Multilevel proteomics reveals host perturbations by SARS-CoV-2 and SARS-CoV.

The emergence and global spread of SARS-CoV-2 has resulted in the urgent need for an in-depth understanding of molecular functions of viral proteins and their interactions with the host proteome. Several individual omics studies have extended our knowledge of COVID-19 pathophysiology1-10. Integration of such datasets to obtain a holistic view of virus-host interactions and to define the pathogenic properties of SARS-CoV-2 is limited by the heterogeneity of the experimental systems. Here we report a concurrent multi-omics study of SARS-CoV-2 and SARS-CoV. Using state-of-the-art proteomics, we profiled the interactomes of both viruses, as well as their influence on the transcriptome, proteome, ubiquitinome and phosphoproteome of a lung-derived human cell line. Projecting these data onto the global network of cellular interactions revealed crosstalk between the perturbations taking place upon infection with SARS-CoV-2 and SARS-CoV at different levels and enabled identification of distinct and common molecular mechanisms of these closely related coronaviruses. The TGF-ß pathway, known for its involvement in tissue fibrosis, was specifically dysregulated by SARS-CoV-2 ORF8 and autophagy was specifically dysregulated by SARS-CoV-2 ORF3. The extensive dataset (available at https://covinet.innatelab.org ) highlights many hotspots that could be targeted by existing drugs and may be used to guide rational design of virus- and host-directed therapies, which we exemplify by identifying inhibitors of kinases and matrix metalloproteases with potent antiviral effects against SARS-CoV-2.

In situ NMR metrology reveals reaction mechanisms in redox flow batteries.

Large-scale energy storage is becoming increasingly critical to balancing renewable energy production and consumption1. Organic redox flow batteries, made from inexpensive and sustainable redox-active materials, are promising storage technologies that are cheaper and less environmentally hazardous than vanadium-based batteries, but they have shorter lifetimes and lower energy density2,3. Thus, fundamental insight at the molecular level is required to improve performance4,5. Here we report two in situ nuclear magnetic resonance (NMR) methods of studying redox flow batteries, which are applied to two redox-active electrolytes: 2,6-dihydroxyanthraquinone (DHAQ) and 4,4'-((9,10-anthraquinone-2,6-diyl)dioxy) dibutyrate (DBEAQ). In the first method, we monitor the changes in the 1H NMR shift of the liquid electrolyte as it flows out of the electrochemical cell. In the second method, we observe the changes that occur simultaneously in the positive and negative electrodes in the full electrochemical cell. Using the bulk magnetization changes (observed via the 1H NMR shift of the water resonance) and the line broadening of the 1H shifts of the quinone resonances as a function of the state of charge, we measure the potential differences of the two single-electron couples, identify and quantify the rate of electron transfer between the reduced and oxidized species, and determine the extent of electron delocalization of the unpaired spins over the radical anions. These NMR techniques enable electrolyte decomposition and battery self-discharge to be explored in real time, and show that DHAQ is decomposed electrochemically via a reaction that can be minimized by limiting the voltage used on charging. We foresee applications of these NMR methods in understanding a wide range of redox processes in flow and other electrochemical systems.

Transcriptional regulation of strigolactone signalling in Arabidopsis.

Plant hormones known as strigolactones control plant development and interactions between host plants and symbiotic fungi or parasitic weeds1-4. In Arabidopsis thaliana and rice, the proteins DWARF14 (D14), MORE AXILLARY GROWTH 2 (MAX2), SUPPRESSOR OF MAX2-LIKE 6, 7 and 8 (SMXL6, SMXL7 and SMXL8) and their orthologues form a complex upon strigolactone perception and play a central part in strigolactone signalling5-10. However, whether and how strigolactones activate downstream transcription remains largely unknown. Here we use a synthetic strigolactone to identify 401 strigolactone-responsive genes in Arabidopsis, and show that these plant hormones regulate shoot branching, leaf shape and anthocyanin accumulation mainly through transcriptional activation of the BRANCHED 1, TCP DOMAIN PROTEIN 1 and PRODUCTION OF ANTHOCYANIN PIGMENT 1 genes. We find that SMXL6 targets 729 genes in the Arabidopsis genome and represses the transcription of SMXL6, SMXL7 and SMXL8 by binding directly to their promoters, showing that SMXL6 serves as an autoregulated transcription factor to maintain the homeostasis of strigolactone signalling. These findings reveal an unanticipated mechanism through which a transcriptional repressor of hormone signalling can directly recognize DNA and regulate transcription in higher plants.

