ABSTRACT
This article describes the methodology and the possibilities of collecting operation data in a mobile network provider. First, the architecture and the principles used in the system are described. The precision analysis of the population commuting in the region and during the pandemic and nonpandemic times. Moreover, several ideas about further utilization of the data will be formulated and described. Finally, a graph-based approach that describes the creation of the community structure between the people and the means of its analysis.
ABSTRACT
Serum protein fingerprints associated with MGUS and MM and their changes in MM after autologous stem cell transplantation (MM-ASCT, day 100) remain unexplored. Using highly-sensitive Proximity Extension ImmunoAssay on 92 cancer biomarkers (Proseek Multiplex, Olink), enhanced serum levels of Adrenomedullin (ADM, Pcorr= .0004), Growth differentiation factor 15 (GDF15, Pcorr= .003), and soluble Major histocompatibility complex class I-related chain A (sMICA, Pcorr= .023), all prosurvival and chemoprotective factors for myeloma cells, were detected in MM comparing to MGUS. Comparison of MGUS and healthy subjects revealed elevation of angiogenic and antia-poptotic midkine (Pcorr= .0007) and downregulation of Transforming growth factor beta 1 (TGFB1, Pcorr= .005) in MGUS. Importantly, altered serum pattern was associated with MM-ASCT compared to paired MM at the diagnosis as well as to healthy controls, namely by upregulated B-Cell Activating Factor (sBAFF) (Pcorr< .006) and sustained elevation of other pro-tumorigenic factors. In conclusion, the serum fingerprints of MM and MM-ASCT were characteristic by elevated levels of prosurvival and chemoprotective factors for myeloma cells.
ABSTRACT
BACKGROUND: Systemic lupus erythematosus (SLE) is a remarkably heterogeneous autoimmune disease. Despite tremendous efforts, our knowledge of serum protein patterns in severe SLE phenotypes is still limited. We investigated the serum protein pattern of SLE, with special emphasis on irreversible organ damage and active lupus nephritis (LN) as assessed by renal Systemic Lupus Erythematosus Disease Activity Index. METHODS: We used proximity extension immunoassay (PEA, Proseek Multiplex, Olink) to assess the serum levels of ninety-two inflammation-related proteins in Czech patients with SLE (n = 75) and age-matched healthy control subjects (n = 23). Subgroup analysis was carried out on the basis of organ damage (with/without, 42/33) and biopsy-proven LN (with/without, 27/48; active LN, n = 13; inactive LN, n = 14). RESULTS: Of thirty deregulated proteins between SLE and the healthy controls (Pcorr < 0.05), the top upregulated proteins in SLE were sirtuin 2, interleukin 18 (IL18), and caspase 8 (Pcorr < 0.0006). Of these, sirtuin 2 and caspase 8 had not yet been reported with SLE. Elevated levels of IL8, CCL2/MCP1, CCL11, and MMP10 (Pcorr < 0.05) were detected in patients with organ damage for which the serum levels of CCL11 and MMP10 were particularly informative in organ damage prediction. Comparing patients based on LN, elevated levels of CSF1, sIL15RA, sCD40, sCX3CL1, caspase 8, sIL18R1, bNGF, and GDNF (Pcorr < 0.05) were detected in active LN. Except GDNF, all LN-associated markers showed usefulness in prediction of active renal disease. CONCLUSIONS: This highly sensitive PEA analysis identified the serum pattern of SLE, organ damage, and active LN, with many novel candidate proteins detected. Their exact role and suitability as biomarkers in SLE deserve further investigation.
