Muscle relaxant and antipyretic effects of pentacyclic triterpenes isolated from the roots of Diospyros lotus L.

The present article describes the muscle relaxant and antipyretic effects of pentacyclic triterpenes, oleanolic acid (OA), ursolic acid (UA) and betulinic acid (BA) isolated from roots of Diospyros lotus in animal models. The muscle relaxant effects of isolated pentacyclic triterpenes were determined by chimney and inclined plane tests. In the chimney test, pretreatment of pentacyclic triterpenes evoked significant dose dependent influence on muscle coordination. When administered intraperitoneally (i.p.) to mice at 10 mg/kg for 90 min, OA, UA, and BA exhibited muscle relaxant effects of 66.72 %, 60.21 %, and 50.77 %, respectively. Similarly, OA, UA, and BA (at 10 mg/kg) illustrated 65.74 %, 59.84 % and 51.40 % muscle relaxant effects in the inclined plane test. In the antipyretic test, significant amelioration was caused by pretreatment of all compounds in dose dependent manner. OA, UA, and BA (at 5 mg/kg) showed 39.32 %, 34.32 % and 29.99 % anti-hyperthermic effects, respectively 4 h post-treatment, while at 10 mg/kg, OA, UA, and BA exhibited 71.59 %, 60.99 % and 52.44 % impact, respectively. The muscle relaxant effect of benzodiazepines is well known for enhancement of GABA receptors. There may exist a similar mechanism for muscle relaxant effect of pentacyclic triterpenes. The in-silico predicted binding pattern of all the compounds reflects good affinity of compounds with GABAA receptor and COX-2. These results indicate that the muscle relaxant and antipyretic activities of these molecules can be further improved by structural optimization.

QSAR-driven screening uncovers and designs novel pyrimidine-4,6-diamine derivatives as potent JAK3 inhibitors.

This study presents a robust and integrated methodology that harnesses a range of computational techniques to facilitate the design and prediction of new inhibitors targeting the JAK3/STAT pathway. This methodology encompasses several strategies, including QSAR analysis, pharmacophore modeling, ADMET prediction, covalent docking, molecular dynamics (MD) simulations, and the calculation of binding free energies (MM/GBSA). An efficacious QSAR model was meticulously crafted through the employment of multiple linear regression (MLR). The initial MLR model underwent further refinement employing an artificial neural network (ANN) methodology aimed at minimizing predictive errors. Notably, both MLR and ANN exhibited commendable performance, showcasing R2 values of 0.89 and 0.95, respectively. The model's precision was assessed via leave-one-out cross-validation (CV) yielding a Q2 value of 0.65, supplemented by rigorous Y-randomization. , The pharmacophore model effectively differentiated between active and inactive drugs, identifying potential JAK3 inhibitors, and demonstrated validity with an ROC value of 0.86. The newly discovered and designed inhibitors exhibited high inhibitory potency, ranging from 6 to 8, as accurately predicted by the QSAR models. Comparative analysis with FDA-approved Tofacitinib revealed that the new compounds exhibited promising ADMET properties and strong covalent docking (CovDock) interactions. The stability of the new discovered and designed inhibitors within the JAK3 binding site was confirmed through 500 ns MD simulations, while MM/GBSA calculations supported their binding affinity. Additionally, a retrosynthetic study was conducted to facilitate the synthesis of these potential JAK3/STAT inhibitors. The overall integrated approach demonstrates the feasibility of designing novel JAK3/STAT inhibitors with robust efficacy and excellent ADMET characteristics that surpass Tofacitinib by a significant margin.Communicated by Ramaswamy H. Sarma.

Identification of Disalicyloyl Curcumin as a Potential DNA Polymerase Inhibitor for Marek's Disease Herpesvirus: A Computational Study Using Virtual Screening and Molecular Dynamics Simulations.

