Discovery of a long half-life AURKA inhibitor to treat MYC-amplified solid tumors as a monotherapy and in combination with everolimus.

Aurora kinase inhibitors such as alisertib can destabilize MYC-family oncoproteins and have demonstrated compelling anti-tumor efficacy. In this study, we report 6K465, a novel pyrimidine-based Aurora A (AURKA) inhibitor that reduces levels of c-MYC and N-MYC oncoproteins more potently than alisertib. In an analysis of the antiproliferative effect of 6K465, the sensitivities of small cell lung cancer (SCLC) and breast cancer (BC) cell lines to 6K465 were strongly associated with the protein levels of c-MYC and/or N-MYC. We also report DBPR728, an acyl-based prodrug of 6K465 bearing fewer hydrogen-bond donors that exhibited 10-fold improved oral bioavailability. DBPR728 induced durable tumor regression of c-MYC- and/or N-MYC- overexpressing xenografts including SCLC, triple-negative breast cancer (TNBC), hepatocellular carcinoma and medulloblastoma using a 5-on-2-off or once-a-week dosing regimen on a 21-day cycle. A single oral dose of DBPR728 at 300 mg/kg induced c-MYC reduction and cell apoptosis in the tumor xenografts for more than 7 days. The inhibitory effect of DBPR728 at a reduced dosing frequency was attributed to its uniquely high tumor/plasma ratio (3.6-fold within 7 days) and the long tumor half-life of active moiety 6K465. Furthermore, DBPR728 was found to synergize with the mTOR inhibitor everolimus to suppress c-MYC- or N-MYC- driven SCLC. Collectively, these results suggest DBPR728 has the potential to treat cancers overexpressing c-MYC- and/or N-MYC.

What are the pandemic's shocks on carbon emission trading? The different management applications.

Maintaining the stability of the carbon market is of great significance for China to meet its goal of "Double Carbon," but at the beginning of 2020 the COVID-19 pandemic emerged and the economy was greatly affected. A natural question is whether it impacted domestic carbon markets. This paper thus presents the event research method on eight carbon emission trading markets in China, because it can timely exhibit the benefits investors gained during the COVID-19 pandemic and also can overcome the difficulty of separating those benefits from the overall performance of the carbon market via high-frequency data. The results herein confirm that China's carbon market has reacted negatively to the COVID-19 pandemic, which mainly relates to the mandatory blockade and isolation policy adopted by the central government. The production and operation activities of enterprises decreased along with the demand for carbon quotas. Because of the panic, investors also had a negative attitude towards the carbon market, influencing the supply and demand curve of carbon quotas and causing a decline in carbon prices. Under the effectiveness of government epidemic prevention and control policies, we further find that the negative impact was gradually eliminated. Overall, our findings offer some important information for the decision-making of governments, carbon market investors, and policymakers.

Identifying the nexus among environmental performance, digital finance, and green innovation: New evidence from prefecture-level cities in China.

Globally, nations are increasingly focusing on green innovation in their environmental protection efforts as part of sustainable development, and digital finance is playing a vital role in enhancing green innovation. Employing annual data from 220 prefecture-level cities between 2011 and 2019, we empirically analyze the connections among environmental performance, digital finance, and green innovation via the Karavias panel unit root test with structural breaks, the Gregory-Hansen structural break cointegration test and pooled mean group (PMG) estimation. The following four points are the key conclusions: (1) The results support cointegration links between these variables when structural breaks are considered. (2) The PMG estimation outcomes indicate that green innovation and digital finance may have a favorable long-term effect on environmental performance. (3) For better environmental performance and more green innovation, the level of digitalization of digital finance is crucial. (4) The potential of digital finance and green innovation to improve environmental performance has not been fully realized in the western region of China.

The transaction behavior of cryptocurrency and electricity consumption.

