セプシス毒性ネットワークの再構築 - ダイナミック・シグナリングと多臓器損傷:レビュー

Shuai Liu¹, Qun Liang²

¹Graduate School, Heilongjiang University of Chinese Medicine, Harbin, China.

Biomolecules & biomedicine

|September 2, 2025

まとめ

セプシスには複雑な全身の毒性があり免疫機能の調節不良が臓器損傷を引き起こしますネットワークモデリングとマルチオミクスの統合により重要な毒性ノードを特定しパーソナライズされた治療のための毒症の進行を予測できます

科学分野:

システム生物学
免疫学
コンピュータ生物学

背景:

セプシスは全身の炎症,免疫機能の不調,多臓器損傷による命に関わる疾患です.
主なメカニズムは酸化ストレス,プログラムされた細胞死 (アポプトーシス,ピロプトーシス,フェロプトーシス),代謝再プログラムなどです.

研究の目的:

セプシス中の臓器内と臓器間の信号伝達経路の進化を合成する
マルチオミクス統合とネットワークモデリングの有用性を評価し,毒性ノードを特定し,疾患の進行を予測する.

主な方法:

PubMed,Web of Science,およびScopusからのメカニズム研究 (2015-2025) のナラティブレビューを実施しました.
非機械的な研究とケースレポートを除く文献のスクリーニングで補完されます.

主要な成果:

セプシスは,炎症から免疫抑制と臓器特異的な損傷への移行を含むダイナミックな全身ネットワークです.
臓器間の通信は,ダメージに関連した分子パターン (DAMP),エクソソーム,および代謝物によって起こります.
ダイナミック・ベイジアン・ネットワーク (DBN) やグラフ・ニューラル・ネットワーク (GNN) のような計算モデルは,規制ハブを特定し,予測を支援します.

結論:

セプシスは一時的に段階的な全身性毒性ネットワークと見なすことができます.
マルチオミクス,DBN/GNNモデリング,AIによる意思決定サポートは,個別化された,メカニズムに基づくセプシスケアのための枠組みを提供します.
これらの高度なアプローチの臨床的適用性を確保するには,厳格な検証が必要です.

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