Verification of optimal conditions for the scattering correction of 123I-FP-CIT SPECT on a single-photon emission tomography system with a two-detector whole-body cadmium-zinc-telluride semiconductor detector.

To identify the optimal scattering correction for 123I-FP-CIT SPECT (DAT-SPECT) using a two-detector whole-body cadmium-zinc-telluride semiconductor detector (C-SPECT) system with a medium-energy high-resolution sensitivity (MEHRS) collimator. The C-SPECT system with the MEHRS collimator assessed image quality and quantification using a striated phantom. Different reconstruction methods and scattering correction settings were compared, including filtered back projection (FBP) and ordered subset expectation maximization (OSEM). Higher %contrast and %CV values were observed > 10% subwindow (SW) for all conditions, with no significant differences between images without scattering correction and those < 7% SW. The FBP images show a greater increase in %CV > 10% SW than the OSEM images. The specific binding ratio in the radioactivity ratio of 8:1 was higher than the true value under all conditions. The C-SPECT system with an MEHRS collimator provided accurate scattering suppression and enabled high-quality imaging for DAT-SPECT. Careful setting of the scattering correction is essential for total count accuracy.

Expression of S100A8 protein on B cells is associated with disease activity in patients with systemic lupus erythematosus.

BACKGROUND: Systemic lupus erythematosus (SLE) is an intractable disease characterized by autoantibody production and autoreactive B and T cell proliferation. Although several studies have revealed multiple genetic and environmental associations, the underlying mechanisms remain unknown. METHODS: We performed proteomics and transcriptomics using liquid chromatography-mass spectrometry and DNA microarray, using peripheral blood B cells from patients with SLE, and healthy controls (HC). We explored molecules associated with the pathophysiology of SLE by flow cytometry and B cell stimulation assay. RESULTS: We identified for the first time that expression of both S100A8 protein and mRNA were markedly upregulated in SLE B cells. The results obtained using flow cytometry showed that S100A8 was highly expressed on the surface of B cells of patients with active SLE (MFI; HC 102.5 ± 5.97, stable SLE 111.4 ± 12.87, active SLE 586.9 ± 142.9), and S100A8 on the cell surface was decreased after treatment (MFI; pre-treat 1094.5 ± 355.38, post-treat 492.25 ± 247.39); therefore, it is suggested that S100A8 may be a marker for disease activity. The mRNA expression of S100A8 was particularly upregulated in memory B cells of SLE (56.68 fold higher than HC), suggesting that S100A8 may be mainly secreted by memory B cells in the pathogenesis of SLE. CONCLUSIONS: Our results imply that the S100A8 proteins secreted from memory B cells may stimulate granulocytes and monocytes through pattern recognition receptors, activate the innate immune system, and are involved in the pathogenesis of SLE.

Dynamics of Type I and Type II Interferon Signature Determines Responsiveness to Anti-TNF Therapy in Rheumatoid Arthritis.

The factors influencing long-term responses to a tumor necrosis factor inhibitor (TNFi) in rheumatoid arthritis (RA) patients currently remain unknown. Therefore, we herein conducted a multi-omics analysis of TNFi responses in a Japanese RA cohort. Blood samples were collected from 27 biological disease-modifying antirheumatic drug (DMARD)-naive RA patients at the initiation of and after three months of treatment with TNFi. Treatment responses were evaluated at one year. Differences in gene expression levels in peripheral blood mononuclear cells (PBMCs), plasma protein levels, drug concentrations, and the presence/absence of anti-drug antibodies were investigated, and a cell phenotypic analysis of PBMCs was performed using flow cytometry. After one year of treatment, thirteen patients achieved clinical remission (responders), while the others did not or switched to other biologics (non-responders). Differentially expressed genes related to treatment responses were enriched for the interferon (IFN) pathway. The expression of type I IFN signaling-related genes was higher in non-responders than in responders before and after treatment (P = 0.03, 0.005, respectively). The expression of type II IFN signaling-related genes did not significantly differ before treatment; however, it increased in non-responders and decreased in responders, with a significant difference being observed after three months of treatment (P = 1.2×10-3). The total number of lymphocytes and C-X-C Motif Chemokine Ligand 10 (CXCL10) protein levels were associated with the type I IFN signature (P = 6.7×10-7, 6.4×10-3, respectively). Hepatocyte growth factor (HGF) protein levels before treatment predicted fold increases in type II IFN (P = 0.03). These IFN signature-related indices (the number of lymphocytes, CXCL10, and HGF) significantly differed between responders and non-responders (P = 0.01, 0.01, and 0.04, respectively). A single-cell analysis revealed that the type I IFN signature was more highly enriched in monocytes than in other cell types. A deconvolution analysis of bulk-RNA sequence data identified CD4+ and CD8+ T cells as the main sources of the type II IFN signature in non-responders. Collectively, the present results demonstrated that the dynamics of the type I and II IFN pathways affected long-term responses to TNFi, providing information on its biological background and potential for clinical applications.