Biomimetic-Structured Cobalt Nanocatalyst Suppresses Aortic Dissection Progression by Catalytic Antioxidation.

As one of the most lethal cardiovascular diseases, aortic dissection (AD) is initiated by overexpression of reactive oxygen species (ROS) in the aorta that damages the vascular structure and finally leads to massive hemorrhage and sudden death. Current drugs used in clinics for AD treatment fail to efficiently scavenge ROS to a large extent, presenting undesirable therapeutic effect. In this work, a nanocatalytic antioxidation concept has been proposed to elevate the therapeutic efficacy of AD by constructing a cobalt nanocatalyst with a biomimetic structure that can scavenge pathological ROS in an efficient and sustainable manner. Theoretical calculations demonstrate that the antioxidation reaction is catalyzed by the redox transition between hydroxocobalt(III) and oxo-hydroxocobalt(V) accompanied by inner-sphere proton-coupled two-electron transfer, forming a nonassociated activation catalytic cycle. The efficient antioxidation action of the biomimetic nanocatalyst in the AD region effectively alleviates oxidative stress, which further modulates the aortic inflammatory microenvironment by promoting phenotype transition of macrophages. Consequently, vascular smooth muscle cells are also protected from inflammation in the meantime, suppressing AD progression. This study provides a nanocatalytic antioxidation approach for the efficient treatment of AD and other cardiovascular diseases.

Sex-based outcomes after thoracic endovascular aortic repair: a systematic review and meta-analysis.

OBJECTIVE: As it remains unclear whether there are sex-based differences in clinical outcomes after thoracic endovascular aortic repair (TEVAR), this meta-analysis aimed to evaluate differences in early outcomes and overall survival between female and male patients who underwent TEVAR. METHODS: The PubMed, Embase, Web of Science, and Cochrane Central databases were searched for eligible studies published through June 10, 2023, that reported sex-based differences in clinical outcomes after TEVAR. The primary outcome was operative mortality; second outcomes included stroke, spinal cord ischemia, acute kidney injury, hospital length of stay, and overall survival. Patient characteristics, operative data, and early outcomes were aggregated using the random-effects model, presenting pooled risk ratio (RR) or standardized mean difference along with their corresponding 95% confidence intervals (CIs). Overall survival was assessed by reconstructing individual patient data to generate sex-specific pooled Kaplan-Meier curves. This study was registered in PROSPERO (CRD42023426069). RESULTS: Of the 1785 studies retrieved, 14 studies met all eligibility criteria, encompassing a total of 17,374 patients, comprising 5026 female and 12,348 male patients. Female patients were older, had a smaller maximum aortic diameter, had lower rates of smoking and coronary artery disease, and had higher rates of anemia. Intraoperatively, female patients were more likely to use iliac conduits and require blood transfusions. There were no sex-based differences in operative mortality (RR: 1.12, 95% CI: 0.90-1.40; P = .309), stroke (RR: 1.14, 95% CI: 0.95-1.38; P = .165), spinal cord ischemia (RR: 1.33, 95% CI: 0.83-2.14; P = .234), acute kidney injury (RR: 0.78, 95% CI: 0.52-1.17; P = .228), and hospital length of stay (standardized mean difference: 0.09, 95% CI: -0.03 to 0.20; P = .141). Pooled Kaplan-Meier estimates showed a worse overall survival in female patients compared with male patients (87.2% vs 89.8% at 2 years, log-rank P = .001). CONCLUSIONS: Among patients treated by TEVAR, female sex was not associated with increased risk of operative mortality or major morbidity. However, female patients exhibited a lower overall survival after TEVAR compared with male patients.

PB-LNet: a model for predicting pathological subtypes of pulmonary nodules on CT images.

