Surface-engineered vertically-aligned ZnO nanorod for sensitive non-enzymatic electrochemical monitoring of cholesterol.

Developing highly sensitive and selective non-enzymatic electrochemical biosensors for disease biomarker detection has become challenging in healthcare applications. However, advances in material science are opening new avenues for creating more dependable biosensing technologies. In this context, the present work introduces a novel approach by engineering a hybrid structure of zinc oxide nanorod (ZnO NR) modified with iron oxide nanoparticle (Fe2O3 NP) on an FTO electrode. This Fe2O3 NP-ZnO NR hybrid material functions as a nanozyme, facilitating the catalysis of cholesterol and enabling the direct transfer of electrons to the fluorine-doped tin oxide (FTO) electrode, limiting the need for costly and traditional enzymes in the detection process. This innovative non-enzymatic cholesterol biosensor showcases remarkable sensitivity, registering at 642.8 µA/mMcm2 within a linear response range of up to 9.0 mM. It also exhibits a low detection limit (LOD) of ∼12.4 µM, ensuring its capability to detect minimal concentrations of cholesterol accurately. Moreover, the developed biosensor displays exceptional selectivity by effectively distinguishing cholesterol molecules from other interfering biological species, while exhibiting outstanding stability and reproducibility. Our findings indicate that the Fe2O3 NP-ZnO NR hybrid nanostructure on the FTO electrode holds promise for enhancing biosensor stability. Furthermore, the present device fabrication platform offers versatility, as it can be adapted with various enzymes or modified with different metal oxides, potentially broadening its applicability in a wide range of biomarkers detection.

A grain-like cerium oxide nanostructure: synthesis and uric acid sensing application.

Utilizing nanomaterials on the working electrode of sensors enables the fabrication of highly sensitive devices for the detection of various analytes. Herein, a facile synthesis method is used to formulate a grain-like cerium oxide (CeO2) nanostructure. The structural features and surface properties of the synthesized CeO2 nanostructure were studied, which showed that the CeO2 nanostructure exhibited grain-like morphology, good crystalline structure, and excellent vibrational properties. To evaluate the sensing properties of grain-like CeO2 nanostructure, nanomaterial slurry was prepared in butyldiglycol acetate binder. Then, the nanomaterial slurry was drop-casted onto the working electrode of the screen-printed carbon electrode (SPCE) to fabricate the CeO2-modified SPCE sensor. The sensor's electrochemical properties were analysed, which showed excellent charge-transfer behavior compared to the bare SPCE. CV-based electrochemical sensing of uric acid (UA) on a CeO2-modified SPCE sensor exhibited excellent linear performance up to 1070 µM UA. Moreover, the sensor offers good sensitivity, low detection limit, reproducibility, selectivity, and long-term stability. The CeO2-modified SPCE sensor demonstrated a promising application for UA detection in real samples, addressing the need for timely UA concentration monitoring.

Genome-Wide Identification and Expression Analysis of MYB Transcription Factor Family in Response to Various Abiotic Stresses in Coconut (Cocos nucifera L.).

Abiotic stresses such as nitrogen deficiency, drought, and salinity significantly impact coconut production, yet the molecular mechanisms underlying coconut's response to these stresses are poorly understood. MYB proteins, a large and diverse family of transcription factors (TF), play crucial roles in plant responses to various abiotic stresses, but their genome-wide characterization and functional roles in coconut have not been comprehensively explored. This study identified 214 CnMYB genes (39 1R-MYB, 171 R2R3-MYB, 2 3R-MYB, and 2 4R-MYB) in the coconut genome. Phylogenetic analysis revealed that these genes are unevenly distributed across the 16 chromosomes, with conserved consensus sequences, motifs, and gene structures within the same subgroups. Synteny analysis indicated that segmental duplication primarily drove CnMYB evolution in coconut, with low nonsynonymous/synonymous ratios suggesting strong purifying selection. The gene ontology (GO) annotation of protein sequences provided insights into the biological functions of the CnMYB gene family. CnMYB47/70/83/119/186 and CnMYB2/45/85/158/195 were identified as homologous genes linked to nitrogen deficiency, drought, and salinity stress through BLAST, highlighting the key role of CnMYB genes in abiotic stress tolerance. Quantitative analysis of PCR showed 10 CnMYB genes in leaves and petioles and found that the expression of CnMYB45/47/70/83/85/119/186 was higher in 3-month-old than one-year-old coconut, whereas CnMYB2/158/195 was higher in one-year-old coconut. Moreover, the expression of CnMYB70, CnMYB2, and CnMYB2/158 was high under nitrogen deficiency, drought, and salinity stress, respectively. The predicted secondary and tertiary structures of three key CnMYB proteins involved in abiotic stress revealed distinct inter-proteomic features. The predicted interaction between CnMYB2/158 and Hsp70 supports its role in coconut's drought and salinity stress responses. These results expand our understanding of the relationships between the evolution and function of MYB genes, and provide valuable insights into the MYB gene family's role in abiotic stress in coconut.

