The importance of allergen immunotherapy (AIT) is multifaceted, encompassing both clinical and quality-of-life improvements and cost-effectiveness in the long term. Key mechanisms of allergen tolerance induced by AIT include changes in memory type allergen-specific T- and B-cell responses towards a regulatory phenotype with decreased Type 2 responses, suppression of allergen-specific IgE and increased IgG1 and IgG4 , decreased mast cell and eosinophil numbers in allergic tissues and increased activation thresholds. The potential of novel patient enrolment strategies for AIT is taking into account recent advances in biomarkers discoveries, molecular allergy diagnostics and mobile health applications contributing to a personalized approach enhancement that can increase AIT efficacy and compliance. Artificial intelligence can help manage and interpret complex and heterogeneous data, including big data from omics and non-omics research, potentially predict disease subtypes, identify biomarkers and monitor patient responses to AIT. Novel AIT preparations, such as synthetic compounds, innovative carrier systems and adjuvants, are also of great promise. Advances in clinical trial models, including adaptive, complex and hybrid designs as well as real-world evidence, allow more flexibility and cost reduction. The analyses of AIT cost-effectiveness show a clear long-term advantage compared to pharmacotherapy. Important research questions, such as defining clinical endpoints, biomarkers of patient selection and efficacy, mechanisms and the modulation of the placebo effect and alternatives to conventional field trials, including allergen exposure chamber studies are still to be elucidated. This review demonstrates that AIT is still in its growth phase and shows immense development prospects.

Hot topics in allergen immunotherapy, 2023: Current status and future perspective.

In addition to the challenge of meeting global demand for food production, there are increasing concerns about food safety and the need to protect consumer health from the negative effects of foodborne allergies. Certain bio‐molecules (usually proteins) present in food can act as allergens that trigger unusual immunological reactions, with potentially life‐threatening consequences. The relentless working lifestyles of the modern era often incorporate poor eating habits that include readymade prepackaged and processed foods, which contain additives such as peanuts, tree nuts, wheat, and soy‐based products, rather than traditional home cooking. Of the predominant allergenic foods (soybean, wheat, fish, peanut, shellfish, tree nuts, eggs, and milk), peanuts (Arachis hypogaea) are the best characterized source of allergens, followed by tree nuts (Juglans regia, Prunus amygdalus, Corylus avellana, Carya illinoinensis, Anacardium occidentale, Pistacia vera, Bertholletia excels), wheat (Triticum aestivum), soybeans (Glycine max), and kidney beans (Phaseolus vulgaris). The prevalence of food allergies has risen significantly in recent years including chance of accidental exposure to such foods. In contrast, the standards of detection, diagnosis, and cure have not kept pace and unfortunately are often suboptimal. In this review, we mainly focus on the prevalence of allergies associated with peanut, tree nuts, wheat, soybean, and kidney bean, highlighting their physiological properties and functions as well as considering research directions for tailoring allergen gene expression. In particular, we discuss how recent advances in molecular breeding, genetic engineering, and genome editing can be used to develop potential low allergen food crops that protect consumer health.

Prospects for developing allergen-depleted food crops.

This chapter explores AI's influence on pharmaceutical sciences, highlighting its enhancement of traditional design methodologies. It explores AI's transformational role in key sectors, including drug discovery, virtual screening, and drug formulation development. AI's ability to efficiently identify potential drug candidates from large chemical libraries and its use of optimization algorithms in the selection of suitable excipients and dosage forms are discussed. The chapter also emphasizes AI's significance in improving pharmaceutical manufacturing processes through parameter refinement, quality outcome prediction, and real-time anomaly detection. The integration of traditional design methods with AI ensures robust, reliable, AI-driven processes that are compliant with regulations. In conclusion, the chapter highlights the potential of AI in pharmaceutical sciences and the importance of its integration with traditional design methods. This approach empowers scientists to innovate, speed up drug development, and improve patient outcomes. 

