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        <title>Frontiers in Science | New and Recent Articles</title>
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        <pubDate>2026-11-15T12:03:02.809+00:00</pubDate>
        <ttl>60</ttl>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.2026739</guid>
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        <title><![CDATA[Large language medicine needs a foundation, not only a frontier]]></title>
        <pubdate>2026-10-30T00:00:00Z</pubdate>
        <category>Frontiers in Science Editorial</category>
        <author>Alain Labrique</author><author>Yu Zhao</author><author>Sameer Pujari</author>
        <description></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.2015324</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsci.2026.2015324</link>
        <title><![CDATA[Human-led, AI-enabled: preventing another AI winter through workforce transformation]]></title>
        <pubdate>2026-10-30T00:00:00Z</pubdate>
        <category>Frontiers in Science Editorial</category>
        <author>Marylyn D. Ritchie</author><author>Justin M. Keally</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.2008129</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsci.2026.2008129</link>
        <title><![CDATA[Targeting G protein-coupled receptor networks for healthy aging: grounding systems geroprotection in biophysical and data realities]]></title>
        <pubdate>2026-10-22T00:00:00Z</pubdate>
        <category>Frontiers in Science Viewpoint</category>
        <author>Marta Filizola</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.2026340</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsci.2026.2026340</link>
        <title><![CDATA[The GPCR-ome as a central regulator of human healthspan]]></title>
        <pubdate>2026-10-22T00:00:00Z</pubdate>
        <category>Frontiers in Science Editorial</category>
        <author>Thomas P. Sakmar</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.1891819</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsci.2026.1891819</link>
        <title><![CDATA[Network-level control of G protein-coupled receptors: a panacea for chronic diseases?]]></title>
        <pubdate>2026-10-22T00:00:00Z</pubdate>
        <category>Frontiers in Science Lead Article</category>
        <author>Tabitha Boeringer</author><author>Mia Pardo</author><author>Carter J. Craig</author><author>Ashley Del Pozo</author><author>Graham Ladds</author><author>Terence E. Hébert</author><author>Silke Dodel</author><author>Howard Prentice</author><author>Roza Bejanyan</author><author>Stuart Maudsley</author>
        <description><![CDATA[G protein-coupled receptors (GPCRs) modulate diverse hormonal, metabolic, neural, and immunological signaling processes. Their age-dependent decline accounts for many fundamental hallmarks of aging, including low-grade inflammation (inflammaging), mitochondrial failure and energy dysregulation, genomic instability and epigenetic dysregulation, dysregulated cellular communication, loss of proteostasis, and cellular senescence. Consequently, GPCR dysfunction underpins nearly all chronic, age-related diseases, including cardiovascular disease, cancer, various endocrine disorders, and neurodegenerative conditions such as Alzheimer’s and Parkinson’s diseases. Therefore, the GPCR network (“GPCR-ome”) constitutes a central, druggable, “mega-trophic” regulator of human healthspan. Individual GPCRs present numerous therapeutic targets for specific conditions, many of which are already being exploited, while others show future promise. Alongside this disease-centric approach, the GPCR-ome offers the more radical opportunity to rebalance entire signaling networks to simultaneously correct the multisystem pathological effects of aging itself. Here, we outline a transformative paradigm for network-level, GPCR-based geroprotection that employs artificial intelligence, digital twins, and quantum computational methods to design biased agonists, allosteric or multitarget modulators, heteromer-selective ligands, and polypharmacological strategies to mitigate and manage age-related disorders. We also explore how combinatorial GPCR-based strategies (e.g., coupled with senolytic, metabolic, or regenerative medicines) hold compelling promise to delay multiple hallmarks of aging and enable personalized anti-aging GPCR therapies based on multiomic biomarkers.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.1939931</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsci.2026.1939931</link>
        <title><![CDATA[Catching aging in motion]]></title>
        <pubdate>2026-09-17T00:00:00Z</pubdate>
        <category>Frontiers in Science Viewpoint</category>
        <author>Joseph P. McGaunn</author><author>Joseph A. Baur</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.1821393</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsci.2026.1821393</link>
        <title><![CDATA[Aging rate indicators and the search for anti-aging drugs]]></title>
        <pubdate>2026-09-17T00:00:00Z</pubdate>
        <category>Frontiers in Science Lead Article</category>
        <author>Steven N. Austad</author><author>Matt Kaeberlein</author><author>Richard A. Miller</author>