The ability of selected fungal strains to produce carboxylesterase enzymes for biodegradation and use of bifenthrin insecticide as carbon source: in vitro and in silico approaches.

Bifenthrin (BF) is a broad-spectrum type I pyrethroid insecticide that acts on insects by impairing the nervous system and inhibiting ATPase activity, and it has toxic effects on non-target organisms and high persistence in the environment. This study aimed to determine the potential of six different fungi, including Pseudozyma hubeiensis PA, Trichoderma reesei PF, Trichoderma koningiopsis PD, Purpureocillium lilacinum ACE3, Talaromyces pinophilus ACE4, and Aspergillus niger AJ-F3, to degrade BF. Three different concentrations of BF, including 0.1%, 0.2%, and 0.3% w/v, were used in the sensitivity testing that revealed a significant (p ≤ 0.01) impact of BF on fungal growth. Enzymatic assays demonstrated that both intracellular and extracellular carboxylesterases hydrolyzed BF with the enzymatic activity of up to 175 ± 3 U (µmol/min) and 45 ± 1 U, respectively. All tested fungi were capable of utilizing BF as a sole carbon source producing 0.06 ± 0.01 to 0.45 ± 0.01 mg dry biomass per mg BF. Moreover, the presence of PytH was determined in the fungi using bioinformatics tools and was found in A. niger, T. pinophilus, T. reesei, and P. lilacinum. 3D structures of the PytH homologs were predicted using AlphaFold2, and their intermolecular interactions with pyrethroids were determined using MOE. All the homologs interacted with different pyrethroids with a binding energy of lesser than - 10 kcal/mol. Based on the study, it was concluded that the investigated fungi have a greater potential for the biodegradation of BF.

Electrochemical detection of nalbuphine drug using oval-like ZnO nanostructure-based sensor.

Monitoring pharmaceutical drugs in various mediums is crucial to mitigate adverse effects. This study presents a chemical sensor using an oval-like zinc oxide (ZnO) nanostructure for electrochemical detection of nalbuphine. The ZnO nanostructure, produced via an efficient sol-gel technique, was extensively characterized using field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), UV-visible spectrophotometry, and fourier transform infrared spectroscopy (FTIR). A slurry of the ZnO nanostructure in a binder was applied to a glassy carbon electrode (GCE). The sensor's responsiveness to nalbuphine was assessed using linear sweep voltammetry (LSV), achieving optimal performance by fine-tuning the pH. The sensor demonstrated a proportional response to nalbuphine concentrations up to 150.0 nM with a good regression coefficient (R2) and a detection limit of 6.20 nM (S/N ratio of 3). Selectivity was validated against various interfering substances, and efficacy was confirmed through real sample analysis, highlighting the sensor's successful application for nalbuphine detection.

Aflatoxins in Wheat Grains: Detection and Detoxification through Chemical, Physical, and Biological Means.

