Tandem Mass Spectrometry across Platforms.

PubChem serves as a comprehensive repository, housing over 100 million unique chemical structures representing the breadth of our chemical knowledge across numerous fields including metabolism, pharmaceuticals, toxicology, cosmetics, agriculture, and many more. Rapid identification of these small molecules increasingly relies on electrospray ionization (ESI) paired with tandem mass spectrometry (MS/MS), particularly by comparison to genuine standard MS/MS data sets. Despite its widespread application, achieving consistency in MS/MS data across various analytical platforms remains an unaddressed concern. This study evaluated MS/MS data derived from one hundred molecular standards utilizing instruments from five manufacturers, inclusive of quadrupole time-of-flight (QTOF) and quadrupole orbitrap "exactive" (QE) mass spectrometers by Agilent (QTOF), Bruker (QTOF), SCIEX (QTOF), Waters (QTOF), and Thermo QE. We assessed fragment ion variations at multiple collisional energies (0, 10, 20, and 40 eV) using the cosine scoring algorithm for comparisons and the number of fragments observed. A parallel visual analysis of the MS/MS spectra across instruments was conducted, consistent with a standard procedure that is used to circumvent the still prevalent issue of mischaracterizations as shown for dimethyl sphingosine and C20 sphingosine. Our analysis revealed a notable consistency in MS/MS data and identifications, with fragment ions' m/z values exhibiting the highest concordance between instrument platforms at 20 eV, the other collisional energies (0, 10, and 40 eV) were significantly lower. While moving toward a standardized ESI MS/MS protocol is required for dependable molecular characterization, our results also underscore the continued importance of corroborating MS/MS data against standards to ensure accurate identifications. Our findings suggest that ESI MS/MS manufacturers, akin to the established norms for gas chromatography mass spectrometry instruments, should standardize the collision energy at 20 eV across different instrument platforms.

Automatic categorization of self-acknowledged limitations in randomized controlled trial publications.

OBJECTIVE: Acknowledging study limitations in a scientific publication is a crucial element in scientific transparency and progress. However, limitation reporting is often inadequate. Natural language processing (NLP) methods could support automated reporting checks, improving research transparency. In this study, our objective was to develop a dataset and NLP methods to detect and categorize self-acknowledged limitations (e.g., sample size, blinding) reported in randomized controlled trial (RCT) publications. METHODS: We created a data model of limitation types in RCT studies and annotated a corpus of 200 full-text RCT publications using this data model. We fine-tuned BERT-based sentence classification models to recognize the limitation sentences and their types. To address the small size of the annotated corpus, we experimented with data augmentation approaches, including Easy Data Augmentation (EDA) and Prompt-Based Data Augmentation (PromDA). We applied the best-performing model to a set of about 12K RCT publications to characterize self-acknowledged limitations at larger scale. RESULTS: Our data model consists of 15 categories and 24 sub-categories (e.g., Population and its sub-category DiagnosticCriteria). We annotated 1090 instances of limitation types in 952 sentences (4.8 limitation sentences and 5.5 limitation types per article). A fine-tuned PubMedBERT model for limitation sentence classification improved upon our earlier model by about 1.5 absolute percentage points in F1 score (0.821 vs. 0.8) with statistical significance (p<.001). Our best-performing limitation type classification model, PubMedBERT fine-tuning with PromDA (Output View), achieved an F1 score of 0.7, improving upon the vanilla PubMedBERT model by 2.7 percentage points, with statistical significance (p<.001). CONCLUSION: The model could support automated screening tools which can be used by journals to draw the authors' attention to reporting issues. Automatic extraction of limitations from RCT publications could benefit peer review and evidence synthesis, and support advanced methods to search and aggregate the evidence from the clinical trial literature.

Mucoadhesive, antioxidant, and lubricant catechol-functionalized poly(phosphobetaine) as biomaterial nanotherapeutics for treating ocular dryness.

