Normal view
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Cell
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Spatial biology reveals altered macrophage states in immunosuppressed non-melanoma skin cancer
Spatial multi-omics reveals macrophage states that constrain adaptive immunity in immunosuppressed non-melanoma skin cancer.
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cs.AI, q-bio.NC updates on arXiv.org
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AsyncFlow: An Asynchronous Streaming RL Framework for Efficient LLM Post-Training
arXiv:2507.01663v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has become a pivotal technology in the post-training phase of large language models (LLMs). Traditional task-collocated RL frameworks suffer from significant scalability bottlenecks, while task-separated RL frameworks face challenges in managing complex dataflows and resolving resource idling. Furthermore, most existing frameworks are tightly coupled with LLM training or inference engines, making them difficul
AsyncFlow: An Asynchronous Streaming RL Framework for Efficient LLM Post-Training
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Nature Biomedical Engineering
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Engineering inflammation-responsive proteins through nitric oxide-caged amino acids
Nature Biomedical Engineering, Published online: 31 August 2026; doi:10.1038/s41551-026-01782-9A protein engineering strategy enables nitric oxide-triggered reactivation of proteins using genetically encoded caged amino acids, allowing inflammation-localized control of protein activity, viral gene delivery and biosensing in vivo.
Engineering inflammation-responsive proteins through nitric oxide-caged amino acids
Nature Biomedical Engineering, Published online: 31 August 2026; doi:10.1038/s41551-026-01782-9
A protein engineering strategy enables nitric oxide-triggered reactivation of proteins using genetically encoded caged amino acids, allowing inflammation-localized control of protein activity, viral gene delivery and biosensing in vivo.-
Omics In Lung
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Biologic Therapy for Severe Asthma: Biomarker-Guided Precision Treatment and Immunopathological Mechanisms
J Vis Exp. 2026 Sep 8;(235). doi: 10.3791/71404.ABSTRACTSevere asthma is a difficult-to-control airway disease with pronounced heterogeneity in both clinical manifestations and underlying inflammatory mechanisms. This review examines the mechanisms, biomarkers, and biologic therapies of severe asthma, with a focus on biomarker-guided treatment selection and emerging precision strategies for type 2-high (T2-high) and type 2-low (T2-low) disease. The development of biologic therapies has changed t
Biologic Therapy for Severe Asthma: Biomarker-Guided Precision Treatment and Immunopathological Mechanisms
J Vis Exp. 2026 Sep 8;(235). doi: 10.3791/71404.
ABSTRACT
Severe asthma is a difficult-to-control airway disease with pronounced heterogeneity in both clinical manifestations and underlying inflammatory mechanisms. This review examines the mechanisms, biomarkers, and biologic therapies of severe asthma, with a focus on biomarker-guided treatment selection and emerging precision strategies for type 2-high (T2-high) and type 2-low (T2-low) disease. The development of biologic therapies has changed the treatment paradigm, particularly for patients with T2-high inflammation. By targeting immunoglobulin E (IgE), interleukin-5 (IL-5), interleukin-4 receptor alpha (IL-4Rα), and thymic stromal lymphopoietin (TSLP)-related pathways, these agents can decrease exacerbations, improve lung function and symptom control, and enhance quality of life. Biomarkers, including blood eosinophils, fractional exhaled nitric oxide (FeNO), total IgE, and sputum eosinophils, have been incorporated into clinical decision-making to support patient stratification. Emerging markers such as periostin, epithelial alarmins, gene-expression patterns, microRNAs, and multi-omics signatures are under investigation for more accurate phenotyping and response prediction. Despite these advances, current biomarkers do not always provide sufficient predictive accuracy, targeted options for T2-low asthma remain limited, biologics are costly, and long-term outcome data remain incomplete. Overall, integrating biomarker findings with clinical phenotype, comorbidities, and treatment history remains central to individualized biologic selection.
PMID:42714006 | DOI:10.3791/71404
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(Multiomics OR Omics) AND (Lung OR gastric OR Hepatocellular)
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Biologic Therapy for Severe Asthma: Biomarker-Guided Precision Treatment and Immunopathological Mechanisms
J Vis Exp. 2026 Sep 8;(235). doi: 10.3791/71404.ABSTRACTSevere asthma is a difficult-to-control airway disease with pronounced heterogeneity in both clinical manifestations and underlying inflammatory mechanisms. This review examines the mechanisms, biomarkers, and biologic therapies of severe asthma, with a focus on biomarker-guided treatment selection and emerging precision strategies for type 2-high (T2-high) and type 2-low (T2-low) disease. The development of biologic therapies has changed t
Biologic Therapy for Severe Asthma: Biomarker-Guided Precision Treatment and Immunopathological Mechanisms
J Vis Exp. 2026 Sep 8;(235). doi: 10.3791/71404.
