The State-of-the-Art Overview to Application of Deep Learning in Accurate Protein Design and Structure Prediction.

In recent years, there has been a notable increase in the scientific community's interest in rational protein design. The prospect of designing an amino acid sequence that can reliably fold into a desired three-dimensional structure and exhibit the intended function is captivating. However, a major challenge in this endeavor lies in accurately predicting the resulting protein structure. The exponential growth of protein databases has fueled the advancement of the field, while newly developed algorithms have pushed the boundaries of what was previously achievable in structure prediction. In particular, using deep learning methods instead of brute force approaches has emerged as a faster and more accurate strategy. These deep-learning techniques leverage the vast amount of data available in protein databases to extract meaningful patterns and predict protein structures with improved precision. In this article, we explore the recent developments in the field of protein structure prediction. We delve into the newly developed methods that leverage deep learning approaches, highlighting their significance and potential for advancing our understanding of protein design.

A comprehensive review of the applications of RNA sequencing in celiac disease research.

RNA sequencing (RNA-seq) has undergone substantial advancements in recent decades and has emerged as a vital technique for profiling the transcriptome. The transition from bulk sequencing to single-cell and spatial approaches has facilitated the achievement of higher precision at cell resolution. It provides valuable biological knowledge about individual immune cells and aids in the discovery of the molecular mechanisms that contribute to the development of autoimmune diseases. Celiac disease (CeD) is an autoimmune disorder characterized by a strong immune response to gluten consumption. RNA-seq has led to significantly advanced research in multiple fields, particularly in CeD research. It has been instrumental in studies involving comparative transcriptomics, nutritional genomics and wheat research, cancer research in the context of CeD, genetic and noncoding RNA-mediated epigenetic insights, disease monitoring and biomarker discovery, regulation of mitochondrial functions, therapeutic target identification and drug mechanism of action, dietary factors, immune cell profiling and the immune landscape. This review offers a comprehensive examination of recent RNA-seq technology research in the field of CeD, highlighting future challenges and opportunities for its application.

Improving hemocompatibility in tissue-engineered products employing heparin-loaded nanoplatforms.

The enhancement of hemocompatibility through the use of nanoplatforms loaded with heparin represents a highly desirable characteristic in the context of emerging tissue engineering applications. The significance of employing heparin in biological processes is unquestionable, owing to its ability to interact with a diverse range of proteins. It plays a crucial role in numerous biological processes by engaging in interactions with diverse proteins and hydrogels. This review provides a summary of recent endeavors focused on augmenting the hemocompatibility of tissue engineering methods through the utilization of nanoplatforms loaded with heparin. This study also provides a comprehensive review of the various applications of heparin-loaded nanofibers and nanoparticles, as well as the techniques employed for encapsulating heparin within these nanoplatforms. The biological and physical effects resulting from the encapsulation of heparin in nanoplatforms are examined. The potential applications of heparin-based materials in tissue engineering are also discussed, along with future perspectives in this field.

Hijacking and rewiring of host CircRNA/miRNA/mRNA competitive endogenous RNA (ceRNA) regulatory networks by oncoviruses during development of viral cancers.

A significant portion of human cancers are caused by oncoviruses (12%-25%). Oncoviruses employ various strategies to promote their replication and induce tumourigenesis in host cells, one of which involves modifying the gene expression patterns of the host cells, leading to the rewiring of genes and resulting in significant changes in cellular processes and signalling pathways. In recent studies, a specific mode of gene regulation known as circular RNA (circRNA)-mediated competing endogenous RNA (ceRNA) networks has emerged as a key player in this context. CircRNAs, a class of non-coding RNA molecules, can interact with other RNA molecules, such as mRNAs and microRNAs (miRNAs), through a process known as ceRNA crosstalk. This interaction occurs when circRNAs, acting as sponges, sequester miRNAs, thereby preventing them from binding to their target mRNAs and modulating their expression. By rewiring the host cell genome, oncoviruses have the ability to manipulate the expression and activity of circRNAs, thereby influencing the ceRNA networks that can profoundly impact cellular processes such as cell proliferation, differentiation, apoptosis, and immune responses. This review focuses on a comprehensive evaluation of the latest findings on the involvement of virus-induced reprogramming of host circRNA-mediated ceRNA networks in the development and pathophysiology of human viral cancers, including cervical cancer, gastric cancer, nasopharyngeal carcinoma, Kaposi's sarcoma, hepatocellular carcinoma, and diffuse large B cell lymphoma. Understanding these mechanisms can improve our knowledge of how oncoviruses contribute to human tumourigenesis and identify potential targets for developing optimised therapies and diagnostic tools for viral cancers.