AI-Driven Decision-Making Applications in Pharmaceutical Sciences

Immuno-correlated dermatological pathologies refer to skin disorders that are closely associated with immune system dysfunction or abnormal immune responses. Advancements in the field of artificial intelligence (AI) have shown promise in enhancing the diagnosis, management, and assessment of immuno-correlated dermatological pathologies. This intersection of dermatology and immunology plays a pivotal role in comprehending and addressing complex skin disorders with immune system involvement. The paper explores the knowledge known so far and the evolution and achievements of AI in diagnosis; discusses segmentation and the classification of medical images; and reviews existing challenges, in immunological-related skin diseases. From our review, the role of AI has emerged, especially in the analysis of images for both diagnostic and severity assessment purposes. Furthermore, the possibility of predicting patients' response to therapies is emerging, in order to create tailored therapies. 

Artificial Intelligence: A Snapshot of Its Application in Chronic Inflammatory and Autoimmune Skin Diseases

Abstract Atopic dermatitis (AD), a complex and heterogeneous chronic inflammatory skin disorder, manifests in a spectrum of clinical subtypes. The application of genomics has elucidated the role of genetic variations in predisposing individuals to AD. Transcriptomics, analyzing gene expression alterations, sheds light on the molecular underpinnings of AD. Proteomics explores the involvement of proteins in AD pathophysiology, while epigenomics examines the impact of environmental factors on gene expression. Lipidomics, which investigates lipid profiles, enhances our understanding of skin barrier functionalities and their perturbations in AD. This review synthesizes insights from these omics approaches, highlighting their collective importance in unraveling the intricate pathogenesis of AD. The review culminates by projecting future trajectories in AD research, particularly the promise of multi‐omics in forging personalized medicine and novel therapeutic interventions. Such an integrated multi‐omics strategy is poised to transform AD comprehension and management, steering towards more precise and efficacious treatment modalities. 

Integrating multi‐omics approaches in deciphering atopic dermatitis pathogenesis and future therapeutic directions

Artificial intelligence (AI) has increasingly been used in healthcare. Given the capacity of AI to handle large data and complex relationships between variables, AI is well suited for applications in healthcare. Recently, AI has been applied to allergy research.In this article, we review how AI technologies have been utilized in basic science and clinical allergy research for asthma, atopic dermatitis, rhinology, adverse reactions to drugs and vaccines, food allergy, anaphylaxis, urticaria, and eosinophilic gastrointestinal disorders. We discuss barriers for AI adoption to improve the care of patients with atopic diseases. These studies demonstrate the utility of applying AI to the field of allergy to help investigators expand their understanding of disease pathogenesis, improve diagnostic accuracy, enable prediction for treatments and outcomes, and for drug discovery. 

/pdf/artificial-intelligence-exploring-the-future-of-innovation-2lzsuyaw.pdf

Artificial Intelligence: Exploring the Future of Innovation in Allergy Immunology

<h3>Introduction</h3> Crizanlizumab is a monoclonal antibody that blocks P-selectin on vascular endothelial cells and platelets. In sickle cell disease (SCD) P-selectin is upregulated promoting adhesion of endovascular cell clusters in vaso-occlusive crisis. Inhibition of P-selectin with crizanlizumab may decrease SCD vaso-occlusive crises. Given the role of P-selectin in neutrophil recruitment, we theorize P-selectin blockade with crizanlizuamb may pose an increased susceptibility to infection. We present a patient who developed fungemia and bacteremia while undergoing treatment with crizanlizumab. <h3>Case Description</h3> An adolescent patient with SCD and chronic pain, but no history of recurrent infections, was admitted for pain crisis. The patient was receiving intermittent crizanlizumab for 15 months, last given 7 weeks prior to admission. While hospitalized the patient developed fever and respiratory failure requiring intubation. Blood cultures grew <i>Candida tropicalis</i> and the patient was treated with micafungin. Over the course of a 2-month hospitalization, subsequent blood cultures grew multiple organisms including <i>Klebsiella pneumoniae, Lactobacillus, Enterococcus faecalis, Staphylococcus epidermidis, Staphylococcus warneri,</i> and <i>Candida glabrata</i>. The patient improved with antimicrobials and was discharged. <h3>Discussion</h3> <i>Candida tropicalis</i> fungemia is most common in patients with risk factors such as neutropenia, indwelling central lines, or malignancy, and not commonly associated with SCD thus representing an unusual infection for this patient without risk factors. Given a non-revealing and thorough immunological evaluation, we hypothesize that crizanlizumab may have led to a functional neutrophil defect, predisposing the patient to fungemia and bacteremia. Since stopping crizanlizumab, this patient has had pain-crises but has not suffered ongoing infectious complications. 

