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Background Single-guide RNA (sgRNA) is one of the two key components of the clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 genome-editing system. The current commonly used sgRNA structure has a shortened duplex compared with the native bacterial CRISPR RNA (crRNA)–transactivating crRNA (tracrRNA) duplex and contains a continuous sequence of thymines, which is the pause signal for RNA polymerase III and thus could potentially reduce transcription efficiency. Results Here, we systematically investigate the effect of these two elements on knockout efficiency and showed that modifying the sgRNA structure by extending the duplex length and mutating the fourth thymine of the continuous sequence of thymines to cytosine or guanine significantly, and sometimes dramatically, improves knockout efficiency in cells. In addition, the optimized sgRNA structure also significantly increases the efficiency of more challenging genome-editing procedures, such as gene deletion, which is important for inducing a loss of function in non-coding genes. Conclusions By a systematic investigation of sgRNA structure we find that extending the duplex by approximately 5 bp combined with mutating the continuous sequence of thymines at position 4 to cytosine or guanine significantly increases gene knockout efficiency in CRISPR-Cas9-based genome editing experiments.

Members of the low-density lipoprotein receptor (LDLR) family, including LDLRAD3, VLDLR, and ApoER2, were recently described as entry factors for different alphaviruses. However, based on studies with gene edited cells and knockout mice, blockade or abrogation of these receptors does not fully inhibit alphavirus infection, indicating the existence of additional uncharacterized entry factors. Here, we perform a CRISPR-Cas9 genome-wide loss-of-function screen in mouse neuronal cells with a chimeric alphavirus expressing the Eastern equine encephalitis virus (EEEV) structural proteins and identify LDLR as a candidate receptor. Expression of LDLR on the surface of neuronal or non-neuronal cells facilitates binding and infection of EEEV, Western equine encephalitis virus, and Semliki Forest virus. Domain mapping and binding studies reveal a low-affinity interaction with LA domain 3 (LA3) that can be enhanced by concatenation of LA3 repeats. Soluble decoy proteins with multiple LA3 repeats inhibit EEEV infection in cell culture and in mice. Our results establish LDLR as a low-affinity receptor for multiple alphaviruses and highlight a possible path for developing inhibitors that could mitigate infection and disease. Ma et al. identify LDLR as an entry receptor for Eastern equine encephalitis virus (EEEV) and other alphaviruses. Soluble decoy proteins with multiple LA domain 3 repeats of LDLR inhibit EEEV infection in cell culture and mice.

Microprocessor [Drosha–DGCR8 (DiGeorge syndrome critical region gene 8) complex] processing of primary microRNA (pri-miRNA) is the critical first step in miRNA biogenesis, but how the Drosha cleavage site is determined has been unclear. Previous models proposed that the Drosha–DGCR8 complex measures either ∼22 nt from the upper stem–single-stranded RNA (ssRNA, terminal loop) junction or ∼11 nt from the lower stem–ssRNA junction to determine the cleavage site. Here, using miRNA-offset RNAs to determine the Drosha cleavage site, we show that the Microprocessor measures the distances from both the lower and upper stem–ssRNA junctions to determine the cleavage site in human cells, and optimal distances from both structures are critical to the precision of Drosha processing. If the distances are not optimal, Drosha tends to cleave at multiple sites, which can, in turn, generate multiple 5′ isomiRs. Thus, our results also reveal a mechanism of 5′ isomiR generation.

To address the limitations of conventional methods that depend on oversimplified line-loss analysis or single data sources—particularly their low accuracy in complex grid environments and insufficient disaster recovery capabilities—this paper proposes an intelligent topology identification system for distribution networks based on carrier communication technology. The proposed solution combines machine learning algorithms with advanced communication protocols to achieve comprehensive network modeling. By analyzing multidimensional distribution node characteristics, including transmission energy signatures and expert maintenance records, the system generates accurate topology representations. Adaptive control mechanisms are trained using these models to enable fully distributed inspection workflows. The architecture deploys carrier communication networks with optimized channel equalization, significantly improving packet routing efficiency. The experimental results demonstrate that the proposed method enhances topology coverage and network security, strengthens terminal security and other protection measures, and exhibits robust disaster recovery and backup capabilities. Compared with traditional approaches, it achieves higher recognition accuracy, improves system stability, and delivers significant overall performance advantages.

