Integrating Clinical Data and Radiomics and Deep Learning Features for End-to-End Delayed Cerebral Ischemia Prediction on Noncontrast CT.

BACKGROUND AND PURPOSE: Delayed cerebral ischemia is hard to diagnose early due to gradual, symptomless development. This study aimed to develop an automated model for predicting delayed cerebral ischemia following aneurysmal SAH on NCCT. MATERIALS AND METHODS: This retrospective study included 400 patients with aneurysmal SAH (156 with delayed cerebral ischemia) who underwent NCCT. The study used ATT-Deeplabv3+ for automatically segmenting hemorrhagic regions using semisupervised learning. Principal component analysis was used for reducing the dimensionality of deep learning features extracted from the average pooling layer of ATT-DeepLabv3+. The classification model integrated clinical data, radiomics, and deep learning features to predict delayed cerebral ischemia. Feature selection involved Pearson correlation coefficients, least absolute shrinkage, and selection operator regression. We developed models based on clinical features, clinical-radiomics, and a combination of clinical, radiomics, and deep learning. The study selected logistic regression, Naive Bayes, Adaptive Boosting (AdaBoost), and multilayer perceptron as classifiers. The performance of segmentation and classification models was evaluated on their testing sets using the Dice similarity coefficient for segmentation, and the area under the receiver operating characteristic curve (AUC) and calibration curves for classification. RESULTS: The segmentation process achieved a Dice similarity coefficient of 0.91 and the average time of 0.037 s/image. Seventeen features were selected to calculate the radiomics score. The clinical-radiomics-deep learning model with multilayer perceptron achieved the highest AUC of 0.84 (95% CI, 0.72-0.97), which outperformed the clinical-radiomics model (P = .002) and the clinical features model (P = .001) with multilayer perceptron. The performance of clinical-radiomics-deep learning model using AdaBoost was significantly superior to its clinical-radiomics model (P = .027). The performance of the clinical-radiomics-deep learning model and the clinical-radiomics model with logistic regression notably exceeded that of the model based solely on clinical features (P = .028; P = .046). The AUC of the clinical-radiomics-deep learning model with multilayer perceptron (P < .001) and the clinical-radiomics model with logistic regression (P = .046) were significantly higher than the clinical model with logistic regression. Of all models, the clinical-radiomics-deep learning model with multilayer perceptron showed best calibration. CONCLUSIONS: The proposed 2-stage end-to-end model not only achieves rapid and accurate segmentation but also demonstrates superior diagnostic performance with high AUC values and good calibration in the clinical-radiomics-deep learning model, suggesting its potential to enhance delayed cerebral ischemia detection and treatment strategies.

A novel hybrid model for species distribution prediction using neural networks and Grey Wolf Optimizer algorithm.

Neural networks are frequently employed to model species distribution through backpropagation methods, known as backpropagation neural networks (BPNN). However, the complex structure of BPNN introduces parameter settings challenges, such as the determination of connection weights, which can affect the accuracy of model simulation. In this paper, we integrated the Grey Wolf Optimizer (GWO) algorithm, renowned for its excellent global search capacity and rapid convergence, to enhance the performance of BPNN. Then we obtained a novel hybrid algorithm, the Grey Wolf Optimizer algorithm optimized backpropagation neural networks algorithm (GNNA), designed for predicting species' potential distribution. We also compared the GNNA with four prevalent species distribution models (SDMs), namely the generalized boosting model (GBM), generalized linear model (GLM), maximum entropy (MaxEnt), and random forest (RF). These models were evaluated using three evaluation metrics: the area under the receiver operating characteristic curve, Cohen's kappa, and the true skill statistic, across 23 varied species. Additionally, we examined the predictive accuracy concerning spatial distribution. The results showed that the predictive performance of GNNA was significantly improved compared to BPNN, was significantly better than that of GLM and GBM, and was even comparable to that of MaxEnt and RF in predicting species distributions with small sample sizes. Furthermore, the GNNA demonstrates exceptional powers in forecasting the potential non-native distribution of invasive plant species.