Candida tropicalis fungemia in an adolescent patient with sickle cell disease on crizanlizumab


 Introduction : Pediatric immune thrombocytopenia (ITP) is thought to develop when a triggering event inappropriately activates an autoimmune anti-platelet response in the context of predisposing genetic factors. Inborn errors of immunity are increasingly being identified in cases of chronic, refractory autoimmune cytopenias. We sought to identify genetic variants associated with predisposition to 1) primary or secondary pediatric ITP of any disease duration versus healthy controls and 2) chronic ITP (cITP) versus disease that spontaneously resolves in < 1 year (sr-ITP).
 Methods : DNA and clinical data were derived from 8 sites from the Pediatric ITP Consortium of North America's (ICON) biorepository. Samples were genotyped using the Illumina Global Screening Array BeadChip. Genotypes were imputed using the Michigan Imputation Server HRC reference panel. Genetic variants that passed standard quality metrics and had a MAF ≥1% were retained. Control samples (n=8,372) were obtained from the National Longitudinal Study of Adolescent to Adult Health (Add Health) cohort. Logistic regression models were used to estimate adjusted odds ratios (aORs) comparing (1) ITP and control cohorts and (2) cITP and sr-ITP cohorts. Models assumed additive allelic effects and accounted for the top 3 principal components. Genome-wide significance was defined as P <5 × 10 -8 and suggestive of genome-wide significance, P <1 x 10 -5.
 Results : Six-hundred ten unique patient samples were genotyped. Nineteen (3.1%) did not pass quality control, leaving 591 for analysis. This cohort included 307 (52.0%) cITP patients, 209 (35.4%) sr-ITP patients, and 75 (12.7%) individuals without complete follow-up data to allow for classification of cITP or sr-ITP. The ITP cohort was 50.1% male, 50.1% non-Hispanic (NH) white, 29.4% Hispanic, 6.1% NH Black, 3.1% NH Asian, and 11.3% Other/Unknown.
 Compared with healthy controls, we identified 6 loci associated with ITP at genome-wide significance (Figure 1). Located within the intronic region of SLC24A4 rs75650997 was associated with an increased risk of ITP compared with controls (aOR: 2.38, P=3.9x10 -8). An intronic variant, rs2165798, in NAV2 was inversely associated with ITP (aOR: 0.52, P=3.2x10 -11). A variant in NKD1 rs4785216, was inversely associated with ITP (aOR: 0.43, P=8.86x10 -15).Another intergenic variant, rs4785426, in close proximity to NKD1 was also inversely associated with ITP (aOR: 0.48, P=1.84x10 -16) . An additional 20 variants met suggestive of genome-wide significance. When comparing sr-ITP and cITP patients, no SNVs (single nucleotide variant) reached genome-wide significance, but one variant, rs117609649, in ABCC4 met suggestive of genome-wide significance (aOR: 0.26, P=4.49x10 -7).
 Discussion : This is the largest, unbiased genetic study of pediatric ITP patients. The analysis comparing ITP versus healthy controls identified 20 suggestive SNVs and 6 which met genome-wide significance. Several of the top SNVs identified in this study affect Wnt/β-catenin signaling. Wnt-signaling impacts the development and regulation of immune cell populations including dendritic cells, macrophages, NK cells, B cells, and T cells. NAV2 activates Wnt/β-catenin signaling. NAV2 variants have been implicated in autoimmune conditions including Celiac disease and rheumatoid arthritis. NKD1 inhibits the canonical Wnt/β-catenin signaling pathway. The cumulative impact of these variants on Wnt activity in ITP should be evaluated in the future.
 No genetic variants met genome-wide significance in a comparison of sr-ITP and cITP patients. Collectively, these findings suggest there may be genetic variants implicated in ITP risk, but those genetic features are not specific to sr-ITP or cITP. A focused analysis of 632 genes that cause inborn errors of immunity (IEI) is ongoing. This includes gene burden testing and analysis of pathogenic variants within this gene subset. Variants in IEI genes will also be evaluated in a sub-population of patients with Evans syndrome.
 Conclusion : ITP is highly heterogenous in its presentation, disease course, and response to therapy. Mirroring its clinical behavior, the genetic contribution to ITP development is complex. This study identified potential SNVs associated with ITP, but not specific to sr-ITP or cITP. Variants in genes that affect the canonical Wnt-signaling pathway may play a role in ITP risk.

