h-FIBER: Microfluidic Topographical Hollow Fiber for Studies of Glomerular Filtration Barrier
Bibliographic record
Abstract
Kidney-on-a-chip devices may revolutionize the discovery of new therapies. However, fabricating a 3D glomerulus remains a challenge, due to a requirement for a microscale soft material with complex topography to support cell culture in a native configuration. Here, we describe the use of microfluidic spinning to recapitulate complex concave and convex topographies over multiple length scales, required for biofabrication of a biomimetic 3D glomerulus. We produced a microfluidic extruded topographic hollow fiber (h-FIBER), consisting of a vessel-like perfusable tubular channel for endothelial cell cultivation, and a glomerulus-like knot with microconvex topography on its surface for podocyte cultivation. Meter long h-FIBERs were produced in microfluidics within minutes, followed by chemically induced inflation for generation of topographical cues on the 3D scaffold surface. The h-FIBERs were assembled into a hot-embossed plastic 96-well plate. Long-term perfusion, podocyte barrier formation, endothelialization, and permeability tests were easily performed by a standard pipetting technique on the platform. Following long-term culture (1 month), a functional filtration barrier, measured by the transfer of albumin from the blood vessel side to the ultrafiltrate side, suggested the establishment of an engineered glomerulus.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".