MultiFeatVotPIP: a voting-based ensemble learning framework for predicting proinflammatory peptides.

Inflammatory responses may lead to tissue or organ damage, and proinflammatory peptides (PIPs) are signaling peptides that can induce such responses. Many diseases have been redefined as inflammatory diseases. To identify PIPs more efficiently, we expanded the dataset and designed an ensemble learning model with manually encoded features. Specifically, we adopted a more comprehensive feature encoding method and considered the actual impact of certain features to filter them. Identification and prediction of PIPs were performed using an ensemble learning model based on five different classifiers. The results show that the model's sensitivity, specificity, accuracy, and Matthews correlation coefficient are all higher than those of the state-of-the-art models. We named this model MultiFeatVotPIP, and both the model and the data can be accessed publicly at https://github.com/ChaoruiYan019/MultiFeatVotPIP. Additionally, we have developed a user-friendly web interface for users, which can be accessed at http://www.bioai-lab.com/MultiFeatVotPIP.

RAVAR: a curated repository for rare variant-trait associations.

Rare variants contribute significantly to the genetic causes of complex traits, as they can have much larger effects than common variants and account for much of the missing heritability in genome-wide association studies. The emergence of UK Biobank scale datasets and accurate gene-level rare variant-trait association testing methods have dramatically increased the number of rare variant associations that have been detected. However, no systematic collection of these associations has been carried out to date, especially at the gene level. To address the issue, we present the Rare Variant Association Repository (RAVAR), a comprehensive collection of rare variant associations. RAVAR includes 95 047 high-quality rare variant associations (76186 gene-level and 18 861 variant-level associations) for 4429 reported traits which are manually curated from 245 publications. RAVAR is the first resource to collect and curate published rare variant associations in an interactive web interface with integrated visualization, search, and download features. Detailed gene and SNP information are provided for each association, and users can conveniently search for related studies by exploring the EFO tree structure and interactive Manhattan plots. RAVAR could vastly improve the accessibility of rare variant studies. RAVAR is freely available for all users without login requirement at http://www.ravar.bio.

DPNN-ac4C: A Dual-Path Neural Network with self-attention mechanism for identification of N4­acetylcytidine (ac4C) in mRNA.

MOTIVATION: The modification of N4-acetylcytidine (ac4C) in RNA is a conserved epigenetic mark that plays a crucial role in post-transcriptional regulation, mRNA stability, and translation efficiency. Traditional methods for detecting ac4C modifications are laborious and costly, necessitating the development of efficient computational approaches for accurate identification of ac4C sites in mRNA. RESULTS: We present DPNN-ac4C, a dual-path neural network with a self-attention mechanism for the identification of ac4C sites in mRNA. Our model integrates embedding modules, bidirectional GRU networks, convolutional neural networks, and self-attention to capture both local and global features of RNA sequences. Extensive evaluations demonstrate that DPNN-ac4C outperforms existing models, achieving an AUROC of 91.03%, accuracy of 82.78%, MCC of 65.78%, and specificity of 84.78% on an independent test set. Moreover, DPNN-ac4C exhibits robustness under the Fast Gradient Method (FGM) attack, maintaining a high level of accuracy in practical applications. AVAILABILITY AND IMPLEMENTATION: The model code and dataset are publicly available on GitHub (https://github.com/shock1ng/DPNN-ac4C).

MVST: Identifying spatial domains of spatial transcriptomes from multiple views using multi-view graph convolutional networks.

