Normal view
-
Molecular Therapy
-
Dysregulated proline metabolism contributes to retinal fibrosis in neovascular AMD: Therapeutic potential of prolyl-4-hydroxylase inhibition
Subretinal fibrosis causes irreversible vision loss in neovascular age-related macular degeneration (AMD). This study shows that proline metabolism, particularly P4HA1-mediated proline hydroxylation, is activated in JR5558 mice and human AMD tissues. Diethyl pythiDC reduced collagen turnover and fibrovascular lesion expansion, with potential added benefit when combined with aflibercept.
-
cs.AI, q-bio.NC updates on arXiv.org
-
KernelGenBench: Can LLMs and Agents Write Efficient Kernels Across Operator Sources and Hardware Platforms?
arXiv:2607.27231v3 Announce Type: replace Abstract: Modern AI systems depend on specialized accelerator kernels, whose development is complicated by increasingly diverse operators and hardware. LLMs and agentic systems promise to automate this work, but existing evaluations do not show whether their performance transfers across operator sources and hardware platforms, or what such transfer costs. We present KernelGenBench, the first unified multi-source and multi-chip infrastructure for evaluat
KernelGenBench: Can LLMs and Agents Write Efficient Kernels Across Operator Sources and Hardware Platforms?
-
Omics In Lung
-
Local lactate-driven H3K18 lactylation impairs anti-influenza immunity through NRF2-dependent dendritic cell dysfunction
Cell Rep. 2026 Sep 3;45(9):117943. doi: 10.1016/j.celrep.2026.117943. Online ahead of print.ABSTRACTMetabolic alterations are increasingly recognized during influenza virus infection, but how local lactate accumulation shapes antiviral immunity remains poorly characterized. By integrating time-series targeted energy metabolomics, single-cell RNA sequencing, flow cytometry, and functional perturbation, we show that influenza virus infection preferentially increases lactate within the lung microen
Local lactate-driven H3K18 lactylation impairs anti-influenza immunity through NRF2-dependent dendritic cell dysfunction
Cell Rep. 2026 Sep 3;45(9):117943. doi: 10.1016/j.celrep.2026.117943. Online ahead of print.
ABSTRACT
Metabolic alterations are increasingly recognized during influenza virus infection, but how local lactate accumulation shapes antiviral immunity remains poorly characterized. By integrating time-series targeted energy metabolomics, single-cell RNA sequencing, flow cytometry, and functional perturbation, we show that influenza virus infection preferentially increases lactate within the lung microenvironment, where it restrains pulmonary CD8+ T cell response. Mechanistically, extracellular lactate enters dendritic cells through monocarboxylate transporter (MCT)-dependent transport and induces a tolerogenic-like state marked by impaired maturation, reduced costimulation, and diminished CD8+ T cell-priming capacity. Direct experimental evidence identifies H3K18la as a prominent lactate-responsive histone lactylation mark, while multi-omics integration links it to enhancer accessibility and NRF2 pathway activation. Functional studies further show that NRF2 promotes dendritic cell suppression by reinforcing tolerogenic programs and limiting mtROS-dependent XBP1 splicing. Together, these findings reveal a lactate-driven histone lactylation-NRF2 pathway that modulates antiviral immunity during influenza infection.
