Switchable pi-coordination and C-H metallation in small-cavity macrocyclic uranium and thorium complexes

New, conformationally restricted ThIV and UIV complexes, [ThCl2(L)] and [UI2(L)], of the small-cavity, dipyrrolide, dianionic macrocycle trans-calix[2]benzene[2]pyrrolide (L)2− are reported and are shown to have unusual κ5:κ5 binding in a bent metallocene-type structure. Single-electron reduction of [UI2(L)] affords [UI(THF)(L)] and results in a switch in ligand binding from κ5-pyrrolide to η6-arene sandwich coordination, demonstrating the preference for arene binding by the electron-rich UIII ion. Facile loss of THF from [UI(THF)(L)] further increases the amount of U–arene back donation. [UI(L)] can incorporate a further UIII equivalent, UI3, to form the very unusual dinuclear complex [U2I4(L)] in which the single macrocycle adopts both κ5:κ5 and η6:κ1:η6:κ1 binding modes in the same complex. Hybrid density functional theory calculations carried out to compare the electronic structures and bonding of [UIIII(L)] and [UIII2I4(L)] indicate increased contributions to the covalent bonding in [U2I4(L)] than in [UI(L)], and similar U–arene interactions in both. MO analysis and QTAIM calculations find minimal U–U interaction in [U2I4(L)]. In contrast to the reducible U complex, treatment of [ThCl2(L)] with either a reductant or non-nucleophilic base results in metallation of the aryl rings of the macrocycle to form the (L−2H)4− tetraanion and two new and robust Th–C bonds in the –ate complexes [K(THF)2ThIV(μ-Cl)(L−2H)]2 and K[ThIV{N(SiMe3)2}(L−2H)]

Evaluation of a Bayesian inference network for ligand-based virtual screening

Background Bayesian inference networks enable the computation of the probability that an event will occur. They have been used previously to rank textual documents in order of decreasing relevance to a user-defined query. Here, we modify the approach to enable a Bayesian inference network to be used for chemical similarity searching, where a database is ranked in order of decreasing probability of bioactivity. Results Bayesian inference networks were implemented using two different types of network and four different types of belief function. Experiments with the MDDR and WOMBAT databases show that a Bayesian inference network can be used to provide effective ligand-based screening, especially when the active molecules being sought have a high degree of structural homogeneity; in such cases, the network substantially out-performs a conventional, Tanimoto-based similarity searching system. However, the effectiveness of the network is much less when structurally heterogeneous sets of actives are being sought. Conclusion A Bayesian inference network provides an interesting alternative to existing tools for ligand-based virtual screening

A model for transition of 5 '-nuclease domain of DNA polymerase I from inert to active modes

Bacteria contain DNA polymerase I (PolI), a single polypeptide chain consisting of similar to 930 residues, possessing DNA-dependent DNA polymerase, 3'-5' proofreading and 5'-3' exonuclease (also known as flap endonuclease) activities. PolI is particularly important in the processing of Okazaki fragments generated during lagging strand replication and must ultimately produce a double-stranded substrate with a nick suitable for DNA ligase to seal. PolI's activities must be highly coordinated both temporally and spatially otherwise uncontrolled 5'-nuclease activity could attack a nick and produce extended gaps leading to potentially lethal double-strand breaks. To investigate the mechanism of how PolI efficiently produces these nicks, we present theoretical studies on the dynamics of two possible scenarios or models. In one the flap DNA substrate can transit from the polymerase active site to the 5'-nuclease active site, with the relative position of the two active sites being kept fixed; while the other is that the 5'-nuclease domain can transit from the inactive mode, with the 5'-nuclease active site distant from the cleavage site on the DNA substrate, to the active mode, where the active site and substrate cleavage site are juxtaposed. The theoretical results based on the former scenario are inconsistent with the available experimental data that indicated that the majority of 5'-nucleolytic processing events are carried out by the same PolI molecule that has just extended the upstream primer terminus. By contrast, the theoretical results on the latter model, which is constructed based on available structural studies, are consistent with the experimental data. We thus conclude that the latter model rather than the former one is reasonable to describe the cooperation of the PolI's polymerase and 5'-3' exonuclease activities. Moreover, predicted results for the latter model are presented

Huntingtin gene repeat size variations affect risk of lifetime depression

Huntington disease (HD) is a severe neuropsychiatric disorder caused by a cytosine-adenine-guanine (CAG) repeat expansion in the HTT gene. Although HD is frequently complicated by depression, it is still unknown to what extent common HTT CAG repeat size variations in the normal range could affect depression risk in the general population. Using binary logistic regression, we assessed the association between HTT CAG repeat size and depression risk in two well-characterized Dutch cohorts─the Netherlands Study of Depression and Anxiety and the Netherlands Study of Depression in Older Persons─including 2165 depressed and 1058 non-depressed persons. In both cohorts, separately as well as combined, there was a significant non-linear association between the risk of lifetime depression and HTT CAG repeat size in which both relatively short and relatively large alleles were associated with an increased risk of depression (β = −0.292 and β = 0.006 for the linear and the quadratic term, respectively; both P < 0.01 after adjustment for the effects of sex, age, and education level). The odds of lifetime depression were lowest in persons with a HTT CAG repeat size of 21 (odds ratio: 0.71, 95% confidence interval: 0.52 to 0.98) compared to the average odds in the total cohort. In conclusion, lifetime depression risk was higher with both relatively short and relatively large HTT CAG repeat sizes in the normal range. Our study provides important proof-of-principle that repeat polymorphisms can act as hitherto unappreciated but complex genetic modifiers of depression

