Physical reservoir computing on a soft bio-inspired swimmer.

Bio-inspired Autonomous Underwater Vehicles with soft bodies provide significant performance benefits over conventional propeller-driven vehicles; however, it is difficult to control these vehicles due to their soft underactuated bodies. This study investigates the application of Physical Reservoir Computing (PRC) in the swimmer's flexible body to perform state estimation. This PRC informed state estimation has potential to be used in vehicle control. PRC is a type of recurrent neural network that leverages the nonlinear dynamics of a physical system to predict a nonlinear spatiotemporal input-output relationship. By embodying the neural network into the physical structure, PRC can process the response to an environment input with high computational efficiency. This study uses a soft bio-inspired propulsor embodied as a physical reservoir. We evaluate its ability to predict different state estimation tasks including hydrodynamic forces and benchmark computational tasks in response to the forcing applied to the artificial muscles during actuation. The propulsor's nonlinear fluid-structural dynamics act as the physical reservoir and the kinematic feedback serves as the reservoir readouts. We show that the bio-inspired underwater propulsor can predict the hydrodynamic thrust and benchmark tasks with high accuracy under specific input frequencies. By analyzing the frequency spectrum of the input, readouts, and target signals, we demonstrate that the system's dynamic response determines the frequency contents relevant to the task being predicted. The propulsor's ability to process information stems from its nonlinearity, as it is responsible to transform the input signal into a broader spectrum of frequency content at the readouts. This broad band of frequency content is necessary to recreate the target signal within the PRC algorithm, thereby improving the prediction performance. The spectral analysis provides a unique perspective to analyze the nonlinear dynamics of a physical reservoir and serves as a valuable tool for examining other types of vibratory systems for PRC. This work serves as a first step towards embodying computation into soft bio-inspired swimmers.

The influence of storage conditions on hygiene condition and eicosapentaenoic acid oxidation in Nannochloropsis algae for sustainable food supply.

BACKGROUND: Nannochloropsis algae contain approximately 20% polyunsaturated fatty acids (PUFA) and hold significant potential for high-quality eicosapentaenoic acid (EPA) food industrialization. However, EPA in Nannochloropsis sp. is prone to oxidation, and microbial growth is a critical factor affecting the shelf life of fresh food. Storage composition and temperature are primary factors influencing microbial growth, yet these aspects are not fully understood. This study investigates the effects of temperature and encapsulation on EPA content in nano-products over time. Nano-powder and nanobeads derived from Nannochloropsis sp. served as raw materials. Additionally, changes in aerobic plate counts and coliform groups were monitored. RESULTS: The results indicated that nanobeads, due to their more complex processing and less mature packaging, were more susceptible to coliform contamination compared to nano-powder. In terms of EPA stability, nanobeads exhibited a longer storage life than nano-powder. The oxidation rate of both nano-powder and nanobeads was faster at 37 °C than at 25 °C. CONCLUSION: These findings can inform general shelf life estimation, rapid detection of total lipid content in nano-products and macro extraction of nano-oil. Moreover, they have significant implications for delaying EPA oxidation in nano-products and improving hygienic quality control for microbial detection. © 2024 Society of Chemical Industry.

A circularly permuted CasRx platform for efficient, site-specific RNA editing.

Inactive Cas13 orthologs have been fused to a mutant human ADAR2 deaminase domain at the C terminus to enable programmable adenosine-to-inosine (A-to-I) RNA editing in selected transcripts. Although promising, existing RNA-editing tools generally suffer from a trade-off between efficacy and specificity, and off-target editing remains an unsolved problem. Here we describe the development of an optimized RNA-editing platform by rational protein engineering, CasRx-based Programmable Editing of RNA Technology (xPERT). We demonstrate that the topological rearrangement of a CasRx K940L mutant by circular permutation results in a robust scaffold for the tethering of a deaminase domain. We benchmark our tool against the REPAIR system and show that xPERT exhibits strong on-target activity like REPAIRv1 but low off-target editing like REPAIRv2. Our xPERT platform can be used to alter RNA sequence information without risking genome damage, effect temporary cellular changes and customize protein function.

Targeting osteoblastic 11ß-HSD1 to combat high-fat diet-induced bone loss and obesity.

