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Neural Circuits

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Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
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In the secretory pathway, vesicles transport proteins from one cellular compartment to another in forward transport to deliver the protein to its correct location. Occasionally, misfolded proteins and incorrect proteins escape their original compartments, and a retrieval pathway is used to return the escaped proteins to their original compartment.
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Extraction: Advanced Methods00:56

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Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
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Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
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Related Experiment Video

Updated: Sep 20, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
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Conditional Probability Joint Extraction of Nested Biomedical Events: Design of a Unified Extraction Framework Based

Yan Wang1, Jian Wang1, Huiyi Lu2

  • 1School of Computer Science and Technology, Dalian University of Technology, Dalian, China.

JMIR Medical Informatics
|June 7, 2022
PubMed
Summary

This study introduces a novel joint extraction model for nested biomedical events, significantly improving performance by integrating trigger probability and syntactic structures. The model effectively reduces cascading errors in event extraction tasks.

Keywords:
Dice lossGCNgraph convolutional networkjoint extractionnested biomedical eventsyntactic structure

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Area of Science:

  • Biomedical Natural Language Processing
  • Computational Linguistics
  • Artificial Intelligence

Background:

  • Nested event extraction in biomedical text is challenging due to complex event structures.
  • Existing pipeline models suffer from cascading errors and ignore task dependencies.
  • Underwhelming performance in nested biomedical event extraction necessitates advanced approaches.

Purpose of the Study:

  • To design a unified framework for joint training of biomedical event triggers and arguments.
  • To enhance the performance of extracting complex, nested biomedical events.
  • To mitigate cascading errors inherent in traditional event extraction pipelines.

Main Methods:

  • Proposed an end-to-end joint extraction model incorporating trigger probability distributions.
  • Integrated syntactic structure using an attention-based gate graph convolutional network.
  • Developed a model to capture interrelations between triggers and entities for improved nested event extraction.

Main Results:

  • Achieved the best F1 score on the multilevel event extraction biomedical event extraction corpus.
  • Demonstrated favorable performance on the 2011 Genia event corpus (biomedical NLP shared task).
  • The proposed method effectively alleviates cascading errors in event extraction.

Conclusions:

  • The conditional probability joint extraction model excels at nested biomedical event extraction.
  • Joint extraction and syntax graph structures are key to the model's success.
  • The model exhibits good generalization performance without external knowledge or feature engineering.