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Increasing evidence suggests that long noncoding RNAs (lncRNAs) play crucial roles in various biological processes. However, little is known about the effects of lncRNAs on autophagy. Here we report that a lncRNA, termed cardiac autophagy inhibitory factor (CAIF), suppresses cardiac autophagy and attenuates myocardial infarction by targeting p53-mediated myocardin transcription. Myocardin expression is upregulated upon H 2 O 2 and ischemia/reperfusion, and knockdown of myocardin inhibits autophagy and attenuates myocardial infarction. p53 regulates cardiomyocytes autophagy and myocardial ischemia/reperfusion injury by regulating myocardin expression. CAIF directly binds to p53 protein and blocks p53-mediated myocardin transcription, which results in the decrease of myocardin expression. Collectively, our data reveal a novel CAIF-p53-myocardin axis as a critical regulator in cardiomyocyte autophagy, which will be potential therapeutic targets in treatment of defective autophagy-associated cardiovascular diseases. Little is known about the role of long lncRNAs in autophagy. The authors identify lncCAIF, and show that it suppresses cardiac autophagy and attenuates myocardial infarction by targeting p53 -mediated transcription of myocardin.

Arabidopsis mutants produced by constitutive overexpression of the CRISPR/Cas9 genome editing system are usually mosaics in the T1 generation. In this study, we used egg cell-specific promoters to drive the expression of Cas9 and obtained non-mosaic T1 mutants for multiple target genes with high efficiency. Comparisons of 12 combinations of eight promoters and two terminators found that the efficiency of the egg cell-specific promoter-controlled CRISPR/Cas9 system depended on the presence of a suitable terminator, and the composite promoter generated by fusing two egg cell-specific promoters resulted in much higher efficiency of mutation in the T1 generation compared with the single promoters.

Dysregulated autophagy is associated with many pathological disorders such as cardiovascular diseases. Emerging evidence has suggested that circular RNAs (circRNAs) have important roles in some biological processes. However, it remains unclear whether circRNAs participate in the regulation of autophagy. Here we report that a circRNA, termed autophagy-related circular RNA (ACR), represses autophagy and myocardial infarction by targeting Pink1-mediated phosphorylation of FAM65B. ACR attenuates autophagy and cell death in cardiomyocytes. Moreover, ACR protects the heart from ischemia/reperfusion (I/R) injury and reduces myocardial infarct sizes. We identify Pink1 as an ACR target to mediate the function of ACR in cardiomyocyte autophagy. ACR activates Pink1 expression through directly binding to Dnmt3B and blocking Dnmt3B-mediated DNA methylation of Pink1 promoter. Pink1 suppresses autophagy and Pink1 transgenic mice show reduced myocardial infarction sizes. Further, we find that FAM65B is a downstream target of Pink1 and Pink1 phosphorylates FAM65B at serine 46. Phosphorylated FAM65B inhibits autophagy and cell death in the heart. Our findings reveal a novel role for the circRNA in regulating autophagy and ACR-Pink1-FAM65B axis as a regulator of autophagy in the heart will be potential therapeutic targets in treatment of cardiovascular diseases.

Conducting polymers, such as the p -doped poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS), have enabled the development of an array of opto- and bio-electronics devices. However, to make these technologies truly pervasive, stable and easily processable, n -doped conducting polymers are also needed. Despite major efforts, no n -type equivalents to the benchmark PEDOT:PSS exist to date. Here, we report on the development of poly(benzimidazobenzophenanthroline):poly(ethyleneimine) (BBL:PEI) as an ethanol-based n -type conductive ink. BBL:PEI thin films yield an n -type electrical conductivity reaching 8 S cm −1 , along with excellent thermal, ambient, and solvent stability. This printable n -type mixed ion-electron conductor has several technological implications for realizing high-performance organic electronic devices, as demonstrated for organic thermoelectric generators with record high power output and n -type organic electrochemical transistors with a unique depletion mode of operation. BBL:PEI inks hold promise for the development of next-generation bioelectronics and wearable devices, in particular targeting novel functionality, efficiency, and power performance. The development of n -type conductive polymer inks is critical for the development of next-generation opto-electronic devices that rely on efficient hole and electron transport. Here, the authors report an alcohol-based, high performance and stable n -type conductive ink for printed electronics.

