Immune ligands for cytotoxic T Lymphocytes CTLS in cancer stem cells CSCS
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
The immune system has come to the forefront of cancer therapeutics in recent years with the success of immune blockade inhibitors in a variety of cancers whose list is increasing with a quick pace. Despite the efficacy of these drugs across a significant part of the cancer spectrum, responses are still seen only in a minority of patients, that implies that most patients are refractory or promptly develop resistance to these agents. Mechanisms of this resistance are important to decipher as this knowledge may lead to the introduction of additional therapies or manipulations to modulate resistance. The cancer stem cell theory stipulates that a minority of cancer cells in a given tumor are responsible for self-renewal and bulk tumor propagation. These cells, in most instances, are rare and less proliferative but give rise to highly proliferative progeny. In addition, they are, in general, resistant to therapies and endowed with metastatic potential through a process called EMT (Epithelial to Mesenchymal Transition). Cancer stem cells resistance to treatments may relate to inherent insensitivity to external apoptotic stimuli and, thus, may extend to immune therapies by inhibiting the actions of Cytotoxic T Lymphocytes (CTLs) in the tumor micro-environment. This paper examines available data on expression and regulation of immune co-modulatory (co-stimulatory and co-inhibitory) ligands on cancer stem cells in order to devise strategies to circumvent resistance.
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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 | 0.001 | 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