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Received — 27 May 2026 ⏭

Context-CoT: Enhancing Context Learning via High-Quality Reasoning Synthesis

✇cs.AI, q-bio.NC updates on arXiv.org
By: Hongbo Jin · Mingnan Zhu · Jingqi Tian · Xu Jiang · Zhongjing Du · Haoran Tang · Siyi Xie · Qiaoman Zhang · Jiayu Ding
26 May 2026 at 12:00
arXiv:2605.25354v1 Announce Type: new Abstract: While LLMs excel at reasoning over prompts using static pretrained knowledge, they struggle significantly with context learning-the ability to dynamically extract, internalize, and apply new knowledge from complex, task-specific contexts. Recent evaluations on the CL-Bench reveal a critical capability gap: frontier models solve only 17.2% of context-dependent tasks on average.

AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration

✇cs.AI, q-bio.NC updates on arXiv.org
By: Jiaqi Liu · Shi Qiu · Mairui Li · Bingzhou Li · Haonian Ji · Siwei Han · Xinyu Ye · Peng Xia · Zihan Dong · Meng Chen · Congyu Zhang · Letian Zhang · Guiming Chen · Haoqin Tu · Xinyu Yang · Lu Feng · Xujiang Zhao · Haifeng Chen · Jiawei Zhou · Xiao Wang · Weitong Zhang · Hongtu Zhu · Yun Li · Jieru Mei · Hongliang Fei · Jiaheng Zhang · Linjie Li · Linjun Zhang · Yuyin Zhou · Sheng Wang · Caiming Xiong · James Zou · Zeyu Zheng · Cihang Xie · Mingyu Ding · Huaxiu Yao
26 May 2026 at 12:00
arXiv:2605.20025v2 Announce Type: replace Abstract: Automating scientific discovery requires more than generating papers from ideas. Real research is iterative: hypotheses are challenged from multiple perspectives, experiments fail and inform the next attempt, and lessons accumulate across cycles. Existing autonomous research systems often model this process as a linear pipeline: they rely on single-agent reasoning, stop when execution fails, and do not carry experience across runs. We present AutoResearchClaw, a multi-agent autonomous research pipeline built on five mechanisms: structured multi-agent debate for hypothesis generation and result analysis, a self-healing executor with a \textsc{Pivot}/\textsc{Refine} decision loop that transforms failures into information, verifiable result reporting that prevents fabricated numbers and hallucinated citations, human-in-the-loop collaboration with seven intervention modes spanning full autonomy to step-by-step oversight, and cross-run evolution that converts past mistakes into future safeguards. On ARC-Bench, a 25-topic experiment-stage benchmark, AutoResearchClaw outperforms AI Scientist v2 by 54.7%. A human-in-the-loop ablation across seven intervention modes reveals that precise, targeted collaboration at high-leverage decision points consistently outperforms both full autonomy and exhaustive step-by-step oversight. We position AutoResearchClaw as a research amplifier that augments rather than replaces human scientific judgment. Code is available at https://github.com/aiming-lab/AutoResearchClaw.

hUCMSC-exosomes attenuate acute lung injury by inhibiting ferroptosis in pulmonary microvascular endothelial cells through ribosomal protein RPS11 upregulation

✇Omics In Lung
By: Anyun Ding · Mingou Yan · Yunong Li · Zhongyun Bi · Jingchun Song · Lin Zhao · Renyu Ding
23 May 2026 at 18:00

J Nanobiotechnology. 2026 May 22. doi: 10.1186/s12951-026-04565-1. Online ahead of print.

ABSTRACT

BACKGROUND: Human umbilical cord mesenchymal stem cell-derived exosomes (hUCMSC-Exos) are a promising treatment for acute lung injury (ALI)/acute respiratory distress syndrome (ARDS), but traditional delivery methods have limitations. Therefore, this study presents a noninvasive therapeutic approach for ALI/ARDS, offering new mechanistic insights and identifying potential therapeutic targets.

RESULTS: We established a nebulized LPS-induced ALI model that was characterized by diffuse lung injury and high homogeneity. Following inhalation, hUCMSC-Exos were observed to be internalized by pulmonary microvascular endothelial cells. Analysis revealed that hUCMSC-Exos alleviated ALI by reducing the severity of histological damage, pulmonary oedema, lung inflammation and ferroptosis. Additionally, hUCMSC-Exos improved the mitochondrial function of human pulmonary microvascular endothelial cells (HPMECs) via the transfer of mitochondrial components. Subsequent proteomic sequencing of mitochondria isolated from HPMECs receiving different treatments revealed the significant differential expression of ribosomal proteins among the groups. The most significantly upregulated protein, RPS11, was identified as a key mediator; its knockdown blocked the ability of hUCMSC-Exos to suppress ferroptosis and restore mitochondrial function in HPMECs. Mechanistically, hUCMSC-Exos exert their effects by enhancing mitochondria-encoded protein translation.

CONCLUSIONS: We report a mechanism whereby hUCMSC-Exos upregulate RPS11 to promote mitochondria-encoded protein translation, rescuing mitochondrial function, inhibiting ferroptosis in HPMECs, and ultimately alleviating ALI. Validated across multiple models and supported by multi-omics analyses, our findings collectively establish nebulized hUCMSC-Exos as a promising cell-free therapy targeting mitochondrial homeostasis in HPMECs for the treatment of ALI.

PMID:42174606 | DOI:10.1186/s12951-026-04565-1

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