Relationship between Vitamin D Status, Dyslipaedemia and Antioxidant Status in Children with Idiopathic Nephrotic Syndrome in South West, Nigeria

Dysregulated lipid metabolism and oxidative stress are strong factors that are implicated in the development of proteinuria and glomerular injury in Nephrotic Syndrome (NS). Vitamin D seems to be a promising tool in influencing lipid metabolism and antioxidant status in NS. Aim: This study aims at investigating the relationship between Vitamin D, dyslipaedemia and oxidative stress in NS. Study Design: This is a case-control study. Place and Duration of Study: Children’s Outpatient Clinic (CHOP) of University College Hospital (UCH) Ibadan, Nigeria between year 2019-2021. Methods: This study involves fifty children aged 5 to 12 years, freshly diagnosed with Idiopathic NS and fifty apparently healthy children as control. Blood samples were taken from them and analytes quantified by standard laboratory methods. Students’ t test and Pearson correlation were used to compare variables between the two groups respectively. Results: Results showed significant decrease (P <.001) in Vit. D levels, GPX, SOD and CAT in NS. A significant decrease (P<.001) occurred in HDL, a significant increase (P <.001) in TG, TC and LDL levels in children with NS when compared with the control. There was a strong significant positive relationship between Catalase and Vit. D, SOD and Vit. D (r= 0.896, 0.869 respectively, P<.001) in NS. While a weak non significant positive relationship occurred between HDL and Vit. D, GPX and Vit D (r=0.0585, 0.0236 respectively, P >.001). A weak negative relationship occurred between TG and Vit. D, TC and Vit. D, LDL and Vit. D (r=-0.0432,-0.219, -0.231 respectively, P>.001), in NS. Thus, vitamin D insufficiency influences serum lipid profiles and antioxidants in paediatric Idiopathic NS.

Research on Application of Artificial Neural Network in Fault Diagnosis of Chemical Process

Chemical processes are usually toxic, corrosive, flammable and explosive. If the process fails, the danger is extremely high. Traditional model-based fault diagnosis methods need to establish an accurate mathematical model of the system, while modern engineering processes are usually large in scale and complex, and it is difficult to establish an accurate mathematical model. Artificial neural network has been widely used in chemical process because of its advantages of parallel processing, self-adaptation, robustness, learnability and fault tolerance. Artificial neural networks based on "deep learning" have been successfully applied to fault diagnosis in various chemical processes. This article summarizes the principle and development process of artificial neural networks, and analyzes the research progress and application status of deep neural networks in chemical process fault diagnosis based on cases. Finally, it is pointed out that deep neural network in the field of chemical process fault diagnosis is of great significance in solving the impact of less fault data and system state changes on the fault detection rate, and promoting the industrial application of fault diagnosis models.

Synthesis and Characterization of Barium-Iron Oxide Based Neodymium, Gadolinium and Praseodymium Doped Ceramic Materials

Neodymium, gadolinium, and praseodymium doped barium-iron oxide ceramic materials were synthesized by polymeric precursor method. No carbon contents or the moisture was observed in infrared spectra of the ceramics. Neodymium and gadolinium doped ceramics were crystallized in cubic lattice form, while praseodymium doped ceramic was formed in hexagonal lattice. Same results were observed from SEM images, Neodymium and gadolinium doped ceramics had similar morphological structures, but praseodymium doped ceramics had slightly different morphology. Neodymium and gadolinium doped ceramics consisted of grain-like structure, while praseodymium doped ceramic material consisted of both grain-like and pillar-like crystal structures.