Facile Friedel-Crafts alkylation of arenes under solvent-free conditions.

The Friedel-Crafts alkylation of arenes is an important part of electrophilic aromatic substitution reactions. However, the reactivity of arenes is weakened by electron-withdrawing substituents, leading to limited substrate scopes and applications. Herein, we developed an efficient HOTf-promoted Friedel-Crafts alkylation reaction of broad arenes with α-aryl-α-diazoesters under metal-free and solvent-free conditions.

Mitochondrial KATP channel-mediated autophagy contributes to angiotensin II-induced vascular dysfunction in mice.

BACKGROUND AND AIM: The present study aimed to investigate whether the mitochondrial KATP channel contributes to angiotensin II (Ang II)-induced vascular dysfunction, the development of hypertension, and atherosclerosis. METHODS AND RESULTS: ApoE (-/-) mice fed a high-fat diet were chronically infused with Ang II for eight weeks and concomitantly treated with losartan (ARB), apocynin, or 5-hydroxy decanoate (5-HD), or 3-methyladenine (3-MA). Systolic blood pressure was measured, and pathological changes of aortic or liver tissue were observed. Nitric oxide (NO), superoxide dismutase 2 (SOD2) levels and vasorelaxation rate were measured, and protein and mRNA expressions were examined by western blot and RT-PCR. Ang II-induced development of hypertension was suppressed not only by ARB, and apocynin but also by 5-HD or 3-MA. Ang II infusion decreased aortic NO production and relaxation, as well as SOD2 activity in liver, which were improved by all treatments. In addition, Ang II-induced activation of autophagy was suppressed by 5-HD in aortic tissue, furthermore, Ang II increases the atherosclerotic index in plasma and exacerbates the development of atherosclerosis by increases of fat deposition in the aorta and liver. Lipid metabolism-related mRNA expressions (LXR-α, LDLR, SRBI, Acca, and FASN) were changed by Ang II. Similarly, not only ARB, and apocynin, but also 5-HD and 3-MA suppressed Ang II-induced these changes. CONCLUSIONS: Our present findings evidence that mitochondrial KATP channel-mediated autophagy contributes to Ang II-induced vascular dysfunction, development of hypertension, and atherosclerosis.

The dimensionality reductions of environmental variables have a significant effect on the performance of species distribution models.

How to effectively obtain species-related low-dimensional data from massive environmental variables has become an urgent problem for species distribution models (SDMs). In this study, we will explore whether dimensionality reduction on environmental variables can improve the predictive performance of SDMs. We first used two linear (i.e., principal component analysis (PCA) and independent components analysis) and two nonlinear (i.e., kernel principal component analysis (KPCA) and uniform manifold approximation and projection) dimensionality reduction techniques (DRTs) to reduce the dimensionality of high-dimensional environmental data. Then, we established five SDMs based on the environmental variables of dimensionality reduction for 23 real plant species and nine virtual species, and compared the predictive performance of those with the SDMs based on the selected environmental variables through Pearson's correlation coefficient (PCC). In addition, we studied the effects of DRTs, model complexity, and sample size on the predictive performance of SDMs. The predictive performance of SDMs under DRTs other than KPCA is better than using PCC. And the predictive performance of SDMs using linear DRTs is better than using nonlinear DRTs. In addition, using DRTs to deal with environmental variables has no less impact on the predictive performance of SDMs than model complexity and sample size. When the model complexity is at the complex level, PCA can improve the predictive performance of SDMs the most by 2.55% compared with PCC. At the middle level of sample size, the PCA improved the predictive performance of SDMs by 2.68% compared with the PCC. Our study demonstrates that DRTs have a significant effect on the predictive performance of SDMs. Specifically, linear DRTs, especially PCA, are more effective at improving model predictive performance under relatively complex model complexity or large sample sizes.

