Translational Efficiency Research Articles

Gle1 is required for tRNA to stimulate Dbp5 ATPase activity in vitro and promote Dbp5-mediated tRNA export in vivo in Saccharomyces cerevisiae

Cells must maintain a pool of processed and charged transfer RNAs (tRNA) to sustain translation capacity and efficiency. Numerous parallel pathways support the processing and directional movement of tRNA in and out of the nucleus to meet this cellular demand. Recently, several proteins known to control messenger RNA (mRNA) transport were implicated in tRNA export. The DEAD-box Protein 5, Dbp5, is one such example. In this study, genetic and molecular evidence demonstrates that Dbp5 functions parallel to the canonical tRNA export factor Los1. In vivo co-immunoprecipitation data further shows Dbp5 is recruited to tRNA independent of Los1, Msn5 (another tRNA export factor), or Mex67 (mRNA export adaptor), which contrasts with Dbp5 recruitment to mRNA that is abolished upon loss of Mex67 function. However, as with mRNA export, overexpression of Dbp5 dominant-negative mutants indicates a functional ATPase cycle and that binding of Dbp5 to Gle1 is required by Dbp5 to direct tRNA export. Biochemical characterization of the Dbp5 catalytic cycle demonstrates the direct interaction of Dbp5 with tRNA (or double-stranded RNA) does not activate Dbp5 ATPase activity, rather tRNA acts synergistically with Gle1 to fully activate Dbp5. These data suggest a model where Dbp5 directly binds tRNA to mediate export, which is spatially regulated via Dbp5 ATPase activation at nuclear pore complexes by Gle1.

Gle1 is required for tRNA to stimulate Dbp5 ATPase activity in vitro and promote Dbp5-mediated tRNA export in vivo in Saccharomyces cerevisiae.

Cells must maintain a pool of processed and charged transfer RNAs (tRNA) to sustain translation capacity and efficiency. Numerous parallel pathways support the processing and directional movement of tRNA in and out of the nucleus to meet this cellular demand. Recently, several proteins known to control messenger RNA (mRNA) transport were implicated in tRNA export. The DEAD-box Protein 5, Dbp5, is one such example. In this study, genetic and molecular evidence demonstrates that Dbp5 functions parallel to the canonical tRNA export factor Los1. In vivo co-immunoprecipitation data further shows Dbp5 is recruited to tRNA independent of Los1, Msn5 (another tRNA export factor), or Mex67 (mRNA export adaptor), which contrasts with Dbp5 recruitment to mRNA that is abolished upon loss of Mex67 function. However, as with mRNA export, overexpression of Dbp5 dominant-negative mutants indicates a functional ATPase cycle and that binding of Dbp5 to Gle1 is required by Dbp5 to direct tRNA export. Biochemical characterization of the Dbp5 catalytic cycle demonstrates the direct interaction of Dbp5 with tRNA (or double-stranded RNA) does not activate Dbp5 ATPase activity, rather tRNA acts synergistically with Gle1 to fully activate Dbp5. These data suggest a model where Dbp5 directly binds tRNA to mediate export, which is spatially regulated via Dbp5 ATPase activation at nuclear pore complexes by Gle1.

Epitranscriptomics m6A analyses reveal distinct m6A marks under tumor necrosis factor α (TNF-α)-induced apoptotic conditions in HeLa cells.

