http://hdl.handle.net/123456789/952 2026-04-14T23:14:16Z 2026-04-14T23:14:16Z Nyarko, Savanna http://hdl.handle.net/123456789/12221 2025-06-09T11:58:43Z 2024-01-01T00:00:00Z

Drug Delivery by Zeolite Nanomaterials in Treatment of Breast Cancer: In Vitro Nyarko, Savanna In this work, synthetic Linde type A (LTA) zeolites were examined to find out how well they could encapsulate and release doxorubicin cancer drug. Synthetic zeolites were used for this study because of their uniform pore distribution and crystal purity. The samples were characterized using X-ray diffraction spectroscopy (XRD) and Fourier Transform Infrared Spectroscopy (FTIR). The XRD data on the control LTA zeolite showed average crystallite size of 40.89 nm, 28.40 nm and 29.76 nm at 60℃, 80 ℃ and 105 ℃ respectively. The percentage crystallinity also revealed values of 65.99, 71.39 and 76.37 at 60℃, 80 ℃ and 105 ℃ respectively. The XRD diffraction pattern on drug loaded LTA zeolite showed average crystallite size of 24.89 nm, 16.44 nm and 26.91 nm at 60℃, 80 ℃ and 105 ℃ respectively. The percentage crystallinity of the loaded drug on LTA zeolite also revealed values of 70.79, 83.78 and 68.82 at 60℃, 80 ℃ and 105 ℃ respectively. The FTIR data also showed the signature peaks characteristics of LTA zeolites at all the three temperatures (60℃, 80 ℃ and 105 ℃). The morphology of the control and loaded LTA zeolites were determined by Helium Ion Microscope (HIM) and Scanning Electron Microscope (SEM). Brunauer-Emmett- Teller (BET) surface area, pore size and pore volume were also determined. The drug release data from 60 ℃ had a correlation (R2) values of 0.9139, 0.8764 and 0.7844 with the first-order, Hixson-Crowell and zero-order models respectively. Drug release data for 80 ℃ and 105 ℃ also had a (R2) values of 0.7345 and 0.5160 respectively for the Korsmeyer-Peppas model. The Alamar blue assay cell viability results showed that 105 ℃ was cytotoxic to the cells with an IC50 of 92 μg/ml. xiii, 100p:, ill.

2024-01-01T00:00:00Z Manu, Jones Asante http://hdl.handle.net/123456789/12219 2025-06-09T11:46:51Z 2023-12-01T00:00:00Z

Quartic Rank Transmutation of Gamma–Type Distributions: Characteristics and Estimation Manu, Jones Asante Rank transmutation maps have emerged as one of the adopted methods for proposing new probability distributions. This study used the quartic rank transmutation to introduce three new probability distributions: the Quartic Transmuted Exponential Distribution, Quartic Transmuted Lindley Distribution, and Quartic Transmuted Rayleigh Distribution. The construction of these distributions involves meticulously examining mathematical concepts, encompassing probability density functions, survival functions, moments, entropies, and order statistics. Visual aids, including cumulative distribution functions, probability density functions, and hazard rate functions, enhance the comprehension of distribution characteristics. A comprehensive simulation study underscores a consistent trend: a reduction in bias for maximum likelihood estimation and refinement in standard errors with increasing sample size. The practical applicability of these newly proposed distributions was demonstrated using real-world datasets. The quartic transmuted exponential distribution was effectively employed to model the lifetime of 50 devices, referencing data from Aarset’s study in 1987. Similarly, the quartic transmuted Lindley distribution was adeptly applied to remission times (measured in months) of 128 bladder cancer patients. Finally, the quartic transmuted Rayleigh distribution was successfully utilized to analyze a dataset comprising 72 instances of exceedance from the Wheaton River flood data near Carcoss in Yukon Territory, Canada. Evaluation criteria such as log-likelihood, AIC, AICc, and BIC affirm the superior flexibility and performance of the proposed distributions. This research significantly contributes to distribution theory, offering innovative methods to enhance distribution adaptability in diverse applications. xi, 171p:, ill.

