| 1. |
- Afrasiabi, Roodabeh, et al.
(författare)
-
Integration of a droplet-based microfluidic system and silicon nanoribbon FET sensor
- 2016
-
Ingår i: Micromachines. - : MDPI AG. - 2072-666X. ; 7:8
-
Tidskriftsartikel (refereegranskat)abstract
- We present a novel microfluidic system that integrates droplet microfluidics with a silicon nanoribbon field-effect transistor (SiNR FET), and utilize this integrated system to sense differences in pH. The device allows for selective droplet transfer to a continuous water phase, actuated by dielectrophoresis, and subsequent detection of the pH level in the retrieved droplets by SiNR FETs on an electrical sensor chip. The integrated microfluidic system demonstrates a label-free detection method for droplet microfluidics, presenting an alternative to optical fluorescence detection. In this work, we were able to differentiate between droplet trains of one pH-unit difference. The pH-based detection method in our integrated system has the potential to be utilized in the detection of biochemical reactions that induce a pH-shift in the droplets.
|
|
| 2. |
- Ahmad, Nouman, et al.
(författare)
-
Voxel-wise body composition analysis using image registration of a three-slice CT imaging protocol : methodology and proof-of-concept studies
- 2024
-
Ingår i: Biomedical engineering online. - : Springer Nature. - 1475-925X. ; 23:1
-
Tidskriftsartikel (refereegranskat)abstract
- Background Computed tomography (CT) is an imaging modality commonly used for studies of internal body structures and very useful for detailed studies of body composition. The aim of this study was to develop and evaluate a fully automatic image registration framework for inter-subject CT slice registration. The aim was also to use the results, in a set of proof-of-concept studies, for voxel-wise statistical body composition analysis (Imiomics) of correlations between imaging and non-imaging data.Methods The current study utilized three single-slice CT images of the liver, abdomen, and thigh from two large cohort studies, SCAPIS and IGT. The image registration method developed and evaluated used both CT images together with image-derived tissue and organ segmentation masks. To evaluate the performance of the registration method, a set of baseline 3-single-slice CT images (from 2780 subjects including 8285 slices) from the SCAPIS and IGT cohorts were registered. Vector magnitude and intensity magnitude error indicating inverse consistency were used for evaluation. Image registration results were further used for voxel-wise analysis of associations between the CT images (as represented by tissue volume from Hounsfield unit and Jacobian determinant) and various explicit measurements of various tissues, fat depots, and organs collected in both cohort studies.Results Our findings demonstrated that the key organs and anatomical structures were registered appropriately. The evaluation parameters of inverse consistency, such as vector magnitude and intensity magnitude error, were on average less than 3 mm and 50 Hounsfield units. The registration followed by Imiomics analysis enabled the examination of associations between various explicit measurements (liver, spleen, abdominal muscle, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), thigh SAT, intermuscular adipose tissue (IMAT), and thigh muscle) and the voxel-wise image information.Conclusion The developed and evaluated framework allows accurate image registrations of the collected three single-slice CT images and enables detailed voxel-wise studies of associations between body composition and associated diseases and risk factors.
|
|
| 3. |
|
|
| 4. |
- Björk, Sara, 1990-, et al.
(författare)
-
Droplet microfluidic microcolony sorting by fluorescence area for high throughput, yield-based screening of triacyl glycerides in S. Cerevisiae
- 2020
-
Ingår i: MicroTAS 2020 - 24th International Conference on Miniaturized Systems for Chemistry and Life Sciences. - : Chemical and Biological Microsystems Society. ; , s. 1015-1016
-
Konferensbidrag (refereegranskat)abstract
- Here we present a droplet microfluidics workflow for cell factory screening by yield of an intracellular product from isogenic microcolonies, i.e. minimal cell populations, encapsulated in picoliter droplets. This allows us to utilize all the benefits of droplet microfluidic screening in terms of throughput, but based on the signal from a population average, rather than the noisy single cell signal. We demonstrate microcolony sorting by integrated droplet fluorescence area of encapsulated E. coli, optimize triglyceride (TG) microcolony assay in droplets and apply the microcolony screening concept to analyze triglyceride (TG) production in S. cerevisiae.