A pan-cancer analysis implicates human NKIRAS1 as a tumor-suppressor gene.

The NF-κB family of transcription factors and the Ras family of small GTPases are important mediators of proproliferative signaling that drives tumorigenesis and carcinogenesis. The κB-Ras proteins were previously shown to inhibit both NF-κB and Ras activation through independent mechanisms, implicating them as tumor suppressors with potentially broad relevance to human cancers. In this study, we have used two mouse models to establish the relevance of the κB-Ras proteins for tumorigenesis. Additionally, we have utilized a pan-cancer bioinformatics analysis to explore the role of the κB-Ras proteins in human cancers. Surprisingly, we find that the genes encoding κB-Ras 1 (NKIRAS1) and κB-Ras 2 (NKIRAS2) are rarely down-regulated in tumor samples with oncogenic Ras mutations. Reduced expression of human NKIRAS1 alone is associated with worse prognosis in at least four cancer types and linked to a network of genes implicated in tumorigenesis. Our findings provide direct evidence that loss of NKIRAS1 in human tumors that do not carry oncogenic RAS mutations is associated with worse clinical outcomes.

Loss of function of SSIIIa and SSIIIb coordinately confers high RS content in cooked rice.

The sedentary lifestyle and refined food consumption significantly lead to obesity, type 2 diabetes, and related complications, which have become one of the major threats to global health. This incidence could be potentially reduced by daily foods rich in resistant starch (RS). However, it remains a challenge to breed high-RS rice varieties. Here, we reported a high-RS mutant rs4 with an RS content of ~10.8% in cooked rice. The genetic study revealed that the loss-of-function SSIIIb and SSIIIa together with a strong Wx allele in the background collaboratively contributed to the high-RS phenotype of the rs4 mutant. The increased RS contents in ssIIIa and ssIIIa ssIIIb mutants were associated with the increased amylose and lipid contents. SSIIIb and SSIIIa proteins were functionally redundant, whereas SSIIIb mainly functioned in leaves and SSIIIa largely in endosperm owing to their divergent tissue-specific expression patterns. Furthermore, we found that SSIII experienced duplication in different cereals, of which one SSIII paralog was mainly expressed in leaves and another in the endosperm. SSII but not SSIV showed a similar evolutionary pattern to SSIII. The copies of endosperm-expressed SSIII and SSII were associated with high total starch contents and low RS levels in the seeds of tested cereals, compared with low starch contents and high RS levels in tested dicots. These results provided critical genetic resources for breeding high-RS rice cultivars, and the evolutionary features of these genes may facilitate to generate high-RS varieties in different cereals.

Hierarchical joint analysis of marginal summary statistics-Part I: Multipopulation fine mapping and credible set construction.

Recent advancement in genome-wide association studies (GWAS) comes from not only increasingly larger sample sizes but also the shift in focus towards underrepresented populations. Multipopulation GWAS increase power to detect novel risk variants and improve fine-mapping resolution by leveraging evidence and differences in linkage disequilibrium (LD) from diverse populations. Here, we expand upon our previous approach for single-population fine-mapping through Joint Analysis of Marginal SNP Effects (JAM) to a multipopulation analysis (mJAM). Under the assumption that true causal variants are common across studies, we implement a hierarchical model framework that conditions on multiple SNPs while explicitly incorporating the different LD structures across populations. The mJAM framework can be used to first select index variants using the mJAM likelihood with different feature selection approaches. In addition, we present a novel approach leveraging the ideas of mediation to construct credible sets for these index variants. Construction of such credible sets can be performed given any existing index variants. We illustrate the implementation of the mJAM likelihood through two implementations: mJAM-SuSiE (a Bayesian approach) and mJAM-Forward selection. Through simulation studies based on realistic effect sizes and levels of LD, we demonstrated that mJAM performs well for constructing concise credible sets that include the underlying causal variants. In real data examples taken from the most recent multipopulation prostate cancer GWAS, we showed several practical advantages of mJAM over other existing multipopulation methods.

Clonal hematopoiesis and risk of prostate cancer in large samples of European ancestry men.