OBJECTIVE: To investigate the correlation between CT imaging features and pathological subtypes of pulmonary nodules and construct a prediction model using deep learning. METHODS: We collected information of patients with pulmonary nodules treated by surgery and the reference standard for diagnosis was post-operative pathology. After using elastic distortion for data augmentation, the CT images were divided into a training set, a validation set and a test set in a ratio of 6:2:2. We used PB-LNet to analyze the nodules in pre-operative CT and predict their pathological subtypes. Accuracy was used as the model evaluation index and Class Activation Map was applied to interpreting the results. Comparative experiments with other models were carried out to achieve the best results. Finally, images from the test set without data augmentation were analyzed to judge the clinical utility. RESULTS: Four hundred seventy-seven patients were included and the nodules were divided into six groups: benign lesions, precursor glandular lesions, minimally invasive adenocarcinoma, invasive adenocarcinoma Grade 1, Grade 2 and Grade 3. The accuracy of the test set was 0.84. Class Activation Map confirmed that PB-LNet classified the nodules mainly based on the lungs in CT images, which is in line with the actual situation in clinical practice. In comparative experiments, PB-LNet obtained the highest accuracy. Finally, 96 images from the test set without data augmentation were analyzed and the accuracy was 0.89. CONCLUSIONS: In classifying CT images of lung nodules into six categories based on pathological subtypes, PB-LNet demonstrates satisfactory accuracy without the need of delineating nodules, while the results are interpretable. A high level of accuracy was also obtained when validating on real data, therefore demonstrates its usefulness in clinical practice.

Detection of the freshness of rice by chemiluminescence.

Reactive oxygen species (ROS) are usually produced in rice under aerobic environmental conditions, resulting in peroxidative changes in polyunsaturated fatty acids, and affecting the deterioration of rice during storage. In addition, as an important enzyme that participates in removing ROS, peroxidase is also present in rice, and takes part in protecting rice from attack by ROS. Moreover, loss of peroxidase activity may give rise to rice deterioration during storage. Therefore, measuring peroxidase activity makes it possible to ascertain the freshness of rice. In addition, peroxidase can also catalyze the luminol-hydrogen peroxide system. Based on this, in this work we established a new chemiluminescence (CL) method that was used to detect the freshness of stored rice. Under optimal experimental conditions, we showed that the freshness of rice can be measured using this CL method. This study is the first to detect the freshness of rice using a CL method, opening up a novel direction for the application of CL.

Distributed Formation Control of Multi-Robot Systems with Path Navigation via Complex Laplacian.

This paper focuses on the formation control of multi-robot systems with leader-follower network structure in directed topology to guide a system composed of multiple mobile robot agents to achieve global path navigation with a desired formation. A distributed linear formation control strategy based on the complex Laplacian matrix is employed, which enables the robot agents to converge into a similar formation of the desired formation, and the size and orientation of the formation are determined by the positions of two leaders. Additionally, in order to ensure that all robot agents in the formation move at a common velocity, the distributed control approach also includes a velocity consensus component. Based on the realization of similar formation control of a multi-robot system, the path navigation algorithm is combined with it to realize the global navigation of the system as a whole. Furthermore, a controller enabling the scalability of the formation size is introduced to enhance the overall maneuverability of the system in specific scenarios like narrow corridors. The simulation results demonstrate the feasibility of the proposed approach.

Monitoring and Visualization of Crystallization Processes Using Electrical Resistance Tomography: CaCO3 and Sucrose Crystallization Case Studies.

In the current research work, electrical resistance tomography (ERT) was employed for monitoring and visualization of crystallization processes. A first-of-its-kind MATLAB-based interactive GUI application "ERT-Vis" is presented. Two case studies involving varied crystallization methods were undertaken. The experiments were designed and performed involving calcium carbonate reactive (precipitative) crystallization for the high conductivity solution-solute media, and the cooling crystallization of sucrose representing the lower conductivity solution-solute combination. The software successfully provided key insights regarding the process in both crystallization systems. It could detect and separate the solid concentration distributions in the low as well as high conductivity solutions using the visual analytics tools provided. The performance and utility of the software were studied using a software evaluation case study involving domain experts. Participant feedback indicated that ERT-Vis software helps by reconstructing images instantaneously, interactively visualizing, and evaluating the output of the crystallization process monitoring data.

Finite-Time Pinning Synchronization Control for T-S Fuzzy Discrete Complex Networks with Time-Varying Delays via Adaptive Event-Triggered Approach.

