实验性血压变化对基础痛阈的影响

目的 :观察左侧肾动脉结扎大鼠血压变化对热痛阈和机械痛阈影响的时程。方法 :将 16只动物分为 3组 :假手术组、肾动脉结扎组和肾动脉结扎 +肌注利血平组 ,每天在一定时间检测动脉收缩压 （BP）、热刺激缩足反应潜伏期 （PWTL ）和机械刺激缩足反应阈值 （PWMT） ,并作定量分析。结果 :1假手术组 BP,PWTL和 PWMT均未发生明显变化 （P>0 .0 5 ）。 2肾动脉结扎组大鼠血压在术后第 1天开始升高 ,第 3天达峰值 ,并维持在高血压水平 （112± 6 vs 16 0± 8m m Hg） ,平行观察显示 PWTL和 PWMT均随动脉收缩压升高而降低 ,提示发生了热和机械痛敏现象。 3利血平降压治疗后动脉收缩压虽然降至正常范围 ,但热痛敏和机械痛敏却未被翻转。结论 :持续实验性高血压可能对伤害性反射的神经通路具有不可逆的调节作用     

Organometallic rotaxane dendrimers with fourth-generation mechanically interlocked branches

Mechanically interlocked molecules, such as catenanes, rotaxanes, and knots, have applications in information storage, switching devices, and chemical catalysis. Rotaxanes are dumbbell-shaped molecules that are threaded through a large ring, and the relative motion of the two components along each other can respond to external stimuli. Multiple rotaxane units can amplify responsiveness, and repetitively branched molecules—dendrimers—can serve as vehicles for assembly of many rotaxanes on single, monodisperse compounds. Here, we report the synthesis of higher-generation rotaxane dendrimers by a divergent approach. Linkages were introduced as spacer elements to reduce crowding and to facilitate rotaxane motion, even at the congested periphery of the compounds up to the fourth generation. The structures were characterized by 1D multinuclear (¹H, ¹³C, and ³¹P) and 2D NMR spectroscopy, MALDI-TOF-MS, gel permeation chromatography (GPC), and microscopy-based methods including atomic force microscopy (AFM) and transmission electron microscopy (TEM). AFM and TEM studies of rotaxane dendrimers vs. model dendrimers show that the rotaxane units enhance the rigidity and reduce the tendency of these assemblies to collapse by self-folding. Surface functionalization of the dendrimers with ferrocenes as termini produced electrochemically active assemblies. The preparation of dendrimers with a well-defined topological structure, enhanced rigidity, and diverse functional groups opens previously unidentified avenues for the application of these materials in molecular electronics and materials science.Dendritic molecules containing rotaxane components are a recently developed subset of mechanically bonded supermolecules (1–3). The combination of the characteristics of both rotaxanes (sliding and rotary motion) and dendrimers (repetitive branching with each generation) provides the resultant rotaxane dendrimers with unusual topological features and potentially useful properties. For example, the introduction of stimuli-responsive rotaxanes (4) such as muscle-like bistable rotaxanes or daisy chains can impart switchable features to the resultant dendrimers that are “smart” to external inputs. The applications of dendrimers in materials science (5, 6) suggest that rotaxane dendrimers could serve as supramolecular dynamic materials.A variety of rotaxane dendrimers have been designed and constructed over the past few years. For examples, mechanically interlocked units were used either as cores or end groups, by Vögtle and coworkers (7), Stoddart and coworkers (8–13), Gibson et al. (14), Kim and coworkers (15, 16), and Kaifer and coworkers (17, 18). Compared with these simpler systems, rotaxane dendrimers with interlocking ring components on the branches or at the branch points are rare. Specifically, Kim et al. (16) and Leung et al. (19) have reported the only two cases of rotaxane branched dendrimers up to the second generation. Third- or higher-generation rotaxane dendrimers equipped with mechanically interlocked functions on the branches (Fig. 1) are unknown to us.Open in a separate windowFig. 1.Schematic representation of a rotaxane dendrimer with mechanically interlocked moieties incorporated on the branches.Herein, we describe the synthesis, characterization, and functionalization of higher-generation (up to fourth-generation) organometallic rotaxane branched dendrimers. A divergent strategy was employed for the dendrimer synthesis in which the host–guest complex of a pillar[5]arene and a neutral alkyl chain were used as the rotaxane subunits. The formation of platinum–acetylide bonds was the growth step in the synthesis; it produced satisfactory yields and allowed construction of the targeted structures. The introduction of macrocyclic wheels enhanced the rigidity of the resultant rotaxane dendrimers and reduced self-folding. Electrochemically active rotaxane dendrimers substituted with different numbered ferrocenes were also prepared by direct surface modification.     