Wheat (Triticum aestivum L.) is an essential food crop in terms of consumption as well as production. Aflatoxin exposure has a widespread public health impact in economically developing nations, so there is a need to establish preventive techniques for these high-risk populations. Pre-harvest and post-harvest practices are the two strategies used to control aflatoxin contamination, which include the use of genetically modified crops that show resistance against Aspergillus infection, the use of pesticides, changing the planting and harvesting time of crops, and physical, chemical, and biological methods. In this research, aflatoxin detection and quantification were performed in different wheat varieties to determine quantitative differences in comparison to the European Commission's limit of 4 ppb aflatoxins in wheat. TLC for qualitative and the ELISA kit method for quantitative analysis of aflatoxins were used. Out of 56 samples, 35 were found contaminated with aflatoxins, while the remaining 21 samples did not show any presence of aflatoxins. Out of the 35 contaminated samples, 20 samples showed aflatoxin contamination within the permissible limit, while the remaining 15 samples showed aflatoxin concentration beyond the permissible level, ranging from 0.49 to 20.56 ppb. After quantification, the nine highly contaminated wheat samples were detoxified using physical, chemical, and biological methods. The efficiency of these methods was assessed, and they showed a significant reduction in aflatoxins of 53-72%, 79-88%, and 80-88%, respectively. In conclusion, the difference in aflatoxin concentration in different wheat varieties could be due to genetic variations. Furthermore, biological treatment could be the method of choice for detoxification of aflatoxins in wheat as it greatly reduced the aflatoxin concentration with no harmful effect on the quality of the grains.

Ectomycorrhiza and ethylenediurea reduced the impact of high nitrogen and ozone stresses and increased the growth of Cedrus deodara.

Cedrus deodara is the central conifer plant affected by ozone and nitrogen pollutants among forest species worldwide. The growth of C. deodara depends upon the ectomycorrhizal (ECM) association, which is usually disturbed by these factors. This study aims to understand how these factors affect plants at physiological and biochemical levels. Three fungal strain consortiums were inoculated with two-year-old C. deodara seedlings. The stresses of 100 kg N h-1and 100 ppb O3 were applied for six months to study their impact on chlorophyll and antioxidant enzymes (SOD, CAT, and APX). The results showed that C2 (Consortium of Cedrus deodara) positively impacted the growth of selected plant species. The high photosynthesis rate was determined by enhanced chlorophyll content, and C2-treated plants showed high chlorophyll content. Relatively, chlorophyll a and b contents increased significantly in the seedlings treated with Ethylenediurea (EDU) alone and with ozone stress. In addition, a significant difference was observed between EDU and O3-treated plants (14% EDU400-O3 and 23% EDU600-O3) and the control. Overall, antioxidant activities were higher in the treated samples than in the control. The order of SOD activity was C2 (448 U/gFW) and lowest (354.7 U/gFW) in control. APX also showed higher activity in treated plants in C1 ≥ C2 ≥ C3+O3, whereas CAT activity was the highest in C2 treatments. Ozone and nitrogen-stressed plants showed higher activities than EDU-treated plants compared to non-treated ones. Our findings highlight the importance of understanding the signaling effects of numerous precursors. Moreover, an extended investigation of seedlings developing into trees must be conducted to verify the potential of ectomycorrhizal strains associated with C. deodara and comprehend EDU's role as a direct molecular scavenger of reactive toxicants.

An Electroanalytical Enzymeless α-Fe2O3-ZnO Hybrid Nanostructure-Based Sensor for Sensitive Quantification of Nitrite Ions.

