13 research outputs found

    Theoretical investigations on modeling blood flow through vessel for understanding effectiveness of magnetic nanocarrier drug delivery systems

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    For cancer therapy, the focus is now on targeting the chemotherapy drugs to cancer cells without damaging other normal cells. The new materials based on bio-compatible magnetic carriers would be useful for targeted cancer therapy, however understanding their effectiveness should be done. This paper presents a comprehensive analysis of a dataset containing variables x(m), y(m), and U(m/s), where U represents velocity of blood through vessel containing ferrofluid. The effect of external magnetic field on the fluid flow is investigated using a hybrid modeling. The primary aim of this research endeavor was to construct precise and dependable predictive models for velocity, utilizing the provided input variables. Several base models, including K-nearest neighbors (KNN), decision tree (DT), and multilayer perceptron (MLP), were trained and evaluated. Additionally, an ensemble model called AdaBoost was implemented to further enhance the predictive performance. The hyper-parameter optimization technique, specifically the BAT optimization algorithm, was employed to fine-tune the models. The results obtained from the experiments demonstrated the effectiveness of the proposed approach. The combination of the AdaBoost algorithm and the decision tree model yielded a highly impressive score of 0.99783 in terms of R2, indicating a strong predictive performance. Additionally, the model exhibited a low error rate, as evidenced by the root mean square error (RMSE) of 5.2893 × 10−3. Similarly, the AdaBoost-KNN model exhibited a high score of 0.98524 using R2 metric, with an RMSE of 1.3291 × 10−2. Furthermore, the AdaBoost-MLP model obtained a satisfactory R2 score of 0.99603, accompanied by an RMSE of 7.1369 × 10−3

    A robust computational investigation on C₆₀ fullerene nanostructure as a novel sensor to detect SCNˉ

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    This study explored on the adsorption properties and electronic structure of SCNˉ via density functional theory analysis on the exterior surfaces of C₆₀ and CNTs using B3LYP functional and 6-31G** standard basis set. Then adsorption of SCNˉ through nitrogen atom on the C60 fullerene is electrostatic (₋48.02 kJ molˉ1) in comparison with the C₅₉Al fullerene that shows covalently attached to fullerene surface (₋389.10 kJ mol̄ˉ1). Our calculations demonstrate that the SCNˉ adsorption on the pristine and Al-doped single-walled CNTs are ₋173.13 and ₋334.43 kJ molˉ1, indicating that the SCNˉ can be chemically bonded on the surface of Al-doped CNTs. Moreover, the adsorption of SCNˉ on the C₆₀ surface is weaker in comparison with C₅₉B, C₅₉Al, and C₅₉Ga systems but its electronic sensitivity improved in comparison with those of C₅₉B, C₅₉Al, and C₅₉Ga fullerenes. The evaluation of adsorption energy, energy gap, and dipole moment demonstrates that the pure fullerene can be exploited in the design practice as an SCNˉ sensor and C₅₉Al can be used for SCNˉ removal application

    Biocompatibility and Hemolytic Activity Studies of Synthesized Alginate-Based Polyurethanes

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    Many investigators have focused on the development of biocompatible polyurethanes by chemical reaction of functional groups contained in a spacer and introduced in the PU backbone or by a grafting method on graft polymerization of functional groups. In this study, alginate-based polyurethane (PU) composites were synthesized via step-growth polymerization by the reaction of hydroxyl-terminated polybutadiene (HTPB) and hexamethylene diisocyanate (HMDI). The polymer chains were further extended with blends of 1,4-butanediol (1,4-BDO) and alginate (ALG) with different mole ratios. The structures of the prepared PU samples were elucidated with FTIR and 1H NMR spectroscopy. The crystallinity of the prepared samples was evaluated with the help of X-ray diffraction (XRD). The XRD results reveal that the crystallinity of the PU samples increases when the concentration of alginate increases. Thermogravimetric (TGA) results show that samples containing a higher amount of alginate possess higher thermal stability. ALG-based PU composite samples show more biocompatibility and less hemolytic activity. Mechanical properties, contact angle, and water absorption (%) were also greatly affected

