A New Methodology for High Spatiotemporal Resolution Measurements of Air Volatile Organic Compounds: From Sampling to Data Deconvolution.

Monitoring of volatile organic compounds (VOCs) in air is crucial for understanding their atmospheric impacts and advancing their emission reduction plans. This study presents an innovative integrated methodology suitable for achieving semireal-time high spatiotemporal resolution three-dimensional measurements of VOCs from ground to hundreds of meters above ground. The methodology integrates an active AirCore sampler, custom-designed for deployment from unmanned aerial vehicles (UAV), a proton-transfer-reaction mass spectrometry (PTR-MS) for sample analysis, and a data deconvolution algorithm for improved time resolution for measurements of multiple VOCs in air. The application of the deconvolution technique significantly improves the signal strength of data from PTR-MS analysis of AirCore samples and enhances their temporal resolution by 4 to 8 times to 4-11 s. A case study demonstrates that the methodology can achieve sample collection and analysis of VOCs within 45 min, resulting in >120-360 spatially resolved data points for each VOC measured and achieving a horizontal resolution of 20-55 m at a UAV flight speed of 5 m/s and a vertical resolution of 5 m. This methodology presents new possibilities for acquiring 3-dimensional spatial distributions of VOC concentrations, effectively tackling the longstanding challenge of characterizing three-dimensional VOC distributions in the lowest portion of the atmospheric boundary layer.

Quantification of Methane Emissions from Cold Heavy Oil Production with Sand Extraction in Alberta and Saskatchewan, Canada.

Cold heavy oil production with sand (CHOPS) is an extraction process for heavy oil in Canada, with the potential to lead to higher CH4 venting than conventional oil sites, that have not been adequately characterized. In order to quantify CH4 emissions from CHOPS activities, a focused aerial measurement campaign was conducted in the Canadian provinces of Alberta and Saskatchewan in June 2018. Total CH4 emissions from each of 10 clusters of CHOPS wells (containing 22-167 well sites per cluster) were derived using a mass balance computation algorithm that uses in situ wind data measurement on board aircraft. Results show that there is no statistically significant difference in CH4 emissions from CHOPS wells between the two provinces. Cluster-aggregated emission factors (EF) were determined using correspondingly aggregated production volumes. The average CH4 EF was 70.4 ± 36.9 kg/m3 produced oil for the Alberta wells and 55.1 ± 13.7 kg/m3 produced oil for the Saskatchewan wells. Using these EF and heavy oil production volumes reported to provincial regulators, the annual CH4 emissions from CHOPS were estimated to be 121% larger than CHOPS emissions extracted from Canada's National Inventory Report (NIR) for Saskatchewan. The EF were found to be positively correlated with the percentage of nonpiped production volumes in each cluster, indicating higher emissions for nonpiped wells while suggesting an avenue for methane emission reductions. A comparison with recent measurements indicates relatively limited effectiveness of regulations for Saskatchewan compared to those in Alberta. The results of this study indicate the substantial contribution of CHOPS operations to the underreporting observed in the NIR and provide measurement-based EF that can be used to develop improved emissions inventories for this sector and mitigate CH4 emissions from CHOPS operations.

Distinct patterns of electrophysiologic-neuroimaging correlations between Parkinson's disease and multiple system atrophy.

