Rab11b promotes M1-like macrophage polarization by restraining autophagic degradation of NLRP3 in alcohol-associated liver disease.

Macrophage polarization is vital to mounting a host defense or repairing tissue in various liver diseases. Excessive activation of the NLR family pyrin domain containing 3 (NLRP3) inflammasome is related to the orchestration of inflammation and alcohol-associated liver disease (ALD) pathology. Rab GTPases play critical roles in regulating vesicular transport. In this study we investigated the role of Rab11b in ALD, aiming to identify effective therapeutic targets. Here, we first demonstrated a decreased expression of Rab11b in macrophages from ALD mice. Knockdown of Rab11b by macrophage-specific adeno-associated virus can alleviate alcohol induced liver inflammation, injury and steatosis. We found that LPS and alcohol stimulation promoted Rab11b transferring from the nucleus to the cytoplasm in bone marrow-derived macrophages (BMDM) cells. Rab11b specifically activated the NLRP3 inflammasome in BMDMs and RAW264.7 cells to induce M1 macrophage polarization. Rab11b overexpression in BMDMs inhibited autophagic flux, leading to the suppression of LC3B-mediated NLRP3 degradation. We conclude that impaired Rab11b could alleviate alcohol-induced liver injury via autophagy-mediated NLRP3 degradation.

Differences in the pathogenicity and molecular characteristics of fowl adenovirus serotype 4 epidemic strains in Guangxi Province, southern China.

Starting in 2015, the widespread prevalence of hydropericardium-hepatitis syndrome (HHS) has led to considerable financial losses within China's poultry farming industry. In this study, pathogenicity assessments, whole-genome sequencing, and analyses were conducted on 10 new isolates of the novel genotype FAdV-4 during a HHS outbreak in Guangxi Province, China, from 2019 to 2020. The results indicated that strains GX2019-010 to GX2019-013 and GX2019-015 to GX2019-018 were highly virulent, while strain GX2020-019 exhibited moderate virulence. Strain GX2019-014 was characterized as a wild-type strain with low virulence, displaying no pathogenic effects when 0.5 mL containing 106 TCID50 virus was inoculated into the muscle of specific pathogen-free (SPF) chickens at 4 weeks of age, while 107 TCID50 and 108 TCID50 resulted in mortality rates of 80 and 100%, respectively. The whole genomes of strains GX2019-010 to GX2019-013, GX2019-015 to GX2019-018, and GX2020-019 showed high homology with other Chinese newly emerging highly pathogenic FAdV-4 strains, whereas GX2019-014 was closer to nonmutant strains and shared the same residues with known nonpathogenic strains (B1-7, KR5, and ON1) at positions 219AA and 380AA of the Fiber-2 protein. Our work enriches the research on prevalent strains of FAdV-4 in China, expands the knowledge on the virulence diversity of the novel genotype FAdV-4, and provides valuable reference material for further investigations into the key virulence-associated genetic loci of FAdV-4.

The Anti-Biofilm Properties of Phloretin and Its Analogs against Porphyromonas gingivalis and Its Complex Flora.

Porphyromonas gingivalis is crucial for the pathogenesis of periodontitis. This research investigated the effects of the fruit-derived flavonoid phloretin and its analogs on the growth of pure P. gingivalis and the flora of P. gingivalis mixed with the symbiotic oral pathogens Fusobacterium nucleatum and Streptococcus mitis. The results showed that the tested flavonoids had little effect on the biofilm amount of pure P. gingivalis, but significantly reduced the biofilm amount of mixed flora to 83.6~89.1%. Biofilm viability decreased to 86.7~92.8% in both the pure- and mixed-bacterial groups after naringenin and phloretin treatments. SEM showed that phloretin and phlorizin displayed a similar and remarkable destructive effect on P. gingivalis and the mixed biofilms. Transcriptome analysis confirmed that biofilm formation was inhibited by these flavonoids, and phloretin significantly regulated the transcription of quorum sensing. Phlorizin and phloretin reduced AI-2 activity to 45.9% and 55.4%, respectively, independent of the regulation of related gene transcription. This research marks the first finding that these flavonoids possess anti-biofilm properties against P. gingivalis and its intricate bacterial community, and the observed performance variations, driven by structural differences, underscore the existence of intriguing structure-activity relationships.

Genomic variation induced by a low concentration of ethyl methanesulfonate (EMS) in quinoa 'Longli-4' variety.

