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    Target trial emulation (TTE) has shown promise in enhancing causal inference from observational data. A recent study identified 90 TTE studies in cancer areas, revealing that registry databases and overall survival were commonly used. However, challenges such as immortal time bias and prevalent user bias were prevalent. Only 42.9% of trials calibrated with RCTs met both statistical and estimate agreement. The study highlights the need for fit-for-purpose data sources and regulatory acceptance to expand the use of real-world data in oncology.

    Hui-Yao Huang, Le Wang, Sheng Xu, Shuo-Peng Jia, Dan-Dan Kong, Xue-Jing Zhang, Si-Qi Wang, Han-Qing He, Hao-Ran Chen, Lu-Zhu Xia, Lan-Wei Guo, Yu Tang, Ling-Bin Du, Ning Li

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    DOI:10.1186/s40779-026-00685-9
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    Abstract:Target trial emulation (TTE) has demonstrated popularity because of its ability to improve the reliability of causal inference from observational data. Nevertheless, knowledge about the current use, potential challenges, and insights of target trials in oncology is scarce. A total of 90 TTE studies in cancer areas were identified through systematic reviews in PubMed and Embase. Among the 54 applications in cancer treatment, registry databases (44.4%) and overall survival (OS, 63.0%) were predominantly used as data sources and primary endpoints, respectively. Approximately 30 (55.6%) of the included TTE cases were associated with immortal time bias, and 21 (38.9%) were associated with prevalent user bias. Among the 21 trials from 13 studies that aimed to calibrate the results from preexisting randomized controlled trials (RCTs), only 42.9% met both statistical agreement and estimate agreement. The availability of fit-for-purpose data sources and uncertainty about result concordance were the main hurdles limiting the quantity and quality of TTE in oncology areas. Promoting regulatory acceptance by initiating special projects could be crucial for the expanded application of real-world data (RWD) using TTE. Potential solutions,such as the integration of electronic medical records at the regional or country level, linkage with insurance claims databases, the modernization of eligibility criteria, the use of OS as the primary endpoint, and other best practices,were recommended for improving the feasibility and quality of oncology TTE.  
    Keywords:Target trial emulation (TTE);Oncology;Bias;Real-world database   
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    Updated:2026-03-06
    Researchers have made significant strides in the field of inflammatory disease treatment. By exploring the therapeutic potential of an epitope from an anti-tetranectin antibody, they developed P2-1, a water-soluble derivative. This targeted therapy significantly improved survival rates and reduced inflammation in sepsis models, and lessened arthritis severity and pain in RA models. The study introduces a novel drug discovery strategy, transforming harmful antibody insights into targeted therapeutics for the HMGB1-pCTS-L axis.

    Wei-Qiang Chen, Li Lou, Xiao-Ling Qiang, Cassie Shu Zhu, Jian-Hua Li, Shu-Jin Chen, Brian Xiong, Huan Yang, Ping Wang, Kevin J. Tracey, Hai-Chao Wang

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    DOI:10.1186/s40779-026-00686-8
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    Abstract:BackgroundSepsis and rheumatoid arthritis (RA) are distinct yet mechanistically related conditions commonly driven by dysregulated inflammatory responses. Here, we explored the counterintuitive hypothesis that an epitope from a deleterious anti-tetranectin (TN) antibody (mAb9) could hold unforeseen therapeutic potential.MethodsBy mapping mAb9’s epitope to P2 (residues 55–70), a region crucial for TN’s protective functions, we developed P2-1, a water-soluble derivative as a targeted therapy. We then employed animal models of sepsis (cecal ligation and puncture) and arthritis (collagen antibody-induced arthritis) to evaluate the therapeutic effects of P2, P2-1, and a procathepsin L (pCTS-L)-neutralizing antibody by assessing septic survival, arthritis severity, pain sensi-tivity, and joint tissue histology. In parallel, we utilized a surface plasmon resonance (SPR) assay and computational modeling to examine the P2-1/high mobility group box 1 (HMGB1) interaction. Finally, we elucidate the effect of P2-1 on the HMGB1-induced release of pCTS-L and other cytokines and chemokines using primary human peripheral blood mononuclear cells (PBMCs).ResultsP2-1 significantly improved survival and reduced systemic inflammation in a sepsis model, and attenuated arthritis severity and pain sensitivity in an RA model, even with therapeutic administration after disease onset. Mecha-nistically, P2-1 exhibited high-affinity binding to HMGB1 and selectively suppressed HMGB1-induced cathepsin L (Ctsl) mRNA upregulation and pCTS-L secretion from human immune cells, crucially without perturbing other HMGB1-induced cytokines and chemokines. We further validated pCTS-L as a therapeutic target by demonstrating that a neu-tralizing antibody conferred potent antiarthritic effects, reducing joint inflammation, pain, and structural damage.ConclusionsOur findings introduce a paradigm-shifting drug discovery strategy that transforms insights from harm-ful antibody action into targeted therapeutics for the HMGB1-pCTS-L axis. This approach not only delivers P2-1 as a potent therapy but also establishes pCTS-L as a crucial mediator in inflammatory diseases such as sepsis and RA.  
    Keywords:High mobility group box 1 (HMGB1);Procathepsin L;Tetranectin;sepsis;Rheumatoid arthritis (RA);antibody;Mimetic peptide;Epitope;Innate immune cells   
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    Updated:2026-03-06
    The latest research in healthcare technology introduces the TRIAD framework. Experts established this system to guide the development, validation, and deployment of clinical AI. It ensures trustworthy governance, real-world clinical value, and integrated adaptive deployment, solving key challenges in AI integration and opening a new direction for healthcare AI research.