Nitrite monitoring serves as a fundamental practice for protecting public health, preserving environmental quality, ensuring food safety, maintaining industrial safety standards, and optimizing agricultural practices. Although many nitrite sensing methods have been recently developed, the quantification of nitrite remains challenging due to sensitivity and selectivity limitations. In this context, we present the fabrication of enzymeless iron oxide nanoparticle-modified zinc oxide nanorod (α-Fe2O3-ZnO NR) hybrid nanostructure-based nitrite sensor fabrication. The α-Fe2O3-ZnO NR hybrid nanostructure was synthesized using a two-step hydrothermal method and characterized in detail utilizing x-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS). These analyses confirm the successful synthesis of an α-Fe2O3-ZnO NR hybrid nanostructure, highlighting its morphology, purity, crystallinity, and elemental constituents. The α-Fe2O3-ZnO NR hybrid nanostructure was used to modify the SPCE (screen-printed carbon electrode) for enzymeless nitrite sensor fabrication. The voltammetric methods (i.e., cyclic voltammetry (CV) and differential pulse voltammetry (DPV)) were employed to explore the electrochemical characteristics of α-Fe2O3-ZnO NR/SPCE sensors for nitrite. Upon examination of the sensor's electrochemical behavior across a range of nitrite concentrations (0 to 500 µM), it is evident that the α-Fe2O3-ZnO NR hybrid nanostructure shows an increased response with increasing nitrite concentration. The sensor demonstrates a linear response to nitrite concentrations up to 400 µM, a remarkable sensitivity of 18.10 µA µM-1 cm-2, and a notably low detection threshold of 0.16 µM. Furthermore, its exceptional selectivity, stability, and reproducibility make it an ideal tool for accurately measuring nitrite levels in serum, yielding reliable outcomes. This advancement heralds a significant step forward in the field of environmental monitoring, offering a potent solution for the precise assessment of nitrite pollution.

Impact of Bacillus licheniformis-Fermented Products on Growth and Productivity in Heat-Stressed Laying Ducks.

The purpose of this study was to assess the impact of various concentrations of Bacillus licheniformis-fermented products (BLFP) on the growth and productivity of laying ducks (Anas platyrhynchos) subjected to heat stress during eight weeks of a feeding trial. A total of 150 one-day-old Brown Tsaiya ducks of both sexes were divided into five groups, with each group having three replicates and 10 ducks each for evaluation of growth performance. The treatment groups received dietary supplements of BLFP at levels of 0.1%, 0.2%, and 0.3%, along with a group receiving flavomycin (F) at 5 ppm, all over a 24-week period. The fermentation process in this study utilized a B. licheniformis strain (ATCC 12713) for the production of the spores through solid-state fermentation. The control group was given a basal diet consisting of yellow corn and soybean meal. The results showed that as compared to the flavomycin group, ducks in the 0.3% BLFP group had significantly higher body weights and better feed conversion rates. In addition, during the three weeks, the BLFP group showed higher feed consumption as compared to the control group. The jejunum villi length was significantly increased in the 0.2% BLPF group as compared to the control and flavomycin groups. This study also found that the flavomycin group had a significantly higher egg conversion rate, while the 0.1-0.3% BLFP groups had improved feed intake and the 0.3% group had significantly enhanced egg yolk color. Additionally, the 0.2% BLFP group showed substantial decreases in IL-1ß, TNF-α, IL-6, and IL-10 levels in the liver as well as an uptick in the tight junction protein Occludin gene expression in the colon when compared to the control group. Furthermore, the expression of the heat shock protein 70 in the gut upregulated in the 0.1% and 0.2% BLFP groups. In conclusion, these observations demonstrate that dietary supplementation of 0.2% BLFP is an ideal concentration to increase gut morphology, alleviate inflammatory response, and promote gut integrity in heat-stressed laying ducks.

A systematic review of robotic efficacy in coral reef monitoring techniques.

Coral reefs are home to a variety of species, and their preservation is a popular study area; however, monitoring them is a significant challenge, for which the use of robots offers a promising answer. The purpose of this study is to analyze the current techniques and tools employed in coral reef monitoring, with a focus on the role of robotics and its potential in transforming this sector. Using a systematic review methodology examining peer-reviewed literature across engineering and earth sciences from the Scopus database focusing on "robotics" and "coral reef" keywords, the article is divided into three sections: coral reef monitoring, robots in coral reef monitoring, and case studies. The initial findings indicated a variety of monitoring strategies, each with its own advantages and disadvantages. Case studies have also highlighted the global application of robotics in monitoring, emphasizing the challenges and opportunities unique to each context. Robotic interventions driven by artificial intelligence and machine learning have led to a new era in coral reef monitoring. Such developments not only improve monitoring but also support the conservation and restoration of these vulnerable ecosystems. Further research is required, particularly on robotic systems for monitoring coral nurseries and maximizing coral health in both indoor and open-sea settings.