This paper is concerned with the adaptive event-triggered finite-time pinning synchronization control problem for T-S fuzzy discrete complex networks (TSFDCNs) with time-varying delays. In order to accurately describe discrete dynamical behaviors, we build a general model of discrete complex networks via T-S fuzzy rules, which extends a continuous-time model in existing results. Based on an adaptive threshold and measurement errors, a discrete adaptive event-triggered approach (AETA) is introduced to govern signal transmission. With the hope of improving the resource utilization and reducing the update frequency, an event-based fuzzy pinning feedback control strategy is designed to control a small fraction of network nodes. Furthermore, by new Lyapunov-Krasovskii functionals and the finite-time analysis method, sufficient criteria are provided to guarantee the finite-time bounded stability of the closed-loop error system. Under an optimization condition and linear matrix inequality (LMI) constraints, the desired controller parameters with respect to minimum finite time are derived. Finally, several numerical examples are conducted to show the effectiveness of obtained theoretical results. For the same system, the average triggering rate of AETA is significantly lower than existing event-triggered mechanisms and the convergence rate of synchronization errors is also superior to other control strategies.

Supporting Visualization Analysis in Industrial Process Tomography by Using Augmented Reality-A Case Study of an Industrial Microwave Drying System.

Industrial process tomography (IPT) based process control is an advisable approach in industrial heating processes for improving system efficiency and quality. When using it, appropriate dataflow pipelines and visualizations are key for domain users to implement precise data acquisition and analysis. In this article, we propose a complete data processing and visualizing workflow regarding a specific case-microwave tomography (MWT) controlled industrial microwave drying system. Furthermore, we present the up-to-date augmented reality (AR) technique to support the corresponding data visualization and on-site analysis. As a pioneering study of using AR to benefit IPT systems, the proposed AR module provides straightforward and comprehensible visualizations pertaining to the process data to the related users. Inside the dataflow of the case, a time reversal imaging algorithm, a post-imaging segmentation, and a volumetric visualization module are included. For the time reversal algorithm, we exhaustively introduce each step for MWT image reconstruction and then present the simulated results. For the post-imaging segmentation, an automatic tomographic segmentation algorithm is utilized to reveal the significant information contained in the reconstructed images. For volumetric visualization, the 3D generated information is displayed. Finally, the proposed AR system is integrated with the on-going process data, including reconstructed, segmented, and volumetric images, which are used for facilitating interactive on-site data analysis for domain users. The central part of the AR system is implemented by a mobile app that is currently supported on iOS/Android platforms.

Affective Colormap Design for Accurate Visual Comprehension in Industrial Tomography.

The design of colormaps can help tomography operators obtain accurate visual comprehension, thereby assisting safety-critical decisions. The research presented here is about deploying colormaps that promote the best affective responses for industrial microwave tomography (MWT). To answer the two research questions related to our study, we firstly conducted a quantitative analysis of 11 frequently-used colormaps on a segmentation task. Secondly, we presented the same colormaps within a crowdsourced study comprising two parts to verify the quantitative outcomes. The first part encoded affective responses from participants into a prevailing four-quadrant valence-arousal grid; the second part recorded participant ratings towards the accuracy of each colormap on MWT segmentation. We concluded that three colormaps are the best suited in the context of MWT tasks. We also found that the colormaps triggering emotions in the positive-exciting quadrant can facilitate more accurate visual comprehension than other affect-related quadrants. A synthetic colormap design guideline was consequently proposed.

Validation of prognostic accuracy of the SOFA score, SIRS criteria, and qSOFA score for in-hospital mortality among cardiac-, thoracic-, and vascular-surgery patients admitted to a cardiothoracic intensive care unit.

