ROS-dependent S-palmitoylation activates cleaved and intact gasdermin D.

Gasdermin D (GSDMD) is the common effector for cytokine secretion and pyroptosis downstream of inflammasome activation and was previously shown to form large transmembrane pores upon cleavage by inflammatory caspases to generate the GSDMD N-terminal domain (GSDMD-NT)1-10. Here we report that GSDMD Cys191 is S-palmitoylated and palmitoylation is required for pore formation. S-palmitoylation, which does not affect GSDMD cleavage, is augmented by mitochondria-generated reactive oxygen species (ROS). Surprisingly, cleavage-deficient D275A GSDMD is also palmitoylated after inflammasome stimulation or treatment with ROS activators, and causes pyroptosis, although less efficiently than palmitoylated GSDMD-NT. Palmitoylated, but not unpalmitoylated, full-length GSDMD induces liposome leakage, and forms a pore similar in structure to GSDMD-NT pores shown by cryogenic electron microscopy. zDHHC5 and zDHHC9 are the major palmitoyltransferases that mediate GSDMD palmitoylation, and their expression is upregulated by inflammasome activation and ROS. The other human gasdermins are also palmitoylated in their N-termini. These data challenge the concept that cleavage is the only trigger for GSDMD activation. They suggest that reversible palmitoylation is a checkpoint for pore formation by both GSDMD-NT and intact GSDMD that serves as a general switch for the activation of this pore-forming family.

CDC45 promotes the stemness and metastasis in lung adenocarcinoma by affecting the cell cycle.

OBJECTIVE: This study aimed to assess the functions of cell division cycle protein 45 (CDC45) in Non-small cell lung cancer (NSCLC) cancer and its effects on stemness and metastasis. METHODS: Firstly, differentially expressed genes related to lung cancer metastasis and stemness were screened by differential analysis and lasso regression. Then, in vitro, experiments such as colony formation assay, scratch assay, and transwell assay were conducted to evaluate the impact of CDC45 knockdown on the proliferation and migration abilities of lung cancer cells. Western blotting was used to measure the expression levels of related proteins and investigate the regulation of CDC45 on the cell cycle. Finally, in vivo model with subcutaneous injection of lung cancer cells was performed to verify the effect of CDC45 on tumor growth. RESULTS: This study identified CDC45 as a key gene potentially influencing tumor stemness and lymph node metastasis. Knockdown of CDC45 not only suppressed the proliferation and migration abilities of lung cancer cells but also caused cell cycle arrest at the G2/M phase. Further analysis revealed a negative correlation between CDC45 and cell cycle-related proteins, stemness-related markers, and tumor mutations. Mouse experiments confirmed that CDC45 knockdown inhibited tumor growth. CONCLUSION: As a novel regulator of stemness, CDC45 plays a role in regulating lung cancer cell proliferation, migration, and cell cycle. Therefore, CDC45 may serve as a potential target for lung cancer treatment and provide a reference for further mechanistic research and therapeutic development.

CO2 Electrolyzers.

CO2 electrolyzers have progressed rapidly in energy efficiency and catalyst selectivity toward valuable chemical feedstocks and fuels, such as syngas, ethylene, ethanol, and methane. However, each component within these complex systems influences the overall performance, and the further advances needed to realize commercialization will require an approach that considers the whole process, with the electrochemical cell at the center. Beyond the cell boundaries, the electrolyzer must integrate with upstream CO2 feeds and downstream separation processes in a way that minimizes overall product energy intensity and presents viable use cases. Here we begin by describing upstream CO2 sources, their energy intensities, and impurities. We then focus on the cell, the most common CO2 electrolyzer system architectures, and each component within these systems. We evaluate the energy savings and the feasibility of alternative approaches including integration with CO2 capture, direct conversion of flue gas and two-step conversion via carbon monoxide. We evaluate pathways that minimize downstream separations and produce concentrated streams compatible with existing sectors. Applying this comprehensive upstream-to-downstream approach, we highlight the most promising routes, and outlook, for electrochemical CO2 reduction.

