❌

Normal view

Tissue-specific silencing of synthetic mRNAs by de-targeting elements maps vaccination-competent tissues and allows Cas9 de-immunization

Sasso and colleagues leveraged organ-specific miRNAs by engineering synthetic mRNA vaccines containing miR target sites to generate a functional map of immunologically competent organs. This work lays the foundation for novel vaccines designed to target the most immunologically proficient organs. They subsequently applied this approach to de-immunize Cas9, rendering it immunologically masked.

Repurposing triamterene as chloride intracellular channel 1 inhibitor via ligand-based approach for glioblastoma

Currently no effective therapies are available for glioblastoma. Florio and colleagues identified, via computational screening, triamterene as a CLIC1 blocker that suppresses human glioblastoma stem cell proliferation, invasiveness, and tumor growth. Triamterene also enhances temozolomide and radio-chemotherapy efficacy, making it a repurposed therapeutic candidate for glioblastoma treatment in future clinical applications.
  • ✇STAT
  • Opinion: Autonomous AI will beat AI-assisted physicians at some medical tasks by 2030 Ezekiel J. Emanuel and Abe Baker-Butler
    Ezekiel J. Emanuel and Abe Baker-Butler have been debating the proper place for AI in medicine with American Medical Association CEO John Whyte. Now, they are taking their discussion to STAT’s First Opinion. Read Emanuel and Baker-Butler’s essay below and read Whyte’s essay here. In 1867, Joseph Lister published his research on carbolic acid and antiseptic surgical technique.  In September 1871, he was summoned to Queen Victoria, who had a rapidly growing abscess in her left armpit. Using his
     

Opinion: Autonomous AI will beat AI-assisted physicians at some medical tasks by 2030

9 September 2026 at 16:30

Ezekiel J. Emanuel and Abe Baker-Butler have been debating the proper place for AI in medicine with American Medical Association CEO John Whyte. Now, they are taking their discussion to STAT’s First Opinion. Read Emanuel and Baker-Butler’s essay below and read Whyte’s essay here.

In 1867, Joseph Lister published his research on carbolic acid and antiseptic surgical technique.  In September 1871, he was summoned to Queen Victoria, who had a rapidly growing abscess in her left armpit. Using his antiseptic surgical technique, Joseph Lister successfully drained the pus. Queen Victoria recovered without fever or other complications. The antiseptic technique quickly gained approval in the U.K. and Europe, but not among American physicians.  

Read the rest…

© Adobe

Advancing conflict research and response through satellite-derived data

Nature, Published online: 09 September 2026; doi:10.1038/s41586-026-11004-6

Integrating satellite-derived war-damage data with text-based fatality records through improvement, enrichment and fusion mitigates limitations inherent in each source, revealing complex violence dynamics beyond fatality-centric paradigms, as case studies from Ukraine and Myanmar illustrate.

Circulating Tumor DNA in Breast Cancer: A Liquid Biopsy Revolution for Non-Invasive Genomic Profiling and Clinical Decision-Making

5 September 2026 at 18:00

Breast Cancer (Auckl). 2026 Sep 3;20:11782234261485831. doi: 10.1177/11782234261485831. eCollection 2026.

ABSTRACT

Breast cancer remains the most frequently diagnosed cancer and a leading cause of cancer-related mortality among women worldwide, underscoring the need for accurate, minimally invasive biomarkers to support precision oncology. Conventional tissue biopsy remains the standard for molecular characterization but is limited by its invasiveness, inability to capture spatial and temporal tumor heterogeneity, and challenges in serial monitoring. Circulating tumor DNA (ctDNA), a tumor-derived fraction of cell-free DNA, has emerged as a promising liquid biopsy biomarker capable of providing real-time genomic information throughout disease progression. This narrative review examines recent advances in ctDNA biology, analytical technologies, clinical applications, current limitations, and future directions in breast cancer management. A structured literature search of PubMed/MEDLINE, Scopus, Embase, Web of Science, and Google Scholar identified relevant English-language publications from 2015 to 2026. Current evidence indicates that highly sensitive platforms, including digital PCR, BEAMing, and next-generation sequencing, can detect clinically actionable alterations in genes such as PIK3CA, ESR1, TP53, ERBB2, AKT1, and BRCA1/2. ctDNA has demonstrated particular utility in identifying minimal residual disease, monitoring therapeutic response, detecting emerging resistance mechanisms, and guiding targeted treatment selection in advanced breast cancer. However, applications in early cancer detection, population screening, and artificial intelligence-assisted clinical decision-making remain investigational. Widespread clinical implementation is constrained by low ctDNA abundance in early-stage disease, analytical variability, limited assay standardization, and cost considerations. Continued technological innovation, prospective multicenter validation, standardized testing protocols, and evidence-based clinical guidelines are essential to fully integrate ctDNA into routine precision breast cancer care.

