acids and ganoderenic acids were the C30 skeleton, containing free-COOH and-OH groups, which could easily lose H_2O and CO_2 to form fragment ions. The D-ring was mostly a five-membered ring, which was prone to breakage. Lucidenic acids were the lanosterolane-type of the C27 skeleton, and the side-chain structure became shorter and contained the same free-COOH and-OH compared with ganoderic acids, which had been reduced from 8 to 5 cartons and prone to lose H_2O and CO_2. Then, six reported FXR receptor agonists were selected to form a training set for establishing a pharmacophore model based on FXR ligands. The 95 identified chemical constituents of G. lucidum were matched with the pharmacophore, and the optimal pharmacophore model 02(sensitivity=0.750 00, specificity=0.555 56, ROC=0.750) was selected for the virtual screening of the G. lucidum compound library through the validation of the test set. Finally, 31 potential G. lucidum active constituents were screened and chosen to activate the FXRs. The ADMET results showed that ganoderic acid H and lucidenic acid J had less than 90% plasma protein binding rate and no hepatotoxicity, which could be used as FXR activators for developing clinical drugs for the treatment of liver fibrosis, either alone or in combination.

SpecEncoder: deep metric learning for accurate peptide identification in proteomics.

Tandem mass spectrometry (MS/MS) is a crucial technology for large-scale proteomic analysis. The protein database search or the spectral library search are commonly used for peptide identification from MS/MS spectra, which, however, may face challenges due to experimental variations between replicated spectra and similar fragmentation patterns among distinct peptides. To address this challenge, we present SpecEncoder, a deep metric learning approach to address these challenges by transforming MS/MS spectra into robust and sensitive embedding vectors in a latent space. The SpecEncoder model can also embed predicted MS/MS spectra of peptides, enabling a hybrid search approach that combines spectral library and protein database searches for peptide identification. We evaluated SpecEncoder on three large human proteomics datasets, and the results showed a consistent improvement in peptide identification. For spectral library search, SpecEncoder identifies 1%-2% more unique peptides (and PSMs) than SpectraST. For protein database search, it identifies 6%-15% more unique peptides than MSGF+ enhanced by Percolator, Furthermore, SpecEncoder identified 6%-12% additional unique peptides when utilizing a combined library of experimental and predicted spectra. SpecEncoder can also identify more peptides when compared to deep-learning enhanced methods (MSFragger boosted by MSBooster). These results demonstrate SpecEncoder's potential to enhance peptide identification for proteomic data analyses. The source code and scripts for SpecEncoder and peptide identification are available on GitHub at https://github.com/lkytal/SpecEncoder. Contact: hatang@iu.edu.

Simultaneous Detection Method of 11 Respiratory Drug Substances Including Theobromine, Oxymetazoline, etc. in Adulterated Dietary Supplements Using Liquid Chromatography–Electrospray Ionization–Tandem Mass Spectrometry and Liquid Chromatography–Quadrupole Time-of-Flight Mass Spectrometry Analysis

Abstract Recently, the demand for respiratory disease-related products has surged due to the influence of coronavirus disease 2019, prompting warnings about illegal dietary supplements containing unauthorized substances. Additionally, adulterated dietary supplements are continuously detected in open markets, posing significant public health safety problem. In this study, we developed and validated an analytical method for 11 respiratory drug substances using liquid chromatography–electrospray ionization–tandem mass spectrometry (LC–ESI–MS/MS) and proposed optimal conditions for LC–quadrupole time-of-flight MS (LC–QTOF-MS) to determine the fragmentation patterns of each substance. This method underwent thorough validation considering specificity, linearity, limits of detection and quantification, accuracy, precision, matrix effect, stability, etc. All results met international guidelines. These validated methods were applied to 52 dietary supplements advertised for treating respiratory diseases and enhancing respiratory function, among which one sample was found to contain 313.7 mg/g of theobromine. This determination was made by comparing the product ion ratios with the standards and subsequent quantification. To re-confirm the detected substances, their fragmentation patterns were compared with those of the standards using LC–QTOF-MS. In conclusion, the mass-based information, coupled with the LC–ESI–MS/MS method development, can be successfully applied to rapidly identify 11 respiratory drug substances in illegal dietary supplements used for respiratory disease treatment. The developed simultaneous detection method contributes to public health and safety improvements.

Translation of Epigenetics in Cell-Free DNA Liquid Biopsy Technology and Precision Oncology.