Exosomes derived from mesenchymal stromal cells exert a therapeutic effect on hypoxia-induced pulmonary hypertension by modulating the YAP1/SPP1 signaling pathway.

OBJECTIVE: Hypoxic pulmonary hypertension (HPH) is a progressive and life-threatening disease characterized by perivascular inflammation, pulmonary vascular remodeling, and occlusion. Mesenchymal stromal cell-derived exosomes (MSC-exo) have emerged as potential therapeutic agents due to their role in cell communication and the transportation of bioactive molecules. In this study, we aimed to investigate the therapeutic effects of MSC-exo against HPH and elucidate the underlying molecular mechanism. METHODS: Exosomes were isolated from conditioned media of human bone mesenchymal stromal cells using ultracentrifugation and characterized through western blotting, transmission electron microscopy (TEM), and nanoparticle tracking analysis (NTA). An HPH animal model was established in male SD rats, and MSC-exo or phosphate-buffered saline (PBS) were administered via the tail vein for three weeks. Subsequently, right ventricular systolic pressure (RVSP), right ventricular hypertrophy index (RVHI), and pulmonary vascular remodeling were evaluated. Lung tissues from HPH rats and normal rats underwent high-throughput sequencing and transcriptomic analysis. Gene Ontology (GO) analysis was employed to identify upregulated differentially expressed genes. Additionally, rat pulmonary artery smooth muscle cells (PASMC) exposed to platelet-derived growth factor-BB (PDGF-BB) were used to simulate HPH-related pathological behavior. In vitro cellular models were established to examine the molecular mechanism of MSC-exo in HPH. RESULTS: MSC-exo administration protected rats from hypoxia-induced increases in RVSP, RVHI, and pulmonary vascular remodeling. Additionally, MSC-exo alleviated PDGF-BB-induced proliferation and migration of PASMC. Transcriptomic analysis revealed 267 upregulated genes in lung tissues of HPH rats compared to control rats. Gene Ontology analysis indicated significant differences in pathways associated with Yes Associated Protein 1 (YAP1), a key regulator of cell proliferation and organ size. RT-qPCR and western blot analysis confirmed significantly increased expression of YAP1 in HPH lung tissues and PASMC, which was inhibited by MSC-exo treatment. Furthermore, analysis of datasets demonstrated that Secreted Phosphoprotein 1 (SPP1), also known as Osteopontin (OPN), is a downstream binding protein of YAP1 and can be upregulated by PDGF-BB. MSC-exo treatment reduced the expression of both YAP1 and SPP1. Lentivirus-mediated knockdown of YAP1 inhibited PDGF-BB-induced PASMC proliferation, migration, and SPP1 protein levels. CONCLUSION: Our findings demonstrate that MSC-exo exert a therapeutic effect against hypoxia-induced pulmonary hypertension by modulating the YAP1/SPP1 signaling pathway. The inhibition of YAP1 and downstream SPP1 expression by MSC-exo may contribute to the attenuation of pulmonary vascular remodeling and PASMC proliferation and migration. These results suggest that MSC-exo could serve as a potential therapeutic strategy for the treatment of HPH. Further investigations are warranted to explore the clinical applicability of MSC-exo-based therapies in HPH patients.

Low polarization-sensitive ultra-broadband anti-reflection coatings with improved reliability.

Broader spectra, lower reflectivity and higher reliability are the performance requirements for broadband antireflective (BBAR) films. In this work, a BBAR film structure was proposed, which maintains extremely low reflectivity, ultra-wide spectra, low polarization sensitivity and practical reliability. The BBAR film consists of a dense multilayer interference stack on the bottom and a nano-grass-like alumina (NGLA) layer with a gradient low refractive index distribution on the top. The film was deposited by atomic layer deposition, while the NGLA layer was formed by means of a hot water bath on Al2O3 layer. The top NGLA layer has extremely high porosity and ultra-low refractive index, along with extremely fragile structure. To surmount the fragility of NGLA layer, a sub-nano layer of SiO2 was grown by atomic layer deposition to solidify its structure and also to adjust the refractive index with different thicknesses of SiO2. Finally, in the wide wavelength range of 400-1100 nm, the average transmittance of the double-sided coated fused quartz reaches 99.2%. The absorption, light scattering, reliability and polarization characteristics of BBAR films were investigated. An optimized BBAR film with low polarization-sensitivity and improved reliability was realized, which should be potentially promising for application in optical systems.

