Cryo-EM Structure of an Extended SARS-CoV-2 Replication and Transcription Complex Reveals an Intermediate State in Cap Synthesis.

Transcription of SARS-CoV-2 mRNA requires sequential reactions facilitated by the replication and transcription complex (RTC). Here, we present a structural snapshot of SARS-CoV-2 RTC as it transitions toward cap structure synthesis. We determine the atomic cryo-EM structure of an extended RTC assembled by nsp7-nsp82-nsp12-nsp132-RNA and a single RNA-binding protein, nsp9. Nsp9 binds tightly to nsp12 (RdRp) NiRAN, allowing nsp9 N terminus inserting into the catalytic center of nsp12 NiRAN, which then inhibits activity. We also show that nsp12 NiRAN possesses guanylyltransferase activity, catalyzing the formation of cap core structure (GpppA). The orientation of nsp13 that anchors the 5' extension of template RNA shows a remarkable conformational shift, resulting in zinc finger 3 of its ZBD inserting into a minor groove of paired template-primer RNA. These results reason an intermediate state of RTC toward mRNA synthesis, pave a way to understand the RTC architecture, and provide a target for antiviral development.

Structural Basis for RNA Replication by the SARS-CoV-2 Polymerase.

Nucleotide analog inhibitors, including broad-spectrum remdesivir and favipiravir, have shown promise in in vitro assays and some clinical studies for COVID-19 treatment, this despite an incomplete mechanistic understanding of the viral RNA-dependent RNA polymerase nsp12 drug interactions. Here, we examine the molecular basis of SARS-CoV-2 RNA replication by determining the cryo-EM structures of the stalled pre- and post- translocated polymerase complexes. Compared with the apo complex, the structures show notable structural rearrangements happening to nsp12 and its co-factors nsp7 and nsp8 to accommodate the nucleic acid, whereas there are highly conserved residues in nsp12, positioning the template and primer for an in-line attack on the incoming nucleotide. Furthermore, we investigate the inhibition mechanism of the triphosphate metabolite of remdesivir through structural and kinetic analyses. A transition model from the nsp7-nsp8 hexadecameric primase complex to the nsp12-nsp7-nsp8 polymerase complex is also proposed to provide clues for the understanding of the coronavirus transcription and replication machinery.

Gibberellin signaling regulates lignin biosynthesis to modulate rice seed shattering.

The elimination of seed shattering was a key step in rice (Oryza sativa) domestication. In this paper, we show that increasing the gibberellic acid (GA) content or response in the abscission region enhanced seed shattering in rice. We demonstrate that SLENDER RICE1 (SLR1), the key repressor of GA signaling, could physically interact with the rice seed shattering-related transcription factors quantitative trait locus of seed shattering on chromosome 1 (qSH1), O. sativa HOMEOBOX 15 (OSH15), and SUPERNUMERARY BRACT (SNB). Importantly, these physical interactions interfered with the direct binding of these three regulators to the lignin biosynthesis gene 4-COUMARATE: COENZYME A LIGASE 3 (4CL3), thereby derepressing its expression. Derepression of 4CL3 led to increased lignin deposition in the abscission region, causing reduced rice seed shattering. Importantly, we also show that modulating GA content could alter the degree of seed shattering to increase harvest efficiency. Our results reveal that the "Green Revolution" phytohormone GA is important for regulating rice seed shattering, and we provide an applicable breeding strategy for high-efficiency rice harvesting.

Structures of fungal and plant acetohydroxyacid synthases.

Acetohydroxyacid synthase (AHAS), also known as acetolactate synthase, is a flavin adenine dinucleotide-, thiamine diphosphate- and magnesium-dependent enzyme that catalyses the first step in the biosynthesis of branched-chain amino acids1. It is the target for more than 50 commercial herbicides2. AHAS requires both catalytic and regulatory subunits for maximal activity and functionality. Here we describe structures of the hexadecameric AHAS complexes of Saccharomyces cerevisiae and dodecameric AHAS complexes of Arabidopsis thaliana. We found that the regulatory subunits of these AHAS complexes form a core to which the catalytic subunit dimers are attached, adopting the shape of a Maltese cross. The structures show how the catalytic and regulatory subunits communicate with each other to provide a pathway for activation and for feedback inhibition by branched-chain amino acids. We also show that the AHAS complex of Mycobacterium tuberculosis adopts a similar structure, thus demonstrating that the overall AHAS architecture is conserved across kingdoms.

