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Abstract Background Tumour immune macroenvironment is comprised of tumour and surrounding organs responding to tumourigenesis and immunotherapy. The lack of comprehensive analytical methods hinders its application for prediction of survival and treatment response in colorectal cancer (CRC) patients. Methods Cytometry by time‐of‐flight (CyTOF) and RNA‐seq was applied to characterise immune cell heterogeneity in a discovery cohort including tumour, blood and intestinal architecture comprising epithelium, lamina propria, submucosa, muscularis propria of normal bowel and tumour–adjacent bowel tissues. Immunoprofiling was also validated by a validation cohort using single‐cell RNA sequencing, spatial transcription, CyTOF and multiplex immunofluorescent staining. Results Based on cell phenotype and transcription, we identify distinct immunotypes in the CRC macroenvironment including blood, tumour and different intestinal architecture, showing disturbed immune cell compositions, increasing expression of immunosuppressive markers and cell–cell interactions contributing to immunosuppressive regulation. Furthermore, we evaluate immune macroenvironment influencing factors including tertiary lymphoid structures (TLSs), consensus molecular subtypes (CMSs) and immune checkpoint inhibitors (ICIs). TLS presence fuels anti‐tumour immunity by promoting CD8+ T cell infiltration and altering activation or suppression of T cell systematically. TLS presence correlates with patient survival, intrinsic CMS and therapeutic efficacy of ICI. PD‐1 and CD69 expressed in effector memory CD8+ T cells from blood can predict TLS presence in the CRC macroenvironment, serving as potential biomarkers for stratifying CRC patients into immunotherapy. Conclusions Our findings provide insights into the CRC immune macroenvironment, highlighting immune cell suppression and activation in tumourigenesis. Our study illustrates the potential utility of blood for predicting immunotherapy response. Key points Distinct immunotypes are identified in the CRC macroenvironment. TLS and immunotherapy exert influence on the immune macroenvironment. TLS presence correlates with patient survival, CMS and therapeutic efficacy of ICI. PD‐1 and CD69 expressed in CD8+ Tem from blood can predict TLS presence in the CRC macroenvironment.

Abstract Collecting duct carcinoma (CDC) is an aggressive rare subtype of kidney cancer with unmet clinical needs. Little is known about its underlying molecular alterations and etiology, primarily due to its rarity, and lack of preclinical models. This study aims to comprehensively characterize molecular alterations in CDC and identify its therapeutic vulnerabilities. Through whole-exome and transcriptome sequencing, we identified KRAS hotspot mutations (G12A/D/V) in 3/13 (23%) of the patients, in addition to known TP53, NF2 mutations. 3/13 (23%) patients carried a mutational signature (SBS22) caused by aristolochic acid (AA) exposures, known to be more prevalent in Asia, highlighting a geologically specific disease etiology. We further discovered that cell cycle-related pathways were the most predominantly dysregulated pathways. Our drug screening with our newly established CDC preclinical models identified a CDK9 inhibitor LDC000067 that specifically inhibited CDC tumor growth and prolonged survival. Our study not only improved our understanding of oncogenic molecular alterations of Asian CDC, but also identified cell-cycle machinery as a therapeutic vulnerability, laying the foundation for clinical trials to treat patients with such aggressive cancer.

Abstract Poly (ADP‐ribose) Polymerase inhibitors (PARPi) have demonstrated remarkable clinical efficacy in treating ovarian cancer (OV) with BRCA1/2 mutations. However, drug resistance inevitably limits their clinical applications and there is an urgent need for improved therapeutic strategies to enhance the clinical utility of PARPi, such as Olaparib. Here, compelling evidence indicates that sensitivity of PARPi is associated with cell cycle dysfunction. Through high‐throughput drug screening with a cell cycle kinase inhibitor library, XL413, a potent cell division cycle 7 (CDC7) inhibitor, is identified which can synergistically enhance the anti‐tumor efficacy of Olaparib. Mechanistically, the combined administration of XL413 and Olaparib demonstrates considerable DNA damage and DNA replication stress, leading to increased sensitivity to Olaparib. Additionally, a robust type‐I interferon response is triggered through the induction of the cGAS/STING signaling pathway. Using murine syngeneic tumor models, the combination treatment further demonstrates enhanced antitumor immunity, resulting in tumor regression. Collectively, this study presents an effective treatment strategy for patients with advanced OV by combining CDC7 inhibitors (CDC7i) and PARPi, offering a promising therapeutic approach for patients with limited response to PARPi.

Soil health reflects the sustained capacity of soil to function as a vital living ecosystem, ensuring support for all forms of life. The evaluation of soil health relies heavily on physicochemical indicators. However, it remains unclear whether and how microbial traits are related to soil health in soil with long-term organic manure amendment. This study aims to examine how detrimental and beneficial microbial traits change with soil health based on physicochemical indicators. This research measures the effects of 9-year manure supplementation on soil health using multiomics techniques. We found that, compared to 100% chemical fertilizers, the soil health index increased by 5.2%, 19.3%, and 72.6% with 25%, 50%, and 100% organic fertilizer amendments, respectively. Correspondingly, the abundance of beneficial microorganisms, including Actinomadura, Actinoplanes, Aeromicrobium, Agromyces, Azospira, Cryobacterium, Dactylosporangium, Devosia, Hyphomicrobium, Kribbella, and Lentzea, increased progressively, while the abundance of the pathogenic fungus Fusarium decreased with the organic manure application rate. In addition, the application of organic manure significantly increased the concentrations of soil metabolites, such as sugars (raffinose, trehalose, maltose, and maltotriose) and lithocholic acid, which promoted plant growth and soil aggregation. Moreover, the abundances of pathogens and beneficial microorganisms and the concentrations of beneficial soil metabolites were significantly correlated with the soil health index based on physicochemical indicators. We conclude that organic fertilizer can enhance soil health by promoting the increase in beneficial microorganisms while suppressing detrimental microorganisms, which can serve as potential indicators for assessing soil health. In agricultural production, substituting 25–50% of chemical fertilizers with organic fertilizers significantly helps improve soil health and promotes crop growth.