PMID:42690934 | DOI:10.1016/j.celrep.2026.117943
-
cs.AI, q-bio.NC updates on arXiv.org
-
Eureka: Intelligent Feature Engineering for Enterprise AI Cloud Resource Demand Prediction
arXiv:2605.25297v1 Announce Type: cross Abstract: Effective features are crucial for predictive model performance, but creating them often requires domain expertise, limiting scalability across applications. We define feature engineering as an agentic code generation problem: features are not static data transformations, but executable programs that can be generated, evaluated, and iteratively improved. We present Eureka, an LLM-driven framework with three stages. (1) An Expert Agent, fine-tune
Eureka: Intelligent Feature Engineering for Enterprise AI Cloud Resource Demand Prediction
-
cs.AI, q-bio.NC updates on arXiv.org
-
FactReview: Evidence-Grounded Reviews with Literature Positioning and Execution-Based Claim Verification
arXiv:2604.04074v2 Announce Type: new Abstract: Peer review in machine learning is under growing pressure from rising submission volume and limited reviewer time. Most LLM-based reviewing systems read only the manuscript and generate comments from the paper's own narrative. This makes their outputs sensitive to presentation quality and leaves them weak when the evidence needed for review lies in related work or released code. We present FactReview, an evidence-grounded reviewing system that com
FactReview: Evidence-Grounded Reviews with Literature Positioning and Execution-Based Claim Verification
-
Oncogene - Issue - nature.com science feeds
-
Deciphering functional intra-tumoral heterogeneity in BRAF<sup>V600E</sup>-driven mouse thyroid cancer reveals EMT trajectory and metabolic remodeling
Oncogene, Published online: 04 April 2026; doi:10.1038/s41388-026-03742-8Deciphering functional intra-tumoral heterogeneity in BRAFV600E-driven mouse thyroid cancer reveals EMT trajectory and metabolic remodeling
Deciphering functional intra-tumoral heterogeneity in BRAF<sup>V600E</sup>-driven mouse thyroid cancer reveals EMT trajectory and metabolic remodeling
Oncogene, Published online: 04 April 2026; doi:10.1038/s41388-026-03742-8
Deciphering functional intra-tumoral heterogeneity in BRAFV600E-driven mouse thyroid cancer reveals EMT trajectory and metabolic remodeling-
Nature Cancer
-
PRET is a few-shot system for pan-cancer recognition without example training
Nature Cancer, Published online: 03 April 2026; doi:10.1038/s43018-026-01141-2Li et al. present PRET, a few-shot system for pan-cancer detection not requiring model fine-tuning, validated it in multicenter datasets and found that it outperformed existing approaches across tasks and pathologists in lymph node metastasis detection.
PRET is a few-shot system for pan-cancer recognition without example training
Nature Cancer, Published online: 03 April 2026; doi:10.1038/s43018-026-01141-2
Li et al. present PRET, a few-shot system for pan-cancer detection not requiring model fine-tuning, validated it in multicenter datasets and found that it outperformed existing approaches across tasks and pathologists in lymph node metastasis detection.-
cs.AI, q-bio.NC updates on arXiv.org
-
Owl-AuraID 1.0: An Intelligent System for Autonomous Scientific Instrumentation and Scientific Data Analysis
arXiv:2603.29828v1 Announce Type: new Abstract: Scientific discovery increasingly depends on high-throughput characterization, yet automation is hindered by proprietary GUIs and the limited generalizability of existing API-based systems. We present Owl-AuraID, a software-hardware collaborative embodied agent system that adopts a GUI-native paradigm to operate instruments through the same interfaces as human experts. Its skill-centric framework integrates Type-1 (GUI operation) and Type-2 (data
Owl-AuraID 1.0: An Intelligent System for Autonomous Scientific Instrumentation and Scientific Data Analysis
-
MRD
-
Dynamic Targetable Extracellular Vesicle Surface Proteins Monitor Depth of Response to CAR T Therapy
Res Sq [Preprint]. 2026 Mar 18:rs.3.rs-8913641. doi: 10.21203/rs.3.rs-8913641/v1.ABSTRACTExtracellular vesicles (EVs) represent a promising liquid biopsy platform in multiple myeloma (MM). We developed an MM EV Surface Protein Assay to quantify and dynamically monitor four MM EV subpopulations defined by targetable MM surface proteins (BCMA, CD38, GPRC5D, and CD319) across 336 serial blood samples from 45 relapsed/refractory MM (RRMM) patients treated with anti-BCMA chimeric antigen receptor (CA
Dynamic Targetable Extracellular Vesicle Surface Proteins Monitor Depth of Response to CAR T Therapy
Res Sq [Preprint]. 2026 Mar 18:rs.3.rs-8913641. doi: 10.21203/rs.3.rs-8913641/v1.
ABSTRACT
Extracellular vesicles (EVs) represent a promising liquid biopsy platform in multiple myeloma (MM). We developed an MM EV Surface Protein Assay to quantify and dynamically monitor four MM EV subpopulations defined by targetable MM surface proteins (BCMA, CD38, GPRC5D, and CD319) across 336 serial blood samples from 45 relapsed/refractory MM (RRMM) patients treated with anti-BCMA chimeric antigen receptor (CAR) T-cell therapy. All four MM EV subpopulations significantly decreased in 43 patients with initial response, while BCMA+, GPRC5D+, and CD319+ MM EVs increased in 19 patients with progression, and antigen escape was detected by BCMA+ MM EVs. MM EV subpopulations differentiated minimal residual disease (MRD) status and complemented MRD for detecting early relapse before clinical progression. Notably, CD319+ MM EVs were early predictors of progression-free and overall survival in MRD-negative patients. This assay enables noninvasive monitoring of deep response, progression, and antigen escape, and stratifies survival in MRD-negative patients with RRMM.