    Jia Li, Zi-Chun Zhou, Zhen-Chang Wang, Han Lv

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    DOI:10.1186/s40779-026-00684-w
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    Abstract:Artificial intelligence (AI) and big data are reshaping the healthcare landscape. However, clinical value depends on how well systems augment clinicians and fit into routine workflows. To this end, we introduce the TRIAD frame-work: trustworthy governance, real-world clinical value, and integrated adaptive deployment, to guide the develop-ment, validation, and deployment of clinical AI. TRIAD requires explicit data provenance and intended use, fairness auditing, and calibrated uncertainty. This framework evaluates the human-AI team in real workflows using teamlevel metrics, including accuracy, safety, workload, and patterns of acceptance, editing, and overriding. Deployment proceeds via staged rollouts with preregistered guardrails and continuous monitoring of performance and subgroup impact. TRIAD views intelligence as a property of the human-AI team rather than the AI model alone. Aligning gov-ernance, evaluation, and deployment around clinicians and patients enables durable gains in safety, equity, efficiency,and experience, thereby elevating clinical value.  
    Keywords:TRIAD;Artificial intelligence (AI);Human-AI collaboration;Trust mechanisms;Clinical decision support   
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    Updated:2026-03-06
    In the field of xxx, expert xx has made significant research progress. By establishing the xx system/exploring the xx topic/verifying the xx conjecture, xx has provided solutions to solve xx problems/open up a new direction for xx research/lay a foundation for the construction of the xx system.

    Jie Wang, Zhao-Jie Lyu, Qi Zhang, William C. Cho, De-Chao Feng

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    DOI:10.1186/s40779-025-00683-3
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    Keywords:G-quadruplex;RNA-DNA hybrids;Genome instability;DNA repair;Chromatin architecture   
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    Updated:2026-01-29
    Cytokine storms, a life-threatening systemic inflammatory syndrome, are the primary driver of multiorgan failure in various clinical situations. This review focuses on cytokine storms triggered by severe infections such as viral pneumonia and bacterial sepsis, exploring the underlying mechanisms and potential therapeutic interventions. Expert xx established the xx system, which provides solutions to solve xx problems.

    Jiang-Bo Fan, Qin-Yuan Li, Xi-Feng Feng, Si-Yuan Huang, Rui Wang, Feng-Ying Liao, Di Liu, Wen-Yi Liu, Jian-Hui Sun, Hua-Cai Zhang, Hui-Ting Zhou, Jian-Xin Jiang, Zhen Wang, Ling Zeng

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    DOI:10.1186/s40779-025-00678-0
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    Abstract:The cytokine storm, a life-threatening systemic inflammatory syndrome, is the primary driver of multiorgan failure in different clinical situations, including severe infections, autoimmune diseases, chimeric antigen receptor (CAR)T cell immunotherapy for cancer, and genetic syndromes. This review focuses primarily on cytokine storms triggered by severe infections such as viral pneumonia and bacterial sepsis, and explores the underlying mechanisms of cytokine storms and potential therapeutic interventions. Cytokine storms are characterized primarily by the excessive release of proinflammatory cytokines, which are triggered by pathogen-associated molecular patterns (PAMPs),damage-associated molecular patterns (DAMPs), and PANoptosis, all of which activate immune signaling cascades. Amplification mechanisms involve positive feedback loops and the failure of negative feedback mechanisms, leading to uncontrolled inflammation. Like a pyrrhic victory, the excessive activation of the immune system eliminated invading pathogens but caused catastrophic damage due to multiple organ dysfunction syndrome (MODS), turning the life-saving response into a life-threatening war. Therapeutic strategies, including cytokine antagonists, Janus kinase (JAK) inhibitors, caspase inhibitors, glucocorticoids, and blood purification therapies, aim to interrupt the self-amplifying cycle of inflammation that propagates organ injury, thereby reducing MODS and mortality. Challenges include optimizing the treatment timing and patient stratification. Future research should focus on combination therapies and personalized medicine based on the heterogeneity of infections and sepsis. Advances in multiomics and targeted therapies provide new hope for managing infections and sepsis.  
    Keywords:Cytokine storm;inflammatory response;Severe infection;sepsis;Multiple organ dysfunction syndrome   
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    Updated:2026-01-29
    In the field of early-stage non-small cell lung cancer treatment, researchers have developed an AI-assisted model called PRIME, which integrates clinical-genomic predictors to enhance risk prediction and guide personalized therapy. The model outperforms single liquid biopsy biomarkers and clinical-therapeutic signatures, demonstrating consistent robustness across different clinical scenarios.

    Yu Wang, Yong-Bo Xiang, Xiao-Wei Chen, Tao Zhang, Jian-Yang Wang, Wen-Yang Liu, Lei Deng, Lu-Hua Wang, Shu-Geng Gao, Nan Bi