Excessive glucocorticoid (GC) action is linked to various metabolic disorders. Recent findings suggest that disrupting skeletal GC signaling prevents bone loss and alleviates metabolic disorders in high-fat diet (HFD)-fed obese mice, underpinning the neglected contribution of skeletal GC action to obesity and related bone loss. Here, we show that the elevated expression of 11ß-hydroxysteroid dehydrogenase type 1 (11ß-HSD1), the enzyme driving local GC activation, and GC signaling in osteoblasts, are associated with bone loss and obesity in HFD-fed male mice. Osteoblast-specific 11ß-HSD1 knockout male mice exhibit resistance to HFD-induced bone loss and metabolic disorders. Mechanistically, elevated 11ß-HSD1 restrains glucose uptake and osteogenic activity in osteoblast. Pharmacologically inhibiting osteoblastic 11ß-HSD1 by using bone-targeted 11ß-HSD1 inhibitor markedly promotes bone formation, ameliorates glucose handling and mitigated obesity in HFD-fed male mice. Taken together, our study demonstrates that osteoblastic 11ß-HSD1 directly contributes to HFD-induced bone loss, glucose handling impairment and obesity.

Multi-omics integration analysis reveals the role of N6-methyladenosine in lncRNA translation during glioma stem cell differentiation.

Glioblastoma is one of the most lethal brain diseases in humans. Although recent studies have shown reciprocal interactions between N6-methyladenosine (m6A) modifications and long noncoding RNAs (lncRNAs) in gliomagenesis and malignant progression, the mechanism of m6A-mediated lncRNA translational regulation in glioblastoma remains unclear. Herein, we profiled the transcriptomes, translatomes, and epitranscriptomics of glioma stem cells and differentiated glioma cells to investigate the role of m6A in lncRNA translation comprehensively. We found that lncRNAs with numerous m6A peaks exhibit reduced translation efficiency. Transcript-level expression analysis demonstrates an enrichment of m6A around short open reading frames (sORFs) of translatable lncRNA transcripts. Further comparison analysis of m6A modifications in different RNA regions indicates that m6A peaks downstream of sORFs inhibit lncRNA translation more than those upstream. Observations in glioma-associated lncRNAs H19, LINC00467, and GAS5 further confirm the negative effect of m6A methylation on lncRNA translation. Overall, these findings elucidate the dynamic profiles of the m6A methylome and enhance the understanding of the complexity of lncRNA translational regulation.

Association of hospital safety climate and compliance with occupational safety practices among nurse interns: A cross-sectional study using canonical correlation analysis.

Background and Aims: Nurse interns may be at a similar or higher risk than registered nurses. The key elements and mechanisms involved in the effects of safety climate on safety performance are not well understood. This study explores the relationship between the perceived hospital safety climate and compliance with occupational safety practices among nurse interns. Methods: A cross-sectional study was conducted among 178 nurse interns in three tertiary university hospitals in Chongqing city, China. The Chinese version of the Hospital Safety Climate Scale (HSCS) was used to measure the perceived hospital safety climate of nurse interns. Compliance behavior was measured using the Compliance with Occupational Safety Practice Scale (COSPS). Canonical correlation analysis and multiple linear regression modeling were used to examine their relationship. Results: Total scores for the HSCS and COSPS were 92 (80,100) and 185 (175,185) [M (P25, P75)], respectively. Canonical correlation coefficients for canonical variates 1 and 2 were 0.636 (p < 0.001) and 0.414 (p < 0.001), respectively. Nurse interns' compliance with occupational safety practices was mainly influenced by management support, feedback/training, personal protective and engineering control equipment availability, and absence of job hindrance. Multiple linear regression showed that management support of HSCS accounted for 37.1% of the variance in compliance (ß = 0.283, p = 0.039). Conclusion: Nurse interns reported high levels of perceived hospital safety climate and compliance with occupational safety practices. Younger nurse interns reported a lower level of perceived hospital safety climate. Nurse educators can improve interns' compliance by promoting better management support, feedback/training, personal protective and engineering control equipment availability, and fewer job hindrance.

Remote ischemic conditioning slows blood-retinal barrier damage in type 1 diabetic rats.