Quinoa (Chenopodium quinoa, 2n = 4x = 36), a super pseudocereal crop, has been introduced into China nearly 60 years. Many excellent varieties have been developed through massive selection; however, few are developed through mutagenesis breeding. In this study, the 'Longli-4' variety, locally cultivated in Gansu province, Northwest China, was selected for experimentation. The grains of 'Longli-4' were treated with ethyl methanesulfonate (EMS) at a concentration of 0.8% for 8 h. Nine plants from independent M2 families were randomly selected to investigate the mutagenesis effect of EMS on the quinoa genome. The results indicated that the single nucleotide polymorphisms (SNPs) induced by EMS were unevenly distributed across all 18 chromosomes, with an average mutation frequency of 91.2 SNPs/Mb, ranging from 4.5 to 203.5 SNPs/Mb. A significant positive correlation between the number of SNPs and chromosome length was identified through linear model analysis. Transitions from G/C to A/T were the most predominated in all variant categories, accounting for 34.4-67.2% of the mutations, and SNPs were significantly enriched in intergenic regions, representing 69.2-75.1% of the total mutations. This study provides empirical support for the application of low concentration EMS treatment in quinoa breeding.

High-Tcsuperconductivity in doped molecular superconductors of K4B8-xMxH32(M = C, N) under high pressure.

Stabilized and metallic light elements hydrides have provided a potential route to achieve the goal of room-temperature superconductors at moderate or ambient pressures. Here, we have performed systematic DFT theoretical calculations to examine the effects of different light elements C and N atoms doped in cubic K4B8H32hydrides on the superconductivity at low pressures. As a result of various atoms substituting, we have found that metallic K4B8-xMxH32(M = C, N) hydrides are dynamically stable at 50 GPa, band structures and density of states indicate that sizeableTccorrelates with a high B-H density of states at the Fermi level. With the increasing of B atoms in K4B8-xMxH32hydrides, the density of states values at Fermi level have been improved due to the delocalized electrons in B-H bonds, which result in strong electron-phonon coupling (EPC) interaction and increase theTcfrom 19.04 to 77.07 K for KC2H8and KB2H8at 50 GPa. The NH4unit in stable K4B7NH32hydrides has weakened the EPC and led to low Tc value of 21.47 K. Our results suggest the light elements hydrides KB2H8and K4B7CH32could estimate highTcvalues at 50 GPa, and the boron hydrides would be potential candidates to design or modulate hydrides superconductors with highTcat moderate or ambient pressures.

Photodetectors Based on MASnI3/MoS2 Hybrid-Dimensional Heterojunction Transistors: Breaking the Responsivity-Speed Trade-Off.

Hybrid-dimensional heterojunction transistor (HDHT) photodetectors (PDs) have achieved high responsivities but unfortunately are still with unacceptably slow response speeds. Here, we propose a MASnI3/MoS2 HDHT PD, which exhibits the possibility to obtain high responsivity and fast response simultaneously. By exploring the detailed photoelectric responses utilizing a precise optoelectronic coupling simulation, the electrical performance of the device is optimally manipulated and the underlying physical mechanisms are carefully clarified. Particularly, the influence and modulation characteristics of the trap effects on the carrier dynamics of the PDs are investigated. We find that the localized trap effect in perovskite, especially at its top surface, is primarily responsible for the high responsivity and long response time; moreover, it is normally hard to break such a responsivity-speed trade-off due to the inherent limitation of the trap effect. By synergistically coupling the photogating effect, trap effect, and gate regulation, we indicate that it is possible to achieve an enhancement of the responsivity-bandwidth product by about 3 orders of magnitude. This study facilitates a fine modulation of the responsivity-speed relationship of hybrid-dimensional PDs, enabling breaking the traditional responsivity-speed trade-off of many PDs.

Methyl jasmonate-induced bHLH42 mediates tissue-specific accumulation of anthocyanins via regulating flavonoid metabolism-related pathways in Caitai.

