Spatiotemporal dynamics of carbon isotope ratios and phytoplankton composition in the eastern Arabian Sea.

This study investigated major contributors of the particulate organic matter (POM) using stable isotope ratios of particulate organic carbon (δC) and its relationship with phytoplankton composition during three seasons across six coast-offshore transects in the eastern Arabian Sea (EAS). Results revealed significant spatiotemporal variations, with elevated δC in coastal waters during the winter and summer monsoon (-22.40 ± 1.

A self-amplifying RNA RSV prefusion-F vaccine elicits potent immunity in pre-exposed and naïve non-human primates.

Newly approved subunit and mRNA vaccines for respiratory syncytial virus (RSV) demonstrate effectiveness in preventing severe disease, with protection exceeding 80% primarily through the generation of antibodies. An alternative vaccine platform called self-amplifying RNA (saRNA) holds promise in eliciting humoral and cellular immune responses. We evaluate the immunogenicity of a lipid nanoparticle (LNP)-formulated saRNA vaccine called SMARRT.

Unraveling the enigma: chronic kidney disease of unknown etiology and its causative factors with a specific focus on dissolved organic compounds in groundwater-reviews and future prospects.

Chronic kidney disease is globally recognized as a highly impactful non-communicable disease. The inability of early identification contributes to its high mortality rate and financial burden on affected individuals. Chronic kidney disease of uncertain etiology (CKDu) constitutes a significant global public health concern.

Fluorescent carbon dot embedded polystyrene: an alternative for micro/nanoplastic translocation study in leguminous plants.

Micro/nanoplastics are widespread in terrestrial ecosystem. Even though many studies have been reported on the effects of these in marine environment, studies concerning their accumulation and impact on terrestrial ecosystem have been scanty. The current study was designed to determine how terrestrial plants, especially legumes, interact with micro/nanoplastics to gain insights into their uptake and translocation.

A deep learning-based toolkit for 3D nuclei segmentation and quantitative analysis in cellular and tissue context.

We present a new set of computational tools that enable accurate and widely applicable 3D segmentation of nuclei in various 3D digital organs. We have developed an approach for ground truth generation and iterative training of 3D nuclear segmentation models, which we applied to popular CellPose, PlantSeg and StarDist algorithms. We provide two high-quality models trained on plant nuclei that enable 3D segmentation of nuclei in datasets obtained from fixed or live samples, acquired from different plant and animal tissues, and stained with various nuclear stains or fluorescent protein-based nuclear reporters.