Dynamics of gene circuits shapes evolvability

To what extent does the dynamical mechanism producing a specific biological phenotype bias the ability to evolve into novel phenotypes? We use the interpretation of a morphogen gradient into a single stripe of gene expression as a model phenotype. Although there are thousands of three-gene circuit topologies that can robustly develop a stripe of gene expression, the vast majority of these circuits use one of just six fundamentally different dynamical mechanisms. Here we explore the potential for gene circuits that use each of these six mechanisms to evolve novel phenotypes such as multiple stripes, inverted stripes, and gradients of gene expression. Through a comprehensive and systematic analysis, we find that circuits that use alternative mechanisms differ in the likelihood of reaching novel phenotypes through mutation. We characterize the phenotypic transitions and identify key ingredients of the evolutionary potential, such as sensitive interactions and phenotypic hubs. Finally, we provide an intuitive understanding on how the modular design of a particular mechanism favors the access to novel phenotypes. Our work illustrates how the dynamical mechanism by which an organism develops constrains how it can evolve. It is striking that these dynamical mechanisms and their impact on evolvability can be observed even for such an apparently simple patterning task, performed by just three-node circuits.Evolution occurs through mutations on existing genotypes, potentially transforming the original phenotype or trait into a novel one, with latent beneficial consequences. It is a fundamental problem in biology to understand the relationship between a genotype and the associated phenotypes accessible through mutations, in other words, its evolvability. From the many definitions of evolvability (1, 2), we refer here to the ability of genotypes to access novel phenotypes, irrespective of the subsequent process of natural selection.To understand how a phenotype evolves we need to consider that a huge number of distinct genotypes can achieve that same phenotype. For example, hundreds of distinct RNA sequences fold in the same secondary structure (3), as do proteins in their 3D structure (4). Similarly, distinct gene regulatory architectures can produce the same gene expression pattern (5, 6) or temporal behavior (7, 8). However, among these genotypes, some are more evolvable than others. The existing studies have targeted two key drivers of evolvability: a genotype’s design and a genotype’s location within a neutral space.A first class of studies focuses on a circuit’s general architectural features, such as feed-back or feed-forward loops, revealing that these distinct families of designs or motifs differ in their evolvability (9, 10). The second class of studies centers not on single designs but on the whole collection of genotypes capable of producing the same phenotype. These genotypes with a common phenotype form a region in genotype space termed a neutral space or neutral network (3), as mutations within this region produce no change in the phenotype.As revealed by many studies, the existence of neutral spaces has two major consequences to the evolutionary process. First, these neutral spaces often appear as fully connected and dense regions (11–13). Therefore, although genotypes internal to the neutral space are highly robust to mutations (i.e., not evolvable), only genotypes close to the edges of the neutral space might access novel phenotypes. From this perspective, neutral mutations and thus the process of neutral drift can generate cryptic genetic variation (14) by moving a species closer to the edges of the neutral space into a more evolvable state (12, 15). Second, different positions in genotype space give access to distinct novel phenotypes. Large neutral spaces percolate through genotype space, providing access to a diversity of novel phenotypes from different genotypes (11–13). In a nutshell, the accessible innovations are critically determined by a genotype’s position in genotype space (16) (Fig. 1).Open in a separate windowFig. 1.Phenotype-based view on evolvability. (A) Evolvability accounts for the accessible novel phenotypes, whereas developmental constraints imply that certain hypothetical forms are not possible: phenotype 2 (purple) is not available by gradual mutation. (B) Innovations accessible from a given genotype constitute its phenotypic neighborhood. The arrangement and diversity of this neighborhood is a measure of the genotype’s evolvability (16). Genotype space is high dimensional, but we schematically represent it here in 2D for illustrative purposes.Although the abovementioned features of genotype-phenotype maps have been much studied, another important aspect of the system has thus far been neglected. None of the existing studies addressed the impact of the underlying dynamical mechanism of a gene circuit on its evolvability. By mechanism, we mean the causal dynamics responsible for the trajectory of the system (i.e., the spatiotemporal course of gene expression) resulting in the final phenotype. In addition to the increasing awareness that dynamics itself is a decisive property of gene circuits (17), several specific observations led us to hypothesize that dynamics does impact on evolvability.First, to achieve a given biological function, a gene circuit uses one of few fundamental solutions referred to as dynamical mechanisms (5–7, 18–20). More specifically, circuits with the same underlying dynamical mechanism share a common arrangement of phase portraits (20, 21). Second, Cotterell and Sharpe (6) revealed that, for a simple patterning function, it is not possible to smoothly and functionally transition from one mechanism to another. That is, in contrast to the common view (11–13), this particular neutral space does not form a single fully connected region when the underlying mechanism is taken into account. Instead, the neutral space for the simple patterning function studied by Cotterell and Sharpe (6) breaks up into scattered islands of genotypes characterized by distinct underlying mechanisms. These observations suggest that evolvability may be constrained specifically by the dynamical mechanism of the gene circuit. As neutral spaces can be broken up into a discrete collection of separated islands, the process of neutral drift may be limited to these mechanism-specific regions.To assess the impact of dynamical mechanisms, we chose to study circuits that control spatial (multicellular) gene expression patterns. It is well established in developmental biology that the spatial organization of gene expression orchestrates cell differentiation. Their diversification causes evolution of both modest morphological traits, such as novel pigmentation patterns (22), and major evolutionary breakthroughs, such as new body structures (23). Here we chose to address the interpretation of a morphogen gradient by a field of cells into different cell fates (5–7, 18, 24–27) (Fig. 2A), a critical patterning event in embryo’s morphogenesis (28). We build on the work of Cotterell and Sharpe (6), who extracted six fundamental mechanisms for this patterning task: Bistable, Incoherent feed-forward, Mutual Inhibition, Overlapping Domains, Classical, and Frozen Oscillator (Fig. 2B and SI Appendix, Fig. S1).Open in a separate windowFig. 2.Alternative mechanisms to achieve a single phenotype. (A) Within the French Flag conceptual framework, a preestablished fixed concentration gradient (input) is interpreted by a one-dimensional row of cells into different cell fates through a threshold-dependent mechanism. Additionally, cells communicate to one another through diffusive gene products (dashed arrows). We exhaustively enumerate all possible three-gene circuit topologies and sample large numbers of genotypes (i.e., parameter values; SI Appendix, Methods). Solutions of our search are genotypes able to interpret the morphogen gradient into a band of gene expression (6). Similar exhaustive approaches have being adopted for exploring a variety of biological functions, such as temporal behaviors (7, 25) or other spatial patterning functions (5, 18). (B) A stripe-forming circuit uses one of six distinct mechanisms (6), each mechanism uses a distinct gene expression dynamics in space and time to reach the same phenotype. Importantly, Mutual Inhibition (bicoid-hunchback-knirps), Incoherent feed-forward (caudal-knirps-giant), and Classical (hunchback-krüppel-knirps) are involved in Drosophila anterior-posterior patterning (26), whereas Incoherent feed-forward controls the mesoderm inducer Xenopus Brachyury (27).For the current study, we analyzed each of these six mechanisms independently and obtained a mechanism-specific measure of evolvability. We found that, indeed, the likelihood of accessing distinct phenotypic innovations is different for each dynamical mechanism, despite the fact that they all produce the same phenotype. Our analysis uncovers key features of the mechanistic neutral spaces and provides useful insight into how phenotypic transitions and thus innovations occur.     