Existing studies indicate that dysregulation or abnormal expression of small nucleolar RNA (snoRNA) is closely associated with various diseases, including lung cancer. Furthermore, these diseases often involve multiple targets, making the redevelopment of traditional medicines highly promising. Accurate prediction of potential snoRNA therapeutic targets is essential for early disease intervention and the redevelopment of traditional medicines. Additionally, researchers have developed artificial intelligence (AI)-based methods to screen and predict potential snoRNA therapeutic targets, thereby advancing traditional drug redevelopment. However, existing methods face challenges such as imbalanced datasets and the dominance of high-degree nodes in graph neural networks (GNNs), which compromise the accuracy of node representations. To address these challenges, we propose an AI model based on variational graph autoencoders (VGAEs) that integrates decoupling and Kolmogorov-Arnold Network (KAN) technologies. The model reconstructs snoRNA-disease graphs by learning snoRNA and disease representations, accurately identifying potential snoRNA therapeutic targets. By decoupling similarity from node degree, the model mitigates the dominance of high-degree nodes, enhances prediction accuracy in scenarios like lung cancer, and leverages KAN technology to improve adaptability and flexibility to new data. Case studies revealed that snoRNA SNORA21 and SNORD33 are abnormally expressed in lung cancer patients and are strong candidates for potential therapeutic targets. These findings validate the proposed model’s effectiveness in identifying therapeutic targets for diseases like lung cancer, supporting early screening and treatment, and advancing the redevelopment of traditional medicines. Data and experimental findings are archived in: https://github.com/shmildsj/data .

As one of the key components of the circuit breaker operating mechanism, the relay can experience performance degradation due to harsh environmental factors, such as salt spray, during operation, which can ultimately affect the normal operation of the circuit breaker and threaten the safe and stable operation of the power system. To effectively evaluate the condition of the relay operating in salt spray environments over the long term, this study conducted accelerated aging experiments on a certain model of auxiliary switch under salt spray conditions using an existing test platform. The relay’s pull-in voltage, release voltage, pull-in time, and release time were analyzed as characteristic parameters affected by salt spray. The results showed that the intrusion of salt spray caused a decline in the coil performance of the relay, which required higher voltage to provide the electromagnetic force needed for operation, leading to an increase in operating voltage. On the other hand, coil degradation also caused a decrease in the electromagnetic force generated by the step voltage, resulting in a slower operating time. Subsequently, a Genetic Algorithm_Back Propagation Neural Network GA_BP) algorithm model suitable for identifying the relay status in this study was established. After optimization by a Genetic Algorithm Neural Network (GA), the recognition accuracy increased from 78.6% to 91.8%, which showed significant improvement. By clarifying the changes in the characteristic parameters of the relay in a salt spray environment and relying on experimental data, this study established a relevant state recognition model. The research results have important engineering application value for understanding the relay operating status of the circuit breaker operating mechanism in salt spray environments, conducting circuit breaker operating mechanism relay life prediction, and preventing circuit breaker operating mechanism failures.

High-voltage switchgear is a key control and protection unit in power systems. The reliable operation of the operating mechanism is essential for the reliable opening and closing of the switchgear. This is a vital guarantee for the safety and stability of the power systems. The spring operating mechanism is a commonly used actuator for circuit breakers at 12–252 kV. However, a reliability estimation method that is convenient, practical and accurate is still lacking. The aim of this paper is to explore a reliability estimation method based on a stress–strength interference reliability theory and a fatigue life theory. The changing rules of the reliability of the main axis, and the closing pawl and opening pawl in the spring operating mechanism during operations, are achieved. The accuracy of the calculated reliability based on theories of stress–strength interference and fatigue life is verified by adopting a test data statistical reliability model based on Weibull distribution. The results show that the reliability estimation method based on stress–strength interference and fatigue life theories has a high degree of confidence. The maximum tolerance is 0.024. The study would help in providing a useful reference for the optimization and durability estimation of a spring operating mechanism and its key components in high-voltage circuit breakers.