PMID:41890853 | PMC:PMC13015583 | DOI:10.21203/rs.3.rs-8913641/v1
-
Omics in Hepatocellular
-
Hepatotoxicity Prediction and Multi-omics Reveal Mitochondrial and Lipid Metabolic Dysregulation in PM<sub>2.5</sub>-Induced Liver Fibrosis
Environ Health (Wash). 2025 Nov 14;4(3):513-521. doi: 10.1021/envhealth.5c00401. eCollection 2026 Mar 20.ABSTRACTProlonged exposure to fine particulate matter (PM2.5) has been linked to chronic liver injury and cancer. However, an alternative risk assessment method to prospective longitudinal studies of exposome-metabolome interactions for liver inflammation-associated hepatocellular carcinoma (HCC) is lacking. This study investigates the risk of long-term real-world PM2.5 exposure in hepatocarc
Hepatotoxicity Prediction and Multi-omics Reveal Mitochondrial and Lipid Metabolic Dysregulation in PM<sub>2.5</sub>-Induced Liver Fibrosis
Environ Health (Wash). 2025 Nov 14;4(3):513-521. doi: 10.1021/envhealth.5c00401. eCollection 2026 Mar 20.
ABSTRACT
Prolonged exposure to fine particulate matter (PM2.5) has been linked to chronic liver injury and cancer. However, an alternative risk assessment method to prospective longitudinal studies of exposome-metabolome interactions for liver inflammation-associated hepatocellular carcinoma (HCC) is lacking. This study investigates the risk of long-term real-world PM2.5 exposure in hepatocarcinogenesis through machine learning techniques. Shotgun mass spectrometry (MS) imaging data were acquired from mouse models across a continuum of fibrosis, cirrhosis, and HCC for training a multiclass classification model to identify "No Risk", "Cancer Risk", and "Cancer". Direct infusion-MS data from PM2.5-exposed mouse livers were analyzed to classify risk. By integrating data-driven and knowledge-based approaches, 14 disease progression biomarkers were identified for modeling. Our results suggest that chronic real-world PM2.5 exposure can induce liver fibrosis, presenting cancer risk. Incorporating metabolomics, lipidomics, and transcriptomics, we propose PM2.5 exposure induces mitochondrial dysfunction, activates AMPK signaling, and increases ceramide accumulation, potentially mediating insulin resistance that contributes to nonalcoholic fatty liver disease and HCC progression. This work represents a significant advancement in assessing hepatotoxicity of environmental toxicants by reducing reliance on traditional animal testing methods. It also underscores the potential of emerging technologies in transforming our understanding of PM2.5 exposure, paving the way for targeted interventions.
PMID:41883379 | PMC:PMC13010293 | DOI:10.1021/envhealth.5c00401
-
Nature Medicine
-
In vivo generation of anti-BCMA CAR-T cells in relapsed or refractory multiple myeloma: a phase 1 study
Nature Medicine, Published online: 25 March 2026; doi:10.1038/s41591-026-04244-6In a phase 1 trial, the in vivo generation of anti-BCMA CAR-T cells by lentiviral delivery was feasible and did not lead to dose-limiting toxicities in five patients with relapsed or refractory multiple myeloma.