Diabetic retinopathy (DR) is one of the major complications of diabetes and can cause severe visual impairment. Blood-retina barrier (BRB) destruction resulted from chronic hyperglycemia underlines its major pathological process. However, current treatments have limited efficacy and may even cause serious complications. Remote ischemic conditioning (RIC), through repeated transient mechanical occlusion of limb blood vessels, has been confirmed to promote blood-brain barrier integrity after stroke, but its role in BRB disruption has not been elucidated. This study aimed to investigate the protective effects of RIC on the BRB in diabetic rats and its potential mechanisms. 48 Sprague-Dawley rats were randomly assigned to the Sham group, Sham + RIC group, diabetes mellitus (DM) group and DM+RIC group. The diabetic model was successfully induced by intraperitoneal injection of streptozotocin (STZ). RIC treatment was administered daily and lasted for 9 weeks. In functional analysis, RIC improved the retinal function based on electroretinogram data and reduced the leakage of BRB in diabetic rats. In proteomic analysis, tight junction pathway was enriched after RIC treatment, in which Patj gene was significantly increased. We also found that RIC increased mRNA levels of Patj, claudin-1 and zonula occludens (ZO)-1, protein expression of claudin-1 when compared with diabetic models. In conclusion, RIC slowed BRB damage in diabetic rats which may be related to the preservation of tight junction proteins. RIC may be a promising protective strategy for the treatment of DR.

New Meroterpenes from South China Sea Soft Coral Litophyton brassicum.

A chemical investigation of the extracts from the soft coral Litophyton brassicum led to the isolation and identification of four new meroterpenes, brassihydroxybenzoquinone A and B (1 and 2) and brassinaphthoquinone A and B (3 and 4), along with two known related meroterpenes (5 and 6). Their structures were elucidated using high-resolution electrospray ionization mass spectrometry (HRESIMS), nuclear magnetic resonance (NMR) spectroscopy, and a comparison with the literature data. All compounds were evaluated for antibacterial activity against six pathogenic bacterial strains and for cytotoxic activity against three cancer cell lines. In the cytotoxic assay, all compounds were inactive at 10 µM against the A549, HeLa, and MDA-MB-231 cell lines. In the antibacterial assay, compounds 1 and 2 exhibited moderate inhibitory activity with minimum inhibitory concentrations (MIC) ranging from 8 to 64 µg/mL.

Analysis on typical characteristics and causes of coal mine gas explosion accidents in China.

Large-scale coal mine gas explosion (CMGE) accidents have occurred occasionally and exerted a devastating effect on society. Therefore, it is essential to systematically identify the characteristics and association rules of causes of CMGE accidents through analysis on large-scale CMGE accident reports. In this study, 298 large-scale CMGE accidents in China from 2000 to 2021 were taken as the data sample, and mathematical statistical methods were adopted to analyze their general characteristics, coupling cross characteristics, and characteristics of gas accumulation and ignition sources. Moreover, the text mining technology and the Apriori algorithm were used for exploring the formation mechanism of CMGE accidents, during which 46 main causal factors were identified and 59 strong association rules were obtained. Furthermore, an accident causation network was constructed based on the co-occurrence matrix. The key causal items and sets of CMGE accidents were clarified through network centrality analysis. According to the research results, electrical equipment failure, cable short circuit, mine lamp misfire, hot-line work, and blasting spark are the key ignition sources of CMGE. Fan failure, airflow short circuit, and local ventilation fan damage are the main causes of gas accumulation. Besides, the confidence levels of two association rules of "static spark-fan failure" and "blasting spark-airflow short circuit" are higher than 70%, indicating that they are the two dominant risk-coupling paths of gas explosions. In addition, six causes appear frequently in the shortest risk paths of gas explosion and are closely related to other causes, i.e., fan failure, local ventilation fan damage, static sparks, electrical equipment failure, self-heating ignition, and friction impact sparks. This study provides a new perspective on identifying causes of accidents and their complex association mechanisms from accident report data for practical guidance in risk assessment and accident prevention.

Genome Mining Analysis Uncovers the Previously Unknown Biosynthetic Capacity for Secondary Metabolites in Verrucomicrobia.