SEPSIS-3 DEFINITION: Sepsis is defined as life-threatening organ dysfunction due to a dysregulated host response to infection. The clinical criteria of sepsis include organ dysfunction, which is defined as an increase of two points or more on the sequential organ failure assessment (SOFA). For patients with infection, an increase of 2 SOFA points yields an overall mortality rate of 10%. Patients with suspected infection who are likely to have a prolonged intensive care unit (ICU) stay or to have in-hospital mortality can be promptly identified at the bedside with a quick SOFA (qSOFA) score of 2 or higher. IMPORTANCE: The sepsis-3 criteria have emphasized the value of a change of two or more points on the SOFA, introduced the qSOFA, and removed the systemic inflammatory response syndrome (SIRS) criteria from the sepsis definition. OBJECTIVE: To externally validate and assess the discriminatory capacities of an increase in the SOFA score by two or more points, the presence of two or more SIRS criteria, or a qSOFA score of 2 or more points for outcomes in 5109 patients, the vast majority of whom were postcardiac surgery patients who were admitted to a Cardiothoracic Surgical ICU in Singapore. DESIGN, SETTING, AND PARTICIPANTS: A retrospective cohort analysis of 5109 patients with an infection-related primary admission diagnosis in the cardiothoracic intensive care unit (CTICU) at the National University Hospital (NUH) in Singapore from 2010 to 2016. EXPOSURES: The SOFA, qSOFA, and SIRS criteria were applied to the data representing the worst condition within 24 hours of ICU admission. MAIN OUTCOMES AND MEASURES: The primary outcome was in-hospital mortality. Discrimination was assessed using the area under the receiver operating characteristic curve (AUROC). RESULTS: In 5109 patients, the average mortality of patients with an increase in the SOFA scores of less than 2 points was 3.5% (n = 64), and it was 6% (n = 199) for those with an increase in the SOFA scores of 2 or more points. The mortality of patients with an increase in the qSOFA scores of less than 2 points was 2.6% (n = 7), and it was 5.3% (n = 256) for those with an increase in the qSOFA scores of 2 or more points. The mortality of patients with an increase in the SIRS criteria of less than 2 points was 3.6% (n = 30), and it was 5.4% (n = 233) for those with an increase in the SIRS criteria of 2 or more points. The AUROC of in-hospital mortality of patients with an increase in the SOFA, qSOFA, and SIRS criteria of 2 or more points was 0.96, 0.95, and 0.95, respectively. CONCLUSIONS AND RELEVANCE: In adults with suspected infection admitted to the CTICU in NUH, the change in in-hospital mortality between patients with an increase in SOFA scores of less than 2 and those with an increase of 2 or more was 2.5 percentage points. In contrast to other studies, the absolute change in mortality was nearly the same compared to the qSOFA and SIRS criteria, and the qSOFA score had the greatest percentage increase of 104%, compared to 71% for the SOFA score and 50% for the SIRS criteria. Besides, from the perspective of discriminatory capacities, an increase in SOFA scores of 2 or more did not demonstrate significantly greater prognostic accuracy for in-hospital mortality than equivalent increases in qSOFA scores or SIRS criteria. These findings suggest distinctive characteristics of the study population in the CTICU that are different from the general population.

Modeling Lower Critical Solution Temperature Behavior of Associating Dendrimers Using Density Functional Theory.

We study the phase behavior of associating dendrimers in explicit solvents using classical density functional theory. The existence of association enables uptake of solvent inside the dendrimer even for unfavorable Lennard-Jones interaction between the solvent and dendrimer. Depending on the distributions of associating sites, the dendrimer conformation can be either dense-core or dense-shell. The conformation of the associating dendrimer is greatly affected by the temperature. Due to the interplay between association interaction and Lennard-Jones attractions, we find the lower critical solution temperature (LCST) behavior of dendrimer conformation and study how it changes as the dendrimer size or solvent size changes. The dendrimer in our study displays no LCST behavior at low generations, and it has a maximum LCST at G4. Moreover, increasing the solvent chain length decreases the LCST. For solvents with self-association, the competition between solvent-solvent association and solvent-dendrimer association also tends to reduce the LCST. Qualitatively consistent with experiments, our results provide insight into the molecular mechanism of the LCST behavior of associating dendrimers.

Shape Memory Hydrogels with Simultaneously Switchable Fluorescence Behavior.

Realization of shape memory process in polymeric hydrogels at ambient condition is a significant development to shape memory materials. The sound understanding of the dynamic shape memory process is fundamentally important but limited. Here, a novel shape memory hydrogel with simultaneously switchable fluorescence behavior is developed. The hydrogel is prepared by incorporating a pH-responsive fluorescent molecule, perylene tetracarboxylic acid, into chitosan-based hydrogel, and the assembly and disassembly of chitosan chains into microcrystals upon the trigger of pH are applied as reversible crosslinks to achieve shape memory effect. Therefore, the formation and disassociation of microcrystalline chitosan, and the switchable fluorescence performance happen concurrently, which bring convenience to monitoring the shape memory process by fluorescent imaging. Moreover, the erasable fluorescence behavior also gives the hydrogel potential applications in information storage.

A Novel Anisotropic Hydrogel with Integrated Self-Deformation and Controllable Shape Memory Effect.

