EMNGly: predicting N-linked glycosylation sites using the language models for feature extraction.

MOTIVATION: N-linked glycosylation is a frequently occurring post-translational protein modification that serves critical functions in protein folding, stability, trafficking, and recognition. Its involvement spans across multiple biological processes and alterations to this process can result in various diseases. Therefore, identifying N-linked glycosylation sites is imperative for comprehending the mechanisms and systems underlying glycosylation. Due to the inherent experimental complexities, machine learning and deep learning have become indispensable tools for predicting these sites. RESULTS: In this context, a new approach called EMNGly has been proposed. The EMNGly approach utilizes pretrained protein language model (Evolutionary Scale Modeling) and pretrained protein structure model (Inverse Folding Model) for features extraction and support vector machine for classification. Ten-fold cross-validation and independent tests show that this approach has outperformed existing techniques. And it achieves Matthews Correlation Coefficient, sensitivity, specificity, and accuracy of 0.8282, 0.9343, 0.8934, and 0.9143, respectively on a benchmark independent test set.

Combination of total glucosides of paeony, narrow-band ultraviolet B, and oral corticosteroid mini-pulse therapy for nonsegmental vitiligo: A retrospective study.

BACKGROUND: The total glucoside of paeony (TGP) is recognized for its immunomodulatory properties and anti-inflammatory effects. This study evaluates the efficacy of TGP combined with oral mini-pulse therapy (OMP) and narrow-band ultraviolet B (NB-UVB) in treating active nonsegmental vitiligo (NSV). MATERIALS AND METHODS: The combination therapy was contrasted against those from a group treated solely with OMP and NB-UVB. Data from 62 patients undergoing TGP combination treatment and 55 without were analyzed over a 3-month period. After 6 months, the differences in recurrence rate were investigated by follow-up. RESULTS: The findings indicate that integrating TGP may yield superior outcomes compared to OMP + NB-UVB alone. Moreover, the patient's oxidative stress makers were significantly reduced after the treatment. The majority of patients in the TGP cohort exhibited enhanced skin pigmentation over the duration. Notably, no increase in side effects or recurrence was observed in this group. Especially, patients with vitiligo on their head and neck experienced pronounced improvements. CONCLUSION: The efficacy of the combination treatment group was better than that of the control group at 2 and 3 months, and there was no difference in recurrence rate and side effects, suggesting that TGP may continue to show efficacy in NSV for a longer period of time by reducing the level of oxidative stress, and is especially suitable for patients with head and neck lesions.

GIPS-Mix for Accurate Identification of Isomeric Components in Glycan Mixtures Using Intelligent Group-Opting Strategy.

Accurate identification of glycan structures is highly desirable as they are intimately linked to their different functions. However, glycan samples generally exist as mixtures with multiple isomeric structures, making assignment of individual glycan components very challenging, even with the aid of multistage mass spectrometry (MSn). Here, we present an approach, GIPS-mix, for assignment of isomeric glycans within a mixture using an intelligent group-opting strategy. Our approach enumerates all possible combinations (groupings) of candidate glycans and opts in the best-matched glycan group(s) based on the similarity between the simulated spectra of each glycan group and the acquired experimental spectra of the mixture. In the case that a single group could not be elected, a tie break is performed by additional MSn scanning using intelligently selected precursors. With 11 standard mixtures and 6 human milk oligosaccharide fractions, we demonstrate the application of GIPS-mix in assignment of individual glycans in mixtures with high accuracy and efficiency.

NIST Interlaboratory Study on Glycosylation Analysis of Monoclonal Antibodies: Comparison of Results from Diverse Analytical Methods.

Glycosylation is a topic of intense current interest in the development of biopharmaceuticals because it is related to drug safety and efficacy. This work describes results of an interlaboratory study on the glycosylation of the Primary Sample (PS) of NISTmAb, a monoclonal antibody reference material. Seventy-six laboratories from industry, university, research, government, and hospital sectors in Europe, North America, Asia, and Australia submitted a total of 103 reports on glycan distributions. The principal objective of this study was to report and compare results for the full range of analytical methods presently used in the glycosylation analysis of mAbs. Therefore, participation was unrestricted, with laboratories choosing their own measurement techniques. Protein glycosylation was determined in various ways, including at the level of intact mAb, protein fragments, glycopeptides, or released glycans, using a wide variety of methods for derivatization, separation, identification, and quantification. Consequently, the diversity of results was enormous, with the number of glycan compositions identified by each laboratory ranging from 4 to 48. In total, one hundred sixteen glycan compositions were reported, of which 57 compositions could be assigned consensus abundance values. These consensus medians provide community-derived values for NISTmAb PS. Agreement with the consensus medians did not depend on the specific method or laboratory type. The study provides a view of the current state-of-the-art for biologic glycosylation measurement and suggests a clear need for harmonization of glycosylation analysis methods.

