Revisiting the anticancer properties of phosphane(9-ribosylpurine-6-thiolato)gold(I) complexes and their 9H-purine precursors

New mono- and di-nuclear thio-purine and thio-purine nucleoside gold(I) complexes were synthesized, characterized, and evaluated in vitro for biological activities in comparison to related known purine complexes. By combining known anti-tumoral thio-purines with R(3)PAu moieties as present in auranofin, complexes with enhanced effects and selectivities were obtained, which not only act as cytostatics, but also disrupt tumor-specific processes. Their IC(50) values in cytotoxicity test with tumor cell lines ranged from three-digit nanomolar to single-digit micromolar, revealing a tentative structure–activity relationship (SAR). Both the residues R(2) of the phosphane ligand and R(1) at C2 of the pyrimidine ring had a significant impact on the cytotoxicity. In most cases, the introduction of a ribo-furanosyl group at N9 of the purine led to a distinctly more cytotoxic complex. Most complexes were more active against multi-drug-resistant tumor cells or such lacking functional p53 when compared to the respective untreated wild type cell lines. Some nucleoside complexes displayed an interesting dose-dependent dual mode of action regarding cell cycle arrest and DNA repair mechanism. Some phosphane(purine-6-thiolato)gold (I) complexes had a stronger inhibitory effect on the thioredoxin reductase (TrxR) and on the reactive oxygen species (ROS) generation in cancer cells than is typical of other gold complexes. They also led to DNA fragmentation and showed anti-angiogenic effects. Their stability under test conditions was demonstrated by (77)Se NMR monitoring of an exemplary selenopurine complex. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00775-022-01968-x

Discovery of CH and OH in the -513 km s-1 Ejecta of Eta Carinae

The very massive star, Eta Carinae, is enshrouded in an unusual complex of stellar ejecta, which is highly depleted in C and O, and enriched in He and N. This circumstellar gas gives rise to distinct absorption components corresponding to at least 20 different velocities along the line-of-sight. The velocity component at -513 kms-1 exhibits very low ionization with predominantly neutral species of iron-peak elements. Our statistical equilibrium/photoionization modeling indicates that the low temperature (T = 760 K) and high density (n_H=10^7 cm^-3) of the -513 kms-1 component is conducive to molecule formation including those with the elements C and O. Examination of echelle spectra obtained with the Space Telescope Imaging Spectrograph (STIS) aboard the confirms the model's predictions. The molecules, H_2, CH, and most likely OH, have been identified in the -513 kms-1 absorption spectrum. This paper presents the analysis of the HST/STIS spectra with the deduced column densities for CH, OH and C I, and upper limit for CO. It is quite extraordinary to see molecular species in a cool environment at such a high velocity. The sharp molecular and ionic absorptions in this extensively CNO- processed material offers us a unique environment for studying the chemistry, dust formation processes, and nucleosynthesis in the ejected layers of a highly evolved massive star.Comment: tentatively scheduled for the ApJ 1 September 2005, v630, 1 issu

Geometry-dependent critical currents in superconducting nanocircuits

In this paper we calculate the critical currents in thin superconducting strips with sharp right-angle turns, 180-degree turnarounds, and more complicated geometries, where all the line widths are much smaller than the Pearl length $\Lambda = 2 \lambda^2/d$. We define the critical current as the current that reduces the Gibbs free-energy barrier to zero. We show that current crowding, which occurs whenever the current rounds a sharp turn, tends to reduce the critical current, but we also show that when the radius of curvature is less than the coherence length this effect is partially compensated by a radius-of-curvature effect. We propose several patterns with rounded corners to avoid critical-current reduction due to current crowding. These results are relevant to superconducting nanowire single-photon detectors, where they suggest a means of improving the bias conditions and reducing dark counts. These results also have relevance to normal-metal nanocircuits, as these patterns can reduce the electrical resistance, electromigration, and hot spots caused by nonuniform heating.Comment: 29 pages, 24 figure