Application of machine learning for identification of heterotic groups in sunflower through combined approach of phenotyping, genotyping and protein profiling.

Application of machine learning in plant breeding is a recent concept, that has to be optimized for precise utilization in the breeding program of high yielding crop plants. Identification and efficient utilization of heterotic grouping pattern aided with machine learning approaches is of utmost importance in hybrid cultivar breeding as it can save time and resources required to breed a new plant hybrid/variety. In the present study, 109 genotypes of sunflower were investigated at morphological, biochemical (SDS-PAGE) and molecular levels (through micro-satellites (SSR) markers) for heterotic grouping. All the three datasets were combined, scaled, and subjected to unsupervised machine learning algorithms, i.e., Hierarchical clustering, K-means clustering and hybrid clustering algorithm (hierarchical + K-means) for assessment of efficiency and resolution power of these algorithms in practical plant breeding for heterotic grouping identification. Following the application of machine learning unsupervised clustering approach, two major groups were identified in the studied sunflower germplasm, and further classification revealed six smaller classes in each major group through hierarchical and hybrid clustering approach. Due to high resolution, obtained in hierarchical clustering, classification achieved through this algorithm was further used for selection of potential parents. One genotype from each smaller group was selected based on the maximum seed yield potential and hybridized in a line × tester mating design producing 36 F1 cross combinations. These F1s along with their parents were studied in open field conditions for validating the efficacy of identified heterotic groups in sunflowers genetic material under study. Data for 11 agronomic and qualitative traits were recorded. These 36 F1 combinations were tested for their combining ability (General/Specific), heterosis, genotypic and phenotypic correlation and path analysis. Results suggested that F1 hybrids performed better for all the traits under investigation than their respective parents. Findings of the study validated the use of machine learning approaches in practical plant breeding; however, more accurate and robust clustering algorithms need to be developed to handle the data noisiness of open field experiments.

Smart-sight: Video-based waste characterization for RDF-3 production.

A material recovery facility (MRF) can transform municipal solid waste (MSW) into a valued commodity called refuse-derived fuel (RDF) as a promising solution to waste-to-energy conversion. The quality of the produced RDF significantly relies on the composition of in-feed waste and waste characterization method applied for auditing purposes, a process that is both time-consuming and fraught with potential hazards. This study focuses to enhance the workflow of the waste characterization process at an MRF. A solution named Smart Sight is proposed to detect and classify waste based on videos recorded after processing MSW through a mechanical sorting line consisting of bag breakers and trommel screens. A comprehensive dataset is created encompassing thirteen mixed waste classes from single and multi-family streams. The dataset is preprocessed with motion compensation techniques and frame differencing methods to extract and refine valuable frames. A one-stage YOLO detector model is then trained over the dataset. The experimental results show that the proposed method works efficiently at detecting and classifying waste objects in indoor MRF environments. Accuracy, precision, recall, and F1 score related to the proposed solution are found to be 0.70, 0.762, 0.69 and 0.72, respectively, with a mAP@0.5 of 0.716. The proposed approach is validated using data collected from local MRF by comparing the estimated waste composition values of the proposed solution with laboratory results obtained through current standardized industrial practices. Comparison reveals that waste characterization estimation obtained is consistent with the laboratory results, inferring that Smart-Sight is a viable tool for estimating waste composition.

Management and control of coccidiosis in poultry - A review.

