Histopathological characteristics of adenomyosis: structure and microstructure

Adenomyosis is a benign uterine disease that pathologically shows endometrial glands and stroma in the myometrium. There are multiple lines of evidence that adenomyosis is associated with abnormal bleeding, painful menstruation, chronic pelvic pain, infertility, and spontaneous pregnancy loss. Pathologists have researched adenomyosis by studying tissue specimens from its first report more than 150 years ago, and differing viewpoints on its pathological alterations have been advanced. However, the gold standard histopathological definition of adenomyosis remains controversial to date. The diagnostic accuracy of adenomyosis has steadily increased due to the continual identification of unique molecular markers. This article provides a brief description of the pathological aspects of adenomyosis and discusses adenomyosis categorization based on histology. The clinical findings of uncommon adenomyosis are also presented to offer a thorough and detailed pathological profile. Furthermore, we describe the histolo

Combined Voronoi-FDEM approach for modelling post-fracture response of laminated tempered glass

In this work, a combined Voronoi and finite-discrete element method (FDEM) approach for reconstructing the post-fracture model of laminated glass (LG) was proposed. The fracture morphology was determined via introducing Voronoi tessellation with statistical distribution parameters such as the fragment face numbers, volume and sphericity. The residual interaction between glass fragments was described with cohesive zone model. One fractured LG block under uniaxial tension, which was taken from a triple layered LG beam with ionoplast interlayers, was modelled and validated with experimentally recorded data. Through iteration analysis, the key cohesive parameters were determined for the most applicable model. It is followed by investigating the influence due to the fragments interaction property. The results show that the cohesion and frictional property can be combined to well describe the residual interaction behaviour between fragments. The frictional property has a remarkable effect on the post-fracture resistance whereas the associated effect on the stiffness is not evident. Compared to other cohesive parameters, the cohesive stiffness factors present predominant effect on both the post-fracture stiffness and resistance

Parameter identification of BIPT system using chaotic-enhanced fruit fly optimization algorithm

Bidirectional inductive power transfer (BIPT) system facilitates contactless power transfer between two sides and across an air-gap, through weak magnetic coupling. Typically, this system is nonlinear high order system which includes nonlinear switch components and resonant networks, developing of accurate model is a challenging task. In this paper, a novel technique for parameter identification of a BIPT system is presented by using chaotic-enhanced fruit fly optimization algorithm (CFOA). The fruit fly optimization algorithm (FOA) is a new meta-heuristic technique based on the swarm behavior of the fruit fly. This paper proposes a novel CFOA, which employs chaotic sequence to enhance the global optimization capacity of original FOA. The parameter identification of the BIPT system is formalized as a multi-dimensional optimization problem, and an objective function is established minimizing the errors between the estimated and measured values. All the 11 parameters of this system (Lpi, LT, Lsi, Lso, CT, Cs, M, Rpi, RT, Rsi and Rso) can be identified simultaneously using measured input–output data. Simulations show that the proposed parameter identification technique is robust to measurements noise and variation of operation condition and thus it is suitable for practical application

Effect of HDAC-6 on PD cell induced by lactacystin

AbstractObjectiveTo explore the effects of histone deacetylase 6(HDAC-6) on the PD cell model induced by proteasome inhibitor lactacystin.MethodsHuman neuroblastoma SK-N-SH cells were cultured. The wild type pcDNA3.1-alpha-synuclein eukaryotic expression plasmid was transferred into the cells which then were divided into control group, group L, group T and group T+L. The cells of group L were added with 5 μmol/L lactacystin dissolved indimethylsulfoxide (DMSO) to induce PD cell model with abnormal protein aggregation, the cells of control group were treated with 5 μmol/L DMSO, the cells of group T were treated with 5 μmol/L selective HDAC-6 inhibitor tubacin dissolved in DMSO, and the cells of group T+L were treated with 5 μmol/L lactacystin and 10 μmol/L tubacin dissolved in DMSO. The expression levels of alpha-synuclein oligomers, HSP-27 and HSP-70 were detected by Western blot and the cell survival rate of all the groups was detected by MTT colorimetric assay, and compared 24 h after the cells were treated.ResultsThe expression levels of alpha-synuclein oligomers, HSP-27 and HSP-70 of the cells of group L were significantly higher than the control group, and the cell survival rate was significantly lower (P < 0.05); the expression level of alpha-synuclein oligomers of the cells of group T+L was significantly higher than group L, but the expression level of HSP-27 and HSP-70 were significantly lower, and so as the cell survival rate (P < 0.05); the differences of the expression level of alpha-synuclein oligomers, HSP-27 and HSP-70 and the cell survival rate of the cells of group T and the control group were not statistically significant (P > 0.05).ConclusionsThe expression level of alpha-synuclein oligomers can be improved and the cell survival rate can be reduced by the PD cell model induced by lactacystin and treated with selective HDAC-6 inhibitor tubacin, which means that alpha-synuclein oligomers of the PD cell model induced by lactacystin can be inhibited and the cell survival rate can be improved by HDAC-6, and the mechanism may be related to the increased of HSP-27 and HSP-70

