New 2D Metal-Organic Monoacid Framework (MOmAF): Realization of Extreme Water Repellence.

Metal-organic frameworks (MOFs) are normally moisture-sensitive and unstable in aqueous environments, which has considerably limited their practical applications because water/moisture is ubiquitous in many industrial processes. New materials with superior water stability are, therefore, in great demand and vital to their practical applications. Here, a novel oil/water interfacial assembly strategy is demonstrated for the synthesis of a new class of metal-organic monoacid framework (MOmAF) with exceptional water stability and chemical stability. Superhydrophobic 2D sheets are synthesized at room temperature, while 1D nanotubes are obtained via the self-scrolling of their 2D sheets for the first time. In addition, a simple sequential drop-casting method is developed to coat as-synthesized MOmAF structures onto porous membranes. This can potentially open up new avenues in the design of superhydrophobic self-cleaning MOmAF materials without tedious post-synthetic modifications and usher in a new class of materials meeting industrial needs.

Predicting muscle invasion in bladder cancer by deep learning analysis of MRI: comparison with vesical imaging-reporting and data system.

OBJECTIVES: To compare the diagnostic performance of a novel deep learning (DL) method based on T2-weighted imaging with the vesical imaging-reporting and data system (VI-RADS) in predicting muscle invasion in bladder cancer (MIBC). METHODS: A total of 215 tumours (129 for training and 31 for internal validation, centre 1; 55 for external validation, centre 2) were included. MIBC was confirmed by pathological examination. VI-RADS scores were provided by two groups of radiologists (readers 1 and readers 2) independently. A deep convolutional neural network was constructed in the training set, and validation was conducted on the internal and external validation sets. ROC analysis was performed to evaluate the performance for MIBC diagnosis. RESULTS: The AUCs of the DL model, readers 1, and readers 2 were as follows: in the internal validation set, 0.963, 0.843, and 0.852, respectively; in the external validation set, 0.861, 0.808, and 0.876, respectively. The accuracy of the DL model in the tumours scored VI-RADS 2 or 3 was higher than that of radiologists in the external validation set: for readers 1, 0.886 vs. 0.600, p = 0.006; for readers 2, 0.879 vs. 0.636, p = 0.021. The average processing time (38 s and 43 s in two validation sets) of the DL method was much shorter than the readers, with a reduction of over 100 s in both validation sets. CONCLUSIONS: Compared to radiologists using VI-RADS, the DL method had a better diagnostic performance, shorter processing time, and robust generalisability, indicating good potential for diagnosing MIBC. KEY POINTS: • The DL model shows robust performance for MIBC diagnosis in both internal and external validation. • The diagnostic performance of the DL model in the tumours scored VI-RADS 2 or 3 is better than that obtained by radiologists using VI-RADS. • The DL method shows potential in the preoperative assessment of MIBC.

The role of GATA switch in benzene metabolite hydroquinone inhibiting erythroid differentiation in K562 cells.

The phenolic metabolite of benzene, hydroquinone (HQ), has potential risks for hematological disorders and hematotoxicity in humans. Previous studies have revealed that reactive oxygen species, DNA methylation, and histone acetylation participate in benzene metabolites inhibiting erythroid differentiation in hemin-induced K562 cells. GATA1 and GATA2 are crucial erythroid-specific transcription factors that exhibit dynamic expression patterns during erythroid differentiation. We investigated the role of GATA factors in HQ-inhibited erythroid differentiation in K562 cells. When K562 cells were induced with 40 µM hemin for 0-120 h, the mRNA and protein levels of GATA1 and GATA2 changed dynamically. After exposure to 40 µM HQ for 72 h, K562 cells were induced with 40 µM hemin for 48 h. HQ considerably reduced the percentage of hemin-induced Hb-positive cells, decreased the GATA1 mRNA, protein, and occupancy levels at α-globin and ß-globin gene clusters, and increased the GATA2 mRNA and protein levels significantly. ChIP-seq analysis revealed that HQ reduced GATA1 occupancy, and increased GATA2 occupancy at most gene loci in hemin-induced K562 cells. And GATA1 and GATA2 might play essential roles in the erythroid differentiation protein interaction network. These results elucidate that HQ decreases GATA1 occupancy and increases GATA2 occupancy at the erythroid gene loci, thereby downregulating GATA1 and upregulating GATA2 expression, which in turn modulates the expression of erythroid genes and inhibits erythroid differentiation. This partially explains the mechanism of benzene hematotoxicity.

