Normal view
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cs.AI, q-bio.NC updates on arXiv.org
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Enhancing behavioral nudges with large language model-based iterative personalization: A field experiment on electricity and hot-water conservation
arXiv:2604.03881v1 Announce Type: cross Abstract: Nudging is widely used to promote behavioral change, but its effectiveness is often limited when recipients must repeatedly translate feedback into workable next steps under changing circumstances. Large language models (LLMs) may help reduce part of this cognitive work by generating personalized guidance and updating it iteratively across intervention rounds. We developed an LLM agent for iterative personalization and tested it in a three-arm r
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(Multiomics OR Omics) AND (Lung OR gastric OR Hepatocellular)
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Protective Effects of the Ethyl Acetate Fraction from Madeng'ai on Lipopolysaccharide-Induced Acute Lung Injury in Mice: Insights from Integrated Multi-Omics Analysis
J Ethnopharmacol. 2026 Apr 4:121650. doi: 10.1016/j.jep.2026.121650. Online ahead of print.ABSTRACTETHNOPHARMACOLOGICAL RELEVANCE: Madeng'ai (MDA) is a traditional medicinal plant of the Dong ethnic group. Its roots have been widely used in folk medicine for clearing heat and removing toxins, alleviating swelling and relieving pain, dispersing blood stasis and arresting bleeding, as well as promoting wound healing. It is taxonomically classified as a variety of Potentilla freyniana Bornm.AIM OF
Protective Effects of the Ethyl Acetate Fraction from Madeng'ai on Lipopolysaccharide-Induced Acute Lung Injury in Mice: Insights from Integrated Multi-Omics Analysis
J Ethnopharmacol. 2026 Apr 4:121650. doi: 10.1016/j.jep.2026.121650. Online ahead of print.
ABSTRACT
ETHNOPHARMACOLOGICAL RELEVANCE: Madeng'ai (MDA) is a traditional medicinal plant of the Dong ethnic group. Its roots have been widely used in folk medicine for clearing heat and removing toxins, alleviating swelling and relieving pain, dispersing blood stasis and arresting bleeding, as well as promoting wound healing. It is taxonomically classified as a variety of Potentilla freyniana Bornm.
AIM OF THE STUDY: Acute lung injury (ALI) is a life-threatening pulmonary disorder associated with high mortality, underscoring the urgent need to explore novel therapeutic strategies. This study aimed to evaluate the protective effects of the ethyl acetate fraction of MDA (MEA) against LPS-induced ALI in mice and to investigate its underlying mechanisms.
MATERIALS AND METHODS: LC-MS/MS was employed to tentatively identify the bioactive components of MEA. A mouse model of ALI was established by LPS induction. The protective effects of MEA were evaluated through assessments of lung histopathology, inflammatory cytokine levels, and oxidative stress markers. The underlying mechanisms were systematically investigated by integrating transcriptomics, metabolomics, network pharmacology, molecular docking, and Western blotting.
RESULTS: MEA significantly attenuated LPS-induced pulmonary pathological lesions, pulmonary edema, and excessive inflammatory responses in ALI mice. Comprehensive bioinformatics analyses predicted potential mechanisms involving oxidative stress and the regulation of metabolic pathways. Experimental validation via Western blotting confirmed that MEA inhibited TLR4-mediated inflammatory signaling and modulated the PI3K/AKT pathway, thereby exerting multi-pathway protective effects against ALI.
CONCLUSIONS: Collectively, this study confirms that MEA, as a traditional herbal extract, holds potential as an adjuvant therapeutic agent for ALI, providing experimental evidence for the modernization and development of ethnic medicines.
PMID:41941987 | DOI:10.1016/j.jep.2026.121650
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(Multiomics OR Omics) AND (Lung OR gastric OR Hepatocellular)
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Multi-omics integration and machine learning reveal gut-immune signatures in idiopathic pulmonary fibrosis: insights from bulk RNA-seq, single-cell profiles, spatial transcriptomics, and experimental validation
Front Immunol. 2026 Mar 19;17:1730289. doi: 10.3389/fimmu.2026.1730289. eCollection 2026.ABSTRACTBACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal lung disease with limited treatment options and a poor prognosis. Recent studies suggest a critical role for the gut-immune-lung axis in IPF, yet the underlying molecular mechanisms remain unclear.METHODS: The current study performed in silico multi-omics integration of publicly available datasets, including bulk RNA-seq, single-
Multi-omics integration and machine learning reveal gut-immune signatures in idiopathic pulmonary fibrosis: insights from bulk RNA-seq, single-cell profiles, spatial transcriptomics, and experimental validation
Front Immunol. 2026 Mar 19;17:1730289. doi: 10.3389/fimmu.2026.1730289. eCollection 2026.