Technological advancements in cell-free DNA (cfDNA) liquid biopsy have triggered exponential growth in numerous clinical applications. While cfDNA-based liquid biopsy has made significant strides in personalizing cancer treatment, the exploration and translation of epigenetics in liquid biopsy to clinical practice is still nascent. This comprehensive review seeks to provide a broad yet in-depth narrative of the present status of epigenetics in cfDNA liquid biopsy and its associated challenges. It highlights the potential of epigenetics in cfDNA liquid biopsy technologies with the hopes of enhancing its clinical translation. The momentum of cfDNA liquid biopsy technologies in recent years has propelled epigenetics to the forefront of molecular biology. We have only begun to reveal the true potential of epigenetics in both our understanding of disease and leveraging epigenetics in the diagnostic and therapeutic domains. Recent clinical applications of epigenetics-based cfDNA liquid biopsy revolve around DNA methylation in screening and early cancer detection, leading to the development of multi-cancer early detection tests and the capability to pinpoint tissues of origin. The clinical application of epigenetics in cfDNA liquid biopsy in minimal residual disease, monitoring, and surveillance are at their initial stages. A notable advancement in fragmentation patterns analysis has created a new avenue for epigenetic biomarkers. However, the widespread application of cfDNA liquid biopsy has many challenges, including biomarker sensitivity, specificity, logistics including infrastructure and personnel, data processing, handling, results interpretation, accessibility, and cost effectiveness. Exploring and translating epigenetics in cfDNA liquid biopsy technology can transform our understanding and perception of cancer prevention and management. cfDNA liquid biopsy has great potential in precision oncology to revolutionize conventional ways of early cancer detection, monitoring residual disease, treatment response, surveillance, and drug development. Adapting the implementation of liquid biopsy workflow to the local policy worldwide and developing point-of-care testing holds great potential to overcome global cancer disparity and improve cancer outcomes.

Structural characterization of sphingomyelins from tissue using electron-induced dissociation.

Sphingomyelins (SMs) and resulting metabolic products serve important functional and cell signaling roles and can act as potential biomarkers and therapeutic targets in many pathological disorders. SMs each contain a sphingoid base, an amide-linked fatty acyl chain, and a phosphocholine headgroup. Despite these simple building blocks, variations and modifications of both the sphingoid base and the fatty acyl chain result in a diverse array of structurally complicated SM compounds. Conventional tandem mass spectrometry (MS/MS) using the collision-induced dissociation (CID) method only provides limited structural information, necessitating other tools to unravel the structural complexity of these lipids. We utilize electron-induced dissociation (EID) and sequential CID/EID approaches to elucidate detailed structural features of SMs. Integrating the CID/EID method into an imaging MS workflow enables accurate identification of SMs directly from kidney tissue. The application of EID enables identification of SMs at the molecular species level, identifying the sphingosine base and the amide-linked fatty acyl chains. Furthermore, removal of the phosphocholine headgroup via CID followed by sequential EID in an MS3 analysis (CID/EID) enhances the structural information obtained. CID/EID provides diagnostic fragmentation patterns revealing the hydroxylation site and double bond position in both the sphingosine base and amide-linked fatty acyl chains. Detailed structural information of SMs from synthetic standards and biological tissue samples is obtained using an alternative electron-based dissociation method. Accurate characterization of SMs promises to better inform studies of tissue biochemistry, lipid metabolism, and molecular pathology.

Matrices to enhance the ion yield of OLED molecules in ToF-SIMS: An interesting alchemist solution

Since the early days of time of flight secondary ion mass spectrometry (ToF-SIMS), increasing the ion signal has been crucial. It is even more crucial when performing tandem mass spectrometry experiments. To achieve this goal, many developments have been made over the years, which are divided into two categories: instrumental development and sample modification. The latter involves sample metallization, matrix deposition, or changing the temperature of the measurement. In this study, the possibility of using matrices to enhance the signals of organic light emitting device (OLED) molecules was explored. Seven molecules commonly used in OLEDs were separately deposited on Si wafers: Alq3, 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane, 1,4,5,8,9,11-hexaazatriphenylenehexacarbonitrile, Ir(mppy)3, N,N′-bis(naphthalene-1-yl)-N,N′-bis(phenyl)benzidine, 2,2′,7,7′-tetra(N,N-ditolyl)-amino-spiro-bifluor (STTB), and tris(4-carbazoyl-9-ylphenyl)amine. Using the same solvent, three different matrices with different thicknesses, common in matrix assisted light desorption ionization time of flight mass spectrometry, α-cyano-4-hydroxycinnamic acid, 2,5-dihydrobenzoic acid (DHB), and dihydrochloride N-(1-Naphthyl)ethylenediamine, were sprayed on these surfaces. Spectra were acquired for all compounds and spraying conditions in static ToF-SIMS experiments for Alq3 chemical imaging and depth profiling were performed. This allowed the investigation of the fragmentation pattern of the chosen matrices in ToF-SIMS and, thus, obtained a reference for these molecules. The results show that matrices can enhance the signal of fragments of the studied molecules, for example, the signal of STTB is increased with DHB spraying. Samples sprayed only with the solvent were also prepared to verify the impact of the matrices on the signal. Spraying with the solvent alone can enhance the signal even more than the matrices up to four times in the case of Alq3. This result opens new possibilities in the field of matrix-enhanced ToF-SIMS in terms of applications and matrix choices.