ABSTRACT
Severe asthma is a difficult-to-control airway disease with pronounced heterogeneity in both clinical manifestations and underlying inflammatory mechanisms. This review examines the mechanisms, biomarkers, and biologic therapies of severe asthma, with a focus on biomarker-guided treatment selection and emerging precision strategies for type 2-high (T2-high) and type 2-low (T2-low) disease. The development of biologic therapies has changed the treatment paradigm, particularly for patients with T2-high inflammation. By targeting immunoglobulin E (IgE), interleukin-5 (IL-5), interleukin-4 receptor alpha (IL-4Rα), and thymic stromal lymphopoietin (TSLP)-related pathways, these agents can decrease exacerbations, improve lung function and symptom control, and enhance quality of life. Biomarkers, including blood eosinophils, fractional exhaled nitric oxide (FeNO), total IgE, and sputum eosinophils, have been incorporated into clinical decision-making to support patient stratification. Emerging markers such as periostin, epithelial alarmins, gene-expression patterns, microRNAs, and multi-omics signatures are under investigation for more accurate phenotyping and response prediction. Despite these advances, current biomarkers do not always provide sufficient predictive accuracy, targeted options for T2-low asthma remain limited, biologics are costly, and long-term outcome data remain incomplete. Overall, integrating biomarker findings with clinical phenotype, comorbidities, and treatment history remains central to individualized biologic selection.
PMID:42714006 | DOI:10.3791/71404
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cs.AI, q-bio.NC updates on arXiv.org
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Fundamental Limitation in Explaining AI
arXiv:2605.24727v1 Announce Type: new Abstract: While large-scale models such as LLMs and diffusion models have achieved practical success, public institutions have emphasized the importance of explainability in AI. Existing methods for explaining AI, however, are not designed to provide completely faithful explanations of the behavior of large-scale AI systems. Although a completely faithful and interpretable explanation of the behavior of an AI system might be useful for AI governance, it has
Fundamental Limitation in Explaining AI
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cs.AI, q-bio.NC updates on arXiv.org
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D3S2: Diffusion-Guided Dataset Distillation for Semantic Segmentation
arXiv:2605.25022v1 Announce Type: cross Abstract: Dataset distillation (DD) aims to compress large-scale datasets into compact synthetic sets while preserving training efficacy. However, existing studies mainly focus on image classification, leaving dense prediction tasks such as semantic segmentation largely underexplored. In this work, we identify three key challenges for segmentation DD: (i) long-tailed class imbalance, (ii) the need for strict pixel-wise alignment between images and dense l
D3S2: Diffusion-Guided Dataset Distillation for Semantic Segmentation
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Nature - Issue - nature.com science feeds
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A pathogen lncRNA secreted into rice sequesters a host miRNA for virulence
Nature, Published online: 20 May 2026; doi:10.1038/s41586-026-10572-xA fungal long non-coding RNA from Magnaporthe oryzae translocates into rice cells to sequester a host microRNA that normally represses PKR1, a negative immunity regulator, thereby facilitating infection and revealing a widespread RNA-based pathogen–host interaction mechanism.
A pathogen lncRNA secreted into rice sequesters a host miRNA for virulence
Nature, Published online: 20 May 2026; doi:10.1038/s41586-026-10572-x
A fungal long non-coding RNA from Magnaporthe oryzae translocates into rice cells to sequester a host microRNA that normally represses PKR1, a negative immunity regulator, thereby facilitating infection and revealing a widespread RNA-based pathogen–host interaction mechanism.-
Nature - Issue - nature.com science feeds
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Neural representation of action symbols in primate frontal cortex
Nature, Published online: 20 May 2026; doi:10.1038/s41586-026-10297-xA drawing-like task designed to study compositional generalization identifies a specific neural population in the ventral premotor cortex in primates that encodes action symbols.
Neural representation of action symbols in primate frontal cortex
Nature, Published online: 20 May 2026; doi:10.1038/s41586-026-10297-x
A drawing-like task designed to study compositional generalization identifies a specific neural population in the ventral premotor cortex in primates that encodes action symbols.-
Omics in Gastric
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Characterization of dysbiosis patterns in gut microbiota of digestive system cancers: an umbrella review
Front Microbiol. 2026 Apr 28;17:1782471. doi: 10.3389/fmicb.2026.1782471. eCollection 2026.ABSTRACTDigestive system cancers (DSCs) represent a substantial global health burden. In recent years, the role of gut microbiota in the DSCs has garnered considerable attention, but its change pattern during tumor progression and the specific mechanisms are still not fully understood. We conducted a comprehensive systematic review to characterize patterns of gut microbiota dysbiosis across different DSC t
Characterization of dysbiosis patterns in gut microbiota of digestive system cancers: an umbrella review
Front Microbiol. 2026 Apr 28;17:1782471. doi: 10.3389/fmicb.2026.1782471. eCollection 2026.