Background The main challenge against patients with cancer to derive benefits from immune checkpoint inhibitors targeting PD-1/PD-L1 appears to be the immunosuppressive tumor microenvironment (TME), in which IL-33/ST2 signal fulfills critical functions. However, whether IL-33 limits the therapeutic efficacy of anti-PD-L1 remains uncertain.Methods Molecular mechanisms of IL-33/ST2 signal on anti-PD-L1 treatment lewis lung carcinoma tumor model were assessed by RNA-seq, ELISA, WB and immunofluorescence (IF). A sST2-Fc fusion protein was constructed for targeting IL-33 and combined with anti-PD-L1 antibody for immunotherapy in colon and lung tumor models. On this basis, bifunctional fusion proteins were generated for PD-L1-targeted blocking of IL-33 in tumors. The underlying mechanisms of dual targeting of IL-33 and PD-L1 revealed by RNA-seq, scRNA-seq, FACS, IF and WB.Results After anti-PD-L1 administration, tumor-infiltrating ST2+ regulatory T cells (Tregs) were elevated. Blocking IL-33/ST2 signal with sST2-Fc fusion protein potentiated antitumor efficacy of PD-L1 antibody by enhancing T cell responses in tumor models. Bifunctional fusion protein anti-PD-L1-sST2 exhibited enhanced antitumor efficacy compared with combination therapy, not only inhibited tumor progression and extended the survival, but also provided long-term protective antitumor immunity. Mechanistically, the superior antitumor activity of targeting IL-33 and PD-L1 originated from reducing immunosuppressive factors, such as Tregs and exhausted CD8+ T cells while increasing tumor-infiltrating cytotoxic T lymphocyte cells.Conclusions In this study, we demonstrated that IL-33/ST2 was involved in the immunosuppression mechanism of PD-L1 antibody therapy, and blockade by sST2-Fc or anti-PD-L1-sST2 could remodel the inflammatory TME and induce potent antitumor effect, highlighting the potential therapeutic strategies for the tumor treatment by simultaneously targeting IL-33 and PD-L1.

Abstract Background Pancreatic cancer is a highly aggressive malignancy with limited treatment options and a poor prognosis. Trophoblast cell surface antigen 2 (TROP2), a cell surface antigen overexpressed in the tumors of more than half of pancreatic cancer patients, has been identified as a potential target for antibody–drug conjugates (ADCs). Almost all reported TROP2-targeted ADCs are of the IgG type and have been poorly studied in pancreatic cancer. Here, we aimed to develop a novel nanobody-drug conjugate (NDC) targeting TROP2 for the treatment of pancreatic cancer. Results In this study, we developed a novel TROP2-targeted NDC, HuNbTROP2-HSA-MMAE, for the treatment of TROP2-positive pancreatic cancer. HuNbTROP2-HSA-MMAE is characterized by the use of nanobodies against TROP2 and human serum albumin (HSA) and has a drug-antibody ratio of 1. HuNbTROP2-HSA-MMAE exhibited specific binding to TROP2 and was internalized into tumor cells with high endocytosis efficiency within 5 h, followed by intracellular translocation to lysosomes and release of MMAE to induce cell apoptosis in TROP2-positive pancreatic cancer cells through the caspase-3/9 pathway. In a xenograft model of pancreatic cancer, doses of 0.2 mg/kg and 1 mg/kg HuNbTROP2-HSA-MMAE demonstrated significant antitumor effects, and a dose of 5 mg/kg even eradicated the tumor. Conclusion HuNbTROP2-HSA-MMAE has desirable affinity, internalization efficiency and antitumor activity. It holds significant promise as a potential therapeutic option for the treatment of TROP2-positive pancreatic cancer. Graphical Abstract

Abstract Extensive investigations in outer space have revealed not only how life adapts to the space environment, but also that interesting biophysical phenomena occur. These phenomena affect human health and other life forms (animals, plants, bacteria, and fungi), and to ensure the safety of future human space exploration need to be further investigated. This calls for joint research efforts between biologists and physicists, as these phenomena present cross-disciplinary barriers. Various national organizations provide useful forums for bridging this gap. Additional discussion avenues and database resources are helpful for facilitating the interdisciplinary investigations of these phenomena. In this paper, we present the newly established Space Life Investigation Database (SpaceLID, https://bidd.group/spacelid/ ) which provides information about biophysical phenomena occurring in space. Examples obtained using the database are given while discussing the underlying causes of these phenomena and their implications for the physiology and health of life in space.

Liquid lead is the main coolant of the fourth generation of advanced nuclear energy system — lead cooled fast reactor (LFR), due to its good neutron economy, high heat transfer performance, stable chemical properties, constant low melting point, high boiling point, etc. Although there are many advantages, the corrosion of metal materials in liquid lead is one of the decisive factors restricting the development of lead cooled fast reactor. In this study, an engineering model for simulating the oxide film growth in liquid lead coolant is established, and the time-dependence of steel flux is analyzed based on the experimental data in the literature. The effects of circuit temperature, hydraulic diameter of section simulated, coolant velocity and steel types on the steel corrosion were investigated. The results showed that the oxide film formed on the steels is of micron grade and the diffusion yield of iron produced in pure lead coolant is of kilogram grade after ten years’ corrosion. The temperature and the coolant velocity have significant effects on the steel corrosion while the effect of hydraulic diameter is mild. Also, the steel types affect the growth of oxide film. The findings provide basic data for the evaluation of radioactive corrosion products of LFR.

FeCrAl alloy is one of the potential candidates of structural materials due to its high strength, low radiation swelling and good oxidation resistance for the application of lead-cooled fast reactors (LFRs). Particularly, FeCrAl alloy can form protective Al-containing oxide scales after exposure to liquid oxygen-rich Pb and lead–bismuth eutectic (LBE) at 400–800 ℃, showing better performance than traditional commercial stainless steels such as T91, 316L and 15-15Ti. Given the possibility that oxygen in liquid metal could be consumed and not be supplied timely in some quasi-static regions of the actual coolant circuit, to figure out the corrosion behavior of FeCrAl alloy in oxygen-depleted LBE is necessary. In this work, the commercial FeCrAl alloy was exposed to static liquid LBE containing Ni impurities with 10−9 wt% oxygen concentration at 600 ℃ for up to 5000 h, and the surface and cross-sectional morphology of the samples was characterized and analysed. It is found that FeCrAl alloy underwent severe dissolution corrosion, and the maximum penetration depth of LBE reached 161.4 μm after the test for 5000 h; PbBi infiltrated into alloy matrix along the GBs and selectively leached Al from the affected grains. Besides, an interesting discovery is the Cr-rich thin layer at LBE/matrix interface and Ni3Al precipitates in LBE penetration front which should be attributed to the deposition of impurity elements dissolved in liquid LBE during the cooling process.