        <description><![CDATA[Evidence that drugs, diets, and single-gene mutations can slow aging and extend the healthy lifespan of mammals has begun to convert biogerontology from an observational science into one based on interventions that could provide people with additional years of healthy, productive life. However, the research and development of anti-aging drugs is hampered by the lack of instantaneous and continuous measures of the rate of aging itself. This article presents recent work on anti-aging drugs that are effective in mice, provides evidence for candidate “aging rate indicators” (ARIs), and outlines a roadmap for translating these into clinical research to slow aging in humans. Thus far, 14 agents or combinations have significantly increased the lifespan of mice in studies conducted under the Interventions Testing Program (ITP) of the National Institute on Aging, often when initiated in late adulthood. Recent evidence suggests that many, perhaps all, interventions that slow aging in mice induce common, shared changes in physiological status and molecular pathways. We have proposed 12 such mechanisms as candidate ARIs, i.e., measurable outcomes that reflect a slow-aging state and that could discriminate between normal mice (and perhaps humans) and those exposed to effective anti-aging interventions—thereby accelerating research. Research priorities now include testing the robustness of these ARIs, extending them to include plasma constituents, elucidating the mechanisms through which diverse interventions alter them, uncovering the links between the ARIs and late-life diseases, and extending research to dogs, non-human primates, and humans. The growing recognition of the legitimacy and promise of evidence-based interventions resulting from aging biology should elevate this field to a level of urgency and respect comparable to that of current research on individual age-related conditions.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.1963812</guid>
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        <title><![CDATA[Is the glucose ketone index a biomarker of metabolic flexibility?]]></title>
        <pubdate>2026-09-15T00:00:00Z</pubdate>
        <category>Frontiers in Science Viewpoint</category>
        <author>Shaminie J. Athinarayanan</author><author>Benjamin T. Bikman</author><author>Richard J. Johnson</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.1810095</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsci.2026.1810095</link>
        <title><![CDATA[Large language medicine: defining a new paradigm in human health]]></title>
        <pubdate>2026-09-01T00:00:00Z</pubdate>
        <category>Frontiers in Science Lead Article</category>
        <author>Ahmad Guni</author><author>Wanheng Hu</author><author>Jessica Morley</author><author>I. Glenn Cohen</author><author>Payam Barnaghi</author><author>Hutan Ashrafian</author>
        <description><![CDATA[Artificial intelligence (AI) is poised to revolutionize our understanding of disease and pre-disease, which could transform the way medicine is practiced. Advances in deep learning systems, alongside the advent of generative AI and large language models, promise to usher in an era of multimodal AI systems that permeate every aspect of medicine. AI is expected to support the full spectrum of public health and clinical functions, including surveillance, monitoring, protection, health promotion, and disease prevention. In parallel, molecular biology has been revolutionized by AI solutions that can accurately model proteins and other biological molecules at scale with the potential to accelerate drug discovery and reshape our understanding of disease and pre-disease mechanisms. However, AI has yet to be incorporated into common day-to-day practice, underscoring the difficulty of clinical integration. Achieving this goal will require advancing algorithmic architecture, sourcing higher-quality multimodal data, increasing processing power and efficiency, developing secure and fit-for-purpose data infrastructures, ensuring interoperability with diverse health systems and clinical workflows, and establishing regulatory pathways to protect patient safety and clarify clinician liability. The potential emergence of autonomous systems capable of carrying out an increasing number of clinical tasks raises important ethical and legal questions about accountability and responsibility in patient care. This review explores the current state of AI in medicine, highlighting that current clinically mature and regulatory-approved products are based on deep learning architecture and are predominantly diagnostic. Robust regulatory frameworks and ethical guidelines must be established to govern the development and deployment of AI, ensuring alignment with patient safety, clinical guidelines, and public trust. Multidisciplinary collaboration among clinicians, researchers, technologists, ethicists, regulators, and policymakers is essential moving forward.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.1913108</guid>
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        <title><![CDATA[The data that biomedical AI still needs]]></title>
        <pubdate>2026-09-01T00:00:00Z</pubdate>
        <category>Frontiers in Science Viewpoint</category>
        <author>Benjamin S. Glicksberg</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.1963817</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsci.2026.1963817</link>
        <title><![CDATA[Lanthanides go bio: the long road to the clinic]]></title>
        <pubdate>2026-08-31T00:00:00Z</pubdate>
        <category>Frontiers in Science Editorial</category>
        <author>Andries Meijerink</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.1939897</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsci.2026.1939897</link>
        <title><![CDATA[The glucose ketone index: a compelling mechanistic hypothesis on the path to clinical validation]]></title>
        <pubdate>2026-08-20T00:00:00Z</pubdate>
        <category>Frontiers in Science Viewpoint</category>
