Inertial Focusing of Particles in Curved Micro-channels

Inertial focusing is the migration of particles in flow laterally across a channel into well-defined equilibrium positions. In microfluidic channels, inertial focusing takes advantage of hydrodynamic interactions even at high flow speeds. Particle isolation through inertial focusing is a high throughput method of processing biological samples for point-of-care diagnostics. While photos provide qualitative analyses of inertial focusing, we desired quantitative characterization of these systems. In this study, we ran flow experiments, first with fluorescent polystyrene beads and later with cells in solution, through curved micro-channels at controlled rates using a syringe pump. Our results from polystyrene bead experiments confirmed previous studies on flow through curved micro-channels, in which particles are focused along both sides of the channel at low flow rates and transition towards the center of the channel as the flow rate increases. FWHM analysis also showed that the streamline width is minimized at an intermediate flow rate, indicating inertial focusing is optimized under that condition. As this method of analysis was confirmed with polystyrene beads, we further used this analysis method to characterize the focusing of cells in solution. To maximize both throughput and purity, microfluidic devices must be designed to operate at the highest flow rate at which effective separation from bulk fluid can occur. The device presented in this report indeed isolates the desired target cells to be studied in downstream characterization.http://deepblue.lib.umich.edu/bitstream/2027.42/169578/1/Honors_Capstone_Anna_Kaehr.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/169578/2/Kaehr_Anna_Capstone_Poster.pptxhttp://deepblue.lib.umich.edu/bitstream/2027.42/169578/3/Capstone_Presentation_Video_Anna_Kaehr.mp

Global sector-specific Scope 1, 2, and 3 analyses for setting net-zero targets: agriculture, forestry, and processing harvested products

The aim of this research was the development of global 1.5 °C net-zero pathways for specific industries as classified under the Global Industry Classification System (GICS). In this article, we described the analysis of the Agriculture & Food and Forestry & Wood Products categories to determine their industry-specific Scope 1, 2, and 3 emissions on a global level. The accounting methodologies for Scope 3 emissions were developed for entity-level accounting and reporting. However, we suggested an alteration of the methodology for industry-wide Scope 3 analyses because of poor data availability and to avoid counting emissions twice. In this article, we described the calculation method and the key results for net-zero pathways for these two industry sectors. We showed that the decarbonization of the energy supply is possible for both sectors globally by 2050. We also described the land-use-related Scope 3 emissions for the agriculture and forestry sectors. The agricultural sector is unlikely to reach net-zero emissions by 2050, whereas the forest industry can become carbon negative

Integrated microfluidic tmRNA purification and real-time NASBA device for molecular diagnostics.

We demonstrate the first integrated microfluidic tmRNA purification and nucleic acid sequence-based amplification (NASBA) device incorporating real-time detection. The real-time amplification and detection step produces pathogen-specific response in < 3 min from the chip-purified RNA from 100 lysed bacteria. On-chip RNA purification uses a new silica bead immobilization method. On-chip amplification uses custom-designed high-selectivity primers and real-time detection uses molecular beacon fluorescent probe technology; both are integrated on-chip with NASBA. Present in all bacteria, tmRNA (10Sa RNA) includes organism-specific identification sequences, exhibits unusually high stability relative to mRNA, and has high copy number per organism; the latter two factors improve the limit of detection, accelerate time-to-positive response, and suit this approach ideally to the detection of small numbers of bacteria. Device efficacy was demonstrated by integrated on-chip purification, amplification, and real-time detection of 100 E. coli bacteria in 100 microL of crude lysate in under 30 min for the entire process

MultiMetEval: comparative and multi-objective analysis of genome-scale metabolic models

Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEv​al/downloads