Search

Designing novel anticancer non-platinum metal agents is fully challenging. Herein, a series of little-known indium (In) 2-acetylpyridine thiosemicarbazone compounds as potential anticancer agents were designed, synthesized, and characterized. The hydrogen atoms at the N-4 position with the alkyl of the In compounds significantly increased cellular uptake and cytotoxicity. In(III) compounds showed significantly higher cytotoxicity toward cisplatin-resistant cell lines than cisplatin. More importantly, C4 greatly inhibited A549DDP tumor growth in a vaccinated mouse model. C4 exerted cytotoxic effects

Purpose To investigate the synergistic effect of vitamin D and neferine on the growth and metastasis of colorectal cancer (CRC). Methods The synergistic effect of biologically active form of vitamin D, VD3 and neferine on the treatment of CRC was investigated by bliss analysis. Colony formation and wound healing ability, migration and invasion ability, and epithelial mesenchymal transition of HCT-116 cells, as a response to the combination treatment with VD3 and neferine were evaluated. Results VD3 and neferine showed a synergistic effect on CRC cell growth at a relatively low dose. The wound healing and colony formation capacity, cell migration and invasion abilities were all decreased by combination use of VD3 and neferine, compared to the VD3 or neferine treated single group. Furthermore, VD3 and neferine significantly decreased the expressions of N-cadherin, vimentin, snail, and slug in HCT-116 cells. Conclusion These data suggest that neferine enhances the anticancer capability of VD3 and reduces the dose dependency of VD3. The combination of vitamin D with neferine appears to be a potential therapeutic strategy for CRC.

Effective delivery of anticancer agents across the blood-brain barrier (BBB) required innovative strategies to achieve glioma regression. To resolve this problem, we proposed to develop a metal agent that target and treat glioma based on the unique property of apoferritin (AFt) nanoparticles (NPs). Thus, we synthesized a series of Au(III) 3-(4-metyl piperidine)thiosemicarbazides compounds and analyzed their structure-activity relationships, obtaining a Au agent (C6) with remarkable cytotoxicity in glioma. Moreover, we confirmed that C6 kills glioma cells by inducing lethal autophagy and apoptosis. Importantly, our results revealed that the successfully constructed apoferritin-C6 NPs (AFt-C6 NPs) can effectively cross the BBB, inhibit glioma growth, and selectively accumulate in tumors.

To effectively integrate diagnosis and therapy for tumors, we proposed to develop an indium (In) agent based on the unique property of human serum albumin (HSA) nanoparticles (NPs). A novel In(III) quinoline-2-formaldehyde thiosemicarbazone compound (C5) was optimized with remarkable cytotoxicity and fluorescence to cancer cells

Smart community is an important constituent part of a smart city and an extension and deepening of the concept of the latter. When it comes to smart community, the digitalization upgrading of traditional community service is conducted via information technology, in an effort to improve the service experience of community residents and elevate their happiness index. From social functions, smart community also has the advantages in facilitating the smart transformation of cities, promoting the harmonious society construction, and improving governmental efficiency and image, among others. However, various problems persist in the construction and development process of a smart community, such as mismatching service contents and low service quality. To explore the influencing factors of smart community service quality, a total of 16 influencing factors were extracted from 5 dimensions: service object, service subject, government role, management system, and service content. The relationships among the influencing factors were analyzed via the decision-making trial and evaluation laboratory (DEMATEL)-interpretative structural modeling (ISM) composite model, and a multi-order explanation model was constructed for these influencing factors. Result shows that the legal guarantee is the root cause influencing the smart community service quality. Development standard, basic service, and expected service are deep influencing factors that play mediating roles. Middle-layer factors such as service and operating systems have a direct bearing on quality perception. The surface-layer factors directly decide residential assessment on the smart community service quality. This study has also manifested the feasibility of the integrated DEMATEL-ISM method in analyzing the action mechanism of influencing factors for smart community service quality, providing a new analytical idea and modeling method for the smart community service quality.