Selective Electrified Propylene-to-Propylene Glycol Oxidation on Activated Rh-Doped Pd.

Renewable-energy-powered electrosynthesis has the potential to contribute to decarbonizing the production of propylene glycol, a chemical that is used currently in the manufacture of polyesters and antifreeze and has a high carbon intensity. Unfortunately, to date, the electrooxidation of propylene under ambient conditions has suffered from a wide product distribution, leading to a low faradic efficiency toward the desired propylene glycol. We undertook mechanistic investigations and found that the reconstruction of Pd to PdO occurs, followed by hydroxide formation under anodic bias. The formation of this metastable hydroxide layer arrests the progressive dissolution of Pd in a locally acidic environment, increases the activity, and steers the reaction pathway toward propylene glycol. Rh-doped Pd further improves propylene glycol selectivity. Density functional theory (DFT) suggests that the Rh dopant lowers the energy associated with the production of the final intermediate in propylene glycol formation and renders the desorption step spontaneous, a concept consistent with experimental studies. We report a 75% faradic efficiency toward propylene glycol maintained over 100 h of operation.

Recent advances in understanding the regulatory mechanism of plasma membrane H+-ATPase through the brassinosteroid signaling pathway.

The polyhydroxylated steroid phytohormone brassinosteroids (BRs) control many aspects of plant growth, development and responses to environmental changes. Plasma membrane (PM) H+-ATPase, the well-known PM proton pump, is a central regulator in plant physiology, which mediates not only plant growth and development, but also adaptation to stresses. Recent studies highlight that PM H+-ATPase is at least partly regulated via the BR signaling. Firstly, the BR cell surface receptor BRASSINOSTEROID-INSENSITIVE 1 (BRI1) and multiple key components of BR signaling directly or indirectly influence PM H+-ATPase activity. Secondly, the SMALL AUXIN UP RNA (SAUR) gene family physically interacts with BRI1 to enhance organ development of Arabidopsis by activating PM H+-ATPase. Thirdly, RNA-sequencing (RNA-seq) assays showed that the expression of some SAUR genes is upregulated under the light or sucrose conditions, which is related to the phosphorylation state of the penultimate residue of PM H+-ATPase in a time-course manner. In this review, we describe the structural and functional features of PM H+-ATPase, and summarize recent progress toward understanding the regulatory mechanism of PM H+-ATPase by BRs, and briefly introduce how PM H+-ATPase activity is modulated by its own biterminal regions and the post-translational modifications.

DeepION: A Deep Learning-Based Low-Dimensional Representation Model of Ion Images for Mass Spectrometry Imaging.

Mass spectrometry imaging (MSI) is a high-throughput imaging technique capable of the qualitative and quantitative in situ detection of thousands of ions in biological samples. Ion image representation is a technique that produces a low-dimensional vector embedded with significant spectral and spatial information on an ion image, which further facilitates the distance-based similarity measurement for the identification of colocalized ions. However, given the low signal-to-noise ratios inherent in MSI data coupled with the scarcity of annotated data sets, achieving an effective ion image representation for each ion image remains a challenge. In this study, we propose DeepION, a novel deep learning-based method designed specifically for ion image representation, which is applied to the identification of colocalized ions and isotope ions. In DeepION, contrastive learning is introduced to ensure that the model can generate the ion image representation in a self-supervised manner without manual annotation. Since data augmentation is a crucial step in contrastive learning, a unique data augmentation strategy is designed by considering the characteristics of MSI data, such as the Poisson distribution of ion abundance and a random pattern of missing values, to generate plentiful ion image pairs for DeepION model training. Experimental results of rat brain tissue MSI show that DeepION outperforms other methods for both colocalized ion and isotope ion identification, demonstrating the effectiveness of ion image representation. The proposed model could serve as a crucial tool in the biomarker discovery and drug development of the MSI technique.

Single walled carbon nanotubes band gap width measurement and the influence of nitrogen doping research.