Anthocyanin is a type of plant secondary metabolite beneficial to human health. The anthocyanin content of vegetable and fruit crops signifies their nutritional quality. However, the molecular mechanism of anthocyanin accumulation, especially tissue-specific accumulation, in Caitai, as well as in other Brassica rapa varieties, remains elusive. In the present study, taking advantage of three kinds of Caitai cultivars with diverse colour traits between leaves and stems, we conducted a comparative transcriptome analysis and identified the molecular pathway of anthocyanin biosynthesis in Caitai leaves and stems, respectively. Our further investigations demonstrate that bHLH42, which is robustly induced by MeJA, closely correlates with tissue-specific accumulation of anthocyanins in Caitai; bHLH42 upregulates the expression of flavonoid/anthocyanin biosynthetic pathway genes to activate anthocyanin biosynthesis pathway, importantly, overexpression of bHLH42 significantly improves the anthocyanin content of Caitai. Our analysis convincingly suggests that bHLH42 induced by jasmonic acid signalling plays a crucial role in tissue-specific accumulation of anthocyanins in Caitai.

Sex disparities of the effect of the COVID-19 pandemic on mortality among patients living with tuberculosis in the United States.

Background: We aimed to determine the trend of TB-related deaths during the COVID-19 pandemic. Methods: TB-related mortality data of decedents aged ≥25 years from 2006 to 2021 were analyzed. Excess deaths were estimated by determining the difference between observed and projected mortality rates during the pandemic. Results: A total of 18,628 TB-related deaths were documented from 2006 to 2021. TB-related age-standardized mortality rates (ASMRs) were 0.51 in 2020 and 0.52 in 2021, corresponding to an excess mortality of 10.22 and 9.19%, respectively. Female patients with TB demonstrated a higher relative increase in mortality (26.33 vs. 2.17% in 2020; 21.48 vs. 3.23% in 2021) when compared to male. Female aged 45-64 years old showed a surge in mortality, with an annual percent change (APC) of -2.2% pre-pandemic to 22.8% (95% CI: -1.7 to 68.7%) during the pandemic, corresponding to excess mortalities of 62.165 and 99.16% in 2020 and 2021, respectively; these excess mortality rates were higher than those observed in the overall female population ages 45-64 years in 2020 (17.53%) and 2021 (33.79%). Conclusion: The steady decline in TB-related mortality in the United States has been reversed by COVID-19. Female with TB were disproportionately affected by the pandemic.

Recent advances and prospects of constructed wetlands in cold climates: a review from 2013 to 2023.

Constructed wetland (CW), a promising, environmentally responsible, and effective green ecological treatment technology, is actively involved in the treatment of various forms of wastewater. Low temperatures will, however, lead to issues including plant dormancy, decreased microbial activity, and ice formation in CWs, which will influence how well CWs process wastewater. Applying CWs successfully and continuously in cold areas is extremely difficult. Therefore, it is crucial to find solutions for the pressing issue of increasing the CWs' ability to process wastewater at low temperatures. This review focuses on the effect of cold climate on CWs (plants, substrates, microorganisms, removal effect of pollutants). It meticulously outlines current strategies to enhance CWs' performance under low-temperature conditions, including modifications for the improvement and optimization of the internal components (i.e., plant and substrate selection, bio-augmentation) and enhancement of the external operation conditions of CWs (such as process combination, effluent recirculation, aeration, heat preservation, and operation parameter optimization). Finally, future perspectives on potential research directions and technological innovations that could strengthen CWs' performance in cold climates are prospected. This review aims to contribute valuable insights into the operation strategies, widespread implementation, and subsequent study of CWs in colder climate regions.

Porphyrin metabolism and carbon fixation response of Skeletonema costatum at different growth phases to mixed emerging PFASs at environmental concentrations.

Per- and polyfluoroalkyl substances (PFASs), especially as emerging compounds, have been widely detected in coastal seawater. However, the awareness of the interaction between PFASs at environmental concentrations and marine diatoms is still limited. In this study, Skeletonema costatum was exposed to three co-existing PFASs, namely hexafluoropropylene oxide dimer acid (HFPO-DA), 6 : 2 chlorinated polyfluorinated ether sulfonate (Cl-PFAES), and perfluoroethylcyclohexane sulfonate (PFECHS) (15-300 ng L-1 in total), for 14 days. In the 300 ng L-1 test group, the significant down-regulation of chlorophyllide a in porphyrin metabolism, light-harvesting capacity and carbon fixation were the main inhibitory mechanisms of photosynthesis by emerging PFASs at the 14th day compared to the 8th day, which indicated that they may have a shading effect on S. costatum. Additionally, mixed PFASs could also activate nicotinamide adenine dinucleotide phosphate (NADPH) oxidase by up-regulating gene gp91 and down-regulating genes CaM4 and NDPK2 to generate excessive ROS. This resulted in a decrease in the algal biomass, which would further weaken the primary productivity of S. costatum. Our findings illustrated that mixed emerging PFASs at environmental concentrations may interfere with the carbon balance of marine diatoms.

