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.

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.

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.

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.

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.

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.

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.

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.

An allergenic plant calmodulin from Artemisia pollen primes human DCs leads to Th2 polarization.

Artemisia pollen is the major cause of seasonal allergic respiratory diseases in the northern hemisphere. About 28.57% of Artemisia allergic patients' IgE can recognize ArtCaM, a novel allergenic calmodulin from Artemisia identified in this study. These patients exhibited stronger allergic reactions and a longer duration of allergic symptoms. However, the signaling mechanism that triggers these allergic reactions is not fully understood. In this study, we found that extracellular ArtCaM directly induces the maturation of human dendritic cells (DCs), which is attributed to a series of Ca2+ relevant cascades, including Ca2+/NFAT/CaMKs. ArtCaM alone induces inflammatory response toward Th1, Th17, and Treg. Interestingly, a combination of ArtCaM and anti-ArtCaM IgE led to Th2 polarization. The putative mechanism is that anti-ArtCaM IgE partially blocks the ArtCaM-induced ERK signal, but does not affect Ca2+-dependent cascades. The crosstalk between ERK and Ca2+ signal primes DCs maturation and Th2 polarization. In summary, ArtCaM related to clinical symptoms when combined with anti-ArtCaM IgE, could be a novel allergen to activate DCs and promote Th2 polarization. Such findings provide mechanistic insights into Th2 polarization in allergic sensitization and pave the way for novel preventive and therapeutic strategies for efficient management of such pollen allergic disease.

MGA-YOLO: A lightweight one-stage network for apple leaf disease detection.

Apple leaf diseases seriously damage the yield and quality of apples. Current apple leaf disease diagnosis methods primarily rely on human visual inspection, which often results in low efficiency and insufficient accuracy. Many computer vision algorithms have been proposed to diagnose apple leaf diseases, but most of them are designed to run on high-performance GPUs. This potentially limits their application in the field, in which mobile devices are expected to be used to perform computer vision-based disease diagnosis on the spot. In this paper, we propose a lightweight one-stage network, called the Mobile Ghost Attention YOLO network (MGA-YOLO), which enables real-time diagnosis of apple leaf diseases on mobile devices. We also built a dataset, called the Apple Leaf Disease Object Detection dataset (ALDOD), that contains 8,838 images of healthy and infected apple leaves with complex backgrounds, collected from existing public datasets. In our proposed model, we replaced the ordinary convolution with the Ghost module to significantly reduce the number of parameters and floating point operations (FLOPs) due to cheap operations of the Ghost module. We then constructed the Mobile Inverted Residual Bottleneck Convolution and integrated the Convolutional Block Attention Module (CBAM) into the YOLO network to improve its performance on feature extraction. Finally, an extra prediction head was added to detect extra large objects. We tested our method on the ALDOD testing set. Results showed that our method outperformed other state-of-the-art methods with the highest mAP of 89.3%, the smallest model size of only 10.34 MB and the highest frames per second (FPS) of 84.1 on the GPU server. The proposed model was also tested on a mobile phone, which achieved 12.5 FPS. In addition, by applying image augmentation techniques on the dataset, mAP of our method was further improved to 94.0%. These results suggest that our model can accurately and efficiently detect apple leaf diseases and can be used for real-time detection of apple leaf diseases on mobile devices.

High-Precision Wheat Head Detection Model Based on One-Stage Network and GAN Model.

Counting wheat heads is a time-consuming process in agricultural production, which is currently primarily carried out by humans. Manually identifying wheat heads and statistically analyzing the findings has a rigorous requirement for the workforce and is prone to error. With the advancement of machine vision technology, computer vision detection algorithms have made wheat head detection and counting feasible. To accomplish this traditional labor-intensive task and tackle various tricky matters in wheat images, a high-precision wheat head detection model with strong generalizability was presented based on a one-stage network structure. The model's structure was referred to as that of the YOLO network; meanwhile, several modules were added and adjusted in the backbone network. The one-stage backbone network received an attention module and a feature fusion module, and the Loss function was improved. When compared to various other mainstream object detection networks, our model outperforms them, with a mAP of 0.688. In addition, an iOS-based intelligent wheat head counting mobile app was created, which could calculate the number of wheat heads in images shot in an agricultural environment in less than a second.

Linaclotide for treating patients with irritable bowel syndrome with predominant constipation: a multicentre study of real-world data in China.

Introduction: Linaclotide, a guanylate cyclase C agonist that improves the symptoms of irritable bowel syndrome with predominant constipation (IBS-C), has been recently approved for IBS-C treatment. This study aimed to report real-world data on linaclotide treatment in China. Methods: This was a prospective multicentre study of the effectiveness of linaclotide treatment in patients with IBS-C from 10 primary medical institutions. Changes in defecation, abdominal symptoms, the IBS symptom severity scale (IBS-SSS), IBS quality of life questionnaire (IBS-QOL), Zung Self-Rating Anxiety Scale and Self-Rating Depression Scale in patients were evaluated to determine the drug's clinical efficacy and safety. Results: We enrolled 97 patients (mean age: 52.39 ± 13.99 years), 55 of whom were women (56.7%). In terms of efficacy, the number of the patients' defecation per week and Bristol stool form scale scores significantly increased at week 4 and week 12 compared with the values at the baseline. The baseline average IBS-SSS score was 211.01 ± 81.23. Of the patients, 24 had severe IBS-C, and their IBS-SSS scores at week 4 (51.81 ± 54.42) and week 12 (9.3 ± 30.39) significantly decreased and showed a pronounced improvement. The IBS-QOL total scores at week 4 and week 12 gradually decreased compared with that at the baseline and the QOL significantly improved. Treatment satisfaction rate was 79.3% in week 4 and 100% in week 12, showing a gradually increased satisfaction and significant differences. However, 11 cases (11.3%) had diarrhoea. Conclusion: Linaclotide has proved to be a safe and effective drug to improve IBS-C symptoms and severity.

