Fluorescence Spectroscopy Based Characterization of Flaxseed Oil.

Fluorescence spectroscopy has been employed for the compositional analysis of flaxseed oil, detection of its adulteration and investigation of the thermal effects on its molecular composition. Excitation wavelengths from 320 to 420 nm have been used to explore the valued ingredients in flaxseed oil. The emission bands of flaxseed oil centred at 390, 414, 441, 475, 515 and 673/720 nm represent vitamin K, isomers of vitamin E, carotenoids and chlorophylls, which can be used as a marker for quality analysis. Due to its high quality, it is highly prone to adulteration and in this study, detection of its adulteration with canola oil is demonstrated by applying principal component analysis. Moreover, the effects of temperature on the molecular composition of cold pressed flaxseed oil has been explored by heating them at cooking temperatures of 100, 110, 120, 130, 140, 150, 160, 170 and 180 °C, each for 30 min. On heating, the deterioration of vitamin E, carotenoids and chlorophylls occurred with an increase in the oxidation products. However, it was found that up to 140 °C, flaxseed oil retains much of its natural composition whereas up to 180 oC, it loses much of its valuable ingredients along with increase of oxidized products.

Assessment of heavy metals level in chicken with indeterminate analysis in localities of Lahore, Pakistan.

The poultry industry is a significant source of animal protein, vitamins, and minerals, particularly through the consumption of chicken meat. In order to conduct the study, 100 samples of liver, chicken feed, and drinking water were collected in nearby areas of Lahore. The investigation aims to detect the presence of specific heavy metals in the collected samples. For this purpose, atomic absorption spectroscopy (AAS) was used to detect heavy metals after proper preparation of the samples. The experimentally observed data were analyzed through a novel statistical approach known as neutrosophic statistics. It was observed that copper (Cu), zinc (Zn), and cadmium (Cd) were the most prominent metals detected with contamination above the safe limits (for chicken drinking water (Zn = 23.09±13.67 mg/L, Cu = 3.84±3.04 mg/L, Cd = 0.805±0.645 mg/L, Pb = 0.275±0.095 mg/L, As = 0.982±0.978 mg/L), for chicken feed (Zn = 2.705±0.715 mg/kg, Cu = 1.85±0.53 mg/kg, Cd = 3.065±1.185 mg/kg, Pb = 0.215±0.175 mg/kg, As = 0.68±0.22 mg/kg), and chicken's liver (Zn = 3.93±0.66 mg/kg, Cu = 1.2±0.52 mg/kg, Cd = 0.07±0.05 mg/kg, Pb = 0.805±0.775 mg/kg, As = 1.05±0.8 mg/kg)). Similarly, the statistical analysis leads that the findings emphasize the importance of monitoring and mitigating heavy metal contamination in the poultry industry to ensure the safety and quality of poultry products.

Correction: Biogenic synthesis of silver nanoparticles using Rubus fruticosus extract and their antibacterial efficacy against Erwinia caratovora and Ralstonia solanacearum phytopathogens.

[This corrects the article DOI: 10.1039/D3RA06723H.].

Modulating plant-soil microcosm with green synthesized ZnONPs in arsenic contaminated soil.