Dry eye disease (DED) is associated with ocular hyperosmolarity and inflammation. The marketed topical eye drops for DED treatment often lack bioavailability and precorneal residence time. In this study, we investigated catechol-functionalized polyzwitterion p(MPC-co-DMA), composed of 2-methacryloyloxyethyl phosphorylcholine (MPC) and dopamine methacrylamide (DMA) monomers, as potential topical nanotherapeutics for DED. The copolymers were synthesized via random free-radical copolymerization, producing different proportions of catecholic functionalization. All as-prepared polymer compositions displayed good ocular biocompatibility. At a feeding ratio of 1:1, p(MPC1-co-DMA1) can facilitate a robust mucoadhesion via Michael addition and/or Schiff base reaction, thus prolonging ocular residence time after 4 days of topical instillation. The hydration lubrication of MPC and radical-scavenging DMA endow the nano-agent to ease tear-film hyperosmolarity and corneal inflammation. A single dose of p(MPC1-co-DMA1) (1 mg/mL) after 4 days post-instillation can protect the cornea against reactive oxygen species, inhibiting cell apoptosis and the over-expression of pro-inflammatory factors (IL-6 and TNF-α). In clinical assessment, DED-induced rabbit eyes receiving p(MPC1-co-DMA1) could increase lacrimal fluid secretion by 5-fold higher than cyclosporine A. The catechol-functionalized polyzwitterion with enhanced lubricity, mucoadhesion, and anti-oxidation/anti-inflammation properties has shown high promise as a bioactive eye drop formulation for treating DED.

Interaction of SARS-CoV-2 with host cells and antibodies: experiment and simulation.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the devastating global COVID-19 pandemic announced by WHO in March 2020. Through unprecedented scientific effort, several vaccines, drugs and antibodies have been developed, saving millions of lives, but the fight against COVID-19 continues as immune escape variants of concern such as Delta and Omicron emerge. To develop more effective treatments and to elucidate the side effects caused by vaccines and therapeutic agents, a deeper understanding of the molecular interactions of SARS-CoV-2 with them and human cells is required. With special interest in computational approaches, we will focus on the structure of SARS-CoV-2 and the interaction of its spike protein with human angiotensin-converting enzyme-2 (ACE2) as a prime entry point of the virus into host cells. In addition, other possible viral receptors will be considered. The fusion of viral and human membranes and the interaction of the spike protein with antibodies and nanobodies will be discussed, as well as the effect of SARS-CoV-2 on protein synthesis in host cells.

Betainization of Polydopamine/Polyethylenimine Coating for Universal Zwitterionization.

Biofoulants can adhere to multiple surfaces, degrading the performance of medical devices and industrial facilities and/or causing nosocomial infection. The surface immobilization of zwitterionic materials can prevent the initial attachment of the foulants but lacks extensive implementation. Herein, we propose a facile, universal, two-step surface modification strategy to improve fouling resistance. In the first step, the substrates were immersed in a codeposition solution containing dopamine and branched polyethylenimine (PEI) to form a "primer" layer (PDA/PEI). In the second step, the primer layers were treated with 1,3-propane sultone to betainize primary/secondary/tertiary amine moieties of PEI, generating zwitterions on substrates. After betainization, PS-grafted PDA/PEI (PDA/PEI/S) via a ring-opening alkylation reaction manifested changes in wettability. X-ray photoelectron spectroscopy revealed the presence of zwitterionic moieties on the PDA/PEI/S surfaces. Further investigations using ellipsometry and atomic force microscopy were conducted to scrutinize the relation among the PEI content, film thickness, primer stability, and betainization. As a result, zwitterion-decorated substrates prepared under optimal conditions can exhibit high resistance against bacterial fouling, achieving a 98.5% reduction in bacterial attachment. In addition, the method shows a substrate-independent property, capable of successfully applying it on organic and inorganic substrates. Finally, the newly developed approach shows excellent biocompatibility, displaying no significant difference compared with blank control samples. Overall, we envision that the facile surface modification strategy can further promote the preparation of zwitterion-decorated materials in the future.

Elastic moduli of normal and cancer cell membranes revealed by molecular dynamics simulations.

