Therapeutic effect of human umbilical cord mesenchymal stem cell transplantation on diabetic peripheral neuropathy
Bibliographic record
Abstract
Objective To observe the therapeutic effect of human umbilical cord mesenchymal stem cells(HUC-MSCs) transplantation on patients with diabetic peripheral neuropathy.Methods FBG,PBG,HbA1C levels,Toronto clinical scoring system(TCSS),electrophysiological examination were measured in 32 patients with diabetic peripheral neuropathy before and 1,3,6 months after they underwent HUC-MSCs transplantation.Observe the changes of clinical symptoms and the adverse reactions.Results The three follow-up results show that the FBG,PBG,HbA1C levels,TCSS,the distal motor latency of the median nerve,the sensory conduction velocity and the distal motor latency of the ulnar nerve,the positive rate of sensory conduction of the posterior tibial nerve,the distal motor latency and the positive rate of the sensory conduction of the common peroneal nerve all obviously improved.During the study period no adverse reaction occurred.The gross and fine motor function was most rapidly improved in 1 month afer the therapy and it could be continuously improved within 6 months after the therapy.Conclusions HUC-MSCs transplantation can significantly improve the clinical symptoms and electrophysiological examination of patients with diabetic peripheral neuropathy.It is a new safe,effective method to treat diabetic peripheral neuropathy.
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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) | 0.000 | 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".