Exploring Health Misinformation Detection with Multi-Agent Debate

By: Chih-Han Chen · Chen-Han Tsai · Yu-Shao Peng

12 December 2025 at 13:00

arXiv:2512.09935v1 Announce Type: new Abstract: Fact-checking health-related claims has become increasingly critical as misinformation proliferates online. Effective verification requires both the retrieval of high-quality evidence and rigorous reasoning processes. In this paper, we propose a two-stage framework for health misinformation detection: Agreement Score Prediction followed by Multi-Agent Debate. In the first stage, we employ large language models (LLMs) to independently evaluate retrieved articles and compute an aggregated agreement score that reflects the overall evidence stance. When this score indicates insufficient consensus-falling below a predefined threshold-the system proceeds to a second stage. Multiple agents engage in structured debate to synthesize conflicting evidence and generate well-reasoned verdicts with explicit justifications. Experimental results demonstrate that our two-stage approach achieves superior performance compared to baseline methods, highlighting the value of combining automated scoring with collaborative reasoning for complex verification tasks.

Mind the Gap! Pathways Towards Unifying AI Safety and Ethics Research

cs.AI, q-bio.NC updates on arXiv.org

By: Dani Roytburg · Beck Miller

12 December 2025 at 13:00

arXiv:2512.10058v1 Announce Type: new Abstract: While much research in artificial intelligence (AI) has focused on scaling capabilities, the accelerating pace of development makes countervailing work on producing harmless, "aligned" systems increasingly urgent. Yet research on alignment has diverged along two largely parallel tracks: safety--centered on scaled intelligence, deceptive or scheming behaviors, and existential risk--and ethics--focused on present harms, the reproduction of social bias, and flaws in production pipelines. Although both communities warn of insufficient investment in alignment, they disagree on what alignment means or ought to mean. As a result, their efforts have evolved in relative isolation, shaped by distinct methodologies, institutional homes, and disciplinary genealogies. We present a large-scale, quantitative study showing the structural split between AI safety and AI ethics. Using a bibliometric and co-authorship network analysis of 6,442 papers from twelve major ML and NLP conferences (2020-2025), we find that over 80% of collaborations occur within either the safety or ethics communities, and cross-field connectivity is highly concentrated: roughly 5% of papers account for more than 85% of bridging links. Removing a small number of these brokers sharply increases segregation, indicating that cross-disciplinary exchange depends on a handful of actors rather than broad, distributed collaboration. These results show that the safety-ethics divide is not only conceptual but institutional, with implications for research agendas, policy, and venues. We argue that integrating technical safety work with normative ethics--via shared benchmarks, cross-institutional venues, and mixed-method methodologies--is essential for building AI systems that are both robust and just.

Are ultrasensitive ctDNA assays ready for clinical use in early-stage NSCLC?

Cell

By: Sam Khan · Janice J.N. Li · Natasha B. Leighl

11 December 2025 at 08:00

Disease recurrence in early-stage non-small cell lung cancer (NSCLC) remains a persistent clinical challenge, underscoring the need for better prognostic biomarkers. In this preview, we highlight the clinical implications of ultrasensitive ctDNA monitoring in lung cancer risk modeling reported by Black et al. in this issue of Cell.

Macrophage-targeted immunocytokine leverages myeloid, T, and NK cell synergy for cancer immunotherapy

Cell

By: Michelle von Locquenghien · Pascale Zwicky · Ken Xie · Diego Adhemar Jaitin · Fadi Sheban · Adam Yalin · Florian Uhlitz · Chamutal Gur · Reut Sharet Eshed · Eyal David · Kfir Mazuz · Caroline Jennings Marin · Ankita Sankar · Devin Mediratta · Roberto Avellino · Assaf Weiner · Ido Amit

19 November 2025 at 08:00

MiTEs are myeloid-targeted immunocytokine prodrugs that block TREM2+ tumor-associated macrophages while activating cytotoxic lymphocytes via TME-specific IL-2 activity, eliciting strong anti-tumor efficacy in preclinical models with minimal systemic toxicity.

Pancreatic Cancer Organoids: Modeling Disease and Guiding Therapy

(Multiomics OR Omics) AND (Pancreatic)

By: Franck Morceau · Victoria El-Khoury · Kyeong Lee · Marc Jean Berna · Yong-Jun Kwon

11 December 2025 at 19:00

Cancers (Basel). 2025 Nov 30;17(23):3850. doi: 10.3390/cancers17233850.