Recent studies indicate that there are mechanical differences between normal cells and cancer cells. Because the cell membrane takes part in a variety of vital processes, we test the hypothesis of whether or not two fundamental alterations in the cell membrane, i.e., the overexpression of phosphatidylserine lipids in the outer leaflet and a reduction in cholesterol concentration, could cause the softening in cancer cells. Adopting ten models of normal and cancer cell membranes, we carry out 1 µs all-atom molecular dynamics simulations to compare the structural properties and elasticity properties of two membrane types. We find that the overexpression of the phosphatidylserine lipids in the outer leaflet does not significantly alter the area per lipid, the membrane thickness, the lipid order parameters and the elasticity moduli of the cancer membranes. However, a reduction in the cholesterol concentration leads to clear changes in those quantities, especially decreases in the bending, tilt and twist moduli. This implies that the reduction of cholesterol concentration in the cancer membranes could contribute to the softening of cancer cells.

XCMS-MRM and METLIN-MRM: a cloud library and public resource for targeted analysis of small molecules.

We report XCMS-MRM and METLIN-MRM ( http://xcmsonline-mrm.scripps.edu/ and http://metlin.scripps.edu/ ), a cloud-based data-analysis platform and a public multiple-reaction monitoring (MRM) transition repository for small-molecule quantitative tandem mass spectrometry. This platform provides MRM transitions for more than 15,500 molecules and facilitates data sharing across different instruments and laboratories.

Toward assessing clinical trial publications for reporting transparency.

OBJECTIVE: To annotate a corpus of randomized controlled trial (RCT) publications with the checklist items of CONSORT reporting guidelines and using the corpus to develop text mining methods for RCT appraisal. METHODS: We annotated a corpus of 50 RCT articles at the sentence level using 37 fine-grained CONSORT checklist items. A subset (31 articles) was double-annotated and adjudicated, while 19 were annotated by a single annotator and reconciled by another. We calculated inter-annotator agreement at the article and section level using MASI (Measuring Agreement on Set-Valued Items) and at the CONSORT item level using Krippendorff's α. We experimented with two rule-based methods (phrase-based and section header-based) and two supervised learning approaches (support vector machine and BioBERT-based neural network classifiers), for recognizing 17 methodology-related items in the RCT Methods sections. RESULTS: We created CONSORT-TM consisting of 10,709 sentences, 4,845 (45%) of which were annotated with 5,246 labels. A median of 28 CONSORT items (out of possible 37) were annotated per article. Agreement was moderate at the article and section levels (average MASI: 0.60 and 0.64, respectively). Agreement varied considerably among individual checklist items (Krippendorff's α= 0.06-0.96). The model based on BioBERT performed best overall for recognizing methodology-related items (micro-precision: 0.82, micro-recall: 0.63, micro-F1: 0.71). Combining models using majority vote and label aggregation further improved precision and recall, respectively. CONCLUSION: Our annotated corpus, CONSORT-TM, contains more fine-grained information than earlier RCT corpora. Low frequency of some CONSORT items made it difficult to train effective text mining models to recognize them. For the items commonly reported, CONSORT-TM can serve as a testbed for text mining methods that assess RCT transparency, rigor, and reliability, and support methods for peer review and authoring assistance. Minor modifications to the annotation scheme and a larger corpus could facilitate improved text mining models. CONSORT-TM is publicly available at https://github.com/kilicogluh/CONSORT-TM.

Comparative TMT Proteomic Analysis Unveils Unique Insights into Helicoverpa armigera (Hübner) Resistance in Cajanus scarabaeoides (L.) Thouars.

Pigeonpea [Cajanus cajan (L.) Millspaugh] is an economically important legume playing a crucial role in the semi-arid tropics. Pigeonpea is susceptible to Helicoverpa armigera (Hübner), which causes devastating yield losses. This pest is developing resistance to many commercially available insecticides. Therefore, crop wild relatives of pigeonpea, are being considered as potential sources of genes to expand the genetic base of cultivated pigeonpea to improve traits such as host plant resistance to pests and pathogens. Quantitative proteomic analysis was conducted using the tandem mass tag platform to identify differentially abundant proteins between IBS 3471 and ICPL 87 tolerant accession and susceptible variety to H. armigera, respectively. Leaf proteome were analysed at the vegetative and flowering/podding growth stages. H. armigera tolerance in IBS 3471 appeared to be related to enhanced defence responses, such as changes in secondary metabolite precursors, antioxidants, and the phenylpropanoid pathway. The development of larvae fed on an artificial diet with IBS 3471 lyophilised leaves showed similar inhibition with those fed on an artificial diet with quercetin concentrations with 32 mg/25 g of artificial diet. DAB staining (3,3'-diaminobenzidine) revealed a rapid accumulation of reactive oxygen species in IBS 3471. We conclude that IBS 3471 is an ideal candidate for improving the genetic base of cultivated pigeonpea, including traits for host plant resistance.