Biogenic nanoparticle (NP), derived from plant sources, is gaining prominence as a viable, cost-effective, sustainable, and biocompatible alternative for mitigating the extensive environmental impact of arsenic on the interplay between plant-soil system. Herein, the impact of green synthesized zinc oxide nanoparticles (ZnONPs) was assessed on Catharanthus roseus root system-associated enzymes and their possible impact on microbiome niches (rhizocompartments) and overall plant performance under arsenic (As) gradients. The application of ZnONPs at different concentrations successfully modified the arsenic uptake in various plant parts, with the root arsenic levels increasing 1.5 and 1.4-fold after 25 and 50 days, respectively, at medium concentration compared to the control. Moreover, ZnONPs gradients regulated the various soil enzyme activities. Notably, urease and catalase activities showed an increase when exposed to low concentrations of ZnONPs, whereas saccharase and acid phosphatase displayed the opposite pattern, showing increased activities under medium concentration which possibly in turn influence the plant root system associated microflora. The use of nonmetric multidimensional scaling ordination revealed a significant differentiation (with a significance level of p < 0.05) in the structure of both bacterial and fungal communities under different treatment conditions across root associated niches. Bacterial and fungal phyla level analysis showed that Proteobacteria and Basidiomycota displayed a significant increase in relative abundance under medium ZnONPs concentration, as opposed to low and high concentrations, respectively. Similarly, in depth genera level analysis revealed that Burkholderia, Halomonas, Thelephora and Sebacina exhibited a notably high relative abundance in both the rhizosphere and rhizoplane (the former refers to the soil region influenced by root exudates, while the latter is the root surface itself) under medium concentrations of ZnONPs, respectively. These adjustments to the plant root-associated microcosm likely play a role in protecting the plant from oxidative stress by regulating the plant's antioxidant system and overall biomass.

Biochar and saline soil: mitigation strategy by incapacitating the ecological threats to agricultural land.

Soil salinity caused a widespread detrimental issue that hinders productivity in agriculture and ecological sustainability, while waste-derived soil amendments like biochar have drawn attention for their capacity to act as a mitigating agent, by enhancing the physical and chemical features of soil, and contributing to the recovery of agricultural waste resources. However, the information concerning biochar and salinity which affect the physicochemical characteristics of soils, crop physiology, and growth is limited. To investigate whether biochar mitigates the salinity stress on wheat crop seedlings, we grow them with salinity stress (120 mM), and biochar (20 tons ha-1), and its interactive effects. The soil properties of soil organic carbon (SOC), soil organic matter (SOM), dissolved organic carbon (DOC), and soil available phosphorus (SAP) decreased in the saline soil by 36.71%, 46.97%, 26.31%, and 15.00%, while biochar treatment increased SOC, DOC, and SAP contents by 7.42%, 31.57%, and 15.00%, respectively. On the other hand, dissolved organic nitrogen (DON) contents decreased in all the treatments compared to the control. The root growth traits, SPAD values, leaf nitrogen, photosynthetic parameters, antioxidant enzymes, and reactive oxygen species decreased in the saline treatment while increasing in the biochar and interactive treatment. Thus, these activities resulted in higher leaves and root biomass in the biochar treatment alone and interactive treatment of salinity and biochar. According to principal component analysis, redundancy analysis, and the mantel test, using biochar in conjunction with salinity treatment was found to be more effective than salinity treatment alone. The results of this study suggest that biochar can be used as a sustainable agricultural technique and a means of mitigation agent by lowering soil salinity while increasing the biomass of crops.

Biochar improves the physical and nutritional quality of soil and plant function.Salinity stress declined the physiological activities and biomass of the crop.Biochar mitigates the salinity stress in soil and enhances the plant functioning.Exposure to both treatments enhances the antioxidant enzyme activity and biomass.

Construction land reduction projects as a pathway to sustainability: an empirical analysis of risks factors in China.

Construction land reduction (CLR) is an effective instrument to improve intensive land use, restrict the expansion of construction land, safeguard the requisition-compensation balance of construction land in China, and realize sustainable development. But multiple risks arise from the process of construction land reduction. In that case, identifying and analyzing the key risks of CLR is the prerequisite for formulating practical policy guidelines. This study is conducted to identify the risk factors of CLR and analyze these risks based on expert opinion. Initially, the original risk factors are sourced from existing literature. In order to tailor them to China's specific context, the Delphi method is employed to systematically refine risk definitions, consolidate similar risk elements, and identify any previously unrecognized risks in the literature. Following an in-depth review of the literature, we create a contextual relationship-based model employing an integrated technique of interpretive structural modeling (ISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis. Based on the ISM and MICMAC analysis, five key risks were identified, and the prevention strategies and policy recommendations for CLR project risks are put forward.