Abstract BackgroundAlthough evidence-based medicine proposes personalized care that considers the best evidence, it still fails to address personal treatment in many real clinical scenarios where the complexity of the situation makes none of the available evidence applicable. “Medicine-based evidence” (MBE), in which big data and machine learning techniques are embraced to derive treatment responses from appropriately matched patients in real-world clinical practice, was proposed. However, many challenges remain in translating this conceptual framework into practice. ObjectiveThis study aimed to technically translate the MBE conceptual framework into practice and evaluate its performance in providing general decision support services for outcomes after congenital heart disease (CHD) surgery. MethodsData from 4774 CHD surgeries were collected. A total of 66 indicators and all diagnoses were extracted from each echocardiographic report using natural language processing technology. Combined with some basic clinical and surgical information, the distances between each patient were measured by a series of calculation formulas. Inspired by structure-mapping theory, the fusion of distances between different dimensions can be modulated by clinical experts. In addition to supporting direct analogical reasoning, a machine learning model can be constructed based on similar patients to provide personalized prediction. A user-operable patient similarity network (PSN) of CHD called CHDmap ResultsUsing 256 CHD cases, CHDmap was evaluated on 2 different types of postoperative prognostic prediction tasks: a binary classification task to predict postoperative complications and a multiple classification task to predict mechanical ventilation duration. A simple poll of the k ConclusionsWithout individual optimization, CHDmap demonstrates competitive performance compared to clinical experts. In addition, CHDmap has the advantage of enabling clinicians to use their superior cognitive abilities in conjunction with it to make decisions that are sometimes even superior to those made using artificial intelligence models. The MBE approach can be embraced in clinical practice, and its full potential can be realized.

Abstract Background Enhancer of zeste homolog 2 (EZH2), the key catalytic subunit of polycomb repressive complex 2 (PRC2), is overexpressed and plays an oncogenic role in various cancers through catalysis-dependent or catalysis-independent pathways. However, the related mechanisms contributing to ovarian cancer (OC) are not well understood. Methods The levels of EZH2 and H3K27me3 were evaluated in 105 OC patients by immunohistochemistry (IHC) staining, and these patients were stratified based on these levels. Canonical and noncanonical binding sites of EZH2 were defined by chromatin immunoprecipitation sequencing (ChIP-Seq). The EZH2 solo targets were obtained by integrative analysis of ChIP-Seq and RNA sequencing data. In vitro and in vivo experiments were performed to determine the role of EZH2 in OC growth. Results We showed that a subgroup of OC patients with high EZH2 expression but low H3K27me3 exhibited the worst prognosis, with limited therapeutic options. We demonstrated that induction of EZH2 degradation but not catalytic inhibition profoundly blocked OC cell proliferation and tumorigenicity in vitro and in vivo. Integrative analysis of genome-wide chromatin and transcriptome profiles revealed extensive EZH2 occupancy not only at genomic loci marked by H3K27me3 but also at promoters independent of PRC2, indicating a noncanonical role of EZH2 in OC. Mechanistically, EZH2 transcriptionally upregulated IDH2 to potentiate metabolic rewiring by enhancing tricarboxylic acid cycle (TCA cycle) activity, which contributed to the growth of OC. Conclusions These data reveal a novel oncogenic role of EZH2 in OC and identify potential therapeutic strategies for OC by targeting the noncatalytic activity of EZH2.

Abstract The pathogenesis of diabetic kidney disease (DKD) is complicated. Current clinical treatments fail to achieve satisfactory efficacy in the prevention of DKD progression, it urgently needs novel and effective treatment for DKD. In this study, we firstly demonstrated that renal lipid metabolism abnormality and inflammation significantly changed in DKD conditions by mining public transcriptomic data of DKD patient samples. KEGG analysis further exhibited the critical role of vascular endothelial growth factor B (VEGF-B) and interleukin 17A (IL-17A) signal pathways in DKD progression, indicating that VEGF-B and IL-17A might be the promising targets for DKD treatment. Then the potential of a novel combination therapy, anti-VEGF-B plus anti-IL-17A antibody, was evaluated for DKD treatment. Our results demonstrated that simultaneous blockade of VEGF-B and IL-17A signaling with their neutralizing antibodies alleviated renal damage and ameliorated renal function. The therapeutic effectiveness was not only related to the reduced lipid deposition especially the neutral lipids in kidney but also associated with the decreased inflammation response. Moreover, the therapy alleviated renal fibrosis by reducing collagen deposition and the expression of fibronectin and α-SMA in kidney tissues. RNA-seq analysis indicated that differential expression genes (DEGs) in db/db mice were significantly clustered into lipid metabolism, inflammation, fibrosis and DKD pathology-related pathways, and 181 of those DEGs were significantly reversed by the combinatory treatment, suggesting the underlying mechanism of administration of anti-VEGF-B and anti-IL-17A antibodies in DKD treatment. Taken together, this study identified that renal lipid metabolism abnormality and inflammation were critically involved in the progression of DKD, and simultaneous blockade of VEGF-B and IL-17A signaling represents a potential DKD therapeutic strategy.

The human gut microbiota, comprising trillions of microorganisms residing in the gastrointestinal tract, has emerged as a pivotal player in modulating various aspects of human health and disease. Recent research has shed light on the intricate relationship between the gut microbiota and pharmaceuticals, uncovering profound implications for drug metabolism, efficacy, and safety. This review depicted the landscape of molecular mechanisms and clinical implications of dynamic human gut Microbiota-Drug Interactions (MDI), with an emphasis on the impact of MDI on drug responses and individual variations. This review also discussed the therapeutic potential of modulating the gut microbiota or harnessing its metabolic capabilities to optimize clinical treatments and advance personalized medicine, as well as the challenges and future directions in this emerging field.

Abstract Background This study compared the survival outcomes of different surgical approaches to determine the optimal approach for gastric cardia adenocarcinoma (GCA) and aimed to standardize the surgical treatment guidelines for GCA. Methods A total of 7103 patients with GCA were enrolled from our previously established gastric cardia and esophageal carcinoma databases. In our database, when the epicenter of the tumor was at or within 2 cm distally from the esophagogastric junction, the adenocarcinoma was considered to originate from the cardia and was considered a Siewert type 2 cancer. The main criteria for the enrolled patients included treatment with radical surgery, no radio- or chemotherapy before the operation, and detailed clinicopathological information. Follow-up was mainly performed by telephone or through home interviews. According to the medical records, the surgical approaches included transthoracic, thoracoabdominal, and transabdominal approaches. Kaplan–Meier and Cox proportional hazards regression models were applied to correlate the surgical approach with survival in patients with GCA. Results There were marked differences in age and tumor stage among the patients who underwent the three surgical approaches (P