Bacteria of the phylum Verrucomicrobia is widely distributed in diverse ecological environments. Their limited cultivability has greatly caused the significant knowledge gap surrounding their secondary metabolites and their mediating ecological functions. This study delved into the diversity and novelty of secondary metabolite biosynthetic gene clusters (BGCs) of Verrucomicrobia by employing a gene-first approach to investigate 2323 genomes. A total of 7552 BGCs, which encompassed 3744 terpene, 805 polyketide, 773 non-ribosomal peptide gene clusters, and 1933 BGCs of other biosynthetic origins, were identified. They were further classified into 3887 gene cluster families (GCFs) based on biosynthetic gene similarity clustering, of which only six GCFs contained reference biosynthetic gene clusters in the Minimum Information about a Biosynthetic Gene Cluster (MIBiG), indicating the striking novelty of secondary metabolites in Verrucomicrobia. Notably, 37.8% of these gene clusters were harbored by unclassified species of Verrucomicrobia phyla, members of which were highly abundant in soil environments. Furthermore, our comprehensive analysis also revealed Luteolibacter and Methylacidiphilum as the most prolific genera in terms of BGC abundance and diversity, with the discovery of a conservative and new NRPS-PKS BGC in Luteolibacter. This work not only unveiled the biosynthetic potential and genetic diversity of secondary metabolites of Verrucomicrobia but also provided a fresh insight for the exploration of new bioactive compounds.

Kinetic-thermodynamic correlation of conformational changes in ammonium complexes of a flexible naphthocage.

Conformational changes in non-covalent complexes are of fundamental importance to many chemical and biological processes. Yet, these low-energy structural changes are usually fast and difficult to monitor, which poses challenges in their detailed kinetic understanding. The correlation between kinetics and thermodynamics of the conformational change of a model supramolecular system featuring a flexible naphthocage and quaternary ammonium guests is described in this work. Guest binding initially locks the host in two major conformations, which then equilibrates over time to the more stable conformer. The overall rate of the system to attain conformational equilibrium is found to inversely correlate with the thermodynamic stability of the host-guest complexes, and hence not only can the kinetic parameters of the conformational exchange be predicted from the easily obtainable thermodynamic data, but the kinetic profile can also be rationalized by using the structural properties of the different guests.

Cluster intercalation of aluminum tetrachloride in AlN cathode: Exploration and analysis of aluminum ion batteries.

When chloroaluminate (AlCl4-) serves as the electrolyte, aluminum nitride (AlN) has shown promise as a cathode material in aluminum ion batteries. However, there is currently a lack of research on the mechanisms of charge transfer and cluster intercalation between AlCl4 and AlN cathode materials. Herein, first-principles calculations are employed to investigate the intercalation mechanism of AlCl4 within the AlN cathode. By calculating the formation energies of stage-1-5 AlN-AlCl4 intercalation compounds with the insertion of individual AlCl4 cluster, we found that the structure of the stage-4 intercalation compounds exhibits the highest stability, suggesting that when the clusters begin to intercalate, it is important to start with the formation of the stage-4 intercalation compounds. In the subsequent phases of the charging process (stages 1 and 2), the stabilized structure with four inserted clusters demonstrates two characteristics: the coexistence of standing and lying clusters and the insertion of two standing clusters in an upside-down doubly stacked configuration, which further improve the spatial utilization while maintaining the structural stability. In addition, we infer that a phenomenon of coexisting intercalation compounds with mixed stages will occur in the course of the charging and discharging processes. More importantly, the diffusion barrier of AlCl4 in AlN-AlCl4 intercalation compounds decreases with the reduction of stage number, ensuring the rate performance of batteries. Therefore, we expect that our work will contribute to comprehend the intercalation mechanism of AlCl4 into the AlN cathode materials of aluminum ion batteries, providing guidance for related experimental work.

Empowering agriculture: The promise of zinc biofortification in rice.

Zinc (Zn) plays a crucial role in metabolism in both plant and animal life. Zn deficiency is a worldwide problem that has recently gotten worse. This micronutrient shortage can be largely attributed to eating foods that are poor in zinc. If biofortification methods were widely used, Zn enrichment of the organ or tissue of interest would increase dramatically. However, Zn absorption mechanisms in rice plants must be understood on a fundamental level before these methods can be used effectively. Plant systems' Zn transporters and metal chelators play a major role in regulating this intricate physiological characteristic. The Zn efficiency of specific species is affected by a variety of factors, including the plant's growth stage, edaphic conditions, the time of year, and more. Both old and new ways of breeding plants can be used for biofortification. We have highlighted the significance of recombinant and genetic approaches to biofortifying in rice. In this review, we have the metabolic role of zinc in rice, and the different transporter families involved in the transportation of zinc in rice. We have also discussed the combined approaches of agronomic and genetic in zinc biofortification in rice and potential outcomes and future predictions.

DeepIRES: a hybrid deep learning model for accurate identification of internal ribosome entry sites in cellular and viral mRNAs.