Best-first search guided multistage mass spectrometry-based glycan identification.

MOTIVATION: Glycan identification has long been hampered by complicated branching patterns and various isomeric structures of glycans. Multistage mass spectrometry (MSn) is a promising glycan identification technique as it generates multiple-level fragments of a glycan, which can be explored to deduce branching pattern of the glycan and further distinguish it from other candidates with identical mass. However, the automatic glycan identification still remains a challenge since it mainly relies on expertise to guide a MSn instrument to generate spectra. RESULTS: Here, we proposed a novel method, named bestFSA, based on a best-first search algorithm to guide the process of spectrum producing in glycan identification using MSn. BestFSA is able to select the most appropriate peaks for next round of experiments and complete the identification using as few experimental rounds. Our analysis of seven representative glycans shows that bestFSA correctly distinguishes actual glycans efficiently and suggested bestFSA could be used in practical glycan identification. The combination of the MSn technology coupled with bestFSA should greatly facilitate the automatic identification of glycan branching patterns, with significantly improved identification sensitivity, and reduce time and cost of MSn experiments. AVAILABILITY AND IMPLEMENTATION: http://glycan.ict.ac.cn. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Vascularized composite allograft rejection is delayed by infusion of IFN-γ-conditioned BMSCs through upregulating PD-L1.

Mesenchymal stromal cells (MSCs) have been applied in prevention from allograft rejection based on their immunomodulatory effects. However, conflicting results have been presented among recent studies, for which one possibility being acknowledged is that the exact effect is determined by the microenvironment when MSCs are applied in vivo. Using a hind limb composite tissue allograft model, we investigate the influence of IFN-γ-preconditioning on the immunomodulatory effects of MSCs and the subsequent allograft survival. Firstly, different doses of IFN-γ were respectively used to incubate with bone marrow-derived MSCs (BMSCs). We found that IFN-γ altered the expression of PD-L1, a major suppressor gene in the immune system during allograft rejection, in a strictly dose-dependent manner in BMSCs. Ten nanograms per milliliter IFN-γ-incubated BMSCs significantly stimulated PD-L1 expression and suppressed T cell proliferation and differentiation, while 50 ng/mL IFN-γ-incubated BMSCs sharply reduced PD-L1 expression. Moreover, we observed that, in contrast to the naive BMSC transplantation group, BMSCs pre-conditioned with 10 ng/mL IFN-γ (BMSCs-IFN-γ) significantly delayed the allograft rejection in vivo. In vitro mixed lymphocyte reaction (MLR) indicated that BMSCs-IFN-γ inhibited T lymphocyte proliferation and activation via PD-L1. Moreover, BMSCs-IFN-γ did not influence the proliferation and activation of T lymphocytes when PD-L1 protein was neutralized by the PD-L1 antibody. These data collectively reveal a role of recipient ongoing immune microenviroment in BMSC-based immunesuppressive therapy. Graphical abstract ᅟ.

Toward Automated Identification of Glycan Branching Patterns Using Multistage Mass Spectrometry with Intelligent Precursor Selection.

Glycans play important roles in a variety of biological processes. Their activities are closely related to the fine details of their structures. Unlike the simple linear chains of proteins, branching is a unique feature of glycan structures, making their identification extremely challenging. Multistage mass spectrometry (MS n) has become the primary method for glycan structural identification. The major difficulty for MS n is the selection of fragment ions as precursors for the next stage of scanning. Widely used strategies are either manual selection by experienced experts, which requires considerable expertise and time, or simply selecting the most intense peaks by which the product-ion spectrum generated may not be structurally informative and therefore fail to make the assignment. We here report a glycan "intelligent precursor selection" strategy (GIPS) to guide MS n experiments. Our approach consists of two key elements, an empirical model to calculate candidate glycan's probability and a statistical model to calculate fragment ion's distinguishing power in order to select the structurally most informative peak as the precursor for next-stage scanning. Using 15 glycan standards, including three pairs with isomeric sequences and eight variously fucosylated oligosaccharides on linear or branched hexasaccharide backbones isolated from a human milk oligosaccharide fraction by HPLC, we demonstrate its successful application to branching pattern analysis with improved efficiency and sensitivity and also the potential for automated operation.

