Effect of illite on the mechanical properties of subgrade soil under varying surcharge loads.

Due to its non-expanding properties, presence of Illite mineral in subgrade soil is investigated particularly on California bearing ratio (CBR), resilient modulus (MR) and swell potential. Multiple samples of stiff and weak subgrade soils with varying illite percentages were tested under six different surcharge loads ranging from 2.27 to 13.8 kg. Mineralogical analysis is performed using X-ray diffractometer and MR of soil is assessed using Ultrasonic pulse velocity (UPV) technique. Results showed a positive correlation between Illite percentage and both CBR and MR value. The soil with higher Illite content tends to exhibit higher CBR and MR values while those with higher montmorillonite content show lower values even with more Illite content. The CBR and MR values increases from 8.4% to 19 % and 139 MPa-315 MPa for stiff soil and 3.8%-11.7 % and 23 MPa-83 MPa for weak soil, respectively when the surcharge load was increase from to 2.27-13.8 kg. Additionally, a decrease in swell potential was observed from 1.64% to 1.09 % for stiff soil and 1.39%-0.84 % for weak soil with an increase in Illite percentage. The study also developed an improved relationship for predicting resilient modulus based on CBR value, showing a strong correlation with equations developed by many researchers in the past.

The Carthamus tinctorius L. genome sequence provides insights into synthesis of unsaturated fatty acids.

Domesticated safflower (Carthamus tinctorius L.) is a widely cultivated edible oil crop. However, despite its economic importance, the genetic basis underlying key traits such as oil content, resistance to biotic and abiotic stresses, and flowering time remains poorly understood. Here, we present the genome assembly for C. tinctorius variety Jihong01, which was obtained by integrating Oxford Nanopore Technologies (ONT) and BGI-SEQ500 sequencing results. The assembled genome was 1,061.1 Mb, and consisted of 32,379 protein-coding genes, 97.71% of which were functionally annotated. Safflower had a recent whole genome duplication (WGD) event in evolution history and diverged from sunflower approximately 37.3 million years ago. Through comparative genomic analysis at five seed development stages, we unveiled the pivotal roles of fatty acid desaturase 2 (FAD2) and fatty acid desaturase 6 (FAD6) in linoleic acid (LA) biosynthesis. Similarly, the differential gene expression analysis further reinforced the significance of these genes in regulating LA accumulation. Moreover, our investigation of seed fatty acid composition at different seed developmental stages unveiled the crucial roles of FAD2 and FAD6 in LA biosynthesis. These findings offer important insights into enhancing breeding programs for the improvement of quality traits and provide reference resource for further research on the natural properties of safflower.

Safflower CtFLS1-Induced Drought Tolerance by Stimulating the Accumulation of Flavonols and Anthocyanins in Arabidopsis thaliana.

Flavonol synthase gene (FLS) is a member of the 2-oxoglutarate-dependent dioxygenase (2-ODD) superfamily and plays an important role in plant flavonoids biosynthetic pathways. Safflower (Carthamus tinctorius L.), a key source of traditional Chinese medicine, is widely cultivated in China. Although the flavonoid biosynthetic pathway has been studied in several model species, it still remains to be explored in safflower. In this study, we aimed to elucidate the role of CtFLS1 gene in flavonoid biosynthesis and drought stress responses. The bioinformatics analysis on the CtFLS1 gene showed that it contains two FLS-specific motifs (PxxxIRxxxEQP and SxxTxLVP), suggesting its independent evolution. Further, the expression level of CtFLS1 in safflower showed a positive correlation with the accumulation level of total flavonoid content in four different flowering stages. In addition, CtFLS1-overexpression (OE) Arabidopsis plants significantly induced the expression levels of key genes involved in flavonol pathway. On the contrary, the expression of anthocyanin pathway-related genes and MYB transcription factors showed down-regulation. Furthermore, CtFLS1-OE plants promoted seed germination, as well as resistance to osmotic pressure and drought, and reduced sensitivity to ABA compared to mutant and wild-type plants. Moreover, CtFLS1 and CtANS1 were both subcellularly located at the cell membrane and nucleus; the yeast two-hybrid and bimolecular fluorescence complementation (BiFC) assay showed that they interacted with each other at the cell membrane. Altogether, these findings suggest the positive role of CtFLS1 in alleviating drought stress by stimulating flavonols and anthocyanin accumulation in safflower.

The interaction between formylphenoxyacetic acid derivatives (chalcone and flavones) and ionic surfactants: Insights into binding constants, solubilisation and physiochemical properties.