In vivo generation of anti-BCMA CAR-T cells in relapsed or refractory multiple myeloma: a phase 1 study
Nature Medicine, Published online: 25 March 2026; doi:10.1038/s41591-026-04244-6
In a phase 1 trial, the in vivo generation of anti-BCMA CAR-T cells by lentiviral delivery was feasible and did not lead to dose-limiting toxicities in five patients with relapsed or refractory multiple myeloma.-
cs.AI, q-bio.NC updates on arXiv.org
-
Re2: A Consistency-ensured Dataset for Full-stage Peer Review and Multi-turn Rebuttal Discussions
arXiv:2505.07920v2 Announce Type: replace-cross Abstract: Peer review is a critical component of scientific progress in the fields like AI, but the rapid increase in submission volume has strained the reviewing system, which inevitably leads to reviewer shortages and declines review quality. Besides the growing research popularity, another key factor in this overload is the repeated resubmission of substandard manuscripts, largely due to the lack of effective tools for authors to self-evaluate
Re2: A Consistency-ensured Dataset for Full-stage Peer Review and Multi-turn Rebuttal Discussions
-
Omics in Hepatocellular
-
HKDC1-Mediated Polyamine Rewiring Drives Lenvatinib Resistance and Immune Escape in Hepatocellular Carcinoma
Clin Mol Hepatol. 2026 Mar 11. doi: 10.3350/cmh.2025.1269. Online ahead of print.ABSTRACTBACKGROUND/AIMS: Lenvatinib resistance and immune exclusion limit outcomes in HCC. We hypothesized that metabolic rewiring orchestrates resistance to lenvatinib and PD-1 blockade.METHODS: We established LS/LR HCC models and employed multi-omics (proteomics/RNA-seq), ChIP, luciferase, and RIP assays to map HKDC1 regulation. Tumor immunity was profiled by scRNA-seq, mIHC, and flow cytometry. SPD + lenvatinib e
HKDC1-Mediated Polyamine Rewiring Drives Lenvatinib Resistance and Immune Escape in Hepatocellular Carcinoma
Clin Mol Hepatol. 2026 Mar 11. doi: 10.3350/cmh.2025.1269. Online ahead of print.
ABSTRACT
BACKGROUND/AIMS: Lenvatinib resistance and immune exclusion limit outcomes in HCC. We hypothesized that metabolic rewiring orchestrates resistance to lenvatinib and PD-1 blockade.
METHODS: We established LS/LR HCC models and employed multi-omics (proteomics/RNA-seq), ChIP, luciferase, and RIP assays to map HKDC1 regulation. Tumor immunity was profiled by scRNA-seq, mIHC, and flow cytometry. SPD + lenvatinib efficacy was tested in cell lines, patient-derived organoids/xenografts. Tested therapy effect in an immunocompetent hydrodynamic HCC model with hepatocyte-specific Hkdc1 deletion; and analyzed a postoperative cohort (n = 40) treated with lenvatinib + PD-1.
RESULTS: HKDC1, upregulated in LR HCC, was transcriptionally activated by USF1 and promoted SMS-mediated polyamine rewiring. This impaired CD8⁺ T-cell metabolism, reversible by HKDC1 knockdown or spermidine (SPD). SPD synergized with lenvatinib, triggering autophagy and suppressing tumor growth in vitro and in vivo. High HKDC1 predicted poor response and survival in patients receiving lenvatinib + aPD-1.
CONCLUSIONS: A USF1/HKDC1/SMS axis couples polyamine metabolism to immune dysfunction and lenvatinib resistance. HKDC1 is a predictive biomarker and therapeutic node and support polyamine-axis modulation to sensitize HCC to lenvatinib plus PD-1 therapy.
PMID:41812646 | DOI:10.3350/cmh.2025.1269
-
cs.AI, q-bio.NC updates on arXiv.org
-
OmniVideoBench: Towards Audio-Visual Understanding Evaluation for Omni MLLMs
arXiv:2510.10689v2 Announce Type: replace Abstract: Recent advances in multimodal large language models (MLLMs) have demonstrated substantial potential in video understanding. However, existing benchmarks fail to comprehensively evaluate synergistic reasoning capabilities across audio and visual modalities, often neglecting either one of the modalities or integrating them in a logically inconsistent manner. To bridge this gap, we introduce OmniVideoBench, a large-scale and rigorously designed b
OmniVideoBench: Towards Audio-Visual Understanding Evaluation for Omni MLLMs
-
cs.AI, q-bio.NC updates on arXiv.org
-
Training Multimodal Large Reasoning Models Needs Better Thoughts: A Three-Stage Framework for Long Chain-of-Thought Synthesis and Selection
arXiv:2512.18956v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) have demonstrated remarkable performance on complex reasoning tasks through long Chain-of-Thought (CoT) reasoning. Extending these successes to multimodal reasoning remains challenging due to the increased complexity of integrating diverse input modalities and the scarcity of high-quality long CoT training data. Existing multimodal datasets and CoT synthesis methods still suffer from limited reasoning depth, modal