OpenMS-Simulator: an open-source software for theoretical tandem mass spectrum prediction.

BACKGROUND: Tandem mass spectrometry (MS/MS) acts as a key technique for peptide identification. The MS/MS-based peptide identification approaches can be categorized into two families, namely, de novo and database search. Both of the two types of approaches can benefit from an accurate prediction of theoretical spectrum. A theoretical spectrum consists of m/z and intensity of possibly occurring ions, which are estimated via simulating the spectrum generating process. Extensive researches have been conducted for theoretical spectrum prediction; however, the prediction methods suffer from low prediciton accuracy due to oversimplifications in the spectrum simulation process. RESULTS: In the study, we present an open-source software package, called OpenMS-Simulator, to predict theoretical spectrum for a given peptide sequence. Based on the mobile-proton hypothesis for peptide fragmentation, OpenMS-Simulator trained a closed-form model for the intensity ratio of adjacent y ions, from which the whole theoretical spectrum can be constructed. On a collection of representative spectra datasets with annotated peptide sequences, experimental results suggest that OpenMS-Simulator can predict theoretical spectra with considerable accuracy. The study also presents an application of OpenMS-Simulator: the similarity between theoretical spectra and query spectra can be used to re-rank the peptide sequence reported by SEQUEST/X!Tandem. CONCLUSIONS: OpenMS-Simulator implements a novel model to predict theoretical spectrum for a given peptide sequence. Compared with existing theoretical spectrum prediction tools, say MassAnalyzer and MSSimulator, our method not only simplifies the computation process, but also improves the prediction accuracy. Currently, OpenMS-Simulator supports the prediction of CID and HCD spectrum for peptides with double charges. The extension to cover more fragmentation models and support multiple-charged peptides remains as one of the future works.

Risk factors for post-ERCP pancreatitis: A systematic review and meta-analysis.

BACKGROUND AND AIM: Pancreatitis is the most common and serious complication of diagnostic and therapeutic endoscopic retrograde cholangiopancreatography (ERCP). Prevention strategies targeting risk factors could be important to reduce the rate of post-ERCP pancreatitis. However, the risk factors for post-ERCP pancreatitis (PEP) are still debated. This systematic review and meta-analysis was performed to identify risk factors for PEP. METHODS: Medline (PubMed and Ovid), Cochrane Central Register of Controlled trials & Database of Systematic Reviews, Embase, Scopus, ScienceDirect, Springer links and WEB OF SCIENCE were searched for published studies in all languages. Inclusion and exclusion criteria were defined a priori. Eighteen probable risk factors were evaluated, and outcomes were expressed in the case of dichotomous variables, as an odds ratio (OR) (with a 95% confidence interval, (CI)). RESULTS: When patient-related risk factors were analyzed, the ORs for female gender was 1.46 (95%CI: 1.30-1.64); for previous pancreatitis 2.03 (95%CI: 1.31-3.14); for previous PEP was 2.90 (95%CI: 1.87-4.48); for Sphincter of Oddi dysfunction (SOD) was 2.04 (95%CI: 1.73-2.33) and for Intraductal papillary mucinous neoplasm (IPMN) was 3.01 (95%CI: 1.34-6.77). Four endoscopy-related factors were confirmed: the OR for difficult cannulation was 3.49 (95%CI: 1.364-8.925); for endoscopic sphincterotomy (EST) it was 1.39 (95%CI: 1.09-1.79); for precut sphincterotomy it was 2.25 (95%CI: 1.70_2.96); and for main pancreatic duct injection it was 1.58 (95%CI: 1.21-2.08). CONCLUSIONS: Female gender, previous pancreatitis, previous PEP, SOD, IPMN, difficult cannulation, EST, precut sphincterotomy and main pancreatic duct injection are risk factors for post-ERCP pancreatitis.