Spatial transcriptome technology can parse transcriptomic data at the spatial level to detect high-throughput gene expression and preserve information regarding the spatial structure of tissues. Identifying spatial domains, that is identifying regions with similarities in gene expression and histology, is the most basic and critical aspect of spatial transcriptome data analysis. Most current methods identify spatial domains only through a single view, which may obscure certain important information and thus fail to make full use of the information embedded in spatial transcriptome data. Therefore, we propose an unsupervised clustering framework based on multiview graph convolutional networks (MVST) to achieve accurate spatial domain recognition by the learning graph embedding features of neighborhood graphs constructed from gene expression information, spatial location information, and histopathological image information through multiview graph convolutional networks. By exploring spatial transcriptomes from multiple views, MVST enables data from all parts of the spatial transcriptome to be comprehensively and fully utilized to obtain more accurate spatial expression patterns. We verified the effectiveness of MVST on real spatial transcriptome datasets, the robustness of MVST on some simulated datasets, and the reasonableness of the framework structure of MVST in ablation experiments, and from the experimental results, it is clear that MVST can achieve a more accurate spatial domain identification compared with the current more advanced methods. In conclusion, MVST is a powerful tool for spatial transcriptome research with improved spatial domain recognition.

AGF-PPIS: A protein-protein interaction site predictor based on an attention mechanism and graph convolutional networks.

Protein-protein interactions play an important role in various biological processes. Interaction among proteins has a wide range of applications. Therefore, the correct identification of protein-protein interactions sites is crucial. In this paper, we propose a novel predictor for protein-protein interactions sites, AGF-PPIS, where we utilize a multi-head self-attention mechanism (introducing a graph structure), graph convolutional network, and feed-forward neural network. We use the Euclidean distance between each protein residue to generate the corresponding protein graph as the input of AGF-PPIS. On the independent test dataset Test_60, AGF-PPIS achieves superior performance over comparative methods in terms of seven different evaluation metrics (ACC, precision, recall, F1-score, MCC, AUROC, AUPRC), which fully demonstrates the validity and superiority of the proposed AGF-PPIS model. The source codes and the steps for usage of AGF-PPIS are available at https://github.com/fxh1001/AGF-PPIS.

Plasma metabolomic signature of healthy lifestyle, structural brain reserve and risk of dementia.

Although the association between healthy lifestyle and dementia risk has been documented, the relationship between a metabolic signature indicative of healthy lifestyle and dementia risk and the mediating role of structural brain impairment remain unknown. We retrieved 136 628 dementia-free participants from UK Biobank. Elastic net regression was used to obtain a metabolic signature that represented lifestyle behaviours. Cox proportional hazard models were fitted to explore the associations of lifestyle-associated metabolic signature with incident dementia. Causal associations between identified metabolites and dementia were investigated using Mendelian randomization. Mediation analysis was also conducted to uncover the potential mechanisms involving 19 imaging-derived phenotypes (brain volume, grey matter volume, white matter volume and regional grey matter volumes). During a follow-up of 12.55 years, 1783 incident cases of all-cause dementia were identified, including 725 cases of Alzheimer's dementia and 418 cases of vascular dementia. We identified 83 metabolites that could represent healthy lifestyle behaviours using elastic net regression. The metabolic signature was associated with a lower dementia risk, and for each standard deviation increment in metabolic signature, the hazard ratio was 0.89 [95% confidence interval (CI): 0.85, 0.93] for all-cause dementia, 0.95 (95% CI: 0.88, 1.03) for Alzheimer's dementia and 0.84 (95% CI: 0.77, 0.91) for vascular dementia. Mendelian randomization revealed potential causal associations between the identified metabolites and risk of dementia. In addition, the specific structural brain reserve, including the hippocampus, grey matter in the hippocampus, parahippocampal gyrus and middle temporal gyrus, were detected to mediate the effects of metabolic signature on dementia risk (mediated proportion ranging from 6.21% to 11.98%). The metabolic signature associated with a healthy lifestyle is inversely associated with dementia risk, and greater structural brain reserve plays an important role in mediating this relationship. These findings have significant implications for understanding the intricate connections between lifestyle, metabolism and brain health.

ABC portal: a single-cell database and web server for blood cells.