The adjustment and measurement of the band gap width of single-walled carbon nanotubes are crucial for optimizing the design and enhancing the performance of carbon-based devices. This study utilizes the relationship between the band gap and temperature of semiconductor-based carbon nanotubes. The electrical conductivity of carbon nanotubes was obtained at various temperatures, and the corresponding band gap width (0.57 eV) was determined. The introduction of nitrogen results in a reduction of the band gap width and an increase in current flow between the device source and drain electrodes. Theoretical calculation demonstrated that nitrogen doping not only increases the conductivity of carbon nanotubes but also effectively inhibits the Schottky barrier between carbon nanotubes and metal electrodes. The Schottky barrier and the internal electric field can be effectively modulated via nitrogen doping in carbon nanotubes, which enhances the performance of carbon-based devices.

RACGAP1 promotes the progression and poor prognosis of lung adenocarcinoma through its effects on the cell cycle and tumor stemness.

OBJECTION: Investigating the key genes and mechanisms that influence stemness in lung adenocarcinoma. METHODS: First, consistent clustering analysis was performed on lung adenocarcinoma patients using stemness scoring to classify them. Subsequently, WGCNA was utilized to identify key modules and hub genes. Then, machine learning methods were employed to screen and identify the key genes within these modules. Lastly, functional analysis of the key genes was conducted through cell scratch assays, colony formation assays, transwell migration assays, flow cytometry cell cycle analysis, and xenograft tumor models. RESULTS: First, two groups of patients with different stemness scores were obtained, where the high stemness score group exhibited poor prognosis and immunotherapy efficacy. Next, LASSO regression analysis and random forest regression were employed to identify genes (PBK, RACGAP1) associated with high stemness scores. RACGAP1 was significantly upregulated in the high stemness score group of lung adenocarcinoma and closely correlated with clinical pathological features, poor overall survival (OS), recurrence-free survival (RFS), and unfavorable prognosis in lung adenocarcinoma patients. Knockdown of RACGAP1 suppressed the migration, proliferation, and tumor growth of cancer cells. CONCLUSION: RACGAP1 not only indicates poor prognosis and limited immunotherapy benefits but also serves as a potential targeted biomarker influencing tumor stemness.

The role of ADAR1 through and beyond its editing activity in cancer.

Adenosine-to-inosine (A-to-I) editing of RNA, catalyzed by adenosine deaminase acting on RNA (ADAR) enzymes, is a prevalent RNA modification in mammals. It has been shown that A-to-I editing plays a critical role in multiple diseases, such as cardiovascular disease, neurological disorder, and particularly cancer. ADARs are the family of enzymes, including ADAR1, ADAR2, and ADAR3, that catalyze the occurrence of A-to-I editing. Notably, A-to-I editing is mainly catalyzed by ADAR1. Given the significance of A-to-I editing in disease development, it is important to unravel the complex roles of ADAR1 in cancer for the development of novel therapeutic interventions.In this review, we briefly describe the progress of research on A-to-I editing and ADARs in cancer, mainly focusing on the role of ADAR1 in cancer from both editing-dependent and independent perspectives. In addition, we also summarized the factors affecting the expression and editing activity of ADAR1 in cancer.

Site-selective protonation enables efficient carbon monoxide electroreduction to acetate.

Electrosynthesis of acetate from CO offers the prospect of a low-carbon-intensity route to this valuable chemical--but only once sufficient selectivity, reaction rate and stability are realized. It is a high priority to achieve the protonation of the relevant intermediates in a controlled fashion, and to achieve this while suppressing the competing hydrogen evolution reaction (HER) and while steering multicarbon (C2+) products to a single valuable product--an example of which is acetate. Here we report interface engineering to achieve solid/liquid/gas triple-phase interface regulation, and we find that it leads to site-selective protonation of intermediates and the preferential stabilization of the ketene intermediates: this, we find, leads to improved selectivity and energy efficiency toward acetate. Once we further tune the catalyst composition and also optimize for interfacial water management, we achieve a cadmium-copper catalyst that shows an acetate Faradaic efficiency (FE) of 75% with ultralow HER (<0.2% H2 FE) at 150 mA cm-2. We develop a high-pressure membrane electrode assembly system to increase CO coverage by controlling gas reactant distribution and achieve 86% acetate FE simultaneous with an acetate full-cell energy efficiency (EE) of 32%, the highest energy efficiency reported in direct acetate electrosynthesis.