Rapidly increasing cryptocurrency prices have encouraged cryptocurrency miners to participate in cryptocurrency production, increasing network hashrates and electricity consumption. Growth in network hashrates has further crowded out small cryptocurrency investors owing to the heightened costs of mining hardware and electricity. These changes prompt cryptocurrency miners to become new investors, leading to cryptocurrency price increases. The potential bidirectional relationship between cryptocurrency price and electricity consumption remains unidentified. Hence, this research thus utilizes July 31 2015-July 12 2019 data from 13 cryptocurrencies to investigate the short- and long-run causal effects between cryptocurrency transaction and electricity consumption. Particularly, we consider structural breaks induced by external shocks through stationary analysis and comovement relationships. Over the examined time period, we found that the series of cryptocurrency transaction and electricity consumption gradually returns to mean convergence after undergoing daily shocks, with prices trending together with hashrates. Transaction fluctuations exert both a temporary effect and permanent influence on electricity consumption. Therefore, owing to the computational power deployed to wherever high profit is found, transactions are vital determinants of electricity consumption.

Modulating the affinity and signaling bias of cannabinoid receptor 1 antagonists.

Cannabinoid receptor 1 (CB1) is a G protein-coupled receptor and a therapeutic target for metabolic disorders. Numerous CB1 antagonists have been developed, but their functional selectivities and bias towards G protein or ß-arrestin signaling have not been systemically characterized. In this study, we analyzed the binding affinities and downstream signaling of two series of pyrazole derivatives bearing 1-aminopiperidine (Series I) or 4-aminothiomorpholine 1,1-dioxide (Series II) moieties, as well as the well-known CB1 antagonists rimonabant and taranabant. Analyses of the results for the Series I and II derivatives showed that minor structure modifications to their functional groups and especially the incorporation of 1-aminopiperidine or 4-aminothiomorpholine 1,1-dioxide motifs can profoundly affect their bias toward G protein or ß-arrestin signaling, and that their binding affinity and functional activity can be disassociated. Docking and molecular dynamics simulations revealed that the binding modes of Series I and II antagonists differed primarily in that Series I antagonists formed an additional hydrogen bond with the receptor, whereas those in Series II formed a water bridge.

Stress of life events and anxiety as mediators of the association between insomnia and triglycerides in college students.

Purpose: This study examined interrelationships among insomnia, stress, anxiety, and metabolic risk factors. Methods: A total of 124 college students were included in the analysis (age = 21 ± 1 years). Insomnia, stress of life events, and anxiety were assessed using self-reported questionnaires. Fasting blood samples were assayed for glucose, insulin, total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-cholesterol), and low-density lipoprotein cholesterol (LDL-cholesterol). Results: Insomnia was positively associated with stress of life events (ß = 0.28, p < .001) and anxiety (ß = 0.46, p < .001). Insomnia was related to elevated fasting insulin (ß = 0.12, p = .04) and triglyceride level (ß = 1.85, p < .001). An inverse association was found between insomnia and HDL-cholesterol (ß = -0.45, p = .03). Sobel's test for mediation showed that stress of life events (p = .020) and anxiety (p = .013) mediated the relationship between insomnia and hypertriglyceridemia. Conclusions: Reducing stress and anxiety among college students with insomnia may influence subsequent cardiovascular health.

Correction to "Synergistic Inhibition of SARS-CoV-2 Replication Using Disulfiram/Ebselen and Remdesivir".

[This corrects the article DOI: 10.1021/acsptsci.1c00022.].

Economic policy uncertainty and energy production in China.