Adaption of distance learning to continue the academic year amid COVID-19 lockdown.

This work investigates the use of distance learning in saving students' academic year amid COVID-19 lockdown. It assesses the adoption of distance learning using various online application tools that have gained widespread attention during the coronavirus infectious disease 2019 (COVID-19) pandemic. Distance learning thrives as a legitimate alternative to classroom instructions, as major cities around the globe are locked down amid the COVID-19 pandemic. To save the academic year, educational institutions have reacted to the situation impulsively and adopted distance learning platforms using online resources. This study surveyed random undergraduate students to identify the impact of trust in formal and informal information sources, awareness and the readiness to adopt distance learning. In this study, we have hypothesized that adopting distance learning is an outcome of situational awareness and readiness, which is achieved by the trust in the information sources related to distance learning. The findings indicate that trust in information sources such as institute and media information or interpersonal communication related to distance learning programs is correlated with awareness (ß = 0.423, t = 12.296, p = 0.000) and contribute to readiness (ß = 0.593, t = 28.762, p = 0.001). The structural model path coefficient indicates that readiness strongly influences the adoption of distance learning (ß = 0.660, t = 12.798, p = 0.000) amid the COVID-19 pandemic. Our proposed model recorded a predictive relevance (Q2) of 0.377 for awareness, 0.559 for readiness, and 0.309 for the adoption of distance learning, which explains how well the model and its parameter estimates reconstruct the values. This study concludes with implications for further research in this area.

Conventional to online education during COVID-19 pandemic: Do develop and underdeveloped nations cope alike.

BACKGROUND: Educational institutes around the globe are facing challenges of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Online learning is being carried out to avoid face to face contact in emergency scenarios such as coronavirus infectious disease 2019 (COVID-19) pandemic. Students need to adapt to new roles of learning through information technology to succeed in academics amid COVID-19. OBJECTIVE: However, access and use of online learning resources and its link with satisfaction of students amid COVID-19 are critical to explore. Therefore, in this paper, we aimed to assess and compare the access & use of online learning of Bruneians and Pakistanis amid enforced lockdown using a five-items satisfaction scale underlying existing literature. METHOD: For this, a cross-sectional study was done in the first half of June 2020 after the pandemic situation among 320 students' across Pakistan and Brunei with a pre-defined questionnaire. Data were analyzed with statistical software package for social sciences (SPSS) 2.0. RESULTS: The finding showed that there is a relationship between students' satisfaction and access & use of online learning. Outcomes of the survey suggest that Bruneian are more satisfied (50%) with the use of online learning amid lockdown as compared to Pakistanis (35.9%). Living in the Urban area as compared to a rural area is also a major factor contributing to satisfaction with the access and use of online learning for both Bruneian and Pakistanis. Moreover, previous experience with the use of online learning is observed prevalent among Bruneians (P = .000), while among friends and family is using online learning (P = .000) were encouraging factors contributed to satisfaction with the use of online learning among Pakistanis amid COVID-19. Correlation results suggest that access and use factors of online learning amid COVID-19 were positively associated with satisfaction among both populations amid COVID-19 pandemic. However, Bruneian is more satisfied with internet access (r = 0.437, P < .000) and affordability of gadgets (r = 0.577, P < .000) as compare to Pakistanis (r = 0.176, P < .050) and (r = 0.152, P < .050). CONCLUSION: The study suggested that it is crucial for the government and other policymakers worldwide to address access and use of online learning resources of their populace amid pandemic.

Benzene metabolite 1,2,4-benzenetriol changes DNA methylation and histone acetylation of erythroid-specific genes in K562 cells.

