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African swine fever virus (ASFV) infection is causing devastating outbreaks globally; pig farming has suffered severe economic losses due to the ASFV. Currently, strict biosecurity control measures can mitigate the incidence of ASF. Rapid, cost-effective, and sensitive detection of ASFV can significantly reduce disease transmission and mortality. CRISPR/Cas-associated proteins can detect polymorphisms with high specificity and sensitivity, making them ideal for detecting pathogens. In this study, based on CRISPR/Cas12a integrated with enzymatic recombinase amplification (ERA) technology, a CRISPR/Cas12a detection system capable of identifying ASFV E183L, K205R, and C962R gene sequences has been developed. The ERA-CRISPR/Cas12a detection system detected ASFV precisely without cross-reactivity with other porcine pathogen templates and with a sensitivity detection limit of 10 copies per reaction; it takes 60 minutes to complete the detection process. In combination with this integrated ERA pre-amplification and Cas12a/crRNA cutting assay, it provides a rapid, straightforward, sensitive, and specific method for ASFV detection in the field. [ABSTRACT FROM AUTHOR]

Knowledge graph completion (KGC) involves inferring missing entities or relationships within a knowledge graph, playing a crucial role across various domains, including intelligent question answering, recommendation systems, and dialogue systems. Traditional knowledge graph embedding (KGE) methods have proven effective in utilizing structured data and relationships. However, these methods often overlook the vast amounts of unstructured data and the complex reasoning capabilities required to handle ambiguous queries or rare entities. Recently, the rapid development of large language models (LLMs) has demonstrated exceptional potential in text comprehension and contextual reasoning, offering new prospects for KGC tasks. By using traditional KGE to capture the structural information of entities and relations to generate candidate entities and then reranking them with a generative LLM, the output of the LLM can be constrained to improve reliability. Despite this, new challenges, such as omissions and incorrect responses, arise during the ranking process. To address these issues, a knowledge-guided LLM reasoning for knowledge graph completion (KLR-KGC) framework is proposed. This model retrieves two types of knowledge from the knowledge graph—analogical knowledge and subgraph knowledge—to enhance the LLM's logical reasoning ability for specific tasks while injecting relevant additional knowledge. By integrating a chain-of-thought (CoT) prompting strategy, the model guides the LLM to filter and rerank candidate entities, constraining its output to reduce omissions and incorrect responses. The framework aims to learn and uncover the latent correspondences between entities, guiding the LLM to make reasonable inferences based on supplementary knowledge for more accurate predictions. The experimental results demonstrate that on the FB15k-237 dataset, KLR-KGC outperformed the entity generation model (CompGCN), achieving a 4.8% improvement in MRR and a 5.8% improvement in Hits@1. [ABSTRACT FROM AUTHOR]

Alphaherpesviruses, including herpes simplex virus type 1 (HSV-1), herpes simplex virus type 2 (HSV-2), and varicella-zoster virus (VZV), infect a diverse array of hosts, spanning both humans and animals. Alphaherpesviruses have developed a well-adapted relationship with their hosts through long-term evolution. Some alphaherpesviruses exhibit a typical neurotropic characteristic, which has garnered widespread attention and in-depth research. Virus latency involves the retention of viral genomes without producing infectious viruses. However, under stress, this can be reversed, resulting in lytic infection. Such reactivation events can lead to recurrent infections, manifesting as diseases like herpes labialis, genital herpes, and herpes zoster. Reactivation is a complex process influenced by both viral and host factors, and identifying how latency and reactivation work is vital to developing new antiviral therapies. Recent research highlights a complex interaction among the virus, neurons, and the immune system in regulating alphaherpesvirus latency and reactivation. Neurotropic alphaherpesviruses can breach host barriers to infect neurons, proliferate extensively within their cell bodies, and establish latent infections or spread further. Whether infecting neurons or spreading further, the virus undergoes transmission along axons or dendrites, making this process an indispensable part of the viral life cycle and a critical factor influencing the virus's invasion of the nervous system. Research on the transmission process of neurotropic alphaherpesviruses within neurons can not only deepen our understanding of the virus but can also facilitate the targeted development of corresponding vaccines. This review concentrates on the relationship between the transmission, latency, and activation of alphaherpesviruses within neurons, summarizes recent advancements in the field, and discusses how these findings can inform the design of live virus vaccines for alphaherpesviruses. [ABSTRACT FROM AUTHOR]

Ferritin, an iron storage protein, is ubiquitously distributed across diverse life forms, fulfilling crucial roles encompassing iron retention, conversion, orchestration of cellular iron metabolism, and safeguarding cells against oxidative harm. Noteworthy attributes of ferritin include its innate amenability to facile modification, scalable mass production, as well as exceptional stability and safety. In addition, ferritin boasts unique physicochemical properties, including pH responsiveness, resilience to elevated temperatures, and resistance to a myriad of denaturing agents. Therefore, ferritin serves as the substrate for creating nanomaterials typified by uniform particle dimensions and exceptional biocompatibility. Comprising 24 subunits, each ferritin nanocage demonstrates self-assembly capabilities, culminating in the formation of nanostructures akin to intricate cages. Recent years have witnessed the ascendance of ferritin-based self-assembled nanoparticles, owing to their distinctive physicochemical traits, which confer substantial advantages and wide-ranging applications within the biomedical domain. Ferritin is highly appealing as a carrier for delivering drug molecules and antigen proteins due to its distinctive structural and biochemical properties. This review aims to highlight recent advances in the use of self-assembled ferritin as a novel carrier for antigen delivery and vaccine development, discussing the molecular mechanisms underlying its action, and presenting it as a promising and effective strategy for the future of vaccine development. [ABSTRACT FROM AUTHOR]