Prediction of the Potential Distribution of the Endangered Species Meconopsis punicea Maxim under Future Climate Change Based on Four Species Distribution Models.

Climate change increases the extinction risk of species, and studying the impact of climate change on endangered species is of great significance to biodiversity conservation. In this study, the endangered plant Meconopsis punicea Maxim (M. punicea) was selected as the research object. Four species distribution models (SDMs): the generalized linear model, the generalized boosted regression tree model, random forest and flexible discriminant analysis were applied to predict the potential distribution of M. punicea under current and future climates scenarios. Among them, two emission scenarios of sharing socio-economic pathways (SSPs; i.e., SSP2-4.5 and SSP5-8.5) and two global circulation models (GCMs) were considered for future climate conditions. Our results showed that temperature seasonality, mean temperature of coldest quarter, precipitation seasonality and precipitation of warmest quarter were the most important factors shaping the potential distribution of M. punicea. The prediction of the four SDMs consistently indicated that the current potential distribution area of M. punicea is concentrated between 29.02° N-39.06° N and 91.40° E-105.89° E. Under future climate change, the potential distribution of M. punicea will expand from the southeast to the northwest, and the expansion area under SSP5-8.5 would be wider than that under SSP2-4.5. In addition, there were significant differences in the potential distribution of M. punicea predicted by different SDMs, with slight differences caused by GCMs and emission scenarios. Our study suggests using agreement results from different SDMs as the basis for developing conservation strategies to improve reliability.

Interpretation of Reflection and Colorimetry Characteristics of Indium-Particle Films by Means of Ellipsometric Modeling.

It is of great technological importance in the field of plasmonic color generation to establish and understand the relationship between optical responses and the reflectance of metallic nanoparticles. Previously, a series of indium nanoparticle ensembles were fabricated using electron beam evaporation and inspected using spectroscopic ellipsometry (SE). The multi-oscillator Lorentz-Drude model demonstrated the optical responses of indium nanoparticles with different sizes and size distributions. The reflectance spectra and colorimetry characteristics of indium nanoparticles with unimodal and bimodal size distributions were interpreted based on the SE analysis. The trends of reflectance spectra were explained by the transfer matrix method. The effects of optical constants n and k of indium on the reflectance were demonstrated by mapping the reflectance contour lines on the n-k plane. Using oscillator decomposition, the influence of different electron behaviors in various indium structures on the reflectance spectra was revealed intuitively. The contribution of each oscillator on the colorimetry characteristics, including hue, lightness and saturation, were determined and discussed from the reflectance spectral analysis.

Dexmedetomidine Alleviates Ischemia/Reperfusion-Associated Acute Kidney Injury by Enhancing Autophagic Activity via the α2-AR/AMPK/mTOR Pathway.

