Novel titanium complexes of a multidentate dicarbollide ligand. Synthesis and structural characterization of a constrained geometry complex

The multidentate dicarbollide ligand nido-7,8-(NMe2CH2)2-7,8-C2B9H11 has been prepared, structurally characterized, and employed in the preparation of the novel mono- and trimetallic titanium complexes [eta5:eta1-(NMe2CH2)C2B9H9CH2NMe2]Ti(NMe2)2 and [eta5:eta1-[(NMe2CH2)C2B9H9CH2NMe2]Ti(NMe2)]2-mu3-O-Ti(NMe2)2.     

Sensitivity of methyl thiolate desulfurization selectivity to reaction temperature and hydroxyl coverage

The adsorption and reaction of methanethiol (CH3SH) and dimethyl disulfide (CH3SSCH3) on Mo(110)-(1 x 6)-O have been studied using temperature-programmed reaction spectroscopy and reflection-absorption infrared spectroscopy over the temperature range of 110-550 K. The S-H bond is broken upon adsorption to form adsorbed OH, water, and methyl thiolate (CH3S-) at low temperature. Water is evolved at 210 and 310 K via molecular desorption and disproportionation of OH, respectively. Some hydroxyl remains on the surface up to 350 K. Methyl thiolate is also formed from CH3SSCH3 on Mo(110)-(1 x 6)-O. Methyl thiolate undergoes C-S cleavage above 300 K, yielding methane and methyl radicals. There is also a minor amount of nonselective decomposition leading to the formation of carbon and hydrogen. Methane production is promoted by adsorbed hydroxyl. As the hydroxyl coverage increases, the yield of methyl radicals relative to methane diminishes. Accordingly, there is more methane produced from methanethiol reaction than from dimethyl disulfide, since S-H dissociation in CH3SH produces OH. The maximum coverage of the thiolate is approximately 0.5 monolayers, based on the amount of sulfur remaining after reaction measured by Auger electron spectroscopy. In contrast to cyclopropylmethanethiol (c-C3H5CH2SH), for which alkyl transfer from sulfur to oxygen is observed, there is no evidence for transfer of the methyl group of methyl thiolate to oxygen on the surface. Specifically, there is no evidence for methoxy (CH3O-) in infrared spectroscopy or temperature-programmed reaction experiments.     

Syntheses and Crystal Structures of Two Metal Succinates Modified by Bipyridines

Two new metal succinates modified by rigid bipyridines, Cd(4, 4′‐bpy)(C₄H₄O₄)·1/4H₂O ( 1 ) and Cu(2, 2′‐bpy)(C₄H₄O₄)_0.5(NO₃)(H₂O) ( 2 ) (bpy = bipyridine), have been synthesized by hydrothermal reactions and structurally determined. Complex 1 crystallizes in the orthorhombic space group Cmca with the cell parameters a = 11.696(2), b = 15.554(2), c = 15.874(3) Å, α = β = γ = 90.00°, V = 2888(3) ų, Z = 8. Complex 2 crystallizes in the triclinic space group with a = 7.077(1), b = 9.838(2), c = 10.461(2) Å, α = 71.941(3)°, β = 73.078(3)°, γ = 74.502(3)°, V = 649.8(2) ų, Z = 2. In complex 1 , a 2‐D network was formed by Cd‐succinato bonding. The 2‐D networks are pillared by 4, 4′‐bpy ligands, forming a 3‐D grid framework. The 2‐fold interpenetration of the resulting 3‐D frameworks completes the molecular structure. In complex 2 , the Cu^II atom adopts a distorted octahedral in which the Cu^II atoms are bridged by two H₂O molecules into an infinite zigzag chain, [Cu₂(H₂O)₂(C₄H₄O₄)]_n. The neighboring chains are further linked by π‐π stacking interactions into a 2‐D network, and the interlayer hydrogen bonds lead to the final 3‐D crystal structure.     

Modelling the Effects of Pest Control with Development of Pesticide Resistance

In this paper,we assume that the pest population is divided into susceptible pests and infected pests,and only susceptible pests do harm to crops.Considering the two methods of spraying pesticides and releasing infected pests and natural enemies to control susceptible pests(the former is applied more frequently),and assuming that only susceptible pests develop resistance to pesticides,a pest control model with resistance development is established.By using the basic theory of impulsive different...     

普适的基于能量的分块局域激发态聚类算法

在普适的基于能量的分块(GEBF)方法的框架下,大体系的局域激发(LE)能可通过一系列活性子体系激发能的线性组合近似得到,从而有效降低了计算的时间标度.然而,在体系的局域激发具有多个激发态的情形下,如何有效识别所有活性子体系的激发特征并将其组合是一个挑战.提出了一种基于局域激发态聚类的算法.该方案基于空穴-电子分析和基于密度的聚类(DBSCAN)机器学习算法,可以自动地聚合不同子体系中最相似的激发态并组合得到相应的局域激发态能量或激发能.结合该算法改进的LE-GEBF方法在荧光分子衍生物、荧光染料-水团簇及绿色荧光蛋白模型体系的计算中均获得了令人满意的结果.该算法有望大大提升LE-GEBF方法在计算局域激发时的稳定性和准确性,并可以有效处理吸收光谱具有多重峰的大体系.     

