In the past decade, there has been significant interest in studying the expression of our genetic code down to the level of single cells, to identify the functions and activities of any cell through the course of health or disease.
The identity of a cell, and the way that identity can go awry, is critical to its role in many of the biggest health challenges we face, including cancer, neurodegeneration, or genetic and developmental disorders. Zooming in on single cells allows us to tell the difference between variants which would otherwise be lost in the average of a region. This is essential for finding new medical solutions to diseases.
Most single-cell gene expression experiments make use of a technology called single-cell RNA sequencing (scRNA-seq), which produces a map of exactly which genes are being copied out into short “transcripts” inside the nucleus. However, scRNA-seq only gives us a window into the intermediate step between the genetic code and the proteins which take care of (almost) all the tasks inside our bodies.
Bioelectronics have transformed our capacity to monitor and treat diseases; however, a lack of micrometer-scale, energy efficient communication options limit these devices from forming integrated networks that enable full-body, sensor driven, physiological control. Inspired by our nervous system’s ability to transmit information via ionic conduction, we engineered a Smart Wireless Artificial Nervous System (SWANS) that utilizes the body’s own tissue to transmit signals between wearables and implantables. When SWANS emits signals, it generates voltage gradients throughout the body that selectively turn on implanted transistor switches when exceeding their gate threshold voltages. SWANS’ implantable communication components maintain syringe-injectable footprints and 15x greater power efficiencies than Bluetooth and Near Field Communication. In vivo studies in rats demonstrate SWANS’ ability to wirelessly regulate dual hind leg motor control by connecting electronic-skin sensors to implantable neural interfaces via ionic signaling as well as coordinate bioelectronics throughout the epidermal, subcutaneous, intraperitoneal, and gastrointestinal spaces.
Ramy ghanim, yoon jae lee, garan byun, joy jackson, julia Z ding, elaine feller, eugene kim, dilay aygun, anika kaushik, alaz cig, jihoon park, sean healy, camille E cunin, aristide gumyusenge, woon hong yeo, alex abramson.
Questions to inspire discussion.
Advanced Navigation and Obstacle Recognition.
🛣️ Q: How will FSD v14 handle unique driveway features? A: The improved neural net and higher resolution video processing will help FSD v14 better recognize and navigate features like speed bumps and humps, adjusting speed and steering smoothly based on their shape and height.
🚧 Q: What improvements are expected in distinguishing real obstacles? A: Enhanced object detection driven by improved algorithms and higher resolution video inputs will make FSD v14 better at distinguishing real obstacles from false positives like tire marks, avoiding abrupt breaking and overreacting.
Edge case handling and smooth operation.
🧩 Q: How will FSD v14 handle complex edge cases? A: The massive jump in parameter count and better video compression will help the AI better understand edge cases, allowing it to reason that non-threatening objects like a stationary hatch in the road aren’t obstacles, maintaining smooth cruising.