Tumor necrosis factor-α (TNF-α) is a ligand that induces both intrinsic and extrinsic apoptotic pathways in HeLa cells by modulating complex gene regulatory mechanisms. However, the full spectrum of TNF-α-modulated epitranscriptomic m6A marks is unknown. We employed a genomewide approach to examine the extent of m6A RNA modifications under TNF-α-modulated apoptotic conditions in HeLa cells. miCLIP-seq analyses revealed a plethora of m6A marks on 632 target mRNAs with an enrichment on 99 mRNAs associated with apoptosis. Interestingly, the m6A RNA modification patterns were quite different under cisplatin- and TNF-α-mediated apoptotic conditions. We then examined the abundance and translational efficiencies of several mRNAs under METTL3 knockdown and/or TNF-α treatment conditions. Our analyses showed changes in the translational efficiency of TP53INP1 mRNA based on the polysome profile analyses. Additionally, TP53INP1 protein amount was modulated by METTL3 knockdown upon TNF-α treatment but not CP treatment, suggesting the existence of a pathway-specific METTL3-TP53INP1 axis. Congruently, METLL3 knockdown sensitized HeLa cells to TNF-α-mediated apoptosis, which was also validated in a zebrafish larval xenograft model. These results suggest that apoptotic pathway-specific m6A methylation marks exist in cells and TNF-α-METTL3-TP53INP1 axis modulates TNF-α-mediated apoptosis in HeLa cells.

N-acetyltransferase 10 regulates alphavirus replication via N4-acetylcytidine (ac4C) modification of the lymphocyte antigen six family member E (LY6E) mRNA.

Epitranscriptomic RNA modifications can regulate the stability of mRNA and affect cellular and viral RNA functions. The N4-acetylcytidine (ac4C) modification in the RNA viral genome was recently found to promote viral replication; however, the mechanism by which RNA acetylation in the host mRNA regulates viral replication remains unclear. To help elucidate this mechanism, the roles of N-acetyltransferase 10 (NAT10) and ac4C during the infection and replication processes of the alphavirus, Sindbis virus (SINV), were investigated. Cellular NAT10 was upregulated, and ac4C modifications were promoted after alphavirus infection, while the loss of NAT10 or inhibition of its N-acetyltransferase activity reduced alphavirus replication. The NAT10 enhanced alphavirus replication as it helped to maintain the stability of lymphocyte antigen six family member E mRNA, which is a multifunctional interferon-stimulated gene that promotes alphavirus replication. The ac4C modification was thus found to have a non-conventional role in the virus life cycle through regulating host mRNA stability instead of viral mRNA, and its inhibition could be a potential target in the development of new alphavirus antivirals.IMPORTANCEThe role of N4-acetylcytidine (ac4C) modification in host mRNA and virus replication is not yet fully understood. In this study, the role of ac4C in the regulation of Sindbis virus (SINV), a prototype alphavirus infection, was investigated. SINV infection results in increased levels of N-acetyltransferase 10 (NAT10) and increases the ac4C modification level of cellular RNA. The NAT10 was found to positively regulate SINV infection in an N-acetyltransferase activity-dependent manner. Mechanistically, the NAT10 modifies lymphocyte antigen six family member E (LY6E) mRNA-the ac4C modification site within the 3'-untranslated region (UTR) of LY6E mRNA, which is essential for its translation and stability. The findings of this study demonstrate that NAT10 regulated mRNA stability and translation efficiency not only through the 5'-UTR or coding sequence but also via the 3'-UTR region. The ac4C modification of host mRNA stability instead of viral mRNA impacting the viral life cycle was thus identified, indicating that the inhibition of ac4C could be a potential target when developing alphavirus antivirals.

Characterization and optimization of 5´ untranslated region containing poly-adenine tracts in Kluyveromyces marxianus using machine-learning model