Abstract Background An increase in the incidence of central venous catheter (CVC)-related thrombosis (CRT) has been reported in pediatric intensive care patients over the past decade. Risk factors for the development of CRT are not well understood, especially in children. The study objective was to identify potential clinical risk factors associated with CRT with novel fusion machine learning models. Methods Patients aged 0–18 who were admitted to intensive care units from December 2015 to December 2018 and underwent at least one CVC placement were included. Two fusion model approaches (stacking and blending) were used to build a better performance model based on three widely used machine learning models (logistic regression, random forest and gradient boosting decision tree). High-impact risk factors were identified based on their contribution in both fusion artificial intelligence models. Results A total of 478 factors of 3871 patients and 3927 lines were used to build fusion models, one of which achieved quite satisfactory performance (AUC = 0.82, recall = 0.85, accuracy = 0.65) in 5-fold cross validation. A total of 11 risk factors were identified based on their independent contributions to the two fusion models. Some risk factors, such as D-dimer, thrombin time, blood acid-base balance-related factors, dehydrating agents, lymphocytes and basophils were identified or confirmed to play an important role in CRT in children. Conclusions The fusion model, which achieves better performance in CRT prediction, can better understand the risk factors for CRT and provide potential biomarkers and measures for thromboprophylaxis in pediatric intensive care settings.

BackgroundThis study was intended to construct a brand new prognostic nomogram after combine clinical and pathological characteristics to increases prognostic value in patients with esophageal squamous cell carcinoma.MethodsA total of 1,634 patients were included. Subsequently, the tumor tissues of all patients were prepared into tissue microarrays. AIPATHWELL software was employed to explore tissue microarrays and calculate the tumor-stroma ratio. X-tile was adopted to find the optimal cut-off value. Univariate and multivariate Cox analyses were used to screen out remarkable characteristics for constructing the nomogram in the total populations. A novel prognostic nomogram with clinical and pathological characteristics was constructed on the basis of the training cohort (n=1,144). What’s more performance was validated in the validation cohort (n=490). Clinical-pathological nomogram were assessed by concordance index, time-dependent receiver operating characteristic, calibration curve and decision curve analysis.ResultsThe patients can divide into two groups with cut-off value of 69.78 for the tumor-stroma ratio. It is noteworthy that the survival difference was noticeable (P

Background: Acute kidney injury (AKI) is a common complication after pediatric cardiac surgery. And autologous blood transfusion (ABT) is an important predictor of postoperative AKI. Unlike previous studies, which mainly focused on the correlation between ABT and AKI, the current study focuses heavily on the causal relationship between them, thus providing guidance for the treatment of patients during hospitalization to reduce the occurrence of AKI. Methods: A retrospective cohort of 3386 patients extracted from the Pediatric Intensive Care database was used for statistical analysis, multifactorial analysis, and causal inference. Characteristics that were correlated with ABT and AKI were categorized as confounders, instrumental variables, and effect modifiers, and were entered into the DoWhy causal inference model to determine causality. The calculated average treatment effect (ATE) was compared with the results of the multifactorial analysis. Results: The adjusted odds ratio (OR) for ABT volume was obtained by multifactorial analysis as 0.964. The DoWhy model refute test was able to indicate a causal relationship between ABT and AKI. Any ABT reduces AKI about 15.3%–18.8% by different estimation methods. The ATE regarding the amount of ABT was –0.0088, suggesting that every 1 mL/kg of ABT reduced the risk of AKI by 0.88%. Conclusions: Intraoperative transfusion of autologous blood can have a protective effect against postoperative AKI.

Abstract Background An increase in the incidence of central venous catheter (CVC)-associated deep venous thrombosis (CADVT) has been reported in pediatric patients over the past decade. At the same time, current screening guidelines for venous thromboembolism risk have low sensitivity for CADVT in hospitalized children. This study utilized a multimodal deep learning model to predict CADVT before it occurs. Methods Children who were admitted to intensive care units (ICUs) between December 2015 and December 2018 and with CVC placement at least 3 days were included. The variables analyzed included demographic characteristics, clinical conditions, laboratory test results, vital signs and medications. A multimodal deep learning (MMDL) model that can handle temporal data using long short-term memory (LSTM) and gated recurrent units (GRUs) was proposed for this prediction task. Four benchmark machine learning models, logistic regression (LR), random forest (RF), gradient boosting decision tree (GBDT) and a published cutting edge MMDL, were used to compare and evaluate the models with a fivefold cross-validation approach. Accuracy, recall, area under the ROC curve (AUC), and average precision (AP) were used to evaluate the discrimination of each model at three time points (24 h, 48 h and 72 h) before CADVT occurred. Brier score and Spiegelhalter’s z test were used measure the calibration of these prediction models. Results A total of 1830 patients were included in this study, and approximately 15% developed CADVT. In the CADVT prediction task, the model proposed in this paper significantly outperforms both traditional machine learning models and existing multimodal deep learning models at all 3 time points. It achieved 77% accuracy and 90% recall at 24 h before CADVT was discovered. It can be used to accurately predict the occurrence of CADVT 72 h in advance with an accuracy of greater than 75%, a recall of more than 87%, and an AUC value of 0.82. Conclusion In this study, a machine learning method was successfully established to predict CADVT in advance. These findings demonstrate that artificial intelligence (AI) could provide measures for thromboprophylaxis in a pediatric intensive care setting.

IntroductionAlthough PD-1/L1 mAb has demonstrated clinical benefits in certain cancer types, low response rate and resistance remain the main challenges for the application of these immune checkpoint inhibitors (ICIs). 4-1BB is a co-stimulator molecule expressed in T cells, which could enhance T cell proliferation and activation. Herein, the synergetic antitumor effect and underlying mechanism of 4-1BB agonist combined with PD-1/PD-L1 blockade were determined in B-cell lymphoma (BCL).MethodsSubcutaneous transplantation BCL tumor models and metastasis models were established to evaluate the therapeutic effect of PD-L1 antibody and/or 4-1BB agonist in vivo. For the mechanistic study, RNA-seq was applied to analyze the tumor microenvironment and immune-related signal pathway after combination treatment. The level of IFN-γ, perforin, and granzyme B were determined by ELISA and Real-time PCR assays, while tumor-infiltrating T cells were measured by flow cytometry and immunohistochemical analysis. CD4/CD8 specific antibodies were employed to deplete the related T cells to investigate the role CD4+ and CD8+ T cells played in combination treatment.ResultsOur results showed that combining anti-PD-L1 ICI and 4-1BB agonists elicited regression of BCL and significantly extended the survival of mice compared to either monotherapy. Co-targeting PD-L1 and 4-1BB preferentially promoted intratumoral cytotoxic lymphocyte infiltration and remodeled their function. RNA-sequence analysis uncovered a series of up-regulated genes related to the activation and proliferation of cytotoxic T lymphocytes, further characterized by increased cytokines including IFN-γ, granzyme B, and perforin. Furthermore, depleting CD8+ T cells not CD4+ T cells totally abrogated the antitumor efficacy, indicating the crucial function of the CD8+ T cell subset in the combination therapy.DiscussionIn summary, our findings demonstrated that 4-1BB agonistic antibody intensified the antitumor immunity of anti-PD-1/PD-L1 ICI via promoting CD8+ T cell infiltration and activation, providing a novel therapeutic strategy to BCL.

