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- All Subjects: Biomaterials
- Creators: Harrington Bioengineering Program
We carried out secondary analyses on a subsample of sedentary, overweight/obese adults who participated in a 4-month, 2x2, randomized-controlled walking intervention examining the effects of goal setting (static v. adaptive goals) and rewards (immediate v. delayed) on steps/day (N=96). Fasting blood samples (n=58) were collected from participants before and after the intervention. Premenopausal females were in the follicular phase of their menstrual cycles. Lipid and glucose levels were measured using an automated chemistry analyzer, while insulin was measured using radio-immunoassay. Homeostatic model of insulin resistance (HOMA-IR) was calculated using the following formula (HOMA-IR=glucose x insulin / 405). We examined associations [partial correlations (adjusted for age)] between changes in blood biomarkers and VO2peak and cfPWV, irrespective of group, and we used linear mixed models to examine between-group differences in levels of and change in biomarker outcomes.
Groups did not differ in overall levels of, or degree of change in, biomarker outcomes (all p>0.05). Mean changes, irrespective of group, in biomarkers were as follows: glucose Δ= 0.74± 4.5mg/dl; insulin Δ= 0.09 ± 4.1 µU/ml; total cholesterol Δ= 0.24 ± 20.6 mg/dl; HDL-C Δ= 0.27 ± 5.1 mg/dl; LDL-C Δ= 1.3 ± 19.9 mg/dl; triglycerides Δ= 1.7 ± 27.2 mg/dl; HOMA-IR Δ = -.0548 ± 1.05). We found no significant associations between change in biomarker levels and change in VO2peak or change in cfPWV (all correlation coefficients < 0.15; p > 0.05).
A 4-month, behavioral economics-based mHealth intervention focused on increasing steps/day did not bring about favorable changes on markers of glycemia, insulin resistance and blood lipids.
The goal of this research project is to create a Mathcad template file capable of statistically modelling the effects of mean and standard deviation on a microparticle batch characterized by the log normal distribution model. Such a file can be applied during manufacturing to explore tolerances and increase cost and time effectiveness. Theoretical data for the time to 60% drug release and the slope and intercept of the log-log plot were collected and subjected to statistical analysis in JMP. Since the scope of this project focuses on microparticle surface degradation drug release with no drug diffusion, the characteristic variables relating to the slope (n = diffusional release exponent) and the intercept (k = kinetic constant) do not directly apply to the distribution model within the scope of the research. However, these variables are useful for analysis when the Mathcad template is applied to other types of drug release models.
Polymeric nanoparticles (NP) consisting of Poly Lactic-co-lactic acid - methyl polyethylene glycol (PLLA-mPEG) or Poly Lactic-co-Glycolic Acid (PLGA) are an emerging field of study for therapeutic and diagnostic applications. NPs have a variety of tunable physical characteristics like size, morphology, and surface topography. They can be loaded with therapeutic and/or diagnostic agents, either on the surface or within the core. NP size is an important characteristic as it directly impacts clearance and where the particles can travel and bind in the body. To that end, the typical target size for NPs is 30-200 nm for the majority of applications. Fabricating NPs using the typical techniques such as drop emulsion, microfluidics, or traditional nanoprecipitation can be expensive and may not yield the appropriate particle size. Therefore, a need has emerged for low-cost fabrication methods that allow customization of NP physical characteristics with high reproducibility. In this study we manufactured a low-cost (<$210), open-source syringe pump that can be used in nanoprecipitation. A design of experiments was utilized to find the relationship between the independent variables: polymer concentration (mg/mL), agitation rate of aqueous solution (rpm), and injection rate of the polymer solution (mL/min) and the dependent variables: size (nm), zeta potential, and polydispersity index (PDI). The quarter factorial design consisted of 4 experiments, each of which was manufactured in batches of three. Each sample of each batch was measured three times via dynamic light scattering. The particles were made with PLLA-mPEG dissolved in a 50% dichloromethane and 50% acetone solution. The polymer solution was dispensed into the aqueous solution containing 0.3% polyvinyl alcohol (PVA). Data suggests that none of the factors had a statistically significant effect on NP size. However, all interactions and relationships showed that there was a negative correlation between the above defined input parameters and the NP size. The NP sizes ranged from 276.144 ± 14.710 nm at the largest to 185.611 ± 15.634 nm at the smallest. In conclusion, the low-cost syringe pump nanoprecipitation method can achieve small sizes like the ones reported with drop emulsion or microfluidics. While there are trends suggesting predictable tuning of physical characteristics, significant control over the customization has not yet been achieved.