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Myeloid-derived suppressor cells (MDSCs) contribute to immune activity suppression and promote the tumor progression. Elimination of MDSCs is a promising cancer therapeutic strategy, and some chemotherapeutic agents have been reported to hamper tumor progression by suppressing MDSCs. Juglone has been showed to exert a direct cytotoxic effect on tumor cells. However, the effect of juglone on MDSCs and anti-tumor immune statue has remained unexplored. In our study, we observed that juglone suppressed tumor growth and metastasis markedly, and the tumor growth suppression in immunocompetent mice was more drastic than that in immunodeficient mice. Juglone reduced the accumulation of MDSCs and increased IFN-γ production by CD8+ T cells. Consistently, juglone affected myeloid cells differentiation and maturation, impairing the immunosuppressive functions of MDSCs. Moreover, juglone down-regulated the level of IL-1β which was mediating accumulation of MDSCs. In addition, juglone inhibited 5FU-induced liver injury in a colorectal carcinoma-bearing mice model. Thus, our work suggests that the anti-tumor effect of juglone is mediated, at least in part, by eliminating accumulation of MDSCs.

The capability of laccase to oxidate a broad range of polyphenols and aromatic substrates in vitro offers a new technological option for the remediation of polycyclic aromatic hydrocarbon (PAH) pollution with high cytotoxicity. However, laccase application in the remediation of PAH-contaminated sites mainly suffers from a low oxidation rate and high cost because of the difficulty in its recovery. In this study, laccases were immobilized on magnetic Fe

Parkinson's disease (PD) is a usual disease caused by degeneration of the central nervous system, which features the denaturation and death of dopaminergic neurons in the substantia nigra compact (SNc) of the midbrain. Neuroinflammation casts a consequential role in its pathogenesis, and the excessive activation of microglia as a major part of neuroinflammation cannot be ignored. Studies have indicated that Hordenine (HOR) functioned widely as an anti-oxidant and anti-inflammatory substance, but there are no reports on neuroinflammation effects. Therefore, this study is devoted to exploring the effect of HOR on neuroinflammation and its specific mechanism. In vivo, results revealed that HOR depressed the activation of microglia in SNc and protected dopaminergic neurons in the 6-hydroxydopamine (6-OHDA)-induced PD rat model, which terminally reduced movement disorders and weight loss. In vitro, studies have shown that HOR can inhibit inflammatory responses triggered by lipopolysaccharide (LPS) in BV-2 cells. More profound studies have discovered that the specific anti-inflammatory mechanism is intimately associated with the NF-κB and MAPK signaling pathways. All in it together, HOR acts as a significant role in preserving dopaminergic neurons by restraining neuroinflammation mediated by activation of microglia. This may provide a potential drug for Parkinson's treatment.

In quasi-linear environments, classic theories state that it is possible to design efficient and incentive-compatible mechanisms, such as Vickrey, Clarke and Groves (VCG) mechanisms. However, once financial constraints are taken into account, we find that almost no financial constraint is compatible with efficiency and individual incentives over unrestricted domains and some restricted domains. Therefore, our results imply that even in quasi-linear environments, it is still impossible to design an efficient and incentive compatible mechanism because of financial constraints.

This paper proposes a model of delegated portfolio management, in which professional fund managers face a value-at-risk (VaR) constraint. We show that the existence of the VaR constraint impairs the optimal risk sharing in both the trading and delegation stages. As a result, the VaR constraint leads household investors to take excessive risk and may cause the prices of fundamentally uncorrelated assets to be correlated.

Whether stock prices are predictable has been the center of debate in academia. In this paper, we propose a hybrid model that combines a deep learning approach with a sentiment analysis model for stock price prediction. We employ a Convolutional Neural Network model for classifying the investors’ hidden sentiments, which are extracted from a major stock forum. We then propose a hybrid research model by applying the Long Short-Term Memory (LSTM) Neural Network approach for analyzing the technical indicators from the stock market and the sentiment analysis results from the first step. Furthermore, this work has conducted real-life experiments from six key industries of three time intervals on the Shanghai Stock Exchange (SSE) to validate the effectiveness and applicability of the proposed model. The experiment results indicate that the proposed model has achieved better performance in classifying investor sentiments than the baseline classifiers, and this hybrid approach performs better in predicting stock prices compared to the single model and the models without sentiment analysis.

