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.

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 after 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 that palmitoylation is required for pore formation. S-palmitoylation, which does not affect GSDMD cleavage, is augmented by mitochondria-generated reactive oxygen species (ROS). Cleavage-deficient GSDMD (D275A) 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 at 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 functions as a general switch for the activation of this pore-forming family.

SPARCLE, a p53-induced lncRNA, controls apoptosis after genotoxic stress by promoting PARP-1 cleavage.

p53, master transcriptional regulator of the genotoxic stress response, controls cell-cycle arrest and apoptosis following DNA damage. Here, we identify a p53-induced lncRNA suicidal PARP-1 cleavage enhancer (SPARCLE) adjacent to miR-34b/c required for p53-mediated apoptosis. SPARCLE is a ∼770-nt, nuclear lncRNA induced 1 day after DNA damage. Despite low expression (<16 copies/cell), SPARCLE deletion increases DNA repair and reduces DNA-damage-induced apoptosis as much as p53 deficiency, while its overexpression restores apoptosis in p53-deficient cells. SPARCLE does not alter gene expression. SPARCLE binds to PARP-1 with nanomolar affinity and causes apoptosis by acting as a caspase-3 cofactor for PARP-1 cleavage, which separates PARP-1's N-terminal (NT) DNA-binding domain from its catalytic domains. NT-PARP-1 inhibits DNA repair. Expressing NT-PARP-1 in SPARCLE-deficient cells increases unrepaired DNA damage and restores apoptosis after DNA damage. Thus, SPARCLE enhances p53-induced apoptosis by promoting PARP-1 cleavage, which interferes with DNA-damage repair.

Streptococcal pyrogenic exotoxin B cleaves GSDMA and triggers pyroptosis.

Gasdermins, a family of five pore-forming proteins (GSDMA-GSDME) in humans expressed predominantly in the skin, mucosa and immune sentinel cells, are key executioners of inflammatory cell death (pyroptosis), which recruits immune cells to infection sites and promotes protective immunity1,2. Pore formation is triggered by gasdermin cleavage1,2. Although the proteases that activate GSDMB, C, D and E have been identified, how GSDMA-the dominant gasdermin in the skin-is activated, remains unknown. Streptococcus pyogenes, also known as group A Streptococcus (GAS), is a major skin pathogen that causes substantial morbidity and mortality worldwide3. Here we show that the GAS cysteine protease SpeB virulence factor triggers keratinocyte pyroptosis by cleaving GSDMA after Gln246, unleashing an active N-terminal fragment that triggers pyroptosis. Gsdma1 genetic deficiency blunts mouse immune responses to GAS, resulting in uncontrolled bacterial dissemination and death. GSDMA acts as both a sensor and substrate of GAS SpeB and as an effector to trigger pyroptosis, adding a simple one-molecule mechanism for host recognition and control of virulence of a dangerous microbial pathogen.

CRISPR interference screens reveal growth-robustness tradeoffs in Synechocystis sp. PCC 6803 across growth conditions.

Barcoded mutant libraries are a powerful tool for elucidating gene function in microbes, particularly when screened in multiple growth conditions. Here, we screened a pooled CRISPR interference library of the model cyanobacterium Synechocystis sp. PCC 6803 in 11 bioreactor-controlled conditions, spanning multiple light regimes and carbon sources. This gene repression library contained 21,705 individual mutants with high redundancy over all open reading frames and noncoding RNAs. Comparison of the derived gene fitness scores revealed multiple instances of gene repression being beneficial in 1 condition while generally detrimental in others, particularly for genes within light harvesting and conversion, such as antennae components at high light and PSII subunits during photoheterotrophy. Suboptimal regulation of such genes likely represents a tradeoff of reduced growth speed for enhanced robustness to perturbation. The extensive data set assigns condition-specific importance to many previously unannotated genes and suggests additional functions for central metabolic enzymes. Phosphoribulokinase, glyceraldehyde-3-phosphate dehydrogenase, and the small protein CP12 were critical for mixotrophy and photoheterotrophy, which implicates the ternary complex as important for redirecting metabolic flux in these conditions in addition to inactivation of the Calvin cycle in the dark. To predict the potency of sgRNA sequences, we applied machine learning on sgRNA sequences and gene repression data, which showed the importance of C enrichment and T depletion proximal to the PAM site. Fitness data for all genes in all conditions are compiled in an interactive web application.