BACKGROUND: Dexmedetomidine (DEX) reportedly protects against ischemia-reperfusion (I/R) injury and associated damage to the kidneys, but the underlying mechanisms have yet to be established. METHODS: Unilateral nephrectomy was performed in Wistar rats, and the remaining kidney was clamped for 1 h prior to reperfusion to establish an experimental model system. These animals were then randomized into Sham, DEX + Sham, DEX + I/R, ATI (Altepamizole, α2-adrenergic receptor inhibitor) + DEX + I/R, and 3-MA (3-methyladenine, autophagy inhibitor) + DEX + I/R groups. Serum renal function biomarkers, acute kidney injury (AKI) histopathological scores, serum inflammatory factors, redox biomarkers, markers of autophagic flux, and autophagosome numbers were assessed. Levels of proteins related to the autophagic pathway, including mTOR and AMPK, were also analyzed. RESULTS: Serum creatinine and urea nitrogen levels in the I/R group were significantly elevated over those in sham control rats, as were AKI scores, serum inflammatory cytokine concentrations (IL-6, IL-1ß, and TNF-α), and serum levels of the oxidative stress biomarker malondialdehyde (MDA). All of these parameters were significantly reduced in the DEX + I/R group relative to I/R model rats. I/R group rats also exhibited significant decreases in renal levels of autophagic flux-related biomarkers and autophagosome numbers relative to sham controls, while DEX administration partially restored normal autophagic flux in these rats. Acute I/R also suppress the expression of AMPK in the kidney while increasing mTOR expression, and DEX reversed these effects. The beneficial impact of DEX on I/R-associated AKI was ablated by ATI or 3-MA administration. CONCLUSIONS: These analyses provide strong evidence for the ability of DEX to protect against I/R-associated AKI via the α2-AR/AMPK/mTOR pathway-mediated enhancement of autophagic activity.

Nanoformulated Bumetanide Ameliorates Social Deficiency in BTBR Mice Model of Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder with few medication options. Bumetanide, an FDA-approved diuretic, has been proposed as a viable candidate to treat core symptoms of ASD, however, neither the brain region related to its effect nor the cell-specific mechanism(s) is clear. The availability of nanoparticles provides a viable way to identify pharmacological mechanisms for use in ASD. Here, we found that treatment with bumetanide, in a systemic and medial prefrontal cortex (mPFC) region-specific way, attenuated social deficits in BTBR mice. Furthermore, using poly (ethylene glycol)-poly(l-lactide) (PEG-PLA) nanoparticles [NP(bumetanide)], we showed that the administration of NP(bumetanide) in a mPFC region-specific way also alleviated the social deficits of BTBR mice. Mechanistically, the behavioral effect of NP(bumetanide) was dependent on selective microglia-specific targeting in the mPFC. Pharmacological depletion of microglia significantly reduced the effect of nanoencapsulation and depletion of microglia alone did not improve the social deficits in BTBR mice. These findings suggest the potential therapeutic capabilities of nanotechnology for ASD, as well as the relevant link between bumetanide and immune cells.

Mo6S8-based single-metal-atom catalysts for direct methane to methanol conversion.

The single atom catalysts have been attracting much attention for catalysis. In this work, the significant influence of single-metal-atom (M = K, Ti, Fe, Co, Ni, Cu, Rh) doping on a Mo6S8 cluster was revealed for the direct methane to methanol conversion in water stream using density functional theory calculations. It was found that all single atom dopants help to facilitate the conversion via the steam reforming of methane (SRM). The single Fe atom on Mo6S8 (Fe-Mo6S8) exhibits the most significant promoting effect, which is followed by Ni, Co, Rh-Mo6S8 > K, Ti, Cu-Mo6S8 > Mo6S8 in a decreasing sequence. The enhanced activity by single atom doping on Mo6S8 is mainly associated with the interplay between the ensemble effect via the direct participation of an active M dopant and the site confinement imposed by doping of a single M atom, in tuning the methane conversion and methanol selectivity. It generates the new active center, M, which confines the SRM to occur at the M-Mo bridge sites and facilitates the selective production of methanol. A good single-atom promoter should not only bind *OH or *O moderately, being strongly enough to help water dissociation and weakly enough to allow the oxidation of methane, but also impose the confinement effect to facilitate the C-O bond association and production of methanol. Our results highlight the importance of the interplay among ligand, ensemble, and confinement effects in promoting the complex SRM over single atom catalysts.

Disulfiram combined with copper inhibits metastasis and epithelial-mesenchymal transition in hepatocellular carcinoma through the NF-κB and TGF-ß pathways.

