Cinobufagin exerts an antitumor effect in non-small-cell lung cancer by blocking STAT3 signaling.

Background: Non-small-cell lung cancer (NSCLC) is the most common histological subtype of lung cancer with significant morbidity and mortality rates worldwide. Cinobufagin, the primary component of Chansu and the major active ingredient of cinobufacini, has attracted widespread attention for its excellent anticancer effects, but its activity remains poorly characterized in NSCLC. Methods: The functions of cinobufagin treatment in anti-tumor was evaluated using various in vitro and in vivo assays. The change of STAT3 signaling by cinobufagin was analyzed using molecular docking, immunofluorescence technic and western blotting. Results: In vitro, we confirmed the inhibitory effect of cinobufagin on cell viability, proliferation, migration, epithelial-mesenchymal transition (EMT), as well as an apoptosis-inducing effect. The antitumor effects of cinobufagin were confirmed in vivo by measuring tumor growth in a mouse xenograft model. Cinobufagin was found to significantly inhibit the phosphorylation of signal transducer and activator of transcription 3 (STAT3) at tyrosine 705 (Y705) in a time- and concentration-dependent manner. Moreover, cinobufagin reversed IL-6-induced nuclear translocation of STAT3. Conclusions: Our study has demonstrated that cinobufagin exerts an antitumor effect in non-small-cell lung cancer by blocking STAT3 signaling, and cinobufagin is a promising candidate agent for NSCLC therapy.

An Internal Defect Detection Algorithm for Concrete Blocks Based on Local Mean Decomposition-Singular Value Decomposition and Weighted Spatial-Spectral Entropy.

Within the scope of concrete internal defect detection via laser Doppler vibrometry (LDV), the acquired signals frequently suffer from low signal-to-noise ratios (SNR) due to the heterogeneity of the concrete's material properties and its rough surface structure. Consequently, these factors make the defect signal characteristics challenging to discern precisely. In response to this challenge, we propose an internal defect detection algorithm that incorporates local mean decomposition-singular value decomposition (LMD-SVD) and weighted spatial-spectral entropy (WSSE). Initially, the LDV vibration signal undergoes denoising via LMD and the SVD algorithms to reduce noise interference. Subsequently, the distribution of each frequency in the scan plane is analyzed utilizing the WSSE algorithm. Since the vibrational energy of the frequencies caused by the defect resonance is concentrated in the defect region, its energy distribution in the scan plane is non-uniform, resulting in a significant difference between the defect resonance frequencies' SSE values and the other frequencies' SSE values. This feature is used to estimate the resonant frequencies of internal defects. Ultimately, the defects are characterized based on the modal vibration patterns of the defect resonant frequencies. Tests were performed on two concrete blocks with simulated cavity defects, using an ultrasonic transducer as the excitation device to generate ultrasonic vibrations directly from the back of the blocks and applying an LDV as the acquisition device to collect vibration signals from their front sides. The results demonstrate the algorithm's capacity to effectively pinpoint the information on the location and shape of shallow defects within the concrete, underscoring its practical significance for concrete internal defect detection in practical engineering scenarios.

The economic impacts of COVID-19 and city lockdown: Early evidence from China.

As the first major developing country heavily struck by the COVID-19 pandemic, China adopted the world's most stringent lockdown interventions to contain the virus spread. Using macro- and micro-level data, this paper shows that both the pandemic and lockdown policies have had negative and significant impacts on the economy. Gross regional product (GRP) fell by 9.5 and 0.3 percentage points in cities with and without lockdown interventions, respectively. These impacts represent a dramatic recession from China's average growth of 6.74% before the pandemic. The results indicate that lockdown explains 2.8 percentage points of the GDP loss. We also document significant spill-over effects of the pandemic in adjacent areas but no such effects of lockdown. Reduced labor mobility, land supply, and entrepreneurship are among the most significant mechanisms underpinning the impacts of the pandemic and lockdown. Cities with higher share of secondary industry, higher traffic intensity, lower population density, lower internet access, and lower fiscal capacity suffered more. However, these cities seem to have recovered well from the recession and quickly closed the economic gap in the aftermath of the pandemic and city lockdown. Our findings have broader implications for the global interventions in pandemic containment.

Pharmacological targeting of MTHFD2 suppresses NSCLC via the regulation of ILK signaling pathway.

Lung cancer is the most common cause of cancer related deaths worldwide with the highest mortality rate. Non-small cell lung cancer (NSCLC) accounts for about 85 % of lung cancers. Mitochondrial methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) is a bifunctional enzyme and is the most differentially expressed metabolic enzyme in various tumors including lung cancer. However, little is known about how MTHFD2 functions in NSCLC. Integrin-linked kinase (ILK) signaling plays key a role in tumor progression including metastasis, proliferation and migration. Here, we show that MTHFD2 inhibition results in suppression of cell growth, migration, invasion and epithelial-mesenchymal transition (EMT) in NSCLC. Microarray analysis suggests that MTHFD2 is positively associated with ILK signaling based on western blotting results. In addition, the phosphorylation of AMPKα plays an essential role in MTHFD2 regulation of ILK signaling. Further, the small-molecule compound C18 inhibits MTHFD2 with great efficiency. C18 blocks MTHFD2/ILK signaling pathway and restrains cell growth, migration, invasion, and EMT of NSCLC and induces apoptosis. In brief, our study found that the positive impact of MTHFD2 is mediated via ILK signaling pathway in NSCLC. Thus, blocking MTHFD2 represents a promising therapeutic strategy against NSCLC clinically.

