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Effect of zinc oxide amounts on the properties and antibacterial activities of zeolite/zinc oxide nanocomposite

Alswat AA, Ahmad MB, Saleh TA, Hussein MZB, Ibrahim NA

Mater Sci Eng C Mater Biol Appl, 2016 Nov 01;68:505-511.
PMID: 27524047 DOI: 10.1016/j.msec.2016.06.028

Nanocomposites of zinc oxide loaded on a zeolite (Zeolite/ZnO NCs) were prepared using co-precipitation method. The ratio effect of ZnO wt.% to the Zeolite on the antibacterial activities was investigated. Various techniques were used for the nanocomposite characterization, including UV-vis, FTIR, XRD, EDX, FESEM and TEM. XRD patterns showed that ZnO peak intensity increased while the intensities of Zeolite peaks decreased. TEM images indicated a good distribution of ZnO-NPs onto the Zeolite framework and the cubic structure of the zeolite was maintained. The average particle size of ZnO-nanoparticles loaded on the surface of the Zeolite was in the range of 1-10nm. Moreover, Zeolite/ZnO NCs showed noticeable antibacterial activities against the tested bacteria; Gram- positive and Gram- negative bacteria, under normal light. The efficiency of the antibacterial increased with increasing the wt.% from 3 to 8 of ZnO NPs, and it reached 87% against Escherichia coli E266.
Predicting of the refractive index of haemoglobin using the Hybrid GA-SVR approach

Oyehan TA, Alade IO, Bagudu A, Sulaiman KO, Olatunji SO, Saleh TA

Comput Biol Med, 2018 07 01;98:85-92.
PMID: 29777986 DOI: 10.1016/j.compbiomed.2018.04.024

The optical properties of blood play crucial roles in medical diagnostics and treatment, and in the design of new medical devices. Haemoglobin is a vital constituent of the blood whose optical properties affect all of the optical properties of human blood. The refractive index of haemoglobin has been reported to strongly depend on its concentration which is a function of the physiology of biological cells. This makes the refractive index of haemoglobin an essential non-invasive bio-marker of diseases. Unfortunately, the complexity of blood tissue makes it challenging to experimentally measure the refractive index of haemoglobin. While a few studies have reported on the refractive index of haemoglobin, there is no solid consensus with the data obtained due to different measuring instruments and the conditions of the experiments. Moreover, obtaining the refractive index via an experimental approach is quite laborious. In this work, an accurate, fast and relatively convenient strategy to estimate the refractive index of haemoglobin is reported. Thus, the GA-SVR model is presented for the prediction of the refractive index of haemoglobin using wavelength, temperature, and the concentration of haemoglobin as descriptors. The model developed is characterised by an excellent accuracy and very low error estimates. The correlation coefficients obtained in these studies are 99.94% and 99.91% for the training and testing results, respectively. In addition, the result shows an almost perfect match with the experimental data and also demonstrates significant improvement over a recent mathematical model available in the literature. The GA-SVR model predictions also give insights into the influence of concentration, wavelength, and temperature on the RI measurement values. The model outcome can be used not only to accurately estimate the refractive index of haemoglobin but also could provide a reliable common ground to benchmark the experimental refractive index results.
Estimating the refractive index of oxygenated and deoxygenated hemoglobin using genetic algorithm - support vector regression model

Alade IO, Bagudu A, Oyehan TA, Rahman MAA, Saleh TA, Olatunji SO

Comput Methods Programs Biomed, 2018 Sep;163:135-142.
PMID: 30119848 DOI: 10.1016/j.cmpb.2018.05.029

