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关键词： Psoriasis   Secukinumab   IL-17 a inhibition   Hypothalamic pituitary adrenal axis  

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关键词： Batatasin III   Enteric nervous system   Microbiota–gut–brain axis   NLRP3   Slow transit constipation  

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关键词： BD   bipolar disorder   M.I.N.I   Mini-International Neuropsychiatric Interview   HAMD-24   Hamilton Depression Rating Scale-24 items   YMRS   Young Mania Rating Scale   MADRS   Montgomery-Åsberg Depression Rating Scale   BSSI   Beck Scale for Suicide Ideation   ORs   odd ratio   CI   confidence interval   IL   interleukin   TNF   tumor necrosis factor   IFN   interferon   FT4   free thyroxine 4   FT3   free thyroxine 3   TT4   total thyroxine 4   TT3   total thyroxine 3   TSH   thyroid stimulating hormone   aTPO   anti-thyroid peroxidase antibody   aTG   anti-thyroglobulin   CRP   C-reaction protein   DSM-5   the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition   ICD-11   the International Classification of Diseases, 11th Revision   PHQ-9   Patient Health Questionnaire-9 items   GAD-7   Generalized Anxiety Disorder-7 items   HAMA   Hamilton Anxiety Rating Scale   SI-C   current suicidal ideation   SI-W   the severity of suicidal thoughts at their worst point   NK cell   natural killer cell   BMI   body mass index   FDR   false discovery rate   Bipolar disorder   Suicide risk   Machine learning   Thyroid function   Biomarkers  

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关键词： Neuropathic pain   Red nucleus   IL-15   Signaling pathway   Inflammatory factors  

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关键词： Breast cancer   P18   interleukin 24   fusion protein   molecular docking   MD simulations  

摘要： Breast cancer is the second leading cause of cancer-related deaths throughout the world, and it remains one of the significant health challenges due to treatment limitations such as drug resistance and adverse side effects. Instead of developing novel treatment approaches, including radiotherapy and chemotherapy, their efficacy is trapped by non-specific toxicity and resistance. This study includes designing a novel chimeric protein combining Interleukin-24 (IL-24) and p18 peptides that are well-being to exhibit significant anticancer properties. The fusion protein, IL-24-P18, was developed to enhance specificity and minimize off-target effects in breast cancer treatment. We used silico techniques to predict this novel fusion protein construct's structural, functional and therapeutic properties. The P18 peptide was fused to the N-terminal of IL-24 using an AEAAAKEAAAKA linker. The fusion protein was found to be nontoxic, non-allergenic and non-antigenic. The fusion protein was hydrophilic with a neutral charge, exhibiting soluble expression in E. coli and stable at varying conditions. Secondary and tertiary structure predictions showed well-defined alpha-helices and a stable 3D conformation. Molecular docking and interaction analysis further confirmed strong binding affinities with a score of -847.5 Kcal/mol between IL-24-P18 and breast cancer receptor proteins, indicating the potential for selective targeting. Moreover, the MD simulation results revealed the interaction stability of the designed fusion protein and receptor. The overall results of this Insilco study showed that IL-24-P18 fusion is a prospective novel candidate against breast cancer that has the potential to inhibit breast cancer with higher accuracy and fewer side effects as compared to already available treatments. Further, in vitro and clinical studies are required to validate its clinical applicability.

关键词： Antibody   Bioinformatics   Biophysics   Immunopeptidomics   Information theory   MHC   Machine learning   Mass spectrometry   Peptide   TCR  

摘要： Immunopeptidomics is a growing subfield of proteomics that has the potential to shed new light on a long-neglected aspect of adaptive immunology: a comprehensive understanding of the peptides presented by major histocompatibility complexes (MHC) to T cells. As the field of immunopeptidomics continues to grow and mature, a parallel expansion in the methods for extracting quantitative features of these peptides is necessary. Currently, massive experimental efforts to isolate a given immunopeptidome are summarized in tables and pie charts or, worse, entirely thrown out in favor of singular peptides of interest. Ideally, an unbiased approach would dive deeper into these large proteomic datasets, identifying sequence-level biochemical signatures inherent to each individual dataset and the given immunological niche. This chapter will outline the steps for a powerful approach to such analysis, utilizing the Automated Immune Molecule Separator (AIMS) software for the characterization of immunopeptidomic datasets. AIMS is a flexible tool for the identification of biophysical signatures in peptidomic datasets, the elucidation of nuanced differences in repertoires collected across tissues or experimental conditions, and the generation of machine learning models for future applications to classification problems. In learning to use AIMS, readers of this chapter will receive a broad introduction to the field of protein bioinformatics and its utility in the analysis of immunopeptidomic datasets and other large-scale immune repertoire datasets.