    Folate Decorated Nanomicelles Loaded with a Potent Curcumin Analogue for Targeting Retinoblastoma

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    The aim of this study was to develop a novel folate receptor-targeted drug delivery system for retinoblastoma cells using a promising anticancer agent, curcumin-difluorinated (CDF), loaded in polymeric micelles. Folic acid was used as a targeting moiety to enhance the targeting and bioavailability of CDF. For this purpose, amphiphilic poly(styrene-co-maleic acid)-conjugated-folic acid (SMA-FA) was synthesized and utilized to improve the aqueous solubility of a highly hydrophobic, but very potent anticancer compound, CDF, and its targeted delivery to folate overexpressing cancers. The SMA-FA conjugate was first synthesized and characterized by 1H NMR, FTIR and DSC. Furthermore, the chromatographic condition (HPLC) for estimating CDF was determined and validated. The formulation was optimized to achieve maximum entrapment of CDF. The particle size of the micelles was measured and confirmed by dynamic light scattering (DLS) and transmission electron microscopy (TEM). Cytotoxicity studies were conducted on (Y-79 and WERI-RB) retinoblastoma cells. Results showed that the solubility of CDF could be increased with the newly-synthesized polymer, and the entrapment efficiency was >85%. The drug-loaded nanomicelles exhibited an appropriate size of <200 nm and a narrow size distribution. The formulation did not show any adverse cytotoxicity on a human retinal pigment epithelial cell (ARPE-19), indicating its safety. However, it showed significant cell killing activity in both Y-79 and WERI-RB retinoblastoma cell lines, indicating its potency in killing cancer cells. In conclusion, the folic acid-conjugated SMA loaded with CDF showed promising potential with high safety and pronounced anticancer activity on the tested retinoblastoma cell lines. The newly-formulated targeted nanomicelles thus could be a viable option as an alternative approach to current retinoblastoma therapies

    Olive Leaf Extracts for a Green Synthesis of Silver-Functionalized Multi-Walled Carbon Nanotubes

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    Green biosynthesis, one of the most dependable and cost-effective methods for producing carbon nanotubes, was used to synthesize nonhazardous silver-functionalized multi-walled carbon nanotubes (SFMWCNTs) successfully. It has been shown that the water-soluble organic materials present in the olive oil plant play a vital role in converting silver ions into silver nanoparticles (Ag-NPs). Olive-leaf extracts contain medicinal properties and combining these extracts with Ag-NPs is often a viable option for enhancing drug delivery; thus, this possibility was employed for in vitro treating cancer cells as a proof of concept. In this study, the green technique for preparing SFMWCNTs composites using plant extracts was followed. This process yielded various compounds, the most important of which were Hydroxytyrosol, Tyrosol, and Oleuropein. Subsequently, a thin film was fabricated from the extract, resulting in a natural polymer. The obtained nanomaterials have an absorption peak of 419 nm in their UV–Vis. spectra. SEM and EDS were also used to investigate the SFMWCNT nanocomposites’ morphology simultaneously. Moreover, the MTT assay was used to evaluate the ability of SFMWCNTs to suppress cancer cell viability on different cancer cell lines, MCF7 (human breast adenocarcinoma), HepG2 (human hepatocellular carcinoma), and SW620 (human colorectal cancer). Using varying doses of SFMWCNT resulted in the most significant cell viability inhibition, indicating the good sensitivity of SFMWCNTs for treating cancer cells. It was found that performing olive-leaf extraction at a low temperature in an ice bath leads to superior results, and the developed SFMWCNT nanocomposites could be potential treatment options for in vitro cancer cells

    Fabrication, In Vitro, and In Vivo Assessment of Eucalyptol-Loaded Nanoemulgel as a Novel Paradigm for Wound Healing

