Normal view
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cs.AI, q-bio.NC updates on arXiv.org
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AI PB: A Grounded Generative Agent for Personalized Investment Insights
arXiv:2510.20099v1 Announce Type: new Abstract: We present AI PB, a production-scale generative agent deployed in real retail finance. Unlike reactive chatbots that answer queries passively, AI PB proactively generates grounded, compliant, and user-specific investment insights. It integrates (i) a component-based orchestration layer that deterministically routes between internal and external LLMs based on data sensitivity, (ii) a hybrid retrieval pipeline using OpenSearch and the finance-domain
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Nature Biotechnology - Issue - nature.com science feeds
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Elucidating lipid nanoparticle properties and structure through biophysical analyses
Nature Biotechnology, Published online: 23 October 2025; doi:10.1038/s41587-025-02855-xGuidance for optimizing lipid nanoparticle formulations is derived using sophisticated biophysical techniques.
Elucidating lipid nanoparticle properties and structure through biophysical analyses
Nature Biotechnology, Published online: 23 October 2025; doi:10.1038/s41587-025-02855-x
Guidance for optimizing lipid nanoparticle formulations is derived using sophisticated biophysical techniques.-
cs.AI, q-bio.NC updates on arXiv.org
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A Goal-Driven Survey on Root Cause Analysis
arXiv:2510.19593v1 Announce Type: cross Abstract: Root Cause Analysis (RCA) is a crucial aspect of incident management in large-scale cloud services. While the term root cause analysis or RCA has been widely used, different studies formulate the task differently. This is because the term "RCA" implicitly covers tasks with distinct underlying goals. For instance, the goal of localizing a faulty service for rapid triage is fundamentally different from identifying a specific functional bug for a d
A Goal-Driven Survey on Root Cause Analysis
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Nature - Issue - nature.com science feeds
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Discovering state-of-the-art reinforcement learning algorithms
Nature, Published online: 22 October 2025; doi:10.1038/s41586-025-09761-xDiscovering state-of-the-art reinforcement learning algorithms
Discovering state-of-the-art reinforcement learning algorithms
Nature, Published online: 22 October 2025; doi:10.1038/s41586-025-09761-x
Discovering state-of-the-art reinforcement learning algorithms-
Nature Biotechnology - Issue - nature.com science feeds
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Integrated epigenetic and genetic programming of primary human T cells
Nature Biotechnology, Published online: 21 October 2025; doi:10.1038/s41587-025-02856-wMultiplexed editing in primary human T cells generates enhanced immune cell therapies.
Integrated epigenetic and genetic programming of primary human T cells
Nature Biotechnology, Published online: 21 October 2025; doi:10.1038/s41587-025-02856-w
Multiplexed editing in primary human T cells generates enhanced immune cell therapies.-
Omics In Lung
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Integrative Transcriptomic and Metabolomic Analysis Reveals Aberrant Glycosylation as a Hallmark of Lung Adenocarcinoma
OMICS. 2025 Oct 16. doi: 10.1177/15578100251387518. Online ahead of print.ABSTRACTLung adenocarcinoma (LUAD) remains the most common subtype of lung cancer, characterized by high heterogeneity and poor survival outcomes. Although transcriptomic and metabolomic alterations have been individually studied, integrated multi-omics analyses are needed to uncover the convergent pathways that drive tumor progression. Differentially expressed genes (DEGs) were identified from the GSE229253 transcriptomic
Integrative Transcriptomic and Metabolomic Analysis Reveals Aberrant Glycosylation as a Hallmark of Lung Adenocarcinoma
OMICS. 2025 Oct 16. doi: 10.1177/15578100251387518. Online ahead of print.
ABSTRACT
Lung adenocarcinoma (LUAD) remains the most common subtype of lung cancer, characterized by high heterogeneity and poor survival outcomes. Although transcriptomic and metabolomic alterations have been individually studied, integrated multi-omics analyses are needed to uncover the convergent pathways that drive tumor progression. Differentially expressed genes (DEGs) were identified from the GSE229253 transcriptomic dataset comprising LUAD tumor and adjacent normal tissues, while significantly altered metabolites were obtained from the Lung Cancer Metabolome Database. The top 10 DEGs and metabolites were analyzed using the search tool for interacting chemicals (STITCH) to construct gene-metabolite networks, and Integrated Molecular Pathway Level Analysis (IMPaLA) was employed for integrated pathway enrichment to identify overlapping molecular processes. Transcriptomic profiling revealed 973 DEGs (410 upregulated and 563 downregulated), and metabolomic analysis identified significant alterations in metabolites linked to redox balance, amino acid derivatives, and nucleotide metabolism. Integration through STITCH generated a network of 16 nodes and 9 edges, highlighting gene-metabolite associations of probable biological relevance. Joint pathway enrichment analysis using IMPaLA consistently identified glycosylation-related pathways, particularly O-linked glycosylation of mucins, as major axes of convergence between transcriptomic and metabolomic alterations in LUAD (joint p = 0.00129-0.00434). Several genes (B3GNT6, FEZF1-AS1, and LCAL1) and metabolites (isoleucylleucine, leucylleucine, and isoleucylvaline) are probable novel candidates, warranting further investigation. These findings provide systems-level evidence that aberrant glycosylation is likely a central hallmark of LUAD, underscore the potential of glycosylation pathways as biomarkers and therapeutic targets, and demonstrate the utility of cross-omics approaches to unpack the molecular complexity of lung cancer.