Extensive research effort has been put in pentacyclic triterpenoids due to their numerous biological activities. However, their poor water solubility and low oral bioavailability limit their antitumor effects in vivo. To address these issues, 37 triterpenoid acid derivatives linked to l-phenylalanine or l-proline were designed and synthesized in this study. Structure-activity relationship (SAR) studies found two promising glycyrrhetinic acid (GA) derivatives 11 and 16. Compound 11 was obtained by C3-OH esterification and C30-COOH modification with l-phenylalanine while 16 was obtained by attaching C3-OH with l-phenylalanine. Compounds 11 and 16 exhibit up to 48- and 120-fold improvement respectively compared with the IC

To effectively treat gastric cancer, we innovatively attempted to develop a metal agent to integrate immunotherapy and chemotherapy by dual targeting the cellular components in the tumor microenvironment (TME) based on the specific residue of human serum albumin (HSA) nanoparticles (NPs). We synthesized a series of Au(III) α-N-heterocyclic thiosemicarbazone compounds and obtained a Au agent (5b) with remarkable cytotoxicity to gastric cancer cells; moreover, we successfully constructed a novel HSA-5b complex NP delivery system. Importantly, the in vivo results showed that 5b/HSA-5b NPs effectively inhibited gastric tumor growth and HSA-5b NPs enhanced the therapeutic efficiency, bioavailability, and targeting ability compared with those of 5b alone. Furthermore, the in vitro/in vivo results revealed that 5b/HSA-5b NPs could integrate chemotherapy and immunotherapy by synergistically attacking two different cellular components in TME at the same time, namely, polarizing the tumor-associated macrophages and inducing apoptosis of gastric cancer cells.

Temporary plugging and diversion technology is simple in operation, low in overall cost, good in adaptability under different target conditions and low in construction risk. It has been widely used in Hydraulic fracturing in China. In the process of Hydraulic fracturing, timely and appropriate temporary plugging agent can effectively plug the fully transformed area, retransform the incomplete transformed area, increase the fracture contact area, improve the fracture complexity, finally realize the full coverage of the transformed section, improve the operation efficiency, and ultimately create economic benefits. The application examples of temporary plugging diversion technology in the three well conditions of refracturing well, casing variable well and infill perforation well are analyzed and summarized. The characteristics of fracturing curve and microseismic monitoring show that the microseismic events increase in most of the well reconstruction section after temporary plugging, and the improvement effect is obvious.

The anticancer function and anticancer mechanism of indium (In) complexes still remain mysterious to date. Furthermore, it is greatly challenging to design a multi-functional metal agent that not only kills cancer cells but also inhibits their invasion and metastasis. Thus, to develop novel next-generation anticancer metal agents, we designed and synthesized a series of novel In(iii) 2,6-diacetylpyridine bis(thiosemicarbazide) complexes (C1-C4) for the first time and then investigated their structure-activity relationships with human urinary bladder cancer (T-24) cells. In particular, C4 not only showed higher cytotoxicity to cancer cells and less toxicity toward normal cells relative to cisplatin but also inhibited cell invasion and metastasis of T-24 cells. Interestingly, C4 acted against T-24 cells exhibiting multiple mechanisms: (1) arresting the S-phase of cell cycle via regulation of cytokine kinases, (2) activating the mitochondrial-mediated apoptosis, endoplasmic reticulum-stress-mediated cell death, PERK and c-Jun N-terminal kinase 1 (JNK) cell signaling pathways, and (3) inhibiting the expression of telomerase via the regulation of c-myc and h-TERT proteins. Our results suggested that C4 may be developed as a potential multi-functional and multi-targeting anticancer candidate.

