High-throughput screening (HTS) assays that measure the in vitro toxicity of environmental compounds have been widely applied as an alternative to in vivo animal tests of chemical toxicity. Current HTS studies provide the community with rich toxicology information that has the potential to be integrated into toxicity research. The available in vitro toxicity data is updated daily in structured formats (e.g., deposited into PubChem and other data-sharing web portals) or in an unstructured way (papers, laboratory reports, toxicity Web site updates, etc.). The information derived from the current toxicity data is so large and complex that it becomes difficult to process using available database management tools or traditional data processing applications. For this reason, it is necessary to develop a big data approach when conducting modern chemical toxicity research. In vitro data for a compound, obtained from meaningful bioassays, can be viewed as a response profile that gives detailed information about the compound’s ability to affect relevant biological proteins/receptors. This information is critical for the evaluation of complex bioactivities (e.g., animal toxicities) and grows rapidly as big data in toxicology communities. This review focuses mainly on the existing structured in vitro data (e.g., PubChem data sets) as response profiles for compounds of environmental interest (e.g., potential human/animal toxicants). Potential modeling and mining tools to use the current big data pool in chemical toxicity research are also described.

This study assessed the usefulness of DNA quantification to predict the success of historical samples when analyzing SNPs, mtDNA, and STR targets. Thirty burials from six historical contexts were utilized, ranging in age from 80 to 800 years postmortem. Samples underwent library preparation and hybridization capture with two bait panels (FORCE and mitogenome), and STR typing (autosomal STR and Y-STR). All 30 samples generated small (~80 bp) autosomal DNA target qPCR results, despite mean mappable fragments ranging from 55–125 bp. The qPCR results were positively correlated with DNA profiling success. Samples with human DNA inputs as low as 100 pg resulted in ≥80% FORCE SNPs at 10X coverage. All 30 samples resulted in mitogenome coverage ≥100X despite low human DNA input (as low as 1 pg). With PowerPlex Fusion, ≥30 pg human DNA input resulted in >40% of auSTR loci. At least 59% of Y-STR loci were recovered with Y-target qPCR-based inputs of ≥24 pg. The results also indicate that human DNA quantity is a better predictor of success than the ratio of human to exogenous DNA. Accurate quantification with qPCR is feasible for historical bone samples, allowing for the screening of extracts to predict the success of DNA profiling.

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Analysis of oil lamps and clay figurines recovered from a Late Roman ceramics workshop at Beit Nattif in Israel has revealed numerous fragments with evidence of the manufacturer's fingerprints preserved on some of the ceramic surfaces. Further study of these fingerprints has provided a unique insight into the production history of the workshop, even showing how particular innovations in technique may be associated with particular individuals.

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