PMID:42699009 | PMC:PMC13542536 | DOI:10.1177/11782234261485831

Role of liquid biopsy in the multimodal assessment and treatment of esophageal cancer: a surgical perspective

Updates Surg. 2026 Aug 24. doi: 10.1007/s13304-026-02814-4. Online ahead of print.

ABSTRACT

Esophageal cancer (EC) remains a highly lethal malignancy, characterized by late diagnosis, early systemic dissemination, and high recurrence rates. Conventional diagnostic and surveillance strategies have limited sensitivity for early disease detection and minimal residual disease. Liquid biopsy technologies have emerged as promising minimally invasive tools for diagnosis, prognostication, and longitudinal monitoring. This scoping review summarizes current evidence on the clinical utilization of liquid biopsies in esophageal squamous cell and adenocarcinoma. PubMed, EMBASE and Cochrane Library were queried. Inclusion criteria encompassed studies investigating the use of liquid biopsy for EC diagnosis, treatment response evaluation, and prognosis definition. A total of 73 studies reported the role of circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), or microRNAs (miRNA). The majority (59%) focused on ctDNA while CTC and miRNA were assessed in 12 and 14 studies, respectively. The reported pooled diagnostic sensitivity and specificity was 71% and 98.6%, respectively, with superior performance in advanced stages (III-IV). Serial ctDNA measurements during neoadjuvant therapy have been reported useful for assessing tumor burden reduction. Additionally, comprehensive ctDNA profiling proved valuable for analysis of tumor heterogeneity and actionable genetic alterations suitable for targeted treatment therapies. Elevated preoperative ctDNA levels correlated with an increased risk of nodal metastasis and postoperative cancer recurrence. ctDNA was also identified as a useful prognostic marker, demonstrating sensitivity and specificity of 49% and 95%, respectively, for survival prediction. Despite limitations related to the various methodologies employed and the lack of laboratory standardization, liquid biopsy constitutes a promising frontier in the surgical management of EC, offering minimally invasive, real-time tool for assessing tumor genetics, genomic heterogeneity, and dynamics of tumor progression. It might enhance early diagnosis, inform neoadjuvant treatment response, and enable postoperative surveillance for residual or recurrent cancer.

PMID:42635711 | DOI:10.1007/s13304-026-02814-4

Safety of Telemedicine Versus In-Person Care for Patients With Tracheal Devices: Propensity Score–Matched Cohort Study

Background: Patients with tracheal diseases often require long-term follow-up after tracheal device placement, with a risk of adverse events that may lead to emergency care and unplanned interventions. Telemedicine has been proposed as an alternative to in-person follow-up to improve access and continuity of care. Objective: The primary objective of this study was to compare the need for emergency department (ED) visits between telemedicine and in-person groups. Secondary objectives included comparing hospital readmissions, 30-day hospital readmissions, and unplanned interventions between groups. Methods: This retrospective, single-institution study included adult patients with tracheal devices who underwent telemedicine and in-person outpatient clinic visits between 2020 and 2024. To balance the groups, we used 1:1 propensity score matching. We collected demographic and clinical data and evaluated the need for ED visits, hospital readmissions, 30-day hospital readmissions, and unplanned interventions. Kaplan-Meier estimation of time to first ED visit was performed to assess outcomes after outpatient visits. Results: A total of 483 patients (n=277, 57% telemedicine and n=206, 43% in-person) underwent 2487 visits (1258 telemedicine and 1229 in-person). After propensity score matching, 336 patients remained (168 in each group). There were no significant differences in the need for ED visits, hospital readmissions, or unplanned interventions. The telemedicine group had significantly fewer 30-day hospital readmissions (odds ratio 0.38, 95% CI 0.16-0.87; =.02). Kaplan-Meier analysis indicated no statistically significant difference in ED-free visits. Conclusions: Telemedicine follow-up was associated with outcomes comparable to those of in-person follow-up in this cohort of adult patients with tracheal devices, with no evidence of an increased need for ED visits. In the matched analysis, telemedicine was associated with lower odds of 30-day hospital readmission.