The Prognostic Value of Tumor Cell Clusters in the Fallopian Tube Lumen in Stage I Endometrioid Carcinoma.

The aim of this study was to investigate the pathologic prognostic factors such as tumor cell clusters (TCCs) in the fallopian tube lumen, myometrial invasion patterns, and positive peritoneal cytology (PPC) in women with Stage I endometrial endometrioid carcinoma (EEC). From 2009 to 2020, consecutive patients with Stage I EEC who underwent hysterectomy and bilateral salpingectomy were included. The primary outcome was the recurrence-free survival (RFS) rate, and the clinicopathological factors affecting RFS were analyzed. A total of 765 patients were enrolled. Seventeen patients (2.2%) had TCC in the fallopian tube lumen, and 58 patients showed a microcystic elongated and fragmented pattern (7.6%). PPC was found in 19 patients (2.5%). The median follow-up period was 61.0 months (range: 2.0-149.7). The majority (88.6%) of patients had Stage IA EEC. The 5-year RFS and overall survival rates were 97.5% and 98.5%, respectively. In multivariate analysis for RFS, the significant prognostic factors were lymphovascular invasion (hazard ratio = 4.604; 95% CI: 1.387-15.288; P = 0.013) and grade (grade 2; hazard ratio = 4.949; 95% CI: 1.035-23.654; P = 0.045, and grade 3; hazard ratio = 5.469; 95% CI: 1.435-20.848; P = 0.013). Other pathologic factors including TCC in the fallopian tube lumen, myometrial invasion patterns, PPC, and hormonal status had no prognostic significance. TCC in the fallopian tube lumen, myometrial invasion pattern, PPC, and estrogen and progesterone receptor positivity were not significant prognostic factors in Stage I EEC. In contrast, lymphovascular invasion and grade were significant prognostic factors.

Benzylic rearrangement for urinary analysis of guanidino and ureido compounds in cardiac surgery-associated acute kidney injury using high-performance liquid chromatography-tandem mass spectrometry.

RationaleBecause acute kidney injury (AKI) is closely related to poor prognosis in critically ill patients, developing biomarkers for its prediction and early diagnosis is particularly important. Endogenous guanidino compounds (GCs) and ureido compounds (UCs) can participate in various biochemical processes because of their important physiological activities. The aim of this study was to investigate the alteration profiles of urinary GCs/UCs as potential biomarkers in patients with cardiac surgery–associated acute kidney injury (CSA‐AKI) at different stages.MethodsGCs/UCs were reacted with benzil via benzylic rearrangement, and their derivatives were used to investigate fragmentation mechanisms using tandem mass spectrometry (MS/MS) in positive ion mode. Furthermore, a high‐performance liquid chromatography (HPLC)–MS/MS method was developed to measure the concentrations of GCs/UCs in urine samples taken from patients with CSA‐AKI at different time points.ResultsMS/MS analysis in positive ion mode showed that benzylic GCs/UCs exhibited similar fragmentation processes, which could produce the characteristic ion (C13H12N+) at m/z 182.0. Furthermore, an obviously different fragmentation pattern of benzylic UCs in the positive ion mode might be due to the neutral loss of the H2CO2 group under low collision energy. Of the eight selected GCs/UCs, methylguanidine exhibited significantly increased concentrations in urine when CSA‐AKI occurred, whereas guanidinoethyl sulfonate (GDS), homoarginine (HArg) and homocitrulline (HCit) exhibited decreased concentrations. After recovery from AKI, the urinary concentrations of the aforementioned GCs/UCs returned to normal. Some of the aforementioned metabolites with significant changes (GDS, HArg and HCit) had large areas under the curve in the receiver operating characteristic curve for distinguishing AKI stages on the third day after surgery.ConclusionsIn patients with CSA‐AKI, urinary GCs/UCs were significantly disrupted due to injured kidney, and some GC/UC metabolites exhibited a good ability to become potential biomarkers for AKI stages. The present study provides essential resources and new therapeutic targets for further research on CSA‐AKI.