关键词： Epitope discovery   HLA   Ligandome   MHC   Mass spectrometry   Peptides   Peptidome   Single-chain dimer  

摘要： The current "gold standard" for the identification of MHC-restricted peptides is conventional immunoprecipitation/mass spectrometry (MS); however, this approach requires a relatively large amount of sample, complex purification procedures, and computational analyses to assign peptides to individual alleles. Here, we provide instructions for the expression, purification, and MS identification of MHC-presented peptides of human and non-human, classical and non-classical, class I and class II proteins using a readily expressible, soluble, and easily purifiable single-chain dimer construct. This procedure enables the identification of up to tens of thousands of allele-specific peptides per run for peptidomics, ligandomics, therapeutic targeting, and motif analyses. Also included are instructions for construct design, streamlined lentiviral transfection and transduction, and computational methods for high-throughput processing of MS results, yielding high confidence peptide lists, motifs, and multiple analytics.

关键词： Cancer   IFNAR   Immunotherapy   Me-ALA   Tumor immunology  

摘要： This chapter outlines a detailed protocol for employing photodynamic therapy (PDT) to induce immunogenic cell death (ICD) in melanoma cells, specifically targeting the type-I-interferons (IFN-1) signaling pathway. Recent studies have highlighted the role of IFN-1 in the immune response against cancer, acting as novel damage-associated molecular patterns (DAMPs) that bridge innate and adaptive immunity. Our approach utilizes methyl-aminolevulinate (Me-ALA) to induce the production of endogenous photosensitizer protoporphyrin IX (PpIX), which preferentially accumulates in the endoplasmic reticulum (ER). Activation of PpIX through visible light irradiation triggers oxidative stress-induced apoptotic cell death. This chapter provides a step-by-step guide to replicate these conditions, which have been shown to significantly upregulate IFN-α/β transcripts in B16-OVA melanoma cells, leading to enhanced expression of GMP-AMP synthase (cGAS) and interferon-stimulated genes (ISGs) like CXCL10, MX1, and ISG15. We further discuss the consequential IFN-1-dependent-phenotypic maturation of monocyte-derived dendritic cells (DCs), evidenced by increased expression of co-stimulatory molecules such as CD80 and MHC-II and enhanced tumor-directed chemotaxis. By detailing the protocol for this novel application of PDT, this chapter aims to facilitate its integration into immunotherapy regimens, providing a comprehensive toolkit for researchers and clinicians aiming to harness the antitumor potential of the IFN-1 pathway.

关键词： Antibody   Antigen   Cancer   Epitope   Immunoproteomics   Infectious disease   MHC   Mass spectrometry  

摘要： The dynamic landscape of the adaptive immune response is shaped by peptides presented on the surface of immune cells, originating from viral or microbial pathogens or cancerous cells. The study of immune biomarkers and antigens has a long history, with classical techniques such as agglutination, enzyme-linked immunosorbent assays (ELISA), and western blotting being widely used to investigate immune responses to vaccination and disease. However, these traditional methods often face limitations in protein and peptide identification, creating bottlenecks in antigen discovery. Recent advancements in genomics and proteomics have significantly accelerated the development of novel analytical approaches. Immunoproteomics has emerged as a rapidly evolving field that integrates a diverse set of methodologies aimed at identifying and quantifying antigenic peptides and proteins. These approaches include gel-based and array-based techniques, mass spectrometry, DNA-based methods, and in silico modeling. By leveraging these tools, immunoproteomics is providing deeper insights into disease mechanisms, immune system dynamics, biomarker discovery, and vaccine development. This review offers an introductory overview of immunoproteomics and related technologies that help define the complete repertoire of protein antigens recognized by the immune system during disease, advancing both diagnostic and therapeutic applications.

关键词： Absolute quantification (TOMAHAQ)   Accurate-mass   Affinity purification   Cancer immunology   High-resolution   Immunopeptidomics   Major histocompatibility complex class I (MHC-I)   Mass spectrometry   Multiplexed   Neoantigen   Semi-automation   Triggered by offset  

摘要： Advances in several key technologies, including major histocompatibility (MHC) peptidomics, have significantly enhanced our understanding of basic immune-regulatory mechanisms and the identification of T-cell receptor targets for the development of immune-therapeutics. Isolating and accurately quantifying MHC-bound peptides from cells and tissues enables the characterization of dynamic changes in the MHC peptidome due to cellular perturbations. However, the current multistep analytical process is challenging, and improvements in throughput, sensitivity, and reproducibility would enable rapid characterization of multiple conditions in *** this chapter, we describe a robust, sensitive, and quantitative method for enriching peptides derived from MHC-I complexes from a variety of cell lines, including challenging adherent lines such as MC38, in a semiautomated fashion using reusable, dry-storage, customized antibody cartridges. This method allows a researcher, with minimal hands-on time, to perform up to 96 simultaneous enrichments reproducibly in a single day, achieving a quality level comparable to that of a manual *** (Triggered by Offset, Multiplexed, Accurate-mass, High-resolution, and Absolute Quantification) is a targeted mass spectrometry technique that combines sample multiplexing and high sensitivity to characterize neoepitopes displayed on MHC-I by tumor cells and to quantitatively assess the influence of neoantigen expression and induced degradation on neoepitope presentation. This unique combination of robust, semiautomated MHC-I peptide isolation and high-throughput multiplexed-targeted quantitation allows for both the routine analysis of over 4000 unique MHC-I peptides from 250 million cells using nontargeted methods, as well as quantitative sensitivity down to the low amol/μL level using TOMAHAQ targeted MS. The protocol and tips on how to execute are outlined below.