OTULIN allies with LUBAC to govern angiogenesis by editing ALK1 linear polyubiquitin.

OTULIN coordinates with LUBAC to edit linear polyubiquitin chains in embryonic development, autoimmunity, and inflammatory diseases. However, the mechanism by which angiogenesis, especially that of endothelial cells (ECs), is regulated by linear ubiquitination remains unclear. Here, we reveal that constitutive or EC-specific deletion of Otulin resulted in arteriovenous malformations and embryonic lethality. LUBAC conjugates linear ubiquitin chains onto Activin receptor-like kinase 1 (ALK1), which is responsible for angiogenesis defects, inhibiting ALK1 enzyme activity and Smad1/5 activation. Conversely, OTULIN deubiquitinates ALK1 to promote Smad1/5 activation. Consistently, embryonic survival of Otulin-deficient mice was prolonged by BMP9 pretreatment or EC-specific ALK1Q200D (constitutively active) knockin. Moreover, mutant ALK1 from type 2 hereditary hemorrhagic telangiectasia (HHT2) patients exhibited excessive linear ubiquitination and increased HOIP binding. As such, a HOIP inhibitor restricted the excessive angiogenesis of ECs derived from ALK1G309S-expressing HHT2 patients. These results show that OTULIN and LUBAC govern ALK1 activity to balance EC angiogenesis.

In situ activation of peroxymonosulfate with bioelectricity for sulfamethoxazole sustainable removal.

Conventional electrochemical activation of peroxymonosulfate (PMS) is not very cost-effective and practical by the excessive input of energy. The electricity generated by photosynthetic microalgae fuel cells (MFCs) is utilized to activate PMS, which would achieve the combination of green bioelectricity and advanced oxidation processes for sustainable pollutants degradation. In this study, a novel dual-chamber of MFCs was constructed by using microalgae as anode electron donor and PMS as cathode electron acceptor, which was operating under both close-circuit and open-circuit conditions. Under close-circuit condition, 1-12 mM PMS in cathode was successfully in situ activated, where 32.00%-99.83% of SMX was removed within 24 h, which was about 1.21-1.78 times of that in the open-circuit of MFCs. Meanwhile, a significant increase in bioelectricity generation in MFCs was observed after the accumulation of microalgae biomass (4.65-5.37 mg/L), which was attributed to the efficient electron separation and transfer. Furthermore, the electrochemical analysis demonstrated that SMX or its products were functioned as electronic shuttles, facilitating the electrochemical reaction and altering the electrical capacitance. The quenching experiments and voltage output results reflected that complex active radical (SO4⋅-, ⋅OH, and 1O2) were involved in SMX removal. Seven degradation products of SMX were detected and S-N bond cleavage was the main degradation pathway. Predicted toxicity values calculated by ECOSAR program showed that all the products were less toxic or nontoxic. Finally, the density functional theory (DFT) calculations revealed that the O and N atoms on SMX were more susceptible to electrophilic reactions, which were more vulnerable to be attacked by reactive species. This study provided new insights into the activation of PMS by bioelectricity for SMX degradation, proposing the mechanisms for PMS activation and degradation sites of SMX.

Intelligent, Flexible Artificial Throats with Sound Emitting, Detecting, and Recognizing Abilities.

In recent years, there has been a notable rise in the number of patients afflicted with laryngeal diseases, including cancer, trauma, and other ailments leading to voice loss. Currently, the market is witnessing a pressing demand for medical and healthcare products designed to assist individuals with voice defects, prompting the invention of the artificial throat (AT). This user-friendly device eliminates the need for complex procedures like phonation reconstruction surgery. Therefore, in this review, we will initially give a careful introduction to the intelligent AT, which can act not only as a sound sensor but also as a thin-film sound emitter. Then, the sensing principle to detect sound will be discussed carefully, including capacitive, piezoelectric, electromagnetic, and piezoresistive components employed in the realm of sound sensing. Following this, the development of thermoacoustic theory and different materials made of sound emitters will also be analyzed. After that, various algorithms utilized by the intelligent AT for speech pattern recognition will be reviewed, including some classical algorithms and neural network algorithms. Finally, the outlook, challenge, and conclusion of the intelligent AT will be stated. The intelligent AT presents clear advantages for patients with voice impairments, demonstrating significant social values.

Facile synthesis of ball-milling and oxalic acid co-modified sludge biochar to efficiently activate peroxymonosulfate for sulfamethoxazole degradation: 1O2 and surface-bound radicals.

