With the growing popularity of single-cell RNA-Seq analysis, the t-SNE projection of multi-dimensional data is appearing more often in publications and online. If you’ve ever wanted to develop a better intuitive feel for what exactly t-SNE does and where it can go wrong, this interactive tutorial (by Martin Wattenberg and Fernanda Viegas) is extremely compelling and useful.
A screen capture of the interactive t-SNE interface.
In addition to providing a wonderful, interactive plotting function, the authors go on to provide an informative tutorial explains the pitfalls and challenges of the optimization and hyper-parameter tuning of t-SNE projections and how to get the most from the plots. Here is an example:
An example of how hyperparameter tuning affects the final plot.
In the example above, tuning the “perplexity” of the t-SNE projection causes the correct reconstruction of the data when values are between 30-50, but the same method fails when the parameter falls outside those ranges (i.e., too small or too large).
Go check out this distill.pub site. It’s worth your time.
So far this year has seen some pretty important research breakthrough advances in several key areas of health and medicine. I want to briefly describe some of what we’ve seen in just the first few months of 2018.
Flu
A pharmaceutical company in Japan has released phase 3 trial results showing that its drug, Xofluza, can effectively kill the virus in just 24 hours in infected humans. And it can do this with just one single dose, compared to a 10-dose, three day regimen of Tamiflu. The drug works by inhibiting an endonuclease needed for replication of the virus.
Germs
It is common knowledge that antibiotics are over-prescribed and over-used. This fact has led to the rise of MRSA and other resistant bacteria which threaten human health. Although it is thought that bacteria could be a source of novel antibiotics since they are in constant chemical warfare with each other, most bacteria aren’t culture-friendly in the lab and so researchers haven’t been looking at them for leads. Until now.
Malacidin drugs kill multi-drug resistant S. Aureus in tests on rats.
By adopting whole genome sequencing approaches to soil bacterial diversity, researchers were able to screen for gene clusters associated with calcium-binding motifs known for antibiotic activity. The result was the discovery of a novel class of lipo-peptides, called malacidins A and B. They showed potent activity against MRSA in skin infection models in rats.
The researchers estimate that 99% of bacterial natural-product antibiotic compounds remain unexplored at present.
Cancer
2017 and 2018 have seen some major advances with cancer treatment. It seems that the field is moving away from the focus on small-molecule drugs towards harnessing the patient’s own immune system to attack cancer. The CAR-T therapies for pediatric leukemia appear extremely promising. These kinds of therapies are now in trials for a wide range of blood and solid tumors.
A great summary of the advances being made is available here from the Fred Hutchinson Cancer Research Center. Here is how Dr. Gilliland, President of Fred Hutch, begins his review of the advances:
I’ve gone on record to say that by 2025, cancer researchers will have developed curative therapeutic approaches for most if not all cancers.
I took some flak for putting that stake in the ground. But we in the cancer research field are making incredible strides toward better and safer, potentially curative treatments for cancer, and I’m excited for what’s next. I believe that we must set a high bar, execute and implement — that there should be no excuses for not advancing the field at that pace.
This is a stunning statement on its own; but made even more so because it is usually the scientists in the day-to-day trenches of research who are themselves the most pessimistic about the possibility of rapid advances.
Additionally, an important paper came out recently proposing a novel paradigm for understanding and modeling cancer incidence with age. For a long time the dominant model has been the “two-hit” hypothesis which predicts that clinically-observable cancers arise when a cell acquires sufficient mutations in tumor-suppressor genes to become a tumor.
This paper challenges that notion and shows that a model of thymic function decline (the thymus produces T-cells) over time better describes the incidence of cancers with age. This model better fits the data and leads to the conclusion that cancers are continually arising in our bodies, but it is our properly functioning immune system that roots them out and prevents clinical disease from emerging. This model also helps explain why novel cancer immunotherapies are so potent and why focus has shifted to supporting and activating T-cells.
Declining T cell production leads to increasing disease incidence with age.
