Assessment of metal-associated health risk in different trophic levels in tropical estuary on the southeast coast of India.

Metal contamination in coastal and marine ecosystems has become a significant global concern due to its hazardous characteristics, environmental persistence, and ability to bioaccumulate in aquatic ecosystems. This poses a serious threat to the environment and the health of humans worldwide. To address these concerns, this study estimated the concentrations of metals in various trophic levels, including phytoplankton, zooplankton, bivalve, and fish.

Anticancer efficacy of magnetite nanoparticles synthesized using aqueous extract of brown seaweed Rosenvingea intricata, South Andaman, India.

Cancer is a global issue and hence various efforts are being made. Iron oxide is considered a significant biochemical agent in the biomedical arena for cancer treatment. Marine macroalgae-mediated iron oxides especially, magnetite (FeO) nanoparticles (NPs) are a prospective alternative to diagnose and treat cancer owing to their fluorescent and magnetic properties.

An impact of tropical cyclone on meiobenthic fauna of Chennai coast, Tamil Nadu, India: A case study of cyclone Mandous.

The meiofaunal diversity is used as an indicator to assess the complex and diverse impacts on the coastal environment during the natural calamities. The present study evaluates the effects of Mandous cyclone on ecologically two different stations, Pattinampakkam beach and Adyar estuary, which are located on Chennai coast, Tamil Nadu, India. The impact of the Mandous cyclone on physico-chemical parameters and meiobenthic faunal composition was investigated during, prior to, and after the cyclone.

Automatic Identification and Severity Classification of Retinal Biomarkers in SD-OCT Using Dilated Depthwise Separable Convolution ResNet with SVM Classifier.

Purpose: Diagnosis of Uveitic Macular Edema (UME) using Spectral Domain OCT (SD-OCT) is a promising method for early detection and monitoring of sight-threatening visual impairment. Viewing multiple B-scans and identifying biomarkers is challenging and time-consuming for clinical practitioners. To overcome these challenges, this paper proposes an image classification hybrid framework for predicting the presence of biomarkers such as intraretinal cysts (IRC), hyperreflective foci (HRF), hard exudates (HE) and neurosensory detachment (NSD) in OCT B-scans along with their severity.