|
|
| 5. |
|
|
| 6. |
- Björk, Sara, 1990-
(författare)
-
Droplet microfluidics for screening and sorting of microbial cell factories
- 2019
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Cell factories are cells that have been engineered to produce a compound of interest, ranging from biopharmaceuticals to biofuels. With advances in metabolic engineering, the number of cell factory variants to evaluate has increased dramatically, necessitating screening methods with increased throughput. Microfluidic droplets, which can be generated, manipulated and interrogated at very high throughput, are isolated reaction vessels at the single cell scale. Compartmentalization maintains the genotype-phenotype link, making droplet microfluidics suitable for screening of extracellular traits such as secreted products and for screening of microcolonies originating from single cells. In Paper I, we investigated the impact of droplet microfluidic incubation formats on cell culture conditions and found that syringe and semi open incubation resulted in different metabolic profiles. Controlling culture conditions is key to cell factory screening, as product formation is influenced by the state of the cell. In Paper II and III, we used droplet microfluidics to perform screening campaigns of interference based cell factory variant libraries. In Paper II, two S. cerevisiae RNAi libraries were screened based on amylase secretion, and from the sorted fraction genes linked to improved protein secretion could be identified. In paper III, we screened a Synecosystis sp. CRISPRi library based on lactate secretion. The library was sorted at different time points after induction, followed by sequencing to reveal genes enriched by droplet sorting. In Paper IV, we developed a droplet microcolony-based assay for screening intracellular triacylglycerol (TAG) in S. cerevisiae, and showed improved strain separation compared to flow cytometry in a hypothetical sorting scenario. By screening microcolonies compartmentalized in droplets, we combine the throughput of single cell screening methods with the reduced impact of cell-to-cell noise in cell ensemble analysis.
|
|
| 7. |
- Björk, Sara, et al.
(författare)
-
Microfluidics for cell factory and bioprocess development
- 2019
-
Ingår i: Current Opinion in Biotechnology. - : Elsevier. - 0958-1669 .- 1879-0429. ; 55, s. 95-102
-
Tidskriftsartikel (refereegranskat)abstract
- Bioindustry is expanding to an increasing variety of food, chemical and pharmaceutical products, each requiring rapid development of a dedicated cell factory and bioprocess. Microfluidic tools are, together with tools from synthetic biology and metabolic modeling, being employed in cell factory and bioprocess development to speed up development and address new products. Recent examples of microfluidics for bioprocess development range from integrated devices for DNA assembly and transformation, to high throughput screening of cell factory libraries, and micron scale bioreactors for process optimization. These improvements act to improve the biotechnological engineering cycle with tools for building, testing and evaluating cell factories and bioprocesses by increasing throughput, parallelization and automation.
|
|
| 8. |
- Damiati, Safa A., et al.
(författare)
-
Artificial intelligence application for rapid fabrication of size-tunable PLGA microparticles in microfluidics
- 2020
-
Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 10:1
-
Tidskriftsartikel (refereegranskat)abstract
- In this study, synthetic polymeric particles were effectively fabricated by combining modern technologies of artificial intelligence (AI) and microfluidics. Because size uniformity is a key factor that significantly influences the stability of polymeric particles, therefore, this work aimed to establish a new AI application using machine learning technology for prediction of the size of poly(d,l-lactide-co-glycolide) (PLGA) microparticles produced by diverse microfluidic systems either in the form of single or multiple particles. Experimentally, the most effective factors for tuning droplet/particle sizes are PLGA concentrations and the flow rates of dispersed and aqueous phases in microfluidics. These factors were utilized to develop five different and simple in structure artificial neural network (ANN) models that are capable of predicting PLGA particle sizes produced by different microfluidic systems either individually or jointly merged. The systematic development of ANN models allowed ultimate construction of a single in silico model which consists of data for three different microfluidic systems. This ANN model eventually allowed rapid prediction of particle sizes produced using various microfluidic systems. This AI application offers a new platform for further rapid and economical exploration of polymer particles production in defined sizes for various applications including biomimetic studies, biomedicine, and pharmaceutics.
|
|
| 9. |
|
|
| 10. |
|
|