ABC portal (http://abc.sklehabc.com) is a database and web portal containing 198 single-cell transcriptomic datasets of development, differentiation and disorder of blood/immune cells. All the datasets were re-annotated with a manually curated and unified single-cell reference, especially for the haematopoietic stem and progenitor cells. ABC portal provides web-based interactive analysis modules, especially a comprehensive cell-cell communication analysis and disease-related gene signature analysis. Importantly, ABC portal allows customized sample selection based on a combination of several metadata for downstream analysis and comparison analysis across datasets. ABC portal also allows users to select multiple cell types for analysis in the modules. Together, ABC portal provides an interactive interface of single-cell data exploration and re-analysis with customized analysis modules for the researchers and clinicians, and will facilitate understanding of haematopoiesis and blood/immune disorders.

msBERT-Promoter: a multi-scale ensemble predictor based on BERT pre-trained model for the two-stage prediction of DNA promoters and their strengths.

BACKGROUND: A promoter is a specific sequence in DNA that has transcriptional regulatory functions, playing a role in initiating gene expression. Identifying promoters and their strengths can provide valuable information related to human diseases. In recent years, computational methods have gained prominence as an effective means for identifying promoter, offering a more efficient alternative to labor-intensive biological approaches. RESULTS: In this study, a two-stage integrated predictor called "msBERT-Promoter" is proposed for identifying promoters and predicting their strengths. The model incorporates multi-scale sequence information through a tokenization strategy and fine-tunes the DNABERT model. Soft voting is then used to fuse the multi-scale information, effectively addressing the issue of insufficient DNA sequence information extraction in traditional models. To the best of our knowledge, this is the first time an integrated approach has been used in the DNABERT model for promoter identification and strength prediction. Our model achieves accuracy rates of 96.2% for promoter identification and 79.8% for promoter strength prediction, significantly outperforming existing methods. Furthermore, through attention mechanism analysis, we demonstrate that our model can effectively combine local and global sequence information, enhancing its interpretability. CONCLUSIONS: msBERT-Promoter provides an effective tool that successfully captures sequence-related attributes of DNA promoters and can accurately identify promoters and predict their strengths. This work paves a new path for the application of artificial intelligence in traditional biology.

Utilization trend of prebiopsy multiparametric magnetic resonance imaging and its impact on prostate cancer detection: Real-world insights from a high-volume center in southwest China.

BACKGROUND: Data on the utilization and effects of prebiopsy prostate multiparametric magnetic resonance imaging (mpMRI) to support its routine use in real-world setting are still scarce. OBJECTIVE: To evaluate the change of clinical practice of prebiopsy mpMRI over time, and assess its diagnostic accuracy. DESIGN, SETTING, AND PARTICIPANTS: We retrospectively analyzed data from 6168 patients who underwent primary prostate biopsy (PBx) between January 2011 and December 2021 and had prostate-specific antigen (PSA) values ranging from 3 to 100 ng/mL. INTERVENTION: Prebiopsy MRI at the time of PBx. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We performed general linear regression and to elucidate trends in the annual use of prebiopsy mpMRI and conducted multivariable logistic regression to evaluate the potential benefits of incorporating prebiopsy mpMRI for prostate cancer (PCa) detection. RESULTS AND LIMITATIONS: The utilization of prebiopsy mpMRI significantly increased from 9.2% in 2011 to 75.0% in 2021 (p < 0.001). In addition, prebiopsy mpMRI significantly reduced negative PBx by 8.6% while improving the detection of clinically significant PCa (csPCa) by 7.0%. Regression analysis showed that the utilization of prebiopsy mpMRI was significantly associated with a 48% (95% confidence interval [CI]: 1.19-1.84) and 36% (95% CI: 1.12-1.66) increased PCa detection rate in the PSA 3-10 ng/mL and 10-20 ng/mL groups, respectively; and a 34% increased csPCa detection rate in the PSA 10-20 ng/mL group (95% CI: 1.09-1.64). The retrospective design and the single center cohort constituted the limitations of this study. CONCLUSIONS: Our study demonstrated a notable rise in the utilization of prebiopsy mpMRI in the past decade. The adoption of this imaging technique was significantly associated with an increased probability of detecting prostate cancer. PATIENT SUMMARY: From 2011 to 2021, we demonstrated a steady increase in the utilization of prebiopsy mpMRI among biopsy-naïve men. We also confirmed the positive impact of prebiopsy mpMRI utilization on the detection of prostate cancer.

