Enhancing nitrogen use efficiency and yield of maize (Zea mays L.) through Ammonia volatilization mitigation and nitrogen management approaches.

Management of nitrogen (N) fertilizer is a critical factor that can improve maize (Zea mays L.) production. On the other hand, high volatilization losses of N also pollute the air. A field experiment was established using a silt clay soil to examine the effect of sulfur-coated urea and sulfur from gypsum on ammonia (NH3) emission, N use efficiency (NUE), and the productivity of maize crop under alkaline calcareous soil. The experimental design was a randomized complete block (RCBD) with seven treatments in three replicates: control with no N, urea150 alone (150 kg N ha-1), urea200 alone (200 kg N ha-1), urea150 + S (60 kg ha-1 S from gypsum), urea200 + S, SCU150 (sulfur-coated urea) and SCU200. The results showed that the urea150 + S and urea200 + S significantly reduced the total NH3 by (58 and 42%) as compared with the sole application urea200. The NH3 emission reduced further in the treatment with SCU150 and SCU200 by 74 and 65%, respectively, compared to the treatment with urea200. The maize plant biomass, grain yield, and total N uptake enhanced by 5-14%, 4-17%, and 7-13, respectively, in the treatments with urea150 + s and urea200 + S, relative to the treatment with urea200 alone. Biomass, grain yield, and total N uptake further increased significantly by 22-30%, 25-28%, and 26-31%, respectively, in the treatments with SCU150 and SCU200, relative to the treatment with urea200 alone. The applications of SCU150 enhanced the nitrogen use efficiency (NUE) by (72%) and SCU200 by (62%) respectively, compared with the sole application of urea200 alone. In conclusion, applying S-coated urea at a lower rate of 150 kg N ha-1 compared with a higher rate of 200 kg N ha-1 may be an effective way to reduce N fertilizer application rate and mitigate NH3 emission, improve NUE, and increase maize yield. More investigations are suggested under different soil textures and climatic conditions to declare S-coated urea at 150 kg N ha-1 as the best application rate for maize to enhance maize growth and yield.

An Omniphobic Spray Coating Created from Hierarchical Structures Prevents the Contamination of High-Touch Surfaces with Pathogens.

Engineered surfaces that repel pathogens are of great interest due to their role in mitigating the spread of infectious diseases. A robust, universal, and scalable omniphobic spray coating with excellent repellency against water, oil, and pathogens is presented. The coating is substrate-independent and relies on hierarchically structured polydimethylsiloxane (PDMS) microparticles, decorated with gold nanoparticles (AuNPs). Wettability studies reveal the relationship between surface texturing of micro- and/or nano-hierarchical structures and the omniphobicity of the coating. Studies of pathogen transfer with bacteria and viruses reveal that an uncoated contaminated glove transfers pathogens to >50 subsequent surfaces, while a coated glove picks up 104 (over 99.99%) less pathogens upon first contact and transfers zero pathogens after the second touch. The developed coating also provides excellent stability under harsh conditions. The remarkable anti-pathogen properties of this surface combined with its ease of implementation, substantiate its use for the prevention of surface-mediated transmission of pathogens.

A Simple Colorimetric Au-on-Au Tip Sensor with a New Functional Nucleic Acid Probe for Food-borne Pathogen Salmonella typhimurium.

An Au-on-Au tip sensor is developed for the detection of Salmonella typhimurium (Salmonella), using a new synthetic nucleic acid probe (NAP) as a linker for the immobilization of a DNA-conjugated Au nanoparticle (AuNP) onto a DNA-attached thin Au layer inside a pipette tip. In the presence of Salmonella, RNase H2 from Salmonella (STH2) cleaves the NAP and the freed DNA-conjugated AuNP can be visually detected by a paper strip. This portable biosensor does not require any electronic, electrochemical or optical equipment. It delivers a detection limit of 3.2×103  CFU mL-1 for Salmonella in 1 h without cell-culturing or signal amplification and does not show cross-reactivity with several control bacteria. Further, the sensor reliably detects Salmonella spiked in food samples, such as ground beef and chicken, milk, and eggs. The sensor can be reused and is stable at ambient temperature, showing its potential as a point-of-need device for the prevention of food poisoning by Salmonella.

Transparent and Highly Flexible Hierarchically Structured Polydimethylsiloxane Surfaces Suppress Bacterial Attachment and Thrombosis Under Static and Dynamic Conditions.