Although the interferon (IFN) signaling pathway is a key host mechanism to restrict infection of a diverse range of viral pathogens, its unrestrained activity either at baseline or in the context of an immune response can result in host cell damage and injury. Here, we used a genome-wide CRISPR-Cas9 screen and identified the DNA binding protein Barrier-to-autointegration factor 1 (Banf1) as a modulator of basal cell-intrinsic immunity. A loss of Banf1 expression resulted in higher level of cytosolic double-stranded DNA at baseline, which triggered IFN-stimulated gene expression via a cGAS-STING-IRF3 axis that did not require type I IFN or STAT1 signaling. Our experiments define a regulatory network in which Banf1 limits basal inflammation by preventing self DNA accumulation in the cytosol. Although the pathogen recognition receptor pathways that activate cell-intrinsic antiviral responses are well delineated, less is known about how the host regulates this response to prevent sustained signaling and possible immune-mediated damage. Using a genome-wide CRISPR-Cas9 screening approach to identify host factors that modulate interferon-stimulated gene (ISG) expression, we identified the DNA binding protein Barrier-to-autointegration factor 1 (Banf1), a previously described inhibitor of retrovirus integration, as a modulator of basal cell-intrinsic immunity. Ablation of Banf1 by gene editing resulted in chromatin activation near host defense genes with associated increased expression of ISGs, including Oas2 , Rsad2 (viperin), Ifit1 , and ISG15 . The phenotype in Banf1-deficient cells occurred through a cGAS-, STING-, and IRF3-dependent signaling axis, was associated with reduced infection of RNA and DNA viruses, and was reversed in Banf1 complemented cells. Confocal microscopy and biochemical studies revealed that a loss of Banf1 expression resulted in higher level of cytosolic double-stranded DNA at baseline. Our study identifies an undescribed role for Banf1 in regulating the levels of cytoplasmic DNA and cGAS-dependent ISG homeostasis and suggests possible therapeutic directions for promoting or inhibiting cell-intrinsic innate immune responses. IMPORTANCE Although the interferon (IFN) signaling pathway is a key host mechanism to restrict infection of a diverse range of viral pathogens, its unrestrained activity either at baseline or in the context of an immune response can result in host cell damage and injury. Here, we used a genome-wide CRISPR-Cas9 screen and identified the DNA binding protein Barrier-to-autointegration factor 1 (Banf1) as a modulator of basal cell-intrinsic immunity. A loss of Banf1 expression resulted in higher level of cytosolic double-stranded DNA at baseline, which triggered IFN-stimulated gene expression via a cGAS-STING-IRF3 axis that did not require type I IFN or STAT1 signaling. Our experiments define a regulatory network in which Banf1 limits basal inflammation by preventing self DNA accumulation in the cytosol.

Pol III promoters such as U6 are commonly used to express small RNAs, including small interfering RNA, short hairpin RNA, and guide RNA, for the clustered regularly interspaced short palindromic repeats genome-editing system. However, whether the small RNAs were precisely expressed as desired has not been studied. Here, using deep sequencing to analyze small RNAs, we show that, for mouse U6 promoter, sequences immediately upstream of the putative initiation site, which is often modified to accommodate the restriction enzyme sites that enable easy cloning of small RNAs, are critical for precise transcription initiation. When the promoter is kept unmodified, transcription starts precisely from the first available A or G within the range of positions −1 to +2. In addition, we show that transcription from another commonly used pol III promoter, H1, starts at multiple sites, which results in variability at the 5′ end of the transcripts. Thus, inaccuracy of 5′ end of small RNA transcripts might be a common problem when using these promoters to express small RNAs based on currently believed concepts. Our study provides general guidelines for minimizing the variability of initiation, thereby enabling more accurate expression of small RNAs.