Lab of the Future – News and Features

Modelling the human senses is an incredibly complex task. Our brains arrange cells into complex hierarchies that process information from our surroundings. Now, a group at MIT have created a model of the human auditory cortex that can hear sounds and music in the same way that humans do.

Research into major diseases is a time-critical field. Automation can help make research faster and more reproducible. In this blog, we discuss the advantages and challenges of incorporating automation into pathology with Coleman Stavish, Proscia Inc's Chief Technology Officer.

The process of assessing and monitoring heart disease, the leading cause of death in the US, is often expensive and time-consuming. A new app that incorporates pulse data to diagnose arterial changes could simplify the whole process.

Researchers have highlighted a link between fetal brain development and the origins of developmental diseases such as schizophrenia.

By combining data on pathology images of 13 types of cancer and correlating that with clinical and genomic data, researchers are able to identify tumor-infiltrating lymphocytes, which will enable cancer specialists to generate tumor-immune information from routinely gathered pathology slides.

Identifying structures in brain cells generally requires a long and potentially damaging process of staining to enable particular features to be picked out. Now, researchers are training computers to do the grunt work for them.

A fascinating study that identified search results or tweets that associated with syphilis was then able to predict syphilis occurrence at a state-wide level.

Can babies really tell the difference between anger and happiness at six months or do they only recognise the physical characteristics of these emotions? Researchers provide a preliminary answer.

Despite advances in matching genetic signatures from cancer tumors to treatment options, certain "hidden responder" patients are currently not helped by this form of personalized medicine. Now, machine learning techniques may allow clinicians to identify these patients.

Boys and young men are more likely to develop respiratory diseases such as asthma. Now, a study examining the epigenome of DNA decoration and modification has classified areas of DNA which may explain this phenomenon.