BoxLitE: A Faithful Knowledge Base Embedding Based on Convex Optimization

arXiv:2605.23937v1 Announce Type: new Abstract: Knowledge base (KB) embeddings aim at combining the capability of classical knowledge graph embeddings to generalize the information present in facts, the ABox, with conceptual knowledge represented in an ontology language, the TBox. Several authors have recently explored the idea of mapping concepts to convex regions in a vector space. This is useful to represent hierarchies, typically present in TBoxes, since more general concepts can be mapped to larger regions, containing those regions associated with more specific concepts. However, the power of convexity is rarely leveraged during the actual learning tasks. Here, we introduce BoxLitE, a KB embedding model for DL-Lite$^{\mathcal{H}}$ that allows for convex optimization. We show that for any satisfiable DL-Lite$^{\mathcal{H}}$ KB, there is a BoxLitE embedding that is a weakly faithful model. As a proof of concept, we show how to formulate the KB embedding task as a convex optimization problem and how to obtain embeddings with such desirable faithfulness properties.

Fibroblast growth factor receptor inhibition for succinate dehydrogenase-deficient gastrointestinal stromal tumors: a phase 2 trial

Nature Medicine, Published online: 26 May 2026; doi:10.1038/s41591-026-04376-9

In a multicenter phase 2 trial, the fibroblast growth factor receptor inhibitor rogaratinib showed encouraging clinical efficacy in patients with succinate dehydrogenase-deficient gastrointestinal stromal tumors, suggesting a potential new treatment option for this patient population and demonstrating that an epigenetic mechanism of oncogene activation can be successfully targeted with a tyrosine kinase inhibitor.

A comparison of deep multiomics profiles across ethnicity, geography, and age

Multiomics profiling of healthy individuals reveals differences across molecular layers and key pathways related to immune, metabolic, and microbiome-linked processes across ethnicities, while geographic relocation reshapes these networks and influences aging trajectories.

Fronto-insular circuit mechanisms of accelerated intermittent theta burst stimulation

An optogenetic model of accelerated intermittent theta burst stimulation reveals cell type-specific plasticity mechanisms and a key role for a fronto-insular circuit in driving the antidepressant effects of this treatment in humans.

Predicting bilingual aphasia treatment outcomes using digital twins: a double-blind randomized controlled trial

npj Digital Medicine, Published online: 10 April 2026; doi:10.1038/s41746-026-02583-9

Predicting bilingual aphasia treatment outcomes using digital twins: a double-blind randomized controlled trial

Nonsense-mediated mRNA decay inhibition reshapes the cancer immunopeptidome

Immunity. 2026 Apr 8:S1074-7613(26)00075-0. doi: 10.1016/j.immuni.2026.02.005. Online ahead of print.

ABSTRACT

DNA mutations are a well-characterized source of neoepitopes in immunotherapy. Here, we examined the contribution of dysregulated RNA processing to neoantigen production. Leveraging multi-omics and checkpoint inhibitor (CPI) response data from >1,000 patients, we identified reduced activity of the nonsense-mediated mRNA decay (NMD) pathway kinase SMG1 as a predictor of improved CPI response. NMD inhibition through SMG1 targeting stabilized transcripts containing premature termination codons, most of which were of non-mutational origin. This reshaped the major histocompatibility complex class I (MHC class I)-bound immunopeptidome and increased neoantigen abundance to levels comparable to high mutation burden tumors. Functionally, NMD inhibition drove antigen-dependent T cell-mediated tumor cell killing in vitro, promoted activation of tissue-resident T cells in patient-derived models ex vivo, and improved CPI efficacy in vivo. Our findings establish NMD inhibition as a strategy to harness a previously inaccessible source of canonical and non-canonical neoantigens, with the potential to increase tumor immunogenicity across cancers.

