Analysis of selected pesticides and alkylphenols in human cord blood by gas chromatograph-mass spectrometer

A total of seven pesticides and eight alkylphenols were monitored using this method for the determination of their trace levels in human cord blood. The pesticides are lindane, diazinon, α-endosulfan, β-endosulfan, endosulfan sulfate, chlorpyrifos and endrin; while the alkylphenols are 4-n-butylphenol, 4-n-pentylphenol, 4-n-hexylphenol, 4-t-octylphenol, 4-n-heptylphenol, nonylphenol, 4-n-octylphenol and bisphenol A. The pesticides and alkylphenols in the cord blood samples were extracted with solid phase extraction IST C18 cartridges and analyzed by selected ion monitoring mode using quadrapole detector in Shimadzu QP-5000 gas chromatograph-mass spectrometer. Trace levels of pesticide and alkylphenols in the range of non-detectable to 15.17 ng ml⁻¹, were detected in the human cord blood samples. This technique of monitoring the levels of endocrine-disruptors in blood samples is consistent, reliable and cost effective while reducing wastage of time and solvents.     

Synthesis of steroidal thiadiazoles from steroidal ketones

Syntheses of steroidal heterocycles containing a five-membered N,S- heterocycle attached at the 6,7 positions of the B ring are reported. 5Alpha-cholestane-6-one (1), its 3beta-acetoxy- (2) and 3beta-chloro- (3) analogues reacted with semicarbazide and aqueous sodium acetate in refluxing ethanol to yield 5alpha-cholestan-6-one-semicarbazone 1a and its 3-beta-acetoxy and 3beta-chloro derivatives 2a and 3a, respectively. The reactions of 1a, 2a and 3a with thionyl chloride in dichloromethane at low temperature afforded the cyclized thiadiazole 4 and its 3beta-acetoxy- and 3beta-chloro analogues 5 and 6 in good yields.     

Nigella sativa L. and COVID-19: A Glance at The Anti-COVID-19 Chemical Constituents,Clinical Trials,Inventions, and Patent Literature

COVID-19 has had an impact on human quality of life and economics. Scientists have been identifying remedies for its prevention and treatment from all possible sources, including plants. Nigella sativa L. (NS) is an important medicinal plant of Islamic value. This review highlights the anti-COVID-19 potential, clinical trials, inventions, and patent literature related to NS and its major chemical constituents, like thymoquinone. The literature was collected from different databases, including Pubmed, Espacenet, and Patentscope. The literature supports the efficacy of NS, NS oil (NSO), and its chemical constituents against COVID-19. The clinical data imply that NS and NSO can prevent and treat COVID-19 patients with a faster recovery rate. Several inventions comprising NS and NSO have been claimed in patent applications to prevent/treat COVID-19. The patent literature cites NS as an immunomodulator, antioxidant, anti-inflammatory, a source of anti-SARS-CoV-2 compounds, and a plant having protective effects on the lungs. The available facts indicate that NS, NSO, and its various compositions have all the attributes to be used as a promising remedy to prevent, manage, and treat COVID-19 among high-risk people as well as for the therapy of COVID-19 patients of all age groups as a monotherapy or a combination therapy. Many compositions of NS in combination with countless medicinal herbs and medicines are still unexplored. Accordingly, the authors foresee a bright scope in developing NS-based anti-COVID-19 composition for clinical use in the future.     

Index for vehicle acoustical comfort inside a passenger car

Sound quality is among the main factors that influence customers’ preference for choosing good automobile products. It all started more than 10 years ago and grows up so fast due to high competition in the automotive industries. A-weighted noise levels and sound power are usually utilised to measure the noise but they are not adequate to characterise the impact sound inside a car. The most popular approach to determine sound quality of a product is to define an annoyance or specific index, which involves both subjective and objective evaluations. Subjective and objective tests should be studied concurrently in order to determine the sound quality inside a passenger car. This approach is used in this paper to evaluate vehicle comfort index according to most frequently used sound quality metrics, namely; Zwicker loudness, sharpness, roughness and fluctuation strength. As a result researchers of different fields of automotive acoustics investigations can use this index according to the type of road (international road roughness) without any need to perform time-consuming jury tests. The metrics are correlated with jury test results that show which of them and how much has affected the acoustical comfort of the vehicle. The relation between road roughness and vehicle acoustical comfort index is another point of interest in this research.     