Study of Synthesis of Dual-Curing Thermoplastic Polyurethane Hot-Melt Adhesive and Optimization by Using Gray Relational Analysis to Apply in Fabric Industry to Solve Seamless Bonding Issues.

People wear clothes for warmth, survival and necessity in modern life, but in the modern era, eco-friendliness, shortened production times, design and intelligence also matter. To determine the relationship between data series and verify the proximity of each data series, a gray relational analysis, or GRA, is applied to textiles, where seamless bonding technology enhances the bond between components. In this study, a polyurethane prepolymer, 2-hydroxyethyl acrylate (2-HEA) as an end-capping agent and n-octyl acrylate (ODA) as a photoinitiator were used to synthesize a dual-curing polyurethane hot-melt adhesive. Taguchi quality engineering and a gray relational analysis were used to discuss the influence of different mole ratios of NCO:OH and the effect of the molar ratio of the addition of octyl decyl acrylate on the mechanical strength. The Fourier transform infrared spectroscopy (FTIR) results showed the termination of the prepolymer's polymerization reaction and the C=O peak intensity at 1730 cm-1, indicating efficient bonding to the main chain. Advanced Polymer Chromatography (APC) was used to investigate the high-molecular-weight (20,000-30,000) polyurethane polymer bonded with octyl decyl acrylate to achieve a photothermosetting effect. The thermogravimetric analysis (TGA) results showed that the thermal decomposition temperature of the polyurethane hot-melt adhesive also increased, and they showed the highest pyrolysis temperature (349.89 °C) for the polyhydric alcohols. Furthermore, high peel strength (1.68 kg/cm) and shear strength (34.94 kg/cm2) values were detected with the dual-cure photothermosetting polyurethane hot-melt adhesive. The signal-to-noise ratio was also used to generate the gray relational degree. It was observed that the best parameter ratio of NCO:OH was 4:1 with five moles of monomer. The Taguchi quality engineering method was used to find the parameters of single-quality optimization, and then the gray relation calculation was used to obtain the parameter combination of multi-quality optimization for thermosetting the polyurethane hot-melt adhesive. The study aims to meet the requirements of seamless bonding in textile factories and optimize experimental parameter design by setting target values that can effectively increase production speed and reduce processing time and costs as well.

Predicting resilient modulus: A data driven approach integrating physical and numerical techniques.

Resilient modulus (MR) is an important parameter in the design of pavement that helps to characterize the quality of sub-grade materials. Generally, it is not determined experimentally due to time consuming, uneconomical, laborious and lack of advanced equipment in many laboratories. The aim of this research is to determine MR values using experimental (Ultrasonic pulse velocity (UPV) and Cyclic Triaxial) and Artificial neural network (ANN) techniques. For experimental study twenty-four soil samples comprising of coarse and fine-grained soils were collected from different locations. For ANN modelling, Input variables comprised of essential soil Atterberg limits (liquid limit, plastic limit, plasticity index) and compaction properties (maximum dry density, optimum moisture content). The validation of ANN model is done by comparing its results with the experimentally evaluated MR from UPV and Cyclic Triaxial test. Experimental results showed that Cyclic Triaxial test yielded resilient modulus value that was 5 % more than obtained from the UPV test. Moreover, results showed that modulus of resilience (MR) values determined by UPV, and artificial neural network (ANN) modelling have significant closeness with the cyclic triaxial results of resilient modulus; thus, making it a significant development in predicting resilient modulus efficiently.

Biogenic synthesis of silver nanoparticles using Rubus fruticosus extract and their antibacterial efficacy against Erwinia caratovora and Ralstonia solanacearum phytopathogens.