囊型肝包虫囊周肝细胞"消失"机制的初步研究

目的 观察囊型肝包虫周围肝细胞的病理形态学变化（肝细胞萎缩、坏死、凋亡）,初步探讨囊型肝包虫病肝细胞“消失”机制。方法 对30例肝包虫囊肿周围肝组织通过光镜观察肝组织的病理形态学变化,运用TUNEL法测定肝细胞凋亡,采用免疫组化技术检测肝包虫囊肿周围肝组织及正常肝组织中Bcl—2及Bax蛋白的表达。结果 TUNEL检测囊型肝包虫病患者肝细胞凋亡指数（TI）为0．12％,与正常肝组织（TI=O．16％）比较差异无显著性（P〉0．05）;Bc卜2及Bax蛋白的囊周肝组织呈低表达,分别为6．67％和13．33％,正常肝组织Bcl一2和Bax均为10．00％,差异无显著性（P〉O＋05）。病理组织学观察示肝细胞萎缩,肝细胞坏死明显。结论 肝细胞萎缩、坏死可能是引起肝细胞“消失”的主要机制,肝细胞压迫性和营养不良性萎缩、肝细胞坏死、肝细胞凋亡共同参与囊型肝包虫病肝细胞“消失”过程。     

The association of lipopolysaccharide and inflammatory factors with hepatopulmonary syndrome and their changes after orthotopic liver transplantation

Background

The level of lipopolysaccharides (LPS) and inflammatory factors were higher in end stage liver disease patient than in normal person for the damage of intestinal mucosal barrier function. Hepatopulmonary syndrome (HPS) was a common pulmonary complication in end stage liver disease. But the association of LPS and inflammatory factors such as toll like receptor 2 (TLR2), TNF-α and ET-1 with the development of HPS was undefined.

Methods

Thirty-one HPS patients were researched (26 patients were performed liver transplantation, five were not). Ten healthy volunteers were recruited as negative control. Blood was collected from the 26 HPS patients before and 3, 7, 14, 21 and 28 days after orthotopic liver transplantation (OLT), and from five HPS patients without OLT and ten healthy volunteers once to detect TLR2 mRNA and iNOS mRNA in peripheral blood monocytes and plasma LPS, TNF-α and ET-1 level. Their levels before and after OLT were compared.

Results

TLR2 mRNA, iNOS mRNA, LPS, TNF-α and ET-1 before OLT in HPS patients were 336,594.1±366,901.1, 63,982.2±74,127.5 copies/ugRNA, 4.3±3.3, 90.1±76.0 and 319.9±124.4 ng/L, respectively. They were 10,338.3±3,814.6, 19,168.5±2,417.4 copies/ugRNA, 0.94±0.69, 2.7±0.1 and 84.2±10.6 ng/L in normal control group. They were significantly higher in HPS patients than those in control group (P<0.05). After OLT, liver function improved to normal. Also TLR2 mRNA, TNF-α and ET-1 decreased in HPS patients after OLT compared with those before OLT. And PaO₂ and PaO₂/FiO₂ improved greatly with intrapulmonary shunt decreased to normal after OLT.

Conclusions

Lipopolysaccharides at the end stage of liver disease with the release of series of inflammatory factors may be associated with the development of HPS.     