Enhancing the diagnostic accuracy of colorectal cancer through the integration of serum tumor markers and hematological indicators with machine learning algorithms.

BACKGROUND: Colorectal cancer has a high incidence and mortality rate due to a low rate of early diagnosis. Therefore, efficient diagnostic methods are urgently needed. PURPOSE: This study assesses the diagnostic effectiveness of Carbohydrate Antigen 19-9 (CA19-9), Carcinoembryonic Antigen (CEA), Alpha-fetoprotein (AFP), and Cancer Antigen 125 (CA125) serum tumor markers for colorectal cancer (CRC) and investigates a machine learning-based diagnostic model incorporating these markers with blood biochemical indices for improved CRC detection. METHOD: Between January 2019 and December 2021, data from 800 CRC patients and 697 controls were collected; 52 patients and 63 controls attending the same hospital in 2022 were collected as an external validation set. Markers' effectiveness was analyzed individually and collectively, using metrics like ROC curve AUC and F1 score. Variables chosen through backward regression, including demographics and blood tests, were tested on six machine learning models using these metrics. RESULT: In the case group, the levels of CEA, CA199, and CA125 were found to be higher than those in the control group. Combining these with a fourth serum marker significantly improved predictive efficacy over using any single marker alone, achieving an Area Under the Curve (AUC) value of 0.801. Using stepwise regression (backward), 17 variables were meticulously selected for evaluation in six machine learning models. Among these models, the Gradient Boosting Machine (GBM) emerged as the top performer in the training set, test set, and external validation set, boasting an AUC value of over 0.9, indicating its superior predictive power. CONCLUSION: Machine learning models integrating tumor markers and blood indices offer superior CRC diagnostic accuracy, potentially enhancing clinical practice.

A teosinte-derived allele of ZmSC improves salt tolerance in maize.

Maize, a salt-sensitive crop, frequently suffers severe yield losses due to soil salinization. Enhancing salt tolerance in maize is crucial for maintaining yield stability. To address this, we developed an introgression line (IL76) through introgressive hybridization between maize wild relatives Zea perennis, Tripsacum dactyloides, and inbred Zheng58, utilizing the tri-species hybrid MTP as a genetic bridge. Previously, genetic variation analysis identified a polymorphic marker on Zm00001eb244520 (designated as ZmSC), which encodes a vesicle-sorting protein described as a salt-tolerant protein in the NCBI database. To characterize the identified polymorphic marker, we employed gene cloning and homologous cloning techniques. Gene cloning analysis revealed a non-synonymous mutation at the 1847th base of ZmSCIL76 , where a guanine-to-cytosine substitution resulted in the mutation of serine to threonine at the 119th amino acid sequence (using ZmSCZ58 as the reference sequence). Moreover, homologous cloning demonstrated that the variation site derived from Z. perennis. Functional analyses showed that transgenic Arabidopsis lines overexpressing ZmSCZ58 exhibited significant reductions in leaf number, root length, and pod number, alongside suppression of the expression of genes in the SOS and CDPK pathways associated with Ca2+ signaling. Similarly, fission yeast strains expressing ZmSCZ58 displayed inhibited growth. In contrast, the ZmSCIL76 allele from Z. perennis alleviated these negative effects in both Arabidopsis and yeast, with the lines overexpressing ZmSCIL76 exhibiting significantly higher abscisic acid (ABA) content compared to those overexpressing ZmSCZ58 . Our findings suggest that ZmSC negatively regulates salt tolerance in maize by suppressing downstream gene expression associated with Ca2+ signaling in the CDPK and SOS pathways. The ZmSCIL76 allele from Z. perennis, however, can mitigate this negative regulatory effect. These results provide valuable insights and genetic resources for future maize salt tolerance breeding programs.

Telehealth With Comprehensive Live-Fed Real-World Data as a Patient Care Platform for Lung Cancer: Implementation and Evaluation Study.