Little is known regarding the potential relationship between clonal hematopoiesis (CH) of indeterminate potential (CHIP), which is the expansion of hematopoietic stem cells with somatic mutations, and risk of prostate cancer, the fifth leading cause of cancer death of men worldwide. We evaluated the association of age-related CHIP with overall and aggressive prostate cancer risk in two large whole-exome sequencing studies of 75 047 European ancestry men, including 7663 prostate cancer cases, 2770 of which had aggressive disease, and 3266 men carrying CHIP variants. We found that CHIP, defined by over 50 CHIP genes individually and in aggregate, was not significantly associated with overall (aggregate HR = 0.93, 95% CI = 0.76-1.13, P = 0.46) or aggressive (aggregate OR = 1.14, 95% CI = 0.92-1.41, P = 0.22) prostate cancer risk. CHIP was weakly associated with genetic risk of overall prostate cancer, measured using a polygenic risk score (OR = 1.05 per unit increase, 95% CI = 1.01-1.10, P = 0.01). CHIP was not significantly associated with carrying pathogenic/likely pathogenic/deleterious variants in DNA repair genes, which have previously been found to be associated with aggressive prostate cancer. While findings from this study suggest that CHIP is likely not a risk factor for prostate cancer, it will be important to investigate other types of CH in association with prostate cancer risk.

InClust+: the deep generative framework with mask modules for multimodal data integration, imputation, and cross-modal generation.

BACKGROUND: With the development of single-cell technology, many cell traits can be measured. Furthermore, the multi-omics profiling technology could jointly measure two or more traits in a single cell simultaneously. In order to process the various data accumulated rapidly, computational methods for multimodal data integration are needed. RESULTS: Here, we present inClust+, a deep generative framework for the multi-omics. It's built on previous inClust that is specific for transcriptome data, and augmented with two mask modules designed for multimodal data processing: an input-mask module in front of the encoder and an output-mask module behind the decoder. InClust+ was first used to integrate scRNA-seq and MERFISH data from similar cell populations, and to impute MERFISH data based on scRNA-seq data. Then, inClust+ was shown to have the capability to integrate the multimodal data (e.g. tri-modal data with gene expression, chromatin accessibility and protein abundance) with batch effect. Finally, inClust+ was used to integrate an unlabeled monomodal scRNA-seq dataset and two labeled multimodal CITE-seq datasets, transfer labels from CITE-seq datasets to scRNA-seq dataset, and generate the missing modality of protein abundance in monomodal scRNA-seq data. In the above examples, the performance of inClust+ is better than or comparable to the most recent tools in the corresponding task. CONCLUSIONS: The inClust+ is a suitable framework for handling multimodal data. Meanwhile, the successful implementation of mask in inClust+ means that it can be applied to other deep learning methods with similar encoder-decoder architecture to broaden the application scope of these models.

Hemodynamic Impairment of Blood Pressure and Stroke Mechanisms in Symptomatic Intracranial Atherosclerotic Stenosis.

BACKGROUND: Hemodynamic impairment of blood pressure may play a crucial role in determining the mechanisms of stroke in symptomatic intracranial atherosclerotic stenosis). We aimed to elucidate this issue and assess the impacts of modifications to blood pressure on hemodynamic impairment. METHODS: From the Third China National Stroke Registry III, computed fluid dynamics modeling was performed using the Newton-Krylov-Schwarz method in 339 patients with symptomatic intracranial atherosclerotic stenosis during 2015 to 2018. The major exposures were translesional systolic blood pressure (SBP) drop and poststenotic mean arterial pressure (MAP), and the major study outcomes were cortex-involved infarcts and borderzone-involved infarcts, respectively. Multivariate logistic regression models and the bootstrap resampling method were utilized, adjusting for demographics and medical histories. RESULTS: In all, 184 (54.3%) cortex-involved infarcts and 70 (20.6%) borderzone-involved infarcts were identified. In multivariate logistic model, the upper quartile of SBP drop correlated with increased cortex-involved infarcts (odds ratio, 1.92 [95% CI, 1.03-3.57]; bootstrap analysis odds ratio, 2.07 [95% CI, 1.09-3.93]), and the lower quartile of poststenotic MAP may correlate with increased borderzone-involved infarcts (odds ratio, 2.07 [95% CI, 0.95-4.51]; bootstrap analysis odds ratio, 2.38 [95% CI, 1.04-5.45]). Restricted cubic spline analysis revealed a consistent upward trajectory of the relationship between translesional SBP drop and cortex-involved infarcts, while a downward trajectory between poststenotic MAP and borderzone-involved infarcts. SBP drop correlated with poststenotic MAP negatively (rs=-0.765; P<0.001). In generating hemodynamic impairment, simulating blood pressure modifications suggested that ensuring adequate blood pressure to maintain sufficient poststenotic MAP appears preferable to the reverse approach, due to the prolonged plateau period in the association between the translesional SBP drop and cortex-involved infarcts and the relatively short plateau period characterizing the correlation between poststenotic MAP and borderzone-involved infarcts. CONCLUSIONS: This research elucidates the role of hemodynamic impairment of blood pressure in symptomatic intracranial atherosclerotic stenosis-related stroke mechanisms, underscoring the necessity to conduct hemodynamic assessments when managing blood pressure in symptomatic intracranial atherosclerotic stenosis.