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    DOI:10.1186/s40779-025-00679-z
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    Abstract:BackgroundDespite the predictive impact of circulating tumor DNA (ctDNA) minimal residual disease (MRD), accurate prediction of failure risk after curative-intent treatments for early-stage or localized non-small cell lung cancer (NSCLC) patients to guide personalized therapy remains challenging. This study aimed to develop and validate an interpretable artificial intelligence-assisted model using global data resources.MethodsLiquid biopsy data, blood-based genomic alterations, clinicopathological features, and survival outcomes of stage I-III NSCLC patients who underwent surgery or definitive chemoradiotherapy were collected from 6 cohorts. PRIME (Progression Risk prediction by Interpretable Machine learning on ctDNA-MRD, Mutations, and clinical-therapeutic features) was trained by 6 machine learning algorithms across 4 cohorts and validated in 2 independent cohorts. Model performance was evaluated by the area under the curve (AUC) and interpreted by SHapley Additive exPlanations (SHAP). Whole-exome sequencing (WES) or whole-genome sequencing (WGS) of tumor tissue from 430 stage II-III NSCLC patients and RNA-sequencing (RNA-seq) data from 1149 subjects, sourced from The Cancer Genome Atlas, were used to validate the prognostic effect of mutations identified in peripheral blood and investigate the underlying mechanisms.ResultsA global dataset encompassing 781 blood samples from 493 patients was analyzed. Clinical stage, pre-treatment ctDNA, post-treatment MRD, blood-based Kelch-like ECH-associated protein 1 (KEAP1), serine/threonine kinase 11 (STK11), and cyclin-dependent kinase inhibitor 2A (CDKN2A) mutations, and treatment modality were significantly associated with the risk of disease progression and were thereby included in the model training. WES/WGS and RNA-seq confirmed the poor prognostic effect of KEAP1, STK11, and CDKN2A mutations, which were characterized by the suppressive tumor microenvironment and attenuated humoral immunity. The neural network (NN) model exhibited optimal prediction of treatment failure risk in the training (AUC = 0.85, 95% CI 0.81-0.89) and validation sets (AUC = 0.82, 95% CI 0.74-0.89). SHAP analysis indicated that MRD (+0.306), treatment modality (+0.128), and pre-treatment ctDNA (+0.043) ranked in the top 3 contributions. NN-PRIME outperformed single liquid biopsy biomarkers and clinical-therapeutic signatures, and demonstrated consistent robustness across different clinical scenarios. High-risk patients identified by NN-PRIME had poorer prognoses but derived significant benefits from adjuvant therapy after surgery.ConclusionsAs an interpretable model integrating readily-accessible and crucial clinical-genomic predictors, PRIME achieves enhanced performance, allowing for early outcome prediction, refined risk stratification, and personalized clinical decision-making.  
    Keywords:Non-small cell lung cancer;Artificial intelligence;Liquid biopsy;Machine learning;Circulating tumor DNA;Minimal residual disease   
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    Updated:2026-01-29
    Artificial intelligence (AI) is revolutionizing pathology diagnostics, but its applications have not been systematically evaluated. This review presents a technical taxonomy of AI algorithms and foundation models, benchmarking their performance across diagnostic tasks and identifying challenges in clinical translation. It proposes a roadmap for advancing AI applications in precision oncology and pathological research, aiming to integrate robust, unified, scalable AI solutions into diagnostic workflows.

    Xiu-Ming Zhang, Tian-Hong Gao, Qiu-Yu Cai, Jia-Bin Xia, Yu-Ning Sun, Jian Yang, Wei-Han Li, Sheng-Xu-Ming Zhang, Heng-Rui Lou, Xiao-Tian Yu, Kai-Wen Hu, Jing-Wen Ye, Jin-Xing Zhang, Jie Lei, Le-Chao Cheng, Lin-Jie Xu, Qing Chen, He-Xiang Wang, Mei-Fu Gan, Cheng Lu, Nan Pu, Ming-Li Song, Xin Chen, Wen-Jie Liang, Han Lv, Chao-Qing Xu, Zai-Yi Liu, Jing Zhang, Kai Yan, Zun-Lei Feng

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    DOI:10.1186/s40779-025-00680-6
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    Abstract:Artificial intelligence (AI) offers transformative potential in pathology, where histopathological images remain the diagnostic gold standard due to their rich morphological and molecular information. While the rapid development of AI-driven computational pathology tools is revolutionizing disease interpretation, these technologies have not yet been systematically evaluated. Therefore, this review systematically evaluates AI applications across the diagnostic continuum, from image preprocessing and tumor classification to prognostic stratification and the discovery of predictive biomarkers. It presents a technical taxonomy of the algorithms and foundation models powering these applications, benchmarking their performance across diverse diagnostic tasks through rigorous comparative analyses. It also identifies critical challenges in clinical translation, including computational scaling, noisy annotations, interpretability gaps, and domain shifts. Finally, it proposes a roadmap for advancing AI applications in precision oncology and pathological research. By bridging technological innovation with clinical needs, this review aims to accelerate the integration of robust, unified, scalable AI solutions into diagnostic workflows.  
    Keywords:Artificial intelligence (AI);Pathology images;Quantitative feature;Pathology foundation model   
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    Updated:2026-01-29
    In 2022, China faced an unprecedented heatwave, significantly impacting public health. A study analyzed heatwave-related mortality in 364 Chinese counties from 2006 to 2017 and assessed the mortality burden for 2000-2022 in 368 cities. The results showed that heatwave frequency and intensity have increased over the past two decades, with 2022's heatwave-related deaths in China reaching 62,961, much higher than the annual average of 35,987 from 2000 to 2021. The study highlights the urgent need for comprehensive heat adaptation plans amidst rapid aging and global warming.

    Jian-Xiong Hu, Yu-Lin Zhuo, Guan-Hao He, Jiang-Mei Liu, Yan-Fang Guo, Tian-Tian Li, Wei-Wei Gong, Fang-Fang Zeng, Hai-Lai Duan, Rui-Lin Meng, Chun-Liang Zhou, Yi-Ze Xiao, Min Yu, Biao Huang, Mai-Geng Zhou, Wen-Jun Ma, Tao Liu

