Elevated sCD30 levels were generally associated with poor prognosis in chronic HIV infection prior to the era of highly active antiretroviral therapy (HAART). Little information is available on sCD30 and HIV-1 viremia. In this study, the association between sCD30 and HIV-1 viremia was investigated in HIV-infected patients who underwent HAART. sCD30 was measured in 276 patients prior (T0) and 6 months after HAART (T6). Standard survival analyses were used to evaluate the prognostic value of sCD30 and sCD30 change from baseline to predict the virological response to HAART. Higher levels (>30 U/ml) of sCD30 prior to HAART were associated with relatively higher viremia (P = 0.0001) and tended to be associated with a lower chance of achieving virological success (P = 0.13). The median T6 sCD30 level in patients who concomitantly had viremia >500 copies/ml was higher than the median sCD30 level of those with viremia =500 copies/ml (P = 0.002). Conversely, within the patients who achieved viral suppression on HAART, those who had concomitantly a larger reduction in sCD30 subsequently experienced a higher rate of virological failure (P = 0.04). A strong, but complex, link exists between sCD30 levels and HIV viremia in the era of HAART. The change in sCD30 levels from pre-therapy to the date of first viral suppression could be used to identify patients who are more likely to experience later virological rebound among those who achieve initially virological success.
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http://dx.doi.org/10.1002/jmv.20733 | DOI Listing |
Front Immunol
October 2024
Department of Infectious Diseases (Internal Medicine II), Faculty of Medicine, Grigore T. Popa University of Medicine and Pharmacy, Iasi, Romania.
Introduction: Over the past four years, the COVID-19 pandemic has posed serious global health challenges. The severe form of disease and death resulted from the failure of immune regulatory mechanisms, closely highlighted by the dual proinflammatory cytokine and soluble immune checkpoint (sICP) storm. Identifying the individual factors impacting on disease severity, evolution and outcome, as well as any additional interconnections, have become of high scientific interest.
View Article and Find Full Text PDFExpert Rev Clin Immunol
December 2024
Department of Pediatrics (Allergy & Immunology Unit), Postgraduate Institute of Medical Education and Research, PGIMER, Chandigarh, India.
Neurol Neuroimmunol Neuroinflamm
September 2024
From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA.
Background And Objectives: To evaluate CSF inflammatory markers with accumulation of cortical damage as well as disease activity in patients with early relapsing-remitting MS (RRMS).
Methods: CSF levels of osteopontin (OPN) and 66 inflammatory markers were assessed using an immune-assay multiplex technique in 107 patients with RRMS (82 F/25 M, mean age 35.7 ± 11.
Front Med (Lausanne)
February 2024
Department of Emergency Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan.
In this study, we analyzed a relatively large subset of proteins, including 109 kinds of blood-circulating cytokines, and precisely described a cytokine storm in the expression level and the range of fluctuations during hospitalization for COVID-19. Of the proteins analyzed in COVID-19, approximately 70% were detected with Bonferroni-corrected significant differences in comparison with disease severity, clinical outcome, long-term hospitalization, and disease progression and recovery. Specifically, IP-10, sTNF-R1, sTNF-R2, sCD30, sCD163, HGF, SCYB16, IL-16, MIG, SDF-1, and fractalkine were found to be major components of the COVID-19 cytokine storm.
View Article and Find Full Text PDFData Brief
February 2024
Internet of Things (IoT) Lab, Department of Engineering and Architecture, University of Parma, Parma 43124, Italy.
The experimental dataset (organized in a semicolon-separated text format) is composed by air quality records collected over a 1-year period (October 2022-October 2023) in an indoor travelers' transit area in the Brindisi airport, Italy. In detail, the dataset consists of three CSV files (ranging from 7M records to 11M records) resulting from the on-field data collection performed by three prototypical (IoT) sensing nodes, designed and implemented at the IoTLab of the University of Parma, Italy, featuring a Raspberry Pi 4 (as processing unit) which three low-cost commercial sensors (namely: Adafruit MiCS5524, Sensirion SCD30, Sensirion SPS30) are connected to. The sensors sample the air in the monitored static indoor environment every 2 s.
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