1,2,4-Benzenetriol (BT) is one of the phenolic metabolites of benzene, a general occupational hazard and ubiquitous environmental air pollutant with leukemogenic potential in humans. Previous studies have revealed that the benzene metabolites phenol and hydroquinone can inhibit hemin-induced erythroid differentiation in K562 cells. We investigated the roles of DNA methylation and histone acetylation in BT-inhibited erythroid differentiation in K562 cells. When K562 cells were treated with 0, 5, 10, 15 or 20 µM BT for 72 h, hemin-induced hemoglobin synthesis decreased in a concentration-dependent manner. Both 5-aza-2'-deoxycytidine (5-aza-CdR, DNA methyltransferase inhibitor) and trichostatin A (TSA, histone deacetylases inhibitor) could prevent 20 µM BT from inhibiting hemin-induced hemoglobin synthesis and the mRNA expression of erythroid genes. Exposure to BT changed DNA methylation levels at several CpG sites of erythroid-specific genes, as well as the acetylation of histone H3 and H4, chromatin occupancy of GATA-1 and recruitment of RNA polymerase II at α-globin and ß-globin gene clusters after hemin induction. These results demonstrated that BT could inhibit hemin-induced erythroid differentiation, where DNA methylation and histone acetylation also played important roles by down-regulating erythroid-specific genes. This partly explained the mechanisms of benzene hematotoxicity.

Role of microglia polarization induced by glucose metabolism disorder in the cognitive impairment of mice from PM2.5 exposure.

Studies have found that PM2.5 can damage the brain, accelerate cognitive impairment, and increase the risk of developing a variety of neurodegenerative diseases. However, the potential molecular mechanisms by which PM2.5 causes learning and memory problems are yet to be explored. In this study, we evaluated the neurotoxic effects in mice after 12 weeks of PM2.5 exposure, and found that this exposure resulted in learning and memory disorders, pathological brain damage, and M1 phenotype polarization on microglia, especially in the hippocampus. The severity of this damage increased with increasing PM2.5 concentration. Proteomic analysis, as well as validation results, suggested that PM2.5 exposure led to abnormal glucose metabolism in the mouse brain, which is mainly characterized by significant expression of hexokinase, phosphofructokinase, and lactate dehydrogenase. We therefore administered the glycolysis inhibitor 2-deoxy-d-glucose (2-DG) to the mice exposed to PM2.5, and showed that inhibition of glycolysis by 2-DG significantly alleviated PM2.5-induced hippocampal microglia M1 phenotype polarization, and reduced the release of inflammatory factors, improved synaptic structure and related protein expression, which alleviated the cognitive impairment induced by PM2.5 exposure. In summary, our study found that abnormal glucose metabolism-mediated inflammatory polarization of microglia played a role in learning and memory disorders in mice exposed to PM2.5. This study provides new insights into the neurotoxicity caused by PM2.5 exposure, and provides some theoretical references for the prevention and control of cognitive impairment induced by PM2.5 exposure.

A multicenter bladder cancer MRI dataset and baseline evaluation of federated learning in clinical application.

Bladder cancer (BCa), as the most common malignant tumor of the urinary system, has received significant attention in research on the clinical application of artificial intelligence algorithms. Nevertheless, it has been observed that certain investigations use data from various medical facilities to train models for BCa, which may pose a privacy risk. Given this concern, protecting patient privacy during machine learning algorithm training is a crucial aspect that requires substantial attention. One emerging machine learning paradigm that addresses this concern is federated learning (FL). FL enables multiple entities to collaboratively build machine learning models while preserving data privacy and security. In this study, we present a multicenter BCa magnetic resonance imaging (MRI) dataset. The dataset comprises 275 three-dimensional bladder T2-weighted MRI scans collected from four medical centers, and each scan includes diagnostic pathological labels for muscle invasion and pixel-level annotations of tumor contours. Four FL methods are used to assess the baseline of the dataset for both the task of diagnosing muscle-invasive bladder cancer and automatic bladder tumor lesion segmentation.

Highly-Controlled Soft-Templating Synthesis of Hollow ZIF-8 Nanospheres for Selective CO2 Separation and Storage.