“拟双子”阴离子表面活性剂在癸烷/水界面的分子动力学模拟

采用全原子分子动力学模拟方法研究了壬基酚取代的系列烷基磺酸盐表面活性剂在癸烷/水界面的微观聚集行为,通过分析界面厚度、界面生成能和界面张力以及表面活性剂分子与水分子之间的径向分布函数和配位数,讨论了不同磺烷基链长度对壬基酚基取代烷基磺酸盐表面活性剂界面性质的影响.结果表明,磺烷基链长为12时,表面活性剂的界面张力最低,界面厚度和界面生成能最大.     

具有高稳定性以及光催化产氢活性的奇数环状异金属钛氧纳米团簇

利用太阳能是解决当前能源危机和环境问题的有效途径.二氧化钛是一种稳定性高、环境友好的新型光催化剂.近年来,具有精确结构信息的晶态钛氧团簇(PTCs)作为TiO2的分子结构模型受到广泛关注.目前大多数PTCs含有烷氧基,在空气中易发生水解.这在很大程度上限制了对其光催化性能的研究.在无机钛氧簇的外围修饰大量的共轭有机配体...     

Bulk viscosity for interacting strange quark matter and r-mode instability windows for strange stars

We investigate the bulk viscosity of strange quark matter in the framework of the equivparticle model,where analytical formulae are obtained for certain temperature ranges,which can be readily applied to those with various quark mass scalings.In the case of adopting a quark mass scaling with both linear confinement and perturbative interactions,the obtained bulk viscosity increases by 1-2 orders of magnitude compared with those in bag model scenarios.Such an enhancement is mainly due to the large quark equivalent masses adopted in the equivparticle model,which are essentially attributed to the strong interquark interactions and are related to the dynamical chiral symmetry breaki ng.Due to the high bulk viscosity,the predicted damping time of oscillatio ns for a can on ical 1.4 M⊙ strange star is less than one millisecond,which is shorter than previous findings.Consequently,the obtained r-mode instability window for the canonical strange stars well accommodates the observational frequencies and temperatures for pulsars in low-mass X-ray binaries(LMXBs).     

Machine-learning algorithms for asthma,COPD, and lung cancer risk assessment using circulating microbial extracellular vesicle data and their application to assess dietary effects

Although mounting evidence suggests that the microbiome has a tremendous influence on intractable disease, the relationship between circulating microbial extracellular vesicles (EVs) and respiratory disease remains unexplored. Here, we developed predictive diagnostic models for COPD, asthma, and lung cancer by applying machine learning to microbial EV metagenomes isolated from patient serum and coded by their accumulated taxonomic hierarchy. All models demonstrated high predictive strength with mean AUC values ranging from 0.93 to 0.99 with various important features at the genus and phylum levels. Application of the clinical models in mice showed that various foods reduced high-fat diet-associated asthma and lung cancer risk, while COPD was minimally affected. In conclusion, this study offers a novel methodology for respiratory disease prediction and highlights the utility of serum microbial EVs as data-rich features for noninvasive diagnosis.Subject terms: Respiratory tract diseases, Machine learning, Predictive markers     

NRBF2-mediated autophagy contributes to metabolite replenishment and radioresistance in glioblastoma

Overcoming therapeutic resistance in glioblastoma (GBM) is an essential strategy for improving cancer therapy. However, cancer cells possess various evasion mechanisms, such as metabolic reprogramming, which promote cell survival and limit therapy. The diverse metabolic fuel sources that are produced by autophagy provide tumors with metabolic plasticity and are known to induce drug or radioresistance in GBM. This study determined that autophagy, a common representative cell homeostasis mechanism, was upregulated upon treatment of GBM cells with ionizing radiation (IR). Nuclear receptor binding factor 2 (NRBF2)—a positive regulator of the autophagy initiation step—was found to be upregulated in a GBM orthotopic xenograft mouse model. Furthermore, ATP production and the oxygen consumption rate (OCR) increased upon activation of NRBF2-mediated autophagy. It was also discovered that changes in metabolic state were induced by alterations in metabolite levels caused by autophagy, thereby causing radioresistance. In addition, we found that lidoflazine—a vasodilator agent discovered through drug repositioning—significantly suppressed IR-induced migration, invasion, and proliferation by inhibiting NRBF2, resulting in a reduction in autophagic flux in both in vitro models and in vivo orthotopic xenograft mouse models. In summary, we propose that the upregulation of NRBF2 levels reprograms the metabolic state of GBM cells by activating autophagy, thus establishing NRBF2 as a potential therapeutic target for regulating radioresistance of GBM during radiotherapy.Subject terms: Cancer metabolism, Prognostic markers