Poultry coccidiosis is an intestinal infection caused by an intracellular parasitic protozoan of the genus Eimeria. Coccidia-induced gastrointestinal inflammation results in large economic losses, hence finding methods to decrease its prevalence is critical for industry participants and academic researchers. It has been demonstrated that coccidiosis can be effectively controlled and managed by employing anticoccidial chemical compounds. However, as a result of their extensive use, anticoccidial drug resistance in Eimeria species has raised concerns. Phytochemical/herbal medicines (Artemisia annua, Bidens pilosa, and garlic) seem to be a promising strategy for preventing coccidiosis, in accordance with the "anticoccidial chemical-free" standards. The impact of herbal supplements on poultry coccidiosis is based on the reduction of oocyst output by preventing the proliferation and growth of Eimeria species in chicken gastrointestinal tissues and lowering intestinal permeability via increased epithelial turnover. This review provides a thorough up-to-date assessment of the state of the art and technologies in the prevention and treatment of coccidiosis in chickens, including the most used phytochemical medications, their mode of action, and the applicable legal framework in the European Union.

Real-time expression and in silico characterization of pea genes involved in salt and water-deficit stress.

BACKGROUND: To tolerate salt and water-deficit stress, the plant adapts to the adverse environment by regulating its metabolism and expressing certain stress-induced metabolic pathways. This research analyzed the relative expression of four pea genes (P5CR, PAL1, SOD, and POX) in three pea varieties (Climax, Green grass, and Meteor) under different levels of salt and water-deficit stress. METHODS AND RESULTS: The experiments on salt stress and water-deficit stress were carried out within greenhouse settings under controlled environment. The saturation percentage was employed to create artificial salinity conditions: Control without NaCl treatment, Treatment 1: 50 mM NaCl treatment, Treatment 2: 75 mM NaCl treatment, and Treatment 3: 100 mM NaCl treatment. Field capacity (FC) was used for the development of artificial water-deficit treatments in the pots, i.e., Treatment 1 (Control; water application 100% of FC), Treatment 2 (water application 75% of FC), and Treatment 3 (water application 50% of FC). Pea genes involved in biosynthetic pathways of proline, flavonoids, and enzymatic antioxidant enzymes including P5CR, PAL1, SOD, and POX were selected based on literature. Quantitative real-time PCR using cDNA as a template was used to analyze the gene expression. Pea genes were analyzed for phylogenetic analysis in closely related crops having similarity percent identity 80% and above. In silico characterization of selected proteins including the family classification was done by the NCBI CDD and INTERPRO online servers. Results from RT-qPCR analysis showed increased expression of P5CR, PAL1, and POX genes, while SOD gene expression decreased under both stresses. Climax exhibited superior stress tolerance with elevated expression of P5CR and PAL1, while Meteor showed better tolerance through increased POX expression. Phylogenetic analysis revealed common ancestry with other species like chickpea, red clover, mung bean, and barrel clover, suggesting the cross relationship among these plant species. Conserved domain analysis of respective proteins revealed that these proteins contain PLNO 2688, PLN02457, Cu-Zn Superoxide dismutase, and secretory peroxidase conserved domains. Furthermore, protein family classification indicated that the oxidation-reduction process is the most common chemical process involved in these stresses given to pea plant which validates the relationship of these proteins. CONCLUSIONS: Salt and water-deficit stresses trigger distinct metabolic pathways, leading to the up-regulation of specific genes and the synthesis of corresponding proteins. These findings further emphasize the conservation of stress-tolerance-related genes and proteins across various plant species. This knowledge enhances our understanding of plant adaptation to stress and offers opportunities for developing strategies to improve stress resilience in crops, thereby addressing global food security challenges.

Design of Experiments to Compare the Mechanical Properties of Polylactic Acid Using Material Extrusion Three-Dimensional-Printing Thermal Parameters Based on a Cyber-Physical Production System.

