Reduced growth of human sarcoma xenografts in hosts homozygous for the <i>lit</i> mutation
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Prior studies have shown that sarcoma growth can be stimulated by insulin-like growth factor-I (IGF-I). To extend this line of research, we carried out in vivo growth studies of primary human sarcoma in immunosuppressed control and IGF-I-deficient mice. METHODS: Human sarcoma specimens (one osteosarcoma and seven soft tissue sarcomas) were harvested in the operating room and implanted in immunosuppressed mice. Second-generation sarcomas were transplanted to control (GH replete lit/+ mice) and to experimental (GH/IGF-I-deficient lit/lit) animals. When tumors reached 1,000 mm(3) in one group, average tumor size was compared in the two groups. IGF-I receptor expression was measured by RT-PCR and IGF-I receptor binding sites were assayed by radiolabeled IGF-I. RESULTS: Five of eight sarcomas demonstrated reduced growth in the GH/IGF-I-deficient lit/lit animals. In four of the five sarcomas that demonstrated growth inhibition, IGF-R was elevated relative to placenta or a positive control cell line (MCF-7, which is known to be responsive to IGF-I in vitro and in vivo). In three of the five sarcomas that demonstrated growth suppression, IGF-R was elevated twofold after implantation in the experimental IGF-I-deficient animals. CONCLUSIONS: The GH-IGF axis may be an important stimulator of tumor growth in sarcomas. These experiments suggest that IGF suppression may inhibit sarcoma growth in vivo.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".