Chemical and Medicinal Properties of Rauwolfia vomitoria (AFZEL) Harvested from the South Eastern Nigeria

Aim: This work was carried out to evaluate the chemical constituents of the leaf of Rauwolfia vomitoria and to determine the activities of the extract on some selected human pathogens Study Design: The study was designed to characterize the compounds in the extract and to determine their medicinal applications Place and Duration of Study: The work was done at the Department of Chemistry Federal University of Technology Owerri Methodology: Standard assay technique was used to evaluate the phytochemical content of the sample. GC-MS analysis was carried out on the chloroform extract of the sample. The anti microbial activities were determines using the well agar diffusion method Results: The analysis of the components of the leaf extract of Rauwolfia vomitoria Afzel revealed the presence of 34 compounds with their molecular masses molecular weights and structures, all elucidated. The initial phytochemical screening revealed the presence of alkaloids 1.92%, saponins 1.12% , flavonoids 1.15% and cardiac glycosides, the extract showed marked inhibition of the growth of certain human pathogens with inhibition diameters recorded against Klebsiella pnuemonia, 22 mm, Pseudomonas aeruginosa 18 mm,Aspergillis niger 24 mm and Mucor specie 9 mm but was resistant to Streptococcus specie.The extract contain anti cancer,anti-tumuor antioxidant, anti-inflammatory ,cardioprotectives compounds which inludes phytol, Vitamin E, Campestrol, sistosterol, squalene, lupeol and vaccenic acid. Conclusion: Owing to the identified properties of the sample ,Rauwofia vomitoria leaf is excellent ingredient for the treatment of diaeases related to Klebsiella pnuemonia, Pseudomonas aeruginosa Aspergillis niger and Mucor specie and also for the treatment cancer, tumuor, inflammation, arthritis,beingn prostate hyperplasia, fibromyalgia, allergies, coronary heart.

Evaluation of Major and Trace Elements Present in Extracted Humic Acid from Bog Peat

The human consumption of humic acid is increasingly relevant therefore the knowledge of exact composition is essential. To make a step in that direction we present gap filling results obtained from three different element analytical investigations of humic acid extracted from fen peat examined in the Carpathian Basin. Prompt-gamma activation (PGAA), neutron activation analytical method (NAA) and X-ray fluorescence (XRF) analysis was carried out. After presenting and explaining the essence of used analytical methods we show some collected spectra and a table where all the concentration of the iden- tified elements are presented with the corresponding measurement errors. All together 42 elements were identified. PACS.78.70.En, 78.70. Nx,78. 90.+t X-ray emission spectra and fluorescence, Neutroninelastic scattering, Other topics in optical properties, condensed matter aspect.

Research Progress in the Application of Artificial Neural Networks in Catalyst Optimization

The catalyst can speed up the chemical reaction and increase the selectivity of the target product, playing an important role in the chemical industry. By improving the performance of the catalyst, the economic benefits can be greatly improved. Artificial Neural Network (ANN), as one of the most popular machine learning algorithms, has parallel processing and self-learning capabilities as well as good fault tolerance, and has been widely used in various fields. By optimizing the catalyst through ANN, time and resource consumption can be greatly reduced, and greater economic benefits can be obtained. This article reviews how CNN technology can help people solve highly complex problems and accelerate progress in the catalytic world.

An Overview of Chemistry Teaching Transformation during COVID-19 Pandemic: An Experience from University of Botswana

COVID-19-related disruption in teaching in the University of Botswana led the school to prepare new strategies for running classes and to design innovative way of instruction. The most notable change was to replace face-to-face lectures with online teaching at least partially (blended teaching and learning). This posed many challenges, especially in the teaching of science and technology subjects. In a laboratory-based discipline such as chemistry the problems encountered were especially daunting. Moreover, writing mathematical equations, chemical reactions and reaction mechanisms posed their own difficulties. The present communication provides a brief overview of how chemistry education at the University, the premier national university of Botswana, has been transformed during the last three semesters. It is based on experience of the author and as judged by the feed-back received from colleagues and the students. Admittedly, the experience is limited and much discussion is still in progress to meet the unresolved challenges. Theory classes at undergraduate levels are now mostly taught online using packages such as Moodle and MS Teams. The tutorial and laboratory sessions have faced the greatest disruptions and the instructors continue to explore ways to conduct these virtually. Online examinations were found to be limited in their effectiveness, especially in the assessment of drawing chemical structure and reaction mechanisms as well as the students’ ability in scientific writing.