Global warming is an ever-rising environmental concern, and carbon dioxide (CO2) is among its major causes. Different technologies, including adsorption, cryogenic separation, and sequestration, have been developed for CO2 separation and storage/utilization. Among these, carbon capture using nano-adsorbents has the advantages of excellent CO2 separation and storage performance as well as superior heat- and mass-transfer characteristics due to their large surface area and pore volume. In this work, an environmentally friendly, facile, bottom-up synthesis of ZIF-8 hollow nanospheres (with reduced chemical consumption) was developed for selective CO2 separation and storage. During this soft-templating synthesis, a combined effect of ultra-sonication and low-temperature hydrothermal synthesis showed better control over an oil-in-water microemulsion formation and the subsequent growth of large-surface-area hollow ZIF-8 nanospheres having excellent particle size distribution. Systematic studies on the synthesis parameters were also performed to achieve fine-tuning of the ZIF-8 crystallinity, hollow structures, and sphere size. The optimized hollow ZIF-8 nanosphere sample having uniform size distribution exhibited remarkable CO2 adsorption capability (∼2.24 mmol g-1 at 0 °C and 1.75 bar), a CO2/N2 separation selectivity of 12.15, a good CO2 storage capacity (1.5-1.75 wt %), and an excellent cyclic adsorption/desorption performance (up to four CO2 adsorption/desorption cycles) at 25 °C. In addition, the samples showed exceptional structural stability with only ∼15% of overall weight loss up to 600 °C under a nitrogen environment. Therefore, the hollow ZIF-8 nanospheres as well as their highly controlled soft-templating synthesis method reported in this work are useful in the course of the development of nanomaterials with optimized properties for future CO2 capture technologies.

Predicting muscle invasion in bladder cancer based on MRI: A comparison of radiomics, and single-task and multi-task deep learning.

BACKGROUND AND OBJECTIVES: Radiomics and deep learning are two popular technologies used to develop computer-aided detection and diagnosis schemes for analysing medical images. This study aimed to compare the effectiveness of radiomics, single-task deep learning (DL) and multi-task DL methods in predicting muscle-invasive bladder cancer (MIBC) status based on T2-weighted imaging (T2WI). METHODS: A total of 121 tumours (93 for training, from Centre 1; 28 for testing, from Centre 2) were included. MIBC was confirmed with pathological examination. A radiomics model, a single-task model, and a multi-task model based on T2WI were constructed in the training cohort with five-fold cross-validation, and validation was conducted in the external test cohort. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of each model. DeLong's test and a permutation test were used to compare the performance of the models. RESULTS: The area under the ROC curve (AUC) values of the radiomics, single-task and multi-task models in the training cohort were: 0.920, 0.933 and 0.932, respectively; and were 0.844, 0.884 and 0.932, respectively, in the test cohort. The multi-task model achieved better performance in the test cohort than did the other models. No statistically significant differences in AUC values and Kappa coefficients were observed between pairwise models, in either the training or test cohorts. According to the Grad-CAM feature visualization results, the multi-task model focused more on the diseased tissue area in some samples of the test cohort compared with the single-task model. CONCLUSIONS: The T2WI-based radiomics, single-task, and multi-task models all exhibited good diagnostic performance in preoperatively predicting MIBC, in which the multi-task model had the best diagnostic performance. Compared with the radiomics method, our multi-task DL method had the advantage of saving time and effort. Compared with the single-task DL method, our multi-task DL method had the advantage of being more lesion-focused and more reliable for clinical reference.

Predicting review helpfulness in the omnichannel retailing context: An elaboration likelihood model perspective.

As increasingly retail enterprises have adopted the omnichannel retailing strategy, both online-generated and offline-generated reviews should be considered to better understand the helpfulness of online reviews in the omnichannel retailing context. Drawing on the Elaboration Likelihood Model, the present study attempts to examine the impacts of review label volume, review content length, and review label-content relevance on review helpfulness in the omnichannel retailing context. The empirical data of 2,822 product reviews were collected from Suning.com. The results of Negative Binomial Regression showed that both central cue (review label-content relevance) and peripheral cue (review content length) positively affect review helpfulness. Specifically, the positive effect of review content length on review helpfulness will be stronger when the online review is submitted from an omnichannel retailer's online store. On the contrary, the positive effect of review label-content relevance on review helpfulness will be weaker when the online review is generated from an omnichannel retailer's online channel.

The Growth of Metal-Organic Frameworks in the Presence of Graphene Oxide: A Mini Review.