A novel approach of ball milling and oxalic acid was employed to modify sludge-based biochar (BOSBC) to boost its activation performance for peroxymonosulfate (PMS) towards efficient degradation of sulfamethoxazole (SMX). 98.6% of SMX was eliminated by PMS/BOSBC system within 60 min. Furthermore, PMS/BOSBC system was capable of maintaining high removal rates for SMX (>88.8%) in a wide pH range from 3 to 9, and displayed a high tolerance to background electrolytes including inorganic ions and humic acid (HA). Quenching experiments, electron paramagnetic resonance (EPR) analysis, in-situ Raman characterization and PMS decomposition experiments confirmed that the non-radicals of 1O2 and surface-bound radicals were the main contributors to SMX degradation by PMS/BOSBC system. The results of ecotoxicity assessment illustrated that all transformed products (TPs) generated in PMS/BOSBC system were less toxic than that of SMX. After five reuse cycles, PMS/BOSBC system still maintained a high removal rate for SMX (77.8%). Additionally, PMS/BOSBC system exhibited excellent degradation performance for SMX in various real waters (Yangtze River water (76.5%), lake water (74.1%), tap water (86.5%), and drinking water (98.1%)). Overall, this study provided novel insights on non-metal modification for sludge-based biochar and non-radical mechanism, and offered a feasible approach for municipal sludge disposal.

Efficient degradation of sulfadiazine by UV-triggered electron transfer on oxalic acid-functionalized corn straw biochar for activating peroxyacetic acid: Performance, mechanism, and theoretical calculation.

A novel UV/oxalic acid functionalized corn straw biochar (OCBC)/peroxyacetic acid (PAA) system was built to degrade sulfadiazine from waters. 94.7 % of SDZ was removed within 30 min by UV/OCBC/PAA. The abundant surface functional groups and persistent free radicals (PFRs) on OCBC were responsible for these performances. Cyclic voltammetry (CV) and other characterization analysis revealed, under UV irradiation, the addition of OCBC served as electron donor, which might promote the reaction of electrons with PAA. The quenching and electron paramagnetic resonance (EPR) tests indicated that R-O•, 1O2 and •OH were generated. Theoretical calculations indicated sulfonamide bridge was vulnerable under the attacks of reactive species. In addition, high removal effect achieved by 5 reuse cycles and different real waters also suggested the sustainability of UV/OCBC/PAA. Overall, this study provided a feasible approach to remove SDZ with high mineralization efficiency, in addition to a potential strategy for resource utilization of corn straw.

Systematic HOIP interactome profiling reveals critical roles of linear ubiquitination in tissue homeostasis.

Linear ubiquitination catalyzed by HOIL-1-interacting protein (HOIP), the key component of the linear ubiquitination assembly complex, plays fundamental roles in tissue homeostasis by executing domain-specific regulatory functions. However, a proteome-wide analysis of the domain-specific interactome of HOIP across tissues is lacking. Here, we present a comprehensive mass spectrometry-based interactome profiling of four HOIP domains in nine mouse tissues. The interaction dataset provides a high-quality HOIP interactome resource with an average of approximately 90 interactors for each bait per tissue. HOIP tissue interactome presents a systematic understanding of linear ubiquitination functions in each tissue and also shows associations of tissue functions to genetic diseases. HOIP domain interactome characterizes a set of previously undefined linear ubiquitinated substrates and elucidates the cross-talk among HOIP domains in physiological and pathological processes. Moreover, we show that linear ubiquitination of Integrin-linked protein kinase (ILK) decreases focal adhesion formation and promotes the detachment of Shigella flexneri-infected cells. Meanwhile, Hoip deficiency decreases the linear ubiquitination of Smad ubiquitination regulatory factor 1 (SMURF1) and enhances its E3 activity, finally causing a reduced bone mass phenotype in mice. Overall, our work expands the knowledge of HOIP-interacting proteins and provides a platform for further discovery of linear ubiquitination functions in tissue homeostasis.

Machine learning-based CT radiomics enhances bladder cancer staging predictions: A comparative study of clinical, radiomics, and combined models.

