Antioxidant and anticancer activities of Trigonella foenum-graecum, Cassia acutifolia and Rhazya stricta.

BACKGROUND: Here, we determined in vitro antioxidant activity, total phenols and flavonoids and evaluated antiproliferative activity of three medicinal plant extracts: Trigonella foenum-graecum (Fenugreek), Cassia acutifolia (Senna) and Rhazya stricta (Harmal). METHODS: The leaves of the three medicinal plants were extracted with 70% ethanol. Antioxidant activities of the extracts were determined by using DPPH (1,1-diphenyl-2-picrylhydrazyl) assay. Total flavonoid and phenolic contents were determined using colorimetric assays. MTT assay was used to estimate the antiproliferative activities of the extracts against human hepatoma (HepG2) cancer cell line. In addition, the effects of R. stricta extract on cell cycle, colony formation, and wound healing of HepG2 cells and tube formation of HUVEC cells were assessed. RESULTS: Percentage inhibition of DPPH scavenging activity were dose-dependent and ranged between (89.9% ± 0.51) and (28.6% ± 2.07). Phenolic contents ranged between (11.5 ± 0.013) and (9.7 ± 0.008) mg GAE/g while flavonoid content ranged between (20.8 ± 0.40) and (0.12 ± 0.0.01) mg QE/g. Antiproliferative results of the extracts were found to be consistent with their antioxidant activity. Among the extracts evaluated, that of R. stricta showed the best antioxidant, antiproliferative and antimetastatic activities at low concentration. It also inhibited the colony-formation capacity of HepG2 cells and exhibited antiangiogenic activity. Cell cycle analysis showed significant arrest of cells at G2/M phase 12 and 48 h after treatment and significant arrest at G1/S phase after 24 h of treatment. Consistent data were observed in western blot analysis of protein levels of Cdc2 and its cyclin partners. CONCLUSIONS: These findings introduce R. stricta as a potentially useful anti-metastatic agent and a novel potential anti-tumour agent for hepatocellular carcinoma (HCC) treatment.

Diagnosis of Oral Squamous Cell Carcinoma Using Deep Neural Networks and Binary Particle Swarm Optimization on Histopathological Images: An AIoMT Approach.

Overall prediction of oral cavity squamous cell carcinoma (OCSCC) remains inadequate, as more than half of patients with oral cavity cancer are detected at later stages. It is generally accepted that the differential diagnosis of OCSCC is usually difficult and requires expertise and experience. Diagnosis from biopsy tissue is a complex process, and it is slow, costly, and prone to human error. To overcome these problems, a computer-aided diagnosis (CAD) approach was proposed in this work. A dataset comprising two categories, normal epithelium of the oral cavity (NEOR) and squamous cell carcinoma of the oral cavity (OSCC), was used. Feature extraction was performed from this dataset using four deep learning (DL) models (VGG16, AlexNet, ResNet50, and Inception V3) to realize artificial intelligence of medial things (AIoMT). Binary Particle Swarm Optimization (BPSO) was used to select the best features. The effects of Reinhard stain normalization on performance were also investigated. After the best features were extracted and selected, they were classified using the XGBoost. The best classification accuracy of 96.3% was obtained when using Inception V3 with BPSO. This approach significantly contributes to improving the diagnostic efficiency of OCSCC patients using histopathological images while reducing diagnostic costs.

Role of Drone Technology Helping in Alleviating the COVID-19 Pandemic.

The COVID-19 pandemic, caused by a new coronavirus, has affected economic and social standards as governments and healthcare regulatory agencies throughout the world expressed worry and explored harsh preventative measures to counteract the disease's spread and intensity. Several academics and experts are primarily concerned with halting the continuous spread of the unique virus. Social separation, the closing of borders, the avoidance of big gatherings, contactless transit, and quarantine are important methods. Multiple nations employ autonomous, digital, wireless, and other promising technologies to tackle this coronary pneumonia. This research examines a number of potential technologies, including unmanned aerial vehicles (UAVs), artificial intelligence (AI), blockchain, deep learning (DL), the Internet of Things (IoT), edge computing, and virtual reality (VR), in an effort to mitigate the danger of COVID-19. Due to their ability to transport food and medical supplies to a specific location, UAVs are currently being utilized as an innovative method to combat this illness. This research intends to examine the possibilities of UAVs in the context of the COVID-19 pandemic from several angles. UAVs offer intriguing options for delivering medical supplies, spraying disinfectants, broadcasting communications, conducting surveillance, inspecting, and screening patients for infection. This article examines the use of drones in healthcare as well as the advantages and disadvantages of strict adoption. Finally, challenges, opportunities, and future work are discussed to assist in adopting drone technology to tackle COVID-19-like diseases.

Antioxidant and anticancer activities of chamomile (Matricaria recutita L.).

OBJECTIVES: The present study aimed at determining the antioxidant activity, total phenols and flavonoids and to evaluate the antiproliferative activity of ethanolic extract of Matricaria recutita L. (chamomile). The antioxidant activities were measured using the 2, 2-diphenyl-1-picrylhydrazyl (DPPH) assay. The total phenolic content was measured by the Folin-Ciocalteu assay. The flavonoid content was determined using the aluminum chloride method. The MTT assay was used to estimate the antiproliferative activities against human hepatoma (HepG2) cancer cell line. We assessed the mode of action of the extract as a cancer preventive agent and reported its ability to regulate tumor angiogenesis by down regulating in a dose dependent manner the expression of some proteins involved in the process. RESULTS: The percentage inhibition of DPPH scavenging activity was dose-dependent ranging between (94.8% ± 0.03) at 1.50 mg/mL and (84.2% ± 0.86) at 0.15 mg/mL. It showed high polyphenols (21.4 ± 0.327 mg GAE/g) and high flavonoids content (157.9 ± 2.22 mg QE/g). Effect of extract was investigated against HepG2 cells. A dose-dependent reduction in cell viability was recorded in cells treated with the extract. The IC50 was ~ 300 µg/mL. It significantly inhibited the level of important prerequisite angiogenesis markers both in HepG2 cells and ex vivo.