Water-Air Interface Imaging: Recovering the Images Distorted by Surface Waves via an Efficient Registration Algorithm.

Imaging through the wavy water-air interface is challenging since the random fluctuations of water will cause complex geometric distortion and motion blur in the images, seriously affecting the effective identification of the monitored object. Considering the problems of image recovery accuracy and computational efficiency, an efficient reconstruction scheme that combines lucky-patch search and image registration technologies was proposed in this paper. Firstly, a high-quality reference frame is rebuilt using a lucky-patch search strategy. Then an iterative registration algorithm is employed to remove severe geometric distortions by registering warped frames to the reference frame. During the registration process, we integrate JADE and LBFGS algorithms as an optimization strategy to expedite the control parameter optimization process. Finally, the registered frames are refined using PCA and the lucky-patch search algorithm to remove residual distortions and random noise. Experimental results demonstrate that the proposed method significantly outperforms the state-of-the-art methods in terms of sharpness and contrast.

Concrete Multi-Type Defect Classification Algorithm Based on MSSMA-SVM.

In order to realize the automatic classification of internal defects for non-contact nondestructive testing of concrete, a concrete multi-type defect classification algorithm based on the mixed strategy slime mold algorithm support vector machine (MSSMA-SVM) was proposed. The concrete surface's vibration signal was obtained using a laser Doppler vibrometer (LDV) for four classification targets for no defect, segregation, cavity, and foreign matter concrete classification targets. The wavelet packet transform (WPT) decomposes the detected signals to get information on different frequency bands. The energy ratio change rate, energy ratio, and wavelet packet singular entropy of each node after the WPT were used as the feature input of MSSMA-SVM. The experimental results show that the designed MSSMA-SVM classifier can accurately detect the type, which provides a practical algorithm for classifying concrete defects by laser vibration measurement.

Cinobufagin suppresses colorectal cancer growth via STAT3 pathway inhibition.

Colorectal cancer (CRC) has become one of the most common types of cancer with the highest morbidity and mortality rates globally. Cinobufagin, a natural product extracted from toad venom and a major active ingredient in cinobufotalin, exhibits high antitumor activity. Here, we investigated the in vitro and in vivo antitumor activities of cinobufagin and explored the underlying mechanisms in CRC. Cinobufagin could inhibit proliferation, migration, invasion and promote apoptosis of HCT116, RKO, and SW480 cells in vitro. Mechanistically, cinobufagin simultaneously suppressed the phosphorylation of signal transducer and activator of transcription 3 (STAT3) and blocked the interleukin-6 (IL6)-induced nuclear translocation of STAT3. IL6 activated the STAT3 pathway, subsequently inducing epithelial-mesenchymal transition (EMT). Furthermore, cinobufagin suppressed EMT in CRC by inhibiting the STAT3 pathway. Animal experiments clearly showed that cinobufagin could reduce tumor growth. Cinobufagin may be used clinically as a novel STAT3 inhibitor for CRC adjuvant therapy.

The shadow price of CO2 emissions in China's iron and steel industry.

As China becomes the world's largest energy consumer and CO2 emitter, there has been a rapidly emerging literature on estimating China's abatement cost for CO2 using a distance function approach. However, the existing studies have mostly focused on the cost estimates at macro levels (provinces or industries) with few examining firm-level abatement costs. No work has attempted to estimate the abatement cost of CO2 emissions in the iron and steel industry. Although some have argued that the directional distance function (DDF) is more appropriate in the presence of bad output under regulation, the choice of directions is largely arbitrary. This study provides the most up-to-date estimate of the shadow price of CO2 using a unique dataset of China's major iron and steel enterprises in 2014. The paper uses output quadratic DDF and investigates the impact of using different directional vectors representing different carbon mitigation strategies. The results show that the mean CO2 shadow price of China's iron and steel enterprises is very sensitive to the choice of direction vectors. The average shadow prices of CO2 are 407, 1226 and 6058Yuan/tonne respectively for the three different direction vectors. We also find substantial heterogeneity in the shadow prices of CO2 emissions among China's major iron and steel enterprises. Larger, listed enterprises are found to be associated lower CO2 shadow prices than smaller, unlisted enterprises.

Carbon farming economics: What have we learned?

This study reviewed 62 economic analyses published between 1995 and 2014 on the economic impacts of policies that incentivise agricultural greenhouse (GHG) mitigation. Typically, biophysical models are used to evaluate the changes in GHG mitigation that result from landholders changing their farm and land management practices. The estimated results of biophysical models are then integrated with economic models to simulate the costs of different policy scenarios to production systems. The cost estimates vary between $3 and $130/t CO2 equivalent in 2012 US dollars, depending on the mitigation strategies, spatial locations, and policy scenarios considered. Most studies assessed the consequences of a single, rather than multiple, mitigation strategies, and few considered the co-benefits of carbon farming. These omissions could challenge the reality and robustness of the studies' results. One of the biggest challenges facing agricultural economists is to assess the full extent of the trade-offs involved in carbon farming. We need to improve our biophysical knowledge about carbon farming co-benefits, predict the economic impacts of employing multiple strategies and policy incentives, and develop the associated integrated models, to estimate the full costs and benefits of agricultural GHG mitigation to farmers and the rest of society.