We study a housing market with household buyers, speculative investors and property developers in a Walrasian scenario. We show that in addition to the factors that affect the real demand of household buyers and the development cost of property developers, investors' speculative behavior is an important factor explaining housing price evolution and dynamics. In particular, investors' extrapolative expectations may drive the housing price to persistently deviate from its benchmark value and even to explode. In contrast, investors' mean-reverting strategy can balance out the position of trend extrapolators, which may stabilize an otherwise explosive housing market. Moreover, the evolutionary process of housing prices driven by investors' speculative behavior is path-dependent in the sense that different initial market conditions may result in different price paths, which corresponds to the localization property empirically documented in the real housing market. In addition, within the stylized model, we provide some policy implications through analyzing the limitation and effectiveness of policy adjustments via down payment and development cost, and find that the decrease of development cost is a better measure to adjust the housing market when it booms or busts.

Calcium peroxide (CaO 2 ), as one of the solid peroxides, has been increasingly used in contaminated site remediation due to its ability to release oxygen (O 2 ) and hydrogen peroxide (H 2 O 2 ). Biodegradation can be enhanced by the existence of O 2 . Hydrogen peroxide can be used to for in situ chemical oxidation via the modified Fenton. Previous studies show inconsistent results about O 2 and H 2 O 2 release during CaO 2 decomposition. Additionally, the release characteristics of O 2 and H 2 O 2 are not evaluated in detail. A series of batch experiments was conducted to investigate the properties of CaO 2 decomposition and the release kinetics of O 2 and H 2 O 2 . O 2 and H 2 O 2 were released directly from CaO 2 dissolution and H 2 O 2 was not an essential intermediate in the conversion of CaO 2 to O 2 . The two release paths formed a parallel reaction system, with a competitive relationship between the two paths. The release of H 2 O 2 and O 2 followed a pseudo-zero-order kinetics pattern and a pseudo-first-order kinetics pattern, respectively. Increasing temperature and decreasing pH could accelerate both O 2 and H 2 O 2 release rate. However, increasing temperature could decrease the H 2 O 2 yield and increase the O 2 yield, which were similar to the impact of increasing pH.

Nitroaromatic compounds (NACs) are one class of typical refractory biodegradable organic pollutants detected in various environmental media. The reductive transformation of NACs by the electrochemically active bacterium Shewanella oneidensis MR-1 is a possible and cost-effective option for the removal of NACs. However, little information on the respiratory pathway employed by S. oneidensis MR-1 to reduce NACs is available. In the present study, we investigated the reduction of NACs with different nitro or alkyl moieties by S. oneidensis MR-1 and eight constructed mutants with the deletion of the mtrA, mtrB, mtrC/omcA, cymA, napA, napB, nrfA, and nfnB genes to explore these key functional enzymes. The reduction of nitrobenzene, 4-nitrotoluene, 4-ethylnitrobenzene, 1-tert-butyl-4-nitrobenzene, 1,2-dinitrobenzene, 1,3-dinitrobenzene, 1,4-dinitrobenzene, 2,4-dinitrotoluene, 2,6-dinitrotoluene and 2,4,6-trinitrotoluene occurs via both the Mtr respiratory pathway and NfnB related pathway. However, 2,5-ditertbutyl-nitrobenzene, 2-nitrobiphenyl and 2,2'-dinitrobiphenyl are reduced only via the Mtr respiratory pathway. The van der Waals volume of NACs was the key factor in determining the reduction by S. oneidensis MR-1 according the correlation analysis. Our study provides new insights into the environmental adaption of S. oneidensis MR-1 and facilitates the bioremediation of NAC-related contamination.