Integrated metal-organic frameworks (MOFs) with graphene oxide (GO) have aroused huge interest in recent years due to their unique properties and excellent performance compared to MOFs or GO alone. While a lot of attention has been focused on the synthesis methodologies and the performance analysis of the composite materials in recent years, the fundamental formation/crystallization mechanism(s) is (are) still not fully understood. Ascribed to the distinctive structural and functional properties of GO, the nucleation and crystallization process of MOFs could be altered/promoted, forming MOF/GO composite materials with different nanostructures. Furthermore, the MOF's parental structure could also influence how the GO and MOF bond together. Thus, this short review attempted to provide critical and indepth discussions of recent research results with a particular focus on the factors that influence the directional growth of parent MOFs in the presence of graphene oxide. Due to the unique structure and enhanced properties, the derived MOF/GO composites have a wide range of applications including gas separation, electrochemistry, and photocatalysis. We hope this review will be of interest to researchers working on MOF design, crystal structure control (e.g., orientation), and composite materials development.

Identification of potential pathways and microRNA-mRNA networks associated with benzene metabolite hydroquinone-induced hematotoxicity in human leukemia K562 cells.

BACKGROUND: Hydroquinone (HQ) is a phenolic metabolite of benzene with a potential risk for hematological disorders and hematotoxicity in humans. In the present study, an integrative analysis of microRNA (miRNA) and mRNA expressions was performed to identify potential pathways and miRNA-mRNA network associated with benzene metabolite hydroquinone-induced hematotoxicity. METHODS: K562 cells were treated with 40 µM HQ for 72 h, mRNA and miRNA expression changes were examined using transcriptomic profiles and miRNA microarray, and then bioinformatics analysis was performed. RESULTS: Out of all the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) induced by HQ, 1482 DEGs and 10 DEMs were up-regulated, and 1594 DEGs and 42 DEMs were down-regulated. HQ-induced DEGs were involved in oxidative stress, apoptosis, DNA methylation, histone acetylation and cellular response to leukemia inhibitory factor GO terms, as well as metabolic, Wnt/ß-catenin, NF-κB, and leukemia-related pathways. The regulatory network of mRNAs and miRNAs includes 23 miRNAs, 1108 target genes, and 2304 potential miRNAs-mRNAs pairs. MiR-1246 and miR-224 had the potential to be major regulators in HQ-exposed K562 cells based on the miRNAs-mRNAs network. CONCLUSIONS: This study reinforces the use of in vitro model of HQ exposure and bioinformatic approaches to advance our knowledge on molecular mechanisms of benzene hematotoxicity at the RNA level.

Lithium Harvesting from the Most Abundant Primary and Secondary Sources: A Comparative Study on Conventional and Membrane Technologies.

The exponential rise in lithium demand over the last decade, as one of the largest sources for energy storage in terms of lithium-ion batteries (LIBs), has posed a great threat to the existing lithium supply and demand balance. The current methodologies available for lithium extraction, separation and recovery, both from primary (brines/seawater) and secondary (LIBs) sources, suffer not only at the hands of excessive use of chemicals but complicated, time-consuming and environmentally detrimental design procedures. Researchers across the world are working to review and update the available technologies for lithium harvesting in terms of their economic and feasibility analysis. Following its excessive consumption of sustainable energy resources, its demand has risen sharply and therefore requires urgent attention. In this paper, different available methodologies for lithium extraction and recycling from the most abundant primary and secondary lithium resources have been reviewed and compared. This review also includes the prospects of using membrane technology as a promising replacement for conventional methods.

Explaining mobile government social media continuance from the valence perspective: A SEM-NN approach.

Different from many previous studies explain mobile social media usage from a technical-center perspective, the present study investigates the factors that influence citizens' mobile government social media (GSM) continuance based on the valence framework. The research model was calculated by using data collected from 509 citizens who are the mobile GSM users in China. A structural equation modeling (SEM)-neural network (NN) method was employed to test the research model. The results of SEM indicated that the positive utilities included social value and hedonic value positively affect mobile GSM continuance, while the negative utility reflected by self-censorship negative affect mobile GSM continuance. This is further supported by the results of the neural network model analysis which indicated that hedonic value is more influencing predictor of continuous usage of mobile GSM, following by social value and self-censorship.