Synthesis and analytical characterization of 1‐(2‐thienoyl)‐6‐allyl‐nor‐d‐lysergic acid diethylamide (1T‐AL‐LAD)

AbstractLysergic acid diethylamide (LSD) analogs have emerged as new psychoactive substances (NPS) since the mid‐2010s, and new compounds continue to emerge for recreational use. Since the end of 2023, “1D‐AL‐LAD” appeared on X (formerly Twitter) and other websites. As for the compound “1D‐LSD” (which also has “1D” in the name), several studies show that the ingredient of seized blotter paper printed “1D‐LSD” was actually 1‐(2‐thienoyl)‐LSD (1T‐LSD). However, there are no reports of seizures of 1‐(1,2‐dimethylcyclobutanecarbonyl)‐LSD (1D‐LSD). Accordingly, it was considered that all or at least a certain percentage of “1D‐AL‐LAD (1‐(1,2‐dimethylcyclobutanecarbonyl)‐6‐allyl‐nor‐LSD)” is actually 1‐(2‐thienoyl)‐6‐allyl‐nor‐LSD (1T‐AL‐LAD). This compound is handled by a number of distributors as of April 2024; therefore, it should be characterized in advance if seized. In this study, 1T‐AL‐LAD was synthesized and characterized using nuclear magnetic resonance spectroscopy, Fourier transform‐infrared spectroscopy, liquid chromatography/high‐resolution mass spectrometry (LC/HRMS) and gas chromatography/MS (GC/MS). This compound was easily distinguished from previously reported lysergamides. There were some differences in the detectability of 1T‐AL‐LAD compared with other lysergamides using GC/MS and the fragmentation patterns in LC/HRMS. These differences can be reasonably explained. This information will be of help to determine this substance in seized materials should it emerge on the market.

Fragmentation Patterns of Phenolic C-Glycosides in Mass Spectrometry Analysis.

Many phenolic C-glycosides possess nutritional benefits and pharmacological efficacies. However, the MS/MS fragmentation pattern of phenolic C-glycosides analysis is understudied. This paper aims to determine the MS/MS fragmentation patterns of phenolic C-glycosides. Ten compounds with different sugar moieties, aglycones, and substitutes were analyzed to determine the impact of these structural features on MS/MS fragmentation using UPLC-QTOF-MS analysis. The results showed that water loss followed by RDA reaction and alpha cleavage in the C-C bonded sugar moieties are the major fragmentation pathways. Additionally, the sugar cleavage was not affected by the skeleton and the substitute of the aglycones. These results suggested that the fragmentation patterns of phenolic C-glycosides differ from those in the O-glycosides, where the O-C glycosidic bond is the most cleavage-liable bond in MS/MS analysis. These MS/MS fragmentation patterns can be used for the identification of C-glycosides from dietary components and herbal medicine as well as developing robust methods using MRM methods to quantify C-glycosides.

Multilayer Annotation Strategy AnnoSePS: Disentangling the Intricate Structure of Selenium-Containing Polysaccharides Based on Preferential Fragmentation Patterns.

Precision mapping of selenium at structural and position levels poses significant challenges in selenium-containing polysaccharide identification. Due to the absence of reference spectra, database-centric approaches are still limited in the discovery of selenium binding sites and distinction among different isomeric structures. A multilayer annotation strategy, AnnoSePS, is proposed for achieving the identification of seleno-substituent and the unbiased profiling of polysaccharides. Applying Snoop-triggered multiple reaction monitoring (Snoop-MRM) identified multidimensional monosaccharides in selenium-containing polysaccharides. Galactose, galacturonic acid, and glucose were the predominant monosaccharides with a molar ratio of 25.19, 19.45, and 11.72, respectively. Selenium present in seleno-rhamnose was found to substitute the hydroxyl group located at C-1 positions through the formation of a Se-H bond. Ions C6H9O3Se-, C6H7O3Se-, C5H5O3Se-, C4H5O2Se-, C3H5O2Se-, C2H3O2Se-, and CHOSe- were defined as the characteristic fragments of seleno-rhamnose. The agglomerative hierarchical clustering algorithm is applied to group spectra from each run based on the characteristic information. Preferential fragmentation patterns in mass spectrometry are revealed by training a probabilistic model. A list of candidate oligosaccharides is generated by step-by-step browsing through the transition pairs for all reference spectra and applying the transitions (addition, insertion, removal, and substitution) to reference structures. Combining time course analyses revealed the linkage composition of selenium-containing oligosaccharides. Glycosidic linkages were annotated based on a synthesis-driven approach. T-Galactose (16.67 ± 5.23%) and T-Galacturonic acid (11.54 ± 4.66%) were the predominant linkage residues. As the database-independent mapping strategy, AnnoSePS makes it possible to comprehensively interrogate spectral data and dissect the fine structure of selenium-containing polysaccharides.

