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Motivation Liquid chromatography coupled with mass spectrometry (LC-MS) is widely used in metabolomics studies, while HILIC LC-MS is particularly suited for polar metabolites. Determining an optimized mobile phase and developing a proper liquid chromatography method tend to be laborious, time-consuming and empirical. Results We developed a containerized web tool providing a workflow to quickly determine the optimized mobile phase by batch-evaluating chromatography peaks for metabolomics LC-MS studies. A mass chromatographic quality value, an asymmetric factor, and the local maximum intensity of the extracted ion chromatogram were calculated to determine the number of peaks and peak retention time. The optimal mobile phase can be quickly determined by selecting the mobile phase that produces the largest number of resolved peaks. Moreover, the workflow enables one to automatically process the repeats by evaluating chromatography peaks and determining the retention time of large standards. This workflow was validated with 20 chemical standards and successfully constructed a reference library of 571 metabolites for the HILIC LC-MS platform. Availability and implementation MetaMOPE is freely available at https://metamope.cmdm.tw. Source code and installation instructions are available on GitHub: https://github.com/CMDM-Lab/MetaMOPE. Supplementary information Supplementary data are available at Bioinformatics Advances online.

For centuries, herbal medicines have been used to treat humans and animals. Veterinary medicines are well-regulated; inspectors monitor milk and associated dairy products to screen for unacceptable contaminants. However, few scholars have discussed how the by-products of veterinary herbal medicine can be found in food products. In this paper, we applied nontargeted profiling of the UHPLC–ESI–TOF platform to screen possible by-products originating from veterinary herbal medicine in commercial milk samples. These tentatively identified alkaloids showed high consistency with the plant extract of Holarrhena antidysenterica (L.) Wall. ex A. DC., which indicated the possibility that dairy farmers had used plants from genus Holarrhena as veterinary herbal medicine. This is the first report showing the presence of by-products originating from veterinary herbal medicine in commercial milk. This finding could help authorities to evaluate the use of veterinary herbal medicine in farm animals.

Background Exposure to air pollution exerts direct effects on respiratory organs; however, molecular alterations underlying air pollution-induced pulmonary injury remain unclear. In this study, we investigated the effect of air pollution on the lung tissues of Sprague-Dawley rats with whole-body exposure to traffic-related PM1 (particulate matter Results Rats in the 6-month PM1-exposed group exhibited a significant decline in lung function, as determined by decreased FEF25–75% and FEV20/FVC; however, histological analysis revealed earlier lung damage, as evidenced by increased congestion and macrophage infiltration in 3-month PM1-exposed rat lungs. The lung tissue proteomics analysis identified 2673 proteins that highlighted the differential dysregulation of proteins involved in oxidative stress, cellular metabolism, calcium signalling, inflammatory responses, and actin dynamics under exposures to PM1 and gaseous pollutants. The presence of PM1 specifically enhanced oxidative stress and inflammatory reactions under subchronic exposure to traffic-related PM1 and suppressed glucose metabolism and actin cytoskeleton signalling. These factors might lead to repair failure and thus to lung function decline after chronic exposure to traffic-related PM1. A detailed pathogenic mechanism was proposed to depict temporal and dynamic molecular regulations associated with PM1- and gaseous pollutants-induced lung injury. Conclusion This study explored several potential molecular features associated with early lung damage in response to traffic-related air pollution, which might be used to screen individuals more susceptible to air pollution.

Immunoglobulin A nephropathy (IgAN) is a highly prevalent autoimmune renal disease. Human IgA1 with galactose deficiency in the hinge region (HR) has been identified as an autoantigen for this disease. Therefore, analyzing IgA1 HR glycoforms in biofluids is important for biomarker discovery. Herein, an analytical method that includes one-pot sample preparation with unbiased plasma IgA purification, dual internal standard addition, and sensitive ultra-high-performance liquid chromatography-triple quadrupole tandem mass spectroscopy (UHPLC-QqQ-MS/MS) was developed. Targeted O-glycopeptides detection was performed in pooled plasma with the validation of theoretical retention times, enzymatic treatment outcomes, product ion scans, and signal repeatability. A total of 42 IgA1 O-glycopeptides with N-acetylgalactosamines, galactoses, and sialic acids were determined from 8 µL of plasma. The newly developed method was applied to plasma samples from 16 non-IgAN controls and 19 IgAN patients. Comparing the 42 targets, 16 IgA1 HR O-glycopeptides were statistically different between the two groups (p0.05). Decreased sialylation was identified in the IgA1 hinge region of IgAN patients, which was also correlated with the estimated glomerular filtration rate (eGFR). The developed method is sensitive and precise and can be used to identify plasma biomarkers for IgA nephropathy.

