Using RNA interference (RNAi) to knock down gene expression is one of the staples of life science research. It’s used in many cellular models, primarily as a tool for assessing the involvement of specific genes in biological systems. However, it wasn’t until recently that this technology was successfully adapted for humans to treat disease.
Over the last 10 years, biobanks have become a staple of biomedical research. The ability to accumulate, catalog, and dispense a variety of sample types from a large population of donors, both healthy and diseased, has facilitated an abundance of new discoveries. Generating new data is so efficient that each week, the UK Biobank publishes a new study based on information obtained from its own samples. However, caring for so many samples requires not just skilled personnel, but also systems that can track and trace these samples without making errors. This has led biobanks to integrate practices from pharmaceutical and biotechnology manufacturing companies to ensure their inventory of samples is properly maintained and distributed accordingly.
As of the day this article was written, more than 20,000 cases of the new coronavirus, named 2019-nCoV, have been confirmed in China.1 The disease, which originated in Wuhan, a city in the Hubei province of China, has taken over headlines across the world as it currently has the potential to drive a global pandemic, with the WHO declaring it a global health emergency. Though the fatality rate is currently not as high as either of its two relatives, SARS and MERS, everyone is taking the threat seriously, particularly in China, where cities have become ghost towns.2
Appropriately identifying patient specimens is of critical importance to pathology labs. The College of Pathologists previously evaluated the average cost of labeling errors at approximately $280,000 per million specimens, adding up to over $1 million dollars a year for some of the larger institutes.1 Specimen labeling errors also result in the failure to provide proper and immediate care for patients, which can severely harm the patient, resulting in unnecessary morbidity and mortality.2
With new artificial intelligence (AI) technology primed to revolutionize medicine, including diagnostics and drug discovery, it was only a matter of time until scientists decided to use AI to solve the question no one has yet been able to answer: why do we age at all?
With cannabis now legalized in Canada, research into the beneficial effects of cannabinoids and terpenes is growing across the country. I was recently at Expo Cannabis 2019 in Montreal, Quebec, and in only its second year of existence, the organizers were able to assemble clinicians and industry opinion leaders from all over the country to discuss the benefits and challenges of using cannabis in healthcare.
In 2018, the term “Blockchain” was one of the most searched terms by scientists on Google.1 This technology first appeared ten years earlier as the driving force behind the cryptocurrency, Bitcoin. Since then, many have followed suit, creating more than 2000 different cryptocurrencies worth hundreds of billions of dollars.2 Blockchain is now being implemented in the healthcare industry, with the opportunity to solve many issues currently plaguing healthcare institutions and companies alike.
Just a couple years ago, I was a research associate working at McGill University in the Meakins-Christie Laboratories, studying a rare disease called lymphangioleiomyomatosis, or LAM. LAM is a progressive, cystic disease afflicting young women with noncancerous lung tumors that can destroy lung function, making the disease potentially fatal. My job was to understand where these tumors came from and what made them propagate throughout the lungs. There was one unfortunate caveat: no one had been able to grow LAM tumor cells outside of the body. As anyone who has ever worked with cancer biology can attest to, there are a multitude of immortalized cancer cell lines, grown from the cells of a patient’s tumor, that can be studied to perform pre-clinical translational research. And yet, not a single representative cell line was available for LAM. Thankfully, my supervisor set me up with just the right project to help solve this puzzle, which centered around induced pluripotent stem cells (iPSCs).
When you hear 3D printing, what do you think of? Perhaps you imagine creating inanimate objects like chairs, wrenches, or toys out of construction materials (e.g. plastic, ceramic, or metal). The uses of additive printing have evolved way past that and now serve an important role in medicine and research.
The main purpose of any vaccine is to stop the spread of communicable diseases from one person to another and, where possible, to abolish the disease outright from the general population. There are many commercially available vaccines for a variety of viral and bacterial diseases, including diphtheria, tetanus, whooping cough, measles, polio, tuberculosis, hepatitis, human papillomavirus, and influenza. To develop these and other vaccines, three things are required: research to find an antigen (usually a protein produced by the pathogen) that produces a protective immune response against the disease, a platform in which to produce the vaccine, and clinical testing.