Bibliographic record
Abstract
INTRODUCTION: This discourse delves into the intricate connections between the endosomal-lysosomal system and antibody-drug conjugates (ADCs), shedding light on an essential yet less understood dimension of targeted therapy. While ADCs have revolutionized cancer treatment, resistance remains a formidable challenge, often involving diverse and overlapping mechanisms. AREAS COVERED: This discourse highlights the roles of various components within the endosomal machinery, including Rab proteins, in ADC resistance development. It also explores how the transferrin-transferrin receptor and epidermal growth factor-epidermal growth factor receptor complexes, known for their roles in recycling and degradation process, respectively, can offer valuable insights for ADC design. Selected strategies to enhance lysosomal targeting are discussed, and potentially offer solutions to improve ADC efficacy. EXPERT OPINION: By harnessing these different insights that connect ADCs with the endosomal-lysosomal system, the field may benefit to shape the next-generation of ADC design for increased efficacy and improved patient outcomes.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".