Marek's disease virus (MDV) is a highly contagious and persistent virus that causes T-lymphoma in chickens, posing a significant threat to the poultry industry despite the availability of vaccines. The emergence of new virulent strains has further intensified the challenge of designing effective antiviral drugs for MDV. In this study, our main objective was to identify novel antiviral phytochemicals through in silico analysis. We employed Alphafold to construct a three-dimensional (3D) structure of the MDV DNA polymerase, a crucial enzyme involved in viral replication. To ensure the accuracy of the structural model, we validated it using tools available at the SAVES server. Subsequently, a diverse dataset containing thousands of compounds, primarily derived from plant sources, was subjected to molecular docking with the MDV DNA polymerase model, utilizing AutoDock software V 4.2. Through comprehensive analysis of the docking results, we identified Disalicyloyl curcumin as a promising drug candidate that exhibited remarkable binding affinity, with a minimum energy of -12.66 Kcal/mol, specifically targeting the DNA polymerase enzyme. To further assess its potential, we performed molecular dynamics simulations, which confirmed the stability of Disalicyloyl curcumin within the MDV system. Experimental validation of its inhibitory activity in vitro can provide substantial support for its effectiveness. The outcomes of our study hold significant implications for the poultry industry, as the discovery of efficient antiviral phytochemicals against MDV could substantially mitigate the economic losses associated with this devastating disease.

Preparation and Characterization of Physically Activated Carbon and Its Energetic Application for All-Solid-State Supercapacitors: A Case Study.

Biomass-derived activated carbons have gained significant attention as electrode materials for supercapacitors (SCs) due to their renewability, low-cost, and ready availability. In this work, we have derived physically activated carbon from date seed biomass as symmetric electrodes and PVA/KOH has been used as a gel polymer electrolyte for all-solid-state SCs. Initially, the date seed biomass was carbonized at 600 °C (C-600) and then it was used to obtain physically activated carbon through CO2 activation at 850 °C (C-850). The SEM and TEM images of C-850 displayed its porous, flaky, and multilayer type morphologies. The fabricated electrodes from C-850 with PVA/KOH electrolytes showed the best electrochemical performances in SCs (Lu et al. Energy Environ. Sci., 2014, 7, 2160) application. Cyclic voltammetry was performed from 5 to 100 mV s-1, illustrating an electric double layer behavior. The C-850 electrode delivered a specific capacitance of 138.12 F g-1 at 5 mV s-1, whereas it retained 16 F g-1 capacitance at 100 mV s-1. Our assembled all-solid-state SCs exhibit an energy density of 9.6 Wh kg-1 with a power density of 87.86 W kg-1. The internal and charge transfer resistances of the assembled SCs were 0.54 and 17.86 Ω, respectively. These innovative findings provide a universal and KOH-free activation process for the synthesis of physically activated carbon for all solid-state SCs applications.

Assessment of Pb and Ni and potential health risks associated with the consumption of vegetables grown on the roadside soils in District Swat, Khyber Pakhtunkhwa, Pakistan.

Vegetables cultivated near roads absorb toxic metals from polluted soil, which enter the human body through the food chain and cause serious health problems to humans. The present study investigated the concentration of lead (Pb) and nickel (Ni) in soils and vegetables grown along the roadside of District Swat, Pakistan, and the health risks associated with the consumption of the tested vegetables. In results, Pb concentration was higher in plants located at the distance between 0-10 m away from the roadside than the WHO permissible limit. In such plants, Pb concentration was higher than Ni. Rumex dentatus contained the highest concentration of Pb (75.63 mg kg-1 DW) among the tested vegetables while Ni concentration (27.57 mg kg-1 DW) was highest in Trachyspermum ammi as compared to other plants. Concentration and accumulation of both the metals decreased in soil and plants with increasing distance from the road. Similarly, target hazard quotient values noted for Pb (up to 3.37) were greater than unity, which shows that there is a potential risk associated with the consumption of tested vegetables near the road. Moreover, the values of target cancer risk (up to 0.8413) were greater than 0.0001, which shows that there is a risk of cancer with the consumption of tested vegetables. In conclusion, the consumption of tested vegetables was very dangerous as it may lead to higher risks of cancer. Strict regulatory control is recommended on the cultivation of these vegetables along the roadside to avoid any contamination due to roadside exhaust.