Involvement of expanded cytotoxic and proinflammatory CD28null T cells in primary Sjögren's syndrome.

OBJECTIVE: The absence of CD28 is a feature of antigen-experienced, highly differentiated and aged T cells. The pathogenicity of CD28null T cells remains elusive in primary Sjögren's syndrome (pSS). Therefore, this study was performed to explore the characteristics of CD28null T cells in both peripheral blood and minor salivary glands (MSGs) of pSS patients. METHODS: pSS patients and paired healthy controls (HCs) were enrolled. The phenotype of peripheral CD28null T cells was analyzed using flow cytometry. In vitro functional assays were performed to evaluate the cytotoxic and proinflammatory effects of peripheral CD28null T cells. In addition, polychromatic immunofluorescence staining was performed to investigate infiltrating CD28null T cells in MSGs. RESULTS: A significant expansion of peripheral CD28null T cells was observed in pSS patients compared with HCs (p < 0.001), which were primarily CD8+CD28null T cells. The proportion of peripheral CD8+CD28null T cells moderately correlated with the erythrocyte sedimentation rate (r = 0.57, p < 0.01) and IgG levels (r = 0.44, p < 0.01). Peripheral CD28null T cells had stronger capacities to secrete granzyme B and perforin, but comparable capacities to secrete IFN-γ and TNF-α than their CD28+ counterparts. An abundant amount of cytotoxic and pro-inflammatory CD28null T cells was also found in MSGs. Moreover, a high expression of the chemokine receptor CXCR3 was found on peripheral and tissue-resident CD28null T cells, with its ligands CXCL9/10 abundantly present in MSGs. CONCLUSION: Increasing CD28null T cells with strong cytotoxicity and proinflammatory effects were observed in both peripheral blood and MSGs from pSS patients. The precise mechanism of action and migration still needs further investigation.

iLSGRN: inference of large-scale gene regulatory networks based on multi-model fusion.

MOTIVATION: Gene regulatory networks (GRNs) are a way of describing the interaction between genes, which contribute to revealing the different biological mechanisms in the cell. Reconstructing GRNs based on gene expression data has been a central computational problem in systems biology. However, due to the high dimensionality and non-linearity of large-scale GRNs, accurately and efficiently inferring GRNs is still a challenging task. RESULTS: In this article, we propose a new approach, iLSGRN, to reconstruct large-scale GRNs from steady-state and time-series gene expression data based on non-linear ordinary differential equations. Firstly, the regulatory gene recognition algorithm calculates the Maximal Information Coefficient between genes and excludes redundant regulatory relationships to achieve dimensionality reduction. Then, the feature fusion algorithm constructs a model leveraging the feature importance derived from XGBoost (eXtreme Gradient Boosting) and RF (Random Forest) models, which can effectively train the non-linear ordinary differential equations model of GRNs and improve the accuracy and stability of the inference algorithm. The extensive experiments on different scale datasets show that our method makes sensible improvement compared with the state-of-the-art methods. Furthermore, we perform cross-validation experiments on the real gene datasets to validate the robustness and effectiveness of the proposed method. AVAILABILITY AND IMPLEMENTATION: The proposed method is written in the Python language, and is available at: https://github.com/lab319/iLSGRN.

Angiographic microvascular resistance in patients with obstructive hypertrophic cardiomyopathy.