A Kohn-Sham Scheme Based Neural Network for Nuclear Systems

A Kohn-Sham scheme based multi-task neural network is elaborated for the supervised learning of nuclear shell evolution. The training set is composed of the single-particle wave functions and occupation probabilities of 320 nuclei, calculated by the Skyrme density functional theory. It is found that the deduced density distributions, momentum distributions, and charge radii are in good agreements with the benchmarking results for the untrained nuclei. In particular, accomplishing shell evolution leads to a remarkable improvement in the extrapolation of nuclear density. After a further charge-radius-based calibration, the network evolves a stronger predictive capability. This opens the possibility to infer correlations among observables by combining experimental data for nuclear complex systems

A modified ant colony optimization algorithm for network coding resource minimization

The paper presents a modified ant colony optimization approach for the network coding resource minimization problem. It is featured with several attractive mechanisms specially devised for solving the network coding resource minimization problem: 1) a multi-dimensional pheromone maintenance mechanism is put forward to address the issue of pheromone overlapping; 2) problem-specific heuristic information is employed to enhance the heuristic search (neighboring area search) capability; 3) a tabu-table based path construction method is devised to facilitate the construction of feasible (link-disjoint) paths from the source to each receiver; 4) a local pheromone updating rule is developed to guide ants to construct appropriate promising paths; 5) a solution reconstruction method is presented, with the aim of avoiding prematurity and improving the global search efficiency of proposed algorithm. Due to the way it works, the ant colony optimization can well exploit the global and local information of routing related problems during the solution construction phase. The simulation results on benchmark instances demonstrate that with the five extended mechanisms integrated, our algorithm outperforms a number of existing algorithms with respect to the best solutions obtained and the computational time

Impact of quadrupole deformation on intermediate-energy heavy-ion collisions

This study employs the isospin-dependent Boltzmann-Uehling-Uhlenbeck model to simulate intermediate-energy heavy-ion collisions between prolate nuclei $^{24}$Mg. The emphasis is on investigating the influence of centrality and orientation in several collision scenarios. The final-state particle multiplicities and anisotropic flows are primarily determined by the eccentricity and the area of the initial overlap. This not only provides feedback on the collision systems, but also, to some extent, provides a means to explore the fine structure inside deformed nuclei. Additionally, non-polarized collisions have been further discussed. These results contribute to the understanding of the geometric effects in nuclear reactions, and aid in the exploration of other information on reaction systems, such as the equation of state and nuclear high-momentum tail

Experimental Test of Bell inequalities with Six-Qubit Graph States

We report on the experimental realization of two different Bell inequality tests based on six-qubit linear-type and Y-shape graph states. For each of these states, the Bell inequalities tested are optimal in the sense that they provide the maximum violation among all Bell inequalities with stabilizing observables and possess the maximum resistance to noise.Comment: 4 pages, 2 figure

Combined effect of Cu- and ZnO- NPs on antibiotic resistance genes in an estuarine water

Most studies of whether and how nanoparticles (NPs) affect antibiotic resistance genes (ARGs) focus on testing single NPs type. In this study, we determined the combined effect of Cu- and ZnO- NPs in the water samples collected from the Yangtze River Estuary and found the effect differs greatly from that produced by individual NPs. The results showed that the Cu- and ZnO- NPs co-exposure resulted in an enrichment of ARGs, whereas individual Cu- and ZnO- NPs exposure decreased the abundance of ARGs. Furthermore, the co-exposure of Cu- and ZnO- NPs induced obvious changes in the microbial communities compared to the control communities. Redundancy analysis suggested that the microbial community contributed the most (43.5%) to the ARG profiles, followed by dissolved metal ions (25.7%), MRGs, (19.4%), and MGEs (4.4%). Network analysis found several potential hosts (such as Mycobacterium and Escherichia coli) and implied the extent of the risk of ARG transmission into various environmental niches by these common microbes