BACKGROUND: Predicting the accurate preoperative staging of bladder cancer (BLCA), which markedly affects treatment decisions and patient outcomes, using traditional clinical parameters is challenging. Nevertheless, emerging studies in radiomics, especially machine learning-based computed tomography (CT) image-based radiomics, hold promise in improving stage prediction accuracy in various tumors. However, the comparative performance and clinical utility of models for BLCA are under investigation. PURPOSE: We aimed to investigate the application value of machine learning-based CT radiomics in preoperative staging prediction by comparing the performance of clinical, radiomics, and clinical-radiomics combined models. METHODS: A retrospective cohort of 105 patients with initial BLCA was randomized into training (70%) and testing (30%) cohorts. Radiomics features were extracted from CT images using the optimal feature filter, followed by the application of the least absolute shrinkage and selection operator algorithm for optimum feature selection. Furthermore, machine learning algorithms were used to establish a radiomics model within the training cohort. Independent risk factors for muscle-invasive BLCA (MIBC) obtained by multivariate logistic regression (LR) analysis were separately used to construct a clinical model. For a clinical-radiomics fusion model, radiomics features were combined with clinical parameters. Performance was evaluated based on receiver operating characteristic curves, calibration curves, decision curve analysis (DCA), and standard performance metrics. RESULTS: Patients exhibited a significantly higher age (p = 0.029), larger tumor size (p = 0.01), and an increased neutrophil-to-lymphocyte ratio (NLR; p = 0.045) in the MIBC group than in the NMIBC group. LR analysis revealed age (p = 0.026), tumor size (p = 0.007), and NLR (p = 0.019) as significant predictors for constructing the clinical model. In the testing cohort, the radiomics model, which used an Support Vector Machine classifier, achieved the highest area under the curve (AUC) value of 0.857. The clinical-radiomics model outperformed the remaining two models, with AUC values of 0.958 and 0.893 in the training and testing cohorts, respectively. DeLong's test indicated significant differences between the three models. Calibration curves showed good agreement, and DCA confirmed the superior clinical utility of the clinical-radiomics model. CONCLUSIONS: Machine learning-based CT radiomics combined with clinical parameters was a promising approach in staging BLCA accurately, which outperformed the individual models. Integrating radiomics features with clinical information holds the potential to improve personalized treatment planning and patient outcomes in BLCA.

One-pot preparation of layered double oxides-engineered biochar for the sustained removal of tetracycline in water.

Tetracycline (TC) and sugarcane bagasse had both exerted enormous strain on environmental security. In this work, new composite adsorbent designed by impregnating bio-waste bagasse with magnesium-aluminum layered double oxides (BC-MA) was innovatively brought forward for TC removal. Benefiting from the abundant adsorption sites supplied by developed pores structure (0.308 cm3·g-1), enlarged surface area (256.8 m2·g-1) and reinforced functional groups, the maximum adsorption amount of BC-MA for TC reached 250.6 mg g-1. Moreover, BC-MA displayed desirable adsorption capacity in diverse water environments coupled with excellent sustainable regeneration ability. The absorption process of TC by BC-MA was spontaneous and endothermic, and the pivotal rate-limiting stage pertained to intraparticle diffusion. The mechanisms proposed here mainly concerned π-π interactions, pore filling, complexation and hydrogen bonding. These findings suggested that the synthesis of modified biochar from bagasse would offer new opportunities for simultaneous waste resource reuse and water pollution control.

Value of the application of computed tomography-based radiomics for preoperative prediction of unfavorable pathology in initial bladder cancer.

OBJECTIVES: To construct and validate unfavorable pathology (UFP) prediction models for patients with the first diagnosis of bladder cancer (initial BLCA) and to compare the comprehensive predictive performance of these models. MATERIALS AND METHODS: A total of 105 patients with initial BLCA were included and randomly enrolled into the training and testing cohorts in a 7:3 ratio. The clinical model was constructed using independent UFP-risk factors determined by multivariate logistic regression (LR) analysis in the training cohort. Radiomics features were extracted from manually segmented regions of interest in computed tomography (CT) images. The optimal CT-based radiomics features to predict UFP were determined by the optimal feature filter and the least absolute shrinkage and selection operator algorithm. The radiomics model consist with the optimal features was constructed by the best of the six machine learning filters. The clinic-radiomics model combined the clinical and radiomics models via LR. The area under the curve (AUC), accuracy, sensitivity, specificity, positive and negative predictive value, calibration curve and decision curve analysis were used to evaluate the predictive performance of the models. RESULTS: Patients in the UFP group had a significantly older age (69.61 vs. 63.93 years, p = 0.034), lager tumor size (45.7% vs. 11.1%, p = 0.002) and higher neutrophil to lymphocyte ratio (NLR; 2.76 vs. 2.33, p = 0.017) than favorable pathologic group in the training cohort. Tumor size (OR, 6.02; 95% CI, 1.50-24.10; p = 0.011) and NLR (OR, 1.50; 95% CI, 1.05-2.16; p = 0.026) were identified as independent predictive factors for UFP, and the clinical model was constructed using these factors. The LR classifier with the best AUC (0.817, the testing cohorts) was used to construct the radiomics model based on the optimal radiomics features. Finally, the clinic-radiomics model was developed by combining the clinical and radiomics models using LR. After comparison, the clinic-radiomics model had the best performance in comprehensive predictive efficacy (accuracy = 0.750, AUC = 0.817, the testing cohorts) and clinical net benefit among UFP-prediction models, while the clinical model (accuracy = 0.625, AUC = 0.742, the testing cohorts) was the worst. CONCLUSION: Our study demonstrates that the clinic-radiomics model exhibits the best predictive efficacy and clinical net benefit for predicting UFP in initial BLCA compared with the clinical and radiomics model. The integration of radiomics features significantly improves the comprehensive performance of the clinical model.