Accurate measurements of the oxygen concentration in liquid lead-bismuth eutectic (LBE) alloys are essential for ensuring optimum cooling conditions in heavy liquid metal coolant fast reactors. However, while unavoidable variations in the Bi contents of these alloys can affect the accuracy of these measurements, this issue has not yet been rigorously evaluated. The present work addresses this issue by evaluating variations in oxygen concentration measurements obtained experimentally for oxygen-saturated liquid LBE alloys with different Bi contents at different temperatures using a solid electrolyte oxygen sensor. Theoretical relationships are established between sensor voltage, oxygen concentration, temperature, and Bi content under the applied experimental conditions, and excellent agreement is obtained between the experimental and theoretical results. The theoretical relationships establish that the voltage decreases by about 1 mV for every 1 wt% increase in Bi content at a temperature of 400 °C. At a fixed voltage, with the increase of T, the influence of the Bi content on the CO calculation results gradually increased. Finally, the impact of varying Bi contents on the accuracy of oxygen concentration measurements is evaluated under practical reactor operation conditions, and higher requirements for the control of dissolved oxygen in LBE-cooled fast reactors are proposed.

Biological experiments performed in space crafts like space stations, space shuttles, and recoverable satellites has enabled extensive spaceflight life investigations (SLIs). In particular, SLIs have revealed distinguished space effects on microbial growth, survival, metabolite production, biofilm formation, virulence development and drug resistant mutations. These provide unique perspectives to ground-based microbiology and new opportunities for industrial pharmaceutical and metabolite productions. SLIs are with specialized experimental setups, analysis methods and research outcomes, which can be accessed by established databases National Aeronautics and Space Administration (NASA) Life Science Data Archive, Erasmus Experiment Archive, and NASA GeneLab. The increasing research across diverse fields may be better facilitated by databases of convenient search facilities and categorized presentation of comprehensive contents. We therefore developed the Space Life Investigation Database (SpaceLID) http://bidd.group/spacelid/, which collected SLIs from published academic papers. Currently, this database provides detailed menu search facilities and categorized contents about the studied phenomena, materials, experimental procedures, analysis methods, and research outcomes of 448 SLIs of 90 species (microbial, plant, animal, human), 81 foods and 106 pharmaceuticals, including 232 SLIs not covered by the established databases. The potential applications of SpaceLID are illustrated by the examples of published experimental design and bioinformatic analysis of spaceflight microbial phenomena.

Abstract The quality of treatment and prognosis after pediatric congenital heart surgery remains unsatisfactory. A reliable prediction model for postoperative complications of congenital heart surgery patients is essential to enable prompt initiation of therapy and improve the quality of prognosis. Here, we develop an interpretable machine-learning-based model that integrates patient demographics, surgery-specific features and intraoperative blood pressure data for accurately predicting complications after pediatric congenital heart surgery. We used blood pressure variability and the k-means algorithm combined with a smoothed formulation of dynamic time wrapping to extract features from time-series data. In addition, SHAP framework was used to provide explanations of the prediction. Our model achieved the best performance both in binary and multi-label classification compared with other consensus-based risk models. In addition, this explainable model explains why a prediction was made to help improve the clinical understanding of complication risk and generate actionable knowledge in practice. The combination of model performance and interpretability is easy for clinicians to trust and provide insight into how they should respond before the condition worsens after pediatric congenital heart surgery.

The Hedgehog (HH) signaling pathway plays important roles in gastrointestinal carcinogenesis and the gastrointestinal tumor microenvironment (TME). Aberrant HH signaling activation may accelerate the growth of gastrointestinal tumors and lead to tumor immune tolerance and drug resistance. The interaction between HH signaling and the TME is intimately involved in these processes, for example, tumor growth, tumor immune tolerance, inflammation, and drug resistance. Evidence indicates that inflammatory factors in the TME, such as interleukin 6 (IL-6) and interferon-γ (IFN-γ), macrophages, and T cell-dependent immune responses, play a vital role in tumor growth by affecting the HH signaling pathway. Moreover, inhibition of proliferating cancer-associated fibroblasts (CAFs) and inflammatory factors can normalize the TME by suppressing HH signaling. Furthermore, aberrant HH signaling activation is favorable to both the proliferation of cancer stem cells (CSCs) and the drug resistance of gastrointestinal tumors. This review discusses the current understanding of the role and mechanism of aberrant HH signaling activation in gastrointestinal carcinogenesis, the gastrointestinal TME, tumor immune tolerance and drug resistance and highlights the underlying therapeutic opportunities.

Abstract Trastuzumab emtansine (T-DM1), an antibody-drug conjugate consisted of the HER2-targeted monoclonal antibody trastuzumab and the tubulin inhibitor emtansine, has shown potent therapeutic value in HER2-positive breast cancer (BC). However, a clinical trial indicated that T-DM1 exerts a limited effect on HER2-positive gastric cancer (GC), but the underlying mechanism is inconclusive. Our research attempted to reveal the probable mechanism and role of autophagy in T-DM1-treated HER2-positive GC. In this study, our results showed that T-DM1 induced apoptosis and exhibited potent therapeutic efficacy in HER2-positive GC cells. In addition, autophagosomes were observed by transmission electron microscopy. Autophagy was markedly activated and exhibited the three characterized gradations of autophagic flux, consisting of the formation of autophagosomes, the fusion of autophagosomes with lysosomes, and the deterioration of autophagosomes in autolysosomes. More importantly, autophagic inhibition by the suppressors 3-methyladenine (3-MA) and LY294002 significantly potentiated cytotoxicity and apoptosis in HER2-positive GC cells in vitro, while the combined use of LY294002 and T-DM1 elicited potent anti-GC efficacy in vivo. In mechanistic experiments, immunoblot analysis indicated the downregulated levels of Akt, mTOR, and P70S6K and confocal microscopy analysis clearly showed that autophagic inhibition promoted the fusion of T-DM1 molecules with lysosomes in GC cells. In conclusion, our research demonstrated that T-DM1 induced apoptosis as well as cytoprotective autophagy, and autophagic inhibition could potentiate the antitumor effect of T-DM1 on HER2-positive GC. Furthermore, autophagic inhibition might increase the fusion of T-DM1 with lysosomes, which might accelerate the release of the cytotoxic molecule emtansine from the T-DM1 conjugate. These findings highlight a promising therapeutic strategy that combines T-DM1 with an autophagy inhibitor to treat HER-positive GC more efficiently.