ABSTRACT
BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal lung disease with limited treatment options and a poor prognosis. Recent studies suggest a critical role for the gut-immune-lung axis in IPF, yet the underlying molecular mechanisms remain unclear.
METHODS: The current study performed in silico multi-omics integration of publicly available datasets, including bulk RNA-seq, single-cell and spatial transcriptomics, as well as peripheral blood multi-omics data to uncover key molecular signatures in IPF. Furthermore, machine learning techniques were utilized to identify core genes, whereas functional analyses and Mendelian randomization were conducted to evaluate the causal relationships among gut microbiota, immune cells, and IPF. Additionally, experimental validation using qPCR and ELISA assays was conducted in vitro, in vivo, and in patient plasma to confirm the expression patterns of key genes.
RESULTS: Across integrated public bulk, single-cell, spatial, and blood multi-omics, CXCL13, IL33, TLR4, and IGF1 were identified as core IPF genes consistently linked to immune infiltration and fibrotic remodeling. Deconvolution, scRNA-seq, and spatial mapping localized their dysregulation to fibroblasts and immune compartments (notably B-cell, macrophage, and mast-cell axes), highlighting fibroblast-immune crosstalk in fibrotic foci. A four-gene model robustly distinguished IPF from controls across cohorts. Mendelian randomization supported a gut-immune-lung axis, indicating causal effects of specific gut taxa on IPF risk via immune phenotypes. qPCR/ELISA in TGF-β1-stimulated fibroblasts, bleomycin mouse lungs, and patient plasma corroborated upregulation of IL33, CXCL13, IGF1 and downregulation of TLR4. Drug-signature reversal nominated cucurbitacin I and temsirolimus; molecular docking was performed as a preliminary in silico, computer-simulation-based assessment of potential ligand-protein interactions between these compounds and the four core targets.
CONCLUSION: This study provides new insights into the importance of gut-immune-lung axis in IPF and identifies CXCL13, IL33, TLR4, and IGF1 as diagnostic signatures and therapeutic targets. By integrating public multi-omics resources with experimental validation, our findings offer a foundation for future diagnostic and treatment strategies aimed at modulating the gut microbiota and immune system in IPF.
PMID:41939867 | PMC:PMC13043422 | DOI:10.3389/fimmu.2026.1730289
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Omics In Lung
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Protective Effects of the Ethyl Acetate Fraction from Madeng'ai on Lipopolysaccharide-Induced Acute Lung Injury in Mice: Insights from Integrated Multi-Omics Analysis
J Ethnopharmacol. 2026 Apr 4:121650. doi: 10.1016/j.jep.2026.121650. Online ahead of print.ABSTRACTETHNOPHARMACOLOGICAL RELEVANCE: Madeng'ai (MDA) is a traditional medicinal plant of the Dong ethnic group. Its roots have been widely used in folk medicine for clearing heat and removing toxins, alleviating swelling and relieving pain, dispersing blood stasis and arresting bleeding, as well as promoting wound healing. It is taxonomically classified as a variety of Potentilla freyniana Bornm.AIM OF
Protective Effects of the Ethyl Acetate Fraction from Madeng'ai on Lipopolysaccharide-Induced Acute Lung Injury in Mice: Insights from Integrated Multi-Omics Analysis
J Ethnopharmacol. 2026 Apr 4:121650. doi: 10.1016/j.jep.2026.121650. Online ahead of print.
ABSTRACT
ETHNOPHARMACOLOGICAL RELEVANCE: Madeng'ai (MDA) is a traditional medicinal plant of the Dong ethnic group. Its roots have been widely used in folk medicine for clearing heat and removing toxins, alleviating swelling and relieving pain, dispersing blood stasis and arresting bleeding, as well as promoting wound healing. It is taxonomically classified as a variety of Potentilla freyniana Bornm.
AIM OF THE STUDY: Acute lung injury (ALI) is a life-threatening pulmonary disorder associated with high mortality, underscoring the urgent need to explore novel therapeutic strategies. This study aimed to evaluate the protective effects of the ethyl acetate fraction of MDA (MEA) against LPS-induced ALI in mice and to investigate its underlying mechanisms.
MATERIALS AND METHODS: LC-MS/MS was employed to tentatively identify the bioactive components of MEA. A mouse model of ALI was established by LPS induction. The protective effects of MEA were evaluated through assessments of lung histopathology, inflammatory cytokine levels, and oxidative stress markers. The underlying mechanisms were systematically investigated by integrating transcriptomics, metabolomics, network pharmacology, molecular docking, and Western blotting.
