Here, we look at the growing applications of AI-driven spatial imaging techniques in healthcare, focusing on interpreting the 3D genome through cell imaging. AI can assist in understanding intricate data patterns, enabling an improved understanding of cell behaviour and diseases.

Advances in spatial imaging have revolutionised disease analysis, revealing new therapeutic targets and biomarkers. However, efficiently interpreting the vast amount of data generated remains a challenge.

Recent advances in spatial transcriptomics have facilitated the development of advanced techniques for uncovering new information about the cellular microenvironment. Two techniques explored here – Giotto and Slide-seq – are on the cutting edge of spatial imaging.

Key opinion leaders discuss analysis pipelines for spatial transcriptomics analysis and the challenges faced in this field.

Richard Stanton, Professor of Virology at Cardiff University, presents the latest on and off-target genome editing techniques.

What are the current opportunities and challenges facing single-cell analysis today? We ask key opinion leaders from Janssen Pharmaceuticals, SciLifeLab, and the Karolinska Institutet.

This Insight Article looks at the short and long-term predictions for spatial technological regulation, standardisation, and collaboration for the omics field.

The gene editing field has exploded in the last ten years, with methods such as CRISPR-Cas9 becoming well-established in the pre-clinical sphere. However, complications in clinical applications have led some researchers to explore alternatives.

Current and upcoming gene editing technologies, such as prime editing and cell line models, have huge potential in applications such as cancer treatment. With the field constantly witnessing new breakthroughs and advances, genome modification holds a lot of promise for the future.

The therapeutic targeting of TME microglia activity may improve the efficacy of treatments for melanoma brain metastasis. Future research could represent a new opportunity in confronting one of the most difficult cancers to treat.

Visualising and monitoring protein localisation requires a high degree of accuracy in image processing. Fortunately, spatial proteomics is proving itself to be an imaging technique which is more than up to the challenge.

Some of the investigative methods explored in this article include mass spectrometry imaging and cell modelling of tumour architecture.

Maintaining tolerance to a graft or organ transplant is a critical aspect of treatment for precision medicine. Antibody-mediated rejection is a serious hurdle to transplantation success, but the integration of highly selected stem cells into treatment may be a solution.

Single-cell metabolomics is a rapidly growing area of study within the field of molecular imaging. By applying metabolomic imaging techniques at a single-cell resolution, it can be used to investigate cellular progression in diseases such as NASH and liver cirrhosis.

The expression of the protein coding gene CXCR6 was observed to be significantly lower in patients with severe cases of COVID-19, suggesting a genetic correlation in severe cases.

Good quality samples are integral to single-cell data analysis, but maintaining sample integrity presents a logistical hurdle for bioinformatics teams worldwide. Read on to learn about how senior healthcare researchers circumvent the issues associated with sample degradation.

In this Commentary article, we explore how the current boom in AI is enabling researchers to take bold new steps in data analysis, with the potential for its utilisation in coordinating new healthcare responses. Trusted research environments have increased the feasibility of using translational research to help tackle new and approaching problems in healthcare.

The potential applications of deep learning tools in preliminary studies have developed along with their complexity in the past few years. Now, they could be used to help to refine a study or programme before it takes place in order to optimise its efficiency.