Development and Validation of HPTLC-Densitometric Method Compared to Titrimetric Method for Determination of L-ascorbic Acid in Citrus Fruits

Aims: The aim of this study is to develop and validate an efficient method for the specific determination of L-ascorbic acid in citrus fruits and to compare it with a usual method, method using 2,6-dichlorophenolindophenol Methodology: The research for a specific method for determination of L-ascorbic acid has led to development and validation of High Performance Thin Layer Chromatography – Densitometric (HPTLC-D) method. The validation criteria evaluated are response function, determination reading wavelength, limit of detection, precision of the technique, limit of quantification and recovery rate. The validated method was applied to citrus juice samples for quantification of L-ascorbic acid. Then a 2,6-dichlorophenolindophenol titrimetric assay of L-ascorbic acid in the same sample was performed for comparison of method results. Results: HPTLC-D method showed improved sensitivity on 360 ​​nm scanner and a good linearity relationship between standard concentrations and absorbance responses. The regression coefficient obtained is R2 = 0.99. The limit of detection (LOD) and the limit of quantification (LOQ) are respectively 3 ng and 9.5 ng per deposit. The method also exhibited good repeatability and precision, with intra-day (n = 3) and inter-day (n = 4) coefficients of variation (CV) of less than 6%. Application of the HPTLC-Dmethod to citrus juices yielded a recovery rate ranging from 97% to 99%. Conclusion: Comparison of results of the two methods shows that the contents obtained by titrimetry are greater than those obtained by HPTLC-D by 42.25%. This is explained by the presence of other redox compounds which are dosed at the same time as L-ascorbic acid. HPTLC-D makes it possible to specifically dose L-ascorbic acid.

Polyvinyl Butyral Synthesis Process Based on Deep Eutectic Solvent as a Catalyst

Polyvinyl butyral (PVB) was prepared by the condensation reaction of polyvinyl alcohol (PVA) with n-butyraldehyde using a catalyst which is a kind of deep eutectic solvent (DES) made of dodecyltrimethylammonium chloride and p-toluenesulfonic acid. The raw materials and products were characterized by Fourier transform infrared spectroscopy (FT-IR). The effects of the following reaction conditions on the degree of PVB acetal, yield and agglomeration of the products were investigated: the mass ratio of n-butyraldehyde to PVA (mBA/mPVA) of 0.48-0.96, the mass ratio of catalyst to PVA (mcat/mPVA) of 0.16-0.64, the low temperature reaction temperature (5-20℃), and the low temperature reaction time (1-3h). The results showed that at mBA/mPVA =0.8, mcat/mPVA =0.32, low temperature reaction temperature of 15°C and low temperature reaction time of 2 hours, the obtained PVB was a homogeneous powder with the highest acetal degree of 73.85%.

Characteristics of Effluent from Formic Acid and Sodium Hydroxide Pulping of Kenaf Stem

The pulp and paper industry is considered as one of the major potential sources of pollution in the environment and a consumer of wood. Environmental effects have been attributed to chemicals introduced during the manufacturing process. This paper investigated the influence of cooking chemicals, concentration and time on the properties of effluent generated during pulping of agricultural residue. A stem of kenaf which is an agricultural residue was pulped with 20%, 60% and 90% concentrations of formic acid and sodium hydroxide at 1 hour, 2 hours and 3 hours intervals to determine the characteristics of their effluents. The lowest Chemical Oxygen Demand (COD) obtained from formic acid effluent for the 3 hours cooking at 20%, 60% and 90% concentrations was 324mg/l at 60% concentration after cooking for 2 hours while sodium hydroxide effluent has 3050mg/l at 20% concentration after 1hour cooking as its lowest. Formic acid effluent showed lowest Biological Oxygen Demand (BOD) of 10.63mg/l at 60% concentration after cooking for 2 hours while sodium hydroxide has 13.75mg/l at 90% after 1 hour cooking. The value of Total Solid (TS) from formic acid effluent was lowest (16890mg/l) at 60% concentration after cooking for 2 hours while sodium hydroxide lowest value (15524mg/l) was recorded at 20% after 3 hours cooking. Sodium hydroxide effluent has lowest Total Suspended Solid (TSS) of 3165mg/l while formic acid has 2245mg/l both at 90% concentrations after 2 and 3 hours cooking.