Anthropogenic biases in chemical reaction data hinder exploratory inorganic synthesis.

Most chemical experiments are planned by human scientists and therefore are subject to a variety of human cognitive biases, heuristics and social influences. These anthropogenic chemical reaction data are widely used to train machine-learning models that are used to predict organic and inorganic syntheses. However, it is known that societal biases are encoded in datasets and are perpetuated in machine-learning models.

T-blocker: a simple and robust probe-free quantitative PCR assay to detect somatic mutations down to 0.1% frequency.

We have developed a simple and robust probe-free quantitative PCR (qPCR) assay method that can detect minor mutant alleles with a frequency as low as 0.1% in a heterogeneous sample by introducing a novel T-blocker concept to the allele-specific PCR method. Four new KRAS and BRAF mutation detection assays were developed and their performance was demonstrated by testing a large number of replicates, utilizing a customized PCR protocol.