Late-stage hepatocellular carcinoma (HCC) usually has a low survival rate because of the high risk of metastases and the lack of an effective cure. Disulfiram (DSF) has copper (Cu)-dependent anticancer properties in vitro and in vivo. The present work aims to explore the anti-metastasis effects and molecular mechanisms of DSF/Cu on HCC cells both in vitro and in vivo. The results showed that DSF inhibited the proliferation, migration and invasion of HCC cells. Cu improved the anti-metastatic activity of DSF, while Cu alone had no effect. Furthermore, DSF/Cu inhibited both NF-κB and TGF-ß signalling, including the nuclear translocation of NF-κB subunits and the expression of Smad4, leading to down-regulation of Snail and Slug, which contributed to phenotype epithelial-mesenchymal transition (EMT). Finally, DSF/Cu inhibited the lung metastasis of Hep3B cells not only in a subcutaneous tumour model but also in an orthotopic liver metastasis assay. These results indicated that DSF/Cu suppressed the metastasis and EMT of hepatic carcinoma through NF-κB and TGF-ß signalling. Our study indicates the potential of DSF/Cu for therapeutic use.

Pseudoginsenoside-F11 attenuates cerebral ischemic injury by alleviating autophagic/lysosomal defects.

AIMS: Pseudoginsenoside-F11 (PF11), an ocotillol-type ginsenoside, has been reported to exert wide-ranging neuroprotective properties. The aim of this study was to investigate the effect and potential mechanisms of PF11 on the autophagic/lysosomal pathway following ischemic stroke. METHODS: Male Sprague-Dawley rats underwent permanent middle cerebral artery occlusion (pMCAO). Cerebral ischemia outcome, TUNEL staining, Fluoro-Jade B staining were carried out 24 hours poststroke. The autophagic/lysosomal-related proteins were measured. RESULTS: A single administration of PF11 significantly decreased the infarct area, reduced the brain water content, and improved neurological functions, even 4 hours after the onset of pMCAO. Meanwhile, PF11 lessened the ischemic insult-mediated loss of neurons and activation of astrocytes and microglia. Furthermore, PF11 attenuated pMCAO-induced accumulations of autophagosomes and apoptosis. We further observed a remarkable effect of PF11 in reversing the ischemic insult-induced accumulation of autophagosomes (LC3-II) and abnormal aggregation of autophagic proteins (SQSTM1 and ubiquitin). Furthermore, PF11 was capable of improving lysosomal function and lysosome/autophagosome fusion following pMCAO, and this change was reversed by the lysosomal inhibitor chloroquine. Also, the improvement of ischemic outcome and the antiapoptotic effect induced by PF11 was reversed by CQ. CONCLUSION: These findings indicate that the autophagic flux is impaired in a rat model of pMCAO, and that PF11 exerts an excellent protective effect against ischemic stroke by alleviating autophagic/lysosomal defects.

An amine-functionalized metal-organic framework as a sensing platform for DNA detection.

An amine-functionalized metal-organic framework (MOF) has been employed as an effective fluorescent sensing platform for DNA detection and is capable of distinguishing complementary and mismatched target sequences with high sensitivity and selectivity.

SOMG-833, a novel selective c-MET inhibitor, blocks c-MET-dependent neoplastic effects and exerts antitumor activity.