The surface fouling of biomedical devices has been an ongoing issue in healthcare. Bacterial and blood adhesion in particular, severely impede the performance of such tools, leading to poor patient outcomes. Various structural and chemical modifications have been shown to reduce fouling, but all existing strategies lack the combination of physical, chemical, and economic traits necessary for widespread use. Herein, a lubricant infused, hierarchically micro- and nanostructured polydimethylsiloxane surface is presented. The surface is easy to produce and exhibits the high flexibility and optical transparency necessary for incorporation into various biomedical tools. Tests involving two clinically relevant, priority pathogens show up to a 98.5% reduction in the biofilm formation of methicillin-resistant Staphylococcus aureus and Pseudomonas aeruginosa. With blood, the surface reduces staining by 95% and suppresses thrombin generation to background levels. Furthermore, the surface shows applicability within applications such as catheters, extracorporeal circuits, and microfluidic devices, through its effectiveness in dynamic conditions. The perfusion of bacterial media shows up to 96.5% reduction in bacterial adhesion. Similarly, a 95.8% reduction in fibrin networks is observed following whole blood perfusion. This substrate stands to hold high applicability within biomedical systems as a means to prevent fouling, thus improving performance.

Antibody Micropatterned Lubricant-Infused Biosensors Enable Sub-Picogram Immunofluorescence Detection of Interleukin 6 in Human Whole Plasma.

Recent studies have shown a correlation between elevated interleukin 6 (IL-6) concentrations and the risk of respiratory failure in COVID-19 patients. Therefore, detection of IL-6 at low concentrations permits early diagnosis of worst-case outcome in viral respiratory infections. Here, a versatile biointerface is presented that eliminates nonspecific adhesion and thus enables immunofluorescence detection of IL-6 in whole human plasma or whole human blood during coagulation, down to a limit of detection of 0.5 pg mL-1 . The sensitivity of the developed lubricant-infused biosensor for immunofluorescence assays in detecting low molecular weight proteins such as IL-6 is facilitated by i) producing a bioink in which the capture antibody is functionalized by an epoxy-based silane for covalent linkage to the fluorosilanized surface and ii) suppressing nonspecific adhesion by patterning the developed bioink into a lubricant-infused coating. The developed biosensor addresses one of the major challenges for biosensing in complex fluids, namely nonspecific adhesion, therefore paving the way for highly sensitive biosensing in complex fluids.

Material Breakthroughs in Smart Food Monitoring: Intelligent Packaging and On-Site Testing Technologies for Spoilage and Contamination Detection.

Despite extensive commercial and regulatory interventions, food spoilage and contamination continue to impose massive ramifications on human health and the global economy. Recognizing that such issues will be significantly eliminated by the accurate and timely monitoring of food quality markers, smart food sensors have garnered significant interest as platforms for both real-time, in-package food monitoring and on-site commercial testing. In both cases, the sensitivity, stability, and efficiency of the developed sensors are largely informed by underlying material design, driving focus toward the creation of advanced materials optimized for such applications. Herein, a comprehensive review of emerging intelligent materials and sensors developed in this space is provided, through the lens of three key food quality markers - biogenic amines, pH, and pathogenic microbes. Each sensing platform is presented with targeted consideration toward the contributions of the underlying metallic or polymeric substrate to the sensing mechanism and detection performance. Further, the real-world applicability of presented works is considered with respect to their capabilities, regulatory adherence, and commercial potential. Finally, a situational assessment of the current state of intelligent food monitoring technologies is provided, discussing material-centric strategies to address their existing limitations, regulatory concerns, and commercial considerations.

High-throughput fabrication of antimicrobial phage microgels and example applications in food decontamination.

Engineered by nature, biological entities are exceptional building blocks for biomaterials. These entities can impart enhanced functionalities on the final material that are otherwise unattainable. However, preserving the bioactive functionalities of these building blocks during the material fabrication process remains a challenge. We describe a high-throughput protocol for the bottom-up self-assembly of highly concentrated phages into microgels while preserving and amplifying their inherent antimicrobial activity and biofunctionality. Each microgel is comprised of half a million cross-linked phages as the sole structural component, self-organized in aligned bundles. We discuss common pitfalls in the preparation procedure and describe optimization processes to ensure the preservation of the biofunctionality of the phage building blocks. This protocol enables the production of an antimicrobial spray containing the manufactured phage microgels, loaded with potent virulent phages that effectively reduced high loads of multidrug-resistant Escherichia coli O157:H7 on red meat and fresh produce. Compared with other microgel preparation methods, our protocol is particularly well suited to biological materials because it is free of organic solvents and heat. Bench-scale preparation of base materials, namely microporous films (the template for casting microgels) and pure concentrated phage suspension, requires 3.5 h and 5 d, respectively. A single production run, that yields over 1,750,000 microgels, ranges from 2 h to 2 d depending on the rate of cross-linking chemistry. We expect that this platform will address bottlenecks associated with shelf-stability, preservation and delivery of phage for antimicrobial applications, expanding the use of phage for prevention and control of bacterial infections and contaminants.