Huanglian decoction suppresses the growth of hepatocellular carcinoma cells by reducing CCNB1 expression.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most prevalent cancers in human populations worldwide. Huanglian decoction is one of the most important Chinese medicine formulas, with the potential to treat cancer. AIM: To investigate the role and mechanism of Huanglian decoction on HCC cells. METHODS: To identify differentially expressed genes (DEGs), we downloaded gene expression profile data from The Cancer Genome Atlas Liver Hepatocellular Carcinoma and Gene Expression Omnibus (GSE45436) databases. We obtained phytochemicals of the four herbs of Huanglian decoction from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. We also established a regulatory network of DEGs and drug target genes and subsequently analyzed key genes using bioinformatics approaches. Furthermore, we conducted in vitro experiments to explore the effect of Huanglian decoction and to verify the predictions. In particular, the CCNB1 gene was knocked down to verify the primary target of this decoction. Through the identification of the expression levels of key proteins, we determined the primary mechanism of Huanglian decoction in HCC. RESULTS: Based on the results of the network pharmacological analysis, we revealed 5 bioactive compounds in Huanglian decoction that act on HCC. In addition, a protein-protein interaction network analysis of the target genes of these five compounds as well as expression and prognosis analyses were performed in tumors. CCNB1 was confirmed to be the primary gene that may be highly expressed in tumors and was significantly associated with a worse prognosis. We also noted that CCNB1 may serve as an independent prognostic indicator in HCC. Moreover, in vitro experiments demonstrated that Huanglian decoction significantly inhibited the growth, migration, and invasiveness of HCC cells and induced cell apoptosis and G2/M phase arrest. Further analysis showed that the decoction may inhibit the growth of HCC cells by downregulating the CCNB1 expression level. After Huanglian decoction treatment, the expression levels of Bax, caspase 3, caspase 9, p21 and p53 in HCC cells were increased, while the expression of CDK1 and CCNB1 was significantly decreased. The p53 signaling pathway was also found to play an important role in this process. CONCLUSION: Huanglian decoction has a significant inhibitory effect on HCC cells. CCNB1 is a potential therapeutic target in HCC. Further analysis showed that Huanglian decoction can inhibit HCC cell growth by downregulating the expression of CCNB1 to activate the p53 signaling pathway.

Melatonin Protects Against Ischemic Brain Injury by Modulating PI3K/AKT Signaling Pathway via Suppression of PTEN Activity.

Stroke is one of the leading causes of death and disability worldwide with limited therapeutic options. Melatonin can attenuate ischemic brain damage with improved functional outcomes. However, the cellular mechanisms of melatonin-driven neuroprotection against post-stroke neuronal death remain unknown. Here, distal middle cerebral artery occlusion (dMCAO) was performed in C57BL/6j mice to develop an ischemic stroke in vivo model. Melatonin was injected intraperitoneally immediately after ischemia, and 24 and 48 hours later. Melatonin treatment, with 5 to 20 mg/kg, elicited a dose-dependent decrease in infarct volume and concomitant increase in sensorimotor function. At the molecular level, phosphorylation of PTEN and Akt were increased, whereas PTEN activity was decreased in melatonin treated animals 72 hours after dMCAO. At the cellular level, oxygenglucose deprivation (OGD) challenge of neuronal cell line Neuro-2a (N2a) and primary neurons supported melatonin's direct protection against neuronal cell death. Melatonin treatment reduced LDH release and neuronal apoptosis at various time points, markedly increased Akt phosphorylation in neuronal membrane, but significantly suppressed it in the cytoplasm of post-OGD neurons. Mechanistically, melatonin-induced Akt phosphorylation and neuronal survival was blocked by Wortmannin, a potent PIP3 inhibitor, exposing increased PI3K/Akt activation as a central player in melatonin-driven neuroprotection. Finally, PTEN knock-down through siRNA significantly inhibited PI3K/Akt activation and cell survival following melatonin treatment, suggesting that melatonin protection against ischemic brain damage, is at least partially, dependent on modulation of the PTEN/PI3K/Akt signaling axis.

Curcumin Ameliorates White Matter Injury after Ischemic Stroke by Inhibiting Microglia/Macrophage Pyroptosis through NF-κB Suppression and NLRP3 Inflammasome Inhibition.

