16
views
0
recommends
+1 Recommend
2 collections
    0
    shares

      Call for Papers: Digital Platforms and Artificial Intelligence in Dementia

      Submit here by August 31, 2025

      About Dementia and Geriatric Cognitive Disorders: 2.2 Impact Factor I 4.7 CiteScore I 0.809 Scimago Journal & Country Rank (SJR)

      Call for Papers: Skin Health in Aging Populations

      Submit here by August 31, 2025

      About Skin Pharmacology and Physiology: 2.8 Impact Factor I 5.2 CiteScore I 0.623 Scimago Journal & Country Rank (SJR)

      • Record: found
      • Abstract: found
      • Article: found

      Proteins in the Skin and Blood in Patients with Psoriasis: A Systematic Review of Proteomic Studies

      systematic-review

      Read this article at

      ScienceOpenPublisherPubMed
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background: Proteins play a central role in psoriasis as they are involved in the structural phenotypic changes and inflammation that characterize the disease. This systematic review aimed to assess which proteins have been consistently reported as upregulated or downregulated in the skin and blood from patients with psoriasis. Methods: We included proteomic studies reporting differentially expressed proteins (DEPs) in at least one of four predefined comparisons using a standardized procedure to extract and align data. Network analysis of functional protein associations was made with StringApp in Cytoscape. A protocol for this review was registered in the PROSPERO database (ref:CRD42022363226). Results: We identified and assessed 772 studies published between December 2, 1996, and April 28, 2023, among which 30 studies met the inclusion and data availability criteria for analysis that together reported a sum of 5,314 DEPs. The majority of consistently reported upregulated and downregulated proteins were found in lesional versus non-lesional skin ( n = 313), followed by lesional versus healthy skin ( n = 185), blood from patients with psoriasis versus blood from healthy individuals ( n = 140), and non-lesional versus healthy skin ( n = 1). Network analysis of upregulated proteins revealed different functional clusters with interleukin (IL)-6, IL-8, IL-17A, C-C motif chemokine (CCL) 20, signal transducer and activator of transcription (STAT) 3, and interferon (IFN)-γ along with less well-studied proteins playing central roles. Some of the reported changes are associated with anti-inflammatory effects. Additionally, the proteomic dysregulation also included antimicrobial peptides, alarmins, angiogenic factors, and proteins related to protein synthesis. Conclusion: Our findings generally support current understandings of the pathological mechanisms in psoriasis. Importantly, some consistent findings have not been discussed before and deserve attention in future research.

          Related collections

          Most cited references62

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Rayyan—a web and mobile app for systematic reviews

          Background Synthesis of multiple randomized controlled trials (RCTs) in a systematic review can summarize the effects of individual outcomes and provide numerical answers about the effectiveness of interventions. Filtering of searches is time consuming, and no single method fulfills the principal requirements of speed with accuracy. Automation of systematic reviews is driven by a necessity to expedite the availability of current best evidence for policy and clinical decision-making. We developed Rayyan (http://rayyan.qcri.org), a free web and mobile app, that helps expedite the initial screening of abstracts and titles using a process of semi-automation while incorporating a high level of usability. For the beta testing phase, we used two published Cochrane reviews in which included studies had been selected manually. Their searches, with 1030 records and 273 records, were uploaded to Rayyan. Different features of Rayyan were tested using these two reviews. We also conducted a survey of Rayyan’s users and collected feedback through a built-in feature. Results Pilot testing of Rayyan focused on usability, accuracy against manual methods, and the added value of the prediction feature. The “taster” review (273 records) allowed a quick overview of Rayyan for early comments on usability. The second review (1030 records) required several iterations to identify the previously identified 11 trials. The “suggestions” and “hints,” based on the “prediction model,” appeared as testing progressed beyond five included studies. Post rollout user experiences and a reflexive response by the developers enabled real-time modifications and improvements. The survey respondents reported 40% average time savings when using Rayyan compared to others tools, with 34% of the respondents reporting more than 50% time savings. In addition, around 75% of the respondents mentioned that screening and labeling studies as well as collaborating on reviews to be the two most important features of Rayyan. As of November 2016, Rayyan users exceed 2000 from over 60 countries conducting hundreds of reviews totaling more than 1.6M citations. Feedback from users, obtained mostly through the app web site and a recent survey, has highlighted the ease in exploration of searches, the time saved, and simplicity in sharing and comparing include-exclude decisions. The strongest features of the app, identified and reported in user feedback, were its ability to help in screening and collaboration as well as the time savings it affords to users. Conclusions Rayyan is responsive and intuitive in use with significant potential to lighten the load of reviewers.
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            UniProt: the Universal Protein Knowledgebase in 2023