In the current research, we produced green, cost-effective, eco-friendly silver nanoparticles using a single-step approach. Plants are considered highly desirable systems for nanoparticle synthesis because they possess a variety of secondary metabolites with significant reduction potential. In the current research, the dried leaf extract of Rubus fruticosus was utilized as a capping and reducing agent for the fabrication of silver nanoparticles, to prepare reliable biogenic silver nanoparticles and subsequently to investigate their potential against some common phytopathogens. The prepared silver nanoparticles were exploited to quantify the total flavonoid content (TFC), total phenolic content (TPC) and DPPH-based antioxidant activity. Different concentrations of aqueous extracts of plant leaves and silver nitrate (AgNO3) were reacted, and the color change of the reactant mixture confirmed the formation of Rubus fruticosus leaf-mediated silver nanoparticles (RFL-AgNPs). A series of characterization techniques such as UV-vis spectroscopy, transmission electron microscopy, energy dispersive X-ray analysis and X-ray diffraction revealed the successful synthesis of silver nanoparticles. The surface plasmon resonance peak appeared at 449 nm. XRD analysis demonstrated the crystalline nature, EDX confirmed the purity, and TEM demonstrated that the nanoparticles are mostly spherical in form. Furthermore, the biosynthesized nanoparticles were screened for in vitro antibacterial activity, antioxidant activity, and total phenolic and flavonoid content. The nanoparticles were used in different concentrations alone and in combination with plant extracts to inhibit Erwinia caratovora and Ralstonia solanacearum. In high-throughput assays used to inhibit these plant pathogens, the nanoparticles were highly toxic against bacterial pathogens. This study can be exploited for planta assays against phytopathogens utilizing the same formulations for nanoparticle synthesis and to develop potent antibacterial agents to combat plant diseases.

Dynamics of Malaria Incidence in Khyber Pakhtunkhwa, Pakistan: Unveiling Rapid Growth Patterns and Forecasting Future Trends.

BACKGROUND: Malaria remains a formidable worldwide health challenge, with approximately half of the global population at high risk of catching the infection. This research study aimed to address the pressing public health issue of malaria's escalating prevalence in Khyber Pakhtunkhwa (KP) province, Pakistan, and endeavors to estimate the trend for the future growth of the infection. METHODS: The data were collected from the IDSRS of KP, covering a period of 5 years from 2018 to 2022. We proposed a hybrid model that integrated Prophet and TBATS methods, allowing us to efficiently capture the complications of the malaria data and improve forecasting accuracy. To ensure an inclusive assessment, we compared the prediction performance of the proposed hybrid model with other widely used time series models, such as ARIMA, ETS, and ANN. The models were developed through R-statistical software (version 4.2.2). RESULTS: For the prediction of malaria incidence, the suggested hybrid model (Prophet and TBATS) surpassed commonly used time series approaches (ARIMA, ETS, and ANN). Hybrid model assessment metrics portrayed higher accuracy and reliability with lower MAE (8913.9), RMSE (3850.2), and MAPE (0.301) values. According to our forecasts, malaria infections were predicted to spread around 99,301 by December 2023. CONCLUSIONS: We found the hybrid model (Prophet and TBATS) outperformed common time series approaches for forecasting malaria. By December 2023, KP's malaria incidence is expected to be around 99,301, making future incidence forecasts important. Policymakers will be able to use these findings to curb disease and implement efficient policies for malaria control.

The evolutionary trajectories of specialized metabolites towards antiviral defense system in plants.

Viral infections in plants pose major challenges to agriculture and global food security in the twenty-first century. Plants have evolved a diverse range of specialized metabolites (PSMs) for defenses against pathogens. Although, PSMs-mediated plant-microorganism interactions have been widely discovered, these are mainly confined to plant-bacteria or plant-fungal interactions. PSM-mediated plant-virus interaction, however, is more complicated often due to the additional involvement of virus spreading vectors. Here, we review the major classes of PSMs and their emerging roles involved in antiviral resistances. In addition, evolutionary scenarios for PSM-mediated interactions between plant, virus and virus-transmitting vectors are presented. These advancements in comprehending the biochemical language of PSMs during plant-virus interactions not only lay the foundation for understanding potential co-evolution across life kingdoms, but also open a gateway to the fundamental principles of biological control strategies and beyond.