The lead-cooled fast reactor (LFR) is one of six reactor concepts selected in the Generation IV Technology Roadmap and is perhaps the first to be applied commercially. Because the heavy liquid metal coolant has a severe corrosion effect on the core structure, the compatibility of the heavy liquid metal coolant and structural materials is recognized as a key limitation in the design and application of the LFR. Corrosion by heavy liquid metals such as liquid lead or lead–bismuth eutectic (LBE) is a physical or physical–chemical process involving surface oxidation, dissolution of material constituents, erosion corrosion, and fretting corrosion. Corrosion by heavy liquid metal can change the microstructure, composition, and surface morphology of structural materials, which will affect their mechanical and physical properties and lead to system failure. Currently, LFR research institutes are devoting great effort to the research and development of structural materials with good high-temperature mechanical properties and excellent corrosion and irradiation resistances. In this study, a series of experiments and analyses were performed on self-developed 11Cr−1Si ferritic/martensitic (F/M) steel, including heat treatment tests, mechanical tests, corrosion tests in static lead-bismuth eutectic (LBE), and slow strain-rate tests (SSRT) in LBE. The heat treatment results show that 11Cr−1Si steel obtains a good combination of high strength and toughness after quenching at 950 ℃ and tempering at 750 ℃. 11Cr−1Si steel was found to have good LBE corrosion resistance after exposure in static LBE for 3368 h, with a sufficiently low oxidation rate and a continuous and compact surface oxide layer, which protect the base metal of 11Cr−1Si from LBE penetration. The SSRT results show that the ductility of 11Cr−1Si in contact with LBE is sensitive to temperature, with loss of ductility observed at 350 ℃ and 400 ℃, but not at 450 ℃.

Titanium stabilized austenitic stainless steel of 15Cr-15Ni-Ti (15-15Ti) is a primary choice for fast reactor cladding material due to its high ductility, high oxidation and corrosion resistance. In order to further improve the irradiation resistance and operating temperature, it is necessary to produce the second phase reinforced 15-15Ti steels. In this work, three 50 kg 15-15Ti-Y ingots were prepared by casting method assisted by oxygen carrier and the Y additions were 0, 0.25 wt% and 0.5 wt%, respectively. Microstructure observation indicated the optimal addition of Y was 0.25 wt%. As Y addition reached 0.5 wt%, nonuniform microstructure with streamline distribution of Y-O-bearing particles and TiC appeared. In the 15-15Ti-25Y steel, average size of the Y-O-bearing particles were 10–155 nm and the number density of second particles was 9.40 × 1020 m−3. Furthermore, the uniform distribution of these fine particles remarkably improved the strength at high temperatures. Specifically, the yield strength of the 15-15Ti-25Y steel was 1.8 times than that of the Y-free steel at 600 °C.

Esophageal squamous cell carcinoma (ESCC) is one of the most common aggressive malignancies worldwide, particularly in northern China. The absence of specific early symptoms and biomarkers leads to late-stage diagnosis, while early diagnosis and risk stratification are crucial for improving overall prognosis. We performed UPLC-MS/MS on 450 ESCC patients and 588 controls consisting of a discovery group and two validation groups to identify biomarkers for early detection and prognosis. Bioinformatics and clinical statistical methods were used for profiling metabolites and evaluating potential biomarkers. A total of 105 differential metabolites were identified as reliable biomarker candidates for ESCC with the same tendency in three cohorts, mainly including amino acids and fatty acyls. A predictive model of 15 metabolites [all-trans-13,14-dihydroretinol, (±)-myristylcarnitine, (2S,3S)-3-methylphenylalanine, 3-(pyrazol-1-yl)-L-alanine, carnitine C10:1, carnitine C10:1 isomer1, carnitine C14-OH, carnitine C16:2-OH, carnitine C9:1, formononetin, hyodeoxycholic acid, indole-3-carboxylic acid, PysoPE 20:3, PysoPE 20:3(2n isomer1), and resolvin E1] was developed by logistic regression after LASSO and random forest analysis. This model held high predictive accuracies on distinguishing ESCC from controls in the discovery and validation groups (accuracies > 89%). In addition, the levels of four downregulated metabolites [hyodeoxycholic acid, (2S,3S)-3-methylphenylalanine, carnitine C9:1, and indole-3-carboxylic acid] were significantly higher in early cancer than advanced cancer. Furthermore, three independent prognostic markers were identified by multivariate Cox regression analyses with and without clinical indicators: a high level of MG(20:4)isomer and low levels of 9,12-octadecadienoic acid and L-isoleucine correlated with an unfavorable prognosis; the risk score based on these three metabolites was able to stratify patients into low or high risk. Moreover, pathway analysis indicated that retinol metabolism and linoleic acid metabolism were prominent perturbed pathways in ESCC. In conclusion, metabolic profiling revealed that perturbed amino acids and lipid metabolism were crucial metabolic signatures of ESCC. Both panels of diagnostic and prognostic markers showed excellent predictive performances. Targeting retinol and linoleic acid metabolism pathways may be new promising mechanism-based therapeutic approaches. Thus, this study would provide novel insights for the early detection and risk stratification for the clinical management of ESCC and potentially improve the outcomes of ESCC.

Laminar separation induced flow transition has been regarded as one main source of flow losses of low-pressure turbines (LPTs). The realistic roughness favors the reduction of flow losses as the separation bubble reduces and even disappears. In this paper, a detailed grid-independent study is first presented to verify and validate the numerical solutions by solving Reynolds-averaged Navier–Stokes and shear stress transport γ-Reθ̃ transition model equations for a typical high-lift LPT. The roughness elements with different heights (Ra) are uniformly imposed on the whole suction side. The effects of Ra on the flow separation and transition and, thus, flow losses are studied. The results demonstrate that there is one critical Ra value, below which the flow losses decrease, while above which the flow losses increase as Ra increases. The roughness allocations by imposing roughness elements on different blade portions of the suction side are also studied. The sensitivities of flow loss reduction to roughness allocation are evaluated and illustrated. Moreover, the effects of Reynolds numbers (Re) are investigated. As Re decreases, the critical Ra value increases and a more roughened blade is favorable for flow loss reduction. This study paves the way for finding a practicable flow control method reducing the flow losses by optimally allocating roughness on the blade of high-lift LPTs.