Structure-Based Discovery of ABCG2 Inhibitors: A Homology Protein-Based Pharmacophore Modeling and Molecular Docking Approach.

ABCG2 is an ABC membrane protein reverse transport pump, which removes toxic substances such as medicines out of cells. As a result, drug bioavailability is an unexpected change and negatively influences the ADMET (absorption, distribution, metabolism, excretion, and toxicity), leading to multi-drug resistance (MDR). Currently, in spite of promising studies, screening for ABCG2 inhibitors showed modest results. The aim of this study was to search for small molecules that could inhibit the ABCG2 pump. We first used the WISS MODEL automatic server to build up ABCG2 homology protein from 655 amino acids. Pharmacophore models, which were con-structed based on strong ABCG2 inhibitors (IC50 < 1 µM), consist of two hydrophobic (Hyd) groups, two hydrogen bonding acceptors (Acc2), and an aromatic or conjugated ring (Aro|PiR). Using molecular docking method, 714 substances from the DrugBank and 837 substances from the TCM with potential to inhibit the ABCG2 were obtained. These chemicals maybe favor synthesized or extracted and bioactivity testing.

Investigation of Binding Affinity between Potential Antiviral Agents and PB2 Protein of Influenza A: Non-equilibrium Molecular Dynamics Simulation Approach.

The PB2 protein of the influenza virus RNA polymerase is a major virulence determinant of influenza viruses. It binds to the cap structure at the 5' end of host mRNA to generate short capped RNA fragments that are used as primers for viral transcription named cap-snatching. A large number of the compounds were shown to bind the minimal cap-binding domain of PB2 to inhibit the cap-snatching machinery. However, their binding in the context of an extended form of the PB2 protein has remained elusive. A previous study reported some promising compounds including azaindole and hydroxymethyl azaindole, which were analyzed here to predict binding affinity to PB2 protein using the steered molecular dynamics (SMD) and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) methods. The results show that the rupture force (Fmax) value of three complexes is in agreement with the binding free energy value (ΔGbind) estimated by the MM-PBSA method, whereas for the non-equilibrium pulling work (Wpull) value a small difference between A_PB2-4 and A_PB2-12 was observed. The binding affinity results indicate the A_PB2-12 complex is more favorable than the A_PB2-4 and A_PB2-16 complexes, which means the inhibitor (12) has the potential to be further developed as anti-influenza agents in the treatment of influenza A.

Comparative Analysis Delineates the Transcriptional Resistance Mechanisms for Pod Borer Resistance in the Pigeonpea Wild Relative Cajanus scarabaeoides (L.) Thouars.

Insect pests pose a serious threat to global food production. Pod borer (Helicoverpa armigera (Hübner)) is one of the most destructive pests of leguminous crops. The use of host resistance has been an effective, environmentally friendly and sustainable approach for controlling several agricultural pests. The exploitation of natural variations in crop wild relatives could yield pest-resistant crop varieties. In this study, we used a high-throughput transcriptome profiling approach to investigate the defense mechanisms of susceptible cultivated and tolerant wild pigeonpea genotypes against H. armigera infestation. The wild genotype displayed elevated pest-induced gene expression, including the enhanced induction of phytohormone and calcium/calmodulin signaling, transcription factors, plant volatiles and secondary metabolite genes compared to the cultivated control. The biosynthetic and regulatory processes associated with flavonoids, terpenes and glucosinolate secondary metabolites showed higher accumulations in the wild genotype, suggesting the existence of distinct tolerance mechanisms. This study provides insights into the molecular mechanisms underlying insect resistance in the wild pigeonpea genotype. This information highlights the indispensable role of crop wild relatives as a source of crucial genetic resources that could be important in devising strategies for crop improvement with enhanced pest resistance.

A Novel Truncated Form of Nephronectin Is Present in Small Extracellular Vesicles Isolated from 66cl4 Cells.