Although shape memory polymers have been highlighted widely and developed rapidly, it is still a challenging task to realize complex temporary shapes automatically in practical applications. Herein, a novel shape memory hydrogel with the ability of self-deformation is presented. Through constructing an anisotropic poly(acrylic acid)-polyacrylamide (PAAc-PAAm) structure, the obtained hydrogel exhibits stable self-deformation behavior in response to pH stimulus, and the shapes that formed automatically can be fixed by the coordination between carboxylic groups and Fe3+ ; therefore, self-deformation and shape memory behaviors are integrated in one system. Moreover, the magnitude of auto-deformation and shape memory could be adjusted with the concentration of corresponding ions, leading to programmable shape memory and shape recovery processes.

Density functional study of dendrimer molecules in solvents of varying quality.

Modified inhomogeneous statistical associating fluid theory (iSAFT) density functional theory is extended to dendrimer molecules in solvents of varying quality. The detailed structures of isolated dendrimers in implicit solvent are calculated and have a semi-quantitative agreement with simulation results available in the literature. The dendrimers form dense-core structures under all conditions, while their radius of gyration follows different scaling laws. Factors that affect the quality of the solvent are systematically studied in the explicit solvent case. It is found that the solvent size, density, chemical affinity and temperature all play a role in determining a solvent to be good or poor. New molecular dynamics simulations are performed to validate the iSAFT results. Our results provide insight into the phase behavior of dendrimer solutions as well as guidance in practical applications.

Oropharyngeal cancer and human papillomavirus: a visualization based on bibliometric analysis and topic modeling.

Objectives: The incidence of oropharyngeal cancer (OPC) is increasing. This study used bibliometric analysis and topic modeling to explore the research trends and advancements in this disease over the past 10 years, providing valuable insights to guide future investigations. Methods: 7,355 English articles from 2013 to 2022 were retrieved from the Web of Science Core Collection for bibliometric analysis. Topic modeling was applied to 1,681 articles from high-impact journals, followed by an assessment of topic significance ranking (TSR). Medical Subject Headings (MeSH) terms were extracted using R and Python, followed by an analysis of the terms associated with each topic and on an annual basis. Additionally, genes were extracted and the number of genes appearing each year and the newly emerged genes were counted. Results: The bibliometric analysis suggested that the United States and several European countries hold pivotal positions in research. Current research is focused on refining treatments, staging and stratification. Topic modeling revealed 12 topics, emphasizing human papillomavirus (HPV) and side effect reduction. MeSH analysis revealed a growing emphasis on prognosis and quality of life. No new MeSH terms emerged after 2018, suggesting that the existing terms have covered most of the core concepts within the field of oropharyngeal cancers. Gene analysis identified TP53 and EGFR as the most extensively studied genes, with no novel genes discovered after 2019. However, CD69 and CXCL9 emerged as new genes of interest in 2019, reflecting recent research trends and directions. Conclusion: HPV-positive oropharyngeal cancer research, particularly treatment de-escalation, has gained significant attention. However, there are still challenges in diagnosis and treatment that need to be addressed. In the future, more research will focus on this issue, indicating that this field still holds potential as a research hotspot.

Shaping high-performance wearable robots for human motor and sensory reconstruction and enhancement.

Most wearable robots such as exoskeletons and prostheses can operate with dexterity, while wearers do not perceive them as part of their bodies. In this perspective, we contend that integrating environmental, physiological, and physical information through multi-modal fusion, incorporating human-in-the-loop control, utilizing neuromuscular interface, employing flexible electronics, and acquiring and processing human-robot information with biomechatronic chips, should all be leveraged towards building the next generation of wearable robots. These technologies could improve the embodiment of wearable robots. With optimizations in mechanical structure and clinical training, the next generation of wearable robots should better facilitate human motor and sensory reconstruction and enhancement.

[68Ga]Ga-FAPI-04 Positron Emission Tomography/ Magnetic Resonance Imaging for Assessing Ascending Aortic Aneurysm.

Comparison of [68Ga]Ga-FAPI-04 PET/MR imaging in patients with stable ascending aortic aneurysm (AA) and rapidly expanding ascending AA. Abnormal uptake of [68Ga]Ga-FAPI-04 was found only in the wall of the progressive ascending AA. The pathology of the aortic wall segments demonstrated greater [68Ga]Ga-FAPI-04 uptake showed greater fibroblast activation protein expression, more elastic fiber degradation and collagen deposition than did the adjacent normal aorta.