Machine learning models combining computed tomography semantic features and selected clinical variables for accurate prediction of the pathological grade of bladder cancer.

Objective: The purpose of this research was to develop a radiomics model that combines several clinical features for preoperative prediction of the pathological grade of bladder cancer (BCa) using non-enhanced computed tomography (NE-CT) scanning images. Materials and methods: The computed tomography (CT), clinical, and pathological data of 105 BCa patients attending our hospital between January 2017 and August 2022 were retrospectively evaluated. The study cohort comprised 44 low-grade BCa and 61 high-grade BCa patients. The subjects were randomly divided into training (n = 73) and validation (n = 32) cohorts at a ratio of 7:3. Radiomic features were extracted from NE-CT images. A total of 15 representative features were screened using the least absolute shrinkage and selection operator (LASSO) algorithm. Based on these characteristics, six models for predicting BCa pathological grade, including support vector machine (SVM), k-nearest neighbor (KNN), gradient boosting decision tree (GBDT), logical regression (LR), random forest (RF), and extreme gradient boosting (XGBOOST) were constructed. The model combining radiomics score and clinical factors was further constructed. The predictive performance of the models was evaluated based on the area under the receiver operating characteristic (ROC) curve, DeLong test, and decision curve analysis (DCA). Results: The selected clinical factors for the model included age and tumor size. LASSO regression analysis identified 15 features most linked to BCa grade, which were included in the machine learning model. The SVM analysis revealed that the highest AUC of the model was 0.842. A nomogram combining the radiomics signature and selected clinical variables showed accurate prediction of the pathological grade of BCa preoperatively. The AUC of the training cohort was 0.919, whereas that of the validation cohort was 0.854. The clinical value of the combined radiomics nomogram was validated using calibration curve and DCA. Conclusion: Machine learning models combining CT semantic features and the selected clinical variables can accurately predict the pathological grade of BCa, offering a non-invasive and accurate approach for predicting the pathological grade of BCa preoperatively.

Performance of a biocrust cyanobacteria-indigenous bacteria (BCIB) co-culture system for nutrient capture and transfer in municipal wastewater.

This study aimed to explore the potential for transferring nutrients from municipal wastewater through the cultivation of biocrust cyanobacteria, since little is known regarding the growth and bioremediation performance of biocrust cyanobacteria in actual wastewater, especially their interaction with indigenous bacteria. Therefore, in this study, the biocrust cyanobacterium, Scytonema hyalinum was cultivated in municipal wastewater under different light intensities, to establish a biocrust cyanobacteria-indigenous bacteria (BCIB) co-culture system, in order to investigate its nutrient removal efficiency. Our results revealed that the cyanobacteria-bacteria consortium could remove up to 91.37 % and 98.86 % of dissolved nitrogen and phosphorus from the wastewater, respectively. The highest biomass accumulation (max. 6.31 mg chlorophyll-a L-1) and exopolysaccharide secretion (max. 21.90 mg L-1) were achieved under respective optimized light intensity (60 and 80 µmol m-2 s-1). High light intensity was found to increase exopolysaccharide secretion, but negatively impacted cyanobacterial growth and nutrient removal. Overall, in the established cultivation system, cyanobacteria accounted for 26-47 % of the total bacterial abundance, while proteobacteria consisted up to 50 % of the mixture. The composition and ratio of cyanobacteria to indigenous bacteria were shown to be altered by adjusting the light intensity of the system. Altogether, our results clearly illustrate the potential of the biocrust cyanobacterium S. hyalinum in establishing a BCIB cultivation system under different light intensity for wastewater treatment and other end-applications (e.g., biomass accumulation and exopolysaccharide secretion). This study presents an innovative strategy for transferring nutrients from wastewater to drylands through cyanobacterial cultivation and subsequent biocrust induction.