Two-dimensional arrays of superconducting strips as dc magnetic metamaterials

We theoretically investigate the magnetic response of two-dimensional arrays of superconducting strips, which are regarded as essential structures of dc magnetic metamaterials. We analytically obtain local distributions of the magnetic field for the ideal complete shielding state (i.e., $\Lambda/w\to 0$, where $2w$ is the strip width, $\Lambda=\lambda^2/d$ is the Pearl length, $\lambda$ is the London penetration depth, and $d$ is the strip thickness), and derive effective permeability by averaging the local field distributions. We also perform numerical calculations for a realistic case, taking finite $\Lambda/w>0$ into account. We investigate two types of strip arrays: a rectangular array and a hexagonal array. The resulting effective permeability has large anisotropy that depends on the dimensions and arrangement of the superconducting strips, and the hexagonal array is found to be more advantageous for obtaining large anisotropy than the rectangular array.Comment: 10 pages, 8 figure

Field and current distributions and ac losses in superconducting strips

In this paper I discuss analytic and numerical calculations of the magnetic-field and sheet-current distributions in superconducting strips of width 2a and arbitrary thickness 2b at the center when the cross section is an ellipse, a rectangle, and a shape intermediate between these limits. Using critical-state theory, I use several methods to determine the functional dependence of the ac transport-current losses upon F = I/Ic, where I is the peak alternating current and Ic is the critical current, and I discuss how this dependence can be affected by the cross-sectional shape, aspect ratio, and a flux-density-dependent critical current density Jc(B).Comment: 13 pages, 11 figure

Patterns and rates of viral evolution in HIV-1 subtype B infected females and males.

Biological sex differences affect the course of HIV infection, with untreated women having lower viral loads compared to their male counterparts but, for a given viral load, women have a higher rate of progression to AIDS. However, the vast majority of data on viral evolution, a process that is clearly impacted by host immunity and could be impacted by sex differences, has been derived from men. We conducted an intensive analysis of HIV-1 gag and env-gp120 evolution taken over the first 6-11 years of infection from 8 Women's Interagency HIV Study (WIHS) participants who had not received combination antiretroviral therapy (ART). This was compared to similar data previously collected from men, with both groups infected with HIV-1 subtype B. Early virus populations in men and women were generally homogenous with no differences in diversity between sexes. No differences in ensuing nucleotide substitution rates were found between the female and male cohorts studied herein. As previously reported for men, time to peak diversity in env-gp120 in women was positively associated with time to CD4+ cell count below 200 (P = 0.017), and the number of predicted N-linked glycosylation sites generally increased over time, followed by a plateau or decline, with the majority of changes localized to the V1-V2 region. These findings strongly suggest that the sex differences in HIV-1 disease progression attributed to immune system composition and sensitivities are not revealed by, nor do they impact, global patterns of viral evolution, the latter of which proceeds similarly in women and men

Activation of PKA leads to mesenchymal-to-epithelial transition and loss of tumor-initiating ability

The epithelial-to-mesenchymal transition enables carcinoma cells to acquire malignancy-associated traits and the properties of tumor-initiating cells (TICs). TICs have emerged in recent years as important targets for cancer therapy, owing to their ability to drive clinical relapse and enable metastasis. Here, we propose a strategy to eliminate mesenchymal TICs by inducing their conversion to more epithelial counterparts that have lost tumor-initiating ability. We report that increases in intracellular levels of the second messenger, adenosine 3',5'-monophosphate, and the subsequent activation of protein kinase A (PKA) induce a mesenchymal-to-epithelial transition (MET) in mesenchymal human mammary epithelial cells. PKA activation triggers epigenetic reprogramming of TICs by the histone demethylase PHF2, which promotes their differentiation and loss of tumor-initiating ability. This study provides proof-of-principle for inducing an MET as differentiation therapy for TICs and uncovers a role for PKA in enforcing and maintaining the epithelial state

YbtT is a low-specificity type II thioesterase that maintains production of the metallophore yersiniabactin in pathogenic enterobacteria