2023-12-01T00:00:00Z Amstrong, Justice Wiston Jonathan http://hdl.handle.net/123456789/12212 2025-06-09T10:48:48Z 2023-02-01T00:00:00Z

Analysis of Levels of Heavy Metals, Essential Elements and Persistent Organic Pollutants (Pops) in Human Breast Milk: A Study at the Ho Teaching Hospital Amstrong, Justice Wiston Jonathan Human breast milk is, by far, the richest source of nutrition. However, breast milk is not pristine. The study aimed to analyse breast milk at lactational stages for persistent organic pollutants (OCPs, PCBs and PFAS), five heavy metals and essential elements. Participants for the study were healthy lactating mothers (aged 18 – 42 years) from first to third week postpartum. Forty-seven participants were recruited for the study. Forty millilitres (40 mL) of colostrum, transitional milk and mature milk were collected from each participant, making a total of 150 samples. Besides, each participant completed a comprehensive questionnaire to elicit information on biodata, place of residence and dietary pattern. Ten millilitres (10 mL) aliquot of each breast milk sample was prepared, extracted and analysed for PFAS using UPLC–MS/MS. Another 10 mL aliquot sample was extracted using QUECHERS and cleaned up and analysed for OCPs and PCBs using GC – ECD and GC–MS respectively A further 10 mL aliquots sample were acid digested employing EPA Method 3010A and analysed using ICP-OES. Statistical analyses were performed using IBM SPSS (Version 24), Excel Tool Pak and XLSTAT 2022.4.1.1377 and the results summarised in tables and figures. The mean Levels and ranges of PFAS detected in breast milk ranged from 2.65 ± 3.31 ng/L (PFHxA) – 83.14 ± 38.61 ng/L (PFOS). Both OCPs and PCBs analyzed were all below limits of detection. Mean levels of heavy metals in colostrum, transitional milk and mature milk respectively ranged from 0.002 (Cd) – 0.872 (Al) μg/L; 0.002 (Cd) – 0.997 (Pb) μg/L and 0.002 (Cd) – 0.564 (Al). The mean levels of essential elements ranged from 0.07 (Se) – 815.00 (K); 0.07 (Se) – 1008,00 (Na) and 0.07 (Se) – 596.00 (K) respectively during the stages of lactation. xxxii, 430p:, ill.

2023-02-01T00:00:00Z Chataa, Paul http://hdl.handle.net/123456789/12200 2025-06-05T13:41:45Z 2024-07-01T00:00:00Z

Mathematical Model of Immune Response to Hepatitis B Virus and Liver Cancer Co-Existence Dynamics in the Presence of Treatment Chataa, Paul The principal method for modeling the spread of infectious diseases generally involves the application of ordinary differential equations. Studies have demonstrated that an effective strategy for refining certain mathematical models is the integration of fractional-order differential equations. To gain a more profound understanding of the interactions between the hepatitis B virus (HBV), liver cancer, and immune system cells, a mathematical model that combined both ordinary and fractional differential equations was investigated. This model was closely aligned with experimental data on viral DNA load. The work concentrated on four qualitative scenarios: the innate immune response, adaptive immune response, cytokine response, and the coexistence of infection dynamics. Unlike earlier models, liver cells were classified into distinct stages of infection. For populations of non-pathogenic macrophages in the presence and absence of malignant cells, the study calculated the invasion probability for transmission dynamics, represented by the control reproduction number, Rc. The iterated two-step Adams-Bashforth method was employed for numerical simulations using the ABC fractional derivative in the Caputo sense, while the Latin Hypercube Sampling (LHS) and Partial Rank Correlation Coefficients (PRCC) techniques were utilized for parameter sensitivity analysis. The work identified the key transmission mechanism of viral load and proposed an optimal therapeutic method for viral treatment. Model parameters were estimated using nonlinear least squares fitting of longitudinal data (serum HBV DNA viral load) from existing literature. Finally, the study compared the classical-order model system with the ABC fractional differential equations model system to determine which offered superior performance. Both methods were evaluated using simulation results of the state variables, revealing that the fractional model provides more detailed results than the classical model. xvi, 226p:, ill.

2024-07-01T00:00:00Z