Entomopathogenic Fungi: An Eco-Friendly Synthesis of Sustainable Nanoparticles and Their Nanopesticide Properties.

The agricultural industry could undergo significant changes due to the revolutionary potential of nanotechnology. Nanotechnology has a broad range of possible applications and advantages, including insect pest management using treatments based on nanoparticle insecticides. Conventional techniques, such as integrated pest management, are inadequate, and using chemical pesticides has negative consequences. As a result, nanotechnology would provide ecologically beneficial and effective alternatives for insect pest control. Considering the remarkable traits they exhibit, silver nanoparticles (AgNPs) are recognized as potential prospects in agriculture. Due to their efficiency and great biocompatibility, the utilization of biologically synthesized nanosilver in insect pest control has significantly increased nowadays. Silver nanoparticles have been produced using a wide range of microbes and plants, which is considered an environmentally friendly method. However, among all, entomopathogenic fungi (EPF) have the most potential to be used in the biosynthesis of silver nanoparticles with a variety of properties. Therefore, in this review, different ways to get rid of agricultural pests have been discussed, with a focus on the importance and growing popularity of biosynthesized nanosilver, especially silver nanoparticles made from fungi that kill insects. Finally, the review highlights the need for further studies so that the efficiency of bio-nanosilver could be tested for field application and the exact mode of action of silver nanoparticles against pests can be elucidated, which will eventually be a boon to the agricultural industry for putting a check on pest populations.

Non-Invasive Monitoring of Increased Fibrotic Tissue and Hyaluronan Deposition in the Tumor Microenvironment in the Advanced Stages of Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinomas are characterized by a complex and robust tumor microenvironment (TME) consisting of fibrotic tissue, excessive levels of hyaluronan (HA), and immune cells. We utilized quantitative multi-parametric magnetic resonance imaging (mp-MRI) methods at 14 Tesla in a genetically engineered KPC (KrasLSL-G12D/+, Trp53LSL-R172H/+, Cre) mouse model to assess the complex TME in advanced stages of tumor development. The whole tumor, excluding cystic areas, was selected as the region of interest for data analysis and subsequent statistical analysis. Pearson correlation was used for statistical inference. There was a significant correlation between tumor volume and T2 (r = -0.66), magnetization transfer ratio (MTR) (r = 0.60), apparent diffusion coefficient (ADC) (r = 0.48), and Glycosaminoglycan-chemical exchange saturation transfer (GagCEST) (r = 0.51). A subset of mice was randomly selected for histological analysis. There were positive correlations between tumor volume and fibrosis (0.92), and HA (r = 0.76); GagCEST and HA (r = 0.81); and MTR and CD31 (r = 0.48). We found a negative correlation between ADC low-b (perfusion) and Ki67 (r = -0.82). Strong correlations between mp-MRI and histology results suggest that mp-MRI can be used as a non-invasive tool to monitor the tumor microenvironment.

The dynamics of stress p53-Mdm2 network regulated by p300 and HDAC1.

We construct a stress p53-Mdm2-p300-HDAC1 regulatory network that is activated and stabilised by two regulatory proteins, p300 and HDAC1. Different activation levels of [Formula: see text] observed due to these regulators during stress condition have been investigated using a deterministic as well as a stochastic approach to understand how the cell responds during stress conditions. We found that these regulators help in adjusting p53 to different conditions as identified by various oscillatory states, namely fixed point oscillations, damped oscillations and sustain oscillations. On assessing the impact of p300 on p53-Mdm2 network we identified three states: first stabilised or normal condition where the impact of p300 is negligible, second an interim region where p53 is activated due to interaction between p53 and p300, and finally the third regime where excess of p300 leads to cell stress condition. Similarly evaluation of HDAC1 on our model led to identification of the above three distinct states. Also we observe that noise in stochastic cellular system helps to reach each oscillatory state quicker than those in deterministic case. The constructed model validated different experimental findings qualitatively.