Integrating bulk-RNA sequencing and single-cell sequencing analyses to characterize adenosine-enriched tumor microenvironment landscape and develop an adenosine-related prognostic signature predicting immunotherapy in lung adenocarcinoma.

The adenosine-signaling axis has been recognized as an important immunomodulatory pathway in tumor immunity. However, the biological role of the adenosine-signaling axis in the remodeling of the tumor microenvironment (TME) in lung adenocarcinoma (LUAD) remains unclear. Here, we quantified adenosine signaling (ado_sig) in LUAD samples using the GSVA method and assessed the prognostic value of adenosine in LUAD. Afterward, we explored the heterogeneity of the tumor-immune microenvironment at different adenosine levels. In addition, we analyzed the potential biological pathways engaged by adenosine. Next, we established single-cell transcriptional profiles of LUAD and analyzed cellular composition and cell-cell communication analysis under different adenosine microenvironments. Moreover, we established adenosine-related prognostic signatures (ARS) based on comprehensive bioinformatics analysis and evaluated the efficacy of ARS in predicting immunotherapy. The results demonstrated that adenosine signaling adversely impacted the survival of immune-enriched LUAD. The high-adenosine microenvironment exhibited elevated pro-tumor-immune infiltration, including M2 macrophages and displayed notably increased epithelial-mesenchymal transition (EMT) transformation. Furthermore, adenosine signaling displayed significant associations with the expression patterns and prognostic value of immunomodulators within the TME. Single-cell sequencing data revealed increased fibroblast occupancy and a prominent activation of the SPP1 signaling pathway in the high adenosine-signaling microenvironment. The ARS exhibited promising effectiveness in prognostication and predicting immunotherapy response in LUAD. In summary, overexpression of adenosine can cause a worsened prognosis in the LUAD with abundant immune infiltration. Moreover, increased adenosine levels are associated with pro-tumor-immune infiltration, active EMT transformation, pro-tumor angiogenesis, and other factors promoting cancer progression, which collectively contribute to the formation of an immunosuppressive microenvironment. Importantly, the ARS developed in this study demonstrate high efficacy in evaluating the response to immunotherapy.

Bimetallic-MOF Derived Carbon with Single Pt Anchored C4 Atomic Group Constructing Super Fuel Cell with Ultrahigh Power Density And Self-Change Ability.

Pursuing high power density with low platinum catalysts loading is a huge challenge for developing high-performance fuel cells (FCs). Herein, a new super fuel cell (SFC) is proposed with ultrahigh output power via specific electric double-layer capacitance (EDLC) + oxygen reduction reaction (ORR) parallel discharge, which is achieved using the newly prepared catalyst, single-atomic platinum on bimetallic metal-organic framework (MOF)-derived hollow porous carbon nanorods (PtSA /HPCNR). The PtSA-1.74 /HPCNR-based SFC has a 3.4-time higher transient specific power density and 13.3-time longer discharge time with unique in situ self-charge and energy storage ability than 20% Pt/C-based FCs. X-ray absorption fine structure, aberration-corrected high-angle annular dark-field scanning transmission electron microscope, and density functional theory calculations demonstrate that the synergistic effect of Pt single-atoms anchored on carbon defects significantly boosts its electron transfer, ORR catalytic activity, durability, and rate performance, realizing rapid " ORR+EDLC" parallel discharge mechanism to overcome the sluggish ORR process of traditional FCs. The promising SFC leads to a new pathway to boost the power density of FCs with extra-low Pt loading.