Due to a high degree of symptom overlap in the early stages, with movement disorders predominating, Parkinson's disease (PD) and multiple system atrophy (MSA) may exhibit a similar decline in motor areas, yet they differ in their spread throughout the brain, ultimately resulting in two distinct diseases. Drawing upon neuroimaging analyses and altered motor cortex excitability, potential diffusion mechanisms were delved into, and comparisons of correlations across distinct disease groups were conducted in a bid to uncover significant pathological disparities. We recruited thirty-five PD, thirty-seven MSA, and twenty-eight matched controls to conduct clinical assessments, electromyographic recording, and magnetic resonance imaging scanning during the "on medication" state. Patients with neurodegeneration displayed a widespread decrease in electrophysiology in bilateral M1. Brain function in early PD was still in the self-compensatory phase and there was no significant change. MSA patients demonstrated an increase in intra-hemispheric function coupled with a decrease in diffusivity, indicating a reduction in the spread of neural signals. The level of resting motor threshold in healthy aged showed broad correlations with both clinical manifestations and brain circuits related to left M1, which was absent in disease states. Besides, ICF exhibited distinct correlations with functional connections between right M1 and left middle temporal gyrus in all groups. The present study identified subtle differences in the functioning of PD and MSA related to bilateral M1. By combining clinical information, cortical excitability, and neuroimaging intuitively, we attempt to bring light on the potential mechanisms that may underlie the development of neurodegenerative disease.

Pharmacological mechanism of natural antidepressants: The role of mitochondrial quality control.

BACKGROUND: Depression is a mental illness characterized by persistent sadness and a reduced capacity for pleasure. In clinical practice, SSRIs and other medications are commonly used for therapy, despite their various side effects. Natural products present distinct advantages, including synergistic interactions among multiple components and targeting multiple pathways, suggesting their tremendous potential in depression treatment. Imbalance in mitochondrial quality control (MQC) plays a significant role in the pathology of depression, emphasizing the importance of regulating MQC as a potential intervention strategy in addressing the onset and progression of depression. However, the role and mechanism through which natural products regulate MQC in depression treatments still need to be comprehensively elucidated, particularly in clinical and preclinical settings. PURPOSE: This review was aimed to summarize the findings of recent studies and outline the pharmacological mechanisms by which natural products modulate MQC to exert antidepressant effects. Additionally, it evaluated current research limitations and proposed new strategies for future preclinical and clinical applications in the depression domain. METHODS: To study the main pharmacological mechanisms underlying the regulation of MQC by natural products in the treatment of depression, we conducted a thorough search across databases such as PubMed, Web of Science, and ScienceDirect databases to classify and summarize the relationship between MQC and depression, as well as the regulatory mechanisms of natural products. RESULTS: Numerous studies have shown that irregularities in the MQC system play an important role in the pathology of depression, and the regulation of the MQC system is involved in antidepressant treatments. Natural products mainly regulate the MQC system to induce antidepressant effects by alleviating oxidative stress, balancing ATP levels, promoting mitophagy, maintaining calcium homeostasis, optimizing mitochondrial dynamics, regulating mitochondrial membrane potential, and enhancing mitochondrial biogenesis. CONCLUSIONS: We comprehensively summarized the regulation of natural products on the MQC system in antidepressants, providing a unique perspective for the application of natural products within antidepressant therapy. However, extensive efforts are imperative in clinical and preclinical investigations to delve deeper into the mechanisms underlying how antidepressant medications impact MQC, which is crucial for the development of effective antidepressant treatments.

Therapeutic potential of esculetin in various cancer types (Review).

Esculetin (Esc), a coumarin derivative and herbal medicinal compound used in traditional Chinese medicine, is extracted from Fraxinus chinensis. Esc has shown notable potential in the inhibition of proliferation, metastasis and cell cycle arrest in various cancer cell lines. The present review is based on research articles regarding Esc in the field of carcinoma, published between 2009 and 2023. These studies have unanimously demonstrated that Esc can effectively inhibit cancer cell proliferation through diverse mechanisms and modulate multiple signaling pathways, such as Wnt/ß-catenin, PI3K/Akt, MAPK and janus kinase/signal transducer and activator of transcription-3. In addition, the safety profile of Esc has been demonstrated in credible animal experiments, which has indicated Esc as an effective compound. Furthermore, the combination therapy of Esc with commonly used chemotherapeutic drugs holds great promise. The aim of the present review was to encourage further studies and applications of Esc in cancer therapy.

A Metastatic Cancer Expression Generator (MetGen): A Generative Contrastive Learning Framework for Metastatic Cancer Generation.

