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DC vaccine loaded with Bacteroides fragilis elicits functional cross-reactivity and enhances anti-PD-1 immunotherapy

Liu and colleagues develop a dendritic cell vaccine loaded with the gut commensals Bacteroides fragilis (DC-Bf), which triggers CD8+ T cell-dependent antitumor immune responses via MHC-I-mediated cross-presentation and interleukin-12 secretion, and enhances the efficacy of PD-1 antibody by improving the immunosuppressive tumor microenvironment and diversifying the T cell receptor repertoire.

PRXL2B facilitates the progression of hepatocellular carcinoma and the therapeutic efficacy of oncolytic adenovirus H101 through the PI3K/AKT/PD-L1 axis

Biosci Trends. 2026 May 21. doi: 10.5582/bst.2026.01000. Online ahead of print.

ABSTRACT

Oncolytic adenovirus H101 has shown antitumor activity in hepatocellular carcinoma (HCC), but the molecular determinants of treatment response remain unclear. In this study, a Hepa1-6 subcutaneous tumor model was established in C57BL/6 mice and treated with intratumoral H101, followed by integrated transcriptomic and proteomic analyses to identify candidate genes associated with H101 response. PRXL2B was selected for further investigation using public multi-omics datasets, tissue microarray-based immunohistochemistry, in vitro functional assays, mechanistic analyses, and in vivo validation experiments. Integrated multi-omics analyses identified PRXL2B as a candidate gene downregulated after H101 treatment. Public datasets and tissue-based validation further showed that PRXL2B was upregulated in HCC tissues. In MHCC97H and HCCLM3 cells, PRXL2B knockdown inhibited proliferation, migration, and invasion, promoted apoptosis and cell-cycle arrest, and enhanced the antitumor effect of H101. Mechanistically, PRXL2B silencing reduced AKT phosphorylation and PD-L1 expression. In vivo, PRXL2B knockdown suppressed tumor growth, and the combination of PRXL2B knockdown and H101 produced the strongest antitumor effect. These findings indicate that PRXL2B promotes malignant phenotypes in HCC and may modulate H101 efficacy through the PI3K/AKT/PD-L1 axis. Targeting PRXL2B may therefore represent a potential strategy to enhance the therapeutic efficacy of oncolytic virus therapy in HCC.

PMID:42161529 | DOI:10.5582/bst.2026.01000

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

Social Media Intervention Based on the Information-Motivation-Behavioral Skills Model Promotes HIV Testing and Reduces High-Risk Behaviors Among Men Who Have Sex With Men in Resource-Limited Settings in China: Randomized Controlled Trial

Background: Social media intervention may enhance HIV prevention among men who have sex with men, but the effect of this intervention in resource-limited settings remains unclear. Objective: This randomized controlled trial evaluated whether a social media intervention grounded in the information-motivation-behavioral skills (IMB) model could be beneficial for HIV prevention among men who have sex with men in resource-limited settings. Methods: Participants were recruited in Nanning, China, between April 2023 and April 2024. Eligible participants were randomly assigned to either the social media intervention group or the routine HIV prevention services control group. Participants in the intervention group received a 3-month social media intervention, which included completing video-based tasks. Baseline surveys were conducted, followed by follow-up surveys every 3 months, for a total of 2 follow-ups. Outcomes included HIV testing uptake, high-risk behavior, AIDS-related knowledge, safe sex self-efficacy, and attitude. Results: A total of 180 eligible men who have sex with men were enrolled (90 per group). Follow-up rates were 97.8% (88/90) and 95.5% (86/90) for the intervention and control groups, respectively. At the follow-ups, the intervention group demonstrated significantly higher uptake of HIV testing, a lower proportion of participants reporting high-risk sexual behaviors, and higher condom use self-efficacy compared to the control group (all

Two-step clinical care pathway to predict MASLD-related advanced fibrosis and long-term outcomes in type 2 diabetes

Gut. 2026 Feb 9;75(3):576-587. doi: 10.1136/gutjnl-2025-337506.

ABSTRACT

BACKGROUND: Current guidelines recommend a two-step approach for risk stratification of metabolic dysfunction-associated steatotic liver disease (MASLD), starting with Fibrosis-4 index (FIB-4) followed by liver stiffness measurement (LSM) using vibration-controlled transient elastography (VCTE).

OBJECTIVE: To evaluate this approach for predicting advanced fibrosis and liver-related events (LREs) in patients with type 2 diabetes (T2D).

DESIGN: A prospective liver biopsy cohort of T2D patients with histologically confirmed MASLD from seven centres in China was used to assess diagnostic performance for advanced fibrosis. The international VCTE-Prognosis cohort, including T2D patients with MASLD who underwent VCTE at 16 centres in the USA, Europe and Asia, with longitudinal follow-up, was used to assess LREs, defined as hepatic decompensation or hepatocellular carcinoma.

RESULTS: 4781 participants were included. In the liver biopsy cohort (n=352; 22.2% with advanced fibrosis), applying LSM thresholds of <8 kPa and >12 kPa after FIB-4 classified patients into 63.4% low-risk, 9.4% intermediate-risk and 27.3% high-risk, with a correct classification rate of 71%. In the VCTE-Prognosis cohort (n=4429; median follow-up 51.3 (IQR 27.4-70.7) months), 140 (3.2%) patients developed LREs (110 (2.5%) with hepatic decompensation and 59 (1.3%) with hepatocellular carcinoma). The two-step approach classified 72.6%, 6.8% and 20.6% of patients into low-risk, intermediate-risk and high-risk groups, with corresponding 5-year cumulative LRE incidences of 0.7%, 0.9% and 11.8%. Refining classification of intermediate FIB-4 patients using LSM <10 kPa (low-risk) and >15 kPa (high-risk) reduced the intermediate-risk group to 5.6% while preserving predictive accuracy.

