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Received β€” 2 April 2026 ⏭

Dunhuang Daxiefei Decoction ameliorates acute lung injury via the HIF-1alpha/glycolysis/H3K18la axis

βœ‡Omics In Lung
By: Jiayun Wang Β· Liangbo Jiao Β· Zhiqiang Yan Β· Shun Wang Β· Suwan Wu Β· Tao Guo Β· Yuetong Yang Β· Xiaoyingzi Su Β· Bo Tan Β· Aidong Yang
28 March 2026 at 18:00

J Ethnopharmacol. 2026 Mar 26;365:121591. doi: 10.1016/j.jep.2026.121591. Online ahead of print.

ABSTRACT

ETHNOPHARMACOLOGICAL RELEVANCE: Acute lung injury (ALI) lacks effective therapies. HIF-1Ξ±-driven glycolysis can promote histone lactylation and sustain pro-inflammatory (M1) macrophage responses. Daxiefei Decoction (DXFD), a classic traditional Chinese medicine formula, is used for pulmonary inflammatory diseases, but its immunometabolic mechanism remains unclear.

AIM OF THE STUDY: To evaluate the protective efficacy of DXFD against lipopolysaccharide (LPS)-induced ALI and to determine whether it acts through the HIF-1Ξ±/glycolysis/histone H3K18 lactylation (H3K18la) axis to regulate macrophage polarization.

MATERIALS & METHODS: DXFD constituents were characterized by UPLC-LTQ-Orbitrap-MS/MS, followed by network pharmacology, molecular docking, and molecular dynamics (MD) simulations. Lung transcriptomics and metabolomics were performed in ALI mice. Efficacy and mechanisms were assessed in LPS-challenged mice and RAW264.7 macrophages using histopathology, ELISA, qRT-PCR, Western blotting, and immunofluorescence. HIF-1Ξ± overexpression was used for validation.

RESULTS: DXFD dose-dependently alleviated lung injury and reduced pro-inflammatory cytokines in vivo, and suppressed M1 polarization in vivo and in LPS-stimulated macrophages. Multi-omics indicated activation of HIF-1Ξ±-associated inflammatory and glycolytic programs in ALI, which were normalized by DXFD. DXFD decreased glycolytic enzyme expression and reduced histone H3K18 lactylation (H3K18la); these effects were partially reversed by HIF-1Ξ± overexpression. Molecular docking and dynamics suggested stable binding of baicalin to HIF-1Ξ±.

CONCLUSIONS: DXFD mitigates ALI by dampening HIF-1Ξ±-dependent glycolysis and H3K18la, thereby restraining M1-driven inflammatory amplification.

PMID:41903585 | DOI:10.1016/j.jep.2026.121591

Received β€” 11 March 2026 ⏭

Accelerating Robotic Reinforcement Learning with Agent Guidance

βœ‡cs.AI, q-bio.NC updates on arXiv.org
By: Haojun Chen Β· Zili Zou Β· Chengdong Ma Β· Yaoxiang Pu Β· Haotong Zhang Β· Yuanpei Chen Β· Yaodong Yang
10 March 2026 at 12:00
arXiv:2602.11978v2 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) offers a powerful paradigm for autonomous robots to master generalist manipulation skills through trial-and-error. However, its real-world application is stifled by low sample efficiency. Recent Human-in-the-Loop (HIL) methods accelerate training by using human corrections, yet this approach faces a scalability barrier. Reliance on human supervisors imposes a 1:1 supervision ratio that limits scalability, suffers from operator fatigue over extended sessions, and introduces high variance due to inconsistent human proficiency. We present Agent-guided Policy Search (AGPS), a framework that automates the training pipeline by replacing human supervisors with a multimodal agent. Our key insight is that the agent can be viewed as a semantic world model, injecting intrinsic value priors to structure physical exploration. By using tools, the agent provides precise guidance via corrective waypoints and spatial constraints for exploration pruning. We validate our approach on three tasks, ranging from precision insertion to deformable object manipulation. Results demonstrate that AGPS outperforms HIL methods in sample efficiency. This automates the supervision pipeline, unlocking the path to labor-free and scalable robot learning. Project website: https://agps-rl.github.io/agps/.
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