Sentence examples for flare samples from inspiring English sources

The six-protein biomarker panel classified the SJIA flare samples with 92% positive agreement and the non-flare samples with 71.4% agreement (Fig.  4c, left panel) (P = 7.9 × 10−5).

Overall, the 17-urine-peptide biomarker panel classified the SJIA flare samples with 90% positive agreement with the clinical diagnosis and quiescent or remission samples with 100% agreement with the clinical diagnosis (P = 4.16 × 10−11).

Overall, the 17-peptide biomarker panel classified the SJIA systemic flare samples with 85% positive agreement with the clinical diagnosis, and the other systemic disease samples with 100% agreement with the clinical diagnosis (P = 4.53 × 10−13).

Our six-biomarker panel classified blindly the bootstrapping samples with 87.8% agreement with the clinical diagnosis for the flare samples and 81.8% agreement for the quiescent samples (Fig.  4c, right panel) (P = 2.4 × 10−5 for the bootstrapping test).

Finally, we investigated the expansion and contraction of T cell clonal lineages between quiescent and flare samples in SLE patients and compared these to the six pairs of HC samples.

We next sought to determine whether the panel of the 17-urine-peptide biomarkers could serve as a flare signature to discriminate SJIA flare samples from samples of patients at QOM and RD.

Clones were identified as expanded or contracted if their abundance in the flare sample was different from their abundance in the quiescent sample at P <0.001 using a DEseq differential abundance model trained on the six HC pairs (see Methods).

While no single peptide was present in all the flare or non-flare samples, combinations of two peptides were found that successfully differentiated 100% of the remission and pre-flare samples from flare and post-flare samples.

The remaining three patients were admitted with recent-onset disease and high disease activity, and in these cases no 'pre-flare' samples were available.

In three patients (HG, AM and DD), elevated levels of anti-CRP preceded the flares (Fig. 3), whereas pre-flare samples were not available for three patients (BÅ, CM and MS).

By highlighting the heterogeneity of disease burden within the gout-diagnosed population, examining the impact of both tophi and flares across samples of US and EU patients, this study adds breadth and specificity to current analyses of gout burden in the literature and can thus contribute to more effective disease management and improved patient outcomes.