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Life Science

A new phage in Microbiome discovery

The Human Genome Project was the largest collaborative scientific project that is credited with transforming our understanding of human genetics and revolutionizing medical research. It’s completion in 2003 was greeted as a watershed moment in the history of scientific discovery.

Today, a much less heralded collaborative scientific project is underway that may have implications for human health that could be as profound as that of the Human Genome Project. The Human Microbiome Project (HMP) is a National Institutes of Health (NIH)-supported collaboration that develops “research resources to enable the study of the microbial communities that live in and on our bodies and the roles they play in human health and disease”.

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Developing a pathology LIS for the digital age

For over a decade, Memorial Sloan Kettering has implemented digital pathology enterprise system for clinical scanning. Over the years that has evolved significantly. Currently, a lot of our efforts are spent on archive scanning to be available for prospective clinical cases.

Efforts to enable pathologists the ability for primary diagnosis are being explored, and we’re currently validating available systems. There’s always a certain flux in terms of vendor communication and networking, meaning that we’re validating systems for our internal use whether that’s for clinical, education, or research.

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Harnessing microfluidics for high throughput microbiology R&D

The BioMillenia technology platform is based on microfluidics, a technology platform widely used in life sciences, but not necessarily in microbiology. There are some commercial developments of the technology, for example NGS or dPCR platforms, but it’s a very new application in the field of microbiology.

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Gut Microbiome analysis – Getting it right

The cascade of new discoveries relating health and disease to our gut microbiome has spurred the notion that we now find ourselves in the middle of a “microbiome revolution”. Just to mention some recent examples, mechanisms have been demonstrated for gut bacteria contributing to Parkinson’s disease,[1] determining response to immune checkpoint inhibitor cancer therapy,[2] and even autistic behavior when fecal material from autistic children was transplanted into mice.[3]

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Infographic: Application of blockchain in Healthcare

Application of blockchain is no longer a concept known only to a few industries. What started with cryptocurrency in 2009 has come a long way since. Its capability for secure transactions has enabled it to find potential in industries such as banking where security is one of key concerns when it comes to digital transformation. Healthcare industry leaders are also waking up to this call and are now exploring ways to embrace the technology owing to the multiple possible use cases for the industry.

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What does the future hold for AI in Digital Pathology?

This is the second of a two-part blog post. In his first post, Liron wrote on embedding AI in Digital Pathology workflows.

Digital Pathology AI apps are certainly feasible, but exactly when they will be ready for clinical use is less clear.

There are potentially hundreds or thousands of algorithms that will need to be developed. Currently, there are only a handful of algorithms that are approved by regulatory bodies for clinical practice, so we’ve got a long way to go.

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How does Maternal Microbiome composition influence offspring metabolic outcomes?

Professor Margaret Morris is Chair and Head of Pharmacology, School of Medical Sciences, University of NSW. Her research explores the underlying brain mechanisms in epilepsy, obesity, diabetes, and the link between obesity and high blood pressure. We recently asked her about her research into obesity and the microbiome.

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How do we embed AI into Digital Pathology workflows?

This is an exciting time in pathology: now that digital pathology is mature, we have noticed an uptake in a lot of AI start-up companies. Most of the algorithms have been developed on a research basis or in a test environment, and only recently applied. What follows is a summary of the work we are doing at the University of Pittsburgh Medical Center testing these AI apps, and some of the questions arising therefrom.

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