Emerging new psychoactive substances (NPS) poses a great risk to public health. Analyzing these large numbers of NPS and other associated substances often relies on liquid chromatography coupled to triple quadrupole mass spectrometry (LC-QqQ-MS) with multiple-reaction monitoring (MRM) mode. However, the differentiation of critical pairs, coeluted isobaric and/or isomeric species, is one of the challenges for this analytical platform. MRM transitions with poor selectivity can jeopardize accurate quantification and lead to biased interpretation. Herein, we refined a novel workflow for developing an MRM-based method with in-house CriticalPairFinder and TransitionFinder tools for the effective identification of unique and selective MRM transitions. Transitions selected by TransitionFinder showed much better accuracies than those selected only by fragment abundance in some mixtures of critical pairs. Using the proposed analytical strategy, a method that can simultaneously determine 219 NPS and 65 other substances across a variety of NPS classes in urine samples was developed, validated and applied to analyze clinical urine samples. This automated workflow is anticipated to facilitate method development for analyzing complex analytes while considering selectivity.

Immunoglobulin G (IgG) N-glycosylation was discovered to have an association with inflammation status, which has the potential to be a novel biomarker for kidney diseases. In this study, we applied an ultra-high performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS) method to plasma and urine samples from 57 individuals with different levels of kidney function. Natural abundances of total IgG, IgG1, IgG2, and IgG3 subclasses in plasma showed positive correlations to the estimated glomerular filtration rates (eGFRs). Eighteen IgG glycopeptides also showed positive correlations. In contrast, higher IgG amounts were found in urine samples from participants with lower eGFR values. After normalizing IgG glycopeptides from plasma to their respective protein amounts, H4N4F1S1-IgG1 (r = 0.37, p = 0.0047, significant) and H5N4F1S1-IgG1 (r = 0.25, p = 0.063, marginally significant) were the two glycopeptides that still had positive correlations with eGFRs. The results showed that the UHPLC-MS/MS method is capable of investigating IgG profiles, and monitoring IgG and glycosylation patterns is worthy of further clinical application for kidney disease.

Summary Drug discovery targeting G protein-coupled receptors (GPCRs), the largest known class of therapeutic targets, is challenging. To facilitate the rapid discovery and development of GPCR drugs, we built a system, PanGPCR, to predict multiple potential GPCR targets and their expression locations in the tissues, side effects and possible repurposing of GPCR drugs. With PanGPCR, the compound of interest is docked to a library of 36 experimentally determined crystal structures comprising of 46 docking sites for human GPCRs, and a ranked list is generated from the docking studies to assess all GPCRs and their binding affinities. Users can determine a given compound’s GPCR targets and its repurposing potential accordingly. Moreover, potential side effects collected from the SIDER (Side-Effect Resource) database and mapped to 45 tissues and organs are provided by linking predicted off-targets and their expressed sequence tag profiles. With PanGPCR, multiple targets, repurposing potential and side effects can be determined by simply uploading a small ligand. Availability and implementation PanGPCR is freely accessible at https://gpcrpanel.cmdm.tw/index.html. Supplementary information Supplementary data are available at Bioinformatics online.

Due to the development of modern techniques, in the recent years, electronic vehicles and autopilot systems have beensignificant emerged in automobile and IT industrial. This leads the electronics automotive systems and auto-control systems consistedof a lot of high performance Electronic Control Units(ECUs) connected by controller area network (CAN). For realizing morecomplicated design in ECUs, this work integrates real-time OS and network management function. The results improve the CANbusnodes' designing level to as a gateway to interconnect CANbus nodes. As the number of CANbus nodes increase, the verification processis more and more complicated and takes much time. For speeding up the verification process, this work uses CANoe package toprogram the testing script for automotive verification environment. Then the engineer can connect the testing device by CAN to theenvironment for automatic verification. The engineer can define the network messages of the CANbus nodes and tune the design asthe validating progress. The testing results present as XML format and can be transferred to HTML pages for readability. Hence, thiswork realizes an automatic verification environment for CANbus in-vehicle networks.