Synthesis,physicochemical characterization and biological activity of nano complexes of iron(III) of 3(2'‐hydroxyphenyl)‐5‐(4′‐substituted phenyl) pyrazolines and aspartic acid

Mixed ligand complexes of Iron(III) with aspartic acid and 3(2′‐hydroxy phenyl)‐5‐(4′‐substituted phenyl) pyrazolines of type [Fe(C₄O₄NH₆)₂(C₁₅H₁₂N₂OX)] and [Fe(C₄O₄NH₆)(C₁₅H₁₂N₂OX)₂], where (C₄O₄NH₆) = aspartate, (C₁₅H₁₂N₂OX) = deprotonated 3(2′‐hydroxyphenyl)‐5‐(4′‐substituted phenyl) pyrazolines (X = H, CH₃, OCH₃, Cl), have been synthesized. These newly synthesized derivatives have been physicochemically characterized by elemental analysis (C, H, N, Cl and Fe), magnetic moment data, thermogravimetric analysis, molar conductance, cyclic voltammetry, spectral analysis (UV–visible, IR, far IR and fast atom bombardment mass spectrometry). Scanning electron microscopy, transmission electron microscopy and X‐ray powder diffraction studies have been carried out for powdered samples, which show nanometric particles of these derivatives. Antibacterial and antifungal potential of free pyrazoline and some iron(III) complexes have been evaluated. Copyright © 2012 John Wiley & Sons, Ltd.     

Fatty amides synthesized from vegetable oil as extractant of molybdenum(VI)

In this study, fatty amides (FAs) synthesized from palm olein were used to extract and separate Mo(VI) from acidic media. Effects of various parameters upon the separation of Mo(VI) from Co(II), Ni(II), Al(III) and Mn(II), including extractant concentration, metal ion concentration, contact time, diluent, and acidity, were investigated. It was found that Mo(VI) was successfully separated from the above commonly associated metal ions by stripping from the loaded organic phase. Different acidic and alkaline solutions were used. Ammonium hydroxide solution was an optimal. Extraction of Mo(VI) into the organic phase involved the formation of 1:3 complexes. This work presents the development of a low-cost and environmentally friendly extractant to recycle and recover molybdenum.     

Artificial neural network‐based modeling of snow properties using field data and hyperspectral imagery

This study attempts to model snow wetness and snow density of Himalayan snow cover using a combination of Hyperspectral image processing and Artificial Neural Network (ANN). Initially, a total of 300 spectral signature measurements, synchronized with snow wetness and snow density, were collected in the field. The spectral reflectance of snow was then modeled as a function of snow properties using ANN. Four snow wetness and three snow density models were developed. A strong correlation was observed in near‐infrared and shortwave‐infrared region. The correlation analysis of ANN modeled snow density and snow wetness showed a strong linear relationship with field‐based data values ranging from 0.87–0.90 and 0.88–0.91, respectively. Our results indicate that an Artificial Intelligence (AI) approach, using a combination of Hyperspectral image processing and ANN, can be efficiently used to predict snow properties (wetness and density) in the Himalayan region. Recommendations for resource managers

• Snow properties, such as snow wetness and snow density are mainly investigated through field‐based survey but rugged terrains, difficult weather conditions, and logistics management issues establish remote sensing as an efficient alternative to monitor snow properties, especially in the mountain environment.
• Although Hyperspectral remote sensing is a powerful tool to conduct the quantitative analysis of the physical properties of snow, only a few studies have used hyperspectral data for the estimation of snow density and wetness in the Himalayan region. This could be because of the lack of synchronized snow properties data with field‐based spectral acquisitions.
• In combination with Hyperspectral image processing, Artificial Neural Network (ANN) can be a useful tool for effective snow modeling because of its ability to capture and represent complex input‐output relationships.
• Further research into understanding the applicability of neural networks to determine snow properties is required to obtain results from large snow cover areas of the Himalayan region.

     

SYNTHESIS AND CHARACTERIzATION OF TRIPHENYLANTIMONY (V) (O-ALKYL,O-CYCLOALKYL AND O-ARYLTRITHIOPHOSPHATES)

Triphenylantimony (V) (O-alkyl,O-cycloalkyl and O-aryltrithiophosphates) of the type Ph ₃ Sb[S ₂ (S)P(OR)] (R = Me, Et, Pr ⁿ , Pr ⁱ , Bu ⁿ , Bu ^s , Bu ⁱ , Am ⁱ , Ph and C.h. = cyclohexyl) have been synthesized for the first time by the reaction of triphenylantimony (V) dibromide with potassium trithiophosphates in 1:1 molar ratio in methanol. These new compounds have been characterized by elemental analysis, molecular weight determinations, and spectroscopic (IR,¹³C and ³¹P NMR) studies. On the basis of these data trigonal bipyramidal geometry has been proposed for these compounds.