Enhanced Electron Transport and Mitigated Voltage Loss in Perovskite Photovoltaics Using Sb2O5@SnO2 Composite Electron Transport Layer.

The efficacy of electron transport layers (ETLs) is pivotal for optimizing the device performance of perovskite photovoltaic applications. However, colloidal dispersions of SnO2 are prone to aggregation and possess structural defects, such as terminal-hydroxyls (OHT) and oxygen vacancies (VOs), which can degrade the quality of ETLs, impede charge extraction and transport, and affect the nucleation and growth processes of the perovskite layer. In this study, the Sb(OH)4 - ions hydrolyzed from SbCl3 in colloidal dispersion can bind to defect sites and effectively stabilize the SnO2 nanocrystals are demonstrated. Upon oxidative annealing, a Sb2O5@SnO2 composite film is formed, in which the Sb2O5 not only mitigates the aforementioned defects but also broadens the energy range of unoccupied states through its dispersed conduction band. The increased electron affinity (EA) facilitates more efficient capture of photoexcited electrons from the perovskite layer, thus augmenting electron extraction and minimizing electron-hole recombination. As a result, a significant improvement in power conversion efficiency (PCE) from 22.60% to 24.54% is achieved, with an open circuit voltage (VOC) of up to 1.195 V, along with excellent stability of unsealed devices under various conditions. This study provides valuable insights for the understanding and design of ETLs in perovskite photovoltaic applications.

Single-cell transcriptome analysis reveals immune microenvironment changes and insights into the transition from DCIS to IDC with associated prognostic genes.

BACKGROUND: Ductal carcinoma in situ (DCIS) of the breast is an early stage of breast cancer, and preventing its progression to invasive ductal carcinoma (IDC) is crucial for the early detection and treatment of breast cancer. Although single-cell transcriptome analysis technology has been widely used in breast cancer research, the biological mechanisms underlying the transition from DCIS to IDC remain poorly understood. RESULTS: We identified eight cell types through cell annotation, finding significant differences in T cell proportions between DCIS and IDC. Using this as a basis, we performed pseudotime analysis on T cell subpopulations, revealing that differentially expressed genes primarily regulate immune cell migration and modulation. By intersecting WGCNA results of T cells highly correlated with the subtypes and the differentially expressed genes, we identified six key genes: FGFBP2, GNLY, KLRD1, TYROBP, PRF1, and NKG7. Excluding PRF1, the other five genes were significantly associated with overall survival in breast cancer, highlighting their potential as prognostic biomarkers. CONCLUSIONS: We identified immune cells that may play a role in the progression from DCIS to IDC and uncovered five key genes that can serve as prognostic markers for breast cancer. These findings provide insights into the mechanisms underlying the transition from DCIS to IDC, offering valuable perspectives for future research. Additionally, our results contribute to a better understanding of the biological processes involved in breast cancer progression.

Epidemiological and Genomic analysis of Vibrio parahaemolyticus isolated from imported travelers at the port of Shanghai, China (2017-2019).

BACKGROUND: Vibrio parahaemolyticus is the predominant etiological agent of seafood-associated foodborne illnesses on a global scale. It is essential to elucidate the mechanisms by which this pathogen disseminates. Given the existing research predominantly concentrates on localized outbreaks, there is a pressing necessity for a comprehensive investigation to capture strains of V. parahaemolyticus cross borders. RESULTS: This study examined the frequency and genetic attributes of imported V. parahaemolyticus strains among travelers entering Shanghai Port, China, between 2017 and 2019.Through the collection of 21 strains from diverse countries and regions, Southeast Asia was pinpointed as a significant source for the emergence of V. parahaemolyticus. Phylogenetic analysis revealed clear delineation between strains originating from human and environmental sources, emphasizing that underlying genome data of foodborne pathogens is essential for environmental monitoring, food safety and early diagnosis of diseases. Furthermore, our study identified the presence of virulence genes (tdh and tlh) and approximately 120 antibiotic resistance-related genes in the majority of isolates, highlighting their crucial involvement in the pathogenesis of V. parahaemolyticus. CONCLUSIONS: This research enhanced our comprehension of the worldwide transmission of V. parahaemolyticus and its antimicrobial resistance patterns. The findings have important implications for public health interventions and antimicrobial stewardship strategies, underscoring the necessity for epidemiological surveillance of pathogen at international travel hubs.