A Dual-Targeting, Multi-Faceted Biocompatible Nanodrug Optimizes the Microenvironment to Ameliorate Abdominal Aortic Aneurysm.

Abdominal aortic aneurysm (AAA) is a highly lethal cardiovascular disease that currently lacks effective pharmacological treatment given the complex pathophysiology of the disease. Here, single-cell RNA-sequencing data from patients with AAA and a mouse model are analyzed, which reveals pivotal pathological changes, including the M1-like polarization of macrophages and the loss of contractile function in smooth muscle cells (SMCs). Both cell types express the integrin αvß3, allowing for their dual targeting with a single rationally designed molecule. To this end, a biocompatible nanodrug, which is termed EVMS@R-HNC, that consists of the multifunctional drug everolimus (EVMS) encapsulated by the hepatitis B virus core protein modifies to contain the RGD sequence to specifically bind to integrin αvß3 is designed. Both in vitro and in vivo results show that EVMS@R-HNC can target macrophages as well as SMCs. Upon binding of the nanodrug, the EVMS is released intracellularly where it exhibits multiple functions, including inhibiting M1 macrophage polarization, thereby suppressing the self-propagating inflammatory cascade and immune microenvironment imbalance, while preserving the normal contractile function of SMCs. Collectively, these results suggest that EVMS@R-HNC presents a highly promising therapeutic approach for the management of AAA.

Generation of allogeneic CAR-NKT cells from hematopoietic stem and progenitor cells using a clinically guided culture method.

Cancer immunotherapy with autologous chimeric antigen receptor (CAR) T cells faces challenges in manufacturing and patient selection that could be avoided by using 'off-the-shelf' products, such as allogeneic CAR natural killer T (AlloCAR-NKT) cells. Previously, we reported a system for differentiating human hematopoietic stem and progenitor cells into AlloCAR-NKT cells, but the use of three-dimensional culture and xenogeneic feeders precluded its clinical application. Here we describe a clinically guided method to differentiate and expand IL-15-enhanced AlloCAR-NKT cells with high yield and purity. We generated AlloCAR-NKT cells targeting seven cancers and, in a multiple myeloma model, demonstrated their antitumor efficacy, expansion and persistence. The cells also selectively depleted immunosuppressive cells in the tumor microenviroment and antagonized tumor immune evasion via triple targeting of CAR, TCR and NK receptors. They exhibited a stable hypoimmunogenic phenotype associated with epigenetic and signaling regulation and did not induce detectable graft versus host disease or cytokine release syndrome. These properties of AlloCAR-NKT cells support their potential for clinical translation.

Revealing a causal relationship between gut microbiota and lung cancer: a Mendelian randomization study.

Background: The gut microbiota has been found to be associated with the risk of lung cancer. However, its causal relationship with various types of lung cancer remains unclear. Methods: We conducted a Mendelian randomization (MR) study using the largest genome-wide association analysis of gut microbiota data to date from the MiBioGen consortium, with pooled statistics for various types of lung cancer from the Transdisciplinary Research in Cancer of the Lung, the International Lung Cancer Consortium, and FinnGen Consortium R7 release data. Inverse variance weighted, weighted model, MR-Egger regression, and weighted median were adapted to assess the causal relationship between gut microbiota and various types of lung cancer. Sensitivity analysis was used to test for the presence of pleiotropy and heterogeneity in instrumental variables. A reverse MR analysis was performed on these bacteria to determine their potential role in causing lung cancer. A reverse MR analysis was performed on these bacteria to determine their potential role in causing lung cancer. Multivariable Mendelian randomization (MVMR) was conducted to assess the direct causal impact of gut microbiota on the risk of various types of lung cancer. Results: Using IVW as the primary analytical method, we identified a total of 40 groups of gut microbiota with potential causal associations with various subtypes of lung cancer, of which 10 were associated with lung cancer, 10 with lung adenocarcinoma, 9 with squamous cell lung cancer, and 11 groups of bacteria associated with small cell lung cancer. After performing FDR correction, we further found that there was still a significant causal relationship between Peptococcaceae and lung adenocarcinoma. Sensitivity analyses demonstrated the robustness of these results, with no heterogeneity or pleiotropy found. Conclusions: Our results confirm a causal relationship between specific gut microbiota and lung cancer, providing new insights into the role of gut microbiota in mediating the development of lung cancer.