BackgroundThe 5´ untranslated region (5´ UTR) plays a key role in regulating translation efficiency and mRNA stability, making it a favored target in genetic engineering and synthetic biology. A common feature found in the 5´ UTR is the poly-adenine (poly(A)) tract. However, the effect of 5´ UTR poly(A) on protein production remains controversial. Machine-learning models are powerful tools for explaining the complex contributions of features, but models incorporating features of 5´ UTR poly(A) are currently lacking. Thus, our goal is to construct such a model, using natural 5´ UTRs from Kluyveromyces marxianus, a promising cell factory for producing heterologous proteins.ResultsWe constructed a mini-library consisting of 207 5´ UTRs harboring poly(A) and 34 5´ UTRs without poly(A) from K. marxianus. The effects of each 5´ UTR on the production of a GFP reporter were evaluated individually in vivo, and the resulting protein abundance spanned an approximately 450-fold range throughout. The data were used to train a multi-layer perceptron neural network (MLP-NN) model that incorporated the length and position of poly(A) as features. The model exhibited good performance in predicting protein abundance (average R2 = 0.7290). The model suggests that the length of poly(A) is negatively correlated with protein production, whereas poly(A) located between 10 and 30 nt upstream of the start codon (AUG) exhibits a weak positive effect on protein abundance. Using the model as guidance, the deletion or reduction of poly(A) upstream of 30 nt preceding AUG tended to improve the production of GFP and a feruloyl esterase. Deletions of poly(A) showed inconsistent effects on mRNA levels, suggesting that poly(A) represses protein production either with or without reducing mRNA levels.ConclusionThe effects of poly(A) on protein production depend on its length and position. Integrating poly(A) features into machine-learning models improves simulation accuracy. Deleting or reducing poly(A) upstream of 30 nt preceding AUG tends to enhance protein production. This optimization strategy can be applied to enhance the yield of K. marxianus and other microbial cell factories.

Associations of MMP9 polymorphism with the risk of severe pneumonia in a Southern Chinese children population

BackgroundSevere pneumonia frequently causes irreversible sequelae and represents a major health burden for children under the age of 5. Matrix Metallopeptidase 9 (MMP9) is a zinc-dependent endopeptidase that is involved in various cellular processes. The correlation between MMP9 and the risk of severe childhood pneumonia remains unclear.MethodsHere we assemble a case–control cohort to study the association of genetic variants in MMP9 gene with severe childhood pneumonia susceptibility in a Southern Chinese population (1034 cases and 8426 controls).ResultsOur results indicate that the allele G in rs3918262 SNP was significantly associated with an increased risk of severe pneumonia. Bioinformatic analyses by expression quantitative trait loci (eQTL), RegulomeDB and FORGEdb database analysis showed that rs3918262 SNP has potential regulatory effect on translational efficiency and protein level of MMP9 gene. Furthermore, MMP9 concentrations were significantly up-regulated in the bronchoalveolar lavages (BALs) of children with severe pneumonia.ConclusionIn summary, our findings suggest that MMP9 is a novel predisposing gene for childhood pneumonia.

Specific RNA structures in the 5' untranslated region of the human cytomegalovirus major immediate early transcript are critical for efficient virus replication.

Human cytomegalovirus (HCMV) requires the robust expression of two immediate early proteins, IE1 and IE2, immediately upon infection to suppress the antiviral response and promote viral gene expression. While transcriptional control of IE1 and IE2 has been extensively studied, the role of post-transcriptional regulation of IE1 and IE2 expression is relatively unexplored. We previously found that the shared major immediate early 5' untranslated region (MIE 5' UTR) of the mature IE1 and IE2 transcripts plays a critical role in facilitating the translation of the IE1 and IE2 mRNAs. As RNA secondary structure in 5' UTRs can regulate mRNA translation efficiency, we used selective 2'-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP) to identify RNA structures in the shared MIE 5' UTR. We found that the MIE 5' UTR contains three stable stem loop structures. Using a series of recombinant viruses to investigate the role of each stem loop in IE1 and IE2 protein synthesis, we found that the stem loop closest to the 5' end of the MIE 5' UTR (SL1) is both necessary and sufficient for efficient IE1 and IE2 mRNA translation and HCMV replication. The positive effect of SL1 on mRNA translation and virus replication was dependent on its location within the 5' UTR. Surprisingly, a synthetic stem loop with the same free energy as SL1 in its native location also supported wild type levels of IE1 and IE2 mRNA translation and virus replication, suggesting that the presence of RNA structure at a specific location in the 5' UTR, rather than the primary sequence of the RNA, is critical for efficient IE1 and IE2 protein synthesis. These data reveal a novel post-transcriptional regulatory mechanism controlling IE1 and IE2 expression and reinforce the critical role of RNA structure in regulating HCMV protein synthesis and replication.IMPORTANCEThese results reveal a new aspect of immediate early gene regulation controlled by non-coding RNA structures in viral mRNAs. Previous studies have largely focused on understanding viral gene expression at the level of transcriptional control. Our results show that a complete understanding of the control of viral gene expression must include an understanding of viral mRNA translation, which is driven in part by RNA structure(s) in the 5' UTR of viral mRNAs. Our results illustrate the importance of these additional layers of regulation by defining specific 5' UTR RNA structures regulating immediate early gene expression in the context of infection and identify important features of RNA structure that govern viral mRNA translation efficiency. These results may therefore broadly impact current thinking on how viral gene expression is regulated for human cytomegalovirus and other DNA viruses.