BACKGROUND: Coronary microvascular dysfunction (CMD) is an important feature of obstructive hypertrophic cardiomyopathy (oHCM). Angiographic microvascular resistance (AMR) offers a potent means for assessing CMD. This study sought to evaluate the prognostic value of CMD burden calculated by AMR among oHCM patients. METHODS: We retrospectively screened all patients diagnosed with oHCM from Fuwai Hospital between January 2017 and November 2021. Off-line AMR assessments were performed for all 3 major coronary vessels by the independent imaging core laboratory. Patients were followed every 6 months post discharge via office visit or telephone contacts. The primary outcome was major adverse cardiovascular events (MACE), including all-cause death, and unplanned rehospitalization for heart failure. RESULTS: A total of 342 patients presented with oHCM diseases enrolled in the present analyses. Mean age was 49.7, 57.6 % were men, mean 3-vessel AMR was 6.9. At a median follow-up of 18 months, high capability of 3-vessel AMR in predicting MACE was identified (AUC: 0.70) with the best cut-off value of 7.04. The primary endpoint of MACE was significantly higher in high microvascular resistance group (3-vessel AMR ≥ 7.04) as compared with low microvascular resistance group (56.5 % vs. 16.5 %; HR: 5.13; 95 % CI: 2.46-10.7; p < 0.001), which was mainly driven by the significantly higher risk of heart failure events in high microvascular resistance group. Additionally, 3-vessel AMR (HR: 4.37; 95 % CI: 1.99-9.58; p < 0.001), and age (per 1 year increase, HR: 1.03; 95 % CI: 1.01-1.06; p = 0.02) were independently associated with MACE. CONCLUSION: The present retrospective study demonstrated that the novel angiography-based AMR was a useful tool for CMD evaluation among patients with oHCM. High microvascular resistance as identified by 3-vessel AMR (≥7.04) was associated with worse prognosis.

The Epidemiology of Dermatofibrosarcoma Protuberans Incidence, Metastasis, and Death Among Various Population Groups: A SEER Database Analysis.

BACKGROUND: Limited information exists regarding the epidemiology, metastasis, and survival of dermatofibrosarcoma protuberans (DFSP). OBJECTIVE: To measure DFSP incidence and assess metastasis and survival outcomes. METHODS: Incidence rate, overall and DFSP-specific survival outcomes for primary DFSP tumors contained in the Surveillance, Epidemiology, and End Results registry (SEER) were analyzed via quasi-poisson regression, Cox and competing risk analyses. RESULTS: DFSP incidence rate was 6.25 (95%CI, 5.93-6.57) cases per million person-years with significantly higher incidence observed among Black individuals than White individuals (8.74 vs 4.53). DSFP with larger tumor size (≥3 cm, Odds ratio,OR,2.24,95%CI,1.62-3.12,p <0.001) and tumors located on the head and neck (OR: 4.88, 95%CI, 3.31-7.18, p<0.001), and genitalia OR:3.16,95%CI:1.17-8.52, p value=0.023) were associated with significantly increased risk of metastasis whereas higher socioeconomic status (SES) was associated with significantly decreased risk of metastasis. Larger tumor size (≥3 cm), regardless of location, and age (≥60) were associated with significantly worse overall and cancer-specific survival. LIMITATIONS: Retrospective design of SEER CONCLUSION: DFSP incidence is 2-fold higher among Black than White individuals. The risk of DFSP metastasis is significantly increased with tumor size ≥3 cm and tumors located on head and neck, and genitalia. Larger tumor size (≥ 3cm), regardless of location, and age (≥60) are the most important prognostic indicators for survival.

Antimicrobial and Anti-inflammatory Cyclic Tetrapeptides from the Co-cultures of Two Marine-Derived Fungi.

Violaceotides B-E (1-4), four new cyclic tetrapeptides, along with seven known compounds, were identified from the sponge-associated Aspergillus insulicola IMB18-072 co-cultivated with the marine-derived Alternaria angustiovoidea IMB20-805. Their structures were elucidated by extensive analysis of spectroscopic data, including HRESIMS, 1D and 2D NMR, and MS/MS data. The absolute configurations were determined by the advanced Marfey's method. Compounds 2, 3, and violaceotide A (5) displayed selective antimicrobial activities against the aquatic pathogenic bacteria Edwardsiella tarda and E. ictaluri. In addition, compounds 1-5 showed inhibitory activities against the LPS-induced expression of the inflammatory mediator IL-6 in RAW264.7 cells at a concentration of 10 µM.

Dual-loaded nano pesticide system based on industrial grade scaleable carrier materials with combinatory efficacy and improved safety.