        <author>Evelyne Bischof</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.1799238</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsci.2026.1799238</link>
        <title><![CDATA[Sequencing life on Earth: why the Global South must be central]]></title>
        <pubdate>2026-08-11T00:00:00Z</pubdate>
        <category>Frontiers in Science Viewpoint</category>
        <author>Sibelle Torres Vilaça</author><author>Alexandre Aleixo</author><author>Juliana A. Vianna</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.1905638</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsci.2026.1905638</link>
        <title><![CDATA[Lanthanide-based probes: beyond conventional imaging agents]]></title>
        <pubdate>2026-07-30T00:00:00Z</pubdate>
        <category>Frontiers in Science Viewpoint</category>
        <author>Jiating Xu</author><author>Jiawei Qu</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.1856377</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsci.2026.1856377</link>
        <title><![CDATA[Lanthanide carriers: biomedical imaging redefined]]></title>
        <pubdate>2026-07-30T00:00:00Z</pubdate>
        <category>Frontiers in Science Lead Article</category>
        <author>Yuxia Liu</author><author>Zixuan Chen</author><author>Mingyu Sui</author><author>Hongxuan Wang</author><author>Marco Bettinelli</author><author>Luís D. Carlos</author><author>Daniel Jaque</author><author>Oscar L. Malta</author><author>Jorge Méndez-Ramos</author><author>Cyrille Richard</author><author>Bruno Viana</author><author>Ka-Leung Wong</author><author>Xiaogang Liu</author>
        <description><![CDATA[Lanthanide-based carriers have emerged as powerful platforms for next-generation biomedical imaging, combining unique optical and magnetic features to address key limitations of conventional agents. Owing to their 4f electron configuration, lanthanide ions provide sharp emission lines, long lifetimes, high photostability, and strong paramagnetism, enabling high-resolution, multiplexed, and deep-tissue imaging with minimal photodamage. This review surveys recent advances across optical, X-ray, and magnetic resonance modalities, focusing on how material design influences performance. We examine representative carriers, such as lanthanide-doped nanoparticles, organic complexes, and lanthanide-binding proteins, and their roles in near-infrared (NIR) imaging (long-term single-particle tracking, molecular sensing, and NIR-II modalities), X-ray imaging (contrast media, scintillators, and persistent emitters for low-dose diagnostics), and magnetic resonance imaging (chemical and biosynthetic agents with enhanced relaxivity, specificity, and safety, including targeted protein constructs). We highlight molecular engineering and surface modification strategies that boost signal and biocompatibility, and discuss emerging directions such as artificial intelligence-enabled data analysis and the integration of multimodal probes to deliver integrated anatomical and functional information. While most advances are still at the proof-of-concept stage, lanthanide carriers show great potential for bridging materials science, biophysics, and clinical needs, and are reshaping biomedical imaging toward more precise, responsive, and personalized diagnostics.]]></description>
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        <title><![CDATA[The glucose ketone index: a proposed quantitative biomarker to support cancer and chronic disease prevention and management]]></title>
        <pubdate>2026-07-14T00:00:00Z</pubdate>
        <category>Frontiers in Science Lead Article</category>
        <author>Derek C. Lee</author><author>Tomas Duraj</author><author>Isabella D. Cooper</author><author>Joseph C. Maroon</author><author>Kris Smith</author><author>Wafaa Abdel-Hadi</author><author>Egiroh Omene</author><author>Athanasios E. Evangeliou</author><author>Thomas N. Seyfried</author>
        <description><![CDATA[The chronic disease burden is rapidly becoming the most significant health challenge of the 21st century. Chronic noncommunicable diseases (NCDs) are replacing infectious diseases as the most significant factor in poor global health outcomes. NCDs account for 75% of disability adjusted life years. Cancer is one of the deadliest chronic diseases and is now on the verge of overtaking heart disease as the leading cause of death in the United States. Mitochondrial dysfunction linked to nutritional imbalance, lack of physical activity, and exposure to a broad range of environmental toxins is implicated in cancer and many chronic diseases. Although nutrition and exercise recommendations have been emphasized for primary prevention, overall health remains poor due to conflicting information and the inability to easily assess adherence. The glucose ketone index (GKI) was originally developed as a quantitative point-of-care blood biomarker for assessing diet adherence in cancer therapy. However, the ratio of glucose to ketones (specifically β-hydroxybutyrate) can also be linked to the risk of chronic diseases and may help predict risk more accurately than the glucose reading alone. Low GKI ratios are hypothesized to decrease risk, while high GKI are hypothesized to increase risk. Non-insulin-compensated euglycemia may help reduce chronic inflammation, insulin resistance, and pro-tumorigenic pathways. Endogenous ketone production reduces glucose requirements while simultaneously enhancing the bioenergetic efficiency of mitochondrial energy metabolism, thus supporting metabolic homeostasis. Hence, we assert that the GKI could represent a parsimonious, individualized, and impartial biomarker for use, together with exercise and nutrition, to support therapeutic strategies to prevent and manage mitochondrial dysfunction, which contributes to cancer and many chronic diseases.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.1907205</guid>