Application and Challenges of Information Theory in English Translation and Cross-cultural Communication

Abstract With the deepening of China's foreign exchange, the importance of translation is becoming more and more prominent, but some scholars and translators still have great misunderstandings about translation, and translation has been in a neglected position. Aiming at this phenomenon, this paper introduces information theory into English translation and cross-cultural communication. It proposes an automatic translation control method based on the information entropy model to improve the accuracy and efficiency of translation. It expands the lexicon based on the information entropy model, which is divided into basic lexicon, specialized lexicon, and neologism lexicon. Then, it constructs a semantic model to complete the automated extraction of lexicon features and realize automatic translation. The transfer of language information and the modification of terminological structure are discussed in cross-cultural communication to improve the challenges of English translation and cross-cultural communication. During the translation process, the correlation between the entropy of Chinese and English corresponding unitary, binary, and ternary words - sentence entropy decreases gradually (0.993->0.977->0.972). The largest value of information entropy loss in different cultural contexts is caused by the tonal-phonetic contrast of combining yinping and declination. The relative degree of information loss is 5.300585%. This study has provided new perspectives for translation research through the use of redundant information theory and discrete information theory.

Design and Application of Language Translation System Resource Platform on Basis of Artificial Intelligence

In daily lives, people often use translators for cross-language translation, but the current translation system has the problem of translation accuracy, and its translation speed also has some limitations. Artificial intelligence has begun to develop, and the language translation system resource platform based on artificial intelligence has gradually attracted attention. The design and application of this platform are of great significance for providing high-quality and efficient language translation services. This research proposes and demonstrates a language translation system resource platform based on artificial intelligence technology. The platform is based on artificial intelligence technology for hardware resources, network resources, and the use of artificial intelligence algorithms to achieve language translation that is accurate and smooth. Through experimental testing, the results showed that the translation accuracy of the system platform reached 95-99%. The platform provides quality and efficient language translation services which can promote and facilitate human cross-language communication and understanding.

Base-modified factor VIII mRNA delivery with galactosylated lipid nanoparticles as a protein replacement therapy for haemophilia A.

The bleeding disorder hemophilia A (HemA) requires systemic functional factor VIII protein infusions on prophylactic schedules. Recently, chemically modified mRNAs have emerged as promising protein replacement therapies to reduce repeated infusions and improve safety profiles. However, the influence of base modifications on mRNA translation kinetics to specific cell types remains unexplored. In this study, towards developing mRNA therapeutics for haemophilia A, we synthesized chemically modified mRNAs with commercially available base modifications of adenine, guanine, uridine, and cytidine, and evaluated in vitro transcription yield and translation kinetics in hepatic cell lines using reporter eGFP mRNA. Our findings demonstrated that mRNA with N1-methyl pseudouridine (m1Ψ) showed a 5-12-fold increase in translation efficiency in both hepatic and endothelial cell lines. As a proof of concept for developing mRNA therapy for HemA, where FVIII is deficient, we developed a m1Ψ modified functional FVIII mRNA with our liver-targeting lipid nanoparticle (Gal-LNP) system. We evaluated its delivery efficiencies in both hepatic cell lines and the HemA mouse model. The m1Ψ-FVIII mRNA showed high therapeutic efficacy up to 15 days in vivo in the HemA mouse model. Gal-LNPs were found to be safe for systemic administration. Our study reveals that incorporating m1Ψ base modifications on mRNAs could improve therapeutic efficacy in liver- and endothelial-based therapeutics. Optimized mRNA synthesis for superior expression kinetics in hepatic cells and its delivery with liver-targeted nanoparticles may emerge as protein replacement therapies for monogenic liver disorders.