ABSTRACT
Digestive system cancers (DSCs) represent a substantial global health burden. In recent years, the role of gut microbiota in the DSCs has garnered considerable attention, but its change pattern during tumor progression and the specific mechanisms are still not fully understood. We conducted a comprehensive systematic review to characterize patterns of gut microbiota dysbiosis across different DSC types and assess their clinical significance. We systematically searched four English and three Chinese databases up to January 2025 to identify systematic reviews focused on the dynamic characteristics of the gut microbiota during gastrointestinal tumorigenesis. Microbiota biodiversity and taxonomic composition were extracted to identify specific signatures associated with DSCs. The ROBIS tool was used to evaluate the methodological quality of the included studies. Ultimately, 59 studies involving six distinct DSC types were included. Data synthesis and comparison revealed distinct microbiota profiles across DSCs. At the phylum level, Bacillota was decreased in esophageal cancer (EC) and pancreatic ductal adenocarcinoma (PDAC), Pseudomonadota was augmented in EC but exhibited divergent trajectories in colorectal cancer (CRC) and PDAC. Genus-level analyses revealed Veillonella enrichment in EC and PDAC, and Fusobacterium outgrowth in EC, gastric cancer (GC) and CRC. Parvimonas and Streptococcus showed a concordant ascending trend in GC and CRC. Prevotella was overrepresented in EC and GC. This synthesis delineates a qualitative landscape of gut microbiota imbalances associated with various DSCs, highlighting the potential for these microbial shifts to serve as markers for early detection and targeted therapy. Multiomics integration and prospective cohort studies should be prioritized to accelerate clinical translation.
PMID:42131199 | PMC:PMC13161176 | DOI:10.3389/fmicb.2026.1782471
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Omics In Lung
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Distinctive respiratory toxicity induced by hypoxanthine metabolic disorder from polystyrene microplastics and nanoplastics at environmentally relevant doses: multi-omics insights and experimental validation
Environ Int. 2026 Mar 28;210:110212. doi: 10.1016/j.envint.2026.110212. Online ahead of print.ABSTRACTMicroplastics (MPs) and nanoplastics (NPs) are pervasive environmental contaminants, raising concerns about their potential to cause inflammation, oxidative stress, and lung injury through respiratory toxicity. Due to their smaller size, larger surface area, and greater reactivity, NPs may pose a greater risk than MPs, yet size-dependent toxicity mechanisms remain unclear. This study investigate
Distinctive respiratory toxicity induced by hypoxanthine metabolic disorder from polystyrene microplastics and nanoplastics at environmentally relevant doses: multi-omics insights and experimental validation
Environ Int. 2026 Mar 28;210:110212. doi: 10.1016/j.envint.2026.110212. Online ahead of print.
ABSTRACT
Microplastics (MPs) and nanoplastics (NPs) are pervasive environmental contaminants, raising concerns about their potential to cause inflammation, oxidative stress, and lung injury through respiratory toxicity. Due to their smaller size, larger surface area, and greater reactivity, NPs may pose a greater risk than MPs, yet size-dependent toxicity mechanisms remain unclear. This study investigates the distinct early molecular initiating events and toxicological effects of 1 μm polystyrene MPs (PS-MPs) and 20 nm polystyrene NPs (PS-NPs). Based on the internal exposure dose estimated from Py-GC/MS analysis, in vitro exposure concentrations were set at 0, 62.5, 125, 250, 500, and 1000 μg/mL. Multi-omics sequencing and integrative analysis identify specific proteomic and metabolomic alterations. Molecular dynamics simulations and co-immunoprecipitation assays elucidate binding interactions between PS-NPs-induced proteins and metabolic enzymes. In vitro and in vivo experiments reveal a greater accumulation of PS-NPs through endocytosis compared to PS-MPs; while pronounced histopathological damage with inflammatory response in mice lungs were only induced by PS-NPs, rather than PS-MPs. Compared to control group, PS-MPs partly caused proteomic or metabolomic perturbations, while PS-NPs induced significant differential expression of more extensive proteins and metabolites. PS-NPs exposure specifically upregulates insulin-like growth factor 2 receptor (IGF2R) expression and reduces Hypoxanthine levels when compared with PS-MPs. IGF2R directly interacts with Hypoxanthine-guanine phosphoribosyl transferase (HPRT), a key enzyme in Hypoxanthine metabolism, causing its disruption. This study provides important insights into the comparative toxic effects between PS-NPs with PS-MPs, especially the unique toxicological mechanisms of PS-NPs, thereby advancing the understanding of airborne plastic pollutant risks and supporting future regulatory assessments.
