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The complexity of eukaryotic organisms is intricately tied to transcriptome‐level processes, notably alternative splicing and the precise modulation of gene expression through a sophisticated interplay involving RNA‐binding protein (RBP) networks and their RNA targets. Recent advances in our understanding of the molecular pathways responsible for this control have paved the way for the development of tools capable of steering and managing RNA regulation and gene expression. The fusion between a rapidly developing understanding of endogenous RNA regulation and the burgeoning capabilities of CRISPR‐Cas and other programmable RBP platforms has given rise to an exciting frontier in engineered RNA regulators. This review offers an overview of the existing toolkit for constructing synthetic RNA regulators using programmable RBPs and effector domains, capable of altering RNA sequence composition or fate, and explores their diverse applications in both basic research and therapeutic contexts.

 

The increasing demand for data-driven machine learning (ML) models has led to the emergence of model markets, where a broker collects personal data from data owners to produce high-usability ML models. To incentivize data owners to share their data, the broker needs to price data appropriately while protecting their privacy. For equitable data valuation , which is crucial in data pricing, Shapley value has become the most prevalent technique because it satisfies all four desirable properties in fairness: balance, symmetry, zero element, and additivity. For the right to be forgotten , which is stipulated by many data privacy protection laws to allow data owners to unlearn their data from trained models, the sharded structure in ML model training has become a de facto standard to reduce the cost of future unlearning by avoiding retraining the entire model from scratch. In this paper, we explore how the sharded structure for the right to be forgotten affects Shapley value for equitable data valuation in model markets. To adapt Shapley value for the sharded structure, we propose S-Shapley value, a sharded structure-based Shapley value, which satisfies four desirable properties for data valuation. Since we prove that computing S-Shapley value is #P-complete, two sampling-based methods are developed to approximate S-Shapley value. Furthermore, to efficiently update valuation results after data owners unlearn their data, we present two delta-based algorithms that estimate the change of data value instead of the data value itself. Experimental results demonstrate the efficiency and effectiveness of the proposed algorithms. 

The crescent-shaped bacterium Caulobacter crescentus divides asymmetrically into a sessile (stalked) cell and a motile (flagellated) cell. This dimorphic cell division cycle is driven by the asymmetric appearance of scaffolding proteins at the cell’s stalk and flagellum poles. The scaffolding proteins recruit enzyme complexes that phosphorylate and degrade a master transcription factor, CtrA, and the abundance and phosphorylation state of CtrA control the onset of DNA synthesis and the differentiation of stalked and flagellated cell types. In this study, we use a Turing-pattern mechanism to simulate the spatiotemporal dynamics of scaffolding proteins in Caulobacter and how they influence the abundance and intracellular distribution of CtrA-P. Our mathematical model captures crucial features of wild-type and mutant strains and predicts the distributions of CtrA-P and signaling proteins in mutant strains. Our model accounts for Caulobacter polar morphogenesis and shows how spatial localization and phosphosignaling cooperate to establish asymmetry during the cell cycle. 

A model DC material based on ethylene propylene rubber (EPR) including the pure EPR and the EPR-based nanodielectrics incorporated with two different nanoclays, Kaoline and Talc, under operational conditions was investigated. The operational conditions include a 20 kV/mm electric field at 25 °C, a 20 kV/mm electric field at 50 °C with a thermal gradient, and a 40 kV/mm electric field at 50 °C with a thermal gradient and polarity reversal. Space charge distribution, surface potential, and electrical conductivity were measured to characterize the model DC material and interpret the discrete charge dynamics in the bulk and at the interface of the three samples. The experimental results revealed that the electrical conductivity of Talc-filled nanodielectric has the least dependency on electric field and temperature, which reduces the conductivity gradient across the dielectric. Moreover, the successful suppression of space charge and the lower dielectric time constant in the Talc-filled nanodielectric result in a tuning electric field in the bulk not only under normal operating conditions but also more importantly under polarity reversal conditions. The maximum of absolute charge density decreases from 10.6 C/m 3 for EPR to 2.9 C/m 3 for the Talc-filled nanodielectric under 40 kV/mm with polarity reversal and at 50 °C with the thermal gradient. The maximum of local electric field enhancement for the mentioned condition reduces significantly from 97 kV/mm, 142% enhancement, for EPR to 45 kV/mm, only 12.5% enhancement, for the Talc-filled nanodielectric. 

Abstract Soft electrothermal actuators have drawn extensive attention in recent years for their promising applications in biomimetic and biomedical areas. Most soft electrothermal actuators reported so far demonstrated uniform bending deformation, due to the deposition based fabrication of the conductive heater layer from nanomaterial-based solutions, which generally provides uniform heating capacity and uniform bending deformation. In this paper, a soft electrothermal actuator that can provide twisting deformation was designed and fabricated. A metallic microfilament heater of the soft twisting actuator was directly printed using electrohydrodynamic (EHD) printing, and embedded between two structural layers, a polyimide film and a polydimethylsiloxane layer, with distinct thermal expansion properties. Assisted by the direct patterning capabilities of EHD printing, a skewed heater pattern was designed and printed. This skewed heater pattern not only produces a skewed parallelogram-shaped temperature field, but also changes the stiffness anisotropy of the actuator, leading to twisting deformation with coupled bending. A theoretical kinematic model was built for the twisting actuator to describe its twisting deformation under different actuation effects. Based on that model, influence of design parameters on the twisting angle and motion trajectory of the twisting actuator were studied and validated by experiments. Finite element analysis was utilized for the thermal and deformation analysis of the actuator. The fabricated twisting actuator was characterized on its heating and twisting performance at different supply voltages. Using three twisting actuators, a soft gripper was designed and fabricated to implement pick-and-place operations of delicate objects.