CAG Repeat Expansions Increase N1-Methyladenine to Alter TDP-43 Phase Separation: Lights Up Therapeutic Intervention for Neurodegeneration.

N1-methyladenine (m1A), a modification of transcripts, regulates mRNA structure and translation efficiency. In a recent issue of Nature, Sun et al. reported that m1A in CAG repeat RNA contributes to CAG repeat expansion-induced neurodegeneration in Caenorhabditis elegans and Drosophila through enhancing the ability of endogenous TDP-43 to partition into stress granules mediated by m1A. The study is especially important for revealing the pathological function of m1A in RNA and the pathological mechanisms of CAG repeat expansion-related neurodegenerative diseases.

LANGUAGE IDENTIFICATION FOR MULTILINGUAL MACHINE

Language Identification for Multilingual Machine Translation is a crucial component in modern natural language processing systems, enabling accurate and efficient translation across multiple languages. This paper presents a comprehensive approach to language identification that enhances the performance of multilingual machine translation systems.The proposed method utilizes advanced machine learning techniques to automatically detect the language of a given text with high accuracy. By incorporating a variety of linguistic features and leveraging large-scale multilingual datasets, the system can identify languages even in challenging scenarios such as code-switching and mixed-language inputs.Key contributions of this work include the development of a robust language identification model that integrates seamlessly with machine translation pipelines. The model is evaluated on diverse datasets, demonstrating its effectiveness in real-world applications. Additionally, we explore the impact of accurate language identification on the overall quality of machine translation, highlighting improvements in translation accuracy and fluency.

Deficiency of the ribosomal protein uS10 (RPS20) reorganizes human cells translatome according to the abundance, CDS length and GC content of mRNAs.

Ribosomal protein uS10, a product of the RPS20 gene, is an essential constituent of the small (40S) subunit of the human ribosome. Disruptive mutations in its gene are associated with a predisposition to hereditary colorectal carcinoma. Here, using HEK293T cells, we show that a deficiency of this protein leads to a decrease in the level of ribosomes (ribosomal shortage). RNA sequencing of the total and polysome-associated mRNA samples reveals hundreds of genes differentially expressed in the transcriptome (t)DEGs and translatome (p)DEGs under conditions of uS10 deficiency. We demonstrate that the (t)DEG and (p)DEG sets partially overlap, determine genes with altered translational efficiency (TE) and identify cellular processes affected by uS10 deficiency-induced ribosomal shortage. We reveal that translated mRNAs of upregulated (p)DEGs and genes with altered TE in uS10-deficient cells are generally more abundant and that their GC contents are significantly lower than those of the respective downregulated sets. We also observed that upregulated (p)DEGs have longer coding sequences. Based on our findings, we propose a combinatorial model describing the process of reorganization of mRNA translation under conditions of ribosomal shortage. Our results reveal rules according to which ribosomal shortage reorganizes the transcriptome and translatome repertoires of actively proliferating cells.