CONCLUSION: The non-invasive two-step approach of FIB-4 followed by LSM effectively stratifies MASLD-related advanced fibrosis and LREs risk in T2D. Applying LSM cut-offs of 10 and 15 kPa further optimises risk stratification for future LREs.

PMID:41911049 | DOI:10.1136/gutjnl-2025-337506

3DCity-LLM: Empowering Multi-modality Large Language Models for 3D City-scale Perception and Understanding

arXiv:2603.23447v1 Announce Type: cross Abstract: While multi-modality large language models excel in object-centric or indoor scenarios, scaling them to 3D city-scale environments remains a formidable challenge. To bridge this gap, we propose 3DCity-LLM, a unified framework designed for 3D city-scale vision-language perception and understanding. 3DCity-LLM employs a coarse-to-fine feature encoding strategy comprising three parallel branches for target object, inter-object relationship, and global scene. To facilitate large-scale training, we introduce 3DCity-LLM-1.2M dataset that comprises approximately 1.2 million high-quality samples across seven representative task categories, ranging from fine-grained object analysis to multi-faceted scene planning. This strictly quality-controlled dataset integrates explicit 3D numerical information and diverse user-oriented simulations, enriching the question-answering diversity and realism of urban scenarios. Furthermore, we apply a multi-dimensional protocol based on text-similarity metrics and LLM-based semantic assessment to ensure faithful and comprehensive evaluations for all methods. Extensive experiments on two benchmarks demonstrate that 3DCity-LLM significantly outperforms existing state-of-the-art methods, offering a promising and meaningful direction for advancing spatial reasoning and urban intelligence. The source code and dataset are available at https://github.com/SYSU-3DSTAILab/3D-City-LLM.

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

RoboPARA: Dual-Arm Robot Planning with Parallel Allocation and Recomposition Across Tasks

arXiv:2506.06683v4 Announce Type: replace-cross Abstract: Dual-arm robots play a crucial role in improving efficiency and flexibility in complex multitasking scenarios. While existing methods have achieved promising results in task planning, they often fail to fully optimize task parallelism, limiting the potential of dual-arm collaboration. To address this issue, we propose RoboPARA, a novel large language model (LLM)-driven framework for dual-arm task parallelism planning. RoboPARA employs a two-stage process: (1) Dependency Graph-based Planning Candidates Generation, which constructs directed acyclic graphs (DAGs) to model task dependencies and eliminate redundancy, and (2) Graph Re-Traversal-based Dual-Arm Parallel Planning, which optimizes DAG traversal to maximize parallelism while maintaining task coherence. In addition, we introduce the Cross-Scenario Dual-Arm Parallel Task dataset (X-DAPT dataset), the first dataset specifically designed to evaluate dual-arm task parallelism across diverse scenarios and difficulty levels. Extensive experiments demonstrate that RoboPARA significantly outperforms existing planning methods, achieving higher efficiency and reliability, particularly in complex task combinations. Our code is publicly available at https://github.com/AiDuanshiying/RoboPARA.

MeanCache: From Instantaneous to Average Velocity for Accelerating Flow Matching Inference

arXiv:2601.19961v3 Announce Type: replace-cross Abstract: We present MeanCache, a training-free caching framework for efficient Flow Matching inference. Existing caching methods reduce redundant computation but typically rely on instantaneous velocity information (e.g., feature caching), which often leads to severe trajectory deviations and error accumulation under high acceleration ratios. MeanCache introduces an average-velocity perspective: by leveraging cached Jacobian--vector products (JVP) to construct interval average velocities from instantaneous velocities, it effectively mitigates local error accumulation. To further improve cache timing and JVP reuse stability, we develop a trajectory-stability scheduling strategy as a practical tool, employing a Peak-Suppressed Shortest Path under budget constraints to determine the schedule. Experiments on FLUX.1, Qwen-Image, and HunyuanVideo demonstrate that MeanCache achieves 4.12X and 4.56X and 3.59X acceleration, respectively, while consistently outperforming state-of-the-art caching baselines in generation quality. We believe this simple yet effective approach provides a new perspective for Flow Matching inference and will inspire further exploration of stability-driven acceleration in commercial-scale generative models.

What happens when reviewers receive AI feedback in their reviews?

arXiv:2602.13817v1 Announce Type: cross Abstract: AI is reshaping academic research, yet its role in peer review remains polarising and contentious. Advocates see its potential to reduce reviewer burden and improve quality, while critics warn of risks to fairness, accountability, and trust. At ICLR 2025, an official AI feedback tool was deployed to provide reviewers with post-review suggestions. We studied this deployment through surveys and interviews, investigating how reviewers engaged with the tool and perceived its usability and impact. Our findings surface both opportunities and tensions when AI augments in peer review. This work contributes the first empirical evidence of such an AI tool in a live review process, documenting how reviewers respond to AI-generated feedback in a high-stakes review context. We further offer design implications for AI-assisted reviewing that aim to enhance quality while safeguarding human expertise, agency, and responsibility.
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