Preparation of mixed-mode stationary phase for separation of peptides and proteins in high performance liquid chromatography.

Porous silica particles were prepared by sol-gel method with some modification to get wide-pore particles. These particles were derivatized with N-phenylmaleimide-methylvinylisocyanate (PMI) and styrene by reversible addition fragmentation chain transfer (RAFT) polymerization to prepare N-phenylmaleimide embedded polystyrene (PMP) stationary phases. Narrow bore stainless steel column (100 × 1.8 mm i.d) was packed by slurry packing method. The chromatographic performance of PMP column was evaluated for the separation of synthetic peptides mixture composed of five peptides (Gly-Tyr, Gly-Leu-Tyr, Gly-Gly-Tyr-Arg, Tyr-Ile-Gly-Ser-Arg, Leucine enkephalin) and tryptic digest of human serum albumin (HAS) respectively. Number of theoretical plates as high as 280,000 plates/m were obtained for peptides mixture at optimum elution condition. Separation performance of the developed column was compared with commercial Ascentis Express RP-Amide column and it was observed that separation performance of PMP column was better than commercial column in terms of separation efficiency and resolution.

Efficient Removal of Pb(II) from Aqueous Medium Using Chemically Modified Silica Monolith.

The adsorptive removal of lead (II) from aqueous medium was carried out by chemically modified silica monolith particles. Porous silica monolith particles were prepared by the sol-gel method and their surface modification was carried out using trimethoxy silyl propyl urea (TSPU) to prepare inorganic-organic hybrid adsorbent. The resultant adsorbent was evaluated for the removal of lead (Pb) from aqueous medium. The effect of pH, adsorbent dose, metal ion concentration and adsorption time was determined. It was found that the optimum conditions for adsorption of lead (Pb) were pH 5, adsorbent dose of 0.4 g/L, Pb(II) ions concentration of 500 mg/L and adsorption time of 1 h. The adsorbent chemically modified SM was characterized by scanning electron microscopy (SEM), BET/BJH and thermo gravimetric analysis (TGA). The percent adsorption of Pb(II) onto chemically modified silica monolith particles was 98%. An isotherm study showed that the adsorption data of Pb(II) onto chemically modified SM was fully fitted with the Freundlich and Langmuir isotherm models. It was found from kinetic study that the adsorption of Pb(II) followed a pseudo second-order model. Moreover, thermodynamic study suggests that the adsorption of Pb(II) is spontaneous and exothermic. The adsorption capacity of chemically modified SM for Pb(II) ions was 792 mg/g which is quite high as compared to the traditional adsorbents. The adsorbent chemically modified SM was regenerated, used again three times for the adsorption of Pb(II) ions and it was found that the adsorption capacity of the regenerated adsorbent was only dropped by 7%. Due to high adsorption capacity chemically modified silica monolith particles could be used as an effective adsorbent for the removal of heavy metals from wastewater.

2-Nitro- and 4-fluorocinnamaldehyde based receptors as naked-eye chemosensors to potential molecular keypad lock.

New-generation chemosensors desire small organic molecules that are easy to synthesise and cost-effective. As a new interdisciplinary area of research, the integration of these chemosensors into keypad locks or other advanced communication protocols is becoming increasingly popular. Our lab has developed new chemosensor probes that contain 2-nitro- (1-3) and 4-fluoro-cinnamaldehyde (4-6) and applied them to the anion recognition and sensing process. Probes 1-6 are colorimetric sensors for naked-eye detection of AcO-/CN-/F-, while probes 4-6 could differentiate between F- and AcO-/CN- anions in acetonitrile. Using the density functional theory (DFT), it was found that probes 1-6 acted as effective chemosensors. By using Probe 5 as a chemosensor, we explored colorimetric recognition of multiple anions in more detail. Probe 5 was tested in combination with a combinatorial approach to demonstrate pattern-generation capability and its ability to distinguish among chemical inputs based on concentration. After pattern discrimination using principal component analysis (PCA), we examined anion selectivity using DFT computation. In our study, probe 5 demonstrates excellent performance as a chemosensor and shows promise as a future molecular-level keypad lock system.