Risk model-guided identification of MTDH expression as a marker for ferroptosis induction therapy in head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) are a prevalent malignancy with high mortality and morbidity rates. Therefore, in this study, we aimed to develop a novel risk score model by using a DNA methylation signature associated with ferroptosis to enhance the prognosis prediction of HNSCC. The transcriptome, methylome, and clinical data of HNSCC patients were collected from The Cancer Genome Atlas (TCGA) database. Additionally, data from a methylation dataset in the Gene Expression Omnibus (GEO) database were used for validation. The ferroptosis score (FS) in each patient was calculated using the transcriptome data, and the single-sample gene set enrichment analysis (ssGSEA) was performed to assess ferroptosis activity. Furthermore, a series of biochemical experiments including CCK8, colony formation, wound healing, and ROS detection were carried out to evaluate the influence of MTDH on the malignancy of HNSCC. Our results revealed that the FS was associated with patient prognosis, as the patients with high FS had a poor prognosis. The receiver operating characteristic (ROC) curve established based on the ferroptosis-associated DNA methylation signature, demonstrated the excellent predictive power of FS for the 1-, 3-, and 5-year survival of HNSCC. Importantly, this predictive model was successfully validated in the GEO dataset. The nomogram also demonstrated excellent accuracy and reliability, as determined by the calibration curves and the decision curve analysis (DCA) plot. Interestingly, the risk score model was found to be correlated with immune cell infiltration and immunotherapy-related biomarkers, suggesting its potential in predicting the immunotherapy response in HNSCC treatment. Moreover, we found that the expression of two risk score model component genes, SETD1B and MTDH, was significantly different between tumor and the adjacent tissues in patients with LSCC, which was also significantly correlated with patient prognosis. Further experimental validation showed that the upregulated expression of MTDH significantly inhibited ferroptosis through regulating GPX4 expression and enhanced the cytotoxicity of ferroptosis inducers in HNSCC cells. In conclusion, we have developed a risk score model by using a ferroptosis-related DNA methylation signature, which can be used as an alternative tool to predict the prognosis of patients with HNSCC. SETD1B and MTDH were identified as the pivotal genes in this model and might play important role in the progression of HNSCC.

Theoretical and experimental investigations of enhanced carbon nanotube-gold interface conductivity through nitrogen doping.

It is necessary to establish high-quality contact between carbon nanotubes and metals in carbon-based devices. However, how to control and reduce contact resistance still remains unsolved. In this study, the effect of N doping in single-walled carbon nanotubes on the contact resistance with gold was studied by combining theoretical calculation with experimental methods. The theoretical results indicate that nitrogen doping in carbon nanotubes can control the bottom of the carbon nanotube conduction band downward, the Fermi level enters the conduction band, the height of the Schottky barrier between the bottom of the carbon nanotube conduction band and the gold Fermi level decreases, and the increase in doping concentration leads to the decrease of Schottky barrier width. As a result, the conductivity between the gold and carbon nanotube interface is enhanced. During experiments, the carrier density and the current of the gold and carbon nanotube device increase gradually with the increase in N doping concentration and a good electron transport channel is established between the gold and carbon nanotubes. The high-quality contact is crucial to reducing the size, improving the performance, and reducing the power consumption of carbon-based devices.

The dual role of regulatory T cells in hepatitis B virus infection and related hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a major contributor to cancer-related deaths worldwide. Hepatitis B virus (HBV) infection is a major etiologic factor leading to HCC. While there have been significant advancements in controlling HBV replication, achieving a complete cure for HBV-related HCC (HBV-HCC) remains an intricate challenge. HBV persistence is attributed to a myriad of mechanisms, encompassing both innate and adaptive immune responses. Regulatory T cells (Tregs) are pivotal in upholding immune tolerance and modulating excessive immune activation. During HBV infection, Tregs mediate specific T cell suppression, thereby contributing to both persistent infection and the mitigation of liver inflammatory responses. Studies have demonstrated an augmented expression of circulating and intrahepatic Tregs in HBV-HCC, which correlates with impaired CD8+ T cell function. Consequently, Tregs play a dual role in the context of HBV infection and the progression of HBV-HCC. In this comprehensive review, we discuss pertinent studies concerning Tregs in HBV infection, HBV-related cirrhosis and HCC. Furthermore, we summarize Treg responses to antiviral therapy and provide Treg-targeted therapies specific to HBV and HCC.