Resolving the HONO formation mechanism in the ionosphere via ab initio molecular dynamic simulations

Solar emission produces copious nitrosonium ions (NO⁺) in the D layer of the ionosphere, 60 to 90 km above the Earth’s surface. NO⁺ is believed to transfer its charge to water clusters in that region, leading to the formation of gaseous nitrous acid (HONO) and protonated water cluster. The dynamics of this reaction at the ionospheric temperature (200–220 K) and the associated mechanistic details are largely unknown. Using ab initio molecular dynamics (AIMD) simulations and transition-state search, key structures of the water hydrates—tetrahydrate NO⁺(H₂O)₄ and pentahydrate NO⁺(H₂O)₅—are identified and shown to be responsible for HONO formation in the ionosphere. The critical tetrahydrate NO⁺(H₂O)₄ exhibits a chain-like structure through which all of the lowest-energy isomers must go. However, most lowest-energy isomers of pentahydrate NO⁺(H₂O)₅ can be converted to the HONO-containing product, encountering very low barriers, via a chain-like or a three-armed, star-like structure. Although these structures are not the global minima, at 220 K, most lowest-energy NO⁺(H₂O)₄ and NO⁺(H₂O)₅ isomers tend to channel through these highly populated isomers toward HONO formation.The ionosphere is the largest layer in the Earth''s atmosphere, ranging in altitude from ∼60 to 1,000 km and includes the thermosphere and parts of the mesosphere and exosphere. The ionosphere contains a high concentration of electrons and ions because of the ionization of gases in that region by short wavelength radiation from the Sun. Therefore, these species play an important role in atmospheric electricity, influencing radio propagation to different regions on the Earth’s surface and space-based navigational systems (1). The D layer is the innermost layer of the ionosphere, ranging from 60 to 90 km in altitude, where Lyman series-α hydrogen radiation from the Sun gives rise to abundant nitrosonium ions (NO⁺). In addition to the ionospheric reaction between NO⁺ and water, explorations of the chemical reactivity of NO⁺ and water clusters (2–4) have implications for understanding the mechanisms of atmospherically relevant reactions in water clusters (5–9).Over the past two decades, several experimental and theoretical studies (10–13) have focused on understanding the chemical and physical properties of the small-sized hydrated nitrosonium ion NO⁺(H₂O)_n, where n = 1–5. Two key processes have been proposed for HONO formation:NO⁺(H₂O)_n + H₂O → {(HONO)H⁺(H₂O)_n}? → H⁺(H₂O)_n + HONO?.[1]Lee and coworkers (14) used vibrational spectroscopy to obtain clear evidence of the rearrangement of the NO⁺(H₂O)_n cluster by observing the appearance of new hydrogen (H)-bonded OH stretching lines. Using quantum molecular dynamics, Ye and Cheng (15) suggested possible structures and corresponding IR spectra for NO⁺(H₂O)_n (n = 1–3) clusters. In a major experimental breakthrough, Relph et al. (16) showed that the extent to which reaction 1 produces HONO and H⁺(H₂O)_n depends on the size and shape of the water clusters. Another key finding was that the reactions for HONO production start with the n = 4 water cluster. Later, the importance of the tetrahydrate isomer NO⁺(H₂O)₄ to its conversion to proton hydrate and HONO at temperature beyond 150 K was further demonstrated experimentally by Eyet et al. (11). Indeed, before Eyet’s study, Siefermann and Abel (17) had already noted that the configurations of the trihydrate and tetrahydrate isomers examined in Relph et al.’s experiment were frozen because of the very low temperature used (5 K). At this low temperature, the most abundant water cluster structures are those found at the global minima of the potential energy surface. At temperatures that are relevant to the ionosphere (200–220 K), these lowest-lying isomers may not directly contribute to the interconversion processes involving the hydrated NO⁺(H₂O)_n ion.An early study suggested that the low rate of reaction 1 can be attributed to the fact that the reactive species responsible for HONO formation include a higher-energy isomer of NO⁺(H₂O)_n that is responsible to the release of a proton (12). Asada et al. (18) reported high-level ab initio molecular-orbital calculations and identified tens of low-energy isomers of NO⁺(H₂O)₄ and NO⁺(H₂O)₅. They also pointed out that relatively higher-energy reactant, transition-state, and product isomers are involved in the formation of HONO from NO⁺(H₂O)_n (n = 4 and 5) clusters. But, the nature of the mechanism by which these relatively higher-energy isomers (in the frozen state at 0 K) can directly contribute to the interconversion processes at temperatures relevant to the ionosphere is little studied.In light of the lack of experimental studies of the dynamics of isomer transformation, we performed Born–Oppenheimer ab initio molecular dynamics (AIMD) simulations to explore the dynamic behaviors of trihydrate NO⁺(H₂O)₃, tetrahydrate NO⁺(H₂O)₄, and pentahydrate NO⁺(H₂O)₅ clusters at 220 K. Our results suggest that 220 K is adequate to drive the isomer interconversion from the lowest-lying isomers to the critical chain-like isomers. Furthermore, based on the climbing image nudged-elastic-band method, a more realistic transition state for the formation of hydrated protons and HONO (coexisting in the tetrahydrate) was identified, with the reactant being the critical tetrahydrate NO⁺(H₂O)₄ isomer. For pentahydrate, two reaction pathways are revealed by the AIMD simulations. Furthermore, the distribution of low-lying isomers at 220 K, including both highly populated critical and less-populated local-minimum isomers, is obtained. In agreement with the results of Relph et al. (16), there is no observed charge transfer between the NO⁺ and the water clusters in the n = 1 or n = 2 NO⁺(H₂O)_n clusters, indicating that these small clusters are inert. The charge transfer observed for clusters with n ≥ 3 suggests the possible formation of HONO from the NO⁺(H₂O)_n clusters. However, the population of water clusters decreases rapidly with increasing n because of the scarcity of the water molecules in the D layer of the ionosphere (17). Therefore, the trihydrate, tetrahydrate, and pentahydrate clusters are most likely the prevailing reactive species for HONO formation in the ionosphere and thus constitute the focus of our AIMD simulations. All the AIMD simulations in this work are performed in the form of the Beche–Lee–Yang–Parr functional (19, 20) with Grimme’s dispersion correction (21) (denoted as BLYP-D method) which can well describe the trend of the charge variation of the NO⁺ hydrates systems (see Fig. S1). Note that our study here is mainly focused on the formation of the HONO species in the hydrates, corresponding to the first step in reaction 1. The detachment of the HONO species from the hydrated proton, which is an endothermic process, is not considered here.Open in a separate windowFig. S1.Charge on the NO varies with the isomers for tetrahydrates on the basis of the Mullikan charge analysis at the BLYP-D and the CCSD(T)/aug-cc-pVTZ//MP2/aug-cc-pVTZ levels of theory [here, CCSD(T) and MP2 refer to the coupled-cluster method with singlet, doublet, and triplet excitations and the second-order Møller–Plesset perturbation theory, respectively]. The CCSD(T)//MP2 denotes that the structure is optimized at the MP2/aug-cc-pVTZ level, whereas the charge analysis is performed at the CCSD(T)/aug-cc-pVTZ level.For the trihydrate cluster, the three experimentally detected low-lying isomers (18) are called 3-α, 3-β, and 3-γ (Fig. 1). Notably, our AIMD simulation shows the isomer interconversion from the two lowest-lying isomers, 3-α and 3-β, to 3-γ (Fig. S2). In the course of AIMD simulation, the N–O₁ distance decreases from ∼2.20 to ∼1.90 Å, concurrent with a slight elongation of the O₁–H₁ and O₁–H₂ bonds, implying the conversion of isomer 3-α or 3-β to the 3-γ isomer (Movies S1A and S1B). No isomerization events are observed in the AIMD simulation with the initial 3-γ configuration, indicating the high thermal stability of 3-γ at 220 K. Hence, the 3-γ isomer is expected to exhibit the highest abundance among trihydrate clusters in the D layer of the ionosphere. Moreover, for the 200-ps AIMD simulation of 3-γ, no evidence of dissociation of the O–H bonds in water molecules was observed, consistent with the previous experiment-based conclusion (16) that trihydrate clusters do not play a major role in reaction 1.Open in a separate windowFig. 