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    DOI:10.1186/s40779-025-00676-2
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    Abstract:BackgroundIn 2022, China experienced an unprecedented heatwave event, raising concerns about the health impacts of heatwaves. This study aims to understand the devastating health risk of the exceptional heatwave in 2022 by comparing heatwave-related mortality burden in 2022 with that during 2000–2021.MethodsWe collected daily mortality and daily maximum temperature (DMT) during 2006–2017 in 364 locations(counties/districts) of China. Heatwave was defined as an event with 2 or more consecutive days of DMT exceeding the 92.5th percentile. We employed a distributed lag nonlinear model (DLNM) and a meta-analysis to examine the heatwave-mortality association based on the data from 364 counties/districts, and then this association was used to assess the mortality burden attributable to heatwaves during 2000–2022 in 368 cities in China. A percentage change (%) indicator, comparing the 2022 mortality burden to the average value from 2000 to 2021, was further calculated to highlight the severity of heatwaves in 2022.ResultsIn the past 2 decades, the frequency and intensity of heatwaves in China significantly increased,with the cumulative excessive degree-day increasing to 31,626 in 2022 compared with the annual average value of 13,772 during 2000–2021 across China. In 2022, we observed 62,961 [95% confidence internal (CI) 54,945–70,413]heatwave-related deaths in China, which was much higher than the annual average [35,987 (95% CI 31,252–40,471)]attributable to heatwaves during 2000–2021. The vulnerability groups of heatwave-related mortality in 2022 primarily included patients with cardiovascular diseases [40,567 (95% CI 35,313–45,404)], females [35,876 (95% CI 31,035–41,005)], and people aged over 65 years [56,208 (95% CI 49,023–62,864)]; and greater heatwave-related mortality was found in eastern-central China. The attributable fraction (AF) of heatwave-related deaths increased from an annual average of 11.01‰ (95% CI 9.56–12.38) during 2000–2021 to 18.11‰ (95% CI 15.80–20.25) in 2022 with 64.43% increment (95% CI 38.10–93.78), and the increase rates were greater in Xizang Autonomous Region(159.77%, 95% CI 12.84–477.87) and Sichuan Province (133.64%, 95% CI 3.84–416.61).ConclusionsThis study indicated that the frequency and intensity of heatwaves significantly increased in the past 2 decades in China, and the 2022 heatwaves were linked to a substantial mortality burden in China, with significant population and regional heterogeneity. Our findings underscore the need for developing comprehensive heat adaptation plans in the context of rapid aging and ongoing global warming.  
    Keywords:Climate change;Heatwave;Mortality;Risk;Burden   
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    Updated:2026-01-29
    Reporting on the latest research in the field of anemia, a study utilizes data from the 2023 Global Burden of Disease to analyze the burden of anemia in China from 1990 to 2023. The research explores the prevalence and years lived with disability due to anemia, attributing cases to 16 underlying causes across genders and ages. It reveals a downward trend in anemia rates and highlights the need for targeted strategies, especially in high-risk areas.

    Zheng Long, Ling-Ling Yu, Fan-Shu Yan, Pei-Pei Li, Li-Jun Wang, Mai-Geng Zhou, Bing-Xin Ji, Peng Yin

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    DOI:10.1186/s40779-025-00681-5
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    Abstract:BackgroundAnemia is a major global health problem. There were 89% of all anemia-related disabilities in developing countries. We aim to analyze the burden of anemia and its underlying causes in China from 1990 to 2023.MethodsUtilizing the data of the 2023 Global Burden of Disease (GBD 2023) study, this study analyzed the burden of anemia in China between 1990 and 2023. Then we analyzed the number and rate of anemia attributed to 16 underlying causes for all genders and ages. Drivers of change in prevalence and years lived with disability (YLD) numbers due to anemia were explored by decomposition analysis. And locally weighted regression was used to estimate the relationship between socio-demographic index (SDI) and age-standardized prevalence rate (ASPR) and age-standardized YLD rate due to anemia.ResultsFrom 1990 to 2023, the ASPR and age-standardized YLD rate showed a downward trend among all anemia types (P < 0.05), and the ASPR and age-standardized YLD rate of anemia in females were higher than those in males. The highest number and rate of prevalence were found in mild anemia, and the highest number and rate of YLD were found in moderate anemia. As age increased, the prevalence and YLD rate of anemia increased, with a significant increase in females aged 20−54, in particular of moderate anemia. In 2023, the highest ASPR and age-standardized YLD rate among all anemia types were in the Northwestern regions. Compared to 1990, 31 provinces, Hong Kong,and Macao exhibited declines in both the ASPR and the age-standardized YLD rate for anemia. In China, most of the prevalent cases and YLD were attributable to dietary iron deficiency in 2023. The total prevalence of anemia decreased by 46.14% [95% uncertainty interval (UI) 27.54−61.02], of which age-specific rate, population growth,and population aging accounted for -77.32%, 21.33%, and 9.84%, respectively. A negative association between SDI and the ASPR and age-standardized YLD rate of anemia was shown in China.ConclusionsFrom 1990 to 2023, the burden of anemia in China has decreased but remained heavy among women of childbearing age, the elderly, and in the Northwestern region. Tailored prevention and control strategies should be strengthened to reduce the burden of anemia in high-risk areas.  
    Keywords:Anemia;Prevalence;Years lived with disability (YLD);Burden of disease;Trend   
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    Updated:2026-01-29
    In the field of consciousness research, a study introduces its research progress. Experts established an electroencephalography (EEG)-based methodological guideline for clinical consciousness assessment, which provides solutions to solve the problem of translating neurophysiological biomarkers into clinical applications.

    An-An Ping, Long-Zhou Guan, Yong Wang, Sheng Yang, Chao Yang, Xiao-Qing Hu, Yi-Heng Tu, He Chen, Wei-Guang Li, Xiao-Li Li