The hepatocyte growth factor/c-MET signaling axis plays an important role in tumor cell proliferation, metastasis, and tumor angiogenesis, and therefore presents as an attractive target for cancer therapy. Notably, most small-molecule c-MET inhibitors currently undergoing clinical trials are multitarget inhibitors with the unwanted inhibition of additional kinases, often accounting for undesirable toxicity. Here, we discovered SOMG-833 [3-(4-methylpiperazin-1-yl)-5-(3-nitrobenzylamino)-7-(trifluoromethyl) quinoline] as a potent and selective small-molecule c-MET inhibitor, with an average IC50 of 0.93 nM against c-MET, over 10,000-fold more potent compared with 19 tyrosine kinases, including c-MET family members and highly homologous kinases. SOMG-833 strongly suppressed c-MET-mediated signaling transduction regardless of mechanistic complexity implicated in c-MET activation, including MET gene amplification, MET gene fusion, and HGF-stimulated c-MET activation. In a panel of 24 human cancer or genetically engineered model cell lines, SOMG-833 potently inhibited c-MET-driven cell proliferation, whereas cancer cells lacking c-MET activation were markedly less sensitive (at least 15-fold) to the treatment. SOMG-833 also suppressed c-MET-mediated migration, invasion, urokinase activity, and invasive growth phenotype. In addition, inhibition of primary human umbilical vascular endothelial cell (HUVEC) proliferation and downregulation of plasma proangiogenic factor interleukin-8 secretion resulted from SOMG-833 treatment, suggesting its significant antiangiogenic properties. Together, these results led to the remarkable antitumor efficacy of SOMG-833 in vivo, as demonstrated in c-MET-dependent NIH-3T3/TPR-MET, U-87MG, and EBC-1 xenograft models. Collectively, our results suggested SOMG-833 as a promising candidate for highly selective c-MET inhibition and a powerful tool to investigate the sole role of MET kinase in cancer.

Yhhu3813 is a novel selective inhibitor of c-Met kinase that inhibits c-Met-dependent neoplastic phenotypes of human cancer cells.

AIM: c-Met kinase deregulation is strongly associated with the formation, progression and dissemination of human cancers. In this study we identified Yhhu3813 as a small-molecule inhibitor of c-Met kinase and characterized its antitumor properties both in vitro and in vivo. METHODS: The activities of different kinases were measured using ELISA assays and signaling proteins in the cells were detected with Western blotting. Cell proliferation was assessed using SRB or MTT assay in twenty human cell lines and cell cycle distribution was determined with flow cytometry. Transwell-based assay was used to evaluate cell migration and invasion. Cell invasive growth was detected by a morphogenesis assay. c-Met overactivated human NSCLC cell line EBC-1 xenografts were used to evaluate the in vivo anti-tumor efficacy. RESULTS: Yhhu3813 potently inhibited c-Met kinase activity in vitro with an IC50 value of 2.4±0.3 nmol/L, >400-fold higher than that for a panel of 15 different tyrosine kinases, suggesting a high selectivity of Yhhu3813. The compound (20, 100 and 500 nmol/L) dose-dependently inhibited the phosphorylation of c-Met and its key downstream Akt and Erk signal cascades in multiple c-Met aberrant human cancer cell lines, regardless of the mechanistic complexity in c-Met activation across different cellular contexts. In 20 human cancer cell lines harboring different backgrounds of c-Met expression/activation, Yhhu3813 potently inhibited c-Met-driven cell proliferation via arresting cells at G1/S phase. Furthermore, Yhhu3813 substantially impaired c-Met-mediated cell migration, invasion, scattering, and invasive growth. Oral administration of EBC-1 xenograft mice with Yhhu3813 (50 or 100 mg·kg(-1)·d(-1), qd, for 2 weeks) dose-dependently suppressed the tumor growth, which was correlated with a reduction in the intratumoral proliferation index and c-Met signaling. CONCLUSION: Yhhu3813 is a potent selective inhibitor of c-Met that inhibits c-Met-dependent neoplastic phenotypes of human cancer cells in vitro and in vivo.

Water-stable metal-organic frameworks with intrinsic peroxidase-like catalytic activity as a colorimetric biosensing platform.

Two iron(III)-based metal-organic frameworks (MOFs) are found to behave as efficient peroxidase mimics and catalyze the oxidation of different peroxidase substrates by H2O2 accompanied with significant color change in the solution. With these findings, a simple and sensitive colorimetric assay to detect H2O2 and ascorbic acid has been established.