Ski diminishes TGF-ß1-induced myofibroblast phenotype via up-regulating Meox2 expression.

OBJECTIVE: The aim of the present work was to investigate the mechanism of transforming growth factor (TGF)-ß1 and Sloan-Kettering Institute (Ski) in the pathogenesis of hypertrophic scars (HS). BACKGROUND: Wound healing is an inherent process, but the aberrant wound healing of skin injury may lead to HS. There has been growing evidence suggesting a role for TGF-ß1 and Ski in the pathogenesis of fibrosis. MATERIAL AND METHODS: The MTT assay was used to detect the cell proliferation induced by TGF-ß1. The Ski gene was transduced into cells with an adenovirus, and then the function of Ski in cell proliferation and differentiation was observed. Ski mRNA levels were measured by RT-PCR. Western blotting was used to detect the protein expression of α-SMA, E-cadherin, Meox1, Meox2, Zeb1 and Zeb2. RESULTS: TGF-ß1 can promote human skin fibroblast (HSF) cell proliferation in a time-dependent manner, but the promoting effect could be suppressed by Ski. TGF-ß1 also induces the formation of the myofibroblast phenotype and the effect of TGF-ß1 could be diminished by Ski. Also, Ski modulates the cardiac myofibroblast phenotype and function through suppression of Zeb2 by up-regulating the expression of Meox2. CONCLUSIONS: Ski diminishes the myofibroblast phenotype induced by TGF-ß1 through the suppression of Zeb2 by up-regulating the expression of Meox2.

Recombinant Art v4.01 protein produces immunological tolerance by subcutaneous immunotherapy in a wormwood pollen-driven allergic asthma female mouse model.

Art v4.01 is a well-known profilin protein belonging to the pan-allergens group and is commonly involved in triggering allergic asthma, polyallergy, and cross-sensitization. It is also referred to as Wormwood due to its origin. Crude wormwood extracts are applied for allergen-specific immunotherapy (AIT). Whether the recombinant Art v4.01 (rArt v4.01) can produce in vivo immunological tolerance by subcutaneous immunotherapy (SCIT) remains elusive. In this study, to investigate the in vivo immunological response of rArt v4.01, Th2, Th1, Treg, Th17 type-related cytokines and phenotypes of immune cells were tested, facilitating the exploration of the underlying mechanisms. The expression and purification of Art v4.01 were carried out using recombinant techniques. Allergic asthma female BALB/c mice were induced by subcutaneous sensitization of wormwood pollen extract and intranasal challenges. SCIT without adjuvant was performed using the rArt v4.01 and wormwood pollen extract for 2 weeks. Following exposure to challenges, the levels of immunoglobulin E (IgE), cytokines, and inflammatory cells were assessed through enzyme-linked immunosorbent assay (ELISA) and histological examination of sera, bronchoalveolar lavage fluid (BALF), and lung tissue. These parameters were subsequently compared between treatment groups receiving rArt v4.01 and wormwood pollen extract. The rArt v4.01 protein was expressed, which had a high purity (>90%) and an allergenic potency. Compared with the pollen extract, rArt v4.01 was superior in terms of reducing the number of white blood cells (WBCs), total nucleated cells (TNCs), and monocytes (MNs) in BALF and the degree of lung inflammation (1.77±0.99 vs. 2.31±0.80, P > 0.05). Compared with the model group, only rArt v4.01 reduced serum IgE level (1.19±0.25 vs. 1.61±0.17 µg/ml, P = 0.062), as well as the levels of Th2 type-related cytokines (interleukin-4 (IL-4) (107.18±16.17 vs. 132.47±20.85 pg/ml, P < 0.05) and IL-2 (19.52±1.19 vs. 24.02±2.14 pg/ml, P < 0.05)). The study suggested that rArt v4.01 was superior to pollen extract in reducing the number of inflammatory cells in BALF, pneumonitis, levels of pro-inflammatory cytokines, and serum IgE level. These findings confirmed that Art v4.01 could be a potential candidate protein for allergen-specific immunotherapy.

Exploration of a Predictive Model for Keloid and Potential Therapeutic Drugs based on Immune Infiltration and Cuproptosis-Related Genes.