RESULTS: MEA significantly attenuated LPS-induced pulmonary pathological lesions, pulmonary edema, and excessive inflammatory responses in ALI mice. Comprehensive bioinformatics analyses predicted potential mechanisms involving oxidative stress and the regulation of metabolic pathways. Experimental validation via Western blotting confirmed that MEA inhibited TLR4-mediated inflammatory signaling and modulated the PI3K/AKT pathway, thereby exerting multi-pathway protective effects against ALI.
CONCLUSIONS: Collectively, this study confirms that MEA, as a traditional herbal extract, holds potential as an adjuvant therapeutic agent for ALI, providing experimental evidence for the modernization and development of ethnic medicines.
PMID:41941987 | DOI:10.1016/j.jep.2026.121650
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Omics In Lung
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Multi-omics integration and machine learning reveal gut-immune signatures in idiopathic pulmonary fibrosis: insights from bulk RNA-seq, single-cell profiles, spatial transcriptomics, and experimental validation
Front Immunol. 2026 Mar 19;17:1730289. doi: 10.3389/fimmu.2026.1730289. eCollection 2026.ABSTRACTBACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal lung disease with limited treatment options and a poor prognosis. Recent studies suggest a critical role for the gut-immune-lung axis in IPF, yet the underlying molecular mechanisms remain unclear.METHODS: The current study performed in silico multi-omics integration of publicly available datasets, including bulk RNA-seq, single-
Multi-omics integration and machine learning reveal gut-immune signatures in idiopathic pulmonary fibrosis: insights from bulk RNA-seq, single-cell profiles, spatial transcriptomics, and experimental validation
Front Immunol. 2026 Mar 19;17:1730289. doi: 10.3389/fimmu.2026.1730289. eCollection 2026.
ABSTRACT
BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal lung disease with limited treatment options and a poor prognosis. Recent studies suggest a critical role for the gut-immune-lung axis in IPF, yet the underlying molecular mechanisms remain unclear.
METHODS: The current study performed in silico multi-omics integration of publicly available datasets, including bulk RNA-seq, single-cell and spatial transcriptomics, as well as peripheral blood multi-omics data to uncover key molecular signatures in IPF. Furthermore, machine learning techniques were utilized to identify core genes, whereas functional analyses and Mendelian randomization were conducted to evaluate the causal relationships among gut microbiota, immune cells, and IPF. Additionally, experimental validation using qPCR and ELISA assays was conducted in vitro, in vivo, and in patient plasma to confirm the expression patterns of key genes.
RESULTS: Across integrated public bulk, single-cell, spatial, and blood multi-omics, CXCL13, IL33, TLR4, and IGF1 were identified as core IPF genes consistently linked to immune infiltration and fibrotic remodeling. Deconvolution, scRNA-seq, and spatial mapping localized their dysregulation to fibroblasts and immune compartments (notably B-cell, macrophage, and mast-cell axes), highlighting fibroblast-immune crosstalk in fibrotic foci. A four-gene model robustly distinguished IPF from controls across cohorts. Mendelian randomization supported a gut-immune-lung axis, indicating causal effects of specific gut taxa on IPF risk via immune phenotypes. qPCR/ELISA in TGF-β1-stimulated fibroblasts, bleomycin mouse lungs, and patient plasma corroborated upregulation of IL33, CXCL13, IGF1 and downregulation of TLR4. Drug-signature reversal nominated cucurbitacin I and temsirolimus; molecular docking was performed as a preliminary in silico, computer-simulation-based assessment of potential ligand-protein interactions between these compounds and the four core targets.
CONCLUSION: This study provides new insights into the importance of gut-immune-lung axis in IPF and identifies CXCL13, IL33, TLR4, and IGF1 as diagnostic signatures and therapeutic targets. By integrating public multi-omics resources with experimental validation, our findings offer a foundation for future diagnostic and treatment strategies aimed at modulating the gut microbiota and immune system in IPF.
