Background: Systemic juvenile idiopathic arthritis (systemic JIA) is a severe disease with both systemic and joint inflammation. This study aims to identify predictors of disease evolution within the systemic JIA population enrolled in the Juvenile Inflammatory Rheumatism cohort (JIRcohort).
Methods: Observational patient cohort study with 201 recruited children from 4 countries (3 European, 1 North Africa) from 2005 until 2019, using retrospectively (2005-2015) and prospectively (2015-2019) routine care collected data.
Results: Sixty-five patients with complete follow-up data for 24 months after first diagnosis were classified as monophasic (n = 23), polyphasic (n = 6) or persistent group (n = 36) corresponding to their evolution (unique flare, recurrent flares, or persistent disease activity respectively). The patients of the persistent group were more likely to have an earlier disease onset, before the age of 6 (OR 2.57, 95%-CI 0.70-9.46), persistence of arthritis at 12-months post-diagnosis (OR 4.45, 95%-CI 0.58-34.20) and higher use of synthetic DMARD (sDMARD, OR 5.28, 95%-CI 1.39-20.01). Other variables like global assessment by physician and by patient and C Reactive Protein levels at 12-months post-diagnosis were assessed but without any predictive value after adjusting for confounding factors.
Conclusions: Our results suggest that the earlier disease onset, the persistence of arthritis throughout the first year of disease evolution and the need of sDMARD might predict a persistent disease course.
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http://dx.doi.org/10.1186/s12969-023-00886-9 | DOI Listing |
Curr Microbiol
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Unit of Microbiology and Immunology, ICMR-Vector Control Research Centre, Medical Complex, Indira Nagar, Puducherry, 605006, India.
In recent years, there has been a global threat from emerging vector-borne diseases (VBD), despite the implementation of several vector control programs. Considering the benefits of bacterial pesticides, the present study aimed to isolate potential mosquitocidal bacteria from the various soil types collected from the Kasaragod (12.5°N, 75.
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University of California Irvine, Irvine, California, USA.
Despite the study of BCR::ABL1-positive and -negative myeloproliferative neoplasms (MPNs) providing seminal insights into cancer biology, tumor evolution and precision oncology over the past half century, significant challenges remain. MPNs are clonal hematopoietic stem cell-derived neoplasms with heterogenous clinical phenotypes and a clonal architecture which impacts the often-complex underlying genetics and microenvironment. The major driving molecular abnormalities have been well characterized, but debate on their role as disease-initiating molecular lesions continues.
View Article and Find Full Text PDFVirulence
December 2025
Manchester Fungal Infection Group (MFIG), Division of Evolution, Infection, and Genomics, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
Sulfur metabolism is an essential aspect of fungal physiology and pathogenicity. Fungal sulfur metabolism comprises anabolic and catabolic routes that are not well conserved in mammals, therefore is considered a promising source of prospective novel antifungal targets. To gain insight into sulfur-related metabolism during infection, we used a NanoString custom nCounter-TagSet and compared the expression of 68 key metabolic genes in different murine models of invasive pulmonary aspergillosis, at 3 time-points, and under a variety of conditions.
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January 2025
Department of Physiology, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Background And Aims: Oncogenic KRAS mutations are present in approximately 90% of pancreatic ductal adenocarcinoma (PDAC). However, Kras mutation alone is insufficient to transform precancerous cells into metastatic PDAC. This study investigates how KRAS-mutated epithelial cells acquire the capacity to escape senescence or even immune clearance, thereby progressing to advanced PDAC.
View Article and Find Full Text PDFNat Med
January 2025
Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands.
Genetic diagnosis of rare diseases requires accurate identification and interpretation of genomic variants. Clinical and molecular scientists from 37 expert centers across Europe created the Solve-Rare Diseases Consortium (Solve-RD) resource, encompassing clinical, pedigree and genomic rare-disease data (94.5% exomes, 5.
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