Abstract: The present disclosure, at least in part, provides RNA cleavage based engineered bi-stable toggle switch utilizing the Programmable Endonucleolytic Scission-Induced Stability Tuning (PERSIST) platform. Also provided herein, are vectors encoding the engineered bi-stable toggle switch, and uses thereof.

Abstract: Disclosed herein are polynucleotides encoding multi-epitope polypeptides and assemblies thereof, and their use for treating or limiting Toxoplasma gondii infection.

Abstract: Compositions and methods are described for inducing an immune response against an immunogen in humans. The induced immune response is obtained by administering a heterologous prime-boost combination of an in vitro transcribed (IVT) self-replicating RNA (repRNA) and an adenovirus vector. The compositions and methods can be used to provide a protective immunity against a disease, such as a viral infection or a cancer, in humans.

Abstract: Provided herein are genetic circuits and encoded RNA transcripts that produce an output molecule in response to an RNA cleavage event that removes a degradation signal. In some embodiments, the genetic circuits described herein may be used for detecting RNA cleaver activities (e.g., in a cell). Methods of using the genetic circuits described herein in diagnostic or therapeutic applications are also provided.

Abstract: The present disclosure relates to synthetic oncolytic viruses comprising a lipid nanoparticle comprising one or more types of lipid and a self-amplifying replicon RNA comprising a sequence that encodes an immunomodulatory molecule.

Abstract: Provided herein are feedback controller circuits and cell state classifiers for tunable phosphorylation-based transcriptional regulation of gene expression in cells based on intracellular miRNA profiles and degradation by small molecules. Also provided are methods of using feedback controller circuits and cell state classifiers for determining the cell state, and methods of treating cells and subjects using feedback controller circuits and cell state classifiers encoding therapeutic output molecules.

Abstract: The present disclosure, at least in part, relates to an engineered RNA (e.g., microRNA and sgRNA), in the absence of an input signal, that is engineered to have a large enough energy gap between the formations of a first secondary structure, which is unrecognizable by an actuator, and a second secondary structure, which is recognizable by an actuator (e.g., Drosha and Cas protein).

Abstract: Provided herein are genetic circuits and encoded RNA transcripts that produce an output molecule in response to an RNA cleavage event that removes a degradation signal. In some embodiments, the genetic circuits described herein may be used for detecting RNA cleaver activities (e.g., in a cell). Methods of using the genetic circuits described herein in diagnostic or therapeutic applications are also provided.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for neural network adaptive beamforming for multichannel speech recognition are disclosed. In one aspect, a method includes the actions of receiving a first channel of audio data corresponding to an utterance and a second channel of audio data corresponding to the utterance. The actions further include generating a first set of filter parameters for a first filter based on the first channel of audio data and the second channel of audio data and a second set of filter parameters for a second filter based on the first channel of audio data and the second channel of audio data. The actions further include generating a single combined channel of audio data. The actions further include inputting the audio data to a neural network. The actions further include providing a transcription for the utterance.

Abstract: The present disclosure relates to synthetic oncolytic viruses comprising a lipid nanoparticle comprising one or more types of lipid and a self-amplifying replicon RNA comprising a sequence that encodes an immunomodulatory molecule.

Abstract: Provided herein are genetic circuits and cell state classifiers for detecting the microRNA profile of a cell. The cell state classifiers of the present disclosure utilize phosphorylation state of a transcription factor to control classifier output. Kinases and phosphatase pairs that function in phosphorylating or dephosphorylating the transcription factor are integrated into the circuit, their expression tuned by the presence of microRNAs of interest (e.g., in a cell). The genetic circuits and cell state classifiers may be used in various applications (e.g., therapeutic or diagnostic applications).

Abstract: A method includes receiving a training example for a listen-attend-spell (LAS) decoder of a two-pass streaming neural network model and determining whether the training example corresponds to a supervised audio-text pair or an unpaired text sequence. When the training example corresponds to an unpaired text sequence, the method also includes determining a cross entropy loss based on a log probability associated with a context vector of the training example. The method also includes updating the LAS decoder and the context vector based on the determined cross entropy loss.

Abstract: The present disclosure, at least in part, relates to an engineered incoherent feed forward loop (iFFL) comprising a first transcription unit encoding an endoribonuclease and a second transcription unit encoding an output molecule and an endoribonuclease target site located in the 5? UTR of the output molecule coding sequence. The engineered iFFL, at least in part, can be used for sustained expression of an output molecule despite of transcription resource disturbance in a given environment.

Abstract: The present disclosure, at least in part, relates to a miRNA based logic gate that comprises an engineered RNA carrier that comprises an nuclear export signal, a target site for a first miRNA and a pre-miRNA sequence for a second miRNA. Also provided by the disclosure are recombinant viruses (e.g., recombinant adeno-associated viruses (rAAV)) for delivery of the miRNA based logic gates.

Abstract: A method includes receiving a training example for a listen-attend-spell (LAS) decoder of a two-pass streaming neural network model and determining whether the training example corresponds to a supervised audio-text pair or an unpaired text sequence. When the training example corresponds to an unpaired text sequence, the method also includes determining a cross entropy loss based on a log probability associated with a context vector of the training example. The method also includes updating the LAS decoder and the context vector based on the determined cross entropy loss.

Abstract: Engineered synthetic RNA-based genetic circuits are provided that are regulated exclusively at the post-transcriptional level.

Abstract: The present disclosure, at least in part, relates to a miRNA based logic gate that comprises an engineered RNA carrier that comprises an nuclear export signal, a target site for a first miRNA and a pre-miRNA sequence for a second miRNA. Also provided by the disclosure are recombinant viruses (e.g., recombinant adeno-associated viruses (rAAV)) for delivery of the miRNA based logic gates.

Abstract: A method of generating diverse and natural text-to-speech (TTS) samples includes receiving a text and generating a speech sample based on the text using a TTS model. A training process trains the TTS model to generate the speech sample by receiving training samples. Each training sample includes a spectrogram and a training text corresponding to the spectrogram. For each training sample, the training process identifies speech units associated with the training text. For each speech unit, the training process generates a speech embedding, aligns the speech embedding with a portion of the spectrogram, extracts a latent feature from the aligned portion of the spectrogram, and assigns a quantized embedding to the latent feature. The training process generates the speech sample by decoding a concatenation of the speech embeddings and a quantized embeddings for the speech units associated with the training text corresponding to the spectrogram.

Abstract: Provided herein are sequestrons for detecting an miRNA profile indicative of a cell state and expressing an output molecule in cells having such an miRNA profile. Also provided are methods of using sequestrons provided herein.

Abstract: Provided herein are genetic circuits and cell state classifiers for detecting the microRNA profile of a cell. The cell state classifiers of the present disclosure are designed to incorporate multiple genetic circuits integrated together by transcriptional or translational control. Multiple inputs can be sensed simultaneously by coupling their detection to different portions of the genetic circuit such that the output molecule is produced only when the correct input profile of miRNAs is detected. The genetic circuits and cell state classifiers may be used in various applications (e.g., therapeutic or diagnostic applications).