Molecular Design of Conjugated Small Molecule Nanoparticles for Synergistically Enhanced PTT/PDT

Simultaneous photothermal therapy(PTT)and photodynamic therapy(PDT)is beneficial for enhanced cancer therapy due to the synergistic effect.Conventional materials developed for synergistic PTT/PDT are generally multicomponent agents that need complicated preparation procedures and be activated by multiple laser sources.The emerging monocomponent diketopyrrolopyrrole(DPP)-based conjugated small molecular agents enable dual PTT/PDT under a single laser irradiation,but suffer from low singlet oxygen quantum yield,which severely restricts the therapeutic efficacy.Herein,we report acceptor-oriented molecular design of a donor-acceptor-donor(D-A-D)conjugated small molecule(IID-ThTPA)-based phototheranostic agent,with isoindigo(IID)as selective acceptor and triphenylamine(TPA)as donor.The strong D-A strength and narrow singlet-triplet energy gap endow IID-ThTPA nanoparticles(IID-ThTPA NPs)high mass extinction coefficient(18.2 L g^-1 cm^-1),competitive photothermal conversion efficiency(35.4%),and a dramatically enhanced singlet oxygen quantum yield(84.0%)comparing with previously reported monocomponent PTT/PDT agents.Such a high PTT/PDT performance of IID-ThTPA NPs achieved superior tumor cooperative eradicating capability in vitro and in vivo.

Molecular design towards two-dimensional electron acceptors for efficient non-fullerene solar cells

Non-fullerene polymer solar cells(NF-PSCs) have gained wide attention recently. Molecular design of non-fullerene electron acceptors effectively promotes the photovoltaic performance of NF-PSCs. However,molecular electron acceptors with 2-dimensional(2 D) configuration and conjugation are seldom reported.Herein, we designed and synthesized a series of novel 2 D electron acceptors for efficient NF-PSCs. With rational optimization on the conjugated moieties in both vertical and horizontal direction, these 2 D electron acceptors showed appealing properties, such as good planarity, full-spectrum absorption, high absorption extinction coefficient, and proper blend morphology with donor polymer. A high PCE of 9.76%was achieved for photovoltaic devices with PBDB-T as the donor and these 2 D electron acceptors. It was also found the charge transfer between the conjugated moieties in two directions of these 2 D molecules contributes to the utilization of absorbed photos, resulting in an exceptional EQE of 87% at 730 nm. This work presents rational design guidelines of 2 D electron acceptors, which showed great promise to achieve high-performance non-fullerene polymer solar cells.

DFT Study on Molecule C_(20)H_(10): Five Carbon-carbon Single Bonds Linking Two Pentaprismane Cages

Using geometry optimization and DFT method at the B3LYP/6-31G* level for C20H10, an equilibrium geometry is identified to have the form of polyhedral hydrocarbon with five carbon-carbon single bonds linking two pentaprismane cages. Thus, C20H10 is a tri-cage molecule with three pentaprismane cages. Vibrational frequencies and infrared spectrum are computed at the same level. The heat of formation for this molecule has also been estimated in this paper.

Adjuvant Effects of Dual Co-stimulatory Molecules on Cellular Responses to HIV Multiple-epitope DNA Vaccination

Designing adjuvants that can induce strong cytotoxic T cell responses is largely required for preparing DNA vaccines. In this study we explored dual costimulatory molecules 4-1BBL and OX40L as adjuvants to improve the efficiency of the HIV multiple-epitope DNA vaccine. When explored in the human dendritic cell-T cell based coculture system, dual costimulatory molecules significantly enhanced the anti-HIV T cell response of the HIV multiple-epitope DNA vaccine, as detected by intracellular cytokine staining to HIV antigens, cytokines accumulation in the cultures, and antigen-specific cytotoxic T lymphocyte responses. These results suggest that dual costimulatory molecules 4-1BBL and OX40L can effectively increase the potential of the HIV multiple-epitope antigen DNA vaccine and may provide an exciting approach for HIV therapy.