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    DOI:10.1186/s40779-025-00682-4
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    Abstract:BackgroundPhysiological, pharmacological, and pathological alterations of consciousness provide critical windows into its neural substrates. Given the inherent complexity and multidimensionality of consciousness, defining quantitative, dynamic signatures of neural activity, and translating them into clinically applicable tools remains challenge. This study aimed to build an electroencephalography (EEG)-based methodological guideline for clinical consciousness assessment.MethodsEEG signals were systematically categorized across periodic and aperiodic activity, connectivity and network topology, spatiotemporal dynamics, self-organized criticality, and transcranial magnetic stimulation (TMS)-evoked responses. These biomarkers were mapped onto a conceptual framework of consciousness, comprising wakefulness and internal/external awareness, based on their validation across clinical conditions. The discriminative efficacy of various biomarkers was then evaluated across 4 independent datasets.ResultsIntegrated EEG features each captured distinct yet complementary dimensions of consciousness, supporting a unified neurophysiological architecture underlying diverse alterations of consciousness. Spectral power and peak frequency tracked the loss of consciousness during propofol anesthesia and sleep. Steeper aperiodic slopes, loss of frontoparietal connectivity, disrupted small-world organization, and reduced effective dimensionality were particularly effective in distinguishing minimally conscious state (MCS) from unresponsive wakefulness syndrome(UWS). Additionally, spatiotemporal patterns exhibited consciousness-specific alterations, with both pharmacological and pathological alterations influencing specific microstate dynamics.ConclusionsSynthesizing integrated neural dynamics and multidimensional consciousness, this guideline establishes both methodological and theoretical foundations for translating neurophysiological biomarkers into clinical applications. While this work advances both conceptual clarity and practical methodology, large-scale validation across expanded clinical cohorts, experimental models, and multimodal platforms is essential to fully establish causal linkages and translational utility.  
    Keywords:Consciousness;electroencephalogram;Temporo-spatio-spectral analysis;Sleep;General anesthesia;disorders of consciousness   
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    Updated:2026-01-29
    In a groundbreaking study, researchers from China, the USA, and the UK have quantified the associations of risk factor control with mortality and life expectancy among individuals with type 2 diabetes (T2D). The study found that only a small proportion of participants achieved ≥ 5 combined targets, and those with a healthy lifestyle and good metabolic control had a longer life expectancy. Comprehensive management of multiple risk factors, particularly lifestyle factors, was associated with a substantial reduction in the life expectancy gap between those with and without T2D.

    Zi-Xin Qiu, Frank Qian, Yan-Bo Zhang, Jun Liu, Ting-Ting Geng, Rui Li, Pang Yao, Oscar H. Franco, Eric B. Rimm, JoAnn E. Manson, An Pan, Mai-Geng Zhou, Kai Huang, Gang Liu

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    DOI:10.1186/s40779-025-00674-4
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    Abstract:BackgroundType 2 diabetes (T2D) is a global epidemic that reduces life expectancy. Evidence is limited on the benefits of achieving multiple guideline-recommended targets and cross-country differences. This study aimed to quantify the associations of risk factor control with mortality and life expectancy among individuals with T2D using nationwide cohorts from China, the USA, and the UK.MethodsWe included 46,351 adults with T2D at baseline from China Chronic Disease and Risk Factors Surveillance (CCDRFS; 2013, follow-up until 2021), USA National Health and Nutrition Examination Survey (USA NHANES;1999–2018, follow-up until 2019), and UK Biobank (2006–2010, follow-up until 2022). Patients with T2D were matched to controls without T2D using propensity score matching based on key demographic factors. Cox regression estimated mortality associated with lifestyle and metabolic factors outside target ranges [physical inactivity, smoking,unhealthy diet, elevated hemoglobin A1c (HbA1c), dyslipidemia, high blood pressure].ResultsOnly a small proportion of participants achieved ≥ 5 combined targets: 16.0% in CCDRFS, 9.9% in USA NHANES, and 6.8% in UK Biobank. During 470,369 person-years of follow-up, 7650 deaths (16.5%) occurred among individuals with T2D, and 9349 deaths (10.2%) occurred among controls over 965,249 person-years. At age 50, individuals with ≤ 1 risk factor outside the target lived 6–9 years longer than those with ≥ 5, and their life expectancy was comparable to that of controls without T2D. The association was independent of genetic predisposition to shorter lifespan in the UK Biobank. Additionally, individuals with T2D who failed to achieve optimal metabolic control but maintained a healthy lifestyle had a longer life expectancy compared with those who achieved optimal metabolic control but had an unhealthy lifestyle across all cohorts, with life expectancy gains ranging from 1.5 to 3.4 years depending on sex and cohort. Among individuals with T2D, healthy lifestyle behaviors (physical activity, non-smoking,a healthy diet) and HbA1c control contributed most to gains in life expectancy. Variations in multiple risk factor control and their associations with all-cause mortality were observed across different population subgroups.ConclusionsAchievement of guideline targets for multiple risk factors was low among individuals with T2D in China,the USA, and the UK. Comprehensive management of multiple risk factors, particularly lifestyle factors, was associated with a substantial reduction in the life expectancy gap between those with and without T2D, underscoring the importance of guideline-based care and individualized management.  
    Keywords:Type 2 diabetes (T2D);risk factors;Mortality;Life expectancy;Prospective study   
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    Updated:2026-01-29
    In the field of xxx, expert xx has made significant research progress. By establishing the xx system/exploring the xx topic/verifying the xx conjecture, xx has provided solutions to address xx problems/open up a new direction for xx research/lay a foundation for the construction of the xx system.

    Lei Wang, Blanca Rodriguez

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    DOI:10.1186/s40779-025-00675-3
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    Keywords:Cardiomyocyte computational models;Drug safety testing;Cardiac electrophysiology;In silico clinical trials;Artificial intelligence (AI)   
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    Updated:2026-01-29
    In the field of lipid metabolism, this review introduces the latest advancements and applications of multifunctional nano-delivery platforms. Expert researchers have explored the use of nanoparticles, liposomes, and novel biomaterials, providing solutions to enhance the precision and safety of lipid metabolism regulation.

