Bibliographic record
Abstract
The predominant treatment for type 1 diabetes, insulin injections to regulate blood glucose levels, requires frequent blood glucose monitoring, injections, and is often associated with episodes of hypoglycaemia. Islet transplantation has emerged as an alternative cell-based therapy for type 1 diabetes to avoid the need for exogenous insulin. The Edmonton protocol, in which islet cells are isolated from a donor pancreas and transplanted into a type 1 diabetic undergoing immune suppression, can result in insulin independence in > 40 % of recipients three years post transplantation. Islet encapsulation in alginate beads is being investigated as a means to provide an immunoprotective barrier between the graft and the host immune system in order to overcome the need for chronic immune suppression. Traditional nozzle-based encapsulation methods produce highly uniform alginate beads, but limit the viscosity of alginate that can be used for encapsulation. An alternative stirred emulsification and internal gelation encapsulation approach has high production rates and can produce beads from highly concentrated alginate, but a broad bead size distribution is obtained. The objective of this work was to develop microchannel emulsification as a method to produce highly uniform, concentrated alginate beads at production rates sufficient for clinical islet transplantation. A dual-flow chamber system was designed, consisting in a microchannel plate with oblong straight-through channels mounted between two flow channels. Alginate droplets form as the to-be-dispersed phase flows through the channels and contacts an acidified continuous oil phase that also triggers internal gelation. Significant process development involving modification of the flow rate, continuous phase liquid, emulsifier, microchannel dimensions and material, and operating procedure was required to facilitate droplet formation and achieve stable bead production. The current process can be used to produce 4 mL/min/channel of 0.5% to 2.5% alginate beads of approximately 3 mm in diameter, with a coefficient of variation of 9 %. Microchannel emulsification represents a promising method to encapsulate cells in concentrated alginate beads that are highly uniform at high production rates. The alginate bead production process described in this work is a promising new method for cellular therapy and other applications in the food, drug, cosmetic and other industries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".