Abstract Background Drug safety in children is a major concern; however, there is still a lack of methods for quantitatively measuring, let alone to improving, drug safety in children under different clinical conditions. To assess pediatric drug safety under different clinical conditions, a computational method based on Electronic Medical Record (EMR) datasets was proposed. Methods In this study, a computational method was designed to extract the significant drug-diagnosis associations (based on a Bonferroni-adjusted hypergeometric P-value

Cisplatin is a major antineoplastic drug that is used to treat solid tumors, but its use is restricted by its nephrotoxicity. Such cisplatin‐induced nephrotoxicity (CIN) is believed to occur primarily through mitochondrial damage and reactive oxygen species (ROS) generation. Our previous studies have indicated that Panax notoginseng saponins (PNSs) mitigate CIN by enhancing hypoxia‐inducible factor 1α (HIF‐1α)‐induced mitochondrial autophagy. In this study, the role of the HIF‐1α/mitochondria/ROS pathway in PNSs protection against CIN was investigated using a rat model. A CIN model was generated by giving rats intraperitoneal injections with cisplatin (a single dose) and then treating them with or without 2‐methoxyestradiol (HIF‐1α inhibitor) and PNSs. We then measured ROS levels, superoxide dismutase, glutathione, catalase malondialdehyde and nitric oxide (to evaluate oxidative stress) and ATP, mitochondrial membrane potential and mitochondrial permeability transition pore opening (to evaluate mitochondrial function) in kidneys at different time points. We observed that PNSs remarkably reduced the levels of ROS, malondialdehyde and nitric oxide, as well as the opening of mitochondrial permeability transition pore, which is increased by cisplatin and further increased by HIF‐1α inhibition. In addition, PNSs increased the levels of superoxide dismutase, catalase and glutathione, as well as ATP and mitochondrial membrane potential in renal tissues; these are all reduced by cisplatin and further reduced by HIF‐1α inhibition. In conclusion, we demonstrate here that PNSs protects against mitochondrial damage induced by cisplatin through HIF‐1α/mitochondria/ROS.

In this paper, nano SiO2 particles modified organic silane coatings were successfully prepared to aim at the application of the self-cleaning coating on PMMA substrate for deep-sea optical windows. The chemicals, surface microstructure, wettability, hardness, adhesion, transparency, water scouring resistance as well as microorganism attachment rate of the coatings were investigated. The results showed that adding SiO2 nanoparticles into the organic silicon coating can effectively improve the hydrophobicity due to generating a micro-nano structure surface. However, excessive addition would result in a decrease in hydrophobicity, adhesion, as well as transparency, due to the inorganic SiO2 particle destroying the integrity of the organic coating. The optimal coating was obtained by adding 0.5 wt% nano SiO2 particles, which possessed a water contact angle of 114.2°, hardness of 4H, adhesion level of 0, and visible light transmittance of 0.886. After 40-h water scouring, the water contact angle decreased to 108.3° and the visible light transmittance decreased to 0.839, suggesting good water scouring resistance. The microorganism attachment rate of the S05 coating was 0.17% after a 6 h immersion test, which was about half that of the PMMA substrate.

Influenza A virus infection is usually associated with acute lung injury, which is typically characterized by tracheal mucosal barrier damage and an interleukin 17A (IL-17A)-mediated inflammatory response in lung tissues. Although targeting IL-17A has been proven to be beneficial for attenuating inflammation around lung cells, it still has a limited effect on pulmonary tissue recovery after influenza A virus infection. In this research, interleukin 22 (IL-22), a cytokine involved in the repair of the pulmonary mucosal barrier, was fused to the C-terminus of the anti-IL-17A antibody vunakizumab to endow the antibody with a tissue recovery function. The vunakizumab-IL22 (vmab-IL-22) fusion protein exhibits favorable stability and retains the biological activities of both the anti-IL-17A antibody and IL-22 in vitro. Mice infected with lethal H1N1 influenza A virus and treated with vmab-mIL22 showed attenuation of lung index scores and edema when compared to those of mice treated with saline or vmab or mIL22 alone. Our results also illustrate that vmab-mIL22 triggers the upregulation of MUC2 and ZO1, as well as the modulation of cytokines such as IL-1β, HMGB1 and IL-10, indicating the recovery of pulmonary goblet cells and the suppression of excessive inflammation in mice after influenza A virus infection. Moreover, transcriptome profiling analysis suggest the downregulation of fibrosis-related genes and signaling pathways, including genes related to focal adhesion, the inflammatory response pathway, the TGF-β signaling pathway and lung fibrosis upon vmab-mIL22 treatment, which indicates that the probable mechanism of vmab-mIL22 in ameliorating H1N1 influenza A-induced lung injury. Our results reveal that the bifunctional fusion protein vmab-mIL22 can trigger potent therapeutic effects in H1N1-infected mice by enhancing lung tissue recovery and inhibiting pulmonary inflammation, which highlights a potential approach for treating influenza A virus infection by targeting IL-17A and IL-22 simultaneously.

Abstract Kidney damage initiates the deteriorating metabolic states in tubule cells that lead to the development of end‐stage renal disease (ESTD). Interleukin‐22 (IL‐22) is an effective therapeutic antidote for kidney injury via promoting kidney recovery, but little is known about the underlying molecular mechanisms. Here, we first provide evidence that IL‐22 attenuates kidney injury via metabolic reprogramming of renal tubular epithelial cells (TECs). Specifically, our data suggest that IL‐22 regulates mitochondrial function and glycolysis in damaged TECs. Further observations indicate that IL‐22 alleviates the accumulation of mitochondrial reactive oxygen species (ROS) and dysfunctional mitochondria via the induction of AMPK/AKT signaling and PFBFK3 activities. In mice, amelioration of kidney injury and necrosis and improvement of kidney functions via regulation of these metabolism relevant signaling and mitochondrial fitness of recombinant IL‐22 are certificated in cisplatin‐induced kidney damage and diabetic nephropathy (DN) animal models. Taken together, our findings unravel new mechanistic insights into protective effects of IL‐22 on kidneys and highlight the therapeutic opportunities of IL‐22 and the involved metabolic regulators in various kidney diseases.