BACKGROUND: Telehealth has emerged as a popular channel for providing outpatient services in many countries. However, the majority of telehealth systems focus on operational functions and offer only a sectional patient journey at most. Experiences with incorporating longitudinal real-world medical record data into telehealth are valuable but have not been widely shared. The feasibility and usability of such a telehealth platform, with comprehensive, real-world data via a live feed, for cancer patient care are yet to be studied. OBJECTIVE: The primary purpose of this study is to understand the feasibility and usability of cancer patient care using a telehealth platform with longitudinal, real-world data via a live feed as a supplement to hospital electronic medical record systems specifically from physician's perspective. METHODS: A telehealth platform was constructed and launched for both physicians and patients. Real-world data were collected and curated using a comprehensive data model. Physician activities on the platform were recorded as system logs and analyzed. In February 2023, a survey was conducted among the platform's registered physicians to assess the specific areas of patient care and to quantify their before and after experiences, including the number of patients managed, time spent, dropout rate, visit rate, and follow-up data. Descriptive and inferential statistical analyses were performed on the data sets. RESULTS: Over a period of 15 months, 16,035 unique users (13,888 patients, 1539 friends and family members, and 174 physician groups with 608 individuals) registered on the platform. More than 382,000 messages including text, reminders, and pictures were generated by physicians when communicating with patients. The survey was completed by 78 group leaders (45% of the 174 physician groups). Of the participants, 84% (65.6/78; SD 8.7) reported a positive experience, with efficient communication, remote supervision, quicker response to questions, adverse event prevention, more complete follow-up data, patient risk reduction, cross-organization collaboration, and a reduction in in-person visits. The majority of the participants (59/78, 76% to 76/78, 97.4%) estimated improvements in time spent, number of patients managed, the drop-off rate, and access to medical history, with the average ranging from 57% to 105%. When compared with prior platforms, responses from physicians indicated better experiences in terms of time spent, the drop-off rate, and medical history, while the number of patients managed did not significantly change. CONCLUSIONS: This study suggests that a telehealth platform, equipped with comprehensive, real-world data via a live feed, is feasible and effective for cancer patient care. It enhances inpatient management by improving time efficiencies, reducing drop-off rates, and providing easy access to medical history. Moreover, it fosters a positive experience in physician-patient interactions.

Arsenic behavior in soil-plant system under the manure application with the combination of antibiotic and roxarsone.

Limited attention has been given to the interaction between antibiotics and arsenic in the soil-plant system. In this investigation, Medicago sativa seedlings were grown in soil treated with cow manure containing oxytetracycline (OTC) or sulfadiazine (SD), as well as arsenic (introduced through roxarsone, referred to as ROX treatment). The study revealed a notable increase in As(III) and dimethylarsinic acid (DMA(V)) levels in rhizosphere soils and plant root tissues as arsenic contamination intensified in the presence of antibiotics, while concentrations of As(V) and monomethylarsonic acid (MMA(V)) decreased. Conversely, elevated antibiotic presence resulted in higher levels of As(V) but reduced DMA concentrations in both rhizosphere soils and plant root tissues in the presence of arsenic. The arsenic biotransformation gene aioA was inhibited by arsenic contamination when antibiotics were present, and suppressed by antibiotic contamination in the presence of arsenic, especially in SD treatments, resulting in reduced expression levels at higher SD concentrations. Conversely, the arsM gene exhibited consistent upregulation under all conditions. However, its expression was found to increase with higher concentrations of ROX in the presence of antibiotics, decrease with increasing SD concentrations, and initially rise before declining with higher levels of OTC in the presence of arsenic. Bacterial genera within the Proteobacteria phylum, such as Geobacter, Lusitaniella, Mesorhizobium, and Methylovirgula, showed significant co-occurrence with both aioA and arsM genes. Correlation analysis demonstrated associations between the four arsenic species and the two arsenic biotransformation genes, emphasizing pH as a critical factor influencing the transformation and uptake of different arsenic species in the soil-plant system. The combined stress of antibiotics and arsenic has the potential to modify arsenic behavior and associated risks in soil-plant systems, highlighting the necessity of considering this interaction in future research endeavors.

Multi-omic profiling reveals potential biomarkers of hepatocellular carcinoma prognosis and therapy response among mitochondria-associated cell death genes in the context of 3P medicine.