Repeated and widespread use of single chemical pesticides raises concerns about efficiency and safety, developing multi-component synergistic pesticides provides a new route for efficient control of diseases. Most commercial compound formulations are open systems with non-adjustable released rates, resulting in a high frequency of applications. Meanwhile, although nano pesticide delivery systems constructed with different carrier materials have been extensively studied, realizing their actual scale-up production still has important practical significance due to the large-scale field application. In this study, a boscalid and pyraclostrobin dual-loaded nano pesticide system (BPDN) was constructed with industrial-grade carrier materials to facilitate the realization of large-scale production. The optimal industrial-scale preparation mechanism of BPDN was studied with surfactants as key factors. When agricultural emulsifier No.600 and polycarboxylate are used as the ratio of 1:2 in the preparation process, the BPDN has a spherical structure with an average size of 270 nm and exhibits superior physical stability. Compared with commercial formulation, BPDN maintains rate-stabilized release up to 5 times longer, exhibits better dispersion and spreading performance on foliar, has more than 20% higher deposition amounts, and reduces loss. A single application of BPDN could efficiently control tomato gray mold during the growing period of tomatoes due to extended duration and combinatory effectiveness, reducing two application times and labor costs. Toxicology tests on various objects systematically demonstrated that BPDN has improved safety for HepG2 cells, and nontarget organism earthworms. This research provides insight into creating safe, efficient, and environmentally friendly pesticide production to reduce manual operation times and labor costs. Accompanied by production strategies that can be easily scaled up industrially, this contributes to the efficient use of resources for sustainable agriculture.

Comparison of lung ultrasound assisted by artificial intelligence to radiology examination in pneumothorax.

BACKGROUND: Lung ultrasound can evaluate for pneumothorax but the accuracy of diagnosis depends on experience among physicians. This study aimed to investigate the sensitivity and specificity of intelligent lung ultrasound in comparison with chest x-ray, employing chest computed tomography (CT) as the gold standard for diagnosis of pneumothorax in critical ill patients. METHODS: This prospective, observational study included 75 dyspnea patients admitted to the Intensive Care Unit of the Fourth Affiliated Hospital of Soochow University from January 2021 to April 2023. Lung ultrasound images were collected using BLUE-plus protocol and analyzed by artificial intelligence software to identify the pleural line, with CT results serving as the gold standard for diagnosis. Pneumothorax was diagnosed based on either the disappearance of pleural slip sign or identification of lung point. Additionally, chest x-ray images and diagnostic results were also obtained during the same period for comparison. RESULTS: The sensitivity and specificity of intelligent lung ultrasound in diagnosing pneumothorax were 79.4% and 85.4%, respectively. The sensitivity and specificity of x-ray diagnosis were 82.4% and 80.5%. Additionally, the diagnostic time for lung ultrasound was significantly shorter than that for x-ray examination. CONCLUSION: Intelligent lung ultrasound has diagnostic efficiency comparable to that of x-ray examination but offers advantages in terms of speed.

Network pharmacology analysis and experimental verification of the antitumor effect and molecular mechanism of isocryptomerin on HepG2 cells.

Isocryptomerin (ISO) is a flavonoid isolated from the natural medicine Selaginellae Herba, which has various pharmacological activities. This study investigated the antitumor effect and underlying molecular mechanism of ISO on hepatocellular carcinoma (HCC) HepG2 cells. The cell viability assay revealed that ISO has a considerable killing effect on HCC cell lines. The apoptosis assay showed that ISO induced mitochondria-dependent apoptosis through the Bad/cyto-c/cleaved (cle)-caspase-3/cleaved (cle)-PARP pathway. The network pharmacological analysis found 13 key target genes, and epidermal growth factor receptor (EGFR), AKT, mitogen-activated protein kinase (MAPK), and reactive oxygen species (ROS) signaling pathways were strongly associated with ISO against HCC. Further verification of the results showed that ISO induced apoptosis by increasing p-p38 and p-JNK expression and decreasing p-EGFR, p-SRC, p-ERK, and p-STAT3 expression. Furthermore, ISO induced G0/G1 phase arrest by downregulating p-AKT, Cyclin D, and CDK 4 expression and upregulating p21 and p27 expression in HepG2 cells. Moreover, ISO inhibited HepG2 cell migration by decreasing p-GSK-3ß, ß-catenin, and N-cadherin expression and increasing E-cadherin expression. Additionally, ISO promoted ROS accumulation in HepG2 cells, and ISO-induced apoptosis, arrest cell cycle, and inhibition of migration were reversed by an ROS scavenger, N-acetyl- l-cysteine. Overall, ISO induced cell apoptosis and cell cycle arrest and inhibited cell migration by ROS-mediated EGFR, AKT, and MAPK signaling pathways in HepG2 cells.