            (2022)
            The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this publication we describe enhancements made to our data processing pipeline and to our website to adapt to an ever-increasing information content. The number of sequences in UniProtKB has risen to over 227 million and we are working towards including a reference proteome for each taxonomic group. We continue to extract detailed annotations from the literature to update or create reviewed entries, while unreviewed entries are supplemented with annotations provided by automated systems using a variety of machine-learning techniques. In addition, the scientific community continues their contributions of publications and annotations to UniProt entries of their interest. Finally, we describe our new website ( https://www.uniprot.org/ ), designed to enhance our users’ experience and make our data easily accessible to the research community. This interface includes access to AlphaFold structures for more than 85% of all entries as well as improved visualisations for subcellular localisation of proteins.
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest

              Much of the complexity within cells arises from functional and regulatory interactions among proteins. The core of these interactions is increasingly known, but novel interactions continue to be discovered, and the information remains scattered across different database resources, experimental modalities and levels of mechanistic detail. The STRING database ( https://string-db.org/ ) systematically collects and integrates protein–protein interactions—both physical interactions as well as functional associations. The data originate from a number of sources: automated text mining of the scientific literature, computational interaction predictions from co-expression, conserved genomic context, databases of interaction experiments and known complexes/pathways from curated sources. All of these interactions are critically assessed, scored, and subsequently automatically transferred to less well-studied organisms using hierarchical orthology information. The data can be accessed via the website, but also programmatically and via bulk downloads. The most recent developments in STRING (version 12.0) are: (i) it is now possible to create, browse and analyze a full interaction network for any novel genome of interest, by submitting its complement of encoded proteins, (ii) the co-expression channel now uses variational auto-encoders to predict interactions, and it covers two new sources, single-cell RNA-seq and experimental proteomics data and (iii) the confidence in each experimentally derived interaction is now estimated based on the detection method used, and communicated to the user in the web-interface. Furthermore, STRING continues to enhance its facilities for functional enrichment analysis, which are now fully available also for user-submitted genomes.

                Author and article information

                Journal
                DRM
                Dermatology
                10.1159/issn.1018-8665
                Dermatology
                Dermatology
                S. Karger AG
                1018-8665
                1421-9832
                2024
                April 2024
                07 November 2023
                : 240
                : 2
                : 317-328
                Affiliations
                [a ]Department of Dermatology and Allergy, Copenhagen University Hospital, Herlev and Gentofte, Denmark
                [b ]Leo Foundation Skin Immunology Research Center, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
                [c ]Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
                [d ]Novo Nordisk Foundation (NNF) Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
                Author notes
                *Bjørn Kromann, bjoern.kromann.hansen@regionh.dk
                Article
                533981 Dermatology 2024;240:317–328
                10.1159/000533981
                37935159
                08fc749f-01cb-468b-b941-b09c4461deeb
                © 2023 The Author(s). Published by S. Karger AG, Basel
                History
                : 07 June 2023
                : 31 August 2023
                Page count
                Figures: 3, Tables: 2, Pages: 12
                Funding
                This work was supported by grants from the Novo Nordisk Foundation (NNF21OC0066694) and Leo Foundation.
                Categories
                Review Article

                Medicine
                Blood,Systematic review,Psoriasis,Proteomics,Skin
                Medicine
                Blood, Systematic review, Psoriasis, Proteomics, Skin

                Comments

                Comment on this article

                Related Documents Log