Research and application of polypropylene: a review.

Polypropylene (PP) is a versatile polymer with numerous applications that has undergone substantial changes in recent years, focusing on the demand for next-generation polymers. This article provides a comprehensive review of recent research in PP and its advanced functional applications. The chronological development and fundamentals of PP are mentioned. Notably, the incorporation of nanomaterial like graphene, MXene, nano-clay, borophane, silver nanoparticles, etc., with PP for advanced applications has been tabulated with their key features and challenges. The article also conducts a detailed analysis of advancements and research gaps within three key forms of PP: fiber, membrane, and matrix. The versatile applications of PP across sectors like biomedical, automotive, aerospace, and air/water filtration are highlighted. However, challenges such as limited UV resistance, bonding issues, and flammability are noted. The study emphasizes the promising potential of PP while addressing unresolved concerns, with the goal of guiding future research and promoting innovation in polymer applications.

Comprehensive fluorescence profiles of contamination-prone foods applied to the design of microcontact-printed in situ functional oligonucleotide sensors.

With both foodborne illness and food spoilage detrimentally impacting human health and the economy, there is growing interest in the development of in situ sensors that offer real-time monitoring of food quality within enclosed food packages. While oligonucleotide-based fluorescent sensors have illustrated significant promise, the development of such on-food sensors requires consideration towards sensing-relevant fluorescence properties of target food products-information that has not yet been reported. To address this need, comprehensive fluorescence profiles for various contamination-prone food products are established in this study across several wavelengths and timepoints. The intensity of these food backgrounds is further contextualized to biomolecule-mediated sensing using overlaid fluorescent oligonucleotide arrays, which offer perspective towards the viability of distinct wavelengths and fluorophores for in situ food monitoring. Results show that biosensing in the Cyanine3 range is optimal for all tested foods, with the Cyanine5 range offering comparable performance with meat products specifically. Moreover, recognizing that mass fabrication of on-food sensors requires rapid and simple deposition of sensing agents onto packaging substrates, RNA-cleaving fluorescent nucleic acid probes are successfully deposited via microcontact printing for the first time. Direct incorporation onto food packaging yields cost-effective sensors with performance comparable to ones produced using conventional deposition strategies.

Predictive modeling of consumer purchase behavior on social media: Integrating theory of planned behavior and machine learning for actionable insights.

In recent times, it has been observed that social media exerts a favorable influence on consumer purchasing behavior. Many organizations are adopting the utilization of social media platforms as a means to promote products and services. Hence, it is crucial for enterprises to understand the consumer buying behavior in order to thrive. This article presents a novel approach that combines the theory of planned behavior (TPB) with machine learning techniques to develop accurate predictive models for consumer purchase behavior. This study examines three distinct factors of the theory of planned behavior (attitude, social norm, and perceived behavioral control) that provide insights into the primary determinants influencing online purchasing behavior. A total of eight machine learning algorithms, namely K-nearest neighbor, Decision Tree, Random Forest, Logistic Regression, Naive Bayes, Support Vector Machine, AdaBoost, and Gradient Boosting, were utilized in order to forecast consumer purchasing behavior. Empirical findings indicate that gradient boosting demonstrates superior performance in predicting customer buying behavior, with an accuracy rate of 0.91 and a macro F1 score of 0.91. This holds true when all factors, namely attitude (ATTD), social norm (SN), and perceived behavioral control (PBC), are included in the analysis. Furthermore, we incorporated Explainable AI (XAI), specifically LIME (Local Interpretable Model-Agnostic Explanations), to elucidate how the best machine learning model (i.e. gradient boosting) makes its prediction. The findings indicate that LIME has demonstrated a high level of confidence in accurately predicting the influence of low and high behavior. The outcome presented in this article has several implications. For instance, this article presents a novel way to combine the theory of planned behavior with machine learning techniques in order to predict consumer purchase behavior. This integration allows for a comprehensive analysis of factors influencing online purchasing decisions. Also, the incorporation of Explainable AI enhances the transparency and interpretability of the model. This feature is valuable for organizations seeking insights into factors driving predictions and the reasons behind certain outcomes. Moreover, these observations have the potential to offer valuable insights for businesses in customizing their marketing strategies to align with these influential factors.