Owing to economics are usually linked with energy production, economic policy may have an instantaneous adjustment according to the current monetary, financial, cultural circumstances. This research thus investigates the dynamic co-movement as well as cointegration relationships between economic policy uncertainty (EPU) and disparate energy productions, i.e., Chinese coal, natural gas, crude oil, electricity as well as renewable energy, during the period from January 1995 to October 2019 in China. We compare the two EPU indices and make empirical and robust analysis to get more evidence for the time-varying co-movement between energy production and EPU. The empirical results show that there are stationary properties and cointegration relationships between energy production and EPU. By utilizing wavelet co-movement analysis in the time-frequency domain, our results show a significant positive co-movement among disparate energy productions and EPU at high frequencies, i.e., in the short term, but weaker co-movement at low frequencies, i.e., in the long term. Hence, the phase-difference series are mostly around the zero line, implying the variables behave to the dynamics of the co-movement with positive causality. Policy recommendations are offered in accordance with our finding.

Discovery and Synthesis of a Pyrimidine-Based Aurora Kinase Inhibitor to Reduce Levels of MYC Oncoproteins.

The A-type Aurora kinase is upregulated in many human cancers, and it stabilizes MYC-family oncoproteins, which have long been considered an undruggable target. Here, we describe the design and synthesis of a series of pyrimidine-based derivatives able to inhibit Aurora A kinase activity and reduce levels of cMYC and MYCN. Through structure-based drug design of a small molecule that induces the DFG-out conformation of Aurora A kinase, lead compound 13 was identified, which potently (IC50 < 200 nM) inhibited the proliferation of high-MYC expressing small-cell lung cancer (SCLC) cell lines. Pharmacokinetic optimization of 13 by prodrug strategies resulted in orally bioavailable 25, which demonstrated an 8-fold higher oral AUC (F = 62.3%). Pharmacodynamic studies of 25 showed it to effectively reduce cMYC protein levels, leading to >80% tumor regression of NCI-H446 SCLC xenograft tumors in mice. These results support the potential of 25 for the treatment of MYC-amplified cancers including SCLC.

Synergistic Inhibition of SARS-CoV-2 Replication Using Disulfiram/Ebselen and Remdesivir.

The SARS-CoV-2 replication and transcription complex (RTC) comprising nonstructural protein (nsp) 2-16 plays crucial roles in viral replication, reducing the efficacy of broad-spectrum nucleoside analog drugs such as remdesivir and evading innate immune responses. Most studies target a specific viral component of the RTC such as the main protease or the RNA-dependent RNA polymerase. In contrast, our strategy is to target multiple conserved domains of the RTC to prevent SARS-CoV-2 genome replication and to create a high barrier to viral resistance and/or evasion of antiviral drugs. We show that the clinically safe Zn-ejector drugs disulfiram and ebselen can target conserved Zn2+ sites in SARS-CoV-2 nsp13 and nsp14 and inhibit nsp13 ATPase and nsp14 exoribonuclease activities. As the SARS-CoV-2 nsp14 domain targeted by disulfiram/ebselen is involved in RNA fidelity control, our strategy allows coupling of the Zn-ejector drug with a broad-spectrum nucleoside analog that would otherwise be excised by the nsp14 proofreading domain. As proof-of-concept, we show that disulfiram/ebselen, when combined with remdesivir, can synergistically inhibit SARS-CoV-2 replication in Vero E6 cells. We present a mechanism of action and the advantages of our multitargeting strategy, which can be applied to any type of coronavirus with conserved Zn2+ sites.

What is the relationship between government response and COVID-19 pandemics? Global evidence of 118 countries.

Using daily data of novel coronavirus pneumonia (COVID-19) covering 118 countries from January 1 to April 13, 2021, this research examines the relationship between the government response stringency index (GRSI) and COVID-19 pandemic. The empirical results show that GRSI significantly negatively impacts confirmed cases, and the effects are especially larger around 14 to 21 days after the implementation of the government response. These results are robust through analysis with sub-samples of Asian countries and non-Asian countries, proving that public prevention policies of being isolated for 14 days and being observed for 7 days are effective. The Dumitrescu-Hurlin causality test uncovers a statistically significant bi-directional correlation between government response stringency and COVID-19 pandemic when analyzing the full samples. In terms of the sub-samples, a bi-directional relationship exists between government response stringency and confirmed cases, while one-way causality runs only from government response stringency to deaths in Asian countries. We offer a policy implication that countries all over the world should continue to carry out public prevention policies, and governments in non-Asian countries should be more concerned about confirmed cases.