1.Illustration of the dynamic-driven isomer interconversion observed in AIMD simulations of the trihydrates and tetrahydrates of NO⁺. The highlighted structures in brackets represent the most likely reaction pathway from the critical (highly populated) isomer 4E to the product isomer 4ii. White, blue, and red spheres represent hydrogen, nitrogen, and oxygen atoms, respectively.Open in a separate windowFig. S2.N–O₁ distance change with time for isomers 3-α (black), 3-β (red), and 3-γ (blue). Time required for the structural transformation from 3-α and 3-β to 3-γ. The atomic label is given. Note that both H₁ and H₂ bind with two different water molecules via H-bond arrangement, which is the so-called “symmetrical H bond.”For the tetrahydrate cluster, the four lowest-lying isomers 4A, 4B, 4C, and 4E (Fig. 1) (18) were selected to investigate their dynamic behaviors at 220 K. As shown in Fig. S3, the O–H bonds of the water molecule directly bound to the NO⁺ are <1.20 Å during the 200-ps AIMD simulations, indicating the absence of HONO-forming reactions in that time period. In contrast, sudden changes in the N–O distance (e.g., at ∼26 ps in Fig. S3A; the definition of N–O distance is given in the caption of Fig. S3) are observed in all four independent AIMD simulations (black lines in Fig. S3), indicating isomer interconversion. To characterize the degree of isomer interconversion, the bond-orientational order parameter (Ψ) given byΨ=1n|∑j=1neinφij|is computed, where n is the total number of atoms j within a given radius cutoff and φ_i?j is the angle between the vector connecting the target atom i with the neighboring atom j and the reference vector connecting the target atom i and the system’s center of mass (marked by the black solid circle in the Inset of Fig. 2A). Two different target atoms with their corresponding neighboring (source) atom j were selected to characterize the structural variation: (i) the N atom in the NO⁺ motif with the O atoms in the water molecules as the source of atom j, and (ii) the O atom (shown by the green sphere in Fig. 2A, Inset) in the water molecule located at the longer end of the chain structure with the O atoms in the other water molecules that forms a hydrogen bond with the target O atom as the source of atom j. In chain-like structures, such as isomer 4E, only one O atom exists within 2.80 Å of the N atom, whereas the target O atom only forms one hydrogen bond with the neighboring water molecule. Hence, the logarithms of Ψ_N?O and Ψ_O?O take values of zero for isomer 4E. For other isomers, either Ψ_N?O or Ψ_O?O is nonzero. Fig. 2A shows the time-dependent order parameters given by the logarithms of Ψ_N?O (red line) and Ψ_O?O (black line), with isomer 4A as the initial structure. The disappearance of the red peaks at ∼26 ps clearly results from the isomer transformation from 4C to 4E (Figs. S3A and ​andS4S4 and Movie S2A). The cyclization of 4E leads to the formation of an additional hydrogen bond with the target O atom, resulting in nonzero values of the logarithm of Ψ_O?O for the ∼50–70-ps time period (see c-4E isomer in Fig. S4). The proximity of the N and O atoms of two nearest water molecules (the corresponding isomer is denoted as d-4E in Fig. S4) results in a small red peak at ∼120 ps. Similar isomer interconversion is also observed in other AIMD simulations with 4B, 4C, or 4E as the initial structure. The corresponding time-evolution data for Ψ_N?O or Ψ_O?O and associate isomer structures are shown in Figs. S5 and ​andS4,S4, respectively.Open in a separate windowFig. 2.(A) Time evolution of the logarithms of the bond-orientational order parameters Ψ_N?O (red line) and Ψ_O?O (black line). (Inset) Illustration of the angle φ_i?j used to calculate Ψ_N?O and Ψ_O?O, where white and red spheres represent oxygen and hydrogen atoms, respectively, and blue and green spheres represent the target nitrogen and oxygen atoms, respectively, used to calculate the bond-orientational order parameter. The pie charts in B–E denote the populations of various isomers observed in four independent AIMD simulations with initial structures of 4A, 4B, 4C, and 4E, respectively. The geometric structures of the isomers are given in Fig. S4.Open in a separate windowFig. S3.Time evolution of the N–O (black line) (where O is the O atom of the nearest H₂O molecule next to the N atom of the NO⁺ ion) and the O–H (red line) (where O–H refers to the averaged O–H bond length for the water molecule nearest to the NO⁺ ion) distances for the AIMD simulations of NO⁺(H₂O)₄ clusters with different initial isomer: (A) isomer 4A, (B) isomer 4B, (C) isomer 4C, and (D) isomer 4E. (Inset) Images represent the initial structures used in each AIMD simulation.Open in a separate windowFig. S4.Geometrical structures of the observed isomers in the AIMD simulation with isomer 4A as the initial structure. The white, blue, and red spheres represent the hydrogen, nitrogen, and oxygen atoms. The arrows and three pairs of circled numbers indicate several possible shifting directions of molecules and corresponding interconversion of isomers.Open in a separate windowFig. S5.Time evolution of the logarithm of the bond-orientational order parameterΨ_N?Ο (red lines) and Ψ_O?O (black lines) for the AIMD simulations starting from isomer 4B (Top), 4C (Middle), and 4E (Bottom), respectively.The chain-like water structure is the critical structure bridging two different isomers during isomer interconversion. As shown in Fig. 2A and Fig. S5, the zero-value interval between two peaks indicates the appearance of isomer 4E during the isomer conversion. More importantly, the population analysis of each isomer over the entire 200-ps AIMD simulation suggests that the chain-like water structure of 4E is much more abundant than the other isomers (Fig. 2 B–E). Specifically, in the four independent AIMD simulations with initial structures of 4A, 4B, 4C, and 4E, the obtained population values are highest for 4E: ∼62.25%, 77.66%, 61.49%, and 86.89%, respectively. Note that at 0 K, BLYP-D functional (19, 20; see Supporting Information, Computational Details) predicts that 4E is lower in energy than 4A (i.e., BLYP-D introduces some biases toward 4E over 4A, see Fig. S6 for MP2 results). But, 4E is still about 1 kcal/mol higher in energy than 4B or 4C at the BLYP-D level. At 220 K, 4E becomes the most thermodynamically favorable isomer at the BLYP-D level. Hence, the 4E isomer can be viewed as the critical isomer among the tetrahydrate clusters and plays a critical role in the D layer of the ionosphere.Open in a separate windowFig. S6.Electronic energies (ΔE), zero-point-energy corrected electronic energies (ΔE+ZPE), and the Gibbs free energies (ΔG) relative to isomer 4A for tetrahydrate isomers at the MP2 level of theory.The HONO-containing tetrahydrate isomer detected experimentally at 5 K (named 4-ii in ref. 16) has nearly the same structure as 4G (Fig. S7). The interconversion between isomer 4-ii and 4G through HONO rotation and flipping of the H₃O⁺ groups was frequently observed in the AIMD simulations (Movie S2B). More importantly, no breaking down of the N–O bonds in HONO was observed in the course of the 200-ps AIMD simulation, suggesting that both isomers are highly stable at 220 K. Therefore, the 4-ii isomer can be viewed as the final product of HONO formation, consistent with the experimental detection of 4-ii at 5 K. To confirm this interpretation, we used climbing image nudge-elastic-band calculations (22) to search for the transition state that bridges the 4E and 4-ii isomers. As shown in Fig. 1, the movement of the water molecule at the short end of the chain-like structure toward the long end and the subsequent formation of two H bonds with two neighboring water molecules led to proton transfer between the two neighboring water molecules, giving rise to the transition state (TS in Fig. 1). Upon passing over the TS, the original water molecule near the short end breaks one hydrogen bond while retaining the other hydrogen bond with the protonated species, concurrent with the formation of HONO species. In this cooperative process, the movement of the water molecule at the short end leads to the formation of a cyclic structure, where the two water molecules and the HONO species act as hydrogen-bond acceptors and form a complete solvation shell around the H₃O⁺ ion. The formation of such a solvation shell can effectively stabilize the