Social companions, including virtual humans and social robots, have attracted increasing attention in recent years. The social companions interact with users in a social and humanlike way that makes them believable and trustable. Recent studies have investigated the problem that people tend to feel bored and lose interest rapidly in the first few interactions with social companions. Thus, many studies have started to improve the capabilities of the social companions to preserve user engagement over long-term period. Such companions are required to display consistent personalities in interactions and remember what has happened in the past with particular users. Therefore, our research here focuses on designing the affective system and the episodic memory model, and studies how to integrate them compatibly with social companions to improve user engagement in interactions. Specifically, we have studied (1) how to design a general system architecture for social companions with necessary modules and connections; (2) how to design an affective system to express specific personalities by organizing emotional behaviors in particular patterns, (3) how to design an episodic memory model with more comprehensive similarity measure that can both improve the agent performance in tasks and the user engagement in social companion interactions, and (4) how to construct a benchmark for episodic memory models designed for free-dialog based social companion interactions. Firstly, we propose a general system architecture for social companions to achieve engaging interactions. The architecture can be shared by our virtual human and our social robot. It is composed of three main components: perception, internal processing and action. Each component contains multiple interconnected modules. The affective system and the episodic memory are two important modules in this architecture which model human-like behaviors and intelligence. The communication and synchronization among the modules are deliberated in this work. Secondly, we propose the personality-characterized mood dynamics (PCMD) model to achieve consistent emotional behavior patterns that reflect particular personalities of a social companion. To connect static personalities and dynamic behaviors, we introduce the mood as an intermediate concept. With well-designed rules of mood-driven behaviors, we transform the problem of personifying behavior patterns to the problem of personifying mood dynamics. This is then formulated as an optimization problem, the objective function of which is constructed in a way that the overall mood converges to the personality after sufficient interactions. Thirdly, we propose a mixed-correlation-analysis based episodic memory (MCAEM) model to improve memory retrieval accuracy. Specifically, we make analysis of correlations of memory elements by considering relations between elements, weights (importance) of attributes and order of events. An overall similarity measure is proposed based on the mixed correlation analysis. The proposed similarity measure can improve retrieval accuracy and thus further support higher-level capabilities. We validate the MCAEM model in two applications. First, the MCAEM model provides agents with better abilities of item finding, weapon selection and decision making which improve their performance in the Unreal Tournament 2004 (UT2004) game. Second, the proposed model has enhanced the user experience in social companion interactions in various aspects. Finally, we construct a benchmark from movie scripts (BMS) to measure the retrieval performance of episodic memory models designed for free-dialog based social companion interactions. We build a dataset with 4,889 episodes that contain 38,058 attribute values and 76,123 events extracted from 106 movie scripts. Besides sentences in subtitles, our episodes also contain sequences of events constituted by attributes like subjects, objects, time, locations and emotion polarities. The benchmark is much more complicated compared to datasets in small domains as a result of considering words as additional attributes. To simulate real-world interactions, the retrieval cues are generated with noise and incompleteness. We analyze the consistency between the results of executing different models on our benchmark and on previous benchmarks. In addition, we also compare the proposed MCAEM model with two previous episodic memory models by evaluating them on our benchmark. Doctor of Philosophy (SCE)

To cause tumor regression by acting against cancer cells and inhibiting neovascularization in the tumor microenvironment, we constructed human serum albumin (HSA)-based delivery systems of 2-acetylpyridine-4,4-dimethyl-3-thiosemicarbazone-copper(II) [Cu(Ap44mT)]Cl and paclitaxel to improve both the therapeutic efficacy and the targeting ability in vivo. X-ray crystallography and matrix-assisted laser desorption/ionization time-of-flight mass spectra confirmed that [Cu(Ap44mT)]Cl complexed with HSA, whereas paclitaxel was tethered to the HSA complex by a linker sensitive to the active matrix metalloproteinase 2 (MMP2) protein. Up to 78% of paclitaxel was released from HSA within 2 h owing to MMP2 protein cleavage. In addition, a large amount of Cu(Ap44mT) was released from HSA in a pH 4.7 buffer. In vivo results revealed the following: (1) the tumor inhibitory rates of the HSA conjugate and the two-agent combination were 72.1 and 50.7%, respectively; (2) the inhibition rate of tumor angiogenesis of the HSA conjugate (73.3%) was higher than that of the two-agent combination (52.4%); (3) the increased amount of Cu in the tumor treated with the HSA conjugate was about 2-fold that in the tumor treated with the two-agent combination. Obviously, the HSA conjugate not only possessed a stronger capacity to inhibit neovascularization and the growth of liver tumors but also improved the targeting ability compared to the combination of the two agents alone.

It is a great challenge to design drugs that penetrate the blood-brain barrier to inhibit brain tumor growth by acting against multiple targets and also improve their delivery efficacy and targeting ability to cancer cells. To overcome the above problems, we designed a multitarget metal agent for treating brain tumors based on an human serum albumin (HSA)-cell penetrating peptide conjugate. Thus, we rationally screened copper (Cu) and 2-acetyl-3-ethylpyrazine thiosemicarbazones to synthesize six compounds, and we investigated their structure-activity relationships and confirmed multiple mechanisms for brain glioma cells. The HSA-6b complex structure indicated that 6b binds to the IIA subdomain of HSA and His242 replaces the Br ligand in 6b in coordination with Cu2+. In vivo data suggested that both 6b and the HSA-6b-peptide conjugate penetrate the blood-brain barrier and inhibit brain tumor growth with few side effects. Furthermore, the HSA-peptide conjugate also improved the delivery efficacy and targeting ability of 6b in vivo.

