Kruppel-like factor 4 expression in normal and pathological human testes
Bibliographic record
Abstract
Krüppel-like factor 4 (KLF4) is a transcription factor involved in many cellular and developmental processes such as terminal differentiation of cells and carcinogenesis. Mice lacking KLF4 die post-natally due to skin barrier deficiencies and exhibit several additional cellular defects. The adult rodent testis expresses high levels of Klf4 mRNA. Using in situ hybridization, we previously localized most of the Klf4 mRNA to round spermatids in mice. Moreover, in rodent Sertoli cells, Klf4 is strongly inducible by FSH. Here, we show by northern blot analysis that the human testis also strongly expresses KLF4. Applying immunohistochemistry, we localized KLF4 protein to the nuclei of round spermatids during normal spermatogenesis stages II-IV. Analysing round spermatid maturation arrests, strong cytoplasmic staining could be seen in two samples. We failed to detect KLF4 in human Sertoli cells. Most human Leydig cells expressed KLF4 at high levels in the nucleus. However, some individual Leydig cells lacked KLF4, suggesting different functional states of the Leydig cells. The strong expression of KLF4 in the human testis and the importance of KLF4 in several mouse tissues suggest a significant role for KLF4 in the human testis. A first hint at a role for KLF4 during spermiogenesis could be the altered subcellular localization of the protein during arrested spermiogenesis.
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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 | 0.001 | 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".