BACKGROUND AND OBJECTIVES: The refractive index of hemoglobin plays important role in hematology due to its strong correlation with the pathophysiology of different diseases. Measurement of the real part of the refractive index remains a challenge due to strong absorption of the hemoglobin especially at relevant high physiological concentrations. So far, only a few studies on direct measurement of refractive index have been reported and there are no firm agreements on the reported values of refractive index of hemoglobin due to measurement artifacts. In addition, it is time consuming, laborious and expensive to perform several experiments to obtain the refractive index of hemoglobin. In this work, we proposed a very rapid and accurate computational intelligent approach using Genetic Algorithm/Support Vector Regression models to estimate the real part of the refractive index for oxygenated and deoxygenated hemoglobin samples.
METHODS: These models utilized experimental data of wavelengths and hemoglobin concentrations in building highly accurate Genetic Algorithm/Support Vector Regression model (GA-SVR).
RESULTS: The developed methodology showed high accuracy as indicated by the low root mean square error values of 4.65 × 10-4 and 4.62 × 10-4 for oxygenated and deoxygenated hemoglobin, respectively. In addition, the models exhibited 99.85 and 99.84% correlation coefficients (r) for the oxygenated and deoxygenated hemoglobin, thus, validating the strong agreement between the predicted and the experimental results CONCLUSIONS: Due to the accuracy and relative simplicity of the proposed models, we envisage that these models would serve as important references for future studies on optical properties of blood.
Fulltext Development of a predictive model for estimating the specific heat capacity of metallic oxides/ethylene glycol-based nanofluids using support vector regression

Alade IO, Abd Rahman MA, Bagudu A, Abbas Z, Yaakob Y, Saleh TA

Heliyon, 2019 Jun;5(6):e01882.
PMID: 31304407 DOI: 10.1016/j.heliyon.2019.e01882

The specific heat capacity of nanofluids ( C P n f ) is a fundamental thermophysical property that measures the heat storage capacity of the nanofluids. C P n f is usually determined through experimental measurement. As it is known, experimental procedures are characterised with some complexities, which include, the challenge of preparing stable nanofluids and relatively long periods to conduct experiments. So far, two correlations have been developed to estimate the C P n f . The accuracies of these models are still subject to further improvement for many nanofluid compositions. This study presents a four-input support vector regression (SVR) model hybridized with a Bayesian algorithm to predict the specific heat capacity of metallic oxides/ethylene glycol-based nanofluids. The bayesian algorithm was used to obtain the optimum SVR hyperparameters. 189 experimental data collected from published literature was used for the model development. The proposed model exhibits low average absolute relative deviation (AARD) and a high correlation coefficient (r) of 0.40 and 99.53 %, respectively. In addition, we analysed the accuracies of the existing analytical models on the considered nanofluid compositions. The model based on the thermal equilibrium between the nanoparticles and base fluid (model II) show good agreement with experimental results while the model based on simple mixing rule (model I) overestimated the specific heat capacity of the nanofluids. To further validate the superiority of the proposed technique over the existing analytical models, we compared various statistical errors for the three models. The AARD for the BSVR, model II, and model I are 0.40, 0.82 and 4.97, respectively. This clearly shows that the model developed has much better prediction accuracy than existing models in predicting the specific heat capacity of metallic oxides/ethylene glycol-based nanofluids. We believe the presented model will be important in the design of nanofluid-based applications due to its improved accuracy.
Hemodialysis performance and anticoagulant activities of PVP-k25 and carboxylic-multiwall nanotube composite blended Polyethersulfone membrane

Irfan M, Irfan M, Shah SM, Baig N, Saleh TA, Ahmed M, et al.

Mater Sci Eng C Mater Biol Appl, 2019 Oct;103:109769.
PMID: 31349444 DOI: 10.1016/j.msec.2019.109769

