A periodic DFT study on adsorption of small molecules(CH_4,CO,H_2O,H_2S,NH_3)on the WO_3(001) surface-supported Au

Gas molecules(such as CH4,CO,H2O,H2S,NH_3)adsorption on the pure and Au-doped WO3(001)surface have been studied by Density functional theory calculations with generalized gradient approximation.Based on the the calculation of adsorption energy,we found the most stable adsorption site for gas molecules by comparing the adsorption energies of different gas molecules on the WO3(001)surface.We have also compared the adsorption energy of five different gas molecules on the WO3(001)surface,our calculation results show that when the five kinds of gases are adsorbed on the pure WO3(001)surface,the order of the surface adsorption energy is CO>H2S>CH4>H2O>NH3.And the results show that NH3 is the most easily adsorbed gas among the other four gases adsorbed on the surface of pure WO3(001)surface.We also calculated the five different gases on the Au-doped WO3(001)surface.The order of adsorption energy was found to be different from the previous calculation:CO>CH4>H2S>H2O>NH3.These results provide a new route for the potential applications of Au-doped WO3 in gas molecules adsorption.     

密度泛函理论研究MN@H_2O (M=Ga,Ge, In,Sn, Sb; N=M,Al)团簇的特性

采用密度泛函理论的B3LYP, B3P86, B1B95, P3PW91和PBE1PBE方法结合SDD, LANL2DZ和CEP-121G基组计算了d~(10)组态二聚物MN(M=Ga, Ge, In, Sn和Sb; N=M和Al)的几何结构.采用B3P86/SDD进一步研究了MN@H_2O团簇的几何结构及吸附能.结果表明,水分子结合在二聚物M_2上时,对二聚物影响较大,对水分子自身影响较小.将M_2中Ga, Ge, In, Sn或Sb替换一个原子为Al时,水分子在GeAl和SnAl上的吸附能变化较大,而在GaAl, InAl和SbAl上吸附能变化较小.另外, H_2O吸附在Ga, Ge, In, Sn和Sb上时,与吸附在Al上时,吸附能的变化不大.     

Evolution and Trade-Off Dynamics of Functional Load

Functional load (FL) quantifies the contributions by phonological contrasts to distinctions made across the lexicon. Previous research has linked particularly low values of FL to sound change. Here, we broaden the scope of enquiry into FL to its evolution at higher values also. We apply phylogenetic methods to examine the diachronic evolution of FL across 90 languages of the Pama–Nyungan (PN) family of Australia. We find a high degree of phylogenetic signal in FL, indicating that FL values covary closely with genealogical structure across the family. Though phylogenetic signals have been reported for phonological structures, such as phonotactics, their detection in measures of phonological function is novel. We also find a significant, negative correlation between the FL of vowel length and of the following consonant—that is, a time-depth historical trade-off dynamic, which we relate to known allophony in modern PN languages and compensatory sound changes in their past. The findings reveal a historical dynamic, similar to transphonologization, which we characterize as a flow of contrastiveness between subsystems of the phonology. Recurring across a language family that spans a whole continent and many millennia of time depth, our findings provide one of the most compelling examples yet of Sapir’s ‘drift’ hypothesis of non-accidental parallel development in historically related languages.     

双β-二酮配体配位性的理论研究

基于自洽反应场(SCRF)中的极化连续介质模型(PCM), 采用密度泛函理论B3LYP/6-31G**计算了以二硫醚和芳环为桥基的两类双β-二酮配体的空间构型和电子结构, 结合其配合物晶体结构数据, 研究配体分子电子结构与配位性的关联性. 结果表明, 配体分子的几何构型、前线轨道、偶极矩和电荷布居, 与配合物构型、活性配位原子和配位形式(单核或多核、分子内或分子间)之间的关联性与一致性十分有意义. 配体的理论计算研究可以在一定层次上为配合物几何结构特征和配位特性提供合理的分析与预测.     