The material extrusion 3D printing process known as fused deposition modeling (FDM) has recently gained relevance in the additive manufacturing industry for large-scale part production. However, improving the real-time monitoring of the process in terms of its mechanical properties remains important to extend the lifespan of numerous critical applications. To enhance the monitoring of mechanical properties during printing, it is necessary to understand the relationship between temperature profiles and ultimate tensile strength (UTS). This study uses a cyber-physical production system (CPPS) to analyze the impact of four key thermal parameters on the tensile properties of polylactic acid (PLA). Layer thickness, printing speed, and extrusion temperature are the most influential factors, while bed temperature has less impact. The Taguchi L-9 array and the full factorial design of experiments were implemented along with the deposited line's local fused temperature profile analysis. Furthermore, correlations between temperature profiles with the bonding strength during layer adhesion and part solidification can be stated. The results showed that layer thickness is the most important factor, followed by printing speed and extrusion temperature, with very close influence between each other. The lowest impact is attributed to bed temperature. In the experiments, the UTS values varied from 46.38 MPa to 56.19 MPa. This represents an increase in the UTS of around 17% from the same material and printing design conditions but different temperature profiles. Additionally, it was possible to observe that the influence of the parameter variations was not linear in terms of the UTS value or temperature profiles. For example, the increase in the UTS at the 0.6 mm layer thickness was around four times greater than the increase at 0.4 mm. Finally, even when it was found that an increase in the layer temperature led to an increase in the value of the UTS, for some of the parameters, it could be observed that it was not the main factor that caused the UTS to increase. From the monitoring conditions analyzed, it was concluded that the material requires an optimal thermal transition between deposition, adhesion, and layer solidification in order to result in part components with good mechanical properties. A tracking or monitoring system, such as the one designed, can serve as a potential tool for reducing the anisotropy in part production in 3D printing systems.

Antibacterial and antibiofilm activity of Abroma augusta stabilized silver (Ag) nanoparticles against drug-resistant clinical pathogens.

Infectious diseases remain among the most pressing concerns for human health. This issue has grown even more complex with the emergence of multidrug-resistant (MDR) bacteria. To address bacterial infections, nanoparticles have emerged as a promising avenue, offering the potential to target bacteria at multiple levels and effectively eliminate them. In this study, silver nanoparticles (AA-AgNPs) were synthesized using the leaf extract of a medicinal plant, Abroma augusta. The synthesis method is straightforward, safe, cost-effective, and environment friendly, utilizing the leaf extract of this Ayurvedic herb. The UV-vis absorbance peak at 424 nm indicated the formation of AA-AgNPs, with the involvement of numerous functional groups in the synthesis and stabilization of the particles. AA-AgNPs exhibited robust antibacterial and antibiofilm activities against methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE). The MIC values of AA-AgNPs ranged from 8 to 32 µg/mL. Electron microscopic examination of the interaction of AA-AgNPs with the test bacterial pathogens showed a deleterious impact on bacterial morphology, resulting from membrane rupture and leakage of intracellular components. AA-AgNPs also demonstrated a dose-dependent effect in curtailing biofilm formation below inhibitory doses. Overall, this study highlights the potential of AA-AgNPs in the successful inhibition of both the growth and biofilms of MRSA and VRE bacteria. Following studies on toxicity and dose optimization, such AgNPs could be developed into effective medical remedies against infections.

Industrial wastewater irrigation increased higher heavy metals uptake and expansins, metacaspases, and cystatin genes expression in Parthenium and maize.

Industrial wastewater irrigation of agricultural crops can cause a lot of environmental and health problems in developing countries due to heavy metals deposition in agricultural soils as well as edible plant consumption by human beings. Therefore, this study was conducted to find out the heavy metals concentration in industrial wastewater and soil irrigated with that wastewater. In addition, the aim was to determine the impact of industrial wastewater irrigation on Parthenium hysterophorus and Zea mays genes involved in growth improvement and inhibition. For this purpose, plant samples from agriculture fields irrigated with wastewater from Hattar Industrial Estate (HIE) of Haripur, Pakistan, and control plants from non-contaminated soil irrigated with tape water were collected after 15 and 45 days of germination. Heavy metals concentration in the collected plant samples, wastewater, and soil was determined. The results revealed that the soil of the sample collection site was predominantly contaminated with Cr, Pb, Ni, Cu, Co, Zn, and Cd up to the concentrations of 38.98, 21.14, 46.01, 155.73, 12.50, 68.50, and 7.01 mg/kg, respectively. The concentrations of these heavy metals were found to surpass the permissible limit in normal agricultural soil. Expansins, cystatins (plant growth enhancers), and metacaspases (plant growth inhibitor) gene expression were studied through reverse transcription polymerase chain reaction. The results showed that the expression of these genes was higher in samples collected from wastewater-irrigated soils as compared to control. The expression of these genes was observed in 45 days old samples, 15 days old samples, and control. Taken together, this study suggests the use of Parthenium and maize for phytoremediation and that they should not be used for eating purposes if irrigated with industrial wastewater.

