New Therapeutic Strategies for the Inflammatory Rheumatoid Arthritis Disease: Emphasizing Mesenchymal Stem Cells and Associated exo-miRNA or exo-lncRNA.

The most prevalent inflammatory arthritis and a leading contributor to disability is rheumatoid arthritis (RA). Although it may not have arrived in Europe until the 17th century, it was present in early Native American communities several thousand years ago. Exosomes released by mesenchymal stem cells (MSCs) are highly immunomodulatory due to the origin of the cell. As a cell-free therapy, MSCs-exosomes are less toxic and elicit a weakened immune response than cell-based therapies. Exosomal noncoding RNAs (ncRNAs) are closely associated with a number of biological and functional facets of human health, especially microRNAs (miRNAs) and long noncoding RNAs (lncRNAs). Various exo-miRNAs and lncRNAs such as HAND2-AS1, miR-150-5p, miRNA-124a, and miR-320a lodged with MSC could be appropriate therapeutic ways for RA treatment. These MSC-derived exosomes affect RA disorders via different molecular pathways such as NFK-ß, MAPK, and Wnt. The purpose of this review is to review the research that has been conducted since 2020 so far in the field of RA disease treatment with MSC-loaded exo-miRNAs and exo-lncRNAs.

Nucleic acid vaccines-based therapy for triple-negative breast cancer: A new paradigm in tumor immunotherapy arena.

Nucleic acid vaccines (NAVs) have the potential to be economical, safe, and efficacious. Furthermore, just the chosen antigen in the pathogen is the target of the immune responses brought on by NAVs. Triple-negative breast cancer (TNBC) treatment shows great promise for nucleic acid-based vaccines, such as DNA (as plasmids) and RNA (as messenger RNA [mRNA]). Moreover, cancer vaccines offer a compelling approach that can elicit targeted and long-lasting immune responses against tumor antigens. Bacterial plasmids that encode antigens and immunostimulatory molecules serve as the foundation for DNA vaccines. In the 1990s, plasmid DNA encoding the influenza A nucleoprotein triggered a protective and targeted cytotoxic T lymphocyte (CTL) response, marking the first instance of DNA vaccine-mediated immunity. Similarly, in vitro transcribed mRNA was first successfully used in animals in 1990. At that point, mice were given an injection of the gene encoding the mRNA sequence, and the researchers saw the production of a protein. We begin this review by summarizing our existing knowledge of NAVs. Next, we addressed NAV delivery, emphasizing the need to increase efficacy in TNBC.

Recent advances in mRNA-based vaccine for cancer therapy; bench to bedside.

The messenger RNA (mRNA) vaccines have progressed from a theoretical concept to a clinical reality over the last few decades. Compared to conventional vaccination methods, these vaccines have a number of benefits, such as substantial potency, rapid growth, inexpensive production, and safe administration. Nevertheless, their usefulness was restricted up to now due to worries about the erratic and ineffective circulation of mRNA in vivo. Thankfully, these worries have largely been allayed by recent technological developments, which have led to the creation of multiple mRNA vaccination platforms for cancer and viral infections. The mRNA vaccines have been demonstrated as a powerful alternative to traditional conventional vaccines because of their high potency, safety and efficacy, capacity for rapid clinical development, and potential for rapid, low-cost manufacturing. The paper will examine the present status of mRNA vaccine technology and suggest future paths for the advancement and application of this exciting vaccine platform as a common therapeutic choice.

Advances in electrochemical-optical dual-mode biosensors for detection of environmental pathogens.