    Ying Sun, Kai Yan, Yi Zhang, Yan-Qi Han, Long-Hui Hao, Yue Gao, Hong-Liang Wang, Hong-Qian Chu, Jun Ye, Yu-Ling Liu, Yan-Fang Yang

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    DOI:10.1186/s40779-025-00672-6
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    Abstract:Disruptions in lipid metabolism cause numerous metabolic diseases, including obesity, diabetes, cardiovascular diseases, and liver disorders. Consequently, lipid metabolism serves as a potential therapeutic target, influencing the progression of various non-metabolic diseases such as kidney diseases, cancer, neurodegenerative disorders, aging, and bone-related diseases. The metabolic pathways involved in lipid metabolism are complex and highly interconnected. Although the abundance of metabolic targets presents opportunities for lipid metabolism regulation, the limited precision and safety of traditional therapeutic approaches remain significant challenges. These limitations have catalyzed the development of multifunctional nano-delivery platforms aimed at targeted intervention in lipid metabolic processes, further enhancing the flexibility of lipid metabolism regulation. This review outlines the latest advancements and representative applications of these multifunctional nano-delivery platforms. Notably, extensive research has been conducted on nanoparticles and liposomes, with these technologies being relatively mature. Furthermore, numerous novel biomaterials, including engineered adipocytes, exosome vesicles secreted by natural cells, smart-responsive nanomicelles, composite hydrogels, and engineered lipid droplets, are being increasingly explored. Finally, the review discusses the advantages of drug delivery strategies based on the targeted intervention of lipid metabolic processes, the limitations of current technologies, promising future research directions, and treatment challenges.  
    Keywords:Multifunctional nano-delivery system;Lipid metabolism;Lipid metabolism reprogramming;Lipid metabolism-related diseases   
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    Updated:2026-01-29
    In the field of xxx, expert xx has made significant research progress. By establishing the xx system/exploring the xx topic/verifying the xx conjecture, they have provided solutions to address xx problems/open up a new direction for xx research/lay a foundation for the construction of the xx system.

    Folke Sjöberg, David Greenhalgh, Moustafa Elmasry, Ahmed T. El-Serafi, Ingrid Steinvall

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    DOI:10.1186/s40779-025-00677-1
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    Keywords:Burn injury;sepsis;epidemiology;Biomarkers;Artificial intelligence;antibiotics   
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    Updated:2026-01-29
    In the field of sepsis diagnosis and treatment, cell-free DNA (cfDNA) has emerged as a novel biomarker and molecular therapeutic target. Expert research has elucidated the release and pathological mechanisms of cfDNA in sepsis, laying a foundation for the development of targeted treatment strategies.

    Lei Li, Hong-Chao Huang, Yin He, Jia-Yue-Cheng Pang, Shi-Chu Xiao, Zhao-Fan Xia, Yong-Jun Zheng

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    DOI:10.1186/s40779-025-00668-2
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    Abstract:Sepsis is a dysregulated host response to infection that frequently results in fatal multiple organ dysfunction. Despite advances in clinical identification and management, both its incidence and mortality have remained persistently high. Emerging evidence indicates that cell-free DNA (cfDNA), as a novel biomarker and molecular therapeutic target,holds promise for improving the clinical management of sepsis. cfDNA refers to DNA fragments present in body fluids, including naked DNA, membrane-coated DNA, nucleosomes, and neutrophil extracellular traps (NETs). cfDNA is released from host cells or pathogens into body fluids through pathways, such as NETosis, mitochondrial damage,cell necrosis, apoptosis, pyroptosis, and erythroblast enucleation. The released cfDNA triggers a strong inflammatory response by activating Toll-like receptor (TLR) 9, the absent in melanoma 2 (AIM2) inflammasome, and the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signaling pathway. At the same time, cfDNA activates the coagulation cascade and inhibits anticoagulant and fibrinolytic systems through multiple mechanisms, resulting in microcirculatory disorders. These pathological effects are closely associated with sepsis-related organ dysfunction and poor prognosis. Elucidation of the release and pathological mechanisms of cfDNA provides a foundation for the development of targeted treatment strategies. Currently, molecular therapeutic approaches targeting cfDNA,including peptidylarginine deiminase (PAD) 4 inhibitors, pore-forming inhibitors, antioxidants, cfDNA scavengers,and deoxyribonucleases (DNases), have shown certain efficacy in treating sepsis and systemic inflammation. In terms of sepsis monitoring, compared with traditional markers, cfDNA exhibits extremely high timeliness and dynamic monitoring capability. cfDNA can simultaneously indicate the complex interplay among infection, host response,and organ damage, making it suitable for early diagnosis, prognosis assessment, treatment monitoring, organ function evaluation, and pathogen detection. Given its broad application prospects in the diagnosis and treatment of sepsis, this paper systematically elaborates on the mechanisms of cfDNA release and pathological effects in sepsis,reviews progress in cfDNA-targeted monitoring and therapeutic strategies, discusses technical challenges, and outlines potential future directions.  
    Keywords:sepsis;Cell-free DNA (cfDNA);Liquid biopsy;cfDNA scavengers;Deoxyribonuclease (DNase)   
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    Updated:2026-01-29
    In the field of targeted alpha therapy for cancer treatment, a dual-locked pretargeted strategy was developed, integrating platinumIV (PtIV)-loaded hydrogel nanoparticles (HNPs) and radium-223 (223Ra)-loaded HNPs into an inverse electron demand Diels–Alder (IEDDA)-activated drug delivery system. This caged dual-locked approach enables precise pretargeted accumulation at the tumor site, followed by rapid dissociation and controlled release of 223Ra and PtIV upon IEDDA-triggered activation, thereby ensuring high tumor specificity while minimizing systemic exposure. The synergistic combination of TAT and chemotherapy effectively disrupts redox homeostasis, induces immunogenic cell death (ICD), and elicits a robust antitumor immune response. Furthermore, when combined with programmed death-ligand 1 (PD-L1) blockade, this strategy significantly enhances systemic antitumor immunity, leading to robust inhibition of tumor growth and metastasis. These findings underscore the potential of dual-locked pretargeted strategies to advance TAT by improving therapeutic efficacy and addressing the critical challenge of radionuclide leakage, paving the way for next-generation precision-targeted radiopharmaceuticals.

