6,008 research outputs found
Formation of octapod MnO nanoparticles with enhanced magnetic properties through kinetically-controlled thermal decomposition of polynuclear manganese complexes
Polynuclear manganese complexes are used as precursors for the synthesis of manganese oxide nanoparticles (MnO NPs). Altering the thermal decomposition conditions can shift the nanoparticle product from spherical, thermodynamically-driven NPs to unusual, kinetically-controlled octapod structures. The resulting increased surface area profoundly alters the NP's surface-dependent magnetism and may have applications in nanomedicine
Individual prognosis at diagnosis in nonmetastatic prostate cancer: Development and external validation of the PREDICT Prostate multivariable model.
BACKGROUND: Prognostic stratification is the cornerstone of management in nonmetastatic prostate cancer (PCa). However, existing prognostic models are inadequate-often using treatment outcomes rather than survival, stratifying by broad heterogeneous groups and using heavily treated cohorts. To address this unmet need, we developed an individualised prognostic model that contextualises PCa-specific mortality (PCSM) against other cause mortality, and estimates the impact of treatment on survival. METHODS AND FINDINGS: Using records from the United Kingdom National Cancer Registration and Analysis Service (NCRAS), data were collated for 10,089 men diagnosed with nonmetastatic PCa between 2000 and 2010 in Eastern England. Median follow-up was 9.8 years with 3,829 deaths (1,202 PCa specific). Totals of 19.8%, 14.1%, 34.6%, and 31.5% of men underwent conservative management, prostatectomy, radiotherapy (RT), and androgen deprivation monotherapy, respectively. A total of 2,546 men diagnosed in Singapore over a similar time period represented an external validation cohort. Data were randomly split 70:30 into model development and validation cohorts. Fifteen-year PCSM and non-PCa mortality (NPCM) were explored using separate multivariable Cox models within a competing risks framework. Fractional polynomials (FPs) were utilised to fit continuous variables and baseline hazards. Model accuracy was assessed by discrimination and calibration using the Harrell C-index and chi-squared goodness of fit, respectively, within both validation cohorts. A multivariable model estimating individualised 10- and 15-year survival outcomes was constructed combining age, prostate-specific antigen (PSA), histological grade, biopsy core involvement, stage, and primary treatment, which were each independent prognostic factors for PCSM, and age and comorbidity, which were prognostic for NPCM. The model demonstrated good discrimination, with a C-index of 0.84 (95% CI: 0.82-0.86) and 0.84 (95% CI: 0.80-0.87) for 15-year PCSM in the UK and Singapore validation cohorts, respectively, comparing favourably to international risk-stratification criteria. Discrimination was maintained for overall mortality, with C-index 0.77 (95% CI: 0.75-0.78) and 0.76 (95% CI: 0.73-0.78). The model was well calibrated with no significant difference between predicted and observed PCa-specific (p = 0.19) or overall deaths (p = 0.43) in the UK cohort. Key study limitations were a relatively small external validation cohort, an inability to account for delayed changes to treatment beyond 12 months, and an absence of tumour-stage subclassifications. CONCLUSIONS: 'PREDICT Prostate' is an individualised multivariable PCa prognostic model built from baseline diagnostic information and the first to our knowledge that models potential treatment benefits on overall survival. Prognostic power is high despite using only routinely collected clinicopathological information.The Urology Foundatio
Finite-Temperature Transition into a Power-Law Spin Phase with an Extensive Zero-Point Entropy
We introduce an generalization of the frustrated Ising model on a
triangular lattice. The presence of continuous degrees of freedom stabilizes a
{\em finite-temperature} spin state with {\em power-law} discrete spin
correlations and an extensive zero-point entropy. In this phase, the unquenched
degrees of freedom can be described by a fluctuating surface with logarithmic
height correlations. Finite-size Monte Carlo simulations have been used to
characterize the exponents of the transition and the dynamics of the
low-temperature phase
Structural insights into the mechanism of the membrane integral N-acyltransferase step in bacterial lipoprotein synthesis
Lipoproteins serve essential roles in the bacterial cell envelope. The posttranslational modification pathway leading to lipoprotein synthesis involves three enzymes. All are potential targets for the development of new antibiotics. Here we report the crystal structure of the last enzyme in the pathway, apolipoprotein N-acyltransferase, Lnt, responsible for adding a third acyl chain to the lipoprotein’s invariant diacylated N-terminal cysteine. Structures of Lnt from Pseudomonas aeruginosa and Escherichia coli have been solved; they are remarkably similar. Both consist of a membrane domain on which sits a globular periplasmic domain. The active site resides above the membrane interface where the domains meet facing into the periplasm. The structures are consistent with the proposed ping-pong reaction mechanism and suggest plausible routes by which substrates and products enter and leave the active site. While Lnt may present challenges for antibiotic development, the structures described should facilitate design of therapeutics with reduced off-target effects
Characterization of Aptamer-Protein Complexes by X-ray Crystallography and Alternative Approaches
Aptamers are oligonucleotide ligands, either RNA or ssDNA, selected for high-affinity binding to molecular targets, such as small organic molecules, proteins or whole microorganisms. While reports of new aptamers are numerous, characterization of their specific interaction is often restricted to the affinity of binding (KD). Over the years, crystal structures of aptamer-protein complexes have only scarcely become available. Here we describe some relevant technical issues about the process of crystallizing aptamer-protein complexes and highlight some biochemical details on the molecular basis of selected aptamer-protein interactions. In addition, alternative experimental and computational approaches are discussed to study aptamer-protein interactions.
