Normal view
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Molecular Therapy
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Treatment with quercetin inhibits SARS-CoV-2 N protein-induced acute kidney injury by blocking Smad3-dependent G1 cell-cycle arrest
(Molecular Therapy 31, 344–361; February 2023)
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npj Digital Medicine
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Evaluating AI in leukocyte classification: performance of the AI system against 15 morphology experts
npj Digital Medicine, Published online: 11 April 2026; doi:10.1038/s41746-026-02601-wEvaluating AI in leukocyte classification: performance of the AI system against 15 morphology experts
Evaluating AI in leukocyte classification: performance of the AI system against 15 morphology experts
npj Digital Medicine, Published online: 11 April 2026; doi:10.1038/s41746-026-02601-w
Evaluating AI in leukocyte classification: performance of the AI system against 15 morphology experts-
Omics in Hepatocellular
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UBTF-HSP90A-MIF stress circuit drives lenvatinib resistance and immune exclusion in hepatocellular carcinoma
J Adv Res. 2026 Apr 5:S2090-1232(26)00280-8. doi: 10.1016/j.jare.2026.04.002. Online ahead of print.ABSTRACTINTRODUCTION: The clinical benefit of combining lenvatinib with PD-1 blockade in HCC is frequently constrained by adaptive resistance and the development of an immune-cold tumor microenvironment.OBJECTIVES: This study aimed to elucidate the molecular mechanisms underlying adaptive resistance and immune exclusion during lenvatinib-PD-1 therapy in HCC, with a particular focus on a UBTF/HSP90
UBTF-HSP90A-MIF stress circuit drives lenvatinib resistance and immune exclusion in hepatocellular carcinoma
J Adv Res. 2026 Apr 5:S2090-1232(26)00280-8. doi: 10.1016/j.jare.2026.04.002. Online ahead of print.
ABSTRACT
INTRODUCTION: The clinical benefit of combining lenvatinib with PD-1 blockade in HCC is frequently constrained by adaptive resistance and the development of an immune-cold tumor microenvironment.
OBJECTIVES: This study aimed to elucidate the molecular mechanisms underlying adaptive resistance and immune exclusion during lenvatinib-PD-1 therapy in HCC, with a particular focus on a UBTF/HSP90A/MIF regulatory circuit. We examined whether genetic or pharmacologic targeting of macrophage migration inhibitory factor (MIF) could restore lenvatinib sensitivity, remodel the tumor immune microenvironment, and serve as a predictive biomarker in clinical cohorts.
METHODS: Paired lenvatinib-sensitive and -resistant HCC models were interrogated using integrated multi-omic and functional approaches, including RNA sequencing, promoter pull-down assays, ChIP, luciferase reporter assays, PLA, and flow cytometry. Key findings were validated in patient-derived organoids and xenografts, as well as in an immunocompetent hydrodynamic HCC mouse model. Clinical relevance was evaluated in independent cohorts treated with lenvatinib plus anti-PD-1 therapy.
RESULTS: UBTF directly bound to and transcriptionally activated the HSP90A promoter, resulting in increased HSP90A expression and stabilization of MIF. MIF signaling through CD74 co-activated the PI3K-AKT and MAPK pathways, sustaining tumor cell proliferation under lenvatinib pressure. Single-cell RNA sequencing and multiplex immunohistochemistry revealed macrophage enrichment and CD8+ T-cell exclusion in resistant tumors. Genetic ablation of Mif (Alb-Cre; Mifflox/flox) or pharmacologic inhibition with 4-IPP (4-Iodo-6-phenylpyrimidine) restored lenvatinib sensitivity, reprogrammed the tumor immune microenvironment, and, when combined with PD-1 blockade, achieved superior tumor control and prolonged survival. In clinical datasets, low pretreatment MIF expression was associated with improved responses to lenvatinib plus PD-1 therapy.
CONCLUSIONS: These findings define a UBTF/HSP90A/MIF axis linking proteostasis and cytokine signaling to immune-metabolic dysfunction and lenvatinib resistance in HCC. MIF emerges as both a mechanistic driver and a predictive biomarker, supporting prospective evaluation of therapeutic strategies combining lenvatinib-PD-1 with MIF- or HSP90A-targeted interventions to personalize TKI-ICI therapy.
PMID:41946392 | DOI:10.1016/j.jare.2026.04.002
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cs.AI, q-bio.NC updates on arXiv.org
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MSR-HuBERT: Self-supervised Pre-training for Adaptation to Multiple Sampling Rates
arXiv:2603.23048v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has advanced speech processing. However, existing speech SSL methods typically assume a single sampling rate and struggle with mixed-rate data due to temporal resolution mismatch. To address this limitation, we propose MSRHuBERT, a multi-sampling-rate adaptive pre-training method. Building on HuBERT, we replace its single-rate downsampling CNN with a multi-sampling-rate adaptive downsampling CNN that maps raw wavef
MSR-HuBERT: Self-supervised Pre-training for Adaptation to Multiple Sampling Rates
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Omics in Hepatocellular
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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
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cs.AI, q-bio.NC updates on arXiv.org
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Breaking Data Efficiency Dilemma: A Federated and Augmented Learning Framework For Alzheimer's Disease Detection via Speech
arXiv:2602.14655v1 Announce Type: cross Abstract: Early diagnosis of Alzheimer's Disease (AD) is crucial for delaying its progression. While AI-based speech detection is non-invasive and cost-effective, it faces a critical data efficiency dilemma due to medical data scarcity and privacy barriers. Therefore, we propose FAL-AD, a novel framework that synergistically integrates federated learning with data augmentation to systematically optimize data efficiency. Our approach delivers three key bre
Breaking Data Efficiency Dilemma: A Federated and Augmented Learning Framework For Alzheimer's Disease Detection via Speech
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cs.AI, q-bio.NC updates on arXiv.org
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OmniVideo-R1: Reinforcing Audio-visual Reasoning with Query Intention and Modality Attention
arXiv:2602.05847v2 Announce Type: replace Abstract: While humans perceive the world through diverse modalities that operate synergistically to support a holistic understanding of their surroundings, existing omnivideo models still face substantial challenges on audio-visual understanding tasks. In this paper, we propose OmniVideo-R1, a novel reinforced framework that improves mixed-modality reasoning. OmniVideo-R1 empowers models to "think with omnimodal cues" by two key strategies: (1) query-i