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        <title><![CDATA[Therapeutic potential of Tregs]]></title>
        <pubdate>2026-06-25T00:00:00Z</pubdate>
        <category>Frontiers in Science Editorial</category>
        <author>Giovanna Lombardi</author><author>Robert Lechler</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.1792210</guid>
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        <title><![CDATA[Regulatory T cells: master orchestrators of immune tolerance and tissue homeostasis]]></title>
        <pubdate>2026-06-25T00:00:00Z</pubdate>
        <category>Frontiers in Science Lead Article</category>
        <author>Jeffrey A. Bluestone</author><author>Megan K. Levings</author><author>Frederick J. Ramsdell</author><author>Alexander Y. Rudensky</author><author>Qizhi Tang</author><author>Piotr Trzonkowski</author>
        <description><![CDATA[Harnessing the biology of regulatory T cells (Tregs) for therapeutic development is one of medicine’s most promising opportunities to transform disease treatment. Initially viewed simply as guardians against destructive immune responses, we now understand that Tregs are adaptive and highly specialized coordinators of immune tolerance and tissue repair. This strategic roadmap examines how evolving insights into their central role in maintaining tolerance and health can transform therapeutic development across medical specialties. Early efforts to evaluate Treg therapies have proven safe and shown some clinical benefit. The convergence of biological insights and technological advances has the potential to harness and exploit this specialized tolerogenic population by augmenting function through environmental cues and reinforcing tissue-repair capabilities. Advanced engineering approaches can now endow Treg therapies with antigen-specificity, enforce suppressive programming, and enable off-the-shelf or in vivo gene therapy opportunities. This new class of therapeutics promises to shift treatment paradigms from lifelong management to drug-free durable remissions or even cures for diseases currently requiring chronic immunosuppression. The recognition that dysregulated inflammation underlies countless human diseases opens unprecedented possibilities for treating intractable conditions across specialties—from transplantation and autoimmunity, metabolic disorders and cardiovascular disease, to neurodegeneration and even aging itself. Realizing the potential of Treg-based therapies remains a primary goal for the field, representing a strategic shift from systemic immunosuppression to precision tolerance restoration as a unifying therapeutic paradigm.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.1874873</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsci.2026.1874873</link>
        <title><![CDATA[Treg therapy needs better trials]]></title>
        <pubdate>2026-06-25T00:00:00Z</pubdate>
        <category>Frontiers in Science Viewpoint</category>
        <author>Fadi Issa</author><author>Kathryn Wood</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsci.2026.1721295</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsci.2026.1721295</link>
        <title><![CDATA[Enhancing soil science research with multi-agent artificial intelligence systems]]></title>
        <pubdate>2026-05-21T00:00:00Z</pubdate>
        <category>Frontiers in Science Lead Article</category>
        <author>Budiman Minasny</author><author>Alex McBratney</author><author>José A.M. Demattê</author><author>Mercedes Román Dobarco</author><author>Pete Smith</author>
        <description><![CDATA[Soil science is entering a new era characterized by the integration of artificial intelligence (AI) multi-agent systems, extending the field beyond traditional machine learning (ML) applications such as digital soil mapping and spectroscopy. While current ML tools are effective for specific tasks, they often lack the reasoning, contextual integration, and adaptability required to address complex, dynamic soil systems. We propose multi-agent AI systems—autonomous, interactive software agents capable of perceptual processing, planning, and scientific reasoning—as a novel framework to support and accelerate soil science research. These agents can fulfill diverse roles, including synthesizing data from field sensors and remote sensing to create dynamic digital soil twins, generating hypotheses, designing experiments, and simulating climate-driven changes in soil function. To illustrate this approach, we tasked a multi-agent system with creating research hypotheses on the topic of mineral-associated organic carbon saturation in soils. The agents generated five hypotheses on effective versus theoretical saturation thresholds, biological and chemical controls, climate influence, interdisciplinary feedback, and actionable management strategies. Each hypothesis was evaluated for empirical grounding, conceptual breadth, and scientific rigor by experts and a simulated peer review. Our findings highlight the potential of multi-agent AI systems, guided by human experts, to accelerate early-stage discovery, support interdisciplinary exploration, and emulate the scientific review process. Nonetheless, challenges remain, particularly around data quality, model transparency, epistemic overtrust, computational cost, ethical implications, and the retention of foundational scientific knowledge. We emphasize AI as an augmentative partner, not a replacement, for human-led discovery.]]></description>
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