Inverse Molecule Design with Invertible Neural Networks as Generative Models

Using neural networks for supervised learning means learning a function that maps input x to output y. However, in many applications, the inverse learning is also wanted, i.e., inferring y from x, which requires invertibility of the learning. Since the dimension of input is usually much higher than that of the output, there is information loss in the forward learning from input to output. Thus, creating invertible neural networks is a difficult task. However, recent development of invertible learning techniques such as normalizing flows has made invertible neural networks a reality. In this work, we applied flow-based invertible neural networks as generative models to inverse molecule design. In this context, the forward learning is to predict chemical properties given a molecule, and the inverse learning is to infer the molecules given the chemical properties. Trained on 100 and 1000 molecules, respectively, from a benchmark dataset QM9, our model identified novel molecules that had chemical property values well exceeding the limits of the training molecules as well as the limits of the whole QM9 of 133,885 molecules, moreover our generative model could easily sample many molecules (x values) from any one chemical property value (y value). Compared with the previous method in the literature that could only optimize one molecule for one chemical property value at a time, our model could be trained once and then be sampled any multiple times and for any chemical property values without the need of retraining. This advantage comes from treating inverse molecule design as an inverse regression problem. In summary, our main contributions were two: 1) our model could generalize well from the training data and was very data efficient, 2) our model could learn bidirectional correspondence between molecules and their chemical properties, thereby offering the ability to sample any number of molecules from any y values. In conclusion, our findings revealed the efficiency and effectiveness of using invertible neural networks as generative models in inverse molecule design.

SYNTHESIS OF MBS RESIN BASED ON MOLECULE DESIGN

The relationships between the properties of PVC-MBS polyblend and of the MBS multiphase structure and between the MBS structure and polymerization parameters are studied theoretically and experimentally. MBS resin synthesized from the molecule design principle is suitable to prepare PVC-MBS polyblend with good transparency and high impact strength.

A Dodecahedrane-like Molecule C_(12)H_(12)B_8 with Uncommon T_h Symmetry

The molecule with Th symmetry is rare.A dodecahedrane-like molecule C12H12B8 with uncommon Th symmetry has been reported here.Density functional calculations and minimization techniques have been employed to characterize its structural and electronic properties.Its geometry,electronic properties,vibrational frequencies and heat of formation have been calculated at the B3LYP/6-311＋G（d,p） level of theory.The absence of imaginary vibrational frequency confirms that it corresponds to true minimum on the potential energy hypersurface.Its vibrational bands in the IR intensity have been discussed and compared with future experimental identification.At the B3LYP/6-311＋G（d,p） level,the heat of formation has been calculated to be 720.9 kJ mol^-1 using the isodesmic reaction.According to this value,it is a potential high energy density molecule.

Expression of co-stimulatory molecules B7-2 and PD-L1 on peripheral blood mononuclear cells in patients with chronic hepatitis B virus infection

Objective： To explore the roles of the expression of the co-stimulatory molecule, B7-2, and the co-inhibitory molecule, PD-L1, on peripheral blood mononuclear cells in the mechanism of immunotolerance in chronic hepatitis B virus infection. Methods： Thirty HBV infected patients in the immunoreactive phase and 20 patients in the immunotolerant phase were enrolled in the study, while 20 healthy volunteers were used as controls. RT- PCR and real-time PCR methods were used to detect the expression levels of B7-2 and PD-L1 mRNA in peripheral blood mononuclear cells in chronic HBV infected patients. Results： The B7-2 expression in irnrnunoreactive and immunotolerant patients was significantly lower than that in the controls （P all 〈 0.01 ）; B7-2 expression in immunoreactive patients was significantly lower than in immunotolerant patients （P 〈 0.01）. PD-L1 expression in irnmunoreactive patients and immunotolerant patients was significantly higher than that in normal controls （P all 〈 0.01）. The PD-L1/BT-2 ratios in immunoreactive and immunotolerant patients were significantly higher than that of the healthy controls （P all 〈 0.01）; the PD-L1/ B7-2 ratio was significantly higher in the immunoreactive patients than in the immunotolerant patients （P 〈 0.01）. Conclusion： In chronic HBV infection, changes in the expression of co-stimulatory and co-inhibitory molecules imply a protective adjustment against the patient＇ s immune response that may result in increased immunotolerance and persistent HBV infection.