Non-covalent electrostatic interaction between amide nitrogen and carbonyl carbon of shorter chain length of polyvinylpyrrolidone (PVP-k25) was developed with in-house carboxylic oxidized multiwall carbon nanotubes (O-MWCNT) and then blended with Polyethersulfone (PES) polymer. FTIR analysis was utilized to confirm bonding nature of nano-composites (NCs) of O-MWCNT/PVP-k25 and casting membranes. Non-solvent induces phase separation process developed regular finger-like channels in composite membranes whereas pristine PES exhibited spongy entities as studied by cross sectional analysis report of FESEM. Further, FESEM instrument was also utilized to observe the dispersion of O-MWCNT/PVP based nanocomposite (NCs) with PES and membranes leaching phenomena analysis. Contact angle experiments described 24% improvement of hydrophilic behaviour, leaching ratio of additives was reduced to 1.89%, whereas water flux enhanced up to 6 times. Bovine serum albumin (BSA) and lysozyme based antifouling analysis shown up to 25% improvement, whereas 84% of water flux was regained after protein fouling than pristine PES. Anticoagulant activity was reported by estimating prothrombin, thrombin, plasma re-calcification times and production of fibrinogen cluster with platelets-adhesions photographs and hemolysis experiments. Composite membranes exhibited 3.4 and 3 times better dialysis clearance ratios of urea and creatinine solutes as compared to the raw PES membrane.
Fabrication and performance evaluation of blood compatible hemodialysis membrane using carboxylic multiwall carbon nanotubes and low molecular weight polyvinylpyrrolidone based nanocomposites

Irfan M, Irfan M, Idris A, Baig N, Saleh TA, Nasiri R, et al.

J Biomed Mater Res A, 2019 03;107(3):513-525.
PMID: 30484939 DOI: 10.1002/jbm.a.36566

This study focused to optimize the performance of polyethersulfone (PES) hemodialysis (HD) membrane using carboxylic functionalized multiwall carbon nanotubes (c-MWCNT) and lower molecular weight grade of polyvinylpyrrolidone (PVP-k30). Initially, MWCNT were chemically functionalized by acid treatment and nanocomposites (NCs) of PVP-k30 and c-MWCNT were formed and subsequently blended with PES polymer. The spectra of FTIR of the HD membranes revealed that NCs has strong hydrogen bonding and their addition to PES polymer improved the capillary system of membranes as confirmed by Field Emission Scanning Electron Microscope (FESEM) and leaching of the additive decreased to 2% and hydrophilicity improved to 22%. The pore size and porosity of NCs were also enhanced and rejection rate was achieved in the establish dialysis range (<60 kDa). The antifouling studies had shown that NCs membrane exhibited 30% less adhesion of protein with 80% flux recovery ratio. The blood compatibility assessment disclosed that NCs based membranes showed prolonged thrombin and prothrombin clotting times, lessened production of fibrinogen cluster, and greatly suppressed adhesion of blood plasma than a pristine PES membrane. The results also unveiled that PVP-k30/NCs improved the surface properties of the membrane and the urea and creatinine removal increased to 72% and 75% than pure PES membranes. © 2018 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 107A: 513-525, 2019.
Fulltext Potential application of nanotechnology in the treatment, diagnosis, and prevention of schistosomiasis

Qadeer A, Ullah H, Sohail M, Safi SZ, Rahim A, Saleh TA, et al.

Front Bioeng Biotechnol, 2022;10:1013354.
PMID: 36568300 DOI: 10.3389/fbioe.2022.1013354

Schistosomiasis is one of the neglected tropical diseases that affect millions of people worldwide. Globally, it affects economically poor countries, typically due to a lack of proper sanitation systems, and poor hygiene conditions. Currently, no vaccine is available against schistosomiasis, and the preferred treatment is chemotherapy with the use of praziquantel. It is a common anti-schistosomal drug used against all known species of Schistosoma. To date, current treatment primarily the drug praziquantel has not been effective in treating Schistosoma species in their early stages. The drug of choice offers low bioavailability, water solubility, and fast metabolism. Globally drug resistance has been documented due to overuse of praziquantel, Parasite mutations, poor treatment compliance, co-infection with other strains of parasites, and overall parasitic load. The existing diagnostic methods have very little acceptability and are not readily applied for quick diagnosis. This review aims to summarize the use of nanotechnology in the treatment, diagnosis, and prevention. It also explored safe and effective substitute approaches against parasitosis. At this stage, various nanomaterials are being used in drug delivery systems, diagnostic kits, and vaccine production. Nanotechnology is one of the modern and innovative methods to treat and diagnose several human diseases, particularly those caused by parasite infections. Herein we highlight the current advancement and application of nanotechnological approaches regarding the treatment, diagnosis, and prevention of schistosomiasis.