Despite significant advances in tumor biology and clinical therapeutics, metastasis remains the primary cause of cancer-related deaths. While RNA-seq technology has been used extensively to study metastatic cancer characteristics, challenges persist in acquiring adequate transcriptomic data. To overcome this challenge, we propose MetGen, a generative contrastive learning tool based on a deep learning model. MetGen generates synthetic metastatic cancer expression profiles using primary cancer and normal tissue expression data. Our results demonstrate that MetGen generates comparable samples to actual metastatic cancer samples, and the cancer and tissue classification yields performance rates of 99.8 ± 0.2% and 95.0 ± 2.3%, respectively. A benchmark analysis suggests that the proposed model outperforms traditional generative models such as the variational autoencoder. In metastatic subtype classification, our generated samples show 97.6% predicting power compared to true metastatic samples. Additionally, we demonstrate MetGen's interpretability using metastatic prostate cancer and metastatic breast cancer. MetGen has learned highly relevant signatures in cancer, tissue, and tumor microenvironments, such as immune responses and the metastasis process, which can potentially foster a more comprehensive understanding of metastatic cancer biology. The development of MetGen represents a significant step toward the study of metastatic cancer biology by providing a generative model that identifies candidate therapeutic targets for the treatment of metastatic cancer.

FvMbp1-Swi6 complex regulates vegetative growth, stress tolerance, and virulence in Fusarium verticillioides.

The mycotoxigenic fungus Fusarium verticillioides is a common pathogen of grain and medicine that contaminates the host with fumonisin B1 (FB1) mycotoxin, poses serious threats to human and animal health. Therefore, it is crucial to unravel the regulatory mechanisms of growth, and pathogenicity of F. verticillioides. Mbp1 is a component of the MluI cell cycle box binding factor complex and acts as an APSES-type transcription factor that regulates cell cycle progression. However, no information is available regarding its role in F. verticillioides. In this study, we demonstrate that FvMbp1 interacts with FvSwi6 that acts as the cell cycle transcription factor, to form the heteromeric transcription factor complexes in F. verticillioides. Our results show that ΔFvMbp1 and ΔFvSwi6 both cause a severe reduction of vegetative growth, conidiation, and increase tolerance to diverse environmental stresses. Moreover, ΔFvMbp1 and ΔFvSwi6 dramatically decrease the virulence of the pathogen on the stalk and ear of maize. Transcriptome profiling show that FvMbp1-Swi6 complex co-regulates the expression of genes associated with multiple stress responses. These results indicate the functional importance of the FvMbp1-Swi6 complex in the filamentous fungi F. verticillioides and reveal a potential target for the effective prevention and control of Fusarium diseases.

Understanding YTHDF2-mediated mRNA degradation by m6A-BERT-Deg.

N6-methyladenosine (m6A) is the most abundant mRNA modification within mammalian cells, holding pivotal significance in the regulation of mRNA stability, translation and splicing. Furthermore, it plays a critical role in the regulation of RNA degradation by primarily recruiting the YTHDF2 reader protein. However, the selective regulation of mRNA decay of the m6A-methylated mRNA through YTHDF2 binding is poorly understood. To improve our understanding, we developed m6A-BERT-Deg, a BERT model adapted for predicting YTHDF2-mediated degradation of m6A-methylated mRNAs. We meticulously assembled a high-quality training dataset by integrating multiple data sources for the HeLa cell line. To overcome the limitation of small training samples, we employed a pre-training-fine-tuning strategy by first performing a self-supervised pre-training of the model on 427 760 unlabeled m6A site sequences. The test results demonstrated the importance of this pre-training strategy in enabling m6A-BERT-Deg to outperform other benchmark models. We further conducted a comprehensive model interpretation and revealed a surprising finding that the presence of co-factors in proximity to m6A sites may disrupt YTHDF2-mediated mRNA degradation, subsequently enhancing mRNA stability. We also extended our analyses to the HEK293 cell line, shedding light on the context-dependent YTHDF2-mediated mRNA degradation.