Exploring Local Chemical Space in De Novo Molecular Generation Using Multi-Agent Deep Reinforcement Learning

Single-agent reinforcement learning (RL) is commonly used to learn how to play computer games, in which the agent makes one move before making the next in a sequential decision process. Recently single agent was also employed in the design of molecules and drugs. While a single agent is a good fit for computer games, it has limitations when used in molecule design. Its sequential learning makes it impossible to modify or improve the previous steps while working on the current step. In this paper, we proposed to apply the multi-agent RL approach to the research of molecules, which can optimize all sites of a molecule simultaneously. To elucidate the validity of our approach, we chose one chemical compound Favipiravir to explore its local chemical space. Favipiravir is a broad-spectrum inhibitor of viral RNA polymerase, and is one of the compounds that are currently being used in SARS-CoV-2 (COVID-19) clinical trials. Our experiments revealed the collaborative learning of a team of deep RL agents as well as the learning of its individual learning agent in the exploration of Favipiravir. In particular, our multi-agents not only discovered the molecules near Favipiravir in chemical space, but also the learnability of each site in the string representation of Favipiravir, critical information for us to understand the underline mechanism that supports machine learning of molecules.

Prospective Development of Small Molecule Targets to Oncogenic Ras Proteins

Abnormal expression or mutations in Ras proteins has been found in up to 30% of cancer cell types, making them excellent protein models to probe structure-function relationships of cell-signaling processes that mediate cell transformtion. Yet, there has been very little development of therapies to help tackle Ras-related diseased states. The development of small molecules to target Ras proteins to potentially inhibit abnormal Ras-stimulated cell signaling has been conceptualized and some progress has been made over the last 16 or so years. Here, we briefly review studies characterizing Ras protein-small molecule interactions to show the importance and potential that these small molecules may have for Ras-related drug discovery. We summarize recent results, highlighting small molecules that can be directly targeted to Ras using Structure-Based Drug Design (SBDD) and Fragment-Based Lead Discovery (FBLD) methods. The inactivation of Ras oncogenic signaling in vitro by small molecules is currently an attractive hurdle to try to and leap over in order to attack the oncogenic state. In this regard, important features of previously characterized properties of small molecule Ras targets, as well as a current understanding of conformational and dynamics changes seen for Ras-related mutants, relative to wild type, must be taken into account as newer small molecule design strategies towards Ras are developed.

Reinforcement Learning of Molecule Optimization with Bayesian Neural Networks

Creating new molecules with desired properties is a fundamental and challenging problem in chemistry. Reinforcement learning (RL) has shown its utility in this area where the target chemical property values can serve as a reward signal. At each step of making a new molecule, the RL agent learns selecting an action from a list of many chemically valid actions for a given molecule, implying a great uncertainty associated with its learning. In a traditional implementation of deep RL algorithms, deterministic neural networks are typically employed, thus allowing the agent to choose one action from one sampled action at each step. In this paper, we proposed a new strategy of applying Bayesian neural networks to RL to reduce uncertainty so that the agent can choose one action from a pool of sampled actions at each step, and investigated its benefits in molecule design. Our experiments suggested the Bayesian approach could create molecules of desirable chemical quality while maintained their diversity, a very difficult goal to achieve in machine learning of molecules. We further exploited their diversity by using them to train a generative model to yield more novel drug-like molecules, which were absent in the training molecules as we know novelty is essential for drug candidate molecules. In conclusion, Bayesian approach could offer a balance between exploitation and exploration in RL, and a balance between optimization and diversity in molecule design.

Study On Pattern Design of Men's Tailored-suit Sleeve

Sleeve pattern design of men’ s tailored - suit is one of the most difficult problems of clothing pattern design. Based on the experimental studies of armhole girth, the difference of armhole width and crown height, crown angle, under sleeve curve’s diagonal line length, crown ease and its distribution rule, this paper mainly deals with the sleeve pattern design of tailored - suit for Chinese men. The influences of these factors are discussed and furthermore, some qualitative, quantifiable conclusions are drawn to design perfect pattern of men’ s tailored - suit sleeve.

SELECTING CLUSTER MODEL IN Sn - BASED SOLDER ALLOY DESIGN WITH DV - X_α CALCULATION METHOD

Applying calculation method in alloy design should be an important tendency due to its characters of inexpensive cost, high efficiency and prediction. DOS calculations of AuSn, AsSn and SbSn Sn- based alloys have been investigated by employing DV - Xa method, in which different cluster models were adopted to calculate electron structure.It is proved that some regulations must be taken into ac- count in order to carry out alloy design calculation successfully,which are described in this paper in detail.