Highly sensitive and multimodal sensors have recently emerged for a wide range of applications, including epidermal electronics, robotics, health‐monitoring devices and human–machine interfaces. However, cross‐sensitivity prevents accurate measurements of the target input signals when a multiple of them are simultaneously present. Therefore, the selection of the multifunctional materials and the design of the sensor structures play a significant role in multimodal sensors with decoupled sensing mechanisms. Hence, this review article introduces varying methods to decouple different input signals for realizing truly multimodal sensors. Early efforts explore different outputs to distinguish the corresponding input signals applied to the sensor in sequence. Next, this study discusses the methods for the suppression of the interference, signal correction, and various decoupling strategies based on different outputs to simultaneously detect multiple inputs. The recent insights into the materials' properties, structure effects, and sensing mechanisms in recognition of different input signals are highlighted. The presence of the various decoupling methods also helps avoid the use of complicated signal processing steps and allows multimodal sensors with high accuracy for applications in bioelectronics, robotics, and human–machine interfaces. Finally, current challenges and potential opportunities are discussed in order to motivate future technological breakthroughs. This review article examines the evolution of multimodal sensors in detecting numerous input signals from discrimination and interference suppression to decoupling. The decoupled mechanisms exploit various materials, structures, and sensing principles. The current limitations and future opportunities also inspire the next‐generation flexible and stretchable sensors with optimized sensing performance to truly decouple complex input signals/stimuli for practical applications.

DNA origami-based nanorobot presents thrombin to cause tumor infarction after specific recognition of a tumor vessel marker. Nanoscale robots have potential as intelligent drug delivery systems that respond to molecular triggers 1 , 2 , 3 , 4 . Using DNA origami we constructed an autonomous DNA robot programmed to transport payloads and present them specifically in tumors. Our nanorobot is functionalized on the outside with a DNA aptamer that binds nucleolin, a protein specifically expressed on tumor-associated endothelial cells 5 , and the blood coagulation protease thrombin within its inner cavity. The nucleolin-targeting aptamer serves both as a targeting domain and as a molecular trigger for the mechanical opening of the DNA nanorobot. The thrombin inside is thus exposed and activates coagulation at the tumor site. Using tumor-bearing mouse models, we demonstrate that intravenously injected DNA nanorobots deliver thrombin specifically to tumor-associated blood vessels and induce intravascular thrombosis, resulting in tumor necrosis and inhibition of tumor growth. The nanorobot proved safe and immunologically inert in mice and Bama miniature pigs. Our data show that DNA nanorobots represent a promising strategy for precise drug delivery in cancer therapy.

In recent decades, the environmental protection and long-term sustainability have become the focus of attention due to the increasing pollution generated by the intense industrialization. To overcome these issues, environmental catalysis has increasingly been used to solve the negative impact of pollutants emission on the global environment and human health. Supported platinum-metal-group (PGM) materials are commonly utilized as the state-of-the-art catalysts to eliminate gaseous pollutants but large quantities of PGMs are required. By comparison, single-atom site catalysts (SACs) have attracted much attention in catalysis owing to their 100% atom efficiency and unique catalytic performances towards various reactions. Over the past decade, we have witnessed burgeoning interests of SACs in heterogeneous catalysis. However, to the best of our knowledge, the systematic summary and analysis of SACs in catalytic elimination of environmental pollutants has not yet been reported. In this paper, we summarize and discuss the environmental catalysis applications of SACs. Particular focus was paid to automotive and stationary emission control, including model reaction (CO oxidation, NO reduction and hydrocarbon oxidation), overall reaction (three-way catalytic and diesel oxidation reaction), elimination of volatile organic compounds (formaldehyde, benzene, and toluene), and removal/decomposition of other pollutants (Hg 0 and SO 3 ). Perspectives related to further challenges, directions and design strategies of single-atom site catalysts in environmental catalysis were also provided.