Extracellular vesicles are emerging as biomarkers in breast cancer. Our recent report suggested that an intracellular granular staining pattern of the extracellular matrix protein nephronectin (NPNT) in breast tumor sections correlated with a poor prognosis. Furthermore, the results showed that NPNT is localized in extracellular vesicles derived from mouse breast cancer cells. In this study, we performed proteomic analysis that revealed that several proteins, including tumor-promoting molecules, are differentially expressed in the cargo of small extracellular vesicles (sEVs) derived from NPNT-expressing mouse breast cancer cells. We also identified three different forms of NPNT at 80, 60, and 20 kDa. We report that the native form of NPNT at 60 kDa becomes further glycosylated and is detected as the 80 kDa NPNT, which may be processed by matrix metalloproteinases to a shorter form of around 20 kDa, which has not previously been described. Although both 80 and 20 kDa NPNT are detected in sEVs derived from breast cancer cells, the 20 kDa form of NPNT is concentrated in sEVs. In summary, we show that a novel truncated form of NPNT is found in sEVs derived from breast cancer cells.

Pegylated Metal-Phenolic Networks for Antimicrobial and Antifouling Properties.

Metal-phenolic networks (MPNs) have recently attracted great interest in material chemistry and biomaterials because of their biocompatible, versatile, and multifunctional properties. In this paper, we describe a facile method for preparation of a designable antifouling, antimicrobial, and substrate-independent coating assembled from the coordination of metal ions and catecholic groups. Hydrophilic and catecholic polymers were synthesized by copolymerization of dopamine methacrylamide (DMA) and poly(ethylene glycol)methyl methacrylate (PEGMA) to afford p(PEGMA- co-DMA). To investigate the assembly and formation of MPN films, two different metal ions, that is, ferrous (FeII) and ferric (FeIII) ions, to react with p(PEGMA- co-DMA) were compared. The binding constants between iron ions and p(PEGMA- co-DMA) have been investigated by ultraviolet-visible spectroscopy (UV-vis). Measurements with atomic force microscopy, contact angle goniometer, and X-ray photoelectron spectroscopy (XPS) were carried out to quantitatively analyze the surface morphology, wettability, and interfacial elemental compositions of coatings, respectively. Moreover, ellipsometric measurements were performed to obtain the film thickness and grafting density. In addition, the pH-responsive property of the MPN films was investigated at different pH values, showing fast disassembly of the networks at low pH. The antifouling properties of the obtained coatings were analyzed by exposing them to bacteria of Escherichia coli and Staphylococcus epidermidis and NIH-3T3 fibroblasts under observation of fluorescence microscopy and cell imaging analysis. The findings suggest that the MPN from complexation of p(PEGMA- co-DMA) and metal ions provides excellent antifouling, pH-responsive, and biocompatible properties on a wide range of substrates. Furthermore, the released iron ions can effectively suppress the growth of bacteria. Accordingly, the new coating architecture offers a universal feature to control surface properties and functionalization for various applications.

Bulk phase resource ratio alters carbon steel corrosion rates and endogenously produced extracellular electron transfer mediators in a sulfate-reducing biofilm.

Desulfovibrio alaskensis G20 biofilms were cultivated on 316 steel, 1018 steel, or borosilicate glass under steady-state conditions in electron-acceptor limiting (EAL) and electron-donor limiting (EDL) conditions with lactate and sulfate in a defined medium. Increased corrosion was observed on 1018 steel under EDL conditions compared to 316 steel, and biofilms on 1018 carbon steel under the EDL condition had at least twofold higher corrosion rates compared to the EAL condition. Protecting the 1018 metal coupon from biofilm colonization significantly reduced corrosion, suggesting that the corrosion mechanism was enhanced through attachment between the material and the biofilm. Metabolomic mass spectrometry analyses demonstrated an increase in a flavin-like molecule under the 1018 EDL condition and sulfonates under the 1018 EAL condition. These data indicate the importance of S-cycling under the EAL condition, and that the EDL is associated with increased biocorrosion via indirect extracellular electron transfer mediated by endogenously produced flavin-like molecules.

Eliminating common biases in modelling the electrical conductivity of carbon nanotube-polymer nanocomposites.

Modelling carbon nanotube-polymer nanocomposites to predict their electrical conductivity demands high computational power. Past research has led to the assumption that conductive networks follow a periodic pattern; however, the impact of the underlying biases had never been investigated. This work provides insights into evaluating such biases and eliminating them to improve simulation accuracy.