Bacterial indole-3-lactic acid affects epithelium-macrophage crosstalk to regulate intestinal homeostasis.

Tryptophan and its derivatives perform a variety of biological functions; however, the role and specific mechanism of many tryptophan derivatives in intestinal inflammation remain largely unclear. Here, we identified that an Escherichia coli strain (Ec-TMU) isolated from the feces of tinidazole-treated individuals, and indole-3-lactic acid (ILA) in its supernatant, decreased the susceptibility of mice to dextran sulfate sodium-induced colitis. Ec-TMU and ILA contribute to the relief of colitis by inhibiting the production of epithelial CCL2/7, thereby reducing the accumulation of inflammatory macrophages in vitro and in vivo. Mechanistically, ILA downregulates glycolysis, NF-κB, and HIF signaling pathways via the aryl hydrocarbon receptor, resulting in decreased CCL2/7 production in epithelial cells. Clinical evidence suggests that the fecal ILA level is negatively correlated with the progression indicator of inflammatory bowel diseases. These results demonstrate that ILA has the potential to regulate intestinal homeostasis by modulating epithelium-macrophage interactions.

Memory deficit in patients with cerebral small vessel disease: evidence from eye tracking technology.

Cerebral small vessel disease is the one of the most prevalent causes of vascular cognitive impairment. We aimed to find objective and process-based indicators related to memory function to assist in the detection of memory impairment in patients with cerebral small vessel disease. Thirty-nine cerebral small vessel disease patients and 22 healthy controls were invited to complete neurological examinations, neuropsychological assessments, and eye tracking tasks. Eye tracking indicators were recorded and analyzed in combination with imaging features. The cerebral small vessel disease patients scored lower on traditional memory task and performed worse on eye tracking memory task performance compared to the healthy controls. The cerebral small vessel disease patients exhibited longer visit duration and more visit count within areas of interest and targets and decreased percentage value of total visit duration on target images to total visit duration on areas of interest during decoding stage among all levels. Our results demonstrated the cerebral small vessel disease patients performed worse in memory scale and eye tracking memory task, potentially due to their heightened attentional allocation to nontarget images during the retrieval stage. The eye tracking memory task could provide process-based indicators to be a beneficial complement to memory assessment and new insights into mechanism of memory impairment in cerebral small vessel disease patients.

Integration of multidimensional splicing data and GWAS summary statistics for risk gene discovery.

A common strategy for the functional interpretation of genome-wide association study (GWAS) findings has been the integrative analysis of GWAS and expression data. Using this strategy, many association methods (e.g., PrediXcan and FUSION) have been successful in identifying trait-associated genes via mediating effects on RNA expression. However, these approaches often ignore the effects of splicing, which can carry as much disease risk as expression. Compared to expression data, one challenge to detect associations using splicing data is the large multiple testing burden due to multidimensional splicing events within genes. Here, we introduce a multidimensional splicing gene (MSG) approach, which consists of two stages: 1) we use sparse canonical correlation analysis (sCCA) to construct latent canonical vectors (CVs) by identifying sparse linear combinations of genetic variants and splicing events that are maximally correlated with each other; and 2) we test for the association between the genetically regulated splicing CVs and the trait of interest using GWAS summary statistics. Simulations show that MSG has proper type I error control and substantial power gains over existing multidimensional expression analysis methods (i.e., S-MultiXcan, UTMOST, and sCCA+ACAT) under diverse scenarios. When applied to the Genotype-Tissue Expression Project data and GWAS summary statistics of 14 complex human traits, MSG identified on average 83%, 115%, and 223% more significant genes than sCCA+ACAT, S-MultiXcan, and UTMOST, respectively. We highlight MSG's applications to Alzheimer's disease, low-density lipoprotein cholesterol, and schizophrenia, and found that the majority of MSG-identified genes would have been missed from expression-based analyses. Our results demonstrate that aggregating splicing data through MSG can improve power in identifying gene-trait associations and help better understand the genetic risk of complex traits.

A comprehensive overview of diffuse correlation spectroscopy: Theoretical framework, recent advances in hardware, analysis, and applications.

