The Evolving Landscape of Cervical Cancer: Breakthroughs in Screening and Therapy Through Integrating Biotechnology and Artificial Intelligence.

Cervical cancer (CC) continues to be a major worldwide health concern, profoundly impacting the lives of countless females worldwide. In low- and middle-income countries (LMICs), where CC prevalence is high, innovative, and cost-effective approaches for prevention, diagnosis, and treatment are vital. These approaches must ensure high response rates with minimal side effects to improve outcomes. The study aims to compile the latest developments in the field of CC, providing insights into the promising future of CC management along with the research gaps and challenges. Integrating biotechnology and artificial intelligence (AI) holds immense potential to revolutionize CC care, from MobileODT screening to precision medicine and innovative therapies. AI enhances healthcare accuracy and improves patient outcomes, especially in CC screening, where its use has increased over the years, showing promising results. Also, combining newly developed strategies with conventional treatment options presents an optimal approach to address the limitations associated with conventional methods. However, further clinical studies are essential for practically implementing these advancements in society. By leveraging these cutting-edge technologies and approaches, there is a substantial opportunity to reduce the global burden of this preventable malignancy, ultimately improving the lives of women in LMICs and beyond.

Reverse pharmacology approach to validate the diabetic wound-healing activity of Jatyadi thailam formulations in vitro on diabetic mimic environment.

Objective: Jatyadi thailam, an Ayurvedic preparation, is renowned for its efficacy in diabetic wound healing and inflammation. This study aimed to validate and compare the diabetic wound-healing potential of two Jatyadi thailam formulations - Ayurvedic formulary of India Jatyadi thailam (JT-AFI) and Yogagrantha formulation of Jatyadi thailam (JT-YG), in a diabetic environment using L929 fibroblast cells in vitro. Methodology: The effects on cell survival, proliferation, migration, angiogenesis, cell cycle progression, apoptosis, ROS generation, and mitochondrial function were evaluated.Results: The formulations promoted cell proliferation, migration, angiogenesis, while also regulating cell cycle and apoptosis. They effectively suppressed ROS generation and modulated mitochondrial function. JT-AFI exhibited superior efficacy in accelerating diabetic wound healing compared to JT-YG.Conclusion: These findings provide substantial support for the mechanistic role of Jatyadi thailam in diabetic wound healing.

Defining new biomarkers for overcoming therapeutical resistance in cervical cancer using lncRNA.

Despite improvements in cervical cancer diagnosis and treatment, the prognosis for cervical cancer patients remains dismal due to the development of drug resistance, metastasis, and invasion resulting leading to treatment failure. Long non-coding RNAs (lncRNAs), a class of RNA transcripts have been reported in mediating carcinogenesis as well as drug, and radio-resistance in tumor cells. These lncRNAs regulate various cancer hallmarks and contribute to the development of therapeutic resistance. They regulates multiple signalling pathways, recruits polycomb group, function as miRNA sponge and scaffolds. Additionally, lncRNAs can act as oncogenes or tumor suppressors in cervical cancer. This comprehensive review outlines the biogenesis of lncRNA and its role in cancer development. It delves into the mechanisms through which various lncRNAs mediate chemoresistance and radioresistance in cervical cancer. By shedding into the light of mechanism, this review will also aids researchers in understanding lncRNAs as biomarkers and latest advancements in clinically targeting them with the help of Artificial Intelligence for overcoming chemoresistance and radioresistance, thereby improving cervical cancer treatment.

Identification of potential probiotics from fermented sour traditional rice varieties and in vitro simulation studies.

Fermented products contain probiotic organisms that have beneficial and therapeutic effects on the gastrointestinal tract. The main objective of the study is to isolate probiotic bacteria from fermented sour traditional rice water and to evaluate their probiotic activity. The microbes were isolated from the fermented rice water and the characterization of the organisms was determined using MALDI-TOF MS. The morphological analysis, biochemical test, and carbohydrate fermentation test were done for further characterization. The colonization and therapeutic properties of organisms were evaluated by performing in vitro simulation studies. The results indicated that the isolated gram-positive organisms Pediococcus pentosaecus and Lactococcus lactis from traditional fermented sour rice water possessed desirable in vitro probiotic properties. Consuming fermented sour rice water enriches intestinal flora with beneficial bacteria and enzymes. Fermented rice water improves gut microbiome health, immune system function, and is also used to treat chronic conditions.

A Review on Deep Learning-driven Drug Discovery: Strategies, Tools and Applications.