central H₃O⁺ ion, a well-established fact in the gas-phase reaction involving ionic clusters (23–26). Due to the stabilization effect, the formation of HONO-containing isomer 4-ii, from the highly populated isomer 4E, entails a low-energy barrier of ∼2.1 kcal/mol. Thus, at the ionospheric temperatures (200–220 K), a chemical equilibrium between 4E and the HONO-containing isomers 4-ii is expected to be an important dynamic channel for HONO formation. Note that in our AIMD simulations, the nuclear quantum effect and the hydrogen tunneling effect are not included. In general, the nuclear quantum effect is equivalent to the lowering of density-functional theory (e.g., BLYP-D) temperature of water by certain degrees (27), whereas the hydrogen tunneling would speed up the proton transfer process in our system not included in the AIMD simulations. Nevertheless, the two effects seem to somewhat offset each other and, as a result, may not affect the qualitative reaction mechanism concluded from the AIMD simulations.Open in a separate windowFig. S7.Geometrical structures of the isomer 4-ii and 4G.Another channel for HONO formation can occur through the pentahydrate NO⁺(H₂O)₅, although the population of pentahydrate clusters is expected to be much lower than that of the tetrahydrate clusters. Here, the lowest-lying four isomers, 5A, 5B, 5D, and 5M (23), are selected as the initial structures in four independent AIMD simulations. In the simulation starting with isomer 5A, no HONO formation or appreciable changes in the N–O and O–H distances were observed within the 200-ps simulation, suggesting that 5A is a highly stable isomer. In contrast, the formation of HONO species is directly observed in the AIMD simulations with initial structures of 5B, 5D, and 5M, indicating that in this case, the HONO-forming reaction has a very low energy barrier. Moreover, as shown in Fig. 3, the final HONO-containing products obtained in the three independent AIMD simulations exhibit the same structure, named 5Γ, which contains a chain-like water structure similar to that found in 4E. To the best of our knowledge, the pentahydrate isomer 5Γ has not been reported in the literature, likely because pentahydrate isomers were previously modeled without considering dynamic effects at 220 K.Open in a separate windowFig. 3.Snapshots of AIMD simulations at different time stages (unit, ps) with initial structures of (A) 5B, (B) 5D, and (C) 5M. White, blue, and red spheres represent hydrogen, nitrogen, and oxygen atoms, respectively. As shown in Fig. 4A, 5C indicates a group of isomers with similar structures. Isomers 5Λ and isomer 5Y are highly populated isomers before the final product 5Γ.As shown by the time evolution of the N–O and O–H distances (Fig. S8), the N–O distance exhibited two sudden decreases, accompanied by sudden increases in the O–H distance. This result suggests that two reaction steps are likely involved in HONO formation in pentahydrate clusters. As shown in Fig. 3A, at ∼13.8 ps, 5B evolves into a group of four intermediate isomers (named isomers 5C-i to 5C-iv) whose structures can all be viewed as derivative from the tetrahydrate isomer 4C (with the addition of one water molecule to different sites of 4C). The added water molecule can move around, thus leading to interconversion of the four isomers as shown in Fig. 4A. The isomer 5C can evolve to a chain-like structure, named 5Λ (e.g., at ∼97.16 ps in Fig. 3A), corresponding to a sudden change in the N–O and O–H distances (Movie S3A). Detailed population analysis of isomers before the formation of HONO (<207.56 ps) indicates high population of both isomer groups 5C (38.63%) and 5Λ (53.19%) (Fig. 4B). Such a population distribution is akin to that for tetrahydrates where the chain-like structure 4E entails the highest population, followed by the isomer 4C (Fig. 2 B and D). The addition of one water molecule can effectively promote the movement of one tail water molecule toward the other end of the chain structure. Meanwhile, proton transfer is observed between the two neighboring water molecules, as shown in Fig. 3A, generating the final product 5Γ (Movie S3B), while the water molecules persist in a chain-like structure similar to that of 4E.Open in a separate windowFig. 4.(A) Schematic illustration of the relocation of one water molecule (with green sphere) around the 4C structure in four different sites, resulting in a group of four different isomers (5C-i to 5C-iv). (B and C) Population of major intermediate isomer observed before the formation of HONO in the AIMD simulation, starting with isomer 5B and 5D, respectively. The isomer structures of 5σ, 5Σ, and 5M′ are illustrated in Fig. S9.Open in a separate windowFig. S8.Time evolution of N–O (black line) and O–H (red line) distance during the AIMD simulation with isomer 5B (Top), 5D (Middle),and 5M (Bottom) as the initial structure.Open in a separate windowFig. S9.Geometry structures for the isomer 5σ, 5Σ, and 5M′ of pentahydrates.In the AIMD simulation starting with the 5D isomer, isomer 5C-i has the highest population before the formation of HONO (<22. 71 ps, Figs. 3B and ​and4C).4C). Here, 5C-i evolves to a three-armed, star-like structure (named 5Y) with the H₃O⁺ at the center, while the N–O distance shortened to ∼1.60 Å and the O–H distance increased to 1.51 Å; The isomer 5Y entails HONO formation (Movie S3C). The HONO-containing 5Y lasts >130 ps during the AIMD simulations, and at ∼155.99 ps the water molecule next to HONO approaches the chain-like structure, further increasing the O–H distance (Fig. S8), and then forms the final product 5Γ (Movie S3D). In the AIMD simulation starting with isomer 5M, which entails a planar cyclic structure, the HONO formation proceeds with a similar path (Fig. 3C) as 5D (Movies S3E and S3F). The same reaction is also observed when a much shorter AIMD time step (0.1 fs) was used in an independent AIMD simulation (Movie S3G). Notably, it converts to the HONO-containing isomer 5Y within 5 ps. Such fast conversion is probably attributed to the initial cyclic water structure which is also observed in the other two cases (Fig. 3). Again, 5Y changes to 5Γ after a relatively longer period of AIMD run.In conclusion, we have shown that the tetrahydrate and pentahydrate structures located at the global minima of potential-energy surface cannot be converted directly to HONO species at the 220-K ionospheric temperature. To achieve HONO formation, the lowest-lying isomers of tetrahydrates must first be converted to the highly populated critical isomer 4E in a dynamic fashion at 220 K. Subsequently, the critical isomer 4E can be converted to the HONO-containing product with encountering very low barriers at 220 K, consistent with previous experiment (11, 17). We also confirmed another experimental finding (18) that the 3γ trihydrate cluster is a highly stable nonreactive cluster, even at 220 K (Fig. 1). However, the addition of one water molecule to 3γ can directly lead to the critical 4E isomer. Thus, the chemical equilibrium between 4E and the product 4ii coupled with the thermodynamically favorable conversion process from the three lowest-lying isomers at 0 K—4A, 4B, and 4C—to the 4E isomer at 220 K represents an important dynamic channel for HONO formation in the ionosphere.Another dynamic channel for HONO formation involves pentahydrate isomers. Upon the addition of one extra water molecule, the formation of HONO can be significantly much faster (11), for example, via a pathway similar to that proposed in the tetrahydrates, namely, via the isomer 5C which contains the motif 4C, followed by the formation of a chain-like water structure akin to 4E and by the bending of the chain to form the product 5Γ. In comparison with the tetrahydrates, the extra water molecule promotes the movement of water molecules, thus leading to the much faster formation of HONO in AIMD simulations. Another possible channel for the formation of HONO could be through the three-armed, star-like precursor isomer 5Y, followed by the combination of a single water molecule with the chain-like water structure to form the product 5Γ. The chemical equilibrium between highly populated 5Λ or 5Y and 5Γ corresponds to the second dynamic channel for HONO formation in the ionosphere. The discovery of these two dynamic channels brings previously unidentified insights into the HONO formation in the 200–220-K temperature range, a key reaction in the D layer of the ionosphere (17).     