Diffuse correlation spectroscopy (DCS) is a powerful tool for assessing microvascular hemodynamic in deep tissues. Recent advances in sensors, lasers, and deep learning have further boosted the development of new DCS methods. However, newcomers might feel overwhelmed, not only by the already-complex DCS theoretical framework but also by the broad range of component options and system architectures. To facilitate new entry to this exciting field, we present a comprehensive review of DCS hardware architectures (continuous-wave, frequency-domain, and time-domain) and summarize corresponding theoretical models. Further, we discuss new applications of highly integrated silicon single-photon avalanche diode (SPAD) sensors in DCS, compare SPADs with existing sensors, and review other components (lasers, sensors, and correlators), as well as data analysis tools, including deep learning. Potential applications in medical diagnosis are discussed and an outlook for the future directions is provided, to offer effective guidance to embark on DCS research.

Synthesis of Polar-functionalized Isotactic Polypropylenes Using Commercial Heterogeneous Ziegler-Natta Catalyst.

The efficient synthesis of polar-functionalized polypropylenes with high molecular weight and high stereoregularity represents a challenging task. This challenge becomes even more daunting when pursuing an industrially preferred heterogeneous process. This study demonstrated the realization of these goals through the use of commercial heterogeneous Ziegler-Natta catalysts in the copolymerization of propylene with ionic cluster polar monomers. The results revealed high copolymerization activity (∼1.1 × 107 g mol-1 h-1), moderate polar monomer incorporation ratios (∼4.9 mol %), high copolymer molecular weight (Mw > 105 g mol-1), high stereoregularity ([mmmm] ∼ 96%), and high melting temperature range (150-162 °C). The utilization of ionic cluster polar monomers improved the thermal stability as well as stereoselectivity of the catalyst. Moreover, the Ziegler-Natta catalyst can homopolymerize ionic cluster polar monomers with high activities (>104 g mol-1 h-1). The resulting polar-functionalized isotactic polypropylenes (iPP) exhibited superior tensile strength, impact strength, creep resistance, transparency, and crystallinity compared with nonpolar iPP. This enhancement was attributable to the dual roles of the ionic cluster polar monomer unit, serving as both a transparent nucleating agent and a dynamic cross-linking functionality. Furthermore, the polar-functionalized iPP exhibited improved compatibility with polar materials, offering benefits for applications in composites, recycling of mixed plastic wastes, 3D printing, and other fields. This study offered a comprehensive solution for the future industrial production of polar-functionalized iPP via copolymerization, bridging the gap between an efficient and practical copolymerization process from a synthetic chemistry perspective and enhanced material properties from an application perspective.

Unfolded Protein-Based Sandwich AIE Probe Imparts High Fluorescent Contrast for Pan-Cancer Surgical Navigation.

Fluorescence imaging-guided navigation for cancer surgery has a promising clinical application. However, pan-cancer encompasses a wide variety of cancer types with significant heterogeneity, resulting in the lack of universal and highly contrasted fluorescent probes for surgical navigation. Here, we developed an aggregation-induced emission (AIE) probe (MI-AIE-TsG, MAT) with dual activation for pan-cancer surgical navigation. MAT weakly activates fluorescence by targeting the SUR1 protein on the endoplasmic reticulum (ER) through the TsG group. Subsequently, the sulfhydryl groups on the unfolded proteins, which are highly enriched in cancer ER, react with the maleimide (MI) of MAT through the thiol-ene click reaction, further enhancing the fluorescence. The formation of a SUR1-MAT-unfolded protein sandwich complex reinforces the restriction of intramolecular motion and eliminates photoinduced electron transfer of MAT, leading to high signal-to-noise (9.2) fluorescence imaging and use for surgical navigation of pan-cancer. The generally high content of unfolded proteins in cancer cells makes MAT imaging generalizable, and it currently has proven feasibility in ovarian, cervical, and breast cancers. Meanwhile, MAT promotes cellular autophagy by hindering protein folding, thereby inhibiting cancer cell proliferation. This generalizable, high-contrast AIE fluorescent probe spans the heterogeneity of pancreatic cancer, enabling precise pancreatic cancer surgery navigation and treatment.

ABEL-FRET: tether-free single-molecule FRET with hydrodynamic profiling.