Flexural Properties of Lattices Fabricated with Planar and Curved Layered Fused Filament Fabrication.

The use of curved layers in fused filament fabrication could lead to various advantages in surface finishing and mechanical properties. Here, the influence of three different structural and manufacturing parameters (volume fraction, raster arrangement, and the use of curved or planar layers) on the mechanical properties of lattice structures under three-point bending is studied. Two different raster arrangements were considered, i.e., those with rasters at planes parallel to the principal axes of the samples and those diagonally arranged, all at four different volume fractions. All different samples were additively manufactured using planar and curved layers. Samples were further dimensionally inspected to refine the computational models before their analysis via finite element simulations. The linear elastic region of the load-displacement curves was further analyzed numerically via finite element models. Predictions with finite element models resulted in good agreement with errors below 10%. Samples with diagonal rasters were 70% softer than those parallel to the principal axes.

Compositional analysis of natural pomegranate peel powder dried by different methods and nutritional and sensory evaluation of cookies fortified with pomegranate peel powder.

Introduction: Fortification of cereal products with natural plant extract is an interesting approach to fulfill the dietary requirement of the people. Materials and methods: Peels of pomegranate (rich source of natural compounds) were cut into small pieces and dried in three different methods such as solar drying (SOD), oven drying (OD), and sun drying (SUD). The fine powder was prepared and proximate compositions (protein, ash, moisture, fats, fiber, and carbohydrates), minerals (zinc, iron, calcium, and potassium), total phenolic content (TPC), total flavonoid content (TFC), and antioxidant activity (DPPH) of the pomegranate peel powder (PP) were evaluated. Fine wheat flour (FWF) was fortified with different concentrations (3, 6, 8, 10, and 12 g) of PP powder, cookies were prepared and all the above analysis along with physical parameters (weight, width, thickness, spread ration) and sensory analysis were conducted. Cookies without PP powder were served as control. Results and discussion: Results showed that a SOD was the best for drying PP powder in terms of compositional analysis. Addition of PP powder significantly (P < 0.05) enhanced the nutritional value, minerals profile and physical attributes of the fortified cookies. Sensory analysis of fortified cookies indicated that the cookies were acceptable to the sensory panel. Therefore, in conclusion, PP powder dried by SOD method could be used commercially in baking industries to provide nutritional enriched cookies to fulfill the dietary requirements of the people.

Highly Sensitive Electrochemical Non-Enzymatic Uric Acid Sensor Based on Cobalt Oxide Puffy Balls-like Nanostructure.

Early-stage uric acid (UA) abnormality detection is crucial for a healthy human. With the evolution of nanoscience, metal oxide nanostructure-based sensors have become a potential candidate for health monitoring due to their low-cost, easy-to-handle, and portability. Herein, we demonstrate the synthesis of puffy balls-like cobalt oxide nanostructure using a hydrothermal method and utilize them to modify the working electrode for non-enzymatic electrochemical sensor fabrication. The non-enzymatic electrochemical sensor was utilized for UA determination using cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The puffy balls-shaped cobalt oxide nanostructure-modified glassy carbon (GC) electrode exhibited excellent electro-catalytic activity during UA detection. Interestingly, when we compared the sensitivity of non-enzymatic electrochemical UA sensors, the DPV technique resulted in high sensitivity (2158 µA/mM.cm2) compared to the CV technique (sensitivity = 307 µA/mM.cm2). The developed non-enzymatic electrochemical UA sensor showed good selectivity, stability, reproducibility, and applicability in the human serum. Moreover, this study indicates that the puffy balls-shaped cobalt oxide nanostructure can be utilized as electrode material for designing (bio)sensors to detect a specific analyte.