Multifunctionalities linked with the microbial communities associated with the millet crop rhizosphere has remained unexplored. In this study, we are analyzing microbial communities inhabiting rhizosphere of kodo millet and their associated functions and its impact over plant growth and survival. Metagenomics of Paspalum scrobiculatum L.(kodo millet) rhizopshere revealed taxonomic communities with functional capabilities linked to support growth and development of the plants under nutrient-deprived, semi-arid and dry biotic conditions. Among 65 taxonomically diverse phyla identified in the rhizobiome, Actinobacteria were the most abundant followed by the Proteobacteria. Functions identified for different genes/proteins led to revelations that multifunctional rhizobiome performs several metabolic functions including carbon fixation, nitrogen, phosphorus, sulfur, iron and aromatic compound metabolism, stress response, secondary metabolite synthesis and virulence, disease, and defense. Abundance of genes linked with N, P, S, Fe and aromatic compound metabolism and phytohormone synthesis-along with other prominent functions-clearly justifies growth, development, and survival of the plants under nutrient deprived dry environment conditions. The dominance of actinobacteria, the known antibiotic producing communities shows that the kodo rhizobiome possesses metabolic capabilities to defend themselves against biotic stresses. The study opens avenues to revisit multi-functionalities of the crop rhizosphere for establishing link between taxonomic abundance and targeted functions that help plant growth and development in stressed and nutrient deprived soil conditions. It further helps in understanding the role of rhizosphere microbiome in adaptation and survival of plants in harsh abiotic conditions.
Cancer is the leading cause of mortality worldwide, requiring continuous advancements in diagnosis and treatment. Traditional methods often lack sensitivity and specificity, leading to the need for new methods. 3D printing has emerged as a transformative tool in cancer diagnosis, offering the potential for precise and customizable nanosensors. These advancements are critical in cancer research, aiming to improve early detection and monitoring of tumors. In current times, the usage of the 3D printing technique has been more prevalent as a flexible medium for the production of accurate and adaptable nanosensors characterized by exceptional sensitivity and specificity. The study aims to enhance early cancer diagnosis and prognosis by developing advanced 3D-printed nanosensors using 3D printing technology. The research explores various 3D printing techniques, design strategies, and functionalization strategies for cancer-specific biomarkers. The integration of these nanosensors with detection modalities like fluorescence, electrochemical, and surface-enhanced Raman spectroscopy is also evaluated. The study explores the use of inkjet printing, stereolithography, and fused deposition modeling to create nanostructures with enhanced performance. It also discusses the design and functionalization methods for targeting cancer indicators. The integration of 3D-printed nanosensors with multiple detection modalities, including fluorescence, electrochemical, and surface-enhanced Raman spectroscopy, enables rapid and reliable cancer diagnosis. The results show improved sensitivity and specificity for cancer biomarkers, enabling early detection of tumor indicators and circulating cells. The study highlights the potential of 3D-printed nanosensors to transform cancer diagnosis by enabling highly sensitive and specific detection of tumor biomarkers. It signifies a pivotal step forward in cancer diagnostics, showcasing the capacity of 3D printing technology to produce advanced nanosensors that can significantly improve early cancer detection and patient outcomes.