The aim of this study was to investigate the correlation between CRGs and immunoinfiltration in keloid, develop a predictive model for keloid occurrence, and explore potential therapeutic drugs. The microarray datasets (GSE7890 and GSE145725) were obtained from Gene Expression Omnibus database to identify the differentially expressed genes (DEGs) between keloid and non-keloid samples. Key genes were identified through immunoinfiltration analysis and DEGs, then analyzed for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, followed by the identification of protein-protein interaction networks, transcription factors, and miRNAs associated with key genes. Additionally, a logistic regression analysis was performed to develop a predictive model for keloid occurrence, and potential candidate drugs for keloid treatment were identified. Three key genes (FDX1, PDHB, DBT) were identified, showing involvement in acetyl-CoA biosynthesis, mitochondrial matrix, oxidoreductase activity, and the tricarboxylic acid cycle. Immune infiltration analysis suggested the involvement of B cells, Th1 cells, DCs, T helper cells, APC co-inhibition, and T cell co-inhibition in keloid. These genes were used to develop a logistic regression-based nomogram for predicting keloid occurrence with an AUC of 0.859 and good calibration.We identified 32 potential drug molecules and extracted the top 10 compounds based on their P-values, showing promise in targeting key genes and potentially effective against keloid. Our study identified some genes in keloid pathogenesis and potential therapeutic drugs. The predictive model enhance early diagnosis and management. Further research is needed to validate and explore clinical implications.

Protocol for automated N-glycan sequencing using mass spectrometry and computer-assisted intelligent fragmentation.

Biological functions of glycans are intimately linked to fine details in branches and linkages, which make structural identification extremely challenging. Here, we present a protocol for automated N-glycan sequencing using multi-stage mass spectrometry (MSn). We describe steps for release/purification and derivation of glycans and procedures for MSn scanning. We then detail "glycan intelligent precursor selection" to computationally guide MSn experiments. The protocol can be used for both discrete individual glycans and isomeric glycan mixtures. For complete details on the use and execution of this protocol, please refer to Sun et al.,1 Huang et al.,2 and Huang et al.3.

Inhibition of Glycyrrhiza Polysaccharide on Human Cytochrome P450 46A1 in vitro and in vivo: Implications in Treating Neurological Diseases.

BACKGROUND: Cytochrome P450 (CYP) 46A1, also known as cholesterol 24S-hydroxylase, is essential for maintaining the homeostasis of cholesterol in the brain and serves as a therapeutic target of neurodegenerative disorders and excitatory neurotoxicity. N-methyl-d-aspartate receptor (NMDAR) is a prototypical receptor for the excitatory neurotransmitter glutamate and can be specifically regulated by 24S-hydroxycholesterol (24S-HC). Glycyrrhiza is one of the most widely used herbs with broad clinical applications. It has several pharmacological activities, such as clearing heat and detoxifying, moistening the lung and relieving cough, analgesic, neuroprotective outcomes, and regulating a variety of drug activities. Glycyrrhiza is a commonly used herb for the treatment of epileptic encephalopathy. However, whether glycyrrhiza can interfere with the activity of CYP46A1 remains unknown. OBJECTIVE: This study aimed to investigate the regulating effects of glycyrrhiza polysaccharides (GP) on CYP46A1-mediated cholesterol conversion, as well as in the modulation of related proteins. MATERIALS AND METHODS: The effects of glycyrrhiza polysaccharide (GP) on the activity of CYP46A1 were investigated in vivo and in vitro. Moreover, the potential regulatory effects of GP on the expressions of CYP46A1, HMG-CoA reductase (HMGCR), and NMDAR were also detected. RESULTS: The in vitro results demonstrated that glycyrrhiza polysaccharide (GP), as the main water-soluble active component of glycyrrhiza, remarkably inhibited the activity of CYP46A1 in a non-competitive mode with a Ki value of 0.7003 mg/ml. Furthermore, the in vivo experiments verified that GP markedly decreased the contents of 24S-HC in rat plasma and brain tissues as compared to the control. More importantly, the protein expressions of CYP46A1, GluN2A, GluN2B, and HMG-CoA reductase (HMGCR) in rat brains were all downregulated, whereas the mRNA expressions of CYP46A1 and HMGCR were not significantly changed after treatment with GP. CONCLUSION: GP exhibits a significant inhibitory effect on CYP46A1 activity in vitro and in vivo, and the protein expressions of CYP46A1, HMGCR, and NMDAR are also inhibited by GP, which are of considerable clinical significance for GP's potential therapeutic role in treating neurological diseases.