Exposome-Scale Investigations Guided by Global Metabolomics, Pathway Analysis, and Cognitive Computing.

Concurrent exposure to a wide variety of xenobiotics and their combined toxic effects can play a pivotal role in health and disease, yet are largely unexplored. Investigating the totality of these exposures, i.e., the "exposome", and their specific biological effects constitutes a new paradigm for environmental health but still lacks high-throughput, user-friendly technology. We demonstrate the utility of mass spectrometry-based global exposure metabolomics combined with tailored database queries and cognitive computing for comprehensive exposure assessment and the straightforward elucidation of biological effects. The METLIN Exposome database has been redesigned to help identify environmental toxicants, food contaminants and supplements, drugs, and antibiotics as well as their biotransformation products, through its expansion with over 700 000 chemical structures to now include more than 950 000 unique small molecules. More importantly, we demonstrate how the XCMS/METLIN platform now allows for the readout of the biological effect of a toxicant through metabolomic-derived pathway analysis, and further, artificial intelligence provides a means of assessing the role of a potential toxicant. The presented workflow addresses many of the methodological challenges current exposomics research is facing and will serve to gain a deeper understanding of the impact of environmental exposures and combinatory toxic effects on human health.

Acylcarnitines are anticoagulants that inhibit factor Xa and are reduced in venous thrombosis, based on metabolomics data.

In many patients with deep vein thrombosis and pulmonary embolism (venous thromboembolism, VTE), biomarkers or genetic risk factors have not been identified. To discover novel plasma metabolites associated with VTE risk, we employed liquid chromatography-mass spectrometry-based untargeted metabolomics, which do not target any specific metabolites. Using the Scripps Venous Thrombosis Registry population for a case-control study, we discovered that 10:1 and 16:1 acylcarnitines were low in plasmas of the VTE patient group compared with matched controls, respectively. Data from targeted metabolomics studies showed that several long-chain acylcarnitines (10:1, 12:0, 12:2, 18:1, and 18:2) were lower in the VTE group. Clotting assays were used to evaluate a causal relationship for low acylcarnitines in patients with VTE. Various acylcarnitines inhibited factor Xa-initiated clotting. Inhibition of factor Xa by acylcarnitines was greater for longer acyl chains. Mechanistic studies showed that 16:0 acylcarnitine had anticoagulant activity in the absence of factor Va or phospholipids. Surface plasmon resonance investigations revealed that 16:0 acylcarnitine was bound to factor Xa and that binding did not require the γ-carboxy glutamic acid domain. In summary, our study identified low plasma levels of acylcarnitines in patients with VTE and showed that acylcarnitines have anticoagulant activity related to an ability to bind and inhibit factor Xa.

Rapid elimination of SARS-CoV-2 in a fully vaccinated patient. / Rask eliminasjon av SARS-CoV-2 hos fullvaksinert pasient.

High SARS-CoV-2 viral loads in respiratory secretions detected by PCR technique are usually an indicator of high transmission risk, but not always. In this article, we present the case of a fully-vaccinated patient with rapid clearance of the alpha variant of the virus.

Determining conserved metabolic biomarkers from a million database queries.

MOTIVATION: Metabolite databases provide a unique window into metabolome research allowing the most commonly searched biomarkers to be catalogued. Omic scale metabolite profiling, or metabolomics, is finding increased utility in biomarker discovery largely driven by improvements in analytical technologies and the concurrent developments in bioinformatics. However, the successful translation of biomarkers into clinical or biologically relevant indicators is limited. RESULTS: With the aim of improving the discovery of translatable metabolite biomarkers, we present search analytics for over one million METLIN metabolite database queries. The most common metabolites found in METLIN were cross-correlated against XCMS Online, the widely used cloud-based data processing and pathway analysis platform. Analysis of the METLIN and XCMS common metabolite data has two primary implications: these metabolites, might indicate a conserved metabolic response to stressors and, this data may be used to gauge the relative uniqueness of potential biomarkers. AVAILABILITY AND IMPLEMENTATION: METLIN can be accessed by logging on to: https://metlin.scripps.edu CONTACT: siuzdak@scripps.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.