Liquid-liquid phase separation of H3K27me3 reader BP1 regulates transcriptional repression.

BACKGROUND: Bromo-adjacent homology-plant homeodomain domain containing protein 1 (BP1) is a reader of histone post-translational modifications in fungi. BP1 recognizes trimethylation of lysine 27 in histone H3 (H3K27me3), an epigenetic hallmark of gene silencing. However, whether and how BP1 participates in transcriptional repression remains poorly understood. RESULTS: We report that BP1 forms phase-separated liquid condensates to modulate its biological function in Fusarium graminearum. Deletion assays reveal that intrinsically disordered region 2 (IDR2) of BP1 mediates its liquid-liquid phase separation. The phase separation of BP1 is indispensable for its interaction with suppressor of Zeste 12, a component of polycomb repressive complex 2. Furthermore, IDR2 deletion abolishes BP1-H3K27me3 binding and alleviates the transcriptional repression of secondary metabolism-related genes, especially deoxynivalenol mycotoxin biosynthesis genes. CONCLUSIONS: BP1 maintains transcriptional repression by forming liquid-liquid phase-separated condensates, expanding our understanding of the relationship between post-translational modifications and liquid-liquid phase separation.

shinyDeepDR: A user-friendly R Shiny app for predicting anti-cancer drug response using deep learning.

Advancing precision oncology requires accurate prediction of treatment response and accessible prediction models. To this end, we present shinyDeepDR, a user-friendly implementation of our innovative deep learning model, DeepDR, for predicting anti-cancer drug sensitivity. The web tool makes DeepDR more accessible to researchers without extensive programming experience. Using shinyDeepDR, users can upload mutation and/or gene expression data from a cancer sample (cell line or tumor) and perform two main functions: "Find Drug," which predicts the sample's response to 265 approved and investigational anti-cancer compounds, and "Find Sample," which searches for cell lines in the Cancer Cell Line Encyclopedia (CCLE) and tumors in The Cancer Genome Atlas (TCGA) with genomics profiles similar to those of the query sample to study potential effective treatments. shinyDeepDR provides an interactive interface to interpret prediction results and to investigate individual compounds. In conclusion, shinyDeepDR is an intuitive and free-to-use web tool for in silico anti-cancer drug screening.

Antidepressant mechanism of traditional Chinese medicine: Involving regulation of circadian clock genes.

Numerous studies have demonstrated an intimate relationship between circadian rhythm disorders and the development and prevention of depression. The biological clock genes, which constitute the molecular basis of endogenous circadian rhythms, hold promising prospects for depression treatment. Based on an extensive review of recent domestic and international research, this article presents a comprehensive analysis of how traditional Chinese medicine (TCM) intervenes in depression by regulating circadian rhythms. The findings indicate that TCM exerts its antidepressant effects by targeting specific biological clock genes such as Bmal1, clock, Arntl, Per1, Per2, Per3, Nr1d1, Cry2, and Dbp, as well as regulating circadian rhythms of hormone secretion. However, most current research is still confined to basic experimental studies, lacking clinical double-blind control trials to further validate these viewpoints. Furthermore, there is insufficient research on the signal transduction pathway between biological clock genes and pathological changes in depression. Additionally, further clarification is needed regarding the specific targets of TCM on the biological clock genes.

reguloGPT: Harnessing GPT for Knowledge Graph Construction of Molecular Regulatory Pathways.