The aim of this study was to develop a method for the in vitro separation and culture of Arbas Cashmere goat bone marrow stromal cells (gBMSCs). Arbas Cashmere gBMSCs were isolated and cultured in vitro, and cell surface markers were identified immunohistochemically. The gBMSCs were differentiated into neurocytes and osteoblasts, and the expression of neuron-specific enolase and osteocalcin was identified by immunohistochemistry. The gBMSCs and goat fetal fibroblast cells (gFFCs) were compared for transient transfection efficiency and fluorescent colony-forming efficiency with Arbas Cashmere gFFCs as a control. pDsRed2-1 encodes DsRed2, a variant of the Discosoma sp. red fluorescent protein (DsRed). In addition, the coding sequence for DsRed2 contains a series of silent base-pair changes for higher expression in mammalian cells. Of the gBMSCs-pDsRed2-1, one fraction was tested for pluripotency, whereas the other fraction was manipulated using somatic cell nuclear transfer, and the in vitro growth status of transgenic embryos derived from gBMSCs-pDsRed2-1 and gFFCs-pDsRed2-1 was compared. The findings showed that gBMSCs were isolated and amplified to express CD29, CD44, and CD90 through adherent culture, with no marked signs of aging after multiple passages. Expression of neuron-specific enolase and osteocalcin by gBMSCs and gBMSCs-pDsRed2-1 was strongly induced by neuronal and osteogenic differentiation, whereas the integrated exogenous genes did not influence pluripotency (P > 0.05). The transient transfection efficiencies of gBMSCs and gFFCs after 48 hours were not significantly different; however, the fluorescent colony-forming efficiency of gBMSCs-pDsRed2-1 after G418 screening was approximately 13% higher than that of gFFCs-pDsRed2-1. The convergence and cleavage rates of cloned embryos derived from gBMSCs-pDsRed2-1 were higher than those derived from gFFCs-pDsRed2-1, whereas their eight-cell and blastocyst rates were similar. The red fluorescent protein expression levels were higher in transgenic embryos derived from gBMSCs-pDsRed2-1 compared with those derived from gFFCs-pDsRed2-1 (48.8% vs. 31.1%, respectively) (P < 0.01). Real-time quantitative Polymerase Chain Reaction analysis showed that DsRed2-1 messenger RNA expression of cloned embryos derived from gBMSCs was 2.24 greater than that of embryos derived from gFFCs-pDsRed2-1 (P < 0.01). Similarly, Western blot analysis showed that DsRed2 protein expression of cloned embryos derived from gBMSCs-pDsRed2-1 was 1.29 greater than that of embryos derived from gFFCs-pDsRed2-1 (P < 0.01). In this study, gBMSCs were also used for somatic cell nuclear transfer and shown to provide effective nuclear donor cells for breeding new genetically modified varieties of livestock.

This paper formulates a continuous-time information transmission model in which an altruistic sender privately observes a stochastic state variable, and incurs a communication cost when she broadcasts a message. We characterize the sender's optimal announcement strategy using an ordinary differential equation. We prove the optimality of the sender's strategies using a martingale verification argument and show that the sender's optimal strategy involves sending discrete messages. Furthermore, we apply the model to the timing decision of credit rating announcements and provide a framework to study various aspects of rating announcements, such as the probability of rating reversals and the expected time before a rating change.

This paper studies the use of incentive contracts in the Bolton–Scharfstein model when some agents in the population are technically constrained from falsifying reports and stealing cash [Bolton, P., Scharfstein, D., 1990. A theory of predation based on agency problems in financial contracting. Amer. Econ. Rev. 80, 94–106]. The original Bolton–Scharfstein contract may not be optimal for a large range of parametric values. The optimal contract may induce falsification and stealing in equilibrium and social welfare may be improved. Moreover, the optimal contract does not screen different types of agents. Empirical implications for various types of staged-contracts are discussed.