The lead–bismuth eutectic (LBE) can be easily activated by neutron radiation to produce the radionuclide 210Po. It is therefore necessary to establish an effective method to remove vaporized polonium in the cover gas to prevent its release into the air in scenarios of reactor maintenance and coolant leakage accidents. This paper presents a SiO2 nanofiber membrane prepared based on the electrostatic spinning and calcination process. The SiO2 nanofiber membrane had the advantages of good flexibility, high-temperature resistance, and corrosion resistance. In the trapping experiments, the SiO2 nanofiber membrane filters showed excellent filtration performance at 300~400 °C, and the filtration efficiencies for Te, Pb, and Bi could reach 99%, 99%, and 98%, respectively. Proper filtration temperature and gas flow rate are important to maintain high filtration efficiency. After five cycles, the SiO2 nanofiber membrane filter still exhibited excellent cycle-use performance. In the density functional theory (DFT) calculations, PbPo and PbTe had strong interactions with amorphous SiO2, having adhesion energies of −2.96 to −2.83 eV/molecule.

Aqueous solubility is an important physicochemical property of compounds in anti-cancer drug discovery. Artificial intelligence solubility prediction tools have scored impressive performances by employing regression, machine learning, and deep learning methods. The reported performances vary significantly partly because of the different datasets used. Solubility prediction on novel compounds needs to be improved, which may be achieved by going deeper with deep learning. We constructed deeper-net models of ~20-layer modified ResNet convolutional neural network architecture, which were trained and tested with 9,943 compounds encoded by molecular fingerprints. Retrospectively tested by 62 recently-published novel compounds, one deeper-net model outperformed four established tools, shallow-net models, and four human experts. Deeper-net models also outperformed others in predicting the solubility values of a series of novel compounds newly-synthesized for anti-cancer drug discovery. Solubility prediction may be improved by going deeper with deep learning. Our deeper-net models are accessible at http://www.npbdb.net/solubility/index.jsp.

A kind of Y-bearing ferritic/martensitic fuel cladding tube with qualified dimensions, acceptable mechanical properties as well as good flattening and flaring performance was manufactured recently by our group. In this paper, to improve and further evaluate its oxidation resistance, the cladding tube was aluminized firstly and then subjected to high temperature steam oxidation at 1200 °C for 8 h. The results indicated that aluminizing coating with gradient content of Al was prepared on the tube successfully. And the matrix microstructure was transformed from tempered martensite into ferrite during aluminizing. Weight gains after high temperature steam oxidation were 72.7 and 1.48 mg cm ^−2 for the bare and aluminized tubes, respectively. The latter one exhibited better oxidation resistance due to the generated dense aluminum oxide film. Meanwhile, Kirkendall pores were formed near oxidation surface and should be eliminated for the real application of the aluminized tube in the future.

Knowledge of protein function is important for biological, medical and therapeutic studies, but many proteins are still unknown in function. There is a need for more improved functional prediction methods. Our SVM-Prot web-server employed a machine learning method for predicting protein functional families from protein sequences irrespective of similarity, which complemented those similarity-based and other methods in predicting diverse classes of proteins including the distantly-related proteins and homologous proteins of different functions. Since its publication in 2003, we made major improvements to SVM-Prot with (1) expanded coverage from 54 to 192 functional families, (2) more diverse protein descriptors protein representation, (3) improved predictive performances due to the use of more enriched training datasets and more variety of protein descriptors, (4) newly integrated BLAST analysis option for assessing proteins in the SVM-Prot predicted functional families that were similar in sequence to a query protein, and (5) newly added batch submission option for supporting the classification of multiple proteins. Moreover, 2 more machine learning approaches, K nearest neighbor and probabilistic neural networks, were added for facilitating collective assessment of protein functions by multiple methods. SVM-Prot can be accessed at http://bidd2.nus.edu.sg/cgi-bin/svmprot/svmprot.cgi.

Autophagy is a critical mechanism in both cancer therapy resistance and tumor suppression. Monoclonal antibodies have been documented to kill tumor cells via apoptosis, antibody-dependent cellular cytotoxicity (ADCC) and complement-dependent cytotoxicity (CDC). In this study, we report for the first time that chLym-1, a chimeric anti-human HLA-DR monoclonal antibody, induces autophagy in Raji Non-Hodgkin's Lymphoma (NHL) cells. Interestingly, inhibition of autophagy by pharmacological inhibitors (3-methyladenine and NH4Cl) or genetic approaches (siRNA targeting Atg5) suppresses chLym-1-induced growth inhibition, apoptosis, ADCC and CDC in Raji cells, while induction of autophagy could accelerate cytotoxic effects of chLym-1 on Raji cells. Furthermore, chLym-1-induced autophagy can mediate apoptosis through Caspase 9 activation, demonstrating the tumor-suppressing role of autophagy in antilymphoma effects of chLym-1. Moreover, chLym-1 can activate several upstream signaling pathways of autophagy including Akt/mTOR and extracellular signal-regulated kinase 1/2 (Erk1/2). These results elucidate the critical role of autophagy in cytotoxicity of chLym-1 antibody and suggest a potential therapeutic strategy of NHL therapy by monoclonal antibody chLym-1 in combination with autophagy inducer.

Resistance to neoadjuvant chemotherapy leads to poor prognosis of locally advanced rectal cancer (LARC), representing an unmet clinical need that demands further exploration of therapeutic strategies to improve clinical outcomes. Here, we identified a noncanonical role of RB1 for modulating chromatin activity that contributes to oxaliplatin resistance in colorectal cancer (CRC). We demonstrate that oxaliplatin induces RB1 phosphorylation, which is associated with the resistance to neoadjuvant oxaliplatin-based chemotherapy in LARC. Inhibition of RB1 phosphorylation by CDK4/6 inhibitor results in vulnerability to oxaliplatin in both intrinsic and acquired chemoresistant CRC. Mechanistically, we show that RB1 modulates chromatin activity through the TEAD4/HDAC1 complex to epigenetically suppress the expression of DNA repair genes. Antagonizing RB1 phosphorylation through CDK4/6 inhibition enforces RB1/ TEAD4/HDAC1 repressor activity, leading to DNA repair defects, thus sensitizing oxaliplatin treatment in LARC. Our study identifies a RB1 function in regulating chromatin activity through TEAD4/HDAC1. It also provides the combination of CDK4/6 inhibitor with oxaliplatin as a potential synthetic lethality strategy to mitigate oxaliplatin resistance in LARC, whereby phosphorylated RB1/TEAD4 can serve as potential biomarkers to guide the patient stratification. [ABSTRACT FROM AUTHOR]