Evaluation of the solubility of 11-keto-ß-boswellic acid and its histological effect on the diabetic mice liver using a novel technique.

BACKGROUND AND AIM: The literature is scant on the effect of 11-keto-ß-boswellic acid (KBA) on the liver of diabetes-induced mice. This study was designed to develop a rapid, sensitive, accurate, and inexpensive detection technique for evaluating the solubility of KBA obtained from the gum resin of Omani frankincense (Boswellia sacra) in the liver of streptozotocin-induced diabetic mice using Fourier transform infrared (FTIR) reflectance spectroscopy coupled with principal components analysis (PCA). It also aimed to investigate the effect of KBA on histological changes in the hepatocytes of diabetic mice. MATERIALS AND METHODS: Eighteen mice were assigned to the healthy control group, the diabetic control group, or the KBA-treated diabetic group. Liver tissue samples from all groups were scanned using an FTIR reflectance spectrophotometer in reflection mode. FTIR reflectance spectra were collected in the wavenumber range of 400-4000 cm-1 using an attenuated total reflectance apparatus. RESULTS: FTIR reflectance spectra were analyzed using PCA. The PCA score plot, which is an exploratory multivariate data set, revealed complete segregation among the three groups' liver samples based on changes in the variation of wavenumber position in the FTIR reflectance spectra, which indicated a clear effect of KBA solubility on treatments. Histological analysis showed an improvement in the liver tissues, with normal structures of hepatocytes exhibiting mild vacuolation in their cytoplasm. CONCLUSION: KBA improved the morphology of liver tissues in the diabetic mice and led to complete recovery of the damage observed in the diabetic control group. FTIR reflectance spectroscopy coupled with PCA could be deployed as a rapid, low-cost, and non-destructive detection method for evaluating treatment effects in diseased liver tissue based on the solubility of KBA.

Determination of residues of pesticides, anabolic steroids, antibiotics, and antibacterial compounds in meat products in Oman by liquid chromatography/mass spectrometry and enzyme-linked immunosorbent assay.

BACKGROUND AND AIM: Meat is a rich source of many nutrients and plays a vital role in human life however, meat safety is one of the top priorities of great concern for consumers today. More than 90% of human exposure to harmful materials is due to consumption of contaminated meat products. This study was designed to compare four valid analytical methods for the determination of organochlorine pesticides 2,4 D (2,4-dichlorophenoxyacetic acid), dichlorodiphenyldichloroethylene/dichlorodiphenyltrichloroethane, alachlor, organophosphate, anabolic steroids (progesterone, testosterone, and estrogen), antibiotics (tetracycline, sulfonamides, gentamycin, and cephalexin), antibacterial compounds (Macrolide, ß-Lactam, Chloramphenicol, Sulphur drugs, and Gentamicin) residues in 135 beef, buffalo, and sheep meat samples (fresh, frozen meats, minced, and sausage samples) of local, regional, and international brands available in Omani markets. MATERIALS AND METHODS: Triplicate meat samples from each brand within each species were extracted with acetonitrile and purified with acetonitrile-saturated n-hexane to remove all impurities. To dry the sample after heating, the residue was passed across a Sep-Pak C18 cartridge for sample cleaning before gas chromatography (GC) (Brand GCMS-QP2010 Plus) coupled with different detectors, including a mass spectrometer or GC-electron capture detector (GC-ECD). Liquid chromatography/mass spectrometry (LC-MS) was also employed for the quantification of the residues in meat products. Enzyme-linked immunosorbent assay (ELISA) kits were employed to assess veterinary drug residues, anabolic steroids, and pesticides. The CHARM II instrument was employed to detect chloramphenicol, gentamicin, sulfa-drug, ß-lactam, and macrolide residues in meat and meat product samples. RESULTS: A thin-layer chromatographic (TLC) method should be considered as another method of choice to determine concentrations of veterinary drugs and anabolic steroids. The TLC results were validated by LC-MS. The three described methods permit the multi-residue analysis of anabolic steroid residue levels of 0.06-1.89 ppb in meat product samples. There were three violative residues of anabolic steroids in red meat products that were above the maximum residue limits (MRLs). Although, the levels of organochlorine pesticides and antibiotic concentrations in meat products were below the MRLs, the long-term consumption is considered a health hazard and will affect the wellbeing of consumers. CONCLUSION: The four techniques (GC, high-performance liquid chromatography, ELISA and CHARM II) provided results that were reliable and precise for the detection of chessssmical residues in meat and meat products.