PMID:41956098 | DOI:10.1016/j.immuni.2026.02.005

High-fidelity collisional quantum gates with fermionic atoms

Nature, Published online: 08 April 2026; doi:10.1038/s41586-026-10356-3

A robust composite pair-exchange gate based on controlled interactions of fermionic atoms in an optical superlattice demonstrates high fidelities and long Bell-state lifetimes, marking an important step towards a fully digital fermionic quantum computer.

AICCE: AI Driven Compliance Checker Engine

arXiv:2604.03330v1 Announce Type: cross Abstract: For digital infrastructure to be safe, compatible, and standards-aligned, automated communication protocol compliance verification is crucial. Nevertheless, current rule-based systems are becoming less and less effective since they are unable to identify subtle or intricate non-compliance, which attackers frequently use to establish covert communication channels in IPv6 traffic. In order to automate IPv6 compliance verification, this paper presents the Artificial Intelligence Driven Compliance Checker Engine (AICCE), a novel generative system that combines dual-architecture reasoning and retrieval-augmented generation (RAG). Specification segments pertinent to each query can be efficiently retrieved thanks to the semantic encoding of protocol standards into a high-dimensional vector space. Based on this framework, AICCE offers two complementary pipelines: (i) Explainability Mode, which uses parallel LLM agents to render decisions and settle disputes through organized discussions to improve interpretability and robustness, and (ii) Script Execution Mode, which converts clauses into Python rules that can be executed quickly for dataset-wide verification. With the debate mechanism enhancing decision reliability in complicated scenarios and the script-based pipeline lowering per-sample latency, AICCE achieves accuracy and F1-scores of up to 99% when tested on IPv6 packet samples across sixteen cutting-edge generative models. By offering a scalable, auditable, and generalizable mechanism for identifying both routine and covert non-compliance in dynamic communication environments, our results show that AICCE overcomes the blind spots of conventional rule-based compliance checking systems.

Zero-Shot Quantization via Weight-Space Arithmetic

arXiv:2604.03420v1 Announce Type: cross Abstract: We show that robustness to post-training quantization (PTQ) is a transferable direction in weight space. We call this direction the quantization vector: extracted from a donor task by simple weight-space arithmetic, it can be used to patch a receiver model and improve robustness to PTQ-induced noise by as much as 60%, without receiver-side quantization-aware training (QAT). Because the method requires no receiver training data, it provides a zero-shot, low-cost alternative to QAT for extremely low-bit deployment. We demonstrate this on Vision Transformer (ViT) models. More broadly, our results suggest that quantization robustness is not merely a byproduct of task-specific training, but a reusable feature of weight-space geometry that can be transferred rather than retrained.

Inference-Path Optimization via Circuit Duplication in Frozen Visual Transformers for Marine Species Classification

arXiv:2604.03428v1 Announce Type: cross Abstract: Automated underwater species classification is constrained by annotation cost and environmental variation that limits the transferability of fully supervised models. Recent work has shown that frozen embeddings from self-supervised vision foundation models already provide a strong label-efficient baseline for marine image classification. Here we investigate whether this frozen-embedding regime can be improved at inference time, without fine-tuning or changing model weights. We apply Circuit Duplication, an inference-time method originally proposed for Large Language Models, in which a selected range of transformer layers is traversed twice during the forward pass. We evaluate on the class-imbalanced AQUA20 benchmark using frozen DINOv3 embeddings under two settings: global circuit selection, where a single duplicated circuit is chosen for the full dataset, and class-specific circuit selection, where each species may receive a different optimal circuit. Both settings use simple semi-supervised downstream classifiers. Circuit Duplication consistently improves over the standard frozen forward pass. At the maximum label budget, class-specific selection reaches a macro F1 of 0.875, closing the gap to the fully supervised ConvNeXt benchmark (0.889) to 1.4 points without any gradient-based training. Four species exceed their fully supervised reference, with octopus improving by +12.1 F1 points. Across all budgets, roughly 75% of classes prefer a class-specific circuit, indicating a genuinely class-dependent benefit. To our knowledge, this is the first application of Circuit Duplication to computer vision.
❌