Cognitive Dynamics in Language Mediation Insights from Translation, Audiovisual Translation, and Interpreting Studies

This article ventures into the intricate world of cognitive processes underlying translation and interpreting. It presents a meticulous examination of the complex mental processes and cognitive strategies that translators and interpreters employ in their professional practices. Central to this exploration is the integration of theoretical models with empirical research findings, a synthesis that offers a profound understanding of the cognitive underpinnings shaping the practice of translating and interpreting. This comprehensive study scrutinizes various established cognitive models, analyzing how they elucidate the cognitive activities involved in language mediation. Furthermore, it delves into the application of these models to real-world scenarios, assessing their practicality and relevance in the dynamic field of translation and interpreting. By bridging the theoretical with the practical, the article sheds light on how cognitive models not only inform academic discourse but also have tangible applications in enhancing the efficiency and effectiveness of translation and interpreting tasks. This investigation thereby contributes significantly to the field by offering insights that have the potential to revolutionize practices and training in translation and interpreting, making it a pivotal resource for professionals, academicians, and students alike.

Keratoconus: exploring fundamentals and future perspectives - a comprehensive systematic review.

New developments in artificial intelligence, particularly with promising results in early detection and management of keratoconus, have favorably altered the natural history of the disease over the last few decades. Features of artificial intelligence in different machine such as anterior segment optical coherence tomography, and femtosecond laser technique have improved safety, precision, effectiveness, and predictability of treatment modalities of keratoconus (from contact lenses to keratoplasty techniques). These options ingrained in artificial intelligence are already underway and allow ophthalmologist to approach disease in the most non-invasive way. This study comprehensively describes all of the treatment modalities of keratoconus considering machine learning strategies. A multidimensional comprehensive systematic narrative review. A comprehensive search was done in the five main electronic databases (PubMed, Scopus, Web of Science, Embase, and Cochrane), without language and time or type of study restrictions. Afterward, eligible articles were selected by screening the titles and abstracts based on main mesh keywords. For potentially eligible articles, the full text was also reviewed. Artificial intelligence demonstrates promise in keratoconus diagnosis and clinical management, spanning early detection (especially in subclinical cases), preoperative screening, postoperative ectasia prediction after keratorefractive surgery, and guiding surgical decisions. The majority of studies employed a solitary machine learning algorithm, whereas minor studies assessed multiple algorithms that evaluated the association of various keratoconus staging and management strategies. Last but not least, AI has proven effective in guiding the implantation of intracorneal ring segments in keratoconus corneas and predicting surgical outcomes. The efficient and widespread clinical translation of machine learning models in keratoconus management is a crucial goal of potential future approaches to better visual performance in keratoconus patients. The article has been registered through PROSPERO, an international database of prospectively registered systematic reviews, with the ID: CRD42022319338.

Harnessing exosomes for advanced osteoarthritis therapy.

Exosomes are nanosized, lipid membrane vesicles secreted by cells, facilitating intercellular communication by transferring cargo from parent to recipient cells. This capability enables biological crosstalk across multiple tissues and cells. Extensive research has been conducted on their role in the pathogenesis of degenerative musculoskeletal diseases such as osteoarthritis (OA), a chronic and painful joint disease that particularly affects cartilage. Currently, no effective treatment exists for OA. Given that exosomes naturally modulate synovial joint inflammation and facilitate cartilage matrix synthesis, they are promising candidates as next generation nanocarriers for OA therapy. Recent advancements have focused on engineering exosomes through endogenous and exogenous approaches to enhance their joint retention, cartilage and chondrocyte targeting properties, and therapeutic content enrichment, further increasing their potential for OA drug delivery. Notably, charge-reversed exosomes that utilize electrostatic binding interactions with cartilage anionic aggrecan glycosaminoglycans have demonstrated the ability to penetrate the full thickness of early-stage arthritic cartilage tissue following intra-articular administration, maximizing their therapeutic potential. These exosomes offer a non-viral, naturally derived, cell-free carrier for OA drug and gene delivery applications. Efforts to standardize exosome harvest, engineering, and property characterization methods, along with scaling up production, will facilitate more efficient and rapid clinical translation. This article reviews the current state-of-the-art, explores opportunities for exosomes as OA therapeutics, and identifies potential challenges in their clinical translation.