Single-molecule Förster resonance energy transfer (smFRET) has become a versatile and widespread method to probe nanoscale conformation and dynamics. However, current experimental modalities often resort to molecule immobilization for long observation times and do not always approach the resolution limit of FRET-based nanoscale metrology. Here we present ABEL-FRET, an immobilization-free platform for smFRET measurements with ultrahigh resolving power in FRET efficiency. Importantly, single-molecule diffusivity is used to provide additional size and shape information for hydrodynamic profiling of individual molecules, which, together with the concurrently measured intramolecular conformation through FRET, enables a holistic and dynamic view of biomolecules and their complexes.

Risk factors for anastomotic leak and postoperative morbidity after right hemicolectomy for colon cancer: results from a prospective, multi-centre, snapshot study in China.

BACKGROUND: Right hemicolectomy is the standard treatment for right-sided colon cancer. There is variation in the technical aspects of performing right hemicolectomy as well as in short-term outcomes. It is therefore necessary to explore best clinical practice following right hemicolectomy in expert centres. METHODS: This snapshot study of right hemicolectomy for colon cancer in China was a prospective, multicentre cohort study in which 52 tertiary hospitals participated. Eligible patients with stage I-III right-sided colon cancer who underwent elective right hemicolectomy were consecutively enrolled in all centres over 10 months. The primary endpoint was the incidence of postoperative 30-day anastomotic leak. RESULTS: Of the 1854 patients, 89.9 per cent underwent laparoscopic surgery and 52.3 per cent underwent D3 lymph node dissection. The overall 30-day morbidity and mortality were 11.7 and 0.2 per cent, respectively. The 30-day anastomotic leak rate was 1.4 per cent. In multivariate analysis, ASA grade > II (P < 0.001), intraoperative blood loss > 50 ml (P = 0.044) and D3 lymph node dissection (P = 0.008) were identified as independent risk factors for postoperative morbidity. Extracorporeal side-to-side anastomosis (P = 0.031), intraoperative blood loss > 50 ml (P = 0.004) and neoadjuvant chemotherapy (P = 0.004) were identified as independent risk factors for anastomotic leak. CONCLUSION: In high-volume expert centres in China, laparoscopic resection with D3 lymph node dissection was performed in most patients with right-sided colon cancer, and overall postoperative morbidity and mortality was low. Further studies are needed to explore the optimal technique for right hemicolectomy in order to improve outcomes further.

Heterometallic AuI 6 AgI 6 Macrocyclic Cluster Templated by a Supramolecular Melamine Dimer.

The application of supramolecular templates in aligning atomically precise heterometal arrays is important for pursuing functional materials. Herein, we report that a bilayered supramolecular tri-deprotonated melamine dimer functions as an effective template in the construction of a heterometallic gold(I)-silver(I) macrocyclic cluster [µ6 -(C3 N6 H3 )3- ]2 -AuI 6 AgI 6 . X-ray single crystal structural analysis showed that a crown-like AuI 6 AgI 6 macrocycle is aligned around two parallelly stacked µ6 -(C3 N6 H3 )3- moieties hold together with π-π interactions. Theoretical calculations revealed that the [µ6 -(C3 N6 H3 )3- ]2 motif dominantly contributes to the near-occupied orbitals in the electronic structure, which is closely related to its luminescence properties. This work demonstrates that the supramolecular templates containing multiple symmetric binding sites may present a facile approach in the construction of functional metal clusters.

'Passivated Precursor' Approach to All-Alkynyl-Protected Gold Nanoclusters and Total Structure Determination of Au130.

A 'passivated precursor' approach is developed for the efficient synthesis and isolation of all-alkynyl-protected gold nanoclusters. Direct reduction of dpa-passivated precursor Au-dpa (Hdpa=2,2'-dipyridylamine) in one-pot under ambient conditions gives a series of clusters including Au22(C≡CR)18 (R=-C6H4-2-F), Au36(C≡CR)24, Au44(C≡CR)28, Au130(C≡CR)50, and Au144(C≡CR)60. These clusters can be well separated via column chromatography. The overall isolation yield of this series of clusters is 40 % (based on gold), which is much improved in comparison with previous approaches. It is notable that the molecular structure of the giant cluster Au130(C≡CR)50 is revealed, which presents important information for understanding the structure of the mysterious Au130 nanoclusters. Theoretical calculations indicated Au130(C≡CR)50 has a smaller HOMO-LUMO gap than Au130(S-C6H4-4-CH3)50. This facile and reliable synthetic approach will greatly accelerate further studies on all-alkynyl-protected gold nanoclusters.