PMID:41939867 | PMC:PMC13043422 | DOI:10.3389/fimmu.2026.1730289
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cs.AI, q-bio.NC updates on arXiv.org
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A Multi-Agent Human-LLM Collaborative Framework for Closed-Loop Scientific Literature Summarization
arXiv:2604.01452v1 Announce Type: new Abstract: Scientific discovery is slowed by fragmented literature that requires excessive human effort to gather, analyze, and understand. AI tools, including autonomous summarization and question answering, have been developed to aid in understanding scientific literature. However, these tools lack the structured, multi-step approach necessary for extracting deep insights from scientific literature. Large Language Models (LLMs) offer new possibilities for
A Multi-Agent Human-LLM Collaborative Framework for Closed-Loop Scientific Literature Summarization
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cs.AI, q-bio.NC updates on arXiv.org
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Reducing Hallucinations in LLM-based Scientific Literature Analysis Using Peer Context Outlier Detection
arXiv:2604.01461v1 Announce Type: new Abstract: Reducing hallucinations in Large Language Models (LLMs) is essential for improving the accuracy of data extraction from large text corpora. Current methods, like prompt engineering and chain-of-thought prompting, focus on individual documents but fail to consider relationships across a corpus. This paper introduces Peer Context Outlier Detection (P-COD), a novel approach that uses the relationships between documents to improve extraction accuracy.
Reducing Hallucinations in LLM-based Scientific Literature Analysis Using Peer Context Outlier Detection
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cs.AI, q-bio.NC updates on arXiv.org
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Lifting Unlabeled Internet-level Data for 3D Scene Understanding
arXiv:2604.01907v1 Announce Type: cross Abstract: Annotated 3D scene data is scarce and expensive to acquire, while abundant unlabeled videos are readily available on the internet. In this paper, we demonstrate that carefully designed data engines can leverage web-curated, unlabeled videos to automatically generate training data, to facilitate end-to-end models in 3D scene understanding alongside human-annotated datasets. We identify and analyze bottlenecks in automated data generation, reveali
Lifting Unlabeled Internet-level Data for 3D Scene Understanding
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npj Digital Medicine
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Multidimensional evaluation of large language models in radiology report readability
npj Digital Medicine, Published online: 01 April 2026; doi:10.1038/s41746-026-02589-3Multidimensional evaluation of large language models in radiology report readability
Multidimensional evaluation of large language models in radiology report readability
npj Digital Medicine, Published online: 01 April 2026; doi:10.1038/s41746-026-02589-3
Multidimensional evaluation of large language models in radiology report readability-
Cell
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Ferritin aggregation cell engager for CAR T avidity engineering against refractory leukemias
Li et al. developed a ferritin aggregation cell engager that helps CAR T cells better recognize and attack leukemia cells without re-engineering the CAR itself. This versatile platform overcomes antigen modulation and enables combination with chemotherapy.
Ferritin aggregation cell engager for CAR T avidity engineering against refractory leukemias
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Oncogene - Issue - nature.com science feeds
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Targeting FTO shows therapeutic potential in esophageal squamous cell carcinoma by modulating microRNA biogenesis
Oncogene, Published online: 01 April 2026; doi:10.1038/s41388-026-03754-4Targeting FTO shows therapeutic potential in esophageal squamous cell carcinoma by modulating microRNA biogenesis
Targeting FTO shows therapeutic potential in esophageal squamous cell carcinoma by modulating microRNA biogenesis
Oncogene, Published online: 01 April 2026; doi:10.1038/s41388-026-03754-4
Targeting FTO shows therapeutic potential in esophageal squamous cell carcinoma by modulating microRNA biogenesis-
Omics in Gastric
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Targeting sialic acid metabolism: a therapeutic strategy against gastric cancer driven by WZ35
Cell Oncol (Dordr). 2026 Mar 23;49(2):60. doi: 10.1007/s13402-026-01194-6.ABSTRACTGlycolytic reprogramming is closely associated with the occurrence and progression of gastric cancer. Specifically, the energy derived from glucose metabolism and the cellular proteins by its intermediate products influence gastric cancer development. However, as an important branch of glucose metabolism, sialic acid metabolism and its mediated sialylation modifications remain insufficiently studied in gastric canc
Targeting sialic acid metabolism: a therapeutic strategy against gastric cancer driven by WZ35
Cell Oncol (Dordr). 2026 Mar 23;49(2):60. doi: 10.1007/s13402-026-01194-6.
ABSTRACT
Glycolytic reprogramming is closely associated with the occurrence and progression of gastric cancer. Specifically, the energy derived from glucose metabolism and the cellular proteins by its intermediate products influence gastric cancer development. However, as an important branch of glucose metabolism, sialic acid metabolism and its mediated sialylation modifications remain insufficiently studied in gastric cancer, and their specific relationship with malignant tumor progression requires further exploration. This study employed a multi‑omics approach, integrating metabolomics, single‑cell RNA sequencing, and bulk RNA sequencing analyses, to investigate the metabolic landscape of gastric cancer and its associated alterations. The results indicated that sialic acid is a characteristic metabolite in malignant gastric cancer tissues. It modulates biological functions such as immune response, proliferative activity, and metabolic remodeling within gastric cancer tissues by influencing sialylation modifications. Furthermore, we identified the drug WZ35, which can inhibit the malignant proliferation of gastric cancer by targeting both sialic acid metabolism and sialylated protein modifications. We put forward a conjecture that the metabolism and modification of sialic acid promote the malignant development of gastric cancer, and we discovered that the drug WZ35 has an inhibitory effect on the sialic acid metabolism of gastric cancer.