Crystal structure of undecaprenyl-pyrophosphate phosphatase and its role in peptidoglycan biosynthesis
As a protective envelope surrounding the bacterial cell, the peptidoglycan sacculus is a site of vulnerability and an antibiotic target. Peptidoglycan components, assembled in the cytoplasm, are shuttled across the membrane in a cycle that uses undecaprenyl-phosphate. A product of peptidoglycan synthesis, undecaprenyl-pyrophosphate, is converted to undecaprenyl-phosphate for reuse in the cycle by the membrane integral pyrophosphatase, BacA. To understand how BacA functions, we determine its crystal structure at 2.6 Å resolution. The enzyme is open to the periplasm and to the periplasmic leaflet via a pocket that extends into the membrane. Conserved residues map to the pocket where pyrophosphorolysis occurs. BacA incorporates an interdigitated inverted topology repeat, a topology type thus far only reported in transporters and channels. This unique topology raises issues regarding the ancestry of BacA, the possibility that BacA has alternate active sites on either side of the membrane and its possible function as a flippase
Grain Boundaries in Graphene on SiC(000) Substrate
Grain boundaries in epitaxial graphene on the SiC(000) substrate are
studied using scanning tunneling microscopy and spectroscopy. All investigated
small-angle grain boundaries show pronounced out-of-plane buckling induced by
the strain fields of constituent dislocations. The ensemble of observations
allows to determine the critical misorientation angle of buckling transition
. Periodic structures are found among the flat
large-angle grain boundaries. In particular, the observed highly ordered grain boundary is assigned to the previously
proposed lowest formation energy structural motif composed of a continuous
chain of edge-sharing alternating pentagons and heptagons. This periodic grain
boundary defect is predicted to exhibit strong valley filtering of charge
carriers thus promising the practical realization of all-electric valleytronic
devices
Structured Sparsity: Discrete and Convex approaches
Compressive sensing (CS) exploits sparsity to recover sparse or compressible
signals from dimensionality reducing, non-adaptive sensing mechanisms. Sparsity
is also used to enhance interpretability in machine learning and statistics
applications: While the ambient dimension is vast in modern data analysis
problems, the relevant information therein typically resides in a much lower
dimensional space. However, many solutions proposed nowadays do not leverage
the true underlying structure. Recent results in CS extend the simple sparsity
idea to more sophisticated {\em structured} sparsity models, which describe the
interdependency between the nonzero components of a signal, allowing to
increase the interpretability of the results and lead to better recovery
performance. In order to better understand the impact of structured sparsity,
in this chapter we analyze the connections between the discrete models and
their convex relaxations, highlighting their relative advantages. We start with
the general group sparse model and then elaborate on two important special
cases: the dispersive and the hierarchical models. For each, we present the
models in their discrete nature, discuss how to solve the ensuing discrete
problems and then describe convex relaxations. We also consider more general
structures as defined by set functions and present their convex proxies.
Further, we discuss efficient optimization solutions for structured sparsity
problems and illustrate structured sparsity in action via three applications.Comment: 30 pages, 18 figure
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