SPOCK1, as a potential prognostic and therapeutic biomarker for lung adenocarcinoma, is associated with epithelial-mesenchymal transition and immune evasion.

BACKGROUND: The occurrence of epithelial-mesenchymal transition (EMT) and immune evasion is considered to contribute to poor prognosis in lung adenocarcinoma (LUAD). Therefore, this study aims to explore the key oncogenes that promote EMT and immune evasion and reveal the expression patterns, prognostic value, and potential biological functions. METHODS: Firstly, we identified gene modules associated with EMT and Tumor Immune Dysfunction and Exclusion (TIDE) through weighted gene co-expression network analysis (WGCNA). Next, we utilized differential analysis and machine learning to identify the key genes and validate them. Moreover, we analyzed the correlation between key genes and tumor microenvironment remodeling, drug sensitivity, as well as mutation frequency. Furthermore, we explored and validated their malignant biological characteristics through in vitro experiments and clinical samples. Finally, potential drugs for LUAD were screened based on CMap and validated through experiments. RESULTS: Firstly, WGCNA analysis revealed that red and green modules were highly correlated with EMT and TIDE. Among them, upregulated expression of SPOCK1 was observed in lung adenocarcinoma tissues and was associated with poor prognosis. Additionally, patients in the high SPOCK1 group showed more activation of malignant oncogenic pathways, higher infiltration of immunosuppressive components, and a higher frequency of mutations. The knockdown of SPOCK1 suppressed invasion and metastasis capabilities of lung adenocarcinoma cells, and the high expression of SPOCK1 was associated with low infiltration of CD8+ T cells. Therapeutic aspects, SPOCK1 can be a candidate indicator for drug sensitivity and CMap showed that VER-155008 was the drug candidate with the largest perturbation effect on the SPOCK1 expression profile. In vitro and in vivo experiments validated the cancer-inhibitory effect of VER-155008 in LUAD. CONCLUSION: This study revealed through comprehensive bioinformatics analysis and experimental analysis that SPOCK1 can promote EMT and immune escape in LUAD, and it may serve as a promising candidate prognostic biomarker and therapeutic target for LUAD.

Predicting potential microbe-disease associations based on auto-encoder and graph convolution network.

The increasing body of research has consistently demonstrated the intricate correlation between the human microbiome and human well-being. Microbes can impact the efficacy and toxicity of drugs through various pathways, as well as influence the occurrence and metastasis of tumors. In clinical practice, it is crucial to elucidate the association between microbes and diseases. Although traditional biological experiments accurately identify this association, they are time-consuming, expensive, and susceptible to experimental conditions. Consequently, conducting extensive biological experiments to screen potential microbe-disease associations becomes challenging. The computational methods can solve the above problems well, but the previous computational methods still have the problems of low utilization of node features and the prediction accuracy needs to be improved. To address this issue, we propose the DAEGCNDF model predicting potential associations between microbes and diseases. Our model calculates four similar features for each microbe and disease. These features are fused to obtain a comprehensive feature matrix representing microbes and diseases. Our model first uses the graph convolutional network module to extract low-rank features with graph information of microbes and diseases, and then uses a deep sparse Auto-Encoder to extract high-rank features of microbe-disease pairs, after which the low-rank and high-rank features are spliced to improve the utilization of node features. Finally, Deep Forest was used for microbe-disease potential relationship prediction. The experimental results show that combining low-rank and high-rank features helps to improve the model performance and Deep Forest has better classification performance than the baseline model.

Gasdermin D permeabilization of mitochondrial inner and outer membranes accelerates and enhances pyroptosis.