Nontarget and suspect screening reveals the presence of multiple plastic-related compounds in polar bear, killer whale, narwhal and long-finned pilot whale blubber from East Greenland

The monitoring of legacy contaminants in sentinel northern marine mammals has revealed some of the highest concentrations globally. However, investigations into the presence of chemicals of emerging Arctic concern (CEACs) and other lesser-known chemicals are rarely conducted, if at all. Here, we used a nontarget/suspect approach to screen for thousands of different chemicals, including many CEACs and plastic-related compounds (PRCs) in blubber/adipose from killer whales (Orcinus orca), narwhals (Monodon monoceros), long-finned pilot whales (Globicephala melas), and polar bears (Ursus maritimus) in East Greenland. 138 compounds were tentatively identified mostly as PRCs, and four were confirmed using authentic standards: di(2-ethylhexyl) phthalate (DEHP), diethyl phthalate (DEP), di(2-propylheptyl) phthalate (DPHP), and one antioxidant (Irganox 1010). Three other PRCs, a nonylphenol isomer, 2,6-di-tert-butylphenol, and dioctyl sebacate, exhibited fragmentation patterns matching those in library databases. While phthalates were only above detection limits in some polar bear and narwhal, Irganox 1010, nonylphenol, and 2,6-di-tert-butylphenol were detected in >50% of all samples. This study represents the first application of a nontarget/suspect screening approach in Arctic cetaceans, leading to the identification of multiple PRCs in their blubber. Further nontarget analyses are warranted to comprehensively characterize the extent of CEAC and PRC contamination within Arctic marine food webs.

Systematically Evaluating Cell-Free DNA Fragmentation Patterns for Cancer Diagnosis and Enhanced Cancer Detection via Integrating Multiple Fragmentation Patterns.

Cell-free DNA (cfDNA) fragmentation patterns have immense potential for early cancer detection. However, the definition of fragmentation varies, ranging from the entire genome to specific genomic regions. These patterns have not been systematically compared, impeding broader research and practical implementation. Here, 1382 plasma cfDNA sequencing samples from 8 cancer types are collected. Considering that cfDNA within open chromatin regions is more susceptible to fragmentation, 10 fragmentation patterns within open chromatin regions as features and employed machine learning techniques to evaluate their performance are examined. All fragmentation patterns demonstrated discernible classification capabilities, with the end motif showing the highest diagnostic value for cross-validation. Combining cross and independent validation results revealed that fragmentation patterns that incorporated both fragment length and coverage information exhibited robust predictive capacities. Despite their diagnostic potential, the predictive power of these fragmentation patterns is unstable. To address this limitation, an ensemble classifier via integrating all fragmentation patterns is developed, which demonstrated notable improvements in cancer detection and tissue-of-origin determination. Further functional bioinformatics investigations on significant feature intervals in the model revealed its impressive ability to identify critical regulatory regions involved in cancer pathogenesis.

Decoding thermal properties in polymer-inorganic heat dissipators: a data-driven approach using pyrolysis mass spectrometry

ABSTRACT Polymeric materials can boost their performances by strategically incorporating inorganic substances. Heat dissipators are a representative class of such composite materials, where inorganic fillers and matrix polymers contribute to high thermal conductivity and strong adhesion, respectively, resulting in excellent heat dissipation performance. However, due to the complex interaction between fillers and polymers, even slight differences in structural parameters, e.g. dispersion/aggregation degree of fillers and crosslink density of polymers, may significantly impact material performance, complicating the quality management and guidelines for material developments. Therefore, we introduce pyrolysis mass spectra (MS) as material descriptors. On the basis of these spectra, we construct prediction models using a data-driven approach, specifically focusing on thermal conductivity and adhesion, which are key indicators for heat dissipating performance. Pyrolysis-MS observes thermally decomposable polymers, which occupy only 0.1 volume fraction of the heat dissipators; nevertheless, the physical states of non-decomposable inorganic fillers are implicitly reflected in the pyrolyzed fragment patterns of the matrix polymers. Consequently, pyrolysis-MS provides sufficient information to construct accurate models for predicting heat dissipation performance, simplifying quality management by substituting time-consuming performance evaluations with rapid pyrolysis-MS measurements. Furthermore, we elucidate that higher crosslinking density of the matrix polymers enhances thermal conductivity. This data-driven method promises to streamline the identification of key functional factors in complex composite materials.