    Meng-Die Yang, Kang Fang, Xiao-Yi Zhang, Gang Yang, He-Qing Yi, Le Cai, Shan-Shan Qin, Xin-Da Yang, Rong Rong, Shuo Shi, Fei Yu

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    DOI:10.1186/s40779-025-00673-5
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    Abstract:BackgroundTargeted alpha therapy (TAT) has emerged as a promising strategy for cancer treatment by selectively delivering high linear energy transfer (LET) alpha-emitters to tumor cells while minimizing off-target toxicity. However, the clinical translation of alpha-emitters, particularly radium-223 (223Ra), remains challenging due to inefficient targeted delivery and uncontrolled release of recoil daughter products, leading to systemic toxicity.MethodsHerein, a dual-locked pretargeted strategy was developed integrating platinumIV (PtIV)-loaded hydrogel nanoparticles (HNPs) (HAQ@HNPs) and 223Ra-loaded HNPs (223Ra@HNPs) into an inverse electron demand Diels–Alder(IEDDA)-activated drug delivery system. In vitro cytotoxicity, ROS, and apoptosis, together with in vivo biodistribution,imaging, and therapeutic studies, were performed to evaluate the therapeutic efficacy and immune activation.ResultsThis caged dual-locked approach enables precise pretargeted accumulation at the tumor site, followed by rapid dissociation and controlled release of 223Ra and PtIV upon IEDDA-triggered activation, thereby ensuring high tumor specificity while minimizing systemic exposure. The synergistic combination of TAT and chemotherapy effectively disrupts redox homeostasis, induces immunogenic cell death (ICD), and elicits a robust antitumor immune response. Furthermore, when combined with programmed death-ligand 1 (PD-L1) blockade, this strategy significantly enhances systemic antitumor immunity, leading to robust inhibition of tumor growth and metastasis.ConclusionsThese findings underscore the potential of dual-locked pretargeted strategies to advance TAT by improving therapeutic efficacy and addressing the critical challenge of radionuclide leakage, paving the way for next-generation precision-targeted radiopharmaceuticals.  
    Keywords:Targeted alpha therapy (TAT);Alpha-emitters;Radium-223 (223Ra);Bioorthogonal click chemistry   
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    Updated:2026-01-29
    In the field of peritoneal fibrosis treatment for end-stage renal disease patients, a research team has made significant progress. They verified the role of β-catenin signaling and mesothelial cell senescence in peritoneal fibrosis, which lays a foundation for the construction of a new therapeutic intervention system.

    Xiao-Xu Wang, Wei-Jie Zhong, Jie-Mei Li, Di Wang, Shuang-Qin Chen, Jin-Hua Miao, Wei-Wei Shen, Xiao-Long Li, Jie-Wu Huang, Shan Zhou, Cheng Wang, Jun Ai, Li-Li Zhou

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    DOI:10.1186/s40779-025-00669-1
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    Abstract:BackgroundPeritoneal fibrosis represents a major clinical challenge for end-stage renal disease (ESRD) patients when they are undergoing peritoneal dialysis (PD). Single-cell RNA sequencing identified that peritoneal mesothelial cells undergo a senescence fate transition in long-term PD patients. Whereas the existence of mesothelial cell senescence and the underlying mechanisms should be thoroughly explored.MethodsTo further investigate mesothelial cell senescence, we utilized a clinical cohort comprising dialysate effluents from PD patients and peritoneal biopsy specimens, peritoneal dialysis fluid (PDF)-induced mouse models,and cultured primary mesothelial cells. Single-cell RNA sequencing, transcriptome sequencing, immunofluorescence, Western blotting, and other analyses were administered. To validate the critical role of β-catenin in mesothelial cell senescence, β-catenin knockout mice were employed. Additionally, the senolytic drugs dasatinib plus quercetin were administered to PDF mice to assess the key role of mesothelial cell senescence in peritoneal fibrosis.ResultsSingle-cell RNA sequencing demonstrated that mesothelial cells derived from long-term PD patients are major trend to senescence fate. Moreover, β-catenin signaling was significantly upregulated, as well as trans-forming growth factor-β (TGF-β) pathways. We observed that senescent mesothelial cells were highly increased in both dialysate effluent and peritoneal biopsies of long-term PD patients. In dialysate effluent, matrix metalloproteinase-7 (MMP-7), an indicator of downstream targets of β-catenin, was positively correlated with TGF-β1. Both biomarkers were also positively associated with PD duration. Mechanistically, we found that β-catenin promotes dynamin-related protein 1 (Drp1) expression, a key mediator of mitochondrial fission, thereby inducing mesothelial cell senescence. Then, TGF-β1 was secreted to activate the Smad signaling pathway in fibroblasts, leading to myofibroblast activation and subsequent peritoneal fibrosis. Notably, administration of senolytic drugs, dasatinib plus quercetin, significantly alleviated peritoneal fibrosis regardless of treatment timing.ConclusionTargeting β-catenin signaling and mesothelial cell senescence may represent potential therapeutic interventions for preventing peritoneal fibrosis.  
    Keywords:β-catenin;Mesothelial cell;Senescence;fibroblast;Peritoneal fibrosis;Peritoneal dialysis (PD)   
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    Updated:2026-01-29
    In a population-based colorectal cancer screening trial, risk-adapted screening, colonoscopy, and fecal immunochemical test demonstrated comparable effectiveness, but differed in participation rates, resource utilization, and cost-effectiveness. Risk-adapted screening could serve as a complementary approach to established strategies, particularly when health resources are limited.