Gasdermin D (GSDMD)-activated inflammatory cell death (pyroptosis) causes mitochondrial damage, but its underlying mechanism and functional consequences are largely unknown. Here, we show that the N-terminal pore-forming GSDMD fragment (GSDMD-NT) rapidly damaged both inner and outer mitochondrial membranes (OMMs) leading to reduced mitochondrial numbers, mitophagy, ROS, loss of transmembrane potential, attenuated oxidative phosphorylation (OXPHOS), and release of mitochondrial proteins and DNA from the matrix and intermembrane space. Mitochondrial damage occurred as soon as GSDMD was cleaved prior to plasma membrane damage. Mitochondrial damage was independent of the B-cell lymphoma 2 family and depended on GSDMD-NT binding to cardiolipin. Canonical and noncanonical inflammasome activation of mitochondrial damage, pyroptosis, and inflammatory cytokine release were suppressed by genetic ablation of cardiolipin synthase (Crls1) or the scramblase (Plscr3) that transfers cardiolipin to the OMM. Phospholipid scramblase-3 (PLSCR3) deficiency in a tumor compromised pyroptosis-triggered anti-tumor immunity. Thus, mitochondrial damage plays a critical role in pyroptosis.

Celastrol as a candidate drug for silicosis: From bioinformatics and network pharmacology to experimental validation.

Silicosis, a highly lethal occupational respiratory disease characterized by irreversible pulmonary fibrosis, remains challenging to treat due to its unclear pathogenesis. In this study, bioinformatics, network pharmacology, and experimental validation were combined to explore potential mechanisms and therapeutic drugs for silicosis. First, the differentially expressed genes（DEGs）and pathway enrichment in pulmonary fibrosis were identified by GO and KEGG analysis. Next, the differential genes were submitted to cMap database for drug prediction and celastrol stood out as the most promising candidate drug. Then, network pharmacology analysis identified pharmacological targets of celastrol and demonstrated that celastrol could regulate JAK-STAT, MAPK, and Toll-like receptor signaling pathways. Finally, we verified the therapeutic role and mechanism of celastrol on silicosis. In vivo, celastrol significantly ameliorated CS-induced inflammation and fibrosis in silicosis mice, including inflammatory cell infiltration, collagen fiber and extracellular matrix deposition, fibroblast activation and related factor expression. Moreover, it dramatically improved lung respiratory function of silicosis mice. In vitro, celastrol suppressed CS-induced cytokine expression, apoptosis of macrophages and activation of Stat3 and Erk1/2 signals. Overall, our research identified and verified celastrol as a novel and promising candidate drug for silicosis.

Efficient multicarbon formation in acidic CO2 reduction via tandem electrocatalysis.

The electrochemical reduction of CO2 in acidic conditions enables high single-pass carbon efficiency. However, the competing hydrogen evolution reaction reduces selectivity in the electrochemical reduction of CO2, a reaction in which the formation of CO, and its ensuing coupling, are each essential to achieving multicarbon (C2+) product formation. These two reactions rely on distinct catalyst properties that are difficult to achieve in a single catalyst. Here we report decoupling the CO2-to-C2+ reaction into two steps, CO2-to-CO and CO-to-C2+, by deploying two distinct catalyst layers operating in tandem to achieve the desired transformation. The first catalyst, atomically dispersed cobalt phthalocyanine, reduces CO2 to CO with high selectivity. This process increases local CO availability to enhance the C-C coupling step implemented on the second catalyst layer, which is a Cu nanocatalyst with a Cu-ionomer interface. The optimized tandem electrodes achieve 61% C2H4 Faradaic efficiency and 82% C2+ Faradaic efficiency at 800 mA cm-2 at 25 °C. When optimized for single-pass utilization, the system reaches a single-pass carbon efficiency of 90 ± 3%, simultaneous with 55 ± 3% C2H4 Faradaic efficiency and a total C2+ Faradaic efficiency of 76 ± 2%, at 800 mA cm-2 with a CO2 flow rate of 2 ml min-1.