PMID:41921402 | DOI:10.1016/j.envint.2026.110212
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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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Cell Death Discovery nature.com science feeds
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O-GlcNAcylation of UGDH: emerging insights into immunometabolic regulation and therapeutic implications
Cell Death Discovery, Published online: 31 March 2026; doi:10.1038/s41420-026-03086-yO-GlcNAcylation of UGDH: emerging insights into immunometabolic regulation and therapeutic implications
O-GlcNAcylation of UGDH: emerging insights into immunometabolic regulation and therapeutic implications
Cell Death Discovery, Published online: 31 March 2026; doi:10.1038/s41420-026-03086-y
O-GlcNAcylation of UGDH: emerging insights into immunometabolic regulation and therapeutic implications-
npj Digital Medicine
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A unified deep learning framework for cross-platform harmonization of multi-tracer PET quantification in neurodegenerative disease
npj Digital Medicine, Published online: 30 March 2026; doi:10.1038/s41746-026-02570-0A unified deep learning framework for cross-platform harmonization of multi-tracer PET quantification in neurodegenerative disease
A unified deep learning framework for cross-platform harmonization of multi-tracer PET quantification in neurodegenerative disease
npj Digital Medicine, Published online: 30 March 2026; doi:10.1038/s41746-026-02570-0
A unified deep learning framework for cross-platform harmonization of multi-tracer PET quantification in neurodegenerative disease-
cs.AI, q-bio.NC updates on arXiv.org
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Leveraging LLMs and Social Media to Understand User Perception of Smartphone-Based Earthquake Early Warnings
arXiv:2603.23322v1 Announce Type: cross Abstract: Android's Earthquake Alert (AEA) system provided timely early warnings to millions during the Mw 6.2 Marmara Ereglisi, T\"urkiye earthquake on April 23, 2025. This event, the largest in the region in 25 years, served as a critical real-world test for smartphone-based Earthquake Early Warning (EEW) systems. The AEA system successfully delivered alerts to users with high precision, offering over a minute of warning before the strongest shaking rea
Leveraging LLMs and Social Media to Understand User Perception of Smartphone-Based Earthquake Early Warnings
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Cell
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Tuning the sensitivity of mechanosensory receptors through histidine scanning
Histidine scanning represents a broadly applicable technique for the identification of critical interaction sites within TCRs and other mechanosensory receptors to enhance receptor signaling strength and augment therapeutic efficacy via the catch bond mechanism.
Tuning the sensitivity of mechanosensory receptors through histidine scanning
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cs.AI, q-bio.NC updates on arXiv.org
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AriadneMem: Threading the Maze of Lifelong Memory for LLM Agents
arXiv:2603.03290v1 Announce Type: cross Abstract: Long-horizon LLM agents require memory systems that remain accurate under fixed context budgets. However, existing systems struggle with two persistent challenges in long-term dialogue: (i) \textbf{disconnected evidence}, where multi-hop answers require linking facts distributed across time, and (ii) \textbf{state updates}, where evolving information (e.g., schedule changes) creates conflicts with older static logs. We propose AriadneMem, a stru
AriadneMem: Threading the Maze of Lifelong Memory for LLM Agents
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cs.AI, q-bio.NC updates on arXiv.org
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DICArt: Advancing Category-level Articulated Object Pose Estimation in Discrete State-Spaces
arXiv:2602.19565v1 Announce Type: cross Abstract: Articulated object pose estimation is a core task in embodied AI. Existing methods typically regress poses in a continuous space, but often struggle with 1) navigating a large, complex search space and 2) failing to incorporate intrinsic kinematic constraints. In this work, we introduce DICArt (DIsCrete Diffusion for Articulation Pose Estimation), a novel framework that formulates pose estimation as a conditional discrete diffusion process. Inst
DICArt: Advancing Category-level Articulated Object Pose Estimation in Discrete State-Spaces
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cs.AI, q-bio.NC updates on arXiv.org
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Feature Recalibration Based Olfactory-Visual Multimodal Model for Fine-Grained Rice Deterioration Detection
arXiv:2602.14408v1 Announce Type: cross Abstract: Multimodal methods are widely used in rice deterioration detection, which exhibit limited capability in representing and extracting fine-grained abnormal features. Moreover, these methods rely on devices, such as hyperspectral cameras and mass spectrometers, increasing detection costs and prolonging data acquisition time. To address these issues, we propose a feature recalibration based olfactory-visual multimodal model for fine-grained rice det