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The human population is growing at an extremely rapid rate, the demand of food supplies for the survival and sustainability of life is a gleaming challenge. Each living being in the planet gets bestowed with the healthy food to remain active and healthy. Agriculture is a domain which is extremely important as it provides the fundamental resources for survival in terms of supplying food and thus the economy of the entire world is highly dependent on agricultural production. The agricultural production is often affected by various environmental and geographical factors which are difficult to avoid being part of nature. Thus, it requires proactive mitigation plans to reduce any detrimental effect caused by the imbalance of these factors. Precision agriculture is an approach that incorporates information technology in agriculture management, the needs of crops and farming fields are fulfilled to optimized crop health and resultant crop production. The proposed study involves an ambient intelligence-based implementation using machine learning to classify diseases in tomato plants based on the images of its leaf dataset. To analytically evaluate the performance of the framework, a publicly available plant-village dataset is used which is transformed to appropriate form using one-hot encoding technique to meet the needs of the machine learning algorithm. The transformed data is dimensionally reduced by Principal Component Analysis (PCA) technique and further the optimal parameters are selected using Spider Monkey Optimization (SMO) approach. The most relevant features as selected using the Hybrid PCA-SMO technique fed into a Deep Neural Networks (DNN) model to classify the tomato diseases. The optimal performance of the DNN model after implementing dimensionality reduction by Hybrid PCA-SMO technique reached at 99% accuracy was achieved in training and 94% accuracy was achieved after testing the model for 20 epochs. The proposed model is evaluated based on accuracy and loss rate metrics; it justifies the superiority of the approach.

We described a copper(I)‐catalyzed atom economic and selective hydroamination‐cyclization of alkynyl‐tethered quinazolinones to prepare a variety of indole‐fused pyrazino[1,2‐a]quinazolinones in good to excellent yields ranging from 39 %–99 % under mild reaction conditions. Control experiments revealed that coordination‐directed method of quinazolinone moiety with copper(I) was important for the selective hydroamination‐cyclization of alkynes at the N1‐atom instead of N3‐atom of quinazolinone. The reaction could be easily performed at gram scales and some prepared indole‐fused pyrazino[1,2‐a]quinazolinones with donating groups on the indole moiety showed a distinct fluorescence emission wavelength with blue shift under the acid conditions. [ABSTRACT FROM AUTHOR]

Antibacterial photocatalytic therapy (APCT) is one of the most promising non‐antibiotic treatment strategies for biofilm‐infected wounds and inflammation caused by drug‐resistant bacteria. However, it still faces issues such as inadequate single antibacterial capacity and lack of antioxidant capacity. In this study, a Z‐scheme heterojunction (Bi2S3‐X@PDA) is designed using a polydopamine (PDA) shell firmly anchored to the surface of sulfur vacancy‐rich bismuth sulfide nanorods (Bi2S3‐X NRs). Under near‐infrared light and hydrogen peroxide, Bi2S3‐X@PDA significantly improves the photocatalytic efficiency of reactive oxygen species generation and shows a nearly 100% broad‐spectrum antibacterial effect against multiple bacterial strains and bacterial biofilms in vitro. Interestingly, the antioxidant activity of the PDA shell in Bi2S3‐X@PDA remarkably downregulates the expression of pro‐inflammatory factors and promotes macrophage reprogramming toward the proregenerative M2 phenotype. In a mouse wound model of methicillin‐resistant Staphylococcus aureus biofilm infection, Bi2S3‐X@PDA effectively eliminates drug‐resistant bacterial biofilms through APCT/mild photothermal therapy, while reducing inflammation in normal tissues and regulating the immune microenvironment, thereby promoting rapid wound healing. Overall, this light‐controlled treatment strategy, which provides both antibacterial and anti‐inflammatory functions, is a reliable tool for combating biofilm infection and inflammation caused by drug‐resistant bacteria. [ABSTRACT FROM AUTHOR]

Hepatic ischemia-reperfusion injury (IRI) is a common pathological process during hepatectomy and liver transplantation and the two primary reasons for hepatic IRI are reactive oxygen species (ROS)-mediated oxidative stress and excessive inflammatory responses. Herein, a novel antioxidant nanodrug (A-MPDA@Fe3O4@PVP) is prepared by employing L -arginine-doped mesoporous polydopamine (A-MPDA) nanoparticles as the carrier for deposition of ultra-small ferric oxide (Fe3O4) nanoparticles and further surface modification with polyvinylpyrrolidone (PVP). A-MPDA@Fe3O4@PVP not only effectively reduces the aggregation of ultra-small Fe3O4, but also simultaneously replicates the catalytic activity of catalase (CAT) and superoxide dismutase (SOD). A-MPDA@Fe3O4@PVP with good antioxidant activity can rapidly remove various toxic reactive oxygen species (ROS) and effectively regulate macrophage polarization in vitro. In the treatment of hepatic IRI, A-MPDA@Fe3O4@PVP effectively alleviates ROS-induced oxidative stress, reduces the expression of inflammatory factors, and prevents apoptosis of hepatocytes through immune regulation. A-MPDA@Fe3O4@PVP can further protect liver tissue by activating the PPARγ/NF-κB pathway. This multiplex antioxidant enzyme therapy can provide new references for the treatment of IRI in organ transplantation and other ROS-related injuries such as fibrosis, cirrhosis, and bacterial and hepatic viral infection. [ABSTRACT FROM AUTHOR]

We assessed the prognostic utility of the new perinephric fat adherence risk score - Mayo Adhesive Probability (MAP), in patients of East Asian ethnicity undergoing either laparoscopic partial nephrectomy (LPN) or laparoscopic radical nephrectomy (LRN). A retrospective analysis of clinical data was carried out on 169 patients who either underwent LPN or LRN surgery. These patients were categorized into two groups, group A (0-2 points) and group B (3-4 points) using the new MAP score. The overall clinical data between these two groups was compared and potential risk factors were investigated using logistic regression analyses. The new MAP score yielded an area under the curve of 0.761 (95 % CI: 0.691-0.831), indicating its effectiveness. Group B had a significantly higher incidence of adherent perirenal fat (APF) during surgery (p<0.001) and had a greater average age (p<0.001). There was an increased prevalence of hypertension (p=0.009), type 2 diabetes mellitus (p<0.001), and MAFLD (p<0.001) in group B. Additionally, there were significant differences in posterior perinephric fat thickness (p<0.05), lateral perinephric fat thickness (p<0.001), and perinephric stranding (p<0.001) between the two groups. The new MAP score holds significance in predicting APF in people of East Asian ethnicity undergoing LPN or LRN, and there is a strong correlation between elevated MAP scores and risk factors such as MAFLD and advanced age. [ABSTRACT FROM AUTHOR]