ABSTRACT

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. An unmet need exists for reliable biomarkers and in vitro models capable of predicting patient drug response to advance personalized medicine. Traditional models fail to represent the tumor's complexity and the role of the stromal environment in chemoresistance. Patient-derived organoids (PDOs) overcome these limitations, enabling multi-omics profiling and reliable drug testing for functional precision medicine. This review provides a comprehensive overview of PDAC PDO research, emphasizing the following major areas: (i) the genetic and phenotypic fidelity of PDOs, (ii) their predictive value for drug response and chemoresistance, (iii) the integration of the extracellular matrix and tumor microenvironment (TME) components, and (iv) emerging technologies. Studies confirm that PDOs faithfully represent the primary tumor's specific genetic features and retain intratumoral heterogeneity. PDO-based platforms have demonstrated a strong correlation between in vitro drug sensitivity and in vivo efficacy in xenograft models, validating their utility for identifying drug candidates, repurposing existing drugs, and determining effective combinations. Efforts are ongoing to integrate crucial TME components, like cancer-associated fibroblasts, using innovative co-culture platforms such as fused PDOs and InterOMaX, to better model desmoplasia and chemoresistance mechanisms. Furthermore, PDO technology is converging with microphysiological systems and artificial intelligence tools to facilitate high-throughput drug screening and dynamic, real-time monitoring of therapeutic effects. The integration of PDOs into biobanks and advanced screening platforms holds the potential to accelerate drug discovery and improve therapeutic outcomes for PDAC patients, if challenges related to protocol standardization and regulatory acceptance are addressed.

PMID:41375051 | PMC:PMC12690986 | DOI:10.3390/cancers17233850

Integrative network pharmacology, transcriptomics, and microbiomics elucidate the therapeutic mechanism of <em>Polygala tenuifolia</em> Willd water extract in chronic obstructive pulmonary disease

Omics In Lung

By: Yiming An · Xiao Yu · Chao Wang · Xin Yu · Jingtong Zheng · Hongqiang Lin

11 December 2025 at 19:00

Front Microbiol. 2025 Nov 25;16:1703853. doi: 10.3389/fmicb.2025.1703853. eCollection 2025.

ABSTRACT

BACKGROUND: Polygala tenuifolia Willd (PT) is a plant with both medicinal and edible values. Traditionally, it has been used for sedation, enhancing cognition, resolving phlegm, and relieving cough. However, its protective effects and mechanisms against chronic obstructive pulmonary disease (COPD) remain unclear.

AIM OF THE STUDY: This study aims to observe the protective effects of the water extract of Polygala tenuifolia Willd (WEPT) on COPD, and to preliminarily elucidate its potential therapeutic mechanisms by integrating network pharmacology, molecular docking, multi-omics analysis, and molecular experiments.

METHODS AND MATERIALS: HPLC quantified WEPT constituents. COPD mice models established via chronic smoke exposure underwent WEPT treatment, and the therapeutic effect was evaluated by lung function test, histopathology and cytokine profiling. Integrated multi-omics analyses (network pharmacology, transcriptomics, microbiomics) identified bioactive compounds, therapeutic targets, pathway regulations, and microbiota dynamics. Molecular docking validated compound-target interactions, while immunohistochemical/fluorescence assays confirmed key protein expression in lung tissues.

RESULTS: WEPT administration effectively reduced inflammatory cytokine levels in COPD mice, improved lung function, and alleviated histopathological damage like alveolar structural injury and airway inflammation. Network pharmacology and transcriptomic analyses identified Norhyoscyamine and Onjixanthone I as key active components, targeting PIK3CA and AKT1 via PI3K-AKT pathway regulation. Microbiome analysis showed WEPT restored gut microbiota balance. Molecular docking confirmed strong binding of bioactive compounds to core targets, while immunostaining assays demonstrated WEPT suppressed p-PI3K and p-AKT protein expression.

CONCLUSION: WEPT may exert its intervention effects on COPD through a multi-target and multi-level comprehensive regulatory mechanism.

PMID:41377050 | PMC:PMC12685879 | DOI:10.3389/fmicb.2025.1703853