Computer-aided Pattern Design of Multi-bar Warp Knitted Fabrics

To meet the development trend of multi-bar warp knit-ting machine towards high-speed,advanced technologyand computer control and the requirements of variousproducts with small quantity,there are many researcheson the computer-aided pattern design of multi-barwarp knitted fabrics.In terms of the special propertiesof the computer-aided pattern design of multi-barwarp knitted fabrics,the Object Oriented Program(OOP)programming-Object Windows class Library(OWL)programming is selected.According to thecharacters of the OWL programming,various functionsare defined.Pattern design and technical parameters canbe output,which offers a great convenience for the fac-tory.

SMA molecular line survey towards the massive star-forming region G10.6-0.4in W31complex

Line surveys of complex molecules with millimeter and sub-millimeter telescopes are important for probing the physical and chemical environments of massive star forming regions(MSFRs).We present a molecular line survey with the Submillimeter Array(SMA) in the frequency ranges of 220.3–222.3 GHz and 230.3–232.3 GHz toward G10.6-0.4, the brightest star forming core in the W31 complex. Ninety-nine transitions from 22 molecular species and their isotopologues are identified. The moment 0 images of typical molecules show a compact core which is concentrated at the continuum peak position. Based on the local thermodynamic equilibrium assumption, the molecular line data are modeled. The rotational temperatures of those molecular species range from 96 to 178 K and their column densities range from 2.0×1014to 3.7×1017cm-2. The observational data suggest that all complex molecules are located in a warm environment. Chemical environments of the molecules are discussed. We compared molecular abundances and gas temperatures in G10.6-0.4 with those in other MSFRs, and found that gas temperatures and fractional abundances of specific molecules in G10.6-0.4 are similar to the typical MSFR W51 North, suggesting that there are similar physical and chemical environments in these two MSFRs.

Suboptimal State Feedback H2/H∞ Controller Design with Spectrum Constraint for Discrete-time Stochastic Systems

With the aid of the spectnnn techique, a new concept named-α-stabilizability （0≤α≤1） is intnxhged and its suffident and necessary canditions are also prvposed. Especially, it is identical with the asymptotically mean square stabilizability when α = 1. As an application, the suboptimal state feedback H2/H∞ controller that satisfies the additional Spectrum canstmint via solving a convex optimization problem is delt with.

MATLAB App Designer在法布里-珀罗干涉实验中的应用

基于法布里-珀罗(F-P)多光束干涉原理,利用MATLAB设计了基于F-P干涉实验的可视化App仿真界面,不仅可复现F-P腔长、入射波长、透镜焦距等参数对F-P干涉图样的影响及实时动态展示,还可观察周围介质折射率、F-P腔折射率与干涉图样的关系,并能进行多波长分辨率和微小波长差测量实验的演示.这些直观形象的模拟结果展示,将有助于改善多光束干涉理论及实验教学效果.

基于片段生长技术的PD-1/PD-L1小分子抑制剂的设计

目的 基于片段生长技术开发小分子PD-L1抑制剂。方法 根据已知的苯甲酰苯胺活性片段结构,使用FDA碎片库进行片段生长,然后使用分子对接和分子动力学对其进行进一步筛选,最终通过体外实验获得活性化合物。结果 获得一系列包含苯甲酰苯胺片段的分子库,其中有8个打分较高的分子,分子动力学模拟表明776191具有最高的结合能,体外抑制实验证明776191具有一定的抑制PD-1/PD-L1结合活性。结论 776191是一种具有新型结构的PD-1/PD-L1抑制剂,这一研究丰富了PD-1/PD-L1抑制剂的多样性,为其开发提供了新的设计思路。

Creative Design Fulfills Brand and Fashion China Fashion Week A/W 2010-2011 Collection held in Beijing

March is a right party time for friends to get together to enjoy the smell of early spring. Moreover, people would like to take off the thick winter coat to showcase their colorful attitude towards the warm spring sunshine. Here, an annual fashion feast in Beijing not only could provide you a visual inspiration of trend, but also would tell you what’s the most "in" factors in the coming season.

融与合——有感于Freedom in Design：The Architectnre of J．J．Pan and Partners．2000-2006

潘冀，1966年毕业于美国莱斯大学建筑学专业1967年获美国哥伦比亚大学城市建筑硕士学位主攻城市设计方向。在之后的几年内．先后为菲利普约翰逊和理查德-罗杰斯等建筑师事务所服务1972年取得美国职业建筑师资格．并于1981年回到台湾成立潘冀联合设计师事务所。在之后20多年内．该事务所逐渐成长为台湾最大的建筑师事务所之一．