Histotoxicity induced by copper oxide nanoparticles (CuO-NPs) on developing mice (Mus musculus).

The wide range of applications of nanoparticles (NPs) in various industries have led to serious consequences in terms of teratogenic toxicity. The aim of current work was to evaluate the teratogenic effects of copper oxide (CuO) nanoparticles in albino mice.In this experimental study, after mating, inseminated 40 female mice were divided randomly into 4 pools (1 control and 3 experimental), ten each. Doses were administered intravenously (We followed the protocol by Yaqub et al. (2018), intravenous application is faster route as compared to oral dosage)to all the experimental groups on the 6th day of gestation (GD), dose concentrations were 200, 133.3 and 100 mg/kg body weights respectively.The doses were prepared in sequence (1/2, 1/3, 1/4 0f LD50) according to already published work. The effects of CuO-NPs show linear relationship with the above sequence. The control group was administered only with distilled water.The gravid females were sacrificed through cervical disruption at the 18th day of gestation, fetuses were removed and divided into four sets (pools) for morphometric, morphological and histological studies. Data were subjected to statistical analysis by using Tukey's test in light of ANOVA at p < 0.05 level of significance. Findings of the present study showed that CuO-NPs various concentrations affect developmental abnormalities i.e.runt embryos, resorbed uteri, exencephaly, hygroma, macroglossia, micromelia, open eye, omphalocoel, scoliosis, kyphosis and kinked tail. It is concluded that exposure to CuO-NPs may potentially lead to the developmental deformities in mice.

Effects of meteorological conditions on the mixing height of Nitrogen dioxide in China using new-generation geostationary satellite measurements and machine learning.

Nitrogen dioxide (NO2) plays a critical role in terms of air quality, human health, ecosystems, and its impact on climate change. While the crucial roles of the vertical structure of NO2 have been acknowledged for some time, there is currently limited knowledge about this aspect in China. The Geostationary Environment Monitoring Spectrometer (GEMS) is the world's first geostationary satellite instrument capable of measuring the hourly columnar amount of NO2. The study presented here introduces the use of mixing height for NO2 in the atmosphere. A thorough examination of spatiotemporal variations in the mixing height of NO2 was conducted using data from both the GEMS and ground-based air quality monitoring networks. A random forest model based on machine learning techniques was utilized to examine how meteorological parameters affect the mixing height of NO2. The results of our study reveal a notable seasonal fluctuation in the mixing height of NO2, with the highest values observed during the summer and the lowest values during the winter. Additionally, there was an increasing diurnal trend from early morning to mid-afternoon. Moreover, the study discovered elevated NO2 mixing heights in the dry regions of northern China. The results also indicated a positive correlation between the mixing height of NO2 and temperature and wind speed, while negative associations were found with relative humidity and air pressure. The machine learning model's predicted NO2 mixing heights were in good agreement with the measurement-based outcomes, as evidenced by a coefficient of determination (R2) value of 0.96 (0.84 for the 10-fold cross-validation). These findings emphasize the noteworthy influence of meteorological variables on the vertical distribution of NO2 in the atmosphere and enhance our comprehension of the three-dimensional variations in NO2.

Development and Validation of RP-HPLC Method for the Determination of Enoxaparin Sodium in Dry Injection Formulation.

