What Works, What Doesn’t? Three Studies Designed to Improve Survey Response

Over the past few decades, the survey industry has experienced a steady decline in response rates, which has posed numerous challenges for researchers, most notably concerns about nonresponse bias. We present results from three studies conducted in an attempt to increase response rates and reduce nonresponse bias for a U.S. national household survey. We examined design features related to mode (i.e., mail-only vs. web-push), incentive, reminder type, nonresponse follow-up, and messaging. Results showed that a combination of a mail-only approach and the use of US$2 prepaid incentives increased response rates. However, using incentives did not bring into the respondent pool sample members who were less likely to respond. Additionally, we found that the use of a seventh follow-up contact only slightly increased response rates. Finally, we found that the use of a friendly message not only suppressed response rates but also increased potential nonresponse bias for sample members aged 35–48.

Drug Efflux Transporters and Imatinib Mesylate Insensitivity in Chronic Myeloid Leukemia

Abstract 4424 Background. Chronic Myeloid Leukemia represents the first human cancer in which a molecular therapy produces an effective clinical response (Holtz Blood 99:3792-800, 2002). The imatinib mesylate (IM) (Novartis Pharmaceuticals™) is a drug, that was designated to inhibit selectively certain tyrosine kinase proteins involved in the process of oncogenesis (Guilhot, The Oncologist, 9:271-81, 2004). In 2005, Michor (Nature 435:1267-70), through mathematical model, concluded that imatinib efficiently reduces the differentiated leukemic cells population, but it has not the same effect on the cell population that drives this disease, the CD34+ leukemic stem cells, which can be kept alive during the treatment. The search for the main causes of imatinib resistance has been intensified in recent years, with a special focus on the possible role of drug transporters (Apperley, Lancet Oncol 8:1018–29, 2007; Baker and Reddy, Mount Sinai J Med, 77:573–86, 2010). These proteins are the main determinants of the intracellular drug concentration, and how they actively regulating the traffic of small molecules through the cell membrane (Melo, Blood 108:1116-7, 2006). Thus, a cell can be resistant to a drug, because the optimum amount of the drug does not stay inside it to a significant effect to be achieved (Kim, Toxicology 182:291-7, 2002). Purpose. Identify differentially expressed genes in CD34+ and CD66b+ cells as candidates for IM transport. Methods. Samples of bone marrow (BM) and peripheral blood (PB) were obtained from five patients with CML treated with imatinib in better then optimal response according to European LeukemiaNet criteria (Baccarani, Blood 108:1809-20, 2006). Cells Isolation and RNA extraction. CD34+ cells were isolated from BM of five patients with CML. Likewise, mature CD66b+ PB cells were isolated from the same patients. SOLiD sequencing and sequence analysis. cDNA was sequenced according to the manufacturer's protocols for the SOLiD Total RNA-Seq kit for whole transcriptome. Data Analysis. To characterize the class genes, we analyzed the Gene Ontology (GO) annotation (Ashburner, Nature Genetics 25:25-9, 2000), and the software Cufflinks (Trapnell, Nature Biotechnology 28:511–15, 2010) were used to identify the differential expression of genes in both samples, in patients (BM × PB) and in control (BM × PB). The difference in gene expression between compared samples, were calculated based on P < 0.05 significance, were called differentially expressed genes those who submit P ≤ 0.05. Results. In pool sample of patients, it was possible to identify the genes SLC22A1 (OCT1) – in both, BM and PB pool samples, without any significant change (p ≤ 0,05) - and SLCO1A2 (OATP1A2) – only in PB sample. Thus its presence could not be identified in any of the control samples, which may reinforce the fact that these channels are actually responsible for the influx of imatinib in cells from patients undergoing treatment (Crossman, Blood:1133-4, 2005; Hu, Clin Cancer Res 14:3141–8, 2008). The presence of ABC gene family (ABCB1; ABCG2; ABCC1), described in the literature as being responsible for imatinib efflux (Jordanides, Blood 108: 1370–3, 2006; Brendel, Leukemia 21:1267–75, 2007) were found only in BM cells of patients. The presence of other two genes responsible for the drug efflux was also found exclusively in BM pool sample of patients, SLC47A1 and SLC47A2. These genes known as Human multidrug and toxin extrusion (MATE1 and MATE2) have also being identified as one important efflux mechanism of various drugs (Yonezawa and Inui, British J Pharmacol, 164:1817–25, 2011; Minematsu and Giacomini, Mol Cancer Ther, 10:531–9, 2011). Conclusion. The presence of more drug influx channels - the SLC family (OCT1 and OATP1A2) in mature cell - and absence of drug efflux channels - family ABC (ABCB1, ABCG2, ABCC1) and MATE genes (SLC47A1 and SLC47A2) - and the reverse in stem cells (CD34+) of patients with CML analyzed in this study may be the answer of why the insensitivity of CD34+ cells to treatment with IM and consequent failure to eliminate minimal residual disease. These genes can be candidates to therapeutic targets in CML. Disclosures: Lemos: Novartis of Brazil: Research Funding.

A Method for Sheath Flow Forming, Controlling and Detecting

An elaborated mechanism for sheath flow forming includes flow cell, vacuum pool, sample pool, syringes, valves, and tubes. Firstly the sample is drawn into the sample inlet of flow cell through vacuum generated with one syringe. Then, the sample and buffer are driven to pass the flow cell to form sheath flow by other two syringes. To visualize and evaluate the sheath flow, black ink is used as sample, and optical imaging system is adopted to capture the formed sheath flow. Sheath flows with sample width of 21μm and 37μm in diameter are formed in a flow cell with micro-square hole of the size 0.2mm×0.2mm when the syringes run in different speed.