Clinical isolates of Yersinia, Klebsiella, and Escherichia coli frequently secrete the small molecule metallophore yersiniabactin (Ybt), which passivates and scavenges transition metals during human infections. YbtT is encoded within the Ybt biosynthetic operon and is critical for full Ybt production in bacteria. However, its biosynthetic function has been unclear because it is not essential for Ybt production by the in vitro reconstituted nonribosomal peptide synthetase/polyketide synthase (NRPS/PKS) pathway. Here, we report the structural and biochemical characterization of YbtT. YbtT structures at 1.4-1.9 Å resolution possess a serine hydrolase catalytic triad and an associated substrate chamber with features similar to those previously reported for low-specificity type II thioesterases (TEIIs). We found that YbtT interacts with the two major Ybt biosynthetic proteins, HMWP1 (high-molecular-weight protein 1) and HMWP2 (high-molecular-weight protein 2), and hydrolyzes a variety of aromatic and acyl groups from their phosphopantetheinylated carrier protein domains. In vivo YbtT titration in uropathogenic E. coli revealed a distinct optimum for Ybt production consistent with a tradeoff between clearing both stalled inhibitory intermediates and productive Ybt precursors from HMWP1 and HMWP2. These results are consistent with a model in which YbtT maintains cellular Ybt biosynthesis by removing nonproductive, inhibitory thioesters that form aberrantly at multiple sites on HMWP1 and HMWP2

Brain tissue segmentation based on MP2RAGE multi-contrast images in 7 T MRI.

We proposed a method for segmentation of brain tissues-gray matter, white matter, and cerebrospinal fluid-using multi-contrast images, including a T1 map and a uniform T1-weighted image, from a magnetization-prepared 2 rapid acquisition gradient echoes (MP2RAGE) sequence at 7 Tesla. The proposed method was evaluated with respect to the processing time and the similarity of the segmented masks of brain tissues with those obtained using FSL, FreeSurfer, and SPM12. The processing time of the proposed method (28 ± 0 s) was significantly shorter than those of FSL and SPM12 (444 ± 4 s and 159 ± 2 s for FSL and SPM12, respectively). In the similarity assessment, the tissue mask of the brain obtained by the proposed method showed higher consistency with those obtained using FSL than with those obtained using SPM12. The proposed method misclassified the subcortical structures and large vessels since it is based on the intensities of multi-contrast images obtained using MP2RAGE, which uses a similar segmentation approach as FSL but is not based on a template image or a parcellated brain atlas, which are used for FreeSurfer and SPM12, respectively. However, the proposed method showed good segmentation in the cerebellum and white matter in the medial part of the brain in comparison with the other methods. Thus, because the proposed method using different contrast images of MP2RAGE sequence showed the shortest processing time and similar segmentation ability as the other methods, it may be useful for both neuroimaging research and clinical diagnosis

Deep active learning for autonomous navigation.

Imitation learning refers to an agent's ability to mimic a desired behavior by learning from observations. A major challenge facing learning from demonstrations is to represent the demonstrations in a manner that is adequate for learning and efficient for real time decisions. Creating feature representations is especially challenging when extracted from high dimensional visual data. In this paper, we present a method for imitation learning from raw visual data. The proposed method is applied to a popular imitation learning domain that is relevant to a variety of real life applications; namely navigation. To create a training set, a teacher uses an optimal policy to perform a navigation task, and the actions taken are recorded along with visual footage from the first person perspective. Features are automatically extracted and used to learn a policy that mimics the teacher via a deep convolutional neural network. A trained agent can then predict an action to perform based on the scene it finds itself in. This method is generic, and the network is trained without knowledge of the task, targets or environment in which it is acting. Another common challenge in imitation learning is generalizing a policy over unseen situation in training data. To address this challenge, the learned policy is subsequently improved by employing active learning. While the agent is executing a task, it can query the teacher for the correct action to take in situations where it has low confidence. The active samples are added to the training set and used to update the initial policy. The proposed approach is demonstrated on 4 different tasks in a 3D simulated environment. The experiments show that an agent can effectively perform imitation learning from raw visual data for navigation tasks and that active learning can significantly improve the initial policy using a small number of samples. The simulated test bed facilitates reproduction of these results and comparison with other approaches