Impact of preoperative antiviral therapy on the prognosis of hepatitis B virus-related hepatocellular carcinoma.

BACKGROUND: For chronic hepatitis B virus (HBV) infection patients, increasing evidence has demonstrated the effectiveness of expanding the indications and applicable population for antiviral therapy. However, the expanded indication of antiviral therapy for hepatocellular carcinoma (HCC) remains to be further explored. METHODS: 196 HBV-related HCC patients who received radical hepatectomy and nucleos(t)ide analogues (NAs) therapy at Sichuan Provincial People's Hospital were enrolled in this study. HCC recurrence, overall survival (OS), early virological (VR) and biochemical responses (BR) of patients were compared between different NAs therapy and the use of anti-programmed cell death protein 1 (PD-1) therapy. RESULTS: NAs therapy at different timing of surgery was a strong independent risk factor for postoperative recurrence and overall mortality of HBV-related HCC patients. Furthermore, in HCC patients who received postoperative anti-PD-1 therapy, patients with HBV DNA < 1000 copy/mL had significantly better recurrence-free survival (RFS) and OS than those with HBV DNA ≥ 1000 copy/mL (HR: 7.783; P = 0.002; HR: 6.699; P < 0.001). However, the differences of RFS and OS rates between entecavir group and tenofovir disoproxil fumarate group were not statistically significant. Similar results were also observed in the rates of early VR, BR and combined VR and BR. CONCLUSION: Timely and reasonable preoperative NAs therapy showed clinical benefit in improving the prognosis of patients with HBV-related HCC, even in the case of normal alanine aminotransferase (ALT) level and negative hepatitis e antigen (HBeAg). Furthermore, a possible synergistic effect between antiviral therapy and anti-PD-1 therapy was founded and need further verification.

Alleviating effect of vagus nerve cutting in Salmonella-induced gut infections and anxiety-like behavior via enhancing microbiota-derived GABA.

The vagus nerve, a pivotal link within the gut-brain axis, plays a critical role in maintaining homeostasis and mediating communication between the gastrointestinal tract and the brain. It has been reported that gastrointestinal infection by Salmonella typhimurium (S. typhimurium) triggers gut inflammation and manifests as anxiety-like behaviors, yet the mechanistic involvement of the vagus nerve remains to be elucidated. In this study, we demonstrated that unilateral cervical vagotomy markedly attenuated anxiety-like behaviors induced by S. typhimurium SL1344 infection in C57BL/6 mice, as evidenced by the open field test and marble burying experiment. Furthermore, vagotomy significantly diminished neuronal activation within the nucleus of the solitary tract and amygdala, alongside mitigating aberrant glial cell activation in the hippocampus and amygdala. Additionally, vagotomy notably decreases serum endotoxin levels, counters the increase in splenic Salmonella concentration, and modulates the expression of inflammatory cytokines-including IL-6, IL-1ß, and TNF-α-in both the gastrointestinal tract and brain, with a concurrent reduction in IL-22 and CXCL1 expression. This intervention also fostered the enrichment of beneficial gut microbiota, including Alistipes and Lactobacillus species, and augmented the production of gamma-aminobutyric acid (GABA) in the gut. Administration of GABA replicated the vagotomy's beneficial effects on reducing gut inflammation and anxiety-like behavior in infected mice. However, blockade of GABA receptors with picrotoxin abrogated the vagotomy's protective effects against gut inflammation, without influencing its impact on anxiety-like behaviors. Collectively, these findings suggest that vagotomy exerts a protective effect against infection by promoting GABA synthesis in the colon and alleviating anxiety-like behavior. This study underscores the critical role of the vagus nerve in relaying signals of gut infection to the brain and posits that targeting the gut-brain axis may offer a novel and efficacious approach to preventing gastrointestinal infections and associated behavioral abnormalities.