Uncovering the underlying biophysical principles of emergent collective computational abilities, such as working memory, in neural circuits is one of the most essential concerns in modern neuroscience. Working memory system is often desired to be robust against noises. Such systems can be highly flexible for adapting environmental demands. How neural circuits reconfigure themselves according to the cognitive task requirement remains unclear. Previous studies explored the robustness and the flexibility in working memory by tracing individual dynamical trajectories in a limited time scale, where the accuracy of the results depends on the volume of the collected statistical data. Inspired by thermodynamics and statistical mechanics in physical systems, we developed a non-equilibrium landscape and flux framework for studying the neural network dynamics. Applying this approach to a biophysically based working memory model, we investigated how changes in the recurrent excitation mediated by slow NMDA receptors within a selective population and mutual inhibition mediated by GABAergic interneurons between populations affect the robustness against noises. This is realized through quantifying the underlying non-equilibrium potential landscape topography and the kinetics of state switching. We found that an optimal compromise for a working memory circuit between the robustness and the flexibility can be achieved through the emergence of an intermediate state between the working memory states. An optimal combination of both increased self-excitation and inhibition can enhance the flexibility to external signals without significantly reducing the robustness to the random fluctuations. Furthermore, we found that the enhanced performance in working memory is supported by larger energy consumption. Our approach can facilitate the design of new network structure for cognitive functions with the optimal balance between performance and cost. Our work also provides a new paradigm for exploring the underlying mechanisms of many cognitive functions based on non-equilibrium physics.

This study aims to examine the relationship between green investment (GI), fiscal policy (FP), environmental tax (ET), energy price (EP), natural resource rent (NRR), and the consumption of clean energy (CE) to promote sustainable development in Cambodia for the period 1990–2021. The study implemented linear and nonlinear frameworks to document explanatory variables’ potential effects on clean energy consumption in the long and short run. The research findings demonstrate a robust and favorable connection between GI, FP, ET and CE, both in the long term and short term. An augmentation in GI results in the establishment of sustainable growth in the utilization of renewable energy, thereby underscoring the significance of green initiatives in advancing clean energy technologies. Fiscal policies, encompassing tax incentives and subsidies, exert a substantial and enduring influence on expanding renewable energy sources. Implementing environmental taxes catalyzes the demand for clean energy, significantly preserving the environment and promoting sustainable energy practices. Furthermore, the study illuminates the inverse correlation between oil prices and REC. Adopting renewable energy sources may face obstacles in the form of elevated oil prices, as conventional energy sources maintain a cost advantage. On the contrary, decreased oil prices and natural resource rent incentivize transitioning towards using clean energy. Countries that heavily depend on the export of natural resources may display a reduced inclination to invest in renewable energy, commonly called the “resource curse” phenomenon. This study provides valuable insights into the intricate interplay of multiple factors that influence renewable energy consumption and contribute to sustainable development. Policymakers, businesses, and researchers can employ these findings to develop productive strategies that advance the inclusion of clean energy, tackle potential challenges, and cultivate a more environmentally friendly and sustainable future.

Background To accelerate the application of the CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/ CRISPR-associated protein 9) system to a variety of plant species, a toolkit with additional plant selectable markers, more gRNA modules, and easier methods for the assembly of one or more gRNA expression cassettes is required. Results We developed a CRISPR/Cas9 binary vector set based on the pGreen or pCAMBIA backbone, as well as a gRNA (guide RNA) module vector set, as a toolkit for multiplex genome editing in plants. This toolkit requires no restriction enzymes besides Bsa I to generate final constructs harboring maize-codon optimized Cas9 and one or more gRNAs with high efficiency in as little as one cloning step. The toolkit was validated using maize protoplasts, transgenic maize lines, and transgenic Arabidopsis lines and was shown to exhibit high efficiency and specificity. More importantly, using this toolkit, targeted mutations of three Arabidopsis genes were detected in transgenic seedlings of the T1 generation. Moreover, the multiple-gene mutations could be inherited by the next generation. Conclusions We developed a toolkit that facilitates transient or stable expression of the CRISPR/Cas9 system in a variety of plant species, which will facilitate plant research, as it enables high efficiency generation of mutants bearing multiple gene mutations.