On Applying Natural Language Processing Technology to Optimize Accuracy of English Interactive Translation Platform

Abstract This research establishes a phrase-based statistical machine translation platform composed of multiple functional modules, including data preprocessing, word alignment, translation model training, ordering model training, language model training, decoding, and parameter optimization. Special emphasis is placed on the quality of bilingual word alignment, utilizing both the IBM model and the statistical collocation model to enhance alignment accuracy. The study reveals that this new platform significantly enhances translation efficiency across diverse corpora, such as legal documents, news articles, and parliamentary records. Notably, the translation of parliamentary records demonstrates a remarkable reduction in average translation time by 27.53% and a decrease in the number of decoding iterations by 56.46% when compared to System1 using the Baseline system. Furthermore, a BLEU-based evaluation indicates that the Baseline system consistently surpasses the comparison system in translating various text types. This study underscores the practical effectiveness of the developed translation platform and its contribution to the advancement of natural language processing technology.

English translation evaluation method based on BP neural network

In order to solve the problems of machine translation efficiency and translation quality, this paper proposes an English translation evaluation system based on BP neural network algorithm. This method provides users with a more intelligent machine translation service experience. With the help of BP neural network algorithm, taking English online translation as the research object, Google's translation quality is the best, with an error frequency of only 167, while Baidu translation and iFLYTEK translation in China have a high error rate of 266 and 301 respectively, which is much higher than Google translation. A model of machine translation evaluation based on neural network algorithm is proposed to better solve the disadvantages of traditional English machine translation. The results show that the machine translation system based on neural network algorithm can further optimize the problems existing in machine translation, such as insufficient use of information and large scale of model parameters, and further improve the performance of neural network machine translation.

Research on the Role of Artificial Intelligence in the Core of Intelligent Translation Systems

With the development of the world economy and the expansion of foreign trade, the status of English as a global language in English teaching is increasingly elevated, and language translation is an indispensable link. In the new intelligent translation and reading system based on language models, its translation part includes at least one dictionary used for translation. The system includes: reading and writing database, loading module, editing module, label module, trigger module, annotation module, and word addition module. Among them, the read-write database is used to store literature; The loading module is used to load article materials as reading documents. It adopts natural language processing technology to save system translation and reading time and improve system efficiency. In order to test the advantages of the system used in this article, 200 vocabulary words were input into the system and compared with the traditional system for translation accuracy. The translation accuracy of the system in this article was 94.64%, while the translation accuracy of the traditional system was 83.34%. The system in this article helps to improve translation efficiency and enhance reading experience.

Silk-gelatin hybrid hydrogel: a potential carrier for RNA therapeutics.

RNA-based therapeutics have exhibited remarkable potential in targeting genetic factors for disease intervention, exemplified by recent mRNA vaccines for COVID-19. Nevertheless, the intrinsic instability of RNA and challenges related to its translational efficiency remain significant obstacles to the development of RNA as therapeutics. This study introduces an innovative RNA delivery approach using a silk fibroin (SF) and positively charged gelatin (Gel) hydrogel matrix to enhance RNA stability for controlled release. As a proof of concept, whole-cell RNA was incorporated into the hydrogel to enhance interactions with RNA molecules. Additionally, molecular modeling studies were conducted to explore the interactions between SF, collagen, chitosan (Chi), and the various RNA species including ribosomal RNAs (28S, 18S, 8.5S, and 5S rRNAs), transfer RNAs (tRNA-ALA, tRNA-GLN, and tRNA-Leu), as well as messenger RNAs (mRNA-GAPDH, mRNA-β actin, and mRNA-Nanog), shedding light on the RNA-polymer interaction and RNA stability; SF exhibits a more robust interaction with RNA compared to collagen/gel and chitosan. We confirmed the molecular interactions of SF and RNA by FTIR and Raman spectroscopy, which were further supported by AFM and contact angle measurement. This research introduces a novel RNA delivery platform and insights into biopolymer-RNA interactions, paving the way for tailored RNA delivery systems in therapeutics and biomedical applications.