Carbazole and tetrahydro-carboline derivatives as dopamine D_(3) receptor antagonists with the multiple antipsychotic-like properties

Dopamine D_(3) receptor(D_(3)R)is implicated in multiple psychotic symptoms.Increasing the D_(3)R selectivity over dopamine D_2 receptor(D_2R)would facilitate the antipsychotic treatments.Herein,novel carbazole and tetrahydro-carboline derivatives were reported as D_(3)R selective ligands.Through a structure-based virtual screen,ZLG-25(D_(3)R K_i=685 nmol/L;D_2R K_i>10,000 nmol/L)was identified as a novel D_(3)R selective bitopic ligand with a carbazole scaffold.Scaffolds hopping led to the discovery of novel D_(3)R-selective analogs with tetrahydro-β-carboline or tetrahydro-γ-carboline core.Further functional studies showed that most derivatives acted as h D_(3)R-selective antagonists.Several lead compounds could dose-dependently inhibit the MK-801-induced hyperactivity.Additional investigation revealed that 23j and 36b could decrease the apomorphine-induced climbing without cataleptic reaction.Furthermore,36b demonstrated unusual antidepressant-like activity in the forced swimming tests and the tail suspension tests,and alleviated the MK-801-induced disruption of novel object recognition in mice.Additionally,preliminary studies confirmed the favorable PK/PD profiles,no weight gain and limited serum prolactin levels in mice.These results revealed that 36b provided potential opportunities to new antipsychotic drugs with the multiple antipsychotic-like properties.

Long-term system load forecasting based on data-driven linear clustering method

In this paper, a data-driven linear clustering(DLC) method is proposed to solve the long-term system load forecasting problem caused by load fluctuation in some developed cities. A large substation load dataset with annual interval is utilized and firstly preprocessed by the proposed linear clustering method to prepare for modelling.Then optimal autoregressive integrated moving average(ARIMA) models are constructed for the sum series of each obtained cluster to forecast their respective future load. Finally, the system load forecasting result is obtained by summing up all the ARIMA forecasts. From error analysis and application results, it is both theoretically and practically proved that the proposed DLC method can reduce random forecasting errors while guaranteeing modelling accuracy, so that a more stable and precise system load forecasting result can be obtained.

A Reinforcement-learning-based Bidding Strategy for Power Suppliers with Limited Information

The power market is a typical imperfectly competitive market where power suppliers gain higher profits through strategic bidding behaviors.Most existing studies assume that a power supplier is accessible to the sufficient market information to derive an optimal bidding strategy.However,this assumption may not be true in reality,particularly when a power market is newly launched.To help power suppliers bid with the limited information,a modified continuous action reinforcement learning automata algorithm is proposed.This algorithm introduces the discretization and Dyna structure into continuous action reinforcement learning automata algorithm for easy implementation in a repeated game.Simulation results verify the effectiveness of the proposed learning algorithm.

日本人类学东南亚区域研究的历程与范式转换

东南亚区域研究是日本人类学界借以确立自身主体性的方法,也是日本知识界沟通世界,生产独创性知识的重要场域。在帝国早期的日本,针对东南亚的人类学研究主要服务于殖民统治,试图论证日本民族起源假说。二战结束后直到20世纪80年代中期,该领域研究的发展与日本的民族国家建设和经济发展相契合,逐步确立了社会文化研究的学科规范,并试图相对客观地认识东南亚。20世纪八九十年代以后,对该领域的研究越来越重视实践应用与现实关怀,倡导连接“自我”与“他者”,共同面对日益深刻的全球性问题,积极推动人类学知识向研究者和研究对象所在社会的公共回归,即所谓“知识的社会还原”。日本人类学的东南亚区域研究在不断反思“自我”与“他者”的关系过程中,完成了从自证(证明自己是谁)、证他(证明他者是谁)到两全(自我与他者相互成全)的范式转换。

基于结构设计的新型mTOR抑制剂的抗宫颈癌活性研究

激酶mTOR是PI3K-AKT信号通路的关键组成部分,该激酶在宫颈癌细胞中被高度激活。本文运用基于结构的药物发现等手段发现了一系列mTOR激酶抑制剂并对其进行生物学评价,发现其可发挥有效的抗宫颈癌作用。酶活性测定结果显示化合物C3具有潜在的mTOR抑制作用(IC50=1.57μM)。随后利用分子对接和动力学模拟探究并预测m TOR激酶和C3的结合模式,初步探讨了化合物的构效关系。在多种肿瘤细胞系上进行细胞增殖活性实验时发现,C3对宫颈癌细胞He La表现出较好的增殖抑制活性(IC50=0.38μM)。此外, C3还能浓度依赖性地降低磷酸化核糖体S6 (p-S6)蛋白在HeLa细胞内的表达水平。值得注意的是,C3发挥显著的抗宫颈癌活性很有可能是mTOR通路和其他细胞内通路的共同作用。本研究表明C3可进一步开发为宫颈癌的治疗药物。

Bone-targeting melphalan prodrug with tumor-microenvironment sensitivity： Synthesis, in vitro and in vivo evaluation

Bone tumor is a refractory neoplastic growth of tissue in bone. According to the unique environment and phys-chemical characteristics of bone tissues, the chemotherapeutic agents are unlikely to prolong the survival of patients and often associated with systemic side effects. The bone targeting drug delivery via systemic administration may provide both better treatment efficacy and less frequent administration. In this study, we describe the synthesis, in vitro and in vivo evaluation of novel melphalan-bisphosphonate hybrids, with a tumor microenvironment sensitive linkage, which could be enzymatic activation under tumor microenvironment conditions. We have also evaluated the in vitro targeting efficiency of these prodrugs via the affinity of hydroxyapatite （HA） and cellular proliferation. The in vivo distribution suggested the bisphosphonate conjugated prodrugs with high bone selectivity.

Extraction of 17β-estradiol in water using non-imprinted polymer submicron particles in membrane filters

17β-Estradiol （E2） is an endocrine disrupting chemical of harm to both animals and human beings at a low concentration level （ng/L）. It cannot be completely removed by wastewater treatments, and is often detected in both environment and drinking waters. The purpose of this feasibility study, towards environmental engineering in the field of water analysis and treatment, was to remove E2 by extraction using non-imprinted polymer （NIP） submicron particles. Experimental results showed that 0.5 mg/L of E2 could be completely extracted by adding 10 mg of NIP particles directly into 10 mL of water. However, the extraction efficiency decreased to 64% for 100 mL of water. prefilling the NIP particles inside a membrane filter showed a potential for water treatment of a large volume, requiring no effort to distribute the particles uniformly in the water. High extraction efficiency （80 ± 10）% for E2 was achieved for 100 mL of water. A total mass of 0.29 mg E2 was extracted from 1000 mL of water containing 0.8 mg/L E2 （by using only 10 mg of NIP particles）. Both efficiency and mass capacity can be increased, by scaling up the amount of NIP particles, towards environmental engineering applications.