PMID:41103242 | DOI:10.1177/15578100251387518
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(Multiomics OR Omics) AND (Lung OR gastric OR Hepatocellular)
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Comprehensive bioinformatics analysis of omics data to reveal molecular mechanisms and biomarkers in multiple cancers
In Silico Pharmacol. 2025 Oct 17;13(3):154. doi: 10.1007/s40203-025-00440-3. eCollection 2025.ABSTRACTBreast, ovarian, lung, cervical, and colorectal cancers are among the most prevalent malignancies affecting women worldwide. This study aimed to elucidate the common molecular mechanisms of tumorigenesis and identify potential biomarkers using an integrative bioinformatics and network-based approach. Integrative profiling of five microarray datasets identified 66 differentially expressed genes (
Comprehensive bioinformatics analysis of omics data to reveal molecular mechanisms and biomarkers in multiple cancers
In Silico Pharmacol. 2025 Oct 17;13(3):154. doi: 10.1007/s40203-025-00440-3. eCollection 2025.
ABSTRACT
Breast, ovarian, lung, cervical, and colorectal cancers are among the most prevalent malignancies affecting women worldwide. This study aimed to elucidate the common molecular mechanisms of tumorigenesis and identify potential biomarkers using an integrative bioinformatics and network-based approach. Integrative profiling of five microarray datasets identified 66 differentially expressed genes (DEGs) that are common across five cancer types. Gene ontology and KEGG pathway analyses of common DEGs were performed using the DAVID database. The cell cycle processes were the most enriched functions, and oocyte meiosis, oocyte maturation, the p53 signaling pathway, cancer pathways, and cellular senescence were the most important pathways identified. Protein-protein interaction (PPI) networks for the DEGs were constructed using the STRING database, and the resulting networks were visualized in Cytoscape. Through PPI network analysis, ten hub genes were identified, and subsequent survival analysis confirmed that CHEK1, DLGAP5, CCNB2, and CCNA2 are significantly associated with poor patient survivability, establishing them as common biomarkers across multiple cancer types. Subsequently, ten transcription factors (TFs) and ten post-transcriptional regulators were identified through the assessment of regulatory networks involving TFs-DEGs and miRNAs-DEGs. Finally, drug-gene association analysis from the GSCA library was used to anticipate drug-like compounds using the drug repurposing approach. Overall, this comprehensive investigation holds promise for future in vitro and in vivo studies, offering a molecular foundation for the diagnosis, prognosis, and treatment of malignant cancers.
SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40203-025-00440-3.
PMID:41113171 | PMC:PMC12534660 | DOI:10.1007/s40203-025-00440-3
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Nature - Issue - nature.com science feeds
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Parity and lactation induce T cell mediated breast cancer protection
Nature, Published online: 20 October 2025; doi:10.1038/s41586-025-09713-5Parity and lactation induce T cell mediated breast cancer protection
Parity and lactation induce T cell mediated breast cancer protection
Nature, Published online: 20 October 2025; doi:10.1038/s41586-025-09713-5
Parity and lactation induce T cell mediated breast cancer protection-
Nature - Issue - nature.com science feeds
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Alternatives to animal testing are the future — it’s time that journals, funders and scientists embrace them
Nature, Published online: 20 October 2025; doi:10.1038/d41586-025-03344-6Biomedical research techniques that don’t involve the use of animals are gaining momentum, but those using innovative approaches still face resistance from some quarters.
Alternatives to animal testing are the future — it’s time that journals, funders and scientists embrace them
Nature, Published online: 20 October 2025; doi:10.1038/d41586-025-03344-6
Biomedical research techniques that don’t involve the use of animals are gaining momentum, but those using innovative approaches still face resistance from some quarters.-
InfoQ

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Article: A Plan-Do-Check-Act Framework for AI Code Generation
AI code generation tools promise faster development but often create quality issues, integration problems, and delivery delays. A structured Plan-Do-Check-Act cycle can maintain code quality while leveraging AI capabilities. Through working agreements, structured prompts, and continuous retrospection, it asserts accountability over code while guiding AI to produce tested, maintainable software. By Ken Judy
Article: A Plan-Do-Check-Act Framework for AI Code Generation
AI code generation tools promise faster development but often create quality issues, integration problems, and delivery delays. A structured Plan-Do-Check-Act cycle can maintain code quality while leveraging AI capabilities. Through working agreements, structured prompts, and continuous retrospection, it asserts accountability over code while guiding AI to produce tested, maintainable software.