It takes an average of 10-15 years to uncover and develop a new drug, and the process is incredibly time-consuming, expensive, difficult, and ineffective. In recent years the dramatic changes in the field of artificial intelligence (AI) have helped to overcome the challenges in the drug discovery pipeline. Artificial intelligence (AI) has taken root in various pharmaceutical sectors, from lead compound identification to clinical trials. Deep learning (DL) is a component of artificial intelligence (AI) that has excelled in many fields of Artificial intelligence (AI) research over the past decades. Its numerous applications in the realms of science and technology, especially in biomedicine and bioinformatics, are witnessed deep learning (DL) applications significantly accelerate drug discovery and pharmaceutical research in recent years, and their usefulness has exceeded expectations and shown good promise in tackling a range of issues with drug discovery. Deep learning (DL) holds great potential for drug development since it allows for sophisticated image interpretation, molecular structure and function prediction, and the automated creation of novel chemical entities with specific features. In the process of drug discovery, deep learning (DL) can be incorporated at all stages like identification of targets, prognostic biomarkers, drug designing and development, synergism and antagonism prediction, etc. This review summarizes various approaches of deep learning (DL) in drug discovery like deep generative models for drug discovery, deep learning (DL) tools for drug discovery, synergy prediction, and precision medicine.

Mechanistic Study on Thymoquinone Conjugated ZnO Nanoparticles Mediated Cytotoxicity and Anticancer Activity in Triple-Negative Breast Cancer Cells.

BACKGROUND: In the current era, the development of molecular techniques involves nano techniques, and the synthesis of nanoparticles is considered the preferred field in nanotechnology. OBJECTIVE: The aim of the present work is to analyze the anticancer activity of the thymoquinone conjugated ZnO nanoparticles and understand its mechanism of action in triple-negative breast cancer cell lines MDA-MB-231. METHODS: Zinc Oxide (ZnO) nanoparticles have extensive applications, and it was synthesized using a chemical precipitation method. Thymoquinone (TQ) is the major bioactive component of the seeds of Nigella sativa. Synthesized nanoparticles were characterized using various spectroscopic techniques. Thymoquinone-coated nanoparticles were checked for their efficiency. The cytotoxicity of ZnO, TQ, and TQ conjugated ZnO nanoparticles against MDA-MB-231. Colony-forming and cell migration assays were performed to measure the proliferative competence of the breast cancer cells on exposure to nanoparticles. The mechanism of apoptosis was probed by assessing MMP, interplay between ER stress and ROS. RESULTS: The results of the characterization techniques confirmed that the particles synthesized were ZnO and TQ-ZnO nanoparticles. pH dependent release of the compound was observed. The anti-proliferative effect that impairs the formation of the colony was found to be enhanced in cells exposed to combined treatment with the nanoconjugate. CONCLUSION: Hence, the TQ conjugated ZnO nanoparticles can act as an efficient carrier for drug delivery at the target site in TNBC cells.

Cytotoxic activity of the methanolic extract of leaves and rhizomes of Curcuma amada Roxb against breast cancer cell lines

OBJECTIVES@#To evaluate the methanol extract of both the leaves and the rhizomes of Curcuma amada (C. amada) for their cytotoxic activity against breast cancer cell lines MCF-7 and MDA MB 231.@*METHODS@#Viability and cytotoxicity induced by the extracts were assessed using 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide, sulforhodamine B, and lactate dehydrogenase release assays. Various staining techniques such as acridine orange/ethidium bromide, Giemsa, ethidium bromide, propidium iodide, and Hoechst 33342 staining were employed to study the mechanism of cell death induced by the extract.@*RESULTS@#The results indicated that the methanol extract of both the leaves and the rhizomes of C. amada exhibited strong cytotoxicity towards breast cancer cell lines MCF-7 and MDA MB 231. The extract also showed less cytotoxicity towards non-cancerous breast cell line HBL-100. The results of staining revealed that the extracts induced cell death in cancer cells which are mediated through apoptotic pathway.@*CONCLUSIONS@#The results indicated that the methanol extract of leaves and rhizomes of C. amada possess anticancer and cytotoxic activity.

Cytotoxic activity of the methanolic extract of leaves and rhizomes of Curcuma amada Roxb against breast cancer cell lines

Objectives: To evaluate the methanol extract of both the leaves and the rhizomes of Curcuma amada (C. amada) for their cytotoxic activity against breast cancer cell lines MCF-7 and MDA MB 231. Methods: Viability and cytotoxicity induced by the extracts were assessed using 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide, sulforhodamine B, and lactate dehydrogenase release assays. Various staining techniques such as acridine orange/ethidium bromide, Giemsa, ethidium bromide, propidium iodide, and Hoechst 33342 staining were employed to study the mechanism of cell death induced by the extract. Results: The results indicated that the methanol extract of both the leaves and the rhizomes of C. amada exhibited strong cytotoxicity towards breast cancer cell lines MCF-7 and MDA MB 231. The extract also showed less cytotoxicity towards non-cancerous breast cell line HBL-100. The results of staining revealed that the extracts induced cell death in cancer cells which are mediated through apoptotic pathway. Conclusions: The results indicated that the methanol extract of leaves and rhizomes of C. amada possess anticancer and cytotoxic activity.