Enoxaparin sodium is an anticoagulant medication that is used as a blood thinning agent. It is mostly used for the treatment and prevention of deep vein thrombosis (DVT) and pulmonary embolism (PE). It is also used in certain surgeries and during pregnancy. For the treatment of acute coronary syndrome (ACS) and heart attacks, it may be used. Enoxaparin sodium was validated by the RP-HPLC method. A simple RP-HPLC method was developed in a single HPLC run in a dry powder injection formulation. All injections of HPLC sample were 20 µL volume. The chromatographic separation was completed in the isocratic mode. The used column was USP-L8 (250 mm × 4.6 mm) of BDS type of 10 µm meters in the same mobile phase throughout the analysis by using methanol and ultrapure water with a ratio of 7:93, respectively. The flow rate was 1.0 mL/min. The mobile phase was filtered through 0.45 µm filter paper, and isocratic elution was performed. The refractive index (RI) detector was used to analyze this sample. The specific peak of enoxaparin sodium was observed at 5:56 min. The calculated detection limit (LOD) was 0.351 ppm, and the calculated quantitation limit was 1.063 ppm. In repeatability of precision, the average calculated assay (%) was 100.85%, and the calculated RSD (%) was 0.01. In the accuracy test, the RSD (%) was 0.50, and the mean recovery (%) was 100.35. The system's suitability was within the limit. This newly developed method is proposed according to ICH guidelines, and rules and can be applied effectively for the exact estimation of enoxaparin sodium in injection formulation. This newly developed methodology is affordable in cost as long as less time is taken and the consumption of samples is in smaller quantities for every investigation. In medicinal chemistry, the USP (United States Pharmacopeia) and BP (British Pharmacopeia) are directly involved in production as well as in quality testing.

Generation of novel in vitro flexible kidney organoid model to investigate the role of extracellular vesicles in induction of nephrogenesis.

BACKGROUND: During kidney organogenesis, metanephric mesenchyme (MM) and ureteric bud (UB) interact reciprocally to form nephrons. Signaling stimuli involved in these interactions include Wnts, growth factors and nano/micro particles. How UB and MM are interacting is not completely understood. Our study investigated the signaling and communication via extracellular vesicles (EVs) during nephrogenesis. Embryonic day (E) 11.5 mouse kidney UB and MM produce very low number of primary cells that have limited ability for proliferation in culture. Such limitations obstruct studying the role of EVs in induction of nephrogenesis. These issues necessitate to generate a nephrogenesis model allowing to study the comprehensive role of EVs during nephrogenesis. RESULTS: Our study generated a UB derived cell line-based in vitro flexible model of nephrogenesis allowing expandable cell culturing, in addition to performing characterization, tracking and blocking of EVs. UB cell line aggregation with E11.5 MM cells induced the formation of segmented nephrons. Most efficient nephrogenesis was obtained by the co-culturing of 30,000 cells of UB cell line with 50,000 MM cells. Results revealed that both the UB and the MM secrete EVs during nephrogenesis. UB cell line derived EVs were characterized by their size, morphology and expression of markers (CD63, TSG101, CD9 and CD81). Furthermore, proteomics data of UB cell line-derived EVs revealed large number of proteins involved in nephrogenesis-related signaling pathways. Palmitoylated GFP-tagged EVs from UB cell line were found in the nephron formation zone in the developing kidney organoid. UB cell line derived EVs did not induce nephrogenesis in MM cells but significantly contributed to the survival and nephrogenesis-competency of MM cells. The secretion of EVs was continuously inhibited during the ongoing nephrogenesis by the knockdown of RalA and RalB gene expression using short hairpin RNAs. This inhibition partially impaired the ability of UB cell line to induce nephrogenesis. Moreover, impaired nephrogenesis was partially rescued by the addition of EVs. CONCLUSION: Our study established a novel in vitro flexible model of nephrogenesis that solved the limitations of primary embryonic kidney cells and mouse embryonic stem cell kidney organoids for the EV research. EVs were found to be an integral part of nephrogenesis process. Video Abstract.

Genome-wide identification and expression analysis of GA20ox and GA3ox genes during pod development in peanut.