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.

Effect of RNA Interference Inhibiting the Expression of the FUBP1 Gene on Biological Function of Gastric Cancer Cell Line SGC7901.

BACKGROUND: The research aimed to observe the effect of gene silencing on the proliferation, migration, cell cycle, apoptosis, and other biological functions of human gastric cancer cells with RNA interference inhibiting the expression of the far upstream element-binding protein 1 (FUBP1) in the gastric cancer cell line SGC7901. METHODS: The shRNA lentivirus vector of the target gene FUBP1 was constructed to transfect the gastric cancer cell line SGC7901. The qRT-PCR and western blot assays were used to detect the expression levels of FUBP1 mRNA and protein in the gastric cancer cells. The CCK-8 assay was used to detect the proliferation of gastric cancer cells. The cell scratch assay and the transwell assays were used to detect the migration of gastric cancer cells. Flow cytometry was used to detect cell cycle distribution and apoptosis. RESULTS: The shRNA lentiviral vector of FUBP1 was successfully transfected into the gastric cancer cell line SGC7901, and could effectively reduce the expression of mRNA and protein of FUBP1. The silencing of FUBP1 could inhibit the gastric cancer cell proliferation and affect the distribution of the cell cycle, resulting in S-phase arrest and cell growth inhibition. However, FUBP1 silencing has no significant effect on cell apoptosis and migration. CONCLUSIONS: The expression of FUBP1 can be inhibited specifically and effectively by RNA interference technology, which can significantly affect the biological function of the gastric cancer cell line SGC7901.

The Formation of Melanocyte Apoptotic Bodies in Vitiligo and the Relocation of Vitiligo Autoantigens under Oxidative Stress.

BACKGROUND: Oxidative stress has a vital role in the early stages of vitiligo. Autoantigens released from apoptotic melanocytes (MC) under oxidative stress are involved in the presentation and recognition of antigens. However, the transport of autoantigens to the cell surface and their release to the extracellular environment are still unclear. Apoptotic bodies (ABs) have always been considered as a key source of immunomodulators and autoantigens. Yet, the role of ABs in the immune mechanism of vitiligo is still unknown. PURPOSE: To explore whether MC's autoantigens translocate into ABs during oxidative stress-induced apoptosis and study the molecular mechanisms underlying autoantigen migration and AB formation. METHODS: PIG3V (an immortalized human vitiligo melanocyte cell line) were treated with H2O2, and ABs were separated. Transmission electron microscopy, flow cytometry, Western blot, mass spectrometry, and other methods were used to determine the relocation of specific antigens in PIG3V cells to ABs. After pretreatment with specific inhibitors (Rho kinase (Y-27632), myosin light chain kinase (MLCK, ML-9), pan-caspase (zVAD-FMK), and JNK (SP600125)), the pathway of autoantigen translocation into ABs and the formation of apoptotic bodies were determined. RESULTS: When treated with 0.8 mM H2O2, ABs were released from these cells. Autoantigens such as tyrosinase-related protein 1 (TYRP-1) and cleavage nuclear membrane antigen Lamin A/C (Asp230) were concentrated in ABs. The expression of autoantigens and the formation of ABs increased in a time- and dose-dependent manner after treatment with H2O2, while the application of specific inhibitors inhibited the formation of apoptotic bodies, i.e., the expression of antigens. CONCLUSION: Vitiligo autoantigens translocate into ABs in the process of apoptosis induced by oxidative stress. The cytoskeletal protein activation pathway and the JNK-related apoptosis pathway are involved in the transport of autoantigens and the formation of ABs. ABs may be the key bridge between MC cell apoptosis and cellular immunity.

HepParser: An Intelligent Software Program for Deciphering Low-Molecular-Weight Heparin Based on Mass Spectrometry.

Low-molecular-weight heparins (LMWHs) are considered to be the most successful carbohydrate-based drugs because of their wide use as anticoagulants in clinics. The efficacy of anticoagulants made by LMWHs mainly depends on the components and structures of LMWHs. Therefore, deciphering the components and identifying the structures of LMWHs are critical to developing high-efficiency anticoagulants. However, most LMWHs are mixtures of linear polysaccharides which are comprised of several disaccharide repeating units with high similarity, making it extremely challenging to separate and decipher each component in LMWHs. Here, we present a new algorithm named hepParser to decipher the main components of LMWHs automatically and precisely based on the liquid chromatography/mass spectrometry (LC/MS) data. When tested on the general LMWH using hepParser, profiling of the oligosaccharides with different degrees of polymerization (dp's) was completed with high accuracy within 1 minute. When compared with the results of GlycReSoft on heparan sulfate samples, hepParser achieved more comprehensive and reasonable results automatically.

Multistage mass spectrometry with intelligent precursor selection for N-glycan branching pattern analysis.

Biological functions of N-glycans are frequently related to their unique branching patterns. Multistage mass spectrometry (MSn) has become the primary method for glycan structural analysis. However, selection of the best fragment as the precursor for the next round of product-ion scanning is important but difficult. We have previously proposed the concept and designed the approach of glycan intelligent precursor selection (GIPS) to guide MSn experiments, but its use in N-glycans is not straightforward as some N-glycans are of high similarity in branching patterns. In the present work we introduced new elements to GIPS to improve its performance in N-glycan branching pattern analysis. These include a hypothesis and significance test, based on Bayes factor, and DPbiased as a new precursor selection strategy. The improved GIPS was successfully applied to identification of individual N-glycans, and incorporated into MALDI-MS N-glycan profiling for assignment of N-glycans obtained from glycoproteins and complex human serum.