Sentence examples for divided t from inspiring English sources

The inhibition of T cell proliferation was represented by the percentage decrease of CSFE+ divided T cells compared to neurosphere medium control.

Mice treated with FTY720 showed a higher accumulation of more extensively divided T cells within draining (cervical and mediastinal) lymph nodes, while in distal lymph nodes the percentage of divided TgN cells was largely reduced.

Whilst the T cells from the Agpos mice divided a similar number of times in response to antigen-specific stimulation, we failed to see an accumulation of the divided T cells (Figure 2 A).

The treatment with FTY720 determined an accumulation of more extensively divided T cells in draining cervical and mediastinal lymph nodes with about 92% of proliferating lymphocytes respect to 69% of untreated mice (Fig. 2 A).

The presence at distal sites was due to migration of locally primed T cells as shown by fingolimod treatment that caused a drastic reduction of proliferated T cells in non-draining lymph nodes and an accumulation of extensively divided T cells within draining lymph nodes.

We have previously observed that divided T cells, primed by nasal immunization, are detectable in distal lymphoid organs, such as iliac and mesenteric lymph nodes and in the spleen [15], [16] and we hypothesized that this could be due to the dissemination of Ag-bearing APCs into distal lymphoid sites, or to the redistribution of T cells primed in the draining lymph nodes.

To equate the number of healthy individuals (74) to the number of patients with T-ALL (173), we divided T-ALL patient samples into two groups randomly.

In order to evaluate why data sets do not perfectly fit with a straight line correlation model, we divided T-UCRs into three groups: highly (CqNA ≤ 25), moderately (25 < CqNA ≤ 30), and low expressed (30 < CqNA ≤ 35) T-UCRs.

For genes that may be controlled by multiple T-DMRs, we divided T-DMR sets into coherent and incoherent, based upon whether or not the multiple T-DMRs had the same correlation direction with gene expression.

Then, we resampled our patient samples 5 times (we again divided T-ALL samples into 2 groups randomly; thus these 2 groups are different from the 2 groups created before. So, we generated 10 different combinations of patients) and repeated the merging and algorithm-running steps.

Divide T into two disjoint sub-families (T_{1}), (T_{2}).