Matias Serebrinsky

Time is becoming a poor measure of how distant the future really is. Ten years used to be a manageable stretch of the future, but with AI, it does not tell you much anymore. After much thinking, I came up with a better framing to measure the future: tokens of thinking. Let me explain:

Your AI agent can find anyone on the internet. It has no idea who can actually get you to them. Until now. Meet Gigi: the trusted network that gives agents access to people. That investor you've been dying to meet. The engineer you'd hire tomorrow. The dream customer you can't get in front of. Chances are, someone in your extended network knows them. Gigi finds out who. Your agent can now search your network, ask the agents of people you trust to search theirs, and find real warm paths to the people you want to reach. All without exposing anyone's contacts. And without reading a single email or message. Your network is no longer who you know. It's who your agent can get you to. Think of one person you wish you knew. Ask Gigi to find your way in. Link in the comments👇

Today, Sculpta releases the first demonstration of bioorthogonal barcoding ("bobcoding"), the process by which we: 1) covalently attach oligonucleotide barcodes to RNA at multiple internal positions with two-step chemistry, and 2) perform a multiplexed reverse transcription reaction to generate barcoded cDNA libraries with >99% barcoding accuracy. To the best of our knowledge, it is the first time ever that either of these steps have ever been performed by anyone. No one has ever broken the barrier of multiplexing prior to any enzymatic step in library preparation, driving simplicity and higher data quality. Instead of other methods that add 0 or 1 barcode, we add one barcode every ~300bp, adding redundancy and fidelity to RNA measurements. In our first application described in our pre-print below, we used bobcodes to create the first RNA isoform-resolved drug screening platform. It beats Novartis' DRUG-seq platform by: - generating full length transcript capture of RNA isoforms, instead of just 3' end counting - capturing 25-fold more RNA splicing events - reducing barcode swapping by 10-fold - using 18 fewer PCR cycles (~250,000 less amplification) - reducing sample-to-sample variability in gene expression measurements - eliminating costly and cumbersome library fragmentation/tagmentation steps completely - reducing workflow complexity and number of steps - reducing overall protocol duration by ~25% Though our chemical barcoding method improved transcriptomic data quality while also being simpler and faster than all existing methods, the implications of this work go well beyond this particular use case: The gate to greater applications of AI in transcriptomics is not a lack of compute. Nor is it a lack of data volume. The elephant in the room has always been our limited ability to faithfully and accurately measure cellular RNAs. Sculpta now has line of sight to build what we call the first ground truth transcriptomics platform [for single cell, spatial and more] for the future of biological research, drug development and AI-enabled discoveries for the betterment of human health and longevity. [PS Until the kind folks at bioRxiv get through the apparent backlog of AI slop submissions, Sculpta will host the pre-print PDF on our website. You can sign up for product offerings and other updates at this link too] sculpta.bio/preprint

Hello world! We’re @MelodyFRO. Most wearables don’t go far beyond heart rate and activity. Lab diagnostics paint a deeper picture but don’t read continuously. Melody is building biosensors, devices, and standards to bridge this gap. Hear our story at melodyfro.org