Association of an IGHV3-66 gene variant with Kawasaki disease.

In a meta-analysis of three GWAS for susceptibility to Kawasaki disease (KD) conducted in Japan, Korea, and Taiwan and follow-up studies with a total of 11,265 subjects (3428 cases and 7837 controls), a significantly associated SNV in the immunoglobulin heavy variable gene (IGHV) cluster in 14q33.32 was identified (rs4774175; OR = 1.20, P = 6.0 × 10-9). Investigation of nonsynonymous SNVs of the IGHV cluster in 9335 Japanese subjects identified the C allele of rs6423677, located in IGHV3-66, as the most significant reproducible association (OR = 1.25, P = 6.8 × 10-10 in 3603 cases and 5731 controls). We observed highly skewed allelic usage of IGHV3-66, wherein the rs6423677 A allele was nearly abolished in the transcripts in peripheral blood mononuclear cells of both KD patients and healthy adults. Association of the high-expression allele with KD strongly indicates some active roles of B-cells or endogenous immunoglobulins in the disease pathogenesis. Considering that significant association of SNVs in the IGHV region with disease susceptibility was previously known only for rheumatic heart disease (RHD), a complication of acute rheumatic fever (ARF), these observations suggest that common B-cell related mechanisms may mediate the symptomology of KD and ARF as well as RHD.

Epidemics and electricity CO2 emissions: a feedback investigation.

We examine the short-term and long-term causal effects between epidemics and electricity CO2 emissions by using panel data from 30 countries over the period of 1990 to 2017. The results show that there is bidirectional relationship between epidemics and electricity CO2 emissions, especially in OECD and Asian countries.

Spillover effect between carbon spot and futures market: evidence from EU ETS.

The spillover effects of European Union Allowances (EUA) spot and futures markets are important for investors in order to understand the relevance and risk management of product prices. This paper uses non-linear methods of Granger causality to test the mean spillover relationship between the two markets and then analyzes volatility spillovers between the two by the non-linear TVP-VAR spillover index. The results show that (1) the non-linear Granger causality test better reflects the mean spillover relationship between EUA spot and futures; (2) there is a bidirectional non-linear mean spillover effect between EUA spot and futures prices for the European Union Emissions Trading Scheme (EU ETS) phases II and III; and (3) volatility spillovers, appearing in EUA spot and future markets in both phases, work increasingly strong over time and are vulnerable to financial crises and extreme events.

Comparative study between deep learning and QSAR classifications for TNBC inhibitors and novel GPCR agonist discovery.

Machine learning is a well-known approach for virtual screening. Recently, deep learning, a machine learning algorithm in artificial neural networks, has been applied to the advancement of precision medicine and drug discovery. In this study, we performed comparative studies between deep neural networks (DNN) and other ligand-based virtual screening (LBVS) methods to demonstrate that DNN and random forest (RF) were superior in hit prediction efficiency. By using DNN, several triple-negative breast cancer (TNBC) inhibitors were identified as potent hits from a screening of an in-house database of 165,000 compounds. In broadening the application of this method, we harnessed the predictive properties of trained model in the discovery of G protein-coupled receptor (GPCR) agonist, by which computational structure-based design of molecules could be greatly hindered by lack of structural information. Notably, a potent (~ 500 nM) mu-opioid receptor (MOR) agonist was identified as a hit from a small-size training set of 63 compounds. Our results show that DNN could be an efficient module in hit prediction and provide experimental evidence that machine learning could identify potent hits in silico from a limited training set.

The impact of international sanctions on environmental performance.