A Stochastic Differential Equation Inventory Model

© 2018, The Author(s). Inventory for an item is being replenished at a constant rate whilst simultaneously being depleted by demand growing randomly and in relation to the inventory level. A stochastic differential equation is put forward to model this situation with solutions to it derived when analytically possible. Probabilities of reaching designated a priori inventory levels from some initial level are considered. Finally, the existence of stable inventory states is investigated by solving the Fokker–Planck equation for the diffusion process at the steady state. Investigation of the stability properties of the Fokker–Planck equation reveals that a judicious choice of control strategy allows the inventory level to remain in a stable regime

The what and where of adding channel noise to the Hodgkin-Huxley equations

One of the most celebrated successes in computational biology is the Hodgkin-Huxley framework for modeling electrically active cells. This framework, expressed through a set of differential equations, synthesizes the impact of ionic currents on a cell's voltage -- and the highly nonlinear impact of that voltage back on the currents themselves -- into the rapid push and pull of the action potential. Latter studies confirmed that these cellular dynamics are orchestrated by individual ion channels, whose conformational changes regulate the conductance of each ionic current. Thus, kinetic equations familiar from physical chemistry are the natural setting for describing conductances; for small-to-moderate numbers of channels, these will predict fluctuations in conductances and stochasticity in the resulting action potentials. At first glance, the kinetic equations provide a far more complex (and higher-dimensional) description than the original Hodgkin-Huxley equations. This has prompted more than a decade of efforts to capture channel fluctuations with noise terms added to the Hodgkin-Huxley equations. Many of these approaches, while intuitively appealing, produce quantitative errors when compared to kinetic equations; others, as only very recently demonstrated, are both accurate and relatively simple. We review what works, what doesn't, and why, seeking to build a bridge to well-established results for the deterministic Hodgkin-Huxley equations. As such, we hope that this review will speed emerging studies of how channel noise modulates electrophysiological dynamics and function. We supply user-friendly Matlab simulation code of these stochastic versions of the Hodgkin-Huxley equations on the ModelDB website (accession number 138950) and http://www.amath.washington.edu/~etsb/tutorials.html.Comment: 14 pages, 3 figures, review articl

The Distances of the Magellanic Clouds

The present status of our knowledge of the distances to the Magellanic Clouds is evaluated from a post-Hipparcos perspective. After a brief summary of the effects of structure, reddening, age and metallicity, the primary distance indicators for the Large Magellanic Cloud are reviewed: The SN 1987A ring, Cepheids, RR Lyraes, Mira variables, and Eclipsing Binaries. Distances derived via these methods are weighted and combined to produce final "best" estimates for the Magellanic Clouds distance moduli.Comment: Invited review article to appear in ``Post Hipparcos Cosmic Candles'', F. Caputo & A. Heck (Eds.), Kluwer Academic Publ., Dordrecht, in pres

Calibration of the charge and energy loss per unit length of the MicroBooNE liquid argon time projection chamber using muons and protons

We describe a method used to calibrate the position- and time-dependent response of the MicroBooNE liquid argon time projection chamber anode wires to ionization particle energy loss. The method makes use of crossing cosmic-ray muons to partially correct anode wire signals for multiple effects as a function of time and position, including cross-connected TPC wires, space charge effects, electron attachment to impurities, diffusion, and recombination. The overall energy scale is then determined using fully-contained beam-induced muons originating and stopping in the active region of the detector. Using this method, we obtain an absolute energy scale uncertainty of 2% in data. We use stopping protons to further refine the relation between the measured charge and the energy loss for highly-ionizing particles. This data-driven detector calibration improves both the measurement of total deposited energy and particle identification based on energy loss per unit length as a function of residual range. As an example, the proton selection efficiency is increased by 2% after detector calibration

Reconstruction and measurement of (100) MeV energy electromagnetic activity from π0 arrow γγ decays in the MicroBooNE LArTPC

We present results on the reconstruction of electromagnetic (EM) activity from photons produced in charged current νμ interactions with final state π0s. We employ a fully-automated reconstruction chain capable of identifying EM showers of (100) MeV energy, relying on a combination of traditional reconstruction techniques together with novel machine-learning approaches. These studies demonstrate good energy resolution, and good agreement between data and simulation, relying on the reconstructed invariant π0 mass and other photon distributions for validation. The reconstruction techniques developed are applied to a selection of νμ + Ar → μ + π0 + X candidate events to demonstrate the potential for calorimetric separation of photons from electrons and reconstruction of π0 kinematics