Far upstream element-binding protein 1 (FUBP1) is overexpressed in human gastric cancer tissue compared to non-cancerous tissue.

BACKGROUND: The aim of this study was to investigate the role of far upstream element-binding protein 1 (FUBP1) in gastric cancer development. PATIENTS AND METHODS: Using immunohistochemistry, we detected FUBP1 expression in 18 chronic superficial gastritis patients, 33 chronic atrophic gastritis patients, 21 moderate and severe gastric dysplasia patients, and 31 gastric cancer patients. FUBP1 mRNA expression in gastric cancer tissue and paraneoplastic tissue was measured with fluorescent quantitative reverse transcription polymerase chain reaction. RESULTS: The FUBP1 expression rates in the chronic atrophic gastritis, moderate and severe dysplasia, and gastric cancer patients were 51.51% (17/33), 76.19% (16/21), and 90.32% (28/31), respectively; these were higher than the expression rate of the chronic superficial gastritis patients (11.11%, 2/18). FUBP1 expression in the gastric cancer patients was significantly higher than that in the chronic atrophic gastritis patients. The relative amount (0.2593 ± 0.1209) of FUBP1 mRNA in the gastric cancer tissue was higher than that in paraneoplastic tissue (0.1969 ± 0.0211) (p < 0.05). There was a statistically significant correlation between overall survival rates and age, sex, lymph node metastasis, and distant metastasis (p < 0.05). CONCLUSION: FUBP1 expression differs among gastric tissues. There is a correlation between overall survival rates and age, sex, lymph node metastasis, and distant metastasis.

[Effect of Hanfangji compound on proliferation of hepatic stellate cells and expressions of TTR, ITIH1 and SERPINF2].

OBJECTIVE: To observe and compare the effects of Hanfangji Compound and IFN-gamma on expressions of transthyretin (TTR) , inter-alpha inhibitor H1 (ITIH1) and serpin peptidase inhibitor clade F member 2 (SERPINF2) of hepatic stellate cells (HSC-T6). METHOD: Hanfangji Compound and IFN-gammaof different concentrations were used in hepatic stellate cell-T6 (HSC-T6) for 48 h. Flow cytometer was used to detect the effects of Hanfangji Compound and IFN-gamma on HSC proliferation. RT-PCR method was adopted to detect mRNA expressions of TFR, ITIH1 and SERPINF2. TTR, ITIH1 and SERPINF2 secretions were detected by ELISA. The protein localizations of TTR, ITIH1 and SERPINF2 were examined by immune fluorescence. The protein expression of TfR and ITIHI were determined by Western blot. RESULT: After Hanfangji Compound and IFN-gamma were adopted in HSC-T6, compared with the control group, the cell proliferation was inhibited obviously (P < 0. 05) , protein expressions of TTR, ITIH1 and SERPINF2 and mRNA expression increased significantly, with certain correlation with concentrations of Hanfangji Compound. The 2. 5 g L-I Hanfangji Compound group was superior to the IFN-gamma group (P <0. 05). CONCLUSION: Hanfangji Compound can inhibit HSC proliferation, upregulated TTR, ITIH1 and SERPINF2 proteins and mRNA expression, which may be one of mechanisms of anti-hepatic fibrosis of Hanfangji Compound.

Based on network pharmacology and bioinformatics to analyze the mechanism of action of Astragalus membranaceus in the treatment of vitiligo and COVID-19.