By Ken Judy-
Cell Death Discovery nature.com science feeds
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Evidence of fructose metabolism in colorectal cancer
Cell Death Discovery, Published online: 16 October 2025; doi:10.1038/s41420-025-02745-wEvidence of fructose metabolism in colorectal cancer
Evidence of fructose metabolism in colorectal cancer
Cell Death Discovery, Published online: 16 October 2025; doi:10.1038/s41420-025-02745-w
Evidence of fructose metabolism in colorectal cancer-
Nature Biotechnology - Issue - nature.com science feeds
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A tumor-on-a-chip for in vitro study of CAR-T cell immunotherapy in solid tumors
Nature Biotechnology, Published online: 17 October 2025; doi:10.1038/s41587-025-02845-zThe interactions of CAR-T cells and solid tumors are modeled on a chip.
A tumor-on-a-chip for in vitro study of CAR-T cell immunotherapy in solid tumors
Nature Biotechnology, Published online: 17 October 2025; doi:10.1038/s41587-025-02845-z
The interactions of CAR-T cells and solid tumors are modeled on a chip.-
Cell
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AI-generated MLH1 small binder improves prime editing efficiency
A compact, AI-generated suppressor of DNA mismatch repair can enhance prime editing in vivo and in vitro and can be integrated into a variety of prime editing architectures.
AI-generated MLH1 small binder improves prime editing efficiency
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Journal of Medical Internet Research
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Framework for the Development and Delivery of Digital Peer Support Programs: Qualitative Study on in-Person and Digital Delivery for People With Cardiovascular Disease
Background: Peer support (sharing experiences/support with others with the same condition) improves health outcomes among people with cardiovascular disease (CVD), including self-management behaviours and self-efficacy. However, current peer support interventions are diverse. Evidence is lacking on peer support attenders perceptions of benefits and the elements that are considered priorities, especially for digital interventions. Objective: The study objectives were to 1) describe perceived bene
Framework for the Development and Delivery of Digital Peer Support Programs: Qualitative Study on in-Person and Digital Delivery for People With Cardiovascular Disease
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Nature Biotechnology - Issue - nature.com science feeds
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Accurate somatic small variant discovery for multiple sequencing technologies with DeepSomatic
Nature Biotechnology, Published online: 16 October 2025; doi:10.1038/s41587-025-02839-xSomatic small variants in cancer genomes are identified in both short-read and long-read data.
Accurate somatic small variant discovery for multiple sequencing technologies with DeepSomatic
Nature Biotechnology, Published online: 16 October 2025; doi:10.1038/s41587-025-02839-x
Somatic small variants in cancer genomes are identified in both short-read and long-read data.-
Journal of Medical Internet Research
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Implementing a Digital Mental Health Intervention—the Lumi Nova App—to Support Children With Anxiety in Economically Disadvantaged Areas: Mixed Methods Study
Background: Anxiety is one of the most common mental health problems experienced by children worldwide. In the UK, many children experiencing anxiety do not receive adequate or timely help. Children living in economically-disadvantaged areas experience more mental health problems than those living in high income areas and are less able to engage in activities that can have a positive or protective impact on their mental health. The need for providing low-cost, accessible and engaging mental heal
Implementing a Digital Mental Health Intervention—the Lumi Nova App—to Support Children With Anxiety in Economically Disadvantaged Areas: Mixed Methods Study
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npj Digital Medicine
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Automated AI based identification of autism spectrum disorder from home videos
npj Digital Medicine, Published online: 10 October 2025; doi:10.1038/s41746-025-01993-5Automated AI based identification of autism spectrum disorder from home videos
Automated AI based identification of autism spectrum disorder from home videos
npj Digital Medicine, Published online: 10 October 2025; doi:10.1038/s41746-025-01993-5
Automated AI based identification of autism spectrum disorder from home videos-
AAAS: Table of Contents
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A human pan-disease blood atlas of the circulating proteome
Science, Ahead of Print.
A human pan-disease blood atlas of the circulating proteome
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Nature - Issue - nature.com science feeds
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Stop treating code like an afterthought: record, share and value it
Nature, Published online: 07 October 2025; doi:10.1038/d41586-025-03196-0Scientists, research institutions, funders, libraries and publishers must all improve software practices.
Stop treating code like an afterthought: record, share and value it
Nature, Published online: 07 October 2025; doi:10.1038/d41586-025-03196-0
Scientists, research institutions, funders, libraries and publishers must all improve software practices.-
Nature Medicine
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Clinical validation of an AI-based blood testing device for diagnosis and prognosis of acute infection and sepsis
Nature Medicine, Published online: 30 September 2025; doi:10.1038/s41591-025-03933-yIn a prospective study enrolling 1,222 patients from 22 emergency departments, a device using a machine-learning-based signature of blood mRNAs demonstrated clinically acceptable performance to diagnose bacterial and viral infections and to predict the all-cause need for critical care interventions within 7 days, with benchmark to established biomarkers and risk scores.
Clinical validation of an AI-based blood testing device for diagnosis and prognosis of acute infection and sepsis
Nature Medicine, Published online: 30 September 2025; doi:10.1038/s41591-025-03933-y
In a prospective study enrolling 1,222 patients from 22 emergency departments, a device using a machine-learning-based signature of blood mRNAs demonstrated clinically acceptable performance to diagnose bacterial and viral infections and to predict the all-cause need for critical care interventions within 7 days, with benchmark to established biomarkers and risk scores.