Spectroscopic and Molecular Methods to Differentiate Gender in Immature Date Palm (Phoenix dactylifera L.).

Phoenix dactylifera (date palm) is a well-known nutritious and economically important fruit tree found in arid regions of the Middle East and North Africa. Being diploid, it has extremely high divergence in gender, where sex differentiation in immature date palms (Phoenix dactylifera L.) has remained an enigma in recent years. Herein, new robust infrared (near-infrared reflectance spectroscopy (NIRS) and Fourier transform infrared attenuated total reflectance (FTIR/ATR)) and nuclear magnetic resonance (NMR) spectroscopy methods coupled with extensive chemometric analysis were used to identify the sex differentiation in immature date palm leaves. NIRS/FTIR reflectance and 1H-NMR profiling suggested that the signals of monosaccharides (glucose and fructose) and/or disaccharides (maltose and sucrose) play key roles in sex differentiation. The three kinds of spectroscopic data were clearly differentiated among known and unknown male and female leaves via principal component and partial least square discriminant analyses. Furthermore, sex-specific genes and molecular markers obtained from the lower halves of LG12 chromosomes showed enhanced transcript accumulation of mPdIRDP52, mPdIRDP50, and PDK101 in females compared with in males. The phylogeny showed that the mPdIRD033, mPdIRD031, and mPdCIR032 markers formed distinctive clades with more than 70% similarity in gender differentiation. The three robust analyses provide an alternative tool to differentiate sex in date palm trees, which offers a solution to the long-standing challenge of dioecism and could enhance in situ tree propagation programs.

Robust Fourier transformed infrared spectroscopy coupled with multivariate methods for detection and quantification of urea adulteration in fresh milk samples.

Urea is added as an adulterant to give milk whiteness and increase its consistency for improving the solid not fat percentage, but the excessive amount of urea in milk causes overburden and kidney damages. Here, an innovative sensitive methodology based on near-infrared spectroscopy coupled with multivariate analysis has been proposed for the robust detection and quantification of urea adulteration in fresh milk samples. In this study, 162 fresh milk samples were used, those consisting 20 nonadulterated samples (without urea) and 142 with urea adulterant. Eight different percentage levels of urea adulterant, that is, 0.10%, 0.30%, 0.50%, 0.70%, 0.90%, 1.10%, 1.30%, and 1.70%, were prepared, each of them prepared in triplicates. A Frontier NIR spectrophotometer (BSEN60825-1:2007) by Perkin Elmer was used for scanning the absorption of each sample in the wavenumber range of 10,000-4,000 cm-1, using 0.2 mm path length CaF2 sealed cell at resolution of 2 cm-1. Principal components analysis (PCA), partial least-squares discriminant analysis (PLS-DA), and partial least-squares regressions (PLSR) methods were applied for the multivariate analysis of the NIR spectral data collected. PCA was used to reduce the dimensionality of the spectral data and to explore the similarities and differences among the fresh milk samples and the adulterated ones. PLS-DA also showed the discrimination between the nonadulterated and adulterated milk samples. The R-square and root mean square error (RMSE) values obtained for the PLS-DA model were 0.9680 and 0.08%, respectively. Furthermore, PLSR model was also built using the training set of NIR spectral data to make a regression model. For this PLSR model, leave-one-out cross-validation procedure was used as an internal cross-validation criteria and the R-square and the root mean square error (RMSE) values for the PLSR model were found as 0.9800 and 0.56%, respectively. The PLSR model was then externally validated using a test set. The root means square error of prediction (RMSEP) obtained was 0.48%. The present proposed study was intended to contribute toward the development of a robust, sensitive, and reproducible method to detect and determine the urea adulterant concentration in fresh milk samples.