Motivation: Molecular Regulatory Pathways (MRPs) are crucial for understanding biological functions. Knowledge Graphs (KGs) have become vital in organizing and analyzing MRPs, providing structured representations of complex biological interactions. Current tools for mining KGs from biomedical literature are inadequate in capturing complex, hierarchical relationships and contextual information about MRPs. Large Language Models (LLMs) like GPT-4 offer a promising solution, with advanced capabilities to decipher the intricate nuances of language. However, their potential for end-to-end KG construction, particularly for MRPs, remains largely unexplored. Results: We present reguloGPT, a novel GPT-4 based in-context learning prompt, designed for the end-to-end joint name entity recognition, N-ary relationship extraction, and context predictions from a sentence that describes regulatory interactions with MRPs. Our reguloGPT approach introduces a context-aware relational graph that effectively embodies the hierarchical structure of MRPs and resolves semantic inconsistencies by embedding context directly within relational edges. We created a benchmark dataset including 400 annotated PubMed titles on N6-methyladenosine (m6A) regulations. Rigorous evaluation of reguloGPT on the benchmark dataset demonstrated marked improvement over existing algorithms. We further developed a novel G-Eval scheme, leveraging GPT-4 for annotation-free performance evaluation and demonstrated its agreement with traditional annotation-based evaluations. Utilizing reguloGPT predictions on m6A-related titles, we constructed the m6A-KG and demonstrated its utility in elucidating m6A's regulatory mechanisms in cancer phenotypes across various cancers. These results underscore reguloGPT's transformative potential for extracting biological knowledge from the literature. Availability and implementation: The source code of reguloGPT, the m6A title and benchmark datasets, and m6A-KG are available at: https://github.com/Huang-AI4Medicine-Lab/reguloGPT.

Landscape of Epstein-Barr virus gene expression and perturbations in cancer.

Epstein-Barr virus (EBV) is the causative agent for multiple neoplastic diseases of epithelial and lymphocytic origin1-3. The heterogeneity of the viral elements expressed and the mechanisms by which these coding and non-coding genes maintain cancer cell properties in vivo remain elusive4,5. Here we conducted a multi-modal transcriptomic analysis of EBV-associated neoplasms and identified that the ubiquitously expressed RPMS1 non-coding RNAs support cancer cell properties by disruption of the interferon response. Our map of EBV expression shows a variable, but pervasive expression of BNLF2 discerned from the overlapping LMP1 RNA in bulk sequencing data. Using long-read single-molecule sequencing, we identified three new viral elements within the RPMS1 gene. Furthermore, single-cell sequencing datasets allowed for the separation of cancer cells and healthy cells from the same tissue biopsy and the characterization of a microenvironment containing interferon gamma excreted by EBV-stimulated T-lymphocytes. In comparison with healthy epithelium, EBV-transformed cancer cells exhibited increased proliferation and inhibited immune response induced by the RPMS1-encoded microRNAs. Our atlas of EBV expression shows that the EBV-transformed cancer cells express high levels of non-coding RNAs originating from RPMS1 and that the oncogenic properties are maintained by RPMS1 microRNAs. Through bioinformatic disentanglement of single cells from cancer tissues we identified a positive feedback loop where EBV-activated immune cells stimulate cancer cells to proliferate, which in turn undergo viral reactivation and trigger an immune response.

GRIM-19 deficiency promotes macrophage polarization to the M1 phenotype partly through glycolysis in unexplained recurrent spontaneous abortion†.

The occurrence of unexplained recurrent spontaneous abortion (URSA) is closely related to immune system disorders, however, the underlying mechanisms remain unclear. The purpose of this study was to investigate the expression of GRIM-19 in URSA and the possible pathogenesis of URSA according to macrophage polarization. Here, we showed that GRIM-19 was downregulated in the uterine decidual macrophages of patients with URSA and that GRIM-19 downregulation was accompanied by increased M1 macrophage polarization. Furthermore, the expression levels of glycolytic enzymes were substantially enhanced in the uterine decidual macrophages of URSA patients, and glycolysis in THP-1-derived macrophages was further enhanced by the downregulation of GRIM-19. Additionally, the increase of M1 macrophages resulting from the loss of GRIM-19 was significantly reversed in cells treated with 2-deoxy-D-glucose (2-DG, an inhibitor of glycolysis). To provide more direct evidence, GRIM-19 deficiency was shown to promote macrophage polarization to the M1 phenotype in GRIM-19+/- mouse uteri. Overall, our study provides evidence that GRIM-19 deficiency may play a role in regulating macrophage polarization in URSA, and that glycolysis may participate in this process.