NLRP3 inflammasome-mediated pyroptosis is a proinflammatory programmed cell death pathway, which plays a vital role in functional outcomes after stroke. We previously described the beneficial effects of curcumin against stroke-induced neuronal damage through modulating microglial polarization. However, the impact of curcumin on microglial pyroptosis remains unknown. Here, stroke was modeled in mice by middle cerebral artery occlusion (MCAO) for 60 minutes and treated with curcumin (150 mg/kg) intraperitoneally immediately after reperfusion, followed by daily administrations for 7 days. Curcumin ameliorated white matter (WM) lesions and brain tissue loss 21 days poststroke and improved sensorimotor function 3, 10, and 21 days after stroke. Furthermore, curcumin significantly reduced the number of gasdermin D+ (GSDMD+) Iba1+ and caspase-1+Iba1+ microglia/macrophage 21 days after stroke. In vitro, lipopolysaccharide (LPS) with ATP treatment was used to induce pyroptosis in primary microglia. Western blot revealed a decrease in pyroptosis-related proteins, e.g., GSDMD-N, cleaved caspase-1, NLRP3, IL-1ß, and IL-18, following in vitro or in vivo curcumin treatment. Mechanistically, both in vivo and in vitro studies confirmed that curcumin inhibited the activation of the NF-κB pathway. NLRP3 knocked down by siRNA transfection markedly increased the inhibitory effects of curcumin on microglial pyroptosis and proinflammatory responses, both in vitro and in vivo. Furthermore, stereotaxic microinjection of AAV-based NLRP3 shRNA significantly improved sensorimotor function and reduced WM lesion following curcumin treatment in MCAO mice. Our study suggested that curcumin reduced stroke-induced WM damage, improved functional outcomes, and attenuated microglial pyroptosis, at least partially, through suppression of the NF-κB/NLRP3 signaling pathway, further supporting curcumin as a potential therapeutic drug for stroke.

Baicalein ameliorates ischemic brain damage through suppressing proinflammatory microglia polarization via inhibiting the TLR4/NF-κB and STAT1 pathway.

Microglial polarization mediated neuroinflammation plays an important role in the pathological process of stroke. The aim of this study is to determine whether baicalein indirectly ameliorates neuronal injury through modulating microglial polarization after stroke and if so, then by what mechanism. The effects of baicalein on microglial polarization were revealed through the middle cerebral artery occlusion mouse model (MCAO, n = 6), the lipopolysaccharide (LPS) + interferon-γ (IFN-γ) and oxygen-glucose deprivation (OGD) induced neuroinflammatory microglia model (BV2, n = 3), respectively. Mice were treated with baicalein (100 mg/kg, i.g.) after reperfusion, and followed by daily administrations for 3 days. Results showed that the infarct volumes at 3 d in vehicle and baicalein-treated MCAO mice were 91.18 ± 4.02% and 55.36 ± 4.10%. Baicalein improved sensorimotor functions (p < 0.01) after MCAO. Real-time PCR revealed that baicalein decreased proinflammatory markers expression (p < 0.05), while elevated the anti-inflammatory markers (p < 0.05) in vivo and in vitro. Both western blot and immunofluorescent staining further confirmed that baicalein reduced proinflammatory marker CD16 levels (p < 0.01) and enhanced anti-inflammatory marker CD206 or Arg-1 levels (p < 0.05). Notably, baicalein suppressed the release of proinflammatory cytokines (p < 0.05) and nitric oxide (NO, p < 0.001). Mechanistically, baicalein prevented increases in TLR4 protein levels (p < 0.001), the phosphorylation of IKBα and p65 (p < 0.01), and the nuclear translocation of NF-κB p65 (p < 0.05). The NF-κB inhibitor, BAY 11-7085, enhanced the inhibitory effect of baicalein on the proinflammatory microglial polarization. Baicalein also inhibited the phosphorylation of signal transducer and activator of transcription 1 (STAT1, p < 0.001). A microglia-neuron co-culture system revealed that baicalein driven neuroprotection against OGD induced neuronal damage through modulating microglial polarization (p < 0.05). Baicalein indirectly ameliorates neuronal injury after stroke by polarizing microglia toward the anti-inflammatory phenotype via inhibition of the TLR4/NF-κB pathway and down-regulation of phosphorylated STAT1, suggesting that baicalein might serve a potential therapy for stroke.