FT-NIRS Coupled with PLS Regression as a Complement to HPLC Routine Analysis of Caffeine in Tea Samples.

Daily consumption of caffeine in coffee, tea, chocolate, cocoa, and soft drinks has gained wide and plentiful public and scientific attention over the past few decades. The concentration of caffeine in vivo is a crucial indicator of some disorders-for example, kidney malfunction, heart disease, increase of blood pressure and alertness-and can cause some severe diseases including type 2 diabetes mellitus (DM), stroke risk, liver disease, and some cancers. In the present study, near-infrared spectroscopy (NIRS) coupled with partial least-squares regression (PLSR) was proposed as an alternative method for the quantification of caffeine in 25 commercially available tea samples consumed in Oman. This method is a fast, complementary technique to wet chemistry procedures as well as to high-performance liquid chromatography (HPLC) methods for the quantitative analysis of caffeine in tea samples because it is reagent-less and needs little or no pre-treatment of samples. In the current study, the partial least-squares (PLS) algorithm was built by using the near-infrared NIR spectra of caffeine standards prepared in tea samples scanned by a Frontier NIR spectrophotometer (L1280034) by PerkinElmer. Spectra were collected in the absorption mode in the wavenumber range of 10,000-4000 cm-1, using a 0.2 mm path length and CaF2 sealed cells with a resolution of 2 cm-1. The NIR results for the contents of caffeine in tea samples were also compared with results obtained by HPLC analysis. Both techniques provided good results for predicting the caffeine contents in commercially available tea samples. The results of the proposed study show that the suggested FT-NIRS coupled with PLS regression algorithun has a high potential to be routinely used for the quick and reproducible analysis of caffeine contents in tea samples. For the NIR method, the limit of quantification (LOQ) was estimated as 10 times the error of calibration (root mean square error of calibration (RMSECV)) of the model; thus, RMSEC was calculated as 0.03 ppm and the LOQ as 0.3 ppm.

An Attempt Towards Lab And Clinical Combine Appraised, Including Future Concerns Regarding Dengue Infection.

BACKGROUND: Dengue infection is a deadly global pandemic due to its fatal nature, being emerged from mild stage to turn into more severe stages and consequently causing casualties. it upsurges various phases, namely subclinical infection, undifferentiated febrile fever, Dengue fever (DF) and devastating states which often ends to life, they are Dengue haemorrhagic fever (DHF) and Dengue shock syndrome (DSS). Dengue infection is a mosquito born disease which has engulfed many regions in general and tropical zone in particular, causing many casualties and has posed a threat to humanity, demanding strategies to resolve the global issue. It is reported that 50-200 million people fall prey to it globally by dint of its causative agents and imperative to mention that over proportional are the minor among the victims. Because of awful joint pain dengue fever is also named break bone fever. The common indicator in infected individuals is thrombocytopenia, coagulopathy and vasculopathy. Apart from supportive therapy, no aphoristic therapy has been introduced so far, however care may prove rescuer. Timely prognosis thwarts to enter it in deteriorating phase. METHODS: In the list of laboratory diagnosis virus serology and detection of Ribonucleic acid are primed. In general, there's no specific decisive diagnostic biomarker present through which accurate and prompt prognosis can possible during the entire patient presentation time, particularly in case of secondary dengue infection. Although, through the advancement and commercialization of point-care combined tests, capable of tracking disease markers present during various phases of infection (viral non-structural protein 1 and immunoglobulin M), such evaluation massively improved the treatment through lab-based. CONCLUSIONS: Despite such improvements, major hurdles persist in the clinical management of patients with dengue infection, particularly lack of dependable biomarkers that have an efficacious prognostic gauge to predict steady progress to severe disease. In the described review both clinical and laboratory diagnosis of dengue infection has been highlighted, including concern regarding future accessibility.

