Researchers in Professor Zhenan Bao's group at Stanford University have developed a biomimetic soft electronic skin (e-skin) with multiple levels of biologically inspired patterning that can detect the direction of applied forces.
A team of Stanford researchers has developed a precisely controlled hydrogel drug delivery system that prevents scarring and promotes wound healing in large, full thickness wounds.
The Rai1-Tag knock-in allele expresses a FLAG/myc-tagged RAI1 (Rai1-Tag) before Cre recombinase exposure. Cre-mediated deletion of the floxed FLAG-myc-STOP sequence results in expression of RAI1/EGFP fusion protein (Rai1EGFP).
When examining one or higher dimensional data, researchers frequently aim to identify individual subsets (clusters) of objects within the dataset. With high-dimensional data (>3 dimensions), the data become progressively more sparsly distributed in space.
Stanford researchers in the McNab lab have developed a marker-less neuro-navigation device that only needs to be setup once during the first transcranial magnetic stimulation (TMS) session and by tracking the subjects head, automatically achieves the same accurate coil locatio
Researchers in Dr. Craig Criddle's lab have developed a method for enriching microorganisms with high poly(3-hydroxy)butyrate (PHB) production in non-sterile mixed culture conditions.
Stanford researchers have recently patented a hybrid LED-LCD screen suitable for applications ranging from large televisions to small mobile displays and capable of significantly reducing power consumption to as little as 1/20th that of conventional design
Engineers in Prof. Khuri-Yakub's laboratory have developed ultrasonic methods for non-invasive flow meters to accurately measure flow rate, pressure, velocity and other parameters of gas or liquid traveling through a pipe.
Engineers in Prof. Khuri-Yakub's laboratory have developed ultrasonic methods for non-invasive flow meters to accurately measure flow rate, pressure, velocity profile and other parameters of gas or liquid traveling through a pipe.
Nonstationary image artifacts frequently arise in MRI from off-resonance and motion. Current methods to correct these nonstationary effects are computationally expensive. Stanford researchers have developed a new deep learning framework to improve image quality in minutes.
Stanford researchers have developed an improved imaging protocol for better visualization of the thalamus. This faster acquisition leads to a better delineation of structures due to the multiple dimensions of information.
Disease indication - Chemo- and radiation therapy resistant cancer, such as ovarian cancer, head and neck cancer (HNC), lung cancer, glioblastoma multiforme and breast cancer.