Sagittal en bloc resection of thoracolumbar tumours: a report of thirty one cases.

PURPOSE: To develop a novel classification of sagittal en bloc resection (SEBR) based on anatomical locations for thoracolumbar spine tumors and assess the clinical outcomes of this surgical procedure. METHODS: 31 patients with thoracolumbar tumours treated with SEBR were enrolled in this study. The individualized surgical strategy was adopted based on our surgical classification. Demographics, perioperative outcomes, complications and postoperative outcomes were assessed. RESULTS: Based on our surgical classifications, patients were divided into four types. All bony resection margins were negative, wide resection was achieved in 25 patients, marginal resection in four, and intralesional resection in two. 18 patients underwent anterior reconstruction. Complications were encountered in five patients, and instrumentation failure occurred in one patient. The median follow-up was 24 (range, 6-72) months and recurrence was found in only one patient. CONCLUSION: SEBR is a safe and effective surgical procedure for patients with thoracolumbar spinal tumours in specific anatomical locations. The proposed surgical classification covers all SEBR types and is easy to apply, it may assist surgical decision-making in patients with spinal tumours.

The key to sustainability: In-depth investigation of environmental quality in G20 countries through the lens of renewable energy, economic complexity and geopolitical risk resilience.

The world is currently facing urgent climate and environmental issues, such as global warming, ecosystem collapse, and energy shortages. In this context, this study selected data from 2000 to 2021 and employed the Method of Moment Quantile Regression (MMQR) to thoroughly investigate the impact of renewable energy consumption, economic complexity, and geopolitical risks on the ecological footprint of the Group of Twenty (G20) countries. The results indicate that in countries with lower quantiles, renewable energy consumption significantly reduces the ecological footprint, whereas its effect is not prominent in countries with higher quantiles. Economic complexity has a negative impact on the ecological footprint, and this impact becomes stronger as the quantile of the ecological footprint rises. Additionally, economic complexity moderates the effect of renewable energy on the ecological footprint. Geopolitical risks facilitate the growth of the ecological footprint. Likewise, robustness tests such as DOLS, FMOLS, and quantile regression confirm these estimates in the same framework. This study has conducted a profound analysis of global environmental issues, offering innovative perspectives and recommendations for achieving goals related to sustainable energy utilization, mitigating climate change, and improving the ecological environment. The findings of this research will guide policymakers in G20 countries to adopt more effective environmental protection measures, thereby contributing to the construction of a sustainable future.

A novel framework for high resolution air quality index prediction with interpretable artificial intelligence and uncertainties estimation.

Accurate air quality index (AQI) prediction is essential in environmental monitoring and management. Given that previous studies neglect the importance of uncertainty estimation and the necessity of constraining the output during prediction, we proposed a new hybrid model, namely TMSSICX, to forecast the AQI of multiple cities. Firstly, time-varying filtered based empirical mode decomposition (TVFEMD) was adopted to decompose the AQI sequence into multiple internal mode functions (IMF) components. Secondly, multi-scale fuzzy entropy (MFE) was applied to evaluate the complexity of each IMF component and clustered them into high and low-frequency portions. In addition, the high-frequency portion was secondarily decomposed by successive variational mode decomposition (SVMD) to reduce volatility. Then, six air pollutant concentrations, namely CO, SO2, PM2.5, PM10, O3, and NO2, were used as inputs. The secondary decomposition and preliminary portion were employed as the outputs for the bidirectional long short-term memory network optimized by the snake optimization algorithm (SOABiLSTM) and improved Catboost (ICatboost), respectively. Furthermore, extreme gradient boosting (XGBoost) was applied to ensemble each predicted sub-model to acquire the consequence. Ultimately, we introduced adaptive kernel density estimation (AKDE) for interval estimation. The empirical outcome indicated the TMSSICX model achieved the best performance among the other 23 models across all datasets. Moreover, implementing the XGBoost to ensemble each predicted sub-model led to an 8.73%, 8.94%, and 0.19% reduction in RMSE, compared to SVM. Additionally, by utilizing SHapley Additive exPlanations (SHAP) to assess the impact of the six pollutant concentrations on AQI, the results reveal that PM2.5 and PM10 had the most notable positive effects on the long-term trend of AQI. We hope this model can provide guidance for air quality management.