Fast detection and quantification of pork meat in other meats by reflectance FT-NIR spectroscopy and multivariate analysis.

This study aimed to develop a fast analytical method, combining near infrared reflectance spectroscopy and multivariate analysis, for detection and quantification of pork meat in other meat samples. A total of 5952 mixture samples from 39 types of meat were prepared in triplicate, with the inclusion of pork at 0%, 1%, 5%, 10%, 30%, 50%, 70%, 90% and 100%. Each sample was scanned using an FT-NIR spectrophotometer in the reflection mode. Spectra were collected in the wavenumber range from 10,000 to 4000 cm-1, at a resolution of 2 cm-1 and a total path length of 0.5 mm. Principal Component Analysis (PCA) revealed the similarities and differences among the various types of meat samples and Partial Least-Squares Discriminant Analysis (PLS-DA) showed a good discrimination between pure and pork-spiked meat samples. A Partial Least-Squares Regression (PLSR) model was built to predict the pork meat contents in other meats, which provided the R2 value of 0.9774 and RMSECV value of 1.08%. Additionally, an external validation was carried out using a test set, providing a rather good prediction error, with an RMSEP value of 1.84%.

Endogenous phytohormones of frankincense producing Boswellia sacra tree populations.

Boswellia sacra, an endemic tree to Oman, is exposed to man-made incisions for commercial level frankincense production, whereas unsustainable harvesting may lead to population decline. In this case, assessment of endogenous phytohormones (gibberellic acid (GA), indole-acetic acid (IAA), salicylic acid (SA) and kinetin) can help to understand population health and growth dynamics. Hence, it was aimed to devise a robust method using Near-Infrared spectroscopy (NIRS) coupled with multivariate methods for phytohormone analysis of thirteen different populations of B. sacra. NIRS data was recorded in absorption mode (10000-4000 cm-1) to build partial least squares regression model (calibration set 70%). Model was externally cross validated (30%) as a test set to check their prediction ability before the application to quantify the unknown amount of phytohormones in thirteen different populations of B. sacra. The results showed that phytohormonal contents varied significantly, showing a trend of SA>GA/IAA>kinetin across different populations. SA and GA contents were significantly higher in Pop13 (Hasik), followed by Pop2 (Dowkah)-an extreme end of B. sacra tree cover in Dhofar region. A similar trend in the concentration of phytohormones was found when the samples from 13 populations were subjected to advance liquid chromatography mass spectrophotometer and gas chromatograph with selected ion monitor analysis. The current analysis provides alternative tool to assess plant health, which could be important to in situ propagation of tree population as well as monitoring tree population growth dynamics.

Synthesis of NiO:V2O5 nanocomposite and its photocatalytic efficiency for methyl orange degradation.

Vanadium oxide has been largely exploited as a catalyst in many industrial applications. In this article, we show the synthesis of vanadium oxide (V2O5): Nickel Oxide (NiO) composite using sol-gel method at optimum conditions. The composite nanomaterials were used to remove methyl orange from waste water via harnessing the photocatalytic activity of it which showed an excellent efficiency of removal at 88%, and 93% after the exposure to the light, and light with heating respectively. This will pave the way into further implementation of these nanomaterials in the removal of some other dyes and contaminants from wastewater.