Herein, to develop a multi-target anticancer metal agent and achieve a “1 + 1 > 2” pharmaceutical effect, we rationally designed and synthesized five complexes (C1–C5) by synergistically exploiting the properties of Zn(ii) and a series of modified 2,6-diacetylpyridine bis(thiosemicarbazone) ligands. By investigating the structure–activity relationships, we found that the binuclear Zn(ii) complex (C5) acts against human bladder cancer cells (T-24) with significant cytotoxicity. We subsequently determined the multiple anticancer mechanisms of C5 to T-24 cells, including inhibiting the activity of topoisomerase I (Topo I), blocking the cell cycle in the S phase, and inducing apoptosis and autophagy in T-24 cells. Furthermore, C5 inhibited the migration of T-24 cells and showed a significant cytostatic effect in the T-24 3D spheroid model.

On the one hand, the multi-target agents have been promising for overcoming the deficiency of the single targeted anticancer metal agents, on the other hand, bismuth (Bi) complexes have shown significant antiproliferative activity and minimal side effects. Therefore, to develop the next-generation anticancer metal agents, we designed and synthesized four novel binuclear Bi(III) complexes by modifying the N-4 position of a series of 2-Acetyl-3-ethylpyrazine thiosemicarbazides, and then investigated their structure-activity relationships to human cancer cell lines, obtaining a lead Bi drug (C4) with significant antiproliferative activity to human bladder cancer cells (T24). C4 arrested the cell cycle in the S-phase by regulation of cyclin and cyclin-dependent kinases, and exerted a chemotherapeutic effect via multi-target mechanism including the activation of apoptotic and autophagic cell signaling pathways. Besides, C4 effectively inhibited metastasis of T24 cell. Our results suggested that C4 can be developed as a potential multi-target anticancer candidate.

This paper considers episodic memory for companion–human interaction, aiming at improving user experience of interactions by endowing social companions with awareness of past experience. Due to noise and incomplete cues from natural language and speech in real-world interaction, accurate memory retrieval is very challenging and the noise resistance is important in practice. To improve the robustness of companion–human interaction, we propose a mixed-correlation analysis-based episodic memory (MCAEM) model, in which the correlations between memory elements are analyzed and then utilized for memory retrieval. In particular, the correlations are analyzed in three aspects: the relations between elements, importance of attributes and order of events. Based on the mixed-correlation analysis, a new similarity measure is constructed, which has substantially enhanced the noise resistance of memory retrieval. Experiments on a dataset collected from interaction in movies quantitatively evaluate the MCAEM model and compare it with prior work. Also, a user study is conducted to investigate the benefits of integrating the MCAEM model into social companions. The results demonstrate that the companions equipped with the MCAEM model not only have better retrieval performance, but also improve user experience in many aspects. NRF (Natl Research Foundation, S’pore) Accepted version

How to endow the virtual characters with personalized behavior patterns remains a challenging problem. Instead of heuristically designing behaviors for certain personalities, this paper bridges the gap between personalities and behaviors using a medium concept, mood, to make the behaviors of the characters consistent enough to convey their personalities, while flexible enough to make appropriate response in various situations. We propose a personality-characterized mood dynamics model, in which the emotion weights are computed as a solution of a convex optimization problem that is constructed to make the overall mood approaches the personality after sufficient interactions. The convergence of the algorithm is demonstrated by numerical simulations. The implementation of the personality-characterized mood dynamics model enables an emotion-oriented virtual human, Sophie, to show personalized behaviors in the emotional interactions with users. Copyright © 2015 John Wiley & Sons, Ltd.

A virtual human is an effective interface for interacting with users and plays an important role in carrying out certain tasks. As social networking sites are getting more and more popular, we propose a Facebook aware virtual human. The social networking sites are used to empower virtual humans for interpersonal conversational interaction in this paper. We combine Internet world, physical world and 3D virtual world together to create a new interface for users to interact with an autonomous virtual human which can behave like a real modern human. In order to take advantages of social networking sites, virtual human gathers information of a user from its profile, its likes, dislikes and gauge mood from most recent status update. In two user studies, we investigated whether and how this new interface can enhance human---virtual human interaction. Some positive results concluded from these studies will be guidelines on research and development of future virtual human interfaces.

