RNA has important and diverse roles in biology, but molecular tools to manipulate and measure it are limited. For example, RNA interference can efficiently knockdown RNAs, but it is prone to off-target effects, and visualizing RNAs typically relies on the introduction of exogenous tags. Here we demonstrate that the class 2 type VI RNA-guided RNA-targeting CRISPR–Cas effector Cas13a (previously known as C2c2) can be engineered for mammalian cell RNA knockdown and binding.
After initial screening of 15 orthologues, we identified Cas13a from Leptotrichia wadei (LwaCas13a) as the most effective in an interference assay in Escherichia coli. LwaCas13a can be heterologously expressed in mammalian and plant cells for targeted knockdown of either reporter or endogenous transcripts with comparable levels of knockdown as RNA interference and improved specificity. Catalytically inactive LwaCas13a maintains targeted RNA binding activity, which we leveraged for programmable tracking of transcripts in live cells.
Our results establish CRISPR–Cas13a as a flexible platform for studying RNA in mammalian cells and therapeutic development.
We show that faces contain much more information about sexual orientation than can be perceived and interpreted by the human brain. We used deep neural networks to extract features from 35,326 facial images. These features were entered into a logistic regression aimed at classifying sexual orientation.
Given a single facial image, a classifier could correctly distinguish between gay and heterosexual men in 81% of cases, and in 74% of cases for women. Human judges achieved much lower accuracy: 61% for men and 54% for women. The accuracy of the algorithm increased to 91% and 83%, respectively, given five facial images per person. Facial features employed by the classifier included both fixed (e.g., nose shape) and transient facial features (e.g., grooming style).
Consistent with the prenatal hormone theory of sexual orientation, gay men and women tended to have gender-atypical facial morphology, expression, and grooming styles. Prediction models aimed at gender alone allowed for detecting gay males with 57% accuracy and gay females with 58% accuracy.
Those findings advance our understanding of the origins of sexual orientation and the limits of human perception. Additionally, given that companies and governments are increasingly using computer vision algorithms to detect people’s intimate traits, our findings expose a threat to the privacy and safety of gay men and women.
Let me reiterate: The accuracy of the algorithm increased to 91% and 83%, respectively, given five facial images per person.
Imagine if this analysis would be incorporated into the hiring process and used to discriminate candidates.
the team’s inventions include a biodegradable semi-conductive polymer, disintegrable and flexible electronic circuits, and a biodegradable substrate material for mounting these electrical components onto.
Totally flexible and biocompatible, the ultra-thin film substrate allows the components to be mounted onto both rough and smooth surfaces.
All together, the components can be used to create biocompatible, ultra-thin, lightweight and low-cost electronics for applications as diverse as wearable electronics to large-scale environmental surveys.
Maybe this is one of the many approaches we’ll use for biohacking or as wearable technology in the future.
When bioengineering students sit down to take their final exams for Stanford University, they are faced with a moral dilemma, as well as a series of grueling technical questions that are designed to sort the intellectual wheat from the less competent chaff: “If you and your future partner are planning to have kids, would you start saving money for college tuition, or for printing the genome of your offspring?”
The question is a follow up to “At what point will the cost of printing DNA to create a human equal the cost of teaching a student in Stanford?”
I’d love to see the breakdown by gender, ethnicity, etc. and how the answers evolve year over year.