Efficacy of chidamide maintenance therapy versus autologous stem cell transplantation versus observation as a post-remission choice in the survival of adult patients with peripheral T-cell lymphoma: Post hoc analysis of a prospective, multicenter, phase 2 study in China.

In this prospective, multicenter, Phase 2 clinical trial (NCT02987244), patients with peripheral T-cell lymphomas (PTCLs) who had responded to first-line chemotherapy with cyclophosphamide, doxorubicin or epirubicin, vincristine or vindesine, etoposide, and prednisone (Chi-CHOEP) were treated by autologous stem cell transplantation (ASCT) or with chidamide maintenance or observation. A total of 85 patients received one of the following interventions: ASCT (n = 15), chidamide maintenance (n = 44), and observation (n = 26). estimated 3 PFS and OS rates were 85.6%, 80.8%, and 49.4% (P = 0.001). The two-year OS rates were 85.6%, 80.8%, and 69.0% (P = 0.075).The ASCT and chidamide maintenance groups had significantly better progression-free survival (PFS) than the observation group (P = 0.001, and P = 0.01, respectively). The overall survival (OS) differed significantly between the chidamide maintenance group and the observation group ( P = 0.041). The multivariate and propensity score matching analyses for PFS revealed better outcomes in the subjects in the chidamide maintenance than observation groups (P = 0.02). The ASCT and chidamide maintenance groups had significant survival advantages over the observation group. In the post-remission stage of the untreated PTCL patients, single-agent chidamide maintenance demonstrated superior PFS and better OS than observation. Our findings highlight the potential benefit of chidamide in this patient subset, warranting further investigation through larger prospective trials. Clinical trial registration: clinicaltrial.gov, NCT02987244. Registered 8 December 2016, http://www.clinicaltrials.gov/ct2/show/NCT02987244 .

Advances in Functionalized Biocomposites of Living Cells Combined with Metal-Organic Frameworks.

Motivated by the remarkable innate characteristics of cells in living organisms, we have found that hybrid materials that combine bioorganisms with nanomaterials have significantly propelled advancements in industrial applications. However, the practical deployment of unmodified living entities is inherently limited due to their sensitivity to environmental fluctuations. To surmount these challenges, an efficacious strategy for the biomimetic mineralization of living organisms with nanomaterials has emerged, demonstrating extraordinary potential in biotechnology. Among them, innovative composites have been engineered by enveloping bioorganisms with a metal-organic framework (MOF) coating. This review systematically summarizes the latest developments in living cells/MOF-based composites, detailing the methodologies employed in structure fabrication and their diverse applications, such as bioentity preservation, sensing, catalysis, photoluminescence, and drug delivery. Moreover, the synergistic benefits arising from the individual compounds are elucidated. This review aspires to illuminate new prospects for fabricating living cells/MOF composites and concludes with a perspective on the prevailing challenges and impending opportunities for future research in this field.

Association of intra-shift nap duration with heart rate variability in medical night shift workers.

Napping during night shifts effectively reduces disease risk and improves work performance, but few studies have investigated the association between napping and physiological changes, particularly in off-duty daily lives. Changes in the autonomic nervous system precede diseases like cardiovascular disease, diabetes, and obesity. Heart rate variability is a good indicator of autonomic nervous system. This study aimed to investigate the link between night shift nap durations and heart rate variability indices in the daily lives of medical workers. As indicators of chronic and long-term alterations, the circadian patterns of heart rate variability indices were evaluated. We recruited 146 medical workers with regular night shifts and divided them into four groups based on their self-reported nap durations. Heart rate variability circadian parameters (midline-estimating statistic of rhythm, amplitude, and acrophase) were obtained by obtaining 24-h electrocardiogram on a day without night shifts, plotting the data of the heart rate variability indices as a function of time, and fitting them into periodic cosine curves. Using clinical scales, depression, anxiety, stress, fatigue, and sleepiness were assessed. Linear regression analysis revealed a positive relationship between 61-120-min naps and 24-h, daytime, and night-time heart rate variability indices, and the parasympathetic activity oscillation amplitude (indexed by high-frequency power, the square root of the mean of the sum of squares of differences between adjacent normal intervals, standard deviation of short-term R-R-interval variability) within one circadian cycle. This study indicated that napping for 61-120 min during night shifts could benefit medical workers' health, providing physiological evidence to promote nap management.