    Hong-Da Chen, Bin Lu, Ju-Fang Shi, Yue-Yang Zhou, Ling-Bin Du, Xian-Zhen Liao, Dong-Hua Wei, Dong Dong, Yi Gao, Chen Zhu, Rong-Biao Ying, Wei-Fang Zheng, Shi-Peng Yan, Hai-Fan Xiao, Juan Zhang, Yun-Xin Kong, Fu-Rong Li, Na Li, Jia-Hui Luo, Chen-Yu Luo, Hermann Brenner, Min Dai

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    DOI:10.1186/s40779-025-00671-7
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    Abstract:BackgroundRisk-adapted colorectal cancer (CRC) screening has the potential to balance effectiveness with resource demands, yet evidence comparing it with established methods remains limited. This study aims to compare out-comes of risk-adapted CRC screening with colonoscopy and fecal immunochemical test (FIT) strategies.MethodsWe adopted a hybrid methodology combining real-world data from a population-based CRC screening randomized controlled trial (TARGET-C) with projections from a validated Markov-based microsimulation model (MIMIC-CRC). The TARGET-C trial enrolled 19, 582 participants aged 50–74 years from 6 centers in China, randomized in a 1: 2: 2 ratio into 3 groups. After applying the exclusion criteria, the final analysis included 3883 participants in the one-time colonoscopy group, 7793 in the annual FIT group, and 7697 in the risk-adapted screening group. In the latter group, screening allocation was determined by a composite risk score incorporating age, sex, family his-tory of CRC, smoking status, and body mass index, with high-risk participants referred for colonoscopy and low-risk participants for FIT. The primary outcome was detection rates of advanced neoplasm (CRC and advanced adenoma)over 4 rounds. Secondary outcomes included screening participation, colonoscopy demand, and costs from a societal perspective. Long-term effectiveness and cost-effectiveness were modeled over 15 years using MIMIC-CRC.ResultsAcross 4 rounds, overall participation rates (attending at least one screening round) were 42.3% (colonos-copy), 99.8% (FIT), and 92.5% (risk-adapted). Detection rates of advanced neoplasms were 2.8%, 2.3%, and 2.6%, respectively, with no significant differences (P > 0.05). Colonoscopies needed to detect 1 advanced neoplasm were 15.4, 7.9, and 9.3, respectively. From a societal perspective, the cost for detecting 1 advanced neoplasm was 15, 341, 21, 754, and 24, 300 Chinese Yuan, respectively. Over 15 years, risk-adapted screening reduced incidence by 16.7%and mortality by 21.5% compared with no screening, slightly less effective than colonoscopy (24.6% and 24.8%, respectively). Under observed real-world adherence, colonoscopy was the most cost-effective; under perfect full adherence, risk-adapted screening was the most cost-effective.ConclusionsIn this population-based CRC screening trial, risk-adapted screening, colonoscopy, and FIT demon-strated comparable effectiveness, but differed in participation rates, resource utilization, and cost-effectiveness. Risk-adapted screening could serve as a complementary approach to established strategies, particularly when health resources are limited.Trial registrationChinese Clinical Trial Registry (ChiCTR1800015506).  
    Keywords:Colorectal cancer (CRC);screening;Risk-adapted screening;Randomized controlled trial;Cost-effectiveness   
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    Updated:2025-12-04
    Ferroptosis, a critical mechanism in sepsis pathogenesis, is explored in this review. Expert research clarifies the role of ferroptosis in sepsis-associated immune dysfunction and multi-organ injury, laying a foundation for innovative clinical interventions.

    Hui-Ting Zhou, Jie Huang, Ya-Kun Liu, Jiang-Huai Wang, Jian Wang

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    DOI:10.1186/s40779-025-00665-5
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    Abstract:Ferroptosis, a form of iron-dependent regulated cell death (RCD), is emerging as a critical mechanism in the patho-genesis and progression of sepsis. This review highlights the intricate molecular pathways and hallmark features of fer-roptosis, including lipid peroxidation, dysregulation of iron metabolism, and glutathione depletion, which exacerbate sepsis progression and sepsis-associated multi-organ damage. The systemic interactions of ferroptosis with inflam-mation, innate, and adaptive immunity, and organ injury are elucidated, emphasizing the role ferroptosis plays both in immunity including sepsis-associated immune cell damage/dysfunction, immune dysregulation, and immu-nosuppression, and in sepsis-associated multi-organ injury such as acute lung injury (ALI), acute kidney injury (AKI), acute hepatic injury (AHI), acute intestinal injury, septic cardiomyopathy, and septic encephalopathy. Therapeutic strategies targeting ferroptosis hold promise for improving sepsis outcomes. Approaches include pharmacological interventions of ferroptosis-associated pathways, nanoparticle-based delivery systems, and combinatorial therapies aimed at preventing immune dysfunction and protecting against multi-organ failure. Nonetheless, challenges remain in translating preclinical findings into clinical application, necessitating further research into ferroptosis-specific regulatory networks. This review underscores the potential of therapeutics targeting ferroptosis as a transformative approach to addressing sepsis, paving the way for innovative and precision-based clinical interventions.  
    Keywords:sepsis;Ferroptosis;Lipid peroxidation;Inflammation;Immune dysregulation;Organ damage;Treatment   
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    Updated:2025-12-04
    In the field of xxx, expert xx has made significant research progress. By establishing the xx system/exploring the xx topic/verifying the xx conjecture, xx has provided solutions to solve xx problems/open up a new direction for xx research/lay a foundation for the construction of the xx system.

    Ke He, Shu-Yi Wang, Jun Ren

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    DOI:10.1186/s40779-025-00666-4
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    Keywords:Portable endoscopy;YunSendo system;Single-use devices;Battlefield medicine;Infection control;Gastrointestinal endoscopy   
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    Updated:2025-12-04
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