AgI/TiO 2 and Ag/TiO 2 porous nanostructures were synthesized using AgNO 3 , KI, thioglycollic acid, and tetrabutyl orthotitanate as a precursor. AgI nanoparticles were used as seeds to initiate the nucleation of a precursor TiO 2 shell, and thioglycollic acid acted as a hydrolysis inhibitor and porosity promoter. The hybridized samples were annealed at different temperatures. Porous AgI/TiO 2 nanostructures were formed at low annealing temperatures (300 and 400 °C). At 600 °C, the porous Ag/TiO 2 nanostructures exhibited a plasmon resonance effect. The formation mechanism of the different porous nanostructures was also investigated. Methylene blue solutions were used as wastewater to evaluate the visible-light photocatalytic activity of the samples. The porous nanostructured photocatalyst exhibited substantially high visible-light-induced photocatalytic activity for the photodegradation of methylene blue compared with pristine AgI and TiO 2 nanoparticles.

High thermal stability C-doped SiO 2 /TiO 2 coated with activated carbon (AC) nanoporous composites that exhibit high absorption capability and efficient visible light photocatalytic activity were synthesized. The silica particles serve as the cores, glycerol used as the carbon source and pore-forming promoter, and TiCl 4 used as the source of TiO 2 . The structure, crystallinity, morphology and other physical–chemical properties of the samples were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), Fourier transform-infrared spectroscopy (FT–IR), N 2 adsorption–desorption isotherms and UV–vis diffuse reflectance spectroscopy (UV–vis DRS). Composition of the composites was also analyzed by energy dispersive x-ray spectra (EDX). The formation mechanism of the nanoporous composites was extensively discussed. Methylene blue (MB) solution was used as a pollution model to evaluate the adsorption capability and photocatalytic activity of the samples under visible light. The as-synthesized nanoporous composites exhibit both much higher absorption capability and better photocatalytic activity for the photooxidation of MB than pure titania. The higher absorption capability and better photocatalytic activity of as-synthesized nanoporous composites are attributed to their high surface area, well conductivity and higher visible light absorption intensity.

We report an architecturally controlled synthesis of SiO2/TiO2−xCx/C nanoporous composites that exhibit high absorption capability and efficient visible-light photocatalytic activity. The nanoporous composites are composed of silica particles as the cores and TiCl4 as the precursor for the TiO2 shell. Tannin is used as the binding agent between the core and the precursor shell, the carbon source, and the porosity promoter. The structure, crystallinity, morphology, and other physical–chemical properties of the samples are characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), high-resolution transmission electron microcopy (HRTEM), X-ray photoelectron spectroscopy (XPS), N2 adsorption–desorption isotherm measurements, UV–vis diffuse reflectance spectroscopy (DRS), and photoluminescence (PL). The chemical contents of the SiO2/TiO2−xCx/C nanoporous composites were also analyzed by energy dispersive X-ray spectra (EDX). The formation mechanism of the nanoporous composites was extensively discussed. Methylene blue (MB) solutions were used as model wastewater to evaluate the adsorption and photocatalytic activity of the samples under natural sunlight and visible light. Fourier transform-infrared spectroscopy (FT-IR) and mass spectrometry (MS) were used to investigate the photodegradated species on the photocatalysts and in solution, respectively. The SiO2/TiO2−xCx/C nanoporous composite samples exhibit remarkably enhanced visible-light photoactivity than Degussa P25 and pure TiO2, and can be readily collected for reuse by gravitational sedimentation.

A yellow/brown powder of(I2)nsensitized nanoporous TiO2was obtained via an hydrolysis with TiCl4and iodine hydrosol as raw material. I2nanoparticles in the hydrosol were used as seeds to initiate the nucleation of a precursory TiO2shell. The hybridized jumbles were further calcinated at different temperatures. The structure, crystallinity, morphology, and other physical-chemical properties of the samples are characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), N2adsorption-desorption isotherms measurements, and UV-vis diffuse reflectance spectroscopy (DRS). The formation mechanism of these(I2)nsensitized nanoporous TiO2is discussed. Methylene blue solutions were used as model wastewater to evaluate the visible light photocatalytic activity of the samples. The results indicate that iodine can exist even in high-temperature calcination for iodine being encapsulated in the nanocavities inside TiO2. The degradation of methylene blue (MB) accorded with the first-order reaction model.

This chapter considers affect dynamics which simulates the relation among the emotions, mood, and personality and updates emotional states for long-term human-agent interactions. Affect dynamics is an important component of the affective system which also contains affect detection, affect appraisal, and affect response and makes indispensable contributions to the personification, believability, and autonomy of autonomous virtual humans (AVH). We first examine basic psychological concepts and computational models for affect dynamics. Then, we present a psychologically plausible affect dynamics algorithm in which the personality influences the updating of emotional states during the whole interactions, rather than just at the beginning as in many previous works. This makes affect dynamics characterized by the personality, which is shown to be important for long-term interactions.