OTUB1 promotes osteoblastic bone formation through stabilizing FGFR2.

Bone homeostasis is maintained by the balance between osteoblastic bone formation and osteoclastic bone resorption. Dysregulation of this process leads to multiple diseases, including osteoporosis. However, the underlying molecular mechanisms are not fully understood. Here, we show that the global and conditional osteoblast knockout of a deubiquitinase Otub1 result in low bone mass and poor bone strength due to defects in osteogenic differentiation and mineralization. Mechanistically, the stability of FGFR2, a crucial regulator of osteogenesis, is maintained by OTUB1. OTUB1 attenuates the E3 ligase SMURF1-mediated FGFR2 ubiquitination by inhibiting SMURF1's E2 binding. In the absence of OTUB1, FGFR2 is ubiquitinated excessively by SMURF1, followed by lysosomal degradation. Consistently, adeno-associated virus serotype 9 (AAV9)-delivered FGFR2 in knee joints rescued the bone mass loss in osteoblast-specific Otub1-deleted mice. Moreover, Otub1 mRNA level was significantly downregulated in bones from osteoporotic mice, and restoring OTUB1 levels through an AAV9-delivered system in ovariectomy-induced osteoporotic mice attenuated osteopenia. Taken together, our results suggest that OTUB1 positively regulates osteogenic differentiation and mineralization in bone homeostasis by controlling FGFR2 stability, which provides an optical therapeutic strategy to alleviate osteoporosis.

Influence of China's Carbon Emissions Trading Scheme on Green Innovation of Enterprises.

China's economic growth has entered "new normal," and the task of reducing carbon emissions has become more onerous. Hence, this study aimed to explore whether China's carbon emissions trading pilot policy stimulated corporate green innovation capabilities. The data pertained to the green patent data of the listed companies in Shanghai and Shenzhen stock exchanges during 2008-2018. Using a difference-in-difference-in-differences (DDD) method, the study took advantage of the variations across regions, across enterprises, and across years and obtained several novel findings. First, the pilot carbon emissions trading policy significantly stimulated the green innovation capabilities of emission control companies in the pilot areas compared with enterprises in nonpilot areas and the nonemission control list. Second, the effect of the policy on the improvement in corporate green innovation capabilities might be driven by the improvement in corporate input factor allocation efficiency and the additional benefits that could be obtained from the carbon trading market. Third, the positive effect of the policy on the green innovation capabilities of state-owned enterprises was more significant. Therefore, the establishment and promotion of a unified national carbon emissions trading market and supporting mechanisms should be accelerated to achieve the balance of stable economic growth and carbon emission task.

Efficient removal of Imidacloprid and nutrients by algae-bacteria biofilm reactor (ABBR) in municipal wastewater: Performance, mechanisms and the importance of illumination.

Neonicotinoids, such as Imidacloprid (IMI), are frequently detected in water and wastewater, posing a threat on both the environment and the health of living things. In this work, a novel algae-bacteria biofilm reactor (ABBR) was constructed to remove IMI and conventional nutrients from municipal wastewater, aiming to explore the removal effect and advantage of ABBR. Results showed that ABBR achieved 74.9% removal of IMI under 80 µmol m-2·s-1 light, higher than photobioreactor (PBR) without biofilm (61.2%) or ABBR under 40 µmol m-2·s-1 light (48.4%) after 16 days of operation. Moreover, it also showed that ABBR allowed a marked improvement on the removal of total dissolved nitrogen (TDN), total dissolved phosphorus (TDP) and soluble chemical oxygen demand (sCOD). ABBR showed different IMI removal efficiencies and bacterial communities under different light conditions, indicating that light played an important role in driving ABBR. The merits of ABBR are including (i) ABBR showed rapid pollutant removal in a short time, (ii) in ABBR, stable consortiums were formed and chlorophyll content in effluent was very low, (iii) compared with PBR, degradation products in ABBR showed lower biological toxicity. Our study highlights the benefits of ABBR on IMI removing from municipal wastewater and provides an effective and environment-friendly engineering application potential of IMI removal.

Ubiquitin ligase CHIP regulates OTUD3 stability and suppresses tumour metastasis in lung cancer.