Genetic Variants in Canonical Wnt Signaling Pathway Associated with Pediatric ITP

The patient is a 13-year-old previously healthy male who presented with 10 days of abdominal pain, generalized pruritus, nausea, one episode of nonbilious, nonbloody emesis, and jaundice of unknown etiology. He was initially evaluated at an urgent care clinic with a chief complaint of severe abdominal pain. He denied night sweats, cough, dyspnea, chest pain, diarrhea, constipation, weight loss, or enlarged lymph nodes. He did not report taking any medications, herbal products, or supplements, and he had no known allergies or family history of gastrointestinal or liver disorders. On examination, he was an overweight (body mass index: 25.19 kg/m2), ill-appearing teenage boy, with scleral icterus, generalized jaundice, and right upper quadrant tenderness. Initial labs were significant for elevated transaminases and total bilirubin; as a result, he was referred to the emergency department. At the local hospital, documentation indicated that the mother again denied any significant medication, herbal products, or supplement use. His significant lab findings at presentation are detailed in Table 1. His hepatitis A, B, and C serologies were negative, and his white blood cell count, lipase, and acetaminophen level were within normal limits. A right upper quadrant ultrasound showed increased echogenicity about the bile ducts and gallbladder, but no evidence of obstruction or gallstones. The patient was transferred to our institution for pediatric hepatology care and further diagnostic workup. He remained inpatient for an additional 2 weeks due to persistently elevated transaminases and conjugated bilirubin (Table 1), for which he received ursodeoxycholic acid and vitamin D and K supplementation. Clinically, he showed persistent jaundice and scleral icterus throughout his admission, while his abdominal pain resolved in the first week. A liver biopsy on the fifth day of admission showed mixed portal and lobular inflammation with diffuse cholestasis and multifocal cell loss. A comprehensive infectious, autoimmune, and metabolic workup was performed, but no underlying cause was elucidated. Idiopathic, drug-induced, and rare genetic causes of liver injury remained on the differential. The patient was started on 5 days of intravenous methylprednisolone followed by a prolonged prednisone taper.

The DILI's in the Details: A 13-Year-Old With Abdominal Pain and Jaundice.

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

D. MacMath

Author Tools

Chat about Author

Papers

Artificial Intelligence: Exploring the Future of Innovation in Allergy Immunology

Candida tropicalis fungemia in an adolescent patient with sickle cell disease on crizanlizumab

Genetic Variants in Canonical Wnt Signaling Pathway Associated with Pediatric ITP

The DILI's in the Details: A 13-Year-Old With Abdominal Pain and Jaundice.