Large inherent variability in data derived from highly standardised cell culture experiments

Systematic heterogenization revisited: Increasing variation in animal experiments to improve reproducibility?

Life sciences are currently facing a reproducibility crisis. Originally, the crisis was born out of single alarming failures to reproduce findings at different times and locations. Nowadays, systematic studies indicate that the prevalence of irreproducible research does in fact exceed 50%. Viewed from a rather cynical perspective, Fett's law of the lab "Never replicate a successful experiment" has thus taken on a completely new meaning. In this respect, animal research has come under particular scrutiny, as the stakes are high in terms of both research ethics and societal impact. To counteract this, it is essential to identify sources of poor reproducibility as well as to iron out these failures. We here review the current debate, briefly discuss potential reasons, and summarize steps that have already been undertaken to improve reproducibility in animal research. By the example of classical behavioural phenotyping studies, we particularly highlight the role strict standardization plays in exacerbating the crisis, and review the concept of systematic heterogenization as an alternative strategy to deal with variation in animal studies. Briefly, we argue that systematic variation rather than strict homogenization of experimental conditions benefits the robustness of research findings, and hence their reproducibility. To this end, we will present concrete examples for systematically heterogenized experiments and provide a practical guide on how to apply systematic heterogenization in experimental practice.

Understanding and tackling the reproducibility crisis - Why we need to study scientists' trust in data

In the life sciences, there is an ongoing discussion about a perceived 'reproducibility crisis'. However, it remains unclear to which extent the perceived lack of reproducibility is the consequence of issues that can be tackled and to which extent it may be the consequence of unrealistic expectations of the technical level of reproducibility. Large-scale, multi-institutional experimental replication studies are very cost- and time-intensive. This Perspective suggests an alternative, complementary approach: meta-research using sociological and philosophical methodologies to examine researcher trust in data. An improved understanding of the criteria used by researchers to judge data reliability will provide crucial, initial evidence on the actual scale of the reproducibility crisis and on measures to tackle it.

Ultrasensitive, Multiplexed Buoyant Sensor for Monitoring Cytokines in Biofluids

Multiplexed quantification of low-abundance protein biomarkers in complex biofluids is important for biomedical research and clinical diagnostics. However, in situ sampling without perturbing biological systems remains challenging. In this work, we report a buoyant biosensor that enables in situ monitoring of protein analytes at attomolar concentrations with a 15 min temporal resolution. The buoyant biosensor implemented with fluorescent nanolabels enabled the ultrasensitive and multiplexed detection and quantification of cytokines. Implementing the biosensor in a digital manner (i.e., counting the individual nanolabels) further improves the low detection limit. We demonstrate that the biosensor enables the detection and quantification of the time-varying concentrations of cytokines (e.g., IL-6 and TNF-α) in macrophage culture media without perturbing the live cells. The easy-to-apply biosensor with attomolar sensitivity and multiplexing capability can enable an in situ analysis of protein biomarkers in various biofluids and tissues to aid in understanding biological processes and diagnosing and treating diverse diseases.