Background: Gibberellins (GAs) play important roles in regulating peanut growth and development. GA20ox and GA3ox are key enzymes involved in GA biosynthesis. These enzymes encoded by a multigene family belong to the 2OG-Fe (II) oxygenase superfamily. To date, no genome-wide comparative analysis of peanut AhGA20ox and AhGA3ox-encoding genes has been performed, and the roles of these genes in peanut pod development are not clear. Methods: A whole-genome analysis of AhGA20ox and AhGA3ox gene families in peanut was carried out using bioinformatic tools. The expression of these genes at different stage of pod development was analyzed using qRT-PCR. Results: In this study, a total of 15 AhGA20ox and five AhGA3ox genes were identified in peanut genome, which were distributed on 14 chromosomes. Phylogenetic analysis divided the GA20oxs and GA3oxs into three groups, but AhGA20oxs and AhGA3oxs in two groups. The conserved pattern of gene structure, cis-elements, and protein motifs further confirmed their evolutionary relationship in peanut. AhGA20ox and AhGA3ox genes were differential expressed at different stages of pod development. The strong expression of AhGA20ox1/AhGA20ox4, AhGA20ox12/AhGA20ox15, AhGA3ox1 and AhGA3ox4/AhGA3ox5 in S1-stage indicated that these genes could have a key role in controlling peg elongation. Furthermore, AhGA20ox and AhGA3ox also showed diverse expression patterns in different peanut tissues including leaves, main stems, flowers and inflorescences. Noticeably, AhGA20ox9/AhGA20ox11 and AhGA3o4/AhGA3ox5 were highly expressed in the main stem, whereas the AhGA3ox1 and AhGA20ox10 were strongly expressed in the inflorescence. The expression levels of AhGA20ox2/AhGA20ox3, AhGA20ox5/AhGA20ox6, AhGA20ox7/AhGA20ox8, AhGA20ox13/AhGA20ox14 and AhGA3ox2/AhGA3ox3 were high in the flowers, suggesting their involvement in flower development. These results provide a basis for deciphering the roles of AhGA20ox and AhGA3ox in peanut growth and development, especially in pod development.

CePP2C19 confers tolerance to drought by regulating the ABA sensitivity in Cyperus esculentus.

BACKGROUND: Tiger nut (Cyperus esculentus) is widely known as an additional source of food, oil and feed worldwide. The agricultural production of tiger nut has been greatly hindered by drought stress, reducing both yield and quality. Protein phosphatase 2 C (PP2Cs) plays an important role in plant responses to drought stress however, the molecular mechanism of PP2Cs in tiger nuts still unclear. RESULTS: In this study, we identified a putative group A PP2C-encoding gene (CePP2C19) from tiger nut using transcriptome analysis, which is highly induced by drought stress. The transient expression assay suggested that CePP2C19 was localized to nucleus. Furthermore, the interaction between CePP2C19 and CePYR1, a coreceptor for ABA signaling, was first detected using a yeast two-hybrid assay and then verified using a bimolecular fluorescence complementation (BiFC) analysis. In addition, the transgenic Arabidopsis lines overexpressing CePP2C19 exhibited extreme tolerance to ABA and mannitol stresses during seed germination and root growth. At the mature stage, overexpression of CePP2C19 resulted in a higher tolerance to drought stress in transgenic Arabidopsis, as confirmed by a visible phenotype and several physiological parameters. Noticeably, the silencing of CePP2C19 by virus-induced gene silencing (VIGS) showed obvious reduction in drought tolerance in tiger nut plants. CONCLUSIONS: The CePP2C19 emerges as a pivotal gene involved in the ABA signaling pathway, which likely reduce ABA sensitivity and thus enhances drought tolerance in Cyperus esculentus.

Fabrication, Properties, and Stability of Oregano Essential Oil and Sodium Alginate-Based Wound-Healing Hydrogels.