Within-canopy variation in chlorophyll fluorescence parameters can be well captured by vertical patterns of leaf biophysical and chemical traits.

The strong correlation between chlorophyll fluorescence (ChlF) parameters and photosynthesis highlights the need for a comprehensive spatial representation of ChlF parameters within the canopy. Such an approach is essential to advance our understanding and to improve the representation and modeling of water and carbon fluxes at scales ranging from the leaf to the canopy level. However, the challenge remains in determining how to effectively describe and track the variability of ChlF parameters within the canopy. In this study, we determined the variation in leaf biophysical and chemical traits and ChlF parameters along the vertical height of the canopy for several species in a temperate deciduous forest. We observed general associations of height with leaf biophysical and chemical traits and ChlF parameters, although these relationships were species-dependent. In addition, leaf biophysical and chemical traits, particularly light-harvesting pigments, showed significant effects on ChlF parameters. To effectively track variation in ChlF parameters within the canopy, we used gradient-boosted regression (GBR) models driven by leaf traits and species, which explained more than 80% of the variation in all ChlF parameters. Our study demonstrates the feasibility of utilizing leaf biophysical and chemical traits to predict vertical variation in ChlF parameters and provide supportive data for modeling canopy photosynthesis.

Integrating leaf spectral and water status information to effectively track chlorophyll a fluorescence parameters during dehydration.

Monitoring changes in chlorophyll a (ChlFa) fluorescence during dehydration can provide insights into plant photosynthetic responses to climate change challenges, which are predicted to increase drought frequency. However, the limited knowledge of how ChlFa parameters respond to water deficit hinders the exploration of the photochemical mechanism of the photosynthetic process and the simulation of photosynthetic fluorescence models. Furthermore, how to track such responses of ChlFa parameters, especially at large scales, remains a challenge. In this study, we attempted to use spectral information reflected from leaves to follow the dynamic response patterns of ChlFa parameters of seven species under prolonged dehydration. The results showed that the investigated ChlFa parameters exhibited significant changes as dehydration progressed, with considerable variability among the different species as well as under different water conditions. This study also demonstrated that the integration of both spectral and water content information can provide an effective method for tracking ChlFa parameters during dehydration, explaining over 90% of the total variance in the measured ChlFa parameters. Collectively, these results should serve as a valuable reference for predicting the response of ChlFa parameters to dehydration and offer a potential method for estimating ChlFa parameters under drought conditions.

Interpretable machine learning-based clinical prediction model for predicting lymph node metastasis in patients with intrahepatic cholangiocarcinoma.

OBJECTIVE: Prediction of lymph node metastasis (LNM) for intrahepatic cholangiocarcinoma (ICC) is critical for the treatment regimen and prognosis. We aim to develop and validate machine learning (ML)-based predictive models for LNM in patients with ICC. METHODS: A total of 345 patients with clinicopathological characteristics confirmed ICC from Jan 2007 to Jan 2019 were enrolled. The predictors of LNM were identified by the least absolute shrinkage and selection operator (LASSO) and logistic analysis. The selected variables were used for developing prediction models for LNM by six ML algorithms, including Logistic regression (LR), Gradient boosting machine (GBM), Extreme gradient boosting (XGB), Random Forest (RF), Decision tree (DT), Multilayer perceptron (MLP). We applied 10-fold cross validation as internal validation and calculated the average of the areas under the receiver operating characteristic (ROC) curve to measure the performance of all models. A feature selection approach was applied to identify importance of predictors in each model. The heat map was used to investigate the correlation of features. Finally, we established a web calculator using the best-performing model. RESULTS: In multivariate logistic regression analysis, factors including alcoholic liver disease (ALD), smoking, boundary, diameter, and white blood cell (WBC) were identified as independent predictors for LNM in patients with ICC. In internal validation, the average values of AUC of six models ranged from 0.820 to 0.908. The XGB model was identified as the best model, the average AUC was 0.908. Finally, we established a web calculator by XGB model, which was useful for clinicians to calculate the likelihood of LNM. CONCLUSION: The proposed ML-based predicted models had a good performance to predict LNM of patients with ICC. XGB performed best. A web calculator based on the ML algorithm showed promise in assisting clinicians to predict LNM and developed individualized medical plans.