ArticleBioactive materials2025
Throw out an oligopeptide to catch a protein: Deep learning and natural language processing-screened tripeptide PSP promotes Osteolectin-mediated vascularized bone regeneration.
Article in Bioactive materials, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Enhancing the fine-scale prediction of pine wilt disease through the integration of a multihead attention mechanism.Pest management science · 2026Article
- AI-guided precise design of antimicrobial polymers through high-throughput screening technology on an automated platform.Bioactive materials · 2026Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Angiogenesis is imperative for bone regeneration, yet the conventional cytokine therapies have been constrained by prohibitive costs and safety apprehensions. It is urgent to develop a safer and more efficient therapeutic alternative. Herein, utilizing the methodologies of Deep Learning (DL) and Natural Language Processing (NLP), we proposed a paradigm algorithm that amalgamates
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.