In this study, UV-vis spectroscopy was employed to investigate the interaction between formylphenoxyacetic acid (FPAA) and its derivatives (chalcone and flavones) with ionic surfactants (SDS, CTAB, and DTAB) in different physiological environments. Changes in the physiochemical properties of FPAA chalcone and flavones including binding constants, partitioning constants, and Gibbs free energy were observed which were influenced by the presence of ionic surfactants computed using mathematical models. The solubilization of the targeted compounds in the ionic surfactants was determined through the binding constant (Kb). The results of the present study indicated that electrostatic interactions played a significant role in the solubilization of the targeted compounds in SDS, CTAB, and DTAB. At pH 4.1, FPAA chalcone exhibited stronger binding affinity with SDS compared to CTAB and DTAB. However, at pH 7.4, chalcone showed stronger binding with DTAB compared to SDS, while negligible interaction with CTAB was observed at pH 7.4. The flavones demonstrated stronger binding with DTAB at pH 7.4 compared to SDS and CTAB and it exhibited strong bonding with CTAB at pH 4.1. The negative values of the Gibbs free energy for binding (ΔGb˚) and partitioning (ΔGp˚) constants displayed the spontaneity of the process. However, FPAA chalcone with SDS and FPAA flavones with DTAB furnished positive ΔGb˚, indicating a non-spontaneous process.

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.

Nanoparticles incorporated hydrogels for delivery of antimicrobial agents: developments and trends.

The prevention and treatment of microbial infections is an imminent global public health concern due to the poor antimicrobial performance of the existing antimicrobial regime and rapidly emerging antibiotic resistance in pathogenic microbes. In order to overcome these problems and effectively control bacterial infections, various new treatment modalities have been identified. To attempt this, various micro- and macro-molecular antimicrobial agents that function by microbial membrane disruption have been developed with improved antimicrobial activity and lesser resistance. Antimicrobial nanoparticle-hydrogels systems comprising antimicrobial agents (antibiotics, biological extracts, and antimicrobial peptides) loaded nanoparticles or antimicrobial nanoparticles (metal or metal oxide) constitute an important class of biomaterials for the prevention and treatment of infections. Hydrogels that incorporate nanoparticles can offer an effective strategy for delivering antimicrobial agents (or nanoparticles) in a controlled, sustained, and targeted manner. In this review, we have described an overview of recent advancements in nanoparticle-hydrogel hybrid systems for antimicrobial agent delivery. Firstly, we have provided an overview of the nanoparticle hydrogel system and discussed various advantages of these systems in biomedical and pharmaceutical applications. Thereafter, different hybrid hydrogel systems encapsulating antibacterial metal/metal oxide nanoparticles, polymeric nanoparticles, antibiotics, biological extracts, and antimicrobial peptides for controlling infections have been reviewed in detail. Finally, the challenges and future prospects of nanoparticle-hydrogel systems have been discussed.

Enhanced efficiency of AgAlO2/g-C3N4 binary composite to degrade organic pollutants for environmental remediation under visible light irradiation.

This study explores the utilization of semiconductor-based photocatalysts for environmental remediation through photocatalytic degradation, harnessing solar energy for effective treatment. The primary focus is on the application of photocatalytic technology for the degradation of 2-chlorophenol and methylene blue, critical pollutants requiring remediation. The research involves the synthesis of binary AgAlO2/g-C3N4 nanocomposites through an exchange ion method, subsequent calcination, and sonication. This process enhances the transfer of photogenerated electrons from AgAlO2 to g-C3N4, resulting in a significantly increased reductive electron charge on the surface of g-C3N4. The photocatalytic activity of the synthesized composites is comprehensively examined in the degradation of 2-chlorophenol and methylene blue through detailed crystallographic, electron-microscopy, photoemission spectroscopy, electrochemical, and spectroscopic characterizations. Among the various composites, AgAlO2/20% g-C3N4 emerges as the most active photocatalyst, achieving an impressive 98% degradation of methylene blue and 97% degradation of 2-chlorophenol under visible light. Notably, AgAlO2/20% g-C3N4 surpasses bare AgAlO2 and bare g-C3N4, exhibiting 1.66 times greater methylene blue degradation and constant rate (k) values of 20.17 × 10-3 min-1, 4.18 × 10-3 min-1 and 3.48 × 10-3 min-1, respectively. The heightened photocatalytic activity is attributed to the diminished recombination rate of electron-hole pairs. Scavenging evaluations confirm that O2•- and h+ are the primary photoactive species steering methylene blue photodegradation over AgAlO2/g-C3N4 in the visible region. These findings present new possibilities for the development of efficient binary photocatalysts for environmental remediation.

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.

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.

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.].

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.

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.

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.

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.

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.

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.

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.