In vitro oxidative stress regulatory potential of Citrullus colocynthis and Tephrosia apollinea.

The present study investigates the potential role of medicinal plants Citrullus colocynthis and Tephrosia apollinea in ameliorating the oxidative stress developed during the generation of reactive oxygen species. Organic extracts of different organs (leaf, stem and root) of these medicinal plants obtained in n-hexane, chloroform, n-butanol and water were assayed for radical scavenging, total antioxidant capacity, anti-lipid peroxidation and reduced glutathione. The total phenolic content (TPC) of both selected medicinal plants was also evaluated. The results indicated that extracts of T. apollinea leaf, stem and root have higher TPC compared to those of C. colocynthis. Similarly, the results of the present study revealed higher bioactivity of C. colocynthis than that of T. apollinea in various antioxidant assays. Various plant parts of each plant were also compared.

Effect of phosphate nutrition on growth, physiology and phosphate transporter expression of cucumber seedlings.

Although abundantly present in soils, inorganic phosphate (Pi) acquisition by plants is highly dependent on the transmembrane phosphate transporter (PT) gene family. Cucumber (Cucumis sativus) requires a large amount of phosphorus (P). The purpose of this study was to isolate the CsPT2-1 from cucumber roots, and to determine the influence of Pi nutrition on cucumber growth, metabolism and transcript levels of CsPT2-1 in tissues. Full length CsPT2-1 was cloned and phylogenetically identified. In two greenhouse experiments, P-deficient seedlings provided with low or high P concentrations were sampled at 10 and 21 days post treatment, respectively. Addition of P dramatically reduced growth of roots but not shoots. Supplying plants with high P resulted in increased total protein in leaves. Acid phosphatase activity increased significantly in leaves at any rate higher than 4 mM P. Increasing P concentration had a notable decrease in glucose concentrations in leaves of plants supplied with >0.5 mM P. In roots, glucose and starch concentrations increased with increasing P supply. Steady-state transcript levels of CsPT2-1 were high in P-deprived roots, but declined when plants were provided >10 mM P. To our knowledge, this is the first report focusing on a PT and its expression levels in cucumber.

Applications of FT-NIRS combined with PLS multivariate methods for the detection & quantification of saccharin adulteration in commercial fruit juices.

Detection of adulteration in carbohydrate-rich foods like fruit juices is particularly difficult because of the variety of the commercial sweeteners available that match the concentration profiles of the major carbohydrates in the foods. In present study, a new sensitive and robust assay using Fourier Transform Near-Infrared Spectroscopy (FT-NIRS) combined with partial least square (PLS) multivariate methods has been developed for detection and quantification of saccharin adulteration in different commercial fruit juice samples. For this investigation, six different commercially available fruit juice samples were intentionally adulterated with saccharin at the following percentage levels: 0%, 0.10%, 0.30%, 0.50%, 0.70%, 0.90%, 1.10%, 1.30%, 1.50%, 1.70% and 2.00% (weight/volume). Altogether, 198 samples were used including 18 pure juice samples (unadulterated) and 180 juice samples adulterated with saccharin. PLS multivariate methods including partial least-squares discriminant analysis (PLS-DA) and partial least-squares regressions (PLSR) were applied to the obtained spectral data to build models. The PLS-DA model was employed to differentiate between pure fruit juice samples and those adulterated with saccharin. The R2 value obtained for the PLS-DA model was 97.90% with an RMSE error of 0.67%. Similarly, a PLS regression model was also developed to quantify the amount of saccharin adulterant in juice samples. The R2 value obtained for the PLSR model was 97.04% with RMSECV error of 0.88%. The employed model was then cross-validated by using a test set which included 30% of the total adulterated juice samples. The excellent performance of the model was proved by the low root mean squared error of prediction value of 0.92% and the high correlation factor of 0.97. This newly developed method is robust, nondestructive, highly sensitive and economical.