Electrochemical techniques are commonly used to analyze and screen various environmental pathogens. When used in conjunction with other optical recognition methods, it can extend the sensing range, lower the detection limit, and offer mutual validation. Nowadays, electrochemical-optical dual-mode biosensors have ensured the accuracy of test results by integrating two signals into one, indicating their potential use in primary food safety quantitative assays and screening tests. Particularly, visible optical signals from electrochemical/colorimetric dual-mode biosensors could meet the demand for real-time screening of microbial pathogens. While electrochemical-optical dual-mode probes have been receiving increasing attention, there is limited emphasis on the design approaches for sensors intended for microbial pathogens. Here, we review the recent progress in the merging of optical and electrochemical techniques, including fluorescence, colorimetry, surface plasmon resonance (SPR), and surface enhanced Raman spectroscopy (SERS). This study particularly emphasizes the reporting of various sensing performances, including sensing principles, types, cutting-edge design approaches, and applications. Finally, some concerns and upcoming advancements in dual-mode probes are briefly outlined.

ETS transcription factor ELK3 in human cancers: An emerging therapeutic target.

Cancer is a genetic and complex disorder, resulting from several events associated with onset, development, and metastasis. Tumor suppressors and oncogenes are among the main regulators of tumor progression, contributing to various cancer-related behaviors like cell proliferation, invasion, migration, epithelial-mesenchymal transition (EMT), cell cycle, and apoptosis. Transcription factors (TFs) could act as tumor suppressors or oncogenes in cancer progression. E-twenty-six/E26 (ETS) family of TFs have a winged helix-turn-helix (HLH) motif, which interacted with specific DNA regions with high levels of purines and GGA core. ETS proteins act as transcriptional repressors or activators to modulate the expression of target genes. ETS transcription factor ELK3 (ELK3), as a type of ETS protein, was shown to enhance in various cancers, suggesting that it may have an oncogenic role. These studies indicated that ELK3 promoted invasion, migration, cell cycle, proliferation, and EMT, and suppressed cell apoptosis. In addition, these studies demonstrated that ELK3 could be a promising diagnostic and prognostic biomarker in human cancer. Moreover, accumulating data proved that ELK3 could be a novel chemoresistance mediator in human cancer. Here, we aimed to explore the overall change of ELK3 and its underlying molecular mechanism in human cancers. Moreover, we aimed to investigate the potential role of ELK3 as a prognostic and diagnostic biomarker as well as its capability as a chemoresistance mediator in cancer.

Intelligent predictions of Covid disease based on lung CT images using machine learning strategy.

Covid or Corona Virus, a term ruling the world from past two years and causes a huge destruction in all countries. One of the most important Covid disease identification method is Lung based Computed Tomography (CT) image scanning, in which it provides an effective disease identification means in clear manner. However, this Lung CT image based disease detection principles are complex to health care representatives and doctors to predict the Covid disease accurately. Several manual errors and medical flaws are raised day-by-day, so that a new systematic methodology is required to identify the Covid disease effectively with respect to machine learning principles. The machine learning principles are most popular to identify the respective disease efficiently as well as classify the disease in accurate manner without any time consumption. The infected portions of the chest are identified accurately and report to the respective person without any delay. In this paper, a new machine learning strategy is introduced called Hybrid Disease Detection Principle (HDDP), in which it is derived from the two classical machine learning algorithms called Convolutional Neural Network (CNN) and the AdaBoost Classifier. Both these algorithms are integrated together to produce a new strategy called HDDP, in which it process the lung CT image based on the machine learning factors such as pre-processing, feature extraction and classification. Based on these effective image processing strategies the proposed algorithm handles the CT images to predict the Covid disease and report to the respective user with proper accuracy ratio. This paper intends to provide effcient disease predictions as well as provide a sufficient support to medical people and patients in fine manner to assist them with modern classification algorithms.

Battling the pandemic by solving the myths of virtual world.

The entire world has gotten caught and is now furious that the deadly corona virus is out. All and every person's life across the globe has stopped. It took millions of lives already. The government of most countries agreed to follow the full lock-down of human activities due to its propensity to a high spread frequency. Therefore, this work of mine would be a accentuating the affectivity of the Aarogya Setu application in spreading realization amongst the masses that self- care in this situation of emergence is the only way not only of saving one's own life but also of others. It would also effectively highlight that though, the use of virtual platform has benefitted all but its improper utilization can create loads of misunderstanding, confusion and can give rise to some devastating situation.