Experimental techniques for detecting and evaluating the amyloid fibrils.

Amyloid fibrils are insoluble proteins with intricate ß-sheet structures associated with various human diseases, including Parkinson's, Alzheimer's, and prion diseases. Proteins can form aggregates when their structure is misfolded, resulting in highly organized amyloid fibrils or amorphous aggregates. The formation of protein aggregates is a promising research field for mitigating diseases and the pharmaceutical and food industries. It is important to monitor and minimize the appearance of aggregates in these protein products. Several methods exist to assess protein aggregation, that includes from basic investigations to advanced biophysical techniques. Physicochemical parameters such as molecular weight, conformation, structure, and dimension are examined to study aggregation. There is an urgent need to develop methods for the detection of protein aggregation and amyloid fibril formation both in vitro and in vivo. This chapter focuses on a comprehensive discussion of the methods used to characterize and evaluate aggregates and amyloid fibrils.

Biotechnological applications of amyloid fibrils.

Protein aggregates and amyloid fibrils have special qualities and are used in a variety of biotechnological applications. They are extensively employed in bioremediation, biomaterials, and biocatalysis. Because of their capacity to encapsulate and release pharmaceuticals and their sensitivity to certain molecules, respectively, they are also used in drug delivery and biosensor applications. They have also demonstrated potential in the domains of food and bioremediation. Additionally, amyloid peptides have drawn interest in biological applications, especially in the investigation of illnesses like Parkinson's and Alzheimer's. The unique characteristics of amyloid fibrils, namely their mechanical strength and ß-sheet structure, make them adaptable to a wide range of biotechnological uses. Even with their promise, one important factor to keep in mind before widely using modified amyloid materials is their potential toxicity. Thus, current research aims to overcome safety concerns while maximizing their potential.

Prediction of protein aggregation.

The scientific community is very interested in protein aggregation because of its involvement in several neurodegenerative diseases and its significance in industry. Remarkably, fibrillar aggregates are utilized naturally for constructing structural scaffolds or creating biological switches and may be intentionally designed to construct versatile nanomaterials. Consequently, there is a significant need to rationalize and predict protein aggregation. Researchers have developed various computational methodologies and algorithms to predict protein aggregation and understand its underlying mechanics. This chapter aims to summarize the significant advancements in computational methods, accessible resources, and prospective developments in the field of in silico research. We assess the existing computational tools for predicting protein aggregation propensities, detecting areas that are prone to sequential and structural aggregation, analyzing the effects of mutations on protein aggregation, or identifying prion-like domains.

Identification of dysregulated competing endogenous RNA networks in glioblastoma: A way toward improved therapeutic opportunities.

Glioblastoma is recognized as one of the leading causes of death worldwide. Although there have been considerable advancements in understanding the causative molecular mechanisms of this malignancy, effective therapeutic strategies are still in limited use. It has been revealed that non-coding RNAs (ncRNAs) play critical roles in glioblastoma development, while interactions between the regulatory molecules such as long ncRNAs (lncRNAs), microRNAs (miRNAs), transcribed pseudogenes, and circular RNAs (circRNAs) remain to be fully deciphered. Over the recent years, researchers have discovered a new category of RNA molecules called competing endogenous RNA (ceRNA). This kind of RNA can contribute to molecular interactions in the form of ceRNA networks (ceRNETs). Multiple lines of evidence have demonstrated that dysregulation of various ceRNA networks is involved in glioblastoma development. Therefore, gaining insights into these dysregulations might offer potential for the early diagnosis of glioblastoma patients and identification of efficient therapeutic targets. In this review, we provide an overview of recent discoveries on ceRNA networks and the involvement of dysregulated networks in posing limitations to temozolomide therapy. We also describe signaling pathways relevant to the progression of glioblastoma.