The internal ribosome entry site (IRES) is a cis-regulatory element that can initiate translation in a cap-independent manner. It is often related to cellular processes and many diseases. Thus, identifying the IRES is important for understanding its mechanism and finding potential therapeutic strategies for relevant diseases since identifying IRES elements by experimental method is time-consuming and laborious. Many bioinformatics tools have been developed to predict IRES, but all these tools are based on structure similarity or machine learning algorithms. Here, we introduced a deep learning model named DeepIRES for precisely identifying IRES elements in messenger RNA (mRNA) sequences. DeepIRES is a hybrid model incorporating dilated 1D convolutional neural network blocks, bidirectional gated recurrent units, and self-attention module. Tenfold cross-validation results suggest that DeepIRES can capture deeper relationships between sequence features and prediction results than other baseline models. Further comparison on independent test sets illustrates that DeepIRES has superior and robust prediction capability than other existing methods. Moreover, DeepIRES achieves high accuracy in predicting experimental validated IRESs that are collected in recent studies. With the application of a deep learning interpretable analysis, we discover some potential consensus motifs that are related to IRES activities. In summary, DeepIRES is a reliable tool for IRES prediction and gives insights into the mechanism of IRES elements.

Accelerated Solar-Driven Polyolefin Degradation via Self-Activated Hydroxy-Rich ZnIn2S4.

Degradation of polyolefin (PE) plastic by a traditional chemical method requires a high pressure and a high temperature but generates complex products. Here, sulfur vacancy-rich ZnIn2S4 and hydroxy-rich ZnIn2S4 were rationally fabricated to realize photocatalytic degradation of PE in an aqueous solution under mild conditions. The results reveal that the optimized photocatalyst could degrade PE into CO2 and CO, and PE had a weight loss of 84.5% after reaction for 60 h. Systematic experiments confirm that the synergetic effect of hydroxyl groups and S vacancies contributes to improve the photocatalytic degradation properties of plastic wastes. In-depth investigation illustrates that the active radicals attack (h+ and •OH) weak spots (C-H and C-C bonds) of the PE chain to form CO2, which is further selectively photoreduced to CO. Multimodule synergistic tandem catalysis can further improve the utilization value of plastic wastes; for example, product CO2/CO in the plastic degradation process can be converted in situ into HCOOH by coupling with electrocatalytic technology.

Phylogenomic analysis uncovers an unexpected capacity for the biosynthesis of secondary metabolites in Pseudoalteromonas.

Pseudoalteromonas is a genus of marine bacteria and a promising source of natural products with antibacterial, antifungal, and antifouling bioactivities. To accelerate the exploration of new compounds from this genus, we applied the gene-first approach to study 632 public Pseudoalteromonas genomes. We identified 3968 biosynthetic gene clusters (BGCs) involved in the biosynthesis of secondary metabolites and classified them into 995 gene cluster families (GCFs). Surprisingly, only 9 GCFs (0.9 %) included an experimentally identified reference biosynthetic gene cluster from the Minimum Information about a Biosynthetic Gene cluster database (MIBiG), suggesting a striking novelty of secondary metabolites in Pseudoalteromonas. Bioinformatic analysis of the biosynthetic diversity encoded in the identified BGCs uncovered six dominant species of this genus, P. citrea, P. flavipulchra, P. luteoviolacea, P. maricaloris, P. piscicida, and P. rubra, that encoded more than 17 BGCs on average. Moreover, each species exhibited a species-specific distribution of BGC. However, a deep analysis revealed two BGCs conserved across five of the six dominant species. These BGCS encoded an unknown lanthipeptide and the siderophore myxochelin B implying an essential role of antibiotics for Pseudoalteromonas. We chemically profiled 11 strains from the 6 dominant species and identified four new antibiotics, korormicins L-O (1-4), from P. citrea WJX-3. Our results highlight the unexplored biosynthetic potential for bioactive compounds in Pseudoalteromonas and provide an important guideline for targeting exploration.

BTN3A1 expressed in cervical cancer cells promotes Vγ9Vδ2 T cells exhaustion through upregulating transcription factors NR4A2/3 downstream of TCR signaling.