Effect of Annealing Process on the Properties of Ni(55%)Cr(40%)Si(5%) Thin-Film Resistors

Resistors in integrated circuits (ICs) are implemented using diffused methods fabricated in the base and emitter regions of bipolar transistor or in source/drain regions of CMOS. Deposition of thin films on the wafer surface is another choice to fabricate the thin-film resistors in ICs’ applications. In this study, Ni(55%)Cr(40%)Si(5%) (abbreviated as NiCrSi) in wt % was used as the target and the sputtering method was used to deposit the thin-film resistors on Al₂O₃ substrates. NiCrSi thin-film resistors with different thicknesses of 30.8 nm~334.7 nm were obtained by controlling deposition time. After deposition, the thin-film resistors were annealed at 400 °C under different durations in N₂ atmosphere using the rapid thermal annealing (RTA) process. The sheet resistance of NiCrSi thin-film resistors was measured using the four-point-probe method from 25 °C to 125 °C, then the temperature coefficient of resistance could be obtained. We aim to show that resistivity of NiCrSi thin-film resistors decreased with increasing deposition time (thickness) and the annealing process had apparent effect on the sheet resistance and temperature coefficient of resistance. We also aim to show that the annealed NiCrSi thin-film resistors had a low temperature coefficient of resistance (TCR) between 0 ppm/°C and +50 ppm/°C.     