Solventless Formation of G‐Quartet Complexes Based on Alkali and Alkaline Earth Salts on Au(111)

Template cations have been extensively employed in the formation, stabilization and regulation of structural polymorphism of G‐quadruplex structures in vitro. However, the direct addition of salts onto solid surfaces, especially under ultra‐high‐vacuum (UHV) conditions, to explore the feasibility and universality of the formation of G‐quartet complexes in a solventless environment has not been reported. By combining UHV‐STM imaging and DFT calculations, we have shown that three different G‐quartet‐M (M: Na/K/Ca) complexes can be obtained on Au(111) using alkali and alkaline earth salts as reactants. We have also identified the driving forces (intra‐quartet hydrogen bonding and electrostatic ionic bonding) for the formation of these complexes and quantified the interactions involved. Our results demonstrate a novel route to fabricate G‐quartet‐related complexes on solid surfaces, providing an alternative feasible way to bring metal elements to surfaces for constructing metal–organic systems.     

Computational Drug Repurposing Based on a Recommendation System and Drug–Drug Functional Pathway Similarity

Drug repurposing identifies new clinical indications for existing drugs. It can be used to overcome common problems associated with cancers, such as heterogeneity and resistance to established therapies, by rapidly adapting known drugs for new treatment. In this study, we utilized a recommendation system learning model to prioritize candidate cancer drugs. We designed a drug–drug pathway functional similarity by integrating multiple genetic and epigenetic alterations such as gene expression, copy number variation (CNV), and DNA methylation. When compared with other similarities, such as SMILES chemical structures and drug targets based on the protein–protein interaction network, our approach provided better interpretable models capturing drug response mechanisms. Furthermore, our approach can achieve comparable accuracy when evaluated with other learning models based on large public datasets (CCLE and GDSC). A case study about the Erlotinib and OSI-906 (Linsitinib) indicated that they have a synergistic effect to reduce the growth rate of tumors, which is an alternative targeted therapy option for patients. Taken together, our computational method characterized drug response from the viewpoint of a multi-omics pathway and systematically predicted candidate cancer drugs with similar therapeutic effects.     

The Current State of Knowledge on Salvia hispanica and Salviae hispanicae semen (Chia Seeds)

Chia seeds (Salviae hispanicae semen) are obtained from Salvia hispanica L. This raw material is distinguished by its rich chemical composition and valuable nutritional properties. It is currently referred to as “health food”. The purpose of the present work was to perform a literature review on S. hispanica and chia seeds, focusing on their chemical composition, biological properties, dietary importance, and medicinal uses. The valuable biological properties of chia seeds are related to their rich chemical composition, with particularly high content of polyunsaturated fatty acids, essential amino acids, polyphenols, as well as vitamins and bioelements. The available scientific literature indicates the cardioprotective, hypotensive, antidiabetic, and antiatherosclerotic effects of this raw material. In addition, studies based on in vitro assays and animal and human models have proven that chia seeds are characterized by neuroprotective, hepatoprotective, anti-inflammatory, and antioxidant properties. These properties indicate a valuable role of chia in the prevention of civilization diseases. Chia seeds are increasingly popular in functional food and cosmetic and pharmaceutical industries. That is attributed not only to their desirable chemical composition and biological activity but also to their high availability. Nevertheless, S. hispanica is also the object of specific biotechnological studies aimed at elaboration of micropropagation protocols of this plant species.     

On the Nature of Functional Differentiation: The Role of Self-Organization with Constraints

The focus of this article is the self-organization of neural systems under constraints. In 2016, we proposed a theory for self-organization with constraints to clarify the neural mechanism of functional differentiation. As a typical application of the theory, we developed evolutionary reservoir computers that exhibit functional differentiation of neurons. Regarding the self-organized structure of neural systems, Warren McCulloch described the neural networks of the brain as being “heterarchical”, rather than hierarchical, in structure. Unlike the fixed boundary conditions in conventional self-organization theory, where stationary phenomena are the target for study, the neural networks of the brain change their functional structure via synaptic learning and neural differentiation to exhibit specific functions, thereby adapting to nonstationary environmental changes. Thus, the neural network structure is altered dynamically among possible network structures. We refer to such changes as a dynamic heterarchy. Through the dynamic changes of the network structure under constraints, such as physical, chemical, and informational factors, which act on the whole system, neural systems realize functional differentiation or functional parcellation. Based on the computation results of our model for functional differentiation, we propose hypotheses on the neuronal mechanism of functional differentiation. Finally, using the Kolmogorov–Arnold–Sprecher superposition theorem, which can be realized by a layered deep neural network, we propose a possible scenario of functional (including cell) differentiation.