Existing RNA-targeting tools for sequence-specific manipulation include anti-sense oligos (ASOs), designer PUF proteins and CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)/Cas systems. However, there are significant limitations to each of the current tools. ASOs are usually not available for most RNA manipulations other than gene silencing. Designer proteins, such as PUF (Pumilio and FBF homology protein), possess low RNA recognition efficiency and it remains challenging to target RNA sequences >8-nucleotides (nt) in length. The bulky Cas protein (Cas13d: average 930 amino acids) leads to complication for transgene delivery and concerns of its immunogenicity due to its bacterial origin. Mutants of zinc finger(ZnF) proteins in ZRANB2 recognize a single-strand RNA containing a novel GGG motif with micromolar affinity, compared to the original motif GGU. These mutants serve as a foundation for RNA-binding ZnF designer protein engineering for in vivo RNA sequence-specific targeting.ZnFs are generally compact domains (~3kDa each) that have been successfully engineered for DNA recognition as modular arrays. A ZnF-based system has unique advantages, especially in a therapeutic context: (1) Broad application with the possibility to fuse with other effector domains; (2) High efficiency of RNA recognition (3 RNA bases recognized per 30-amino-acid ZnF) with a small size of protein. Only 4 ZnFs (~100 aa) is required for specific targeting in the transcriptome. (3) Humanized components without immunogenic concern.By engineering new sequence specificity of the ZRANB2 ZnF1, researchers from UC San Diego identified 13 mutants that altered their preferred RNA binding motif from GGU to GGG. They are N24R, N24H, N14D/N24R, N14D/N24H, N14R/N24R, N14R/N24H, N14H/N24R, N14H/N24H, N14Q/N24R, N14Q/N24H, N14E/N24R, N14S/N24R, N14E/N24H.

This technology introduces a novel approach to MEMS integration, utilizing folding techniques to enable special distribution of sensor components and co-integration of multiple physical sensor modalities with control electronics in a compact formfactor.

Researchers at the University of California Davis have developed a technology that enables the provable editing of DNNs (deep neural networks) to meet specified safety criteria without altering their architecture.

Professor Bahman Anvari and colleagues from the University of California, Riverside and the University of Maryland have developed nanoparticle systems with greater fluorescence emission when compared to known dyes. These nanoparticles incorporate dual near infrared fluorescence (NIR) and magnetic resonance (MR) dyes for improved fluorescence.  The nanoparticles encapsulate brominated carbocyanine dyes with MR qualities and ICG with NIR properties. This technology is advantageous because these nanoparticles containing these dyes exhibit greater fluorescence emission when compared to the individual dyes.  This presents a promising dual-mode platform with high optical sensitivity and clinical diagnostic and research applications.  

Hybridization capture approaches allow targeted high-throughput sequencing analysis at reduced costs compared to shotgun sequencing. Hybridization capture is particularly useful in analyses of genomic data from ancient, environmental, and forensic samples, where target content is low, DNA is fragmented and multiplex PCR or other targeted approaches often fail. Hybridization capture involves the use of "bait" nucleotides that capture genomic sequences that are of particular interest for the researcher. Current bait synthesis methods require large-scale oligonucleotide chemical synthesis and/or in vitro transcription. Both RNA and DNA bait generation requires synthesizing template oligonucleotides using phosphoramidite chemistry. Microarray-based synthesis generates oligonucleotides in femtomole scales with high chemical coupling error rates. Templates synthesized at small-scale require enzymatic amplification before use in hybridization capture.The solution proposed here involves a simple and highly efficient method to generate target probes using isothermal amplification. Target sequences are circularized and then amplified by rolling circle amplification. This method generates concatemers comprising thousands of copies of the target seqeuence. Restriction digestion of the amplified product then produces probes to use in target enrichment applications. 

Researchers from UC San Diego have developed RadSenNet, a new approach of sequential fusing of information from radars and cameras. The key idea of sequential fusion is to fundamentally shift the center of focus in radar-camera fusion systems from cameras to radars. This shift enables their invention (RadSegNet) to achieve all-weather perception benefits of radar sensing. Keeping radars as the primary modality ensures reliability in all situations including occlusions, longrange and bad weather.

This technology provides methods for synthesizing a group of naturally occurring compounds, syrbactins, and their derivatives, being of significant commercial value due to the ability of some of the members to inhibit proteasomal activity. TIR-199, for example, is one of the most potent proteasome inhibitors synthesized so far. The efficacy and efficiency of this novel drug candidate in inducing tumor cell death in multiple myeloma, neuroblastoma, and other types of cancer (e.g. kidney, colon, melanoma, ovarian) has been demonstrated using in vitro systems, cell lines, and animal models (reported for the first time for a syrbactin compound). TIR-199 drug candidate is ready for further pre-clinical and eventually clinical studies.  

Bento is an open-source software toolkit that uses single-molecule information to enable spatial analysis at the subcellular scale. Bento ingests molecular coordinates and segmentation boundaries to perform three analyses: defining subcellular domains, annotating localization patterns, and quantifying gene-gene colocalization. The toolkit is compatible with datasets produced by commercial and academic platforms. Bento is integrated with the open-source single-cell analysis software ecosystem.