This paper studies the impact of international sanctions on environmental performance by using the panel fixed effect model for 22 sanctioned states over the period 2002-2016 while considering several cases of international sanctions (unilateral, plurilateral, U.S., EU, UN, economic, and intensity) and measures environmental performance by the Environmental Performance Index (EPI). Overall, we find that the imposition of unilateral, plurilateral, U.S., EU, and economic sanctions has a significantly negative impact on EPI, dropping their EPI scores respectively by 0.114, 0.060, 0.045, 0.084, and 0.063, while a level increase of intensity results in EPI dropping by 0.028. Moreover, the simultaneous-equation models and Sobel tests show that the intermediate effect about GDP between international sanctions on environmental performance is significantly negative. We believe that our empirical findings can contribute to policy formulation by those sanctioned countries.

Fiscal decentralization, environmental regulation, and pollution: a spatial investigation.

To investigate the effects of regulation on environmental pollution under Chinese-style fiscal decentralization, this research analyzes annual data over the period 2003 to 2017 covering 30 provinces in China with the spatial economic model. The empirical results show significant spatial agglomeration effects on the emissions of wastewater, sulfur dioxide, and solid waste. Environmental regulation helps reduce discharge of wastewater and solid waste, but does not help reduce the emission of sulfur dioxide; because there is significantly positive externality in treating pollutants with high fluidity, cost is larger than revenue for local governments. The relationship between fiscal decentralization and pollutants shapes an inverted U-shaped curve. We finally offer some implications in accordance with our empirical finding, such as the intensity of environmental regulation should be suitable for economic development, different measures should be taken based on the fluidity of pollutants, and a new evaluation system should be established.

The relationship between shale gas production and natural gas prices: An environmental investigation using structural breaks.

This paper investigates the long-run cointegration relationship between shale gas production and natural gas prices during the period from January 2007 to December 2016 for 16 states in the U.S., by utilizing the Generalized Least Squares (GLS) based univariate unit root test, the PANICCA panel unit root test, the cointegration tests of Gregory and Hansen (1996), Westerlund and Edgerton (2008) as well as Banerjee and Carrión-i-Silvestre (2015) tests with structural breaks. The empirical finding shows that the mean-reverting property exists in both variables, and most structural breaks emerge around 2007-2009 and 2011-2014, during the period when shale gas production sharply increased, the global financial crisis erupted, and external energy shocks emerged. We also find a strong cointegrated relationship, denoting a long-run equilibrium property appears among the variables. Overall, we demonstrate an interaction nexus between price and production variables and put forward some vital implications for authorities and gas market participants.

Inhibition of SARS-CoV-2 by Highly Potent Broad-Spectrum Anti-Coronaviral Tylophorine-Based Derivatives.

Tylophorine-based compounds and natural cardiotonic steroids (cardenolides and bufadienolides) are two classes of transmissible gastroenteritis coronavirus inhibitors, targeting viral RNA and host cell factors, respectively. We tested both types of compounds against two types of coronaviruses, to compare and contrast their antiviral properties, and with view to their further therapeutic development. Examples of both types of compounds potently inhibited the replication of both feline infectious peritonitis virus and human coronavirus OC43 with EC50 values of up to 8 and 16 nM, respectively. Strikingly, the tylophorine-based compounds tested inhibited viral yields of HCoV-OC43 to a much greater extent (7-8 log magnitudes of p.f.u./ml) than the cardiotonic steroids (about 2-3 log magnitudes of p.f.u./ml), as determined by end point assays. Based on these results, three tylophorine-based compounds were further examined for their anti-viral activities on two other human coronaviruses, HCoV-229E and SARS-CoV-2. These three tylophorine-based compounds inhibited HCoV-229E with EC50 values of up to 6.5 nM, inhibited viral yields of HCoV-229E by 6-7 log magnitudes of p.f.u./ml, and were also found to inhibit SARS-CoV-2 with EC50 values of up to 2.5-14 nM. In conclusion, tylophorine-based compounds are potent, broad-spectrum inhibitors of coronaviruses including SARS-CoV-2, and could be used for the treatment of COVID-19.