Renal Autologous Cell Therapy to Stabilize Function in Diabetes-Related Chronic Kidney Disease: Corroboration of Mechanistic Action With Cell Marker Analysis
Bibliographic record
Abstract
Introduction Chronic kidney disease (CKD) is a worldwide disease without cure. Selected renal cells (SRCs) can augment kidney function in animal models. This study correlates the phenotypical characteristics of autologous homologous SRCs (formulated product called Renal Autologous Cell Therapy [REACT]) injected into patients' kidneys with advanced type 2 diabetes-related CKD (D-CKD) to clinical and laboratory findings. Methods A total of 22 adults with type 2 D-CKD underwent a kidney biopsy followed by 2 subcortical injections of SRCs, 7 ± 3 months apart. There were 2 patients who had only 1 injection. We compared annualized estimated glomerular filtration rate (eGFR) slopes pre- and post-REACT injection using the 2009 CKD-EPI formula for serum creatinine (sCr) and the 2012 CKD-EPI Creatinine-Cystatin C equation and report clinical/laboratory changes. Fluorescent Activated Cell Sorting (FACS) Analysis for renal progenitor lineages in REACT and donor vascular endothelial growth factor A (VEGF-A) analysis were performed. Longitudinal parameter changes were analyzed with longitudinal linear mixed effects model. Results At baseline, the mean diabetes duration was 18.4 ± 8.80 years, glycated hemoglobin (Hgb) was 7.0 ± 1.05, and eGFR was 40.3 ± 9.35 ml/min per 1.73 m 2 using the 2012 CKD-EPI cystatin C and sCr formulas. The annualized eGFR slope (2012 CKD-EPI) was −4.63 ml/min per 1.73 m 2 per year pre-injection and improved to −1.69 ml/min per 1.73 m 2 per year post-injection ( P = 0.015). There were 7 patients who had an eGFR slope of >0 ml/min per 1.73 m 2 postinjection. SRCs were found to have cell markers of ureteric bud, mesenchyme cap, and podocyte sources and positive VEGF. There were 2 patients who had remote fatal adverse events determined as unrelated with the biopsies/injections or the REACT product. Conclusion Our cell marker analysis suggests that SRCs may enable REACT to stabilize and improve kidney function, possibly halting type 2 D-CKD progression.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".