Fibromyalgia syndrome (FM) is a multifactorial disorder whose pathogenesis and diagnosis are poorly understood. This study investigated differential serum proteome profiles in patients with FM and healthy pain-free controls and explored the association between serum proteome and clinical profiles in patients with FM. Twenty patients with FM (according to the American College of Rheumatology criteria, 2010) and 20 healthy pain-free controls were recruited for optimized quantitative serum proteomics analysis. The levels of pain, pressure pain threshold, sleep, anxiety, depression, and functional status were evaluated for patients with FM. We identified 22 proteins differentially expressed in FM when compared with healthy pain-free controls and propose a panel of methyltransferase-like 18 (METTL18), immunoglobulin lambda variable 3-25 (IGLV3-25), interleukin-1 receptor accessory protein (IL1RAP), and IGHV1OR21-1 for differentiating FM from controls by using a decision tree model (accuracy: 0.97). In addition, we noted several proteins involved in coagulation and inflammation pathways with distinct expression patterns in patients with FM. Novel proteins were also observed to be correlated with the levels of pain, depression, and dysautonomia in patients with FM. We suggest that upregulated inflammation can play a major role in the pathomechanism of FM. The differentially expressed proteins identified may serve as useful biomarkers for diagnosis and evaluation of FM in the future.

Background: Exposure to particulate matter (PM) pollution has direct impacts on the respiratory organs, yet the molecular alterations underlying PM-induced pulmonary injury remain unclear. In this study, we investigated the effect of PM on lung tissues of SD rats with whole-body exposure to traffic-related PM1 (< 1 mm in aerodynamic diameter) pollutants and compared it with rats exposed to high-efficiency particulate air-filtered gaseous pollutants and clean air control for 3 and 6 months. Lung function and histological examinations as well as quantitative proteomics analysis and functional validation were performed. Results: The rats in 6-month PM1-exposed group showed significant decline in lung function by decreased forced expiratory flow and forced expiratory volume, but the histological analysis revealed an earlier lung damage evidenced by increased congestion and macrophage infiltration in 3-month PM1-exposed rat lungs. The lung tissue proteomics analysis identified 2,673 proteins which highlighted dysregulations on proteins involved in oxidative stress, cellular metabolisms, calcium signaling, inflammatory responses, and actin dynamics. The presence of fine particles specifically enhanced the oxidative stress and inflammatory reactions under sub-chronic exposure of traffic-related PM1 and suppressed the glucose metabolism and actin cytoskeleton signaling which might lead to repair failure and thus lung function decline after chronic exposure of traffic-related PM1. A detailed pathogenic mechanism was proposed to depict the temporal and dynamic molecular regulations associated with PM1-induced lung injury.Conclusion: Our study explored the earlier lung injury prior to lung function decline and proposed potential molecular features for traffic-related PM1-induced lung injury.

Background: Exposure to particulate matter (PM) pollution has direct impacts on the respiratory organs, yet the molecular alterations underlying PM-induced pulmonary injury remain unclear. In this study, we investigated the effect of PM on lung tissues from our previously reported rat model with whole-body exposure to traffic-related PM1 pollutants and compared it with rats exposed to high-efficiency particulate air-filtered gaseous pollutants and clean air control for 3 and 6 months. Lung function and histological examinations as well as quantitative proteomics analysis and functional validation were performed. Results: The rats in 6-month PM1-exposed group showed significant decline in lung function by decreased forced expiratory flow and forced expiratory volume, but the histological analysis revealed an earlier lung damage evidenced by increased congestion and macrophage infiltration in 3-month PM1-exposed rat lungs. The lung tissue proteomics analysis identified 2,673 proteins which highlighted dysregulations on proteins involved in oxidative stress, cellular metabolisms, calcium signaling, inflammatory responses, and actin dynamics. The presence of fine particles specifically enhanced the oxidative stress and inflammatory reactions under sub-chronic exposure of traffic-related PM1 and suppressed the glucose metabolism and actin cytoskeleton signaling which might lead to repair failure and thus lung function decline after chronic exposure of traffic-related PM1. A detailed pathogenic mechanism was proposed to depict the temporal and dynamic molecular regulations associated with PM1-induced lung injury.Conclusion: Our study explored the earlier lung injury prior to lung function decline and proposed several proteins as potential molecular features for traffic-related PM1-induced lung injury.