Understanding YTHDF2-mediated mRNA Degradation By m6A-BERT-Deg.

N6-methyladenosine (m6A) is the most abundant mRNA modification within mammalian cells, holding pivotal significance in the regulation of mRNA stability, translation, and splicing. Furthermore, it plays a critical role in the regulation of RNA degradation by primarily recruiting the YTHDF2 reader protein. However, the selective regulation of mRNA decay of the m6A-methylated mRNA through YTHDF2 binding is poorly understood. To improve our understanding, we developed m6A-BERT-Deg, a BERT model adapted for predicting YTHDF2-mediated degradation of m6A-methylated mRNAs. We meticulously assembled a high-quality training dataset by integrating multiple data sources for the HeLa cell line. To overcome the limitation of small training samples, we employed a pre-training-fine-tuning strategy by first performing a self-supervised pre-training of the model on 427,760 unlabeled m6A site sequences. The test results demonstrated the importance of this pre-training strategy in enabling m6A-BERT-Deg to outperform other benchmark models. We further conducted a comprehensive model interpretation and revealed a surprising finding that the presence of co-factors in proximity to m6A sites may disrupt YTHDF2-mediated mRNA degradation, subsequently enhancing mRNA stability. We also extended our analyses to the HEK293 cell line, shedding light on the context-dependent YTHDF2-mediated mRNA degradation.

Risk-Adapted Starting Age of Personalized Lung Cancer Screening: A Population-Based, Prospective Cohort Study in China.

BACKGROUND: The current one-size-fits-all screening strategy for lung cancer is not suitable for personalized screening. RESEARCH QUESTION: What is the risk-adapted starting age of lung cancer screening with comprehensive consideration of risk factors? STUDY DESIGN AND METHODS: The National Lung Cancer Screening program, a multicenter, population-based, prospective cohort study, was analyzed. Information on risk factor exposure was collected during the baseline risk assessment. A Cox proportional hazards model was used to estimate the association between risk factors and lung cancer incidence. Age-specific 10-year cumulative risk was calculated to determine the age at which individuals with various risk factors reached the equivalent risk level as individuals aged ≥ 50 years with active tobacco use and a ≥ 20 pack-year smoking history. RESULTS: Of the 1,031,911 participants enrolled in this study, 3,908 demonstrated lung cancer after a median follow-up of 3.8 years. We identified seven risk factors for lung cancer, including pack-years of smoking, secondhand smoke exposure, family history of lung cancer in first-degree relatives, history of respiratory diseases, occupational hazardous exposure, BMI, and diabetes. The 10-year cumulative risk of lung cancer for people aged ≥ 50 years with active tobacco use and a ≥ 20 pack-year smoking history was 1.37%, which was treated as the risk threshold for screening. Individuals who never smoked and those with active tobacco use and a < 30-pack-year history of smoking reached the equivalent risk level 1 to 14 years later compared with the starting age of 50 years. Men with active tobacco use, a ≥ 30-pack-year history of smoking, and concurrent respiratory diseases or diabetes should be screened 1 year earlier at the age of 49 years. INTERPRETATION: The personalized risk-adapted starting ages for lung cancer screening, based on the principle of equal management of equal risk, can served as an optimized screening strategy to identify high-risk individuals.

Zinc Transporters Serve as Prognostic Predictors and their Expression Correlates with Immune Cell Infiltration in Specific Cancer: A Pan-cancer Analysis.

