The present study aimed to assess and monitor the therapeutic potential of antimicrobial metabolites from marine sponge-associated bacteria collected from the southeast coast of India against multidrug-resistant clinical bacterial isolates. Five sponge samples were collected and the metabolite-producing bacteria were screened from the Gulf of Mannar, India, and their antibacterial potential was studied against drug-resistant clinical bacterial isolates obtained from the hospitals. The two metabolite-producing bacteria (IS1 and IS2) were characterized by standard microbiology protocols and 16S rRNA sequencing. The antibacterial metabolites were characterized by liquid chromatography mass spectrometry (LCMS) analysis. The study suggested that marine sponges such as Spheciospongia spp., Haliclona spp., Mycale spp., Tedania spp., and SS-01 were associated with 30 ± 2, 26 ± 2, 23 ± 3, 21 ± 2, and 20 ± 2% of antibacterial metabolite-producing bacteria, respectively. The LCMS analysis of metabolites extracted from IS1 (4,6-dimethyl-2-pyrimidinamine; 4,5-dimethyl-2-propylsilyl-1H-imidazole) and IS2 (caproyl amide, 2-imidazoline) associated with Spheciospongia spp. exhibited significant antibacterial properties against drug-resistant bacteria. IS1 showed antimicrobial potential against the clinical isolates of Proteus spp., and IS2 showed antibacterial potential against isolates of both Proteus mirabilis and Salmonella typhi. IS1 and IS2 were identified by 16S rRNA sequencing and designated as Klebsiella spp. DSCE-bt01 and Pseudomonas spp. DSCE-bt02, respectively. The current study concluded that the assessment and monitoring of novel isolates from sponge-associated bacteria from marine coastal areas probably offer latest breakthrough in curtailing the global antimicrobial resistance and the study of such ecosystems adds value addition to the searching of novel bioactive compounds from terrestrial ecosystems.The novel coronavirus (COVID-19) outbreak, which was identified in late 2019, requires special attention because of its future epidemics and possible global threats. Beside clinical procedures and treatments, since Artificial Intelligence (AI) promises a new paradigm for healthcare, several different AI tools that are built upon Machine Learning (ML) algorithms are employed for analyzing data and decision-making processes. This means that AI-driven tools help identify COVID-19 outbreaks as well as forecast their nature of spread across the globe. However, unlike other healthcare issues, for COVID-19, to detect COVID-19, AI-driven tools are expected to have active learning-based cross-population train/test models that employs multitudinal and multimodal data, which is the primary purpose of the paper.The review provides information on the mechanisms underlying the development of spontaneous and pathogen-induced tumors in higher plants. The activation of meristem-specific regulators in plant tumors of various origins suggests the meristem-like nature of abnormal plant hyperplasia. Plant tumor formation has more than a century of research history. The study of this phenomenon has led to a number of important discoveries, including the development of the Agrobacterium-mediated transformation technique and the discovery of horizontal gene transfer from bacteria to plants. There are two main groups of plant tumors pathogen-induced tumors (e.g., tumors induced by bacteria, viruses, fungi, insects, etc.), and spontaneous ones, which are formed in the absence of any pathogen in plants with certain genotypes (e.g., interspecific hybrids, inbred lines, and mutants). The causes of the transition of plant cells to tumor growth are different from those in animals, and they include the disturbance of phytohormonal balance and the acquisition of meristematic characteristics by differentiated cells. The aim of this review is to discuss the mechanisms underlying the development of most known examples of plant tumors.BACKGROUND It is well known that a severe cell injury after exposure to ionizing radiation is the induction of DNA double-strand breaks (DSBs). After exposure, an early response to DSBs is the phosphorylation of the histone H2AX molecule regions adjacent to the DSBs, referred to as γ-H2AX foci. The γ-H2AX assay after external exposure is a good tool for investigating the link between the absorbed dose and biological effect. However, less is known about DNA DSBs and γ-H2AX foci within the tissue microarchitecture after internal irradiation from radiopharmaceuticals. Therefore, in this study, we aimed to develop and validate a quantitative ex vivo model using γ-H2AX immunofluorescence staining and confocal laser scanning microscopy (CLSM) to investigate its applicability in nuclear medicine dosimetry research. Memantine Liver and testis were selected as the organs to study after intravenous administration of 111InCl3. RESULTS In this study, we developed and validated a method that combines ex vivo γ-H2AX foci labeling of tissue sections with in vivo systemically irradiated mouse testis and liver tissues. The method includes CLSM imaging for intracellular cell-specific γ-H2AX foci detection and quantification and absorbed dose calculations. After exposure to ionizing radiation from 111InCl3, both hepatocytes and non-hepatocytes within the liver showed an absorbed dose-dependent elevation of γ-H2AX foci, whereas no such correlation was seen for the testis tissue. CONCLUSION It is possible to detect and quantify the radiation-induced γ-H2AX foci within the tissues of organs at risk after internal irradiation. We conclude that our method developed is an appropriate tool to study dose-response relationships in animal organs and human tissue biopsies after internal exposure to radiation.BACKGROUND Anti-programmed cell death 1 (PD-1) antibody is an immune checkpoint inhibitor, and anti-PD-1 therapy improves the anti-tumor functions of T cells and affects tumor microenvironment. We previously reported that anti-PD-1 treatment affected tumor glycolysis by using 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography (PET). That study showed that anti-PD-1 therapy in a mouse B16F10 melanoma model increased glucose metabolism in cancer cells at the point where anti-PD-1 therapy did not cause a significant inhibition of tumor growth. However, the B16F10 melanoma model is poorly immunogenic, so it is not clear how anti-PD-1 treatment affects glucose metabolism in highly immunogenic cancer models. In this study, we used a cyclic dinucleotide GMP-AMP (cGAMP)-injected B16F10 melanoma model to investigate the effect of anti-PD-1 therapy on [18F]FDG uptake in a highly immune activated tumor in mice. RESULTS To compare the cGAMP-injected B16F10 model with the B16F10 model, experiments were performed as described in our previous manuscript.