Long-term exposure to ambient ozone and adult-onset asthma: A prospective cohort study.

BACKGROUND: The association between long-term exposure to ozone (O3) and adult-onset asthma (AOA) remains inconclusive, and analysis of causality is lacking. OBJECTIVES: To examine the causal association between long-term O3 exposure and AOA. METHODS: A prospective cohort study of 362,098 participants was conducted using the UK Biobank study. Incident cases of AOA were identified using health administrative data of the National Health Services. O3 exposure at participants' residential addresses was estimated by a spatio-temporal model. Instrumental variable (IV) modelling was used to analyze the causal association between O3 exposure and AOA, by incorporating wind speed and planetary boundary layer height as IVs into time-dependent Cox model. Negative control outcome (accidental injury) was also used to additionally evaluate unmeasured confounding. RESULTS: During a mean follow-up of 11.38 years, a total of 10,973 incident AOA cases were identified. A U-shaped concentration-response relationship was observed between O3 exposure and AOA in the traditional Cox models with HR of 0.916 (95% CI: 0.888, 0.945) for O3 at low levels (<38.17 ppb), and 1.204 (95% CI: 1.168, 1.242) for O3 at high levels (≥38.17 ppb). However, in the IV analysis we only found a statistically significant association between high-level O3 exposure and AOA risk, but not for low-level O3 exposure. No significant associations between O3 exposure and accidental injury were observed. CONCLUSION: Our findings suggest a potential causal relationship between long-term exposure to high-level ambient O3 and increased risks of AOA.

webTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study.

The development of transcriptome-wide association studies (TWAS) has enabled researchers to better identify and interpret causal genes in many diseases. However, there are currently no resources providing a comprehensive listing of gene-disease associations discovered by TWAS from published GWAS summary statistics. TWAS analyses are also difficult to conduct due to the complexity of TWAS software pipelines. To address these issues, we introduce a new resource called webTWAS, which integrates a database of the most comprehensive disease GWAS datasets currently available with credible sets of potential causal genes identified by multiple TWAS software packages. Specifically, a total of 235 064 gene-diseases associations for a wide range of human diseases are prioritized from 1298 high-quality downloadable European GWAS summary statistics. Associations are calculated with seven different statistical models based on three popular and representative TWAS software packages. Users can explore associations at the gene or disease level, and easily search for related studies or diseases using the MeSH disease tree. Since the effects of diseases are highly tissue-specific, webTWAS applies tissue-specific enrichment analysis to identify significant tissues. A user-friendly web server is also available to run custom TWAS analyses on user-provided GWAS summary statistics data. webTWAS is freely available at http://www.webtwas.net.

Associations between maternal exposure to air pollution during pregnancy and trajectories of infant growth: A birth cohort study.

OBJECTIVE: We examined the relationships between infants' growth trajectories and prenatal exposure to air pollution, which is still under-investigated. METHODS: A birth cohort study was constructed using medical records of pregnant women and infants born between 2015 and 2019 in Foshan, China. Using satellite-based spatial-temporal models, prenatal exposure to air pollutants including particulate matter with an aerodynamic dimension of < 2.5 µm (PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) was assessed at each woman's residence. Latent class growth modeling was used to identify trajectories of physical (body length and weight) growth and neurodevelopment, which were repeatedly measured within 1 year after birth. Logistic regression models were used to investigate the associations between prenatal exposure to air pollution and the risks of growth disorders, adjusting for an array of potential confounders. RESULTS: We identified two growth trajectories for body length [normal: 3829 (93%); retardation: 288 (7%)], three for weight [normal: 2475 (59.6%); retardation: 390 (9.4%); overgrowth: 1287 (31%)], and two for neurodevelopment [normal: 956 (66.1%); retardation: 491 (33.9%)]. For exposure over whole pregnancy, SO2 was associated with an increased risk of body length retardation (OR for per 1 µg/m3 increment: 1.09, 95%CI: 1.01-1.17); PM2.5 (OR: 1.05, 95%CI: 1.03-1.07), SO2 (OR: 1.15, 95%CI: 1.08-1.22), and NO2 (OR: 1.05, 95%CI: 1.03-1.07) were positively associated with neurodevelopmental retardation. Such associations appeared stronger for exposures over the first and second trimesters. No significant associations were detected for weight growth. CONCLUSIONS: Maternal exposure to air pollution during pregnancy was associated with higher risks of impairments in both physical growth, particularly body length, and neurodevelopment.