In this paper, we study a costly information transmission problem in the continuous time domain. We formulate a model that incorporates broadcasting costs, misaligned incentives between the information sender and receiver, receiver's naivety, and penality costs of misrepresenting information. We derive the Hamilton-Jacobi equation associated with this stochastic control problem and characterize the sender's optimal strategy. Two specific model settings are examined here. The infinite time horizon case is solved analytically while the finite time horizon case is solved numerically. Furthermore, this paper includes a practical application of the proposed model to the stock recommendation analysis, which is also solved numerically. The sensitivity of the numerical solution to model parameters is analyzed.

The large amount of leverage used by institutional investors and retail investors, corporations and households, is frequently cited as a major contributor of the current financial crisis. Recent events highlight the importance of leverage management, and the painful decision to de-leverage, especially when the market conditions may change drastically. Many institutional investors and university endowments managers debated heavily whether they should reduce leverage, or decrease their positions in risky asset holdings in a market downturn.Should an investor unwind his portfolio in the face of changing economic conditions?We completely characterize an investor's optimal trading strategy in the presence of transaction costs in an economy that switches stochastically between two market conditions. We show that absent transactions cost, the investor acts myopically in each market, as if the other market did not exist, and invests a constant fraction of wealth in stock and bond. With transaction cost, we find that de-leveraging, reducing the degree of leverage, or keeping leverage unchanged can all be optimal outcomes as the market switches from a "bull" regime with high expected return and low volatility to a "bear" regime with low expected return and high volatility. The investor's strategy depends crucially on the switch intensities between the two markets.If the switch intensity is high from the "bear" market to the "bull" market, leverage may be optimal even in the "bear" market. On the other hand, if this switch intensity is low, the investor may choose not to leverage at all in both markets. Furthermore, we find that it may be optimal for the investor not to sell off his illiquid asset in the "bear" market to reduce leverage. In addition, the investor may optimally increase leverage in the "bear" market for illiquid asset to avoid frequent re-balancing as the market switches conditions. This is in sharp contrast to the one market case where a higher transaction cost always implies a lower optimal leverage. We also show that a lower borrowing cost may also encourage the investor to keep his stock position and avoid sell offs.

This paper formulates a continuous time information transmission model in which an altruistic sender privately observes a stochastic state variable, and incurs a communication cost when she sends a message. We study three issues associated with this costly information transmission: 1) The sender's optimal strategy involves sending discrete messages; 2) With pre-fixed ranking intervals, the sender optimally sets a tolerance band around the cutoff point of each interval; 3) The optimal announcement frequency is characterized. We also propose to use this model to study the tradeoff between rating accuracy and stability.

I study the role of reputation in a multi-stage strategic information transmission game between an analyst and an investor. Absent reputation concerns, a biased analyst does not communicate any information in equilibrium. The unbiased analyst can credibly reveal all but sufficiently good information. In the multi-stage game, (i) when a biased analyst misrepresents her information, she will elevate a set of the worst stocks to the strongest recommendation; (ii) both types of analysts will misrepresent less frequently when they have a higher reputation; and (iii) misrepresentation happens more frequently when there is more market uncertainty.

This study re-examines the performance of analyst recommendations on newly public firms. Specifically, we examine the return performance associated with the stock recommendations of both underwriter and unaffiliated analysts. Using post-recommendation returns of IPO offerings during the period 1993 through 2002, we document that (i) Strong Buy recommendations by lead underwriter analysts exhibit inferior performance relative to those of non-lead analysts. The differences in post-recommendation returns between lead and non-lead underwriters do not persist in any of the other recommendation categories; (ii) the long-term underperformance of underwriter analysts' recommendations increases with the difference between the event-period market reactions towards positive and negative recommendations; (iii) the underperformance of lead-underwriter analysts' Strong Buy recommendations increases with aggregate market uncertainty. These results are consistent with a dynamic cheap talk game where analysts facing conflicts of interest and reputation consequences are more likely to elevate a subset of the worst stocks to the strongest category when the short-term incentive becomes sufficiently strong.