Coronavirus disease 2019 (COVID-19) is spreading rapidly around the world. However, the treatment of vitiligo combined with COVID-19 has not been reported. Astragalus membranaceus (AM) has a therapeutic effect on patients with vitiligo and COVID-19. This study aims to discover its possible therapeutic mechanisms and provide potential drug targets. Using the Chinese Medicine System Pharmacological Database (TCMSP), GEO database and Genecards websites and other databases, AM target, vitiligo disease target, and COVID-19 related gene set were established. Then find the crossover genes by taking the intersection. Then use GO, KEGG enrichment analysis, and PPI network to discover its underlying mechanism. Finally, by importing drugs, active ingredients, crossover genes, and enriched signal pathways into Cytoscape software, a "drug-active ingredient-target signal pathway-" network is constructed. TCMSP screened and obtained 33 active ingredients including baicalein (MOL002714), NEOBAICALEIN (MOL002934), Skullcapflavone II (MOL002927), and wogonin (MOL000173), which acted on 448 potential targets. 1166 differentially expressed genes for vitiligo were screened by GEO. CIVID-19 related genes were screened by Genecards. Then by taking the intersection, a total of 10 crossover genes (PTGS2, CDK1, STAT1, BCL2L1, SCARB1, HIF1A, NAE1, PLA2G4A, HSP90AA1, and HSP90B1) were obtained. KEGG analysis found that it was mainly enriched in signaling pathways such as IL-17 signaling pathway, Th17 cell differentiation, Necroptosis, NOD-like receptor signaling pathway. Five core targets (PTGS2, STAT1, BCL2L1, HIF1A, and HSP90AA1) were obtained by analyzing the PPI network. The network of "active ingredients-crossover genes" was constructed by Cytoscape, and the 5 main active ingredients acting on the 5 core crossover genes acacetin, wogonin, baicalein, bis2S)-2-ethylhexyl) benzene-1,2-dicarboxylate and 5,2'-Dihydroxy-6,7,8-trimethoxyflavone. The core crossover genes obtained by PPI and the core crossover genes obtained by the "active ingredient-crossover gene" network are intersected to obtain the three most important core genes (PTGS2, STAT1, HSP90AA1). AM may act on PTGS2, STAT1, HSP90AA1, etc. through active components such as acacetin, wogonin, baicalein, bis2S)-2-ethylhexyl) benzene-1,2-dicarboxylate and 5,2'-Dihydroxy-6,7,8-trimethoxyflavone to activate IL-17 signaling pathway, Th17 cell differentiation, Necroptosis, NOD-like receptor signaling pathway, Kaposi sarcoma-associated herpesvirus infection, and VEGF signaling pathway and other signaling pathways to achieve the effect of treating vitiligo and COVID-19.

MS-Simulator: predicting y-ion intensities for peptides with two charges based on the intensity ratio of neighboring ions.

For the identification of peptides with tandem mass spectrometry (MS/MS), many software tools rely on the comparison between an experimental spectrum and a theoretically predicted spectrum. Consequently, the accurate prediction of the theoretical spectrum from a peptide sequence can potentially improve the peptide identification performance and is an important problem for mass spectrometry based proteomics. In this study a new approach, called MS-Simulator, is presented for predicting the y-ion intensities in the spectrum of a given peptide. The new approach focuses on the accurate prediction of the relative intensity ratio between every two adjacent y-ions. The theoretical spectrum can then be derived from these ratios. The prediction of a ratio is a closed-form equation that involves up to five consecutive amino acids nearby the two y-ions and the two peptide termini. Compared with another existing spectrum prediction tool MassAnalyzer, the new approach not only simplifies the computation, but also improves the prediction accuracy.

Microblog-HAN: A micro-blog rumor detection model based on heterogeneous graph attention network.

Although social media has highly facilitated people's daily communication and dissemination of information, it has unfortunately been an ideal hotbed for the breeding and dissemination of Internet rumors. Therefore, automatically monitoring rumor dissemination in the early stage is of great practical significance. However, the existing detection methods fail to take full advantage of the semantics of the microblog information propagation graph. To address this shortcoming, this study models the information transmission network of a microblog as a heterogeneous graph with a variety of semantic information and then constructs a Microblog-HAN, which is a graph-based rumor detection model, to capture and aggregate the semantic information using attention layers. Specifically, after the initial textual and visual features of posts are extracted, the node-level attention mechanism combines neighbors of the microblog nodes to generate three groups of node embeddings with specific semantics. Moreover, semantic-level attention fuses different semantics to obtain the final node embedding of the microblog, which is then used as a classifier's input. Finally, the classification results of whether the microblog is a rumor or not are obtained. The experimental results on two real-world microblog rumor datasets, Weibo2016 and Weibo2021, demonstrate that the proposed Microblog-HAN can detect microblog rumors with an accuracy of over 92%, demonstrating its superiority over the most existing methods in identifying rumors from the view of the whole information transmission graph.