Objectives To evaluate at which sensitivity digital breast tomosynthesis (DBT) would become cost-effective compared to digital mammography (DM) in a population breast cancer screening program, given a constant estimate of specificity. Methods In a microsimulation model, the cost-effectiveness of biennial screening for women aged 50–75 was simulated for three scenarios: DBT for women with dense breasts and DM for women with fatty breasts (scenario 1), DBT for the whole population (scenario 2) or maintaining DM screening (reference). For DM, sensitivity was varied depending on breast density from 65 to 87%, and for DBT from 65 to 100%. The specificity was set at 96.5% for both DM and DBT. Direct medical costs were considered, including screening, biopsy and treatment costs. Scenarios were considered to be cost-effective if the incremental cost-effectiveness ratio (ICER) was below €20,000 per life year gain (LYG). Results For both scenarios, the ICER was more favourable at increasing DBT sensitivity. Compared with DM screening, 0.8–10.2% more LYGs were found when DBT sensitivity was at least 75% for scenario 1, and 4.7–18.7% when DBT sensitivity was at least 80% for scenario 2. At €96 per DBT, scenario 1 was cost-effective at a DBT sensitivity of at least 90%, and at least 95% for scenario 2. At €80 per DBT, these values decreased to 80% and 90%, respectively. Conclusion DBT is more likely to be a cost-effective alternative to mammography in women with dense breasts. Whether DBT could be cost-effective in a general population highly depends on DBT costs. Key Points • DBT could be a cost-effective screening modality for women with dense breasts when its sensitivity is at least 90% at a maximum cost per screen of €96. • DBT has the potential to be cost-effective for screening all women when sensitivity is at least 90% at a maximum cost per screen of €80. • Whether DBT could be used as an alternative to mammography for screening all women is highly dependent on the cost of DBT per screen.

Here, we developed a cell-based biosensor that can assess meat freshness using the Gram-positive model bacterium Bacillus subtilis as a chassis. Using transcriptome analysis, we identified promoters that are specifically activated by volatiles released from spoiled meat. The most strongly activated promoter was PsboA, which drives expression of the genes required for the bacteriocin subtilosin. Next, we created a novel BioBrick compatible integration plasmid for B. subtilis and cloned PsboA as a BioBrick in front of the gene encoding the chromoprotein amilGFP inside this vector. We show that the newly identified promoter could efficiently drive fluorescent protein production in B. subtilis in response to spoiled meat and thus can be used as a biosensor to detect meat spoilage.

The authors regret that the name Alicja M. Daszczuck, has been misspelled and should be Alicja M. Daszczuk.The authors would like to apologise for any inconvenience caused.

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