GRAPHICAL ABSTRACT:
PMID:41870836 | PMC:PMC13009457 | DOI:10.1007/s13402-026-01194-6
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(Multiomics OR Omics) AND (Lung OR gastric OR Hepatocellular)
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RFC4 drives temozolomide resistance in glioblastoma by activating STK38-BECN1-dependent autophagy
Nat Commun. 2026 Mar 23. doi: 10.1038/s41467-026-70798-1. Online ahead of print.ABSTRACTGlioblastoma (GBM) remains a lethal brain tumor due to therapy resistance. While autophagy contributes to temozolomide (TMZ) resistance, its regulation is incompletely understood. This study investigates the role of replication factor RFC4, which is associated with poor prognosis and TMZ resistance in GBM. Multi-omics analyses and molecular experiments reveal that TMZ-induced chromatin accessibility enables t
RFC4 drives temozolomide resistance in glioblastoma by activating STK38-BECN1-dependent autophagy
Nat Commun. 2026 Mar 23. doi: 10.1038/s41467-026-70798-1. Online ahead of print.
ABSTRACT
Glioblastoma (GBM) remains a lethal brain tumor due to therapy resistance. While autophagy contributes to temozolomide (TMZ) resistance, its regulation is incompletely understood. This study investigates the role of replication factor RFC4, which is associated with poor prognosis and TMZ resistance in GBM. Multi-omics analyses and molecular experiments reveal that TMZ-induced chromatin accessibility enables transcription factor YY1 to bind the RFC4 promoter and upregulate its expression. RFC4, in turn, stabilizes the kinase STK38, which is essential for autophagosome formation. The RFC4-STK38 interaction facilitates BECN1 recruitment, thereby activating autophagy. Phosphorylation of STK38 at T444 stabilizes this complex, whereas a phospho-deficient mutant impairs autophagy. In vivo, RFC4 overexpression confers TMZ resistance, reversible by autophagy inhibition. Thus, our findings identify the RFC4-STK38-BECN1 axis as a mechanism underlying TMZ resistance and a potential target for precision therapy in GBM.
PMID:41872171 | DOI:10.1038/s41467-026-70798-1
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(Multiomics OR Omics) AND (Lung OR gastric OR Hepatocellular)
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Targeting sialic acid metabolism: a therapeutic strategy against gastric cancer driven by WZ35
Cell Oncol (Dordr). 2026 Mar 23;49(2):60. doi: 10.1007/s13402-026-01194-6.NO ABSTRACTPMID:41870836 | DOI:10.1007/s13402-026-01194-6
Targeting sialic acid metabolism: a therapeutic strategy against gastric cancer driven by WZ35
Cell Oncol (Dordr). 2026 Mar 23;49(2):60. doi: 10.1007/s13402-026-01194-6.
NO ABSTRACT
PMID:41870836 | DOI:10.1007/s13402-026-01194-6
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Oncogene - Issue - nature.com science feeds
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<i>KRAS</i>-extrachromosomal DNA drives intratumoral heterogeneity in gastric cancer
Oncogene, Published online: 05 March 2026; doi:10.1038/s41388-026-03713-zKRAS-extrachromosomal DNA drives intratumoral heterogeneity in gastric cancer
<i>KRAS</i>-extrachromosomal DNA drives intratumoral heterogeneity in gastric cancer
Oncogene, Published online: 05 March 2026; doi:10.1038/s41388-026-03713-z
KRAS-extrachromosomal DNA drives intratumoral heterogeneity in gastric cancer-
cs.AI, q-bio.NC updates on arXiv.org
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PROSPECT: Unified Streaming Vision-Language Navigation via Semantic--Spatial Fusion and Latent Predictive Representation
arXiv:2603.03739v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have advanced zero-shot end-to-end Vision-Language Navigation (VLN), yet robust navigation requires not only semantic understanding but also predictive modeling of environment dynamics and spatial structure. We propose PROSPECT, a unified streaming navigation agent that couples a streaming Vision-Language-Action (VLA) policy with latent predictive representation learning. PROSPECT uses CUT3R as a streamin