The disruption of zinc (Zn) homeostasis has been implicated in cancer development and progression through various signaling pathways. Maintaining intracellular zinc balance is crucial in the context of cancer. Human cells rely on two families of transmembrane transporters, SLC30A/ZNT and SLC39A/ZIP, to coordinate zinc homeostasis. While some ZNTs and ZIPs have been linked to cancer progression, limited information is available regarding the expression patterns of zinc homeostasis-related genes and their potential roles in predicting prognosis and developing therapeutic strategies for specific cancers. In this study, a systematic analysis was conducted to examine the expression of all genes from the SLC30A and SLC39A families at both mRNA and protein levels across different cancers. As a result, three SLC39A genes (SLC39A1, SLC39A4, and SLC39A8) were found to be significantly dysregulated in specific cancers, including cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), liver hepatocellular carcinoma (LIHC), pancreatic adenocarcinoma (PAAD), and kidney renal papillary cell carcinoma (KIRP). Moreover, the dysregulation of these genes was tightly associated with the prognosis of patients with those cancers. Furthermore, we found that the gene SLC39A8 exhibited the lowest mutation frequency in KIRP, whereas mutations in SLC39A4 were found to significantly impact overall survival (OS), disease-free (DF), and progress-free survival (PFS) in cancer patients, particularly in those with PAAD. Additionally, immune infiltration analysis revealed that SLC39A1, SLC39A4, and SLC39A8 may function as immune regulators in cancers. This provides new insights into understanding the complex relationship between zinc homeostasis and cancer progression.

Computer-assisted microcatheter shaping for intracranial aneurysm embolization: evaluation of safety and efficacy in a multicenter randomized controlled trial.

BACKGROUND: This study aimed to evaluate the efficacy, stability, and safety of computer-assisted microcatheter shaping (CAMS) in patients with intracranial aneurysms. METHODS: A total of 201 patients with intracranial aneurysms receiving endovascular coiling therapy were continuously recruited and randomly assigned to the CAMS and manual microcatheter shaping (MMS) groups. The investigated outcomes included the first-trial success rate, time to position the microcatheter in aneurysms, rate of successful microcatheter placement within 5 min, delivery times, microcatheter stability, and delivery performance. RESULTS: The rates of first-trial success (96.0% vs 66.0%, P<0.001), successful microcatheter placement within 5 min (96.04% vs 72.00%, P<0.001), microcatheter stability (97.03% vs 84.00%, P=0.002), and 'excellent' delivery performance (45.54% vs 24.00%, P<0.001) in the CAMS group were significantly higher than those in the MMS group. Additionally, the total microcatheter delivery and positioning time (1.05 minutes (0.26) vs 1.53 minutes (1.00)) was significantly shorter in the CAMS group than in the MMS group (P<0.001). Computer assistance (OR 14.464; 95% CI 4.733 to 44.207; P<0.001) and inflow angle (OR 1.014; 95% CI 1.002 to 1.025; P=0.021) were independent predictors of the first-trial success rate. CAMS could decrease the time of microcatheter position compared with MMS, whether for junior or senior surgeons (P<0.001). Moreover, computer assistance technology may be more helpful in treating aneurysms with acute angles (p<0.001). CONCLUSIONS: The use of computer-assisted procedures can enhance the efficacy, stability, and safety of surgical plans for coiling intracranial aneurysms.

Activation of glucocorticoid receptor signaling inhibits KSHV-induced inflammation and tumorigenesis.

IMPORTANCE: Kaposi's sarcoma (KS) is the most common cancer in HIV-infected patients caused by Kaposi's sarcoma-associated herpesvirus (KSHV) infection. Hyperinflammation is the hallmark of KS. In this study, we have shown that KSHV mediates hyperinflammation by inducing IL-1α and suppressing IL-1Ra. Mechanistically, KSHV miRNAs and vFLIP induce hyperinflammation by activating the NF-κB pathway. A common anti-inflammatory agent dexamethasone blocks KSHV-induced hyperinflammation and tumorigenesis by activating glucocorticoid receptor signaling to suppress IL-1α and induce IL-1Ra. This work has identified IL-1-mediated inflammation as a potential therapeutic target and dexamethasone as a potential therapeutic agent for KSHV-induced malignancies.