Ovarian tumour domain-containing protein 3 (OTUD3), a key OTU (ovarian tumour protease) family deubiquitylase, plays context-dependent roles in cancers. It suppresses tumorigenesis in breast, colon, liver and cervical cancer through stabilizing PTEN (phosphatase and tension homologue deleted on chromosome 10) while promotes lung tumorigenesis through stabilizing GRP78 (The glucose-regulated protein 78 kDa). The regulation especially post-translational modification of OTUD3 remains unclear. Here, we report that the carboxyl terminus of Hsc70-interacting protein (CHIP) is a ubiquitin ligase for OTUD3. CHIP interacts with, polyubiquitylates OTUD3 and promotes OTUD3 degradation. Knockdown of CHIP stabilizes OTUD3 which leads to elevated GRP78 levels in lung cancer cells. CHIP-knockdown lung cancer cells exhibit increased invasion in OTUD3 and GRP78 dependent manner. Further study demonstrates that CHIP-knockdown lung cancer cells are more prone to metastasize to mice lung when injected intravenously or subcutaneously. Moreover, the expression of CHIP is low in human lung cancer tissues and inversely correlates with OTUD3 expression and GRP78 expression. Furthermore, we identified CHIP mutations in human lung cancers, which reduce CHIP catalytic activity. These findings demonstrate that CHIP is a negative regulator of OTUD3 and CHIP suppresses lung cancer metastasis through inhibiting OTUD3-GRP78 signaling axis.

Temperature modulating sand-consolidating cyanobacterial biomass, nutrients removal and bacterial community dynamics in municipal wastewater.

Cultivating sand-consolidating cyanobacteria using wastewater has unique advantages on both nutrients recycling and ecological restoration by transferring excessive nutrients from wastewaters to desert areas. Although previous study showed that sand-consolidating cyanobacterium well adapted to synthetic domestic wastewater, no study has been carried out on actual wastewater. This study aims to investigate the sand-consolidating cyanobacterial biomass production and nutrients removal by cultivating Scytonema hyalinum in the municipal wastewater under different temperatures. The results showed that biomass accumulation increased with temperature from 20 â„ƒ to 30 â„ƒ, while severely depressed at 35 â„ƒ. More than 81.63% sCOD, 90.64% TDN and 97.08% TDP were removed by day 30 under each temperature except for 35℃. The inoculation of S. hyalinum strongly regulated the native wastewater bacterial community. These results indicated that sand-consolidating cyanobacterium S. hyalinum well adapted to municipal wastewater and temperature had remarkable effects on cyanobacterial biomass accumulation, nutrients removal and wastewater native bacterial community dynamics.

Deubiquitylase OTUD6B Governs pVHL Stability in an Enzyme-Independent Manner and Suppresses Hepatocellular Carcinoma Metastasis.

Hypoxia inducible factors (HIFs) are the key transcription factors that allow cancer cells to survive hypoxia. HIF's stability is mainly controlled by von Hippel-Lindau (pVHL)-mediated ubiquitylation. Unlike sporadic clear-cell renal carcinomas, VHL mutation is rarely observed in hepatocellular carcinoma (HCC) and the regulatory mechanisms of pVHL-HIF signaling remain elusive. Here, it is shown that deubiquitylase ovarian tumor domain-containing 6B (OTUD6B) suppresses HCC metastasis through inhibiting the HIF activity. OTUD6B directly interacts with pVHL, decreases its ubiquitylation and proteasomal degradation to reduce HIF-1α accumulation in HCC cells under hypoxia. Surprisingly, OTUD6B limits the ubiquitylation of pVHL independent of its deubiquitylase activity. OTUD6B couples pVHL and elongin B/C to form more CBCVHL ligase complex, which protects pVHL from proteasomal degradation. Depletion of OTUD6B results in the dissociation of CBCVHL complex and the degradation of pVHL by Trp Asp repeat and suppressors of cytokine signaling box-containing protein 1 (WSB1). In human HCC tissues, the protein level of OTUD6B is positively correlated with pVHL, but negatively with HIF-1α and vascular endothelial growth factor. Low expression of OTUD6B predicts poor patient survival. Furthermore, OTUD6B gene is a direct transcriptional target of HIF-1α and upregulated upon hypoxia. These results indicate a previously unrecognized feedback loop consisting of OTUD6B, pVHL, and HIF-1α, and provide insights into the targeted hypoxic microenvironment for HCC therapy.