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.

Disulfiram blocks inflammatory TLR4 signaling by targeting MD-2.

Toll-like receptor 4 (TLR4) sensing of lipopolysaccharide (LPS), the most potent pathogen-associated molecular pattern of gram-negative bacteria, activates NF-κB and Irf3, which induces inflammatory cytokines and interferons that trigger an intense inflammatory response, which is critical for host defense but can also cause serious inflammatory pathology, including sepsis. Although TLR4 inhibition is an attractive therapeutic approach for suppressing overexuberant inflammatory signaling, previously identified TLR4 antagonists have not shown any clinical benefit. Here, we identify disulfiram (DSF), an FDA-approved drug for alcoholism, as a specific inhibitor of TLR4-mediated inflammatory signaling. TLR4 cell surface expression, LPS sensing, dimerization and signaling depend on TLR4 binding to MD-2. DSF and other cysteine-reactive drugs, previously shown to block LPS-triggered inflammatory cell death (pyroptosis), inhibit TLR4 signaling by covalently modifying Cys133 of MD-2, a key conserved residue that mediates TLR4 sensing and signaling. DSF blocks LPS-triggered inflammatory cytokine, chemokine, and interferon production by macrophages in vitro. In the aggressive N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine mouse model of Parkinson's disease (PD) in which TLR4 plays an important role, DSF markedly suppresses neuroinflammation and dopaminergic neuron loss, and restores motor function. Our findings identify a role for DSF in curbing TLR4-mediated inflammation and suggest that DSF and other drugs that target MD-2 might be useful for treating PD and other diseases in which inflammation contributes importantly to pathogenesis.

Absence of alka(e)nes triggers profound remodeling of glycerolipid and carotenoid composition in cyanobacteria membrane.

Alka(e)nes are produced by many living organisms and exhibit diverse physiological roles, reflecting a high functional versatility. Alka(e)nes serve as waterproof wax in plants, communicating pheromones for insects, and microbial signaling molecules in some bacteria. Although alka(e)nes have been found in cyanobacteria and algal chloroplasts, their importance for photosynthetic membranes has remained elusive. In this study, we investigated the consequences of the absence of alka(e)nes on membrane lipid composition and photosynthesis using the cyanobacterium Synechocystis PCC6803 as a model organism. By following the dynamics of membrane lipids and the photosynthetic performance in strains defected and altered in alka(e)ne biosynthesis, we show that drastic changes in the glycerolipid contents occur in the absence of alka(e)nes, including a decrease in the membrane carotenoid content, a decrease in some digalactosyldiacylglycerol (DGDG) species and a parallel increase in monogalactosyldiacylglycerol (MGDG) species. These changes are associated with a higher susceptibility of photosynthesis and growth to high light in alka(e)ne-deficient strains. All these phenotypes are reversed by expressing an algal photoenzyme producing alka(e)nes from fatty acids. Therefore, alkenes, despite their low abundance, are an essential component of the lipid composition of membranes. The profound remodeling of lipid composition that results from their absence suggests that they play an important role in one or more membrane properties in cyanobacteria. Moreover, the lipid compensatory mechanism observed is not sufficient to restore normal functioning of the photosynthetic membranes, particularly under high light intensity. We conclude that alka(e)nes play a crucial role in maintaining lipid homeostasis of thylakoid membranes, thereby contributing to the proper functioning of photosynthesis, particularly under elevated light intensities.

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.

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.

R-loop and diseases: the cell cycle matters.

