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Sixty-five years ago today, Theodore Maiman successfully operated the first laser. In commemoration, this online Collection brings together many of the light-based Primers we have published, encompassing microscopy, spectroscopy and other optical techniques.
Machine learning models are increasingly being deployed in real-world clinical settings and have shown promise in patient diagnosis, treatment and outcome tasks. However, such models have also been shown to exhibit biases towards specific demographic groups, leading to inequitable outcomes for under-represented or historically marginalized communities.
Thriving in academia with a disability sparks creativity and innovation. My experience in chemistry and pharmacy laboratories highlights the need for universities to establish inclusive environments with clear, effective accommodations. I advocate for inclusivity, urging academia to support all researchers to excel and making science accessible to everyone.
Whole-brain modelling is an essential tool that provides relevant insights for neuroscientists as they work to discover the fundamental principles of healthy brain function.
Single-case experimental designs are rapidly growing in popularity. This popularity needs to be accompanied by transparent and well-justified methodological and statistical decisions. Appropriate experimental design including randomization, proper data handling and adequate reporting are needed to ensure reproducibility and internal validity. The degree of generalizability can be assessed through replication.
Bayesian optimization is a promising approach towards a more environmentally friendly chemical synthesis, in line with the Sustainable Development Goals. It can aid chemists to explore vast chemical spaces and find green reaction conditions with few experiments, decreasing resource consumption and waste generation while reducing discovery timelines and costs.
To improve early-stage research in the field of RNA lipid nanoparticles, there are several best practices to be considered for the collection, interpretation and reporting of characterization data.
To ensure a sustainable future and combat food scarcity, we must boost agricultural productivity, improve climate resilience and optimize resource usage. There is untapped potential for dense wireless sensor networks in agriculture that can increase yields and support resilient production when linked to smart decision and control systems.
New nanomaterials are being developed for efficient biomolecule delivery to plants. However, detection and quantification of plant cell entry are challenging and currently rely on subjective methods that lack proper controls. The necessary considerations of performing nanoparticle-mediated delivery in plants and how to accurately quantify delivery efficiency are discussed.
Laboratory hardware is often custom made or significantly modified. To improve reproducibility, it is imperative that these novel instruments are properly documented. Increasing adoption of open source hardware practices can potentially improve this situation. This article explores how open licences and open development methodologies enable custom instrumentation to be reproduced, scrutinized and properly recorded.
Logic diagrams are employed in electrical engineering for visualizing switching circuits. However, their utility and applicability extend far beyond the technical sciences. Here, we argue that natural and social scientists alike should consider using logic diagrams in their research. For certain analytical problems, logic diagrams are a perfect fit.
Data analysis relies heavily on computation, and algorithms have grown more demanding in terms of hardware and energy. Monitoring their environmental impacts is and will continue to be an essential part of sustainable research. Here, we provide guidance on how to do so accurately and with limited overheads.
Designing technology for point-of-care use in low- and middle-income countries requires understanding of the underlying barriers that contribute to recalcitrant global problems. The only way to understand those barriers is to work with local experts, otherwise you may wind up solving the wrong problem.
As we close our second volume of Nature Reviews Methods Primers, we look back on our achievements in 2022 and opportunities to better serve our community.
Black box machine learning models can be dangerous for high-stakes decisions. They rely on untrustworthy databases, and their predictions are difficult to troubleshoot, explain and error check for real-time predictions. Their use leads to serious ethics and accountability issues.
Lokwani et al. discuss the necessary considerations when performing spectral cytometry on highly autofluorescent samples to extract phenotypic information from autofluorescence spectra and perform accurate quantification of fluorescent labels.
Addressing current and future global problems requires sustainable practices in chemistry. We discuss ways to incorporate sustainability in laboratory practice, processes and beyond.