The lattice as allosteric effector: structural studies of alphabeta- and gamma-tubulin clarify the role of GTP in microtubule assembly

GTP-dependent microtubule polymerization dynamics are required for cell division and are accompanied by domain rearrangements in the polymerizing subunit, alphabeta-tubulin. Two opposing models describe the role of GTP and its relationship to conformational change in alphabeta-tubulin. The allosteric model posits that unpolymerized alphabeta-tubulin adopts a more polymerization-competent conformation upon GTP binding. The lattice model posits that conformational changes occur only upon recruitment into the growing lattice. Published data support a lattice model, but are largely indirect and so the allosteric model has prevailed. We present two independent solution probes of the conformation of alphabeta-tubulin, the 2.3 A crystal structure of gamma-tubulin bound to GDP, and kinetic simulations to interpret the functional consequences of the structural data. These results (with our previous gamma-tubulin:GTPgammaS structure) support the lattice model by demonstrating that major domain rearrangements do not occur in eukaryotic tubulins in response to GTP binding, and that the unpolymerized conformation of alphabeta-tubulin differs significantly from the polymerized one. Thus, geometric constraints of lateral self-assembly must drive alphabeta-tubulin conformational changes, whereas GTP plays a secondary role to tune the strength of longitudinal contacts within the microtubule lattice. alphabeta-Tubulin behaves like a bent spring, resisting straightening until forced to do so by GTP-mediated interactions with the growing microtubule. Kinetic simulations demonstrate that resistance to straightening opposes microtubule initiation by specifically destabilizing early assembly intermediates that are especially sensitive to the strength of lateral interactions. These data provide new insights into the molecular origins of dynamic microtubule behavior.