Background: Cancer cell growth, metastasis, and drug resistance are major challenges in treating liver hepatocellular carcinoma (LIHC). However, the lack of comprehensive and reliable models hamper the effectiveness of the predictive, preventive, and personalized medicine (PPPM/3PM) strategy in managing LIHC. Methods: Leveraging seven distinct patterns of mitochondrial cell death (MCD), we conducted a multi-omic screening of MCD-related genes. A novel machine learning framework was developed, integrating 10 machine learning algorithms with 67 different combinations to establish a consensus mitochondrial cell death index (MCDI). This index underwent rigorous evaluation across training, validation, and in-house clinical cohorts. A comprehensive multi-omics analysis encompassing bulk, single-cell, and spatial transcriptomics was employed to achieve a deeper insight into the constructed signature. The response of risk subgroups to immunotherapy and targeted therapy was evaluated and validated. RT-qPCR, western blotting, and immunohistochemical staining were utilized for findings validation. Results: Nine critical differentially expressed MCD-related genes were identified in LIHC. A consensus MCDI was constructed based on a 67-combination machine learning computational framework, demonstrating outstanding performance in predicting prognosis and clinical translation. MCDI correlated with immune infiltration, Tumor Immune Dysfunction and Exclusion (TIDE) score and sorafenib sensitivity. Findings were validated experimentally. Moreover, we identified PAK1IP1 as the most important gene for predicting LIHC prognosis and validated its potential as an indicator of prognosis and sorafenib response in our in-house clinical cohorts. Conclusion: This study developed a novel predictive model for LIHC, namely MCDI. Incorporating MCDI into the PPPM framework will enhance clinical decision-making processes and optimize individualized treatment strategies for LIHC patients. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00362-8.

Potential role of blood pressure variability and plasma neurofilament light in the mechanism of comorbidity between Alzheimer's disease and cerebral small vessel disease.

INTRODUCTION: Long-term blood pressure variability (BPV) and plasma neurofilament light (pNfL) have been identified as potential biomarkers for Alzheimer's disease (AD) and cerebral small vessel disease (CSVD). However, the relationship between BPV, pNfL, and their association with the comorbidity of AD and CSVD remains unknown. METHODS: Participants with normal cognition and mild cognitive impairment from the Alzheimer's Disease Neuroimaging Initiative study were included in the data analysis. Linear mixed-effects regression models and causal mediation analyses were conducted to investigate the relationship among BPV, pNfL, comorbidity-related brain structural changes (hippocampal atrophy and white matter hyperintensities [WMH]), and cognitive function. RESULTS: BPV was associated with pNfL, volumes of hippocampus and WMH, and cognition. pNfL mediated the effects of BPV on brain structural changes and cognition. DISCUSSION: Our findings suggest a potential role of BPV and pNfL in the mechanism of comorbidity between AD and CSVD, underscoring the importance of BPV intervention in the general population. HIGHLIGHTS: Individuals with both Alzheimer's disease (AD) and cerebral small vessel disease (CSVD) pathologies had elevated blood pressure variability (BPV) and plasma neurofilament light (pNfL). The association between different components of BPV and brain structural changes may vary. BPV was associated with pNfL levels independent of average blood pressure. pNfL mediated the effects of BPV on comorbidity-related brain structural changes and cognitive performance.

A predictive radiotranscriptomics model based on DCE-MRI for tumor immune landscape and immunotherapy in cholangiocarcinoma.

This study aims to determine the predictive role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) derived radiomic model in tumor immune profiling and immunotherapy for cholangiocarcinoma. To perform radiomic analysis, immune related subgroup clustering was first performed by single sample gene set enrichment analysis (ssGSEA). Second, a total of 806 radiomic features for each phase of DCE-MRI were extracted by utilizing the Python package Pyradiomics. Then, a predictive radiomic signature model was constructed after a three-step features reduction and selection, and receiver operating characteristic (ROC) curve was employed to evaluate the performance of this model. In the end, an independent testing cohort involving cholangiocarcinoma patients with anti-PD-1 Sintilimab treatment after surgery was used to verify the potential application of the established radiomic model in immunotherapy for cholangiocarcinoma. Two distinct immune related subgroups were classified using ssGSEA based on transcriptome sequencing. For radiomic analysis, a total of 10 predictive radiomic features were finally identified to establish a radiomic signature model for immune landscape classification. Regarding to the predictive performance, the mean AUC of ROC curves was 0.80 in the training/validation cohort. For the independent testing cohort, the individual predictive probability by radiomic model and the corresponding immune score derived from ssGSEA was significantly correlated. In conclusion, radiomic signature model based on DCE-MRI was capable of predicting the immune landscape of chalangiocarcinoma. Consequently, a potentially clinical application of this developed radiomic model to guide immunotherapy for cholangiocarcinoma was suggested.