The wound dressings fabricated by polymers and oregano essential oil (OEO) can be very effective as a hydrogel. The current study has been focused on fabricating the hydrogel membranes of oregano oil encapsulated as an antibacterial agent into sodium alginate (SA) solution by solvent casting method and then evaluated the antibacterial, antioxidant activity, and physicochemical performance of SA/OEO-based polymeric membranes. The polymeric interactions, surface morphology, water absorption capability, thermal stability, and encapsulation efficiency were investigated by FT-IR, SEM, swelling ratio, DSC, and encapsulation efficiency. The percentage encapsulation efficiency of essential oil was 40.5%. FTIR validated the presence of molecular interaction between individual components. SEM images showed a rough and porous appearance for hydrogel membranes. Moreover, DSC showed that the fabricated membranes were thermally stable. The inclusion of more content OEO decreased swelling ratios. The antioxidant test was carried out by DPPH assay and antibacterial test through disc diffusion method against microbes. The results revealed that membranes containing the highest content of OEO had more excellent antioxidant and antibacterial efficacy. Therefore, the polymeric membranes of sodium alginate loaded with oregano essential oil can be employed as an effective wound-healing candidate.

Utilizing hydrothermal time models to assess the effects of temperature and osmotic stress on maize (Zea mays L.) germination and physiological responses.

The application of germination models in economic crop management makes them extremely useful for predicting seed germination. Hence, we examined the effect of varying water potentials (Ψs; 0. - 0.3, - 0.6, - 0.9, - 1.2 MPa) and temperatures (Ts; 20, 25, 30, 35, 40 °C) on maize germination and enzymatic antioxidant mechanism. We observed that varying Ts and Ψs significantly influenced germination percentage (GP) and germination rate (GR), and other germination parameters, including germination rate index (GRI), germination index (GI), mean germination index (MGI), mean germination time (MGT), coefficient of the velocity of germination (CVG), and germination energy (GE) (p ≤ 0.01). Maximum (87.60) and minimum (55.20) hydro-time constant (θH) were reported at 35 °C and 20 °C, respectively. In addition, base water potential at 50 percentiles was highest at 30 °C (15.84 MPa) and lowest at 20 °C (15.46 MPa). Furthermore, the optimal, low, and ceiling T (To, Tb and Tc, respectively) were determined as 30 °C, 20 °C and 40 °C, respectively. The highest θT1 and θT2 were reported at 40 °C (0 MPa) and 20 °C (- 0.9 MPa), respectively. HTT has a higher value (R2 = 0.43 at 40 °C) at sub-optimal than supra-optimal temperatures (R2 = 0.41 at 40 °C). Antioxidant enzymes, including peroxidase (POD), catalase (CAT), superoxide dismutase (SOD), ascorbate peroxidase (APX), and glutathione peroxidase (GPX), increased with decreasing Ψs. In contrast, CAT and POD were higher at 20 °C and 40 °C but declined at 25, 30, and 35 °C. The APX and GPX remained unchanged at 20, 25, 30, and 40 °C but declined at 35 °C. Thus, maintaining enzymatic activity is a protective mechanism against oxidative stress. A decline in germination characteristics may result from energy diverting to anti-stress tools (antioxidant enzymes) necessary for eliminating reactive oxygen species (ROS) to reduce salinity-induced oxidative damage. The parameters examined in this study are easily applicable to simulation models of Z. mays L. germination under extreme environmental conditions characterized by water deficits and temperature fluctuations.

BlockAuth: A blockchain-based framework for secure vehicle authentication and authorization.

Intelligent Transport System (ITS) offers inter-vehicle communication, safe driving, road condition updates, and intelligent traffic management. This research intends to propose a novel decentralized "BlockAuth" architecture for vehicles, authentication, and authorization, traveling across the border. It is required because the existing architects rely on a single Trusted Authority (TA) for issuing certifications, which can jeopardize privacy and system integrity. Similarly, the centralized TA, if failed, can cause the whole system to collapse. Furthermore, a unique "Proof of Authenticity and Integrity" process is proposed, redirecting drivers/vehicles to their home country for authentication, ensuring the security of their credentials. Implemented with Hyperledger Fabric, BlockAuth ensures secure vehicle authentication and authorization with minimal computational overhead, under 2%. Furthermore, it opens up global access, enforces the principles of separation of duty and least privilege, and reinforces resilience via decentralization and automation.