The cell cycle is a crucial biological process that is involved in cell growth, development, and reproduction. It can be divided into G1, S, G2, and M phases, and each period is closely regulated to ensure the production of two similar daughter cells with the same genetic material. However, many obstacles influence the cell cycle, including the R-loop that is formed throughout this process. R-loop is a triple-stranded structure, composed of an RNA: DNA hybrid and a single DNA strand, which is ubiquitous in organisms from bacteria to mammals. The existence of the R-loop has important significance for the regulation of various physiological processes. However, aberrant accumulation of R-loop due to its limited resolving ability will be detrimental for cells. For example, DNA damage and genomic instability, caused by the R-loop, can activate checkpoints in the cell cycle, which in turn induce cell cycle arrest and cell death. At present, a growing number of factors have been proven to prevent or eliminate the accumulation of R-loop thereby avoiding DNA damage and mutations. Therefore, we need to gain detailed insight into the R-loop resolution factors at different stages of the cell cycle. In this review, we review the current knowledge of factors that play a role in resolving the R-loop at different stages of the cell cycle, as well as how mutations of these factors lead to the onset and progression of diseases.

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.

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.

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.

Predicting multiple types of miRNA-disease associations using adaptive weighted nonnegative tensor factorization with self-paced learning and hypergraph regularization.

More and more evidence indicates that the dysregulations of microRNAs (miRNAs) lead to diseases through various kinds of underlying mechanisms. Identifying the multiple types of disease-related miRNAs plays an important role in studying the molecular mechanism of miRNAs in diseases. Moreover, compared with traditional biological experiments, computational models are time-saving and cost-minimized. However, most tensor-based computational models still face three main challenges: (i) easy to fall into bad local minima; (ii) preservation of high-order relations; (iii) false-negative samples. To this end, we propose a novel tensor completion framework integrating self-paced learning, hypergraph regularization and adaptive weight tensor into nonnegative tensor factorization, called SPLDHyperAWNTF, for the discovery of potential multiple types of miRNA-disease associations. We first combine self-paced learning with nonnegative tensor factorization to effectively alleviate the model from falling into bad local minima. Then, hypergraphs for miRNAs and diseases are constructed, and hypergraph regularization is used to preserve the high-order complex relations of these hypergraphs. Finally, we innovatively introduce adaptive weight tensor, which can effectively alleviate the impact of false-negative samples on the prediction performance. The average results of 5-fold and 10-fold cross-validation on four datasets show that SPLDHyperAWNTF can achieve better prediction performance than baseline models in terms of Top-1 precision, Top-1 recall and Top-1 F1. Furthermore, we implement case studies to further evaluate the accuracy of SPLDHyperAWNTF. As a result, 98 (MDAv2.0) and 98 (MDAv2.0-2) of top-100 are confirmed by HMDDv3.2 dataset. Moreover, the results of enrichment analysis illustrate that unconfirmed potential associations have biological significance.

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.

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.

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.

Mechanisms of denitrifying granular sludge disintegration and calcium ion-enhanced re-granulation in acidic wastewater treatment.

Granular sludge is an alternative technology for the direct treatment of acidic nitrate-containing wastewater. Rapid remediation of disintegrated granules is essential to achieve efficient nitrogen removal. In this study, denitrifying granules were inactivated and disintegrated when the influent nitrate-nitrogen concentration was elevated from 240 to 360 mg L-1 in acidic wastewater (pH = 4.1) in a sequencing batch reactor. Tightly bound extracellular polymeric substances (TB-EPS) decreased by 60%, and extracellular protein (PN) was the main component of the reduced EPS. The three-dimensional excitation emission matrices (3D-EEM) results confirmed that the PNs that decreased were mainly tryptophan-like, tyrosine-like, and aromatic. This study further confirmed that the decrease in PN was mainly from the destruction of C=O (amide I) and N-H functional groups. Overloading of nitrogen-inhibited denitrifying activity and the destruction and dissolution of TB-EPS by acidic pH were responsible for granule disintegration, with PNs playing a major role in maintaining granule stability. Based on this, new granules with an average particle size of 454.4 µm were formed after calcium chloride addition; EPS nearly doubled during granule formation with PN as the dominant component, accounting for 64.7-78.4% of the EPS. Atomic force microscopy (AFM) revealed that PN-PN adhesion increased by 1.6-4.9 times in the presence of calcium ions, accelerating the re-granulation of disintegrated particles. This study provides new insights into the disintegration and remediation of granular sludge under acidic conditions.