The Sources, Structures and Cytotoxicity of Animal-Derived Bisindole Compounds.

Bisindole compounds constitute a significant class of natural compounds distinguished by their characteristic bisindole structure and renowned for their anticancer properties. Over the past four decades, researchers have isolated 229 animal-derived bisindole compounds (ADBCs) from various animals. These compounds demonstrate a wide range of pharmacological properties, including cytotoxicity, antibacterial, antifungal, antiviral, and other activities. Notably, among these activities, cytotoxicity emerges as the most prominent characteristic of ADBCs. This review also summarizes the structureactivity relationship (SAR) studies associated with the cytotoxicity of these compounds and explores the druggability of these compounds. In summary, our objective is to provide an overview of the research progress concerning ADBCs, with the aim of fostering their continued development and utilization.

Revealing the Intrinsic Correlation between Cu Scales and Free Radical Chain Reactions in the Regulation of Catalytic Behaviour.

Defining the copper-based catalysts that are responsible for the catalytic behaviour of oil-paper insulation systems and implementing effective regulation are of great significance. Accelerated ageing experiments were conducted to reveal variations in copper scales and deterioration in insulation properties. As ageing progressed, TEM images demonstrated that copper species were adsorbed and aggregated on the fibre surface in the form of nanoparticles (NPs). The scale of NPs exhibited a continuous increase, from 27.06 nm to 94.19 nm. Cu(I) and Cu(II) species were identified as the active sites for inducing intense free radical reactions, which significantly reduced the activation energy, making the insulating oil more susceptible to oxidation. The role of the antioxidant di-tert-butyl-p-cresol (DBPC) in extending the insulation life was regulated by determining the optimal addition time based on variations in the interfacial tension. After the second addition of DBPC, the ageing rates of the dissipation factor, acidity, micro-water and breakdown voltage in the Cu+DBPC group decreased by 28.8%, 43.2%, 52.9% and 46.7%, respectively, compared to the Cu group. This finding not only demonstrates the crucial role of DBPC in preventing the copper-based catalyst-induced oxidation of insulating oil, but also furnishes a vital foundation for enhancing the long-term stability of transformer insulation systems.

Fully Aromatic Self-Assembled Hole-Selective Layer toward Efficient Inverted Wide-Bandgap Perovskite Solar Cells with Ultraviolet Resistance.

Ultraviolet-induced degradation has emerged as a critical stability concern impeding the widespread adoption of perovskite solar cells (PSCs), particularly in the context of phase-unstable wide-band gap perovskite films. This study introduces a novel approach by employing a fully aromatic carbazole-based self-assembled monolayer, denoted as (4-(3,6-dimethoxy-9H-carbazol-9-yl)phenyl)phosphonic acid (MeO-PhPACz), as a hole-selective layer (HSL) in inverted wide-band gap PSCs. Incorporating a conjugated linker plays a pivotal role in promoting the formation of a dense and highly ordered HSL on substrates, facilitating subsequent perovskite interfacial interactions, and fostering the growth of uniform perovskite films. The high-quality film could effectively suppress interfacial non-radiative recombination, improving hole extraction/transport efficiency. Through these advancements, the optimized wide-band gap PSCs, featuring a band gap of 1.68 eV, attain an impressive power conversion efficiency (PCE) of 21.10 %. Remarkably, MeO-PhPACz demonstrates inherent UV resistance and heightened UV absorption capabilities, substantially improving UV resistance for the targeted PSCs. This characteristic holds significance for the feasibility of large-scale outdoor applications.