BACKGROUND: Clinical trials have shown that immunotherapy based on Vγ9Vδ2 T cells (Vδ2 T cells) is safe and well-tolerated for various cancers including cervical cancer (CC), but its overall treatment efficacy remains limited. Therefore, exploring the mechanisms underlying the suboptimal efficacy of Vδ2 T cell-based cancer immunotherapy is crucial for enabling its successful clinical translation. METHODS: Tumor samples from CC patients and CC cell line-derived xenograft (CDX) mice were analyzed using flow cytometry to examine the exhausted phenotype of tumor-infiltrating Vδ2 T cells. The interrelationship between BTN3A1 expression and Vδ2 T cells in CC, along with their correlation with patient prognosis, was analyzed using data from The Cancer Genome Atlas (TCGA) database. CC cell lines with BTN3A1 knockout (KO) and overexpression (OE) were constructed through lentivirus transduction, which were then co-cultured with expanded Vδ2 T cells, followed by detecting the function of Vδ2 T cells using flow cytometry. The pathways and transcription factors (TFs) related to BTN3A1-induced Vδ2 T cells exhaustion and the factors affecting BTN3A1 expression were identified by RNA-seq analysis, which was confirmed by flow cytometry, Western Blot, and gene manipulation. RESULTS: Tumor-infiltrating Vδ2 T cells exhibited an exhausted phenotype in both CC patients and CDX mice. BTN3A1 expressed in CC is highly enhancing exhaustion markers, while reducing the secretion of effector molecules in Vδ2 T cells. Blocking TCR or knocking down nuclear receptor subfamily 4 group A (NR4A) 2/3 can reverse BTN3A1-induced exhaustion in Vδ2 T cells. On the other hand, IFN-γ secreted by Vδ2 T cells promoted the expression of BTN3A1 and PD-L1. CONCLUSIONS: Through binding γδ TCRs, BTN3A1 expressed on tumor cells, which is induced by IFN-γ, can promote Vδ2 T cells to upregulate the expression of TFs NR4A2/3, thereby affecting their activation and expression of exhaustion-related molecules in the tumor microenvironment (TME). Therefore, targeting BTN3A1 might overcome the immunosuppressive effect of the TME on Vδ2 T cells in CC.

L-Glutamate Regulates Npy via the mGluR4-Ca2+-ERK1/2 Signaling Pathway in Mandarin Fish (Siniperca chuatsi).

Metabotropic glutamate receptor 4 (mGluR4) is widely regarded as an umami receptor activated by L-glutamate to exert essential functions. Numerous studies have shown that umami receptors participate in food intake regulation. However, little is known about mGluR4's role in mediating food ingestion and its possible molecular mechanism. Mandarin fish, a typical carnivorous fish, is sensitive to umami substances and is a promising vertebrate model organism for studying the umami receptor. In this study, we identified the mGluR4 gene and conducted evolutionary analyses from diverse fish species with different feeding habits. mGluR4 of mandarin fish was cloned and functionally expressed to investigate the effects of L-glutamate on mGluR4. We further explored whether the signal pathway mGluR4-Ca2+-ERK1/2 participates in the process in mandarin fish brain cells. The results suggest that L-glutamate could regulate Neuropeptide Y (Npy) via the mGluR4-Ca2+-ERK1/2 signaling pathway in mandarin fish. Our findings unveil the role of mGluR4 in feeding decisions and its possible molecular mechanisms in carnivorous fishes.

Berberine sensitizes immune checkpoint blockade therapy in melanoma by NQO1 inhibition and ROS activation.

Unprecedented progress in immune checkpoint blockade (ICB) therapy has been made in cancer treatment. However, the response to ICB therapy is limited to a small subset of patients. The development of ICB sensitizers to improve cancer immunotherapy outcomes is urgently needed. Berberine (BBR), a well-known phytochemical compound isolated from many kinds of medicinal plants such as Berberis aristata, Coptis chinensis, and Phellondendron chinense Schneid, has shown the ability to inhibit the proliferation, invasion and metastasis of cancer cells. In this study, we investigated whether BBR can enhance the therapeutic benefit of ICB for melanoma, and explored the underlying mechanisms involved. The results showed that BBR could sensitize ICB to inhibit tumor growth and increased the survival rate of mice. Moreover, BBR stimulated intracellular ROS production partially by inhibiting NQO1 activity, which induced immunogenic cell death (ICD) in melanoma, elevated the levels of damage-associated molecular patterns (DAMPs), and subsequently activated DC cells and CD8 + T cells in vitro and in vivo. In conclusion, BBR is a novel ICD inducer. BBR could enhance the therapeutic benefit of ICB for melanoma. These effects were partially mediated through the inhibition of NQO1 and ROS activation.