Facile Synthesis of Manganese Tellurite Nanoparticles for Magnetic Resonance Imaging-Guided Photothermal Therapy

In this study, manganese tellurite (MnTeO₃) nanoparticles are developed as theranostic agents for magnetic resonance imaging (MRI)-guided photothermal therapy of tumor. MnTeO₃ nanoparticles are synthesized via a simple one-step method. The as-synthesized MnTeO₃ nanoparticles with uniform size show good biocompatibility. In particular, MnTeO₃ nanoparticles exhibit a high photothermal conversion efficiency (η = 26.3%), which is higher than that of gold nanorods. Moreover, MnTeO₃ nanoparticles also have high MRI performance. The longitudinal relaxivity (r₁) value of MnTeO₃ nanoparticles is determined to be 8.08 ± 0.2 mm ⁻¹ s⁻¹, which is higher than that of clinically approved T₁-contrast agents Gd-DTPA (4.49 ± 0.1 mm ⁻¹ s⁻¹). The subsequent MnTeO₃ nanoparticles-mediated photothermal therapy displays a highly efficient ablation of tumor cells both in vitro and in vivo with negligible toxicity. It is demonstrated that MnTeO₃ nanoparticles can serve as promising theranostic agents with great potentials for MRI-guided photothermal therapy.     

3.0T MRI检查结合X线钼靶诊断乳腺恶性肿瘤的研究

本研究探讨3.0T磁共振成像(MRI)结合X线钼靶诊断乳腺恶性肿瘤的价值。采用回顾性研究方法,选取乳腺肿块患者110例162个病灶,给予3.0T MRI及X线钼靶检查。经病理确诊为恶性病变101个;恶性病灶形态不规则、边缘毛刺、时间-信号强度曲线(TIC)类型Ⅲ型和早期增强率≥60%比例明显高于良性病灶(P<0.05),而分叶状比例和表观扩散系数(ADC)值明显低于良性病变(P<0.05);恶性病变X线钼靶表现:形态不规则、钙化、结构不对称和大导管征比例明显高于良性病变(P<0.05);MRI联合X线钼靶诊断乳腺恶性病变的灵敏性、准确性和阴性预测值明显高于MRI诊断(P<0.05)。3.0T MRI检查结合X线钼靶诊断乳腺恶性肿瘤有较好的价值。     

On the Brauer p-dimension of Henselian discrete valued fields of residual characteristic p > 0

Let $(K,v)$ be a Henselian discrete valued field with residue field $\stackrel{?}{K}$ of characteristic $p>0$, and ${\text{Brd}}_p(K)$ be the Brauer p-dimension of K. This paper shows that ${\text{Brd}}_p(K)\ge n$ if $[\stackrel{?}{K}:{\stackrel{?}{K}}^p]=p^n$, for some $n\in \mathbb{N}$. It proves that ${\text{Brd}}_p(K)=\infty$ if and only if $[\stackrel{?}{K}:{\stackrel{?}{K}}^p]=\infty$.     

Air-Stable Hexagonal Bipyramidal Dysprosium(III) Single-Ion Magnets with Nearly Perfect D6h Local Symmetry

Eight-coordinated Dy^III centres with D_6h symmetry are expected to act as high-performance single-molecule magnets (SMMs) due to the simultaneous fulfilment of magnetic axiality and a high coordination number (a requisite for air stability). But the experimental realization is challenging due to the requirement of six coordinating atoms in the equatorial plane of the hexagonal bipyramid; this is usually too crowded for the central Dy^III ion. Here a hexaaza macrocyclic Schiff base ligand and finetuned axial alkoxide/phenol-type ligands are used to show that a family of hexagonal bipyramidal Dy^III complexes can be isolated. Among them, three complexes possess nearly perfect D_6h local symmetry. The highest effective magnetic reversal barrier is found at 1338(3) K and an open hysteresis temperature of 6 K at the field sweeping rate of 1.2 mT s⁻¹; this represents a new record for D_6h SMMs.     

NIFTy 3 – Numerical Information Field Theory: A Python Framework for Multicomponent Signal Inference on HPC Clusters

NIFTy , “Numerical Information Field Theory,” is a software framework designed to ease the development and implementation of field inference algorithms. Field equations are formulated independently of the underlying spatial geometry allowing the user to focus on the algorithmic design. Under the hood, NIFTy ensures that the discretization of the implemented equations is consistent. This enables the user to prototype an algorithm rapidly in 1D and then apply it to high‐dimensional real‐world problems. This paper introduces NIFTy  3, a major upgrade to the original NIFTy  framework. NIFTy  3 allows the user to run inference algorithms on massively parallel high performance computing clusters without changing the implementation of the field equations. It supports n‐dimensional Cartesian spaces, spherical spaces, power spaces, and product spaces as well as transforms to their harmonic counterparts. Furthermore, NIFTy  3 is able to handle non‐scalar fields, such as vector or tensor fields. The functionality and performance of the software package is demonstrated with example code, which implements a mock inference inspired by a real‐world algorithm from the realm of information field theory. NIFTy  3 is open‐source software available under the GNU General Public License v3 (GPL‐3) at https://gitlab.mpcdf.mpg.de/ift/NIFTy/tree/NIFTy_3 .     

Magnetic properties of a polyfluorene derivative containing complexed neodymium ions

Poly[9,9′‐dihexylfluorene‐2,7‐diyl)‐6,6″‐(2,2′:6′,2″‐terpyridine)] (LaPPS75) and its complexes with neodymium were synthesized and characterized. Magnetic measurements showed that the noncomplexed polymer presented a ferromagnetic contribution due to the formation of π stacking, and that in absence of those, the ferromagnetic behavior is suppressed. The pristine polymer, the complexed one and a low‐molecular‐weight model compound with the same structure of the complexed site in the parent polymer were studied. The observed behavior found is presented and discussed, the most important finding was that when a conjugated chain is used as a host for the metallic ion, an amplification of four times for the magnetization is achieved, using the same metallic content for complexed polymer and model compound for comparison. © 2019 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2019 , 57, 304–311     

Mean field limits for nonlinear spatially extended Hawkes processes with exponential memory kernels

We consider spatially extended systems of interacting nonlinear Hawkes processes modeling large systems of neurons placed in ${\mathbb{R}}^d$ and study the associated mean field limits. As the total number of neurons tends to infinity, we prove that the evolution of a typical neuron, attached to a given spatial position, can be described by a nonlinear limit differential equation driven by a Poisson random measure. The limit process is described by a neural field equation. As a consequence, we provide a rigorous derivation of the neural field equation based on a thorough mean field analysis.     

Semi-concurrent vector fields in Finsler geometry

In the present paper, we give an answer to a question which is closely related to doubly warped product of Finsler metrics: ‘‘For each n, is there an n-dimensional Finsler manifold $(M,F)$, admitting a non-constant smooth function f on M such that $\frac{\partial f}{\partial x^i}\frac{\partial g^{ij}}{\partial y^k}=0$?”. We relate the preceding mentioned condition to different concepts appeared and studied in Finsler geometry. We introduce and investigate the notion of a semi concurrent vector field on a Finsler manifold. We show that some special Finsler manifolds admitting such vector fields turn out to be Riemannian. We prove that Tachibana's characterization of Finsler manifolds admitting a concurrent vector field leads to Riemannian metrics. Various examples for conic Finsler spaces that admit semi-concurrent vector field are presented.