Valorization of Adhatoda vasica leaves: Extraction, in vitro analyses and in silico approaches.

Adhatoda vasica (also called Vasaka) is a traditional medicinal herb used traditionally for the relief of cough, asthma, nasal congestion, bronchial inflammation, upper respiratory infections, bleeding disorders, skin diseases, leprosy, tuberculosis, diabetes, allergic conditions, rheumatism, tumor, and many more diseases. The present study aims to investigate the biological activities of vasicine, a potent alkaloid from A. vasica with different biological/ pharmacological assays and in silico techniques. Vasicine showed antimicrobial activity as evidenced fromthe colony-forming unit assay. It showed antioxidant activity in ABTS scavenging assay (IC50 = 11.5 µg/ml), ferric reducing power assay (IC50 = 15 µg/ml), DPPH radical scavenging assay (IC50 = 18.2 µg/ml), hydroxyl radical scavenging assay (IC50 = 22 µg/ml), and hydrogen peroxide assay (IC50 = 27.8 µg/ml). It also showed anti-inflammatory activity in proteinase inhibitory assay (IC50 = 76 µg/ml), BSA method (IC50 = 51.7 µg/ml), egg albumin method (IC50 = 53.2 µg/ml), and lipooxygenase inhibition assay (IC50 = 76 µg/ml). Vasicine showed antidiabetic activity in α-amylase inhibition assay (IC50 = 47.6 µg/ml), α-glucosidase inhibition assay (IC50 = 49.68 µg/ml), and non-enzymatic glycosylation of hemoglobin assay. It showed antiviral activity against HIV-protease (IC50 = 38.5 µg/ml). Vasicine also showed anticancer activity against lung cancer cells (IC50 = 46.5 µg/ml) and human fibroblast cells (IC50 = 82.5 µg/ml). In silico studies revealed that similar to the native ligands, vasicine also showed a low binding energy, i.e., good binding affinity for the active binding sites and interacted with α-amylase (-6.7 kcal/mol), α-glucosidase (-7.6 kcal/mol), cyclooxygenase (-7.4 kcal/mol), epidermal growth factor receptor (-6.4 kcal/mol), lipooxygenase (-6.9 kcal/mol), and HIV-protease (-6.4 kcal/mol). The present study ascertains the potential of vasicine as a bioactive compound isolated from A. vasica having therapeutic usefulness in many human diseases.

Interaction between HER2 and ATM predicts poor survival in bladder cancer patients.

Human Epidermal Growth Factor Receptor 2 (HER2) overexpression is considered one of the interesting prognostic biomarkers in bladder cancer. However, the mechanism of bladder cancer development in relation to HER2 status remains to be elucidated. In this study, we investigated HER2-Ataxia telangiectasia mutated (ATM) kinase interaction and their impact on patient survival and cancer aggressiveness. Using the Cancer Genome Atlas (TCGA) cohorts, we demonstrated that ATM expression (protein/mRNA) is increased in HER2 deficient compared with proficient HER2 patients. This finding was then validated using the Gene Expression Omnibus database (GEO). Correlation analysis (using low expression vs high expression as a discriminator) revealed a significant association of ATM low and HER2 high status with several clinicopathological variables such as high tumour grade, late disease stage and tumour shape. Kaplan-Meier survival analysis indicated that ATM low and HER2 high is a powerful prognosticator of both overall survival (OS) and disease-free survival (DFS). Furthermore, using bioinformatics and protein/protein interaction analyses, we identified 66 putative overlapping proteins with direct link between HER2 and ATM most of which are functionally involved in transcription regulation, apoptotic process and cell proliferation. Interestingly, the results showed that these proteins are strongly linked with PI3K-Akt pathway, p53 pathway and microRNAs in cancer. Altogether, our data pinpoint an important biological role of the interconnection between HER2 and ATM. The latter appear to be an independent prognostic biomarker and may serve as targets to develop novel combination therapies to improve the outcome of patients with bladder cancer.

Stem cells and the pursuit of youth, a tale of limitless possibilities and commercial fraud.

This article examines the hype generated around the term "stem cell", and the capitalization of the stem cell craze by the cosmetic industry. It started by introducing product lines containing active ingredients derived from plant stem cells. Then, evolved to using own cells for skin regeneration and hair loss treatment, and allogenic cells for the manufacturing of stem cell-derived products. This article also discusses the missing links for safe and reliable stem cell applications in cosmetics, and why local regulatory bodies, members of the industry and consumers must all work together to stop the illegitimate use of the "stem cell" good name in unsafe or fraudulent commercial practices.

Nanogenomics and Artificial Intelligence: A Dynamic Duo for the Fight Against Breast Cancer.

Application software is utilized to aid in the diagnosis of breast cancer. Yet, recent advances in artificial intelligence (AI) are addressing challenges related to the detection, classification, and monitoring of different types of tumors. AI can apply deep learning algorithms to perform automated analysis on mammographic or histologic examinations. Large volume of data generated by digitalized mammogram or whole-slide images can be interoperated through advanced machine learning. This enables fast evaluation of every tissue patch on an image, resulting in a quicker more sensitivity, and more reproducible diagnoses compared to human performance. On the other hand, cancer cell-exosomes which are extracellular vesicles released by cancer cells into the blood circulation, are being explored as cancer biomarker. Recent studies on cancer-exosome-content revealed that the encapsulated miRNA and other biomolecules are indicative of tumor sub-type, possible metastasis and prognosis. Thus, theoretically, through nanogenomicas, a profile of each breast tumor sub-type, estrogen receptor status, and potential metastasis site can be constructed. Then, a laboratory instrument, fitted with an AI program, can be used to diagnose suspected patients by matching their sera miRNA and biomolecules composition with the available template profiles. In this paper, we discuss the advantages of establishing a nanogenomics-AI-based breast cancer diagnostic approach, compared to the gold standard radiology or histology based approaches that are currently being adapted to AI. Also, we discuss the advantages of building the diagnostic and prognostic biomolecular profiles for breast cancers based on the exosome encapsulated content, rather than the free circulating miRNA and other biomolecules.

Exosomes, cancer's little army.

In an attempt to conceptualize the process of cancer formation, Hanahan and Weinberg [2000] have outlined six universal characteristics of tumorigenesis, and labelled them as the "hallmarks of cancer". These hallmarks include; unlimited proliferation, evading growth suppressors, resisting cell death, replicative immortality, inducing angiogenesis, initiating invasion and metastasis. Cancer cell signalling is crucial for initiating and controlling cellular pathways that are involved in these hallmarks. The intricate network of communication between cancer cells and other cancer or non-cancer cells is still being investigated, and is yet to be fully understood. Initially it was proposed that the main form of communication between cells within the tumour microenvironment are soluble growth factors, and gap junctions. Then, researchers reported another form of cell-to-cell communication, through the release of spherical particles called exosomes. It is believed that these exosomes enable communication through the transfer of active components from the releasing cell, and off-loading it into the recipient cell. As researchers continue to examine the development of the cancer hallmarks and the pathways involved, it became evident that cancer cell-derived exosomes play a major role in almost all of them. This review will examine the role played by cancer cell-derived exosomes in development of cancer.