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    Wounds are the most common causes of mortality all over the world. Topical drug delivery systems are more efficient in treating wounds as compared to oral delivery systems because they bypass the disadvantages of the oral route. The aim of the present study was to formulate and evaluate in vitro in vivo nanoemulgels loaded with eucalyptol for wound healing. Nanoemulsions were prepared using the solvent emulsification diffusion method by mixing an aqueous phase and an oil phase, and a nanoemulgel was then fabricated by mixing nanoemulsions with a gelling agent (Carbopol 940) in a 1:1 ratio. The nanoemulgels were evaluated regarding stability, homogeneity, pH, viscosity, Fourier-transform infrared spectroscopy (FTIR), droplet size, zeta potential, polydispersity index (PDI), spreadability, drug content, in vitro drug release, and in vivo study. The optimized formulation, F5, exhibited pH values between 5 and 6, with no significant variations at different temperatures, and acceptable homogeneity and spreadability. F5 had a droplet size of 139 ± 5.8 nm, with a low polydispersity index. FTIR studies showed the compatibility of the drug with the excipients. The drug content of F5 was 94.81%. The percentage of wound contraction of the experimental, standard, and control groups were 100% ± 0.015, 98.170% ± 0.749, and 70.846% ± 0.830, respectively. Statistically, the experimental group showed a significant difference (p < 0.03) from the other two groups. The results suggest that the formulated optimized dosage showed optimum stability, and it can be considered an effective wound healing alternative

    Knowledge of and Testing Rate for Hepatitis C Infection among the General Public of Saudi Arabia: A Cross-Sectional Study

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    Introduction: The Ministry of Health in Saudi Arabia has announced a plan to eradicate hepatitis C virus (HCV) infection. This study sought to evaluate the knowledge levels and testing rate among the general population of Saudi Arabia. Methods: A cross-sectional study was conducted using data collected from an online, self-administered survey. Multivariable analysis was conducted using multiple binary logistic regression models to identify factors associated with low knowledge levels as well as predictors of HCV testing. Results: A total of 689 participants completed the survey. While most participants (88%) have heard of HCV infection, less than half (47.3%) understood that HCV is curable with medications. More than half of the participants (53.7%) have low knowledge about HCV infection. Testing for HCV was reported by 123 respondents (17.8%), and the odds of testing for HCV were significantly lower among residents of the Makkah region (OR = 0.59 [95% CI: 0.36&ndash;0.97]) and those with low knowledge level (OR = 0.47 [95% CI: 0.29&ndash;0.74]). HCV diagnosis was reported by nine respondents (1.3%), of whom only four reported receiving treatment (44%). Conclusions: Our study indicates inadequate knowledge levels and relatively low testing rate. These findings underscore the need for national awareness campaigns and more effective strategies for HCV screening

    The Bayesian-Based Area under the Curve of Vancomycin by Using a Single Trough Level: An Evaluation of Accuracy and Discordance at Tertiary Care Hospital in KSA

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    The AUC0–24 is the most accurate way to track the vancomycin level while the Cmin is not an accurate surrogate. Most hospitals in Saudi Arabia are under-practicing the AUC-guided vancomycin dosing and monitoring. No previous work has been conducted to evaluate such practice in the whole kingdom. The current study objective is to calculate the AUC0–24 using the Bayesian dosing software (PrecisePK), identify the probability of patients who receive the optimum dose of vancomycin, and evaluate the accuracy and precision of the Bayesian platform. This retrospective study was conducted at King Abdulaziz medical city, Jeddah. All adult patients treated with vancomycin were included. Pediatric patients, critically ill patients requiring ICU admission, patients with acute renal failure or undergoing dialysis, and febrile neutropenic patients were excluded. The AUC0–24 was predicted using the PrecisePK platform based on the Bayesian principle. The two-compartmental model by Rodvold et al. in this platform and patients’ dose data were utilized to calculate the AUC0–24 and trough level. Among 342 patients included in the present study, the mean of the estimated vancomycin AUC0–24 by the posterior model of PrecisePK was 573 ± 199.6 mg, and the model had a bias of 16.8%, whereas the precision was 2.85 mg/L. The target AUC0–24 (400 to 600 mg·h/L) and measured trough (10 to 20 mg/L) were documented in 127 (37.1%) and 185 (54%), respectively. Furthermore, the result demonstrated an increase in odds of AUC0–24 > 600 mg·h/L among trough level 15–20 mg/L group (OR = 13.2, p 0–24 ratio and measured trough concentration may jeopardize patient safety, and implantation of the Bayesian approach as a workable alternative to the traditional trough method should be considered
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