Development and Use of a Galectin-1-Specific Nanobody for Tumor Imaging and Elucidating the Role of Galectin-1 in Cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Galectin-1 (GAL-1) plays a crucial role in cancer biology, especially in triple-negative breast cancer (TNBC), where it facilitates immune evasion and tumor progression. This study presents G1N1, a novel nanobody that specifically targets GAL-1 and exhibits remarkable affinity and selectivity. G1N1 effectively inhibits GAL-1-induced apoptosis in T cells while leaving GAL-7-induced apoptosis unaffected. Preclinical positron emission tomography (PET) imaging studies indicate that the radiolabeled [ 64 Cu]Cu-NOTA-G1N1 accumulates significantly in breast cancer tumors, highlighting its potential for diagnostic imaging and therapeutic monitoring. Transcriptomic analyses suggest that G1N1 may counteract GAL-1-induced immunosuppression and downregulate chemoresistance-associated genes, particularly those involved in the NF-κB/TNFα signaling pathway, while also decreasing the expression of prometastatic genes like MMP-3 . In conclusion, G1N1’s dual functionality as a diagnostic and therapeutic agent emphasizes its promise in personalized medicine, potentially enhancing clinical management strategies for TNBC and other aggressive cancers
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it