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Ruptured ectopic pregnancy (REP), a pregnancy complication caused by aberrant implantation, deep invasion, and overgrowth of embryos in fallopian tubes, could lead to rupture of fallopian tubes and accounts for 4%–10% of pregnancy-related deaths. The lack of ectopic pregnancy phenotypes in rodents hampers our understanding of its pathological mechanisms. Here, we employed cell culture and organoid models to investigate the crosstalk between human trophoblast development and intravillous vascularization in the REP condition. Compared with abortive ectopic pregnancy (AEP), the size of REP placental villi and the depth of trophoblast invasion are correlated with the extent of intravillous vascularization. We identified a key pro-angiogenic factor secreted by trophoblasts, WNT2B, that promotes villous vasculogenesis, angiogenesis, and vascular network expansion in the REP condition. Our results reveal the important role of WNT-mediated angiogenesis and an organoid co-culture model for investigating intricate communications between trophoblasts and endothelial/endothelial progenitor cells. [Display omitted] • Ruptured ectopic pregnancy (REP) is characterized by highly vascularized placental villi • Aberrant WNT2B expression in REP trophoblasts could promote intravillous angiogenesis • Co-cultured organoids model the crosstalk between trophoblasts and endothelial cells Zhao et al. establish an organoid co-culture system to model human ectopic pregnancy and to study the interaction between trophoblasts and endothelial cells. A trophoblast-secreted pro-angiogenic factor, WNT2B, is found to promote intravillous vascularization, which is associated with the risk of ruptured ectopic pregnancy. [ABSTRACT FROM AUTHOR]

The grain morphology and oxidation behavior of the Y/Ta/Hf co-doped AlCoCrFeNi high-entropy alloy (HEA) were investigated in air at 1100 ℃. The Y/Ta/Hf co-doped significantly improves the high-temperature oxidation resistance of the alloy. Hf doped AlCoCrFeNiYTa HEA presents the larger grain sizes of Al 2 O 3 , which effectively reduces the inward diffusion of O along the grain boundaries. In addition, Y/Ta/Hf co-doped AlCoCrFeNi HEA accelerates the transformation metastable Al 2 O 3 to α-Al 2 O 3. The oxide pegs formed at the oxide/substrate interface have a positive effect on improving the adhesion of the oxide scale, and Ta increased the probability of oxide peg formation. • The oxidation resistance of the AlCoCrFeNi HEA is significantly improved by Y/Ta/Hf co-doping. • The REs-doped AlCoCrFeNi HEA accelerates the transition from θ-Al 2 O 3 to α-Al 2 O 3. • Hf doping promotes Al 2 O 3 grain growth for the Y/Ta/Hf co-doped AlCoCrFeNi HEA. • Ta doping increases the probability of oxide peg formation depending on the doping content. • Ta is mainly dissolved in the β-NiAl phase of the AlCoCrFeNi HEA. [ABSTRACT FROM AUTHOR]

This paper is concerned with a class of highly nonlinear hybrid stochastic differential delay equations (SDDEs). Different from the most existing papers, the time delay functions in the SDDEs are no longer required to be differentiable, not to mention their derivatives are less than 1. The generalized Hasminskii-type theorems are established for the existence and uniqueness of the global solutions. Comparing with the existing results, we show our new theorems are much more general and can be applied to a much wider class of highly nonlinear SDDEs. Further sufficient conditions are also obtained for the asymptotic boundedness and stability. [ABSTRACT FROM AUTHOR]

The fixed-time synchronization (FTS) of complex-valued memristive competitive neural networks (CVMCNNs) with mixed delays is the main topic of this paper. Firstly, two new fixed-time (FT) stability criteria are obtained. In the FT stability criterion, the exponent is usually positive, but the exponent can be less than zero and varies with the error state in this paper. Then, based on two new stability theorems, the FTS of CVMCNNs is studied in the sense of 1-norm and 2-norm, respectively, without dividing the complex-valued state variables into the real part (RP) and the imaginary part (IP). Finally, two numerical simulation examples are given to further demonstrate the validity and superiority of our results. [ABSTRACT FROM AUTHOR]

• We study a new type of stochastic functional differential equation. The PSFDEs differs markedly from PSDEs, since the current state of PSFDEs depends on a past segment of its solution while the current state of PSDEs depends only on a past point of its solution. • We are the first to give the definition of the approximate solution for PSFDEs. The approximate solution converges strongly to the analytical solution in finite time interval. • The numerical solutions preserve the exponential stability and polynomial stability of the analytical solution under the certain conditions. The paper studies the convergence of the numerical solutions for pantograph stochastic functional differential equations which was proposed in Wu et al.(2022)[16]. We also show that the approximate solutions have the properties of almost surely polynomial stability and exponential stability. [ABSTRACT FROM AUTHOR]

A direct diastereoselective synthesis approach of important 9 H-pyrrolo[1,2- a]azepin-9-amines was established via base-promoted [4+3] annulation between donor-acceptor reagents derived from 1 H-pyrrole-2-carbaldehydes and alkyl 2-aroyl-1-chlorocyclopropanecarboxylates. This transition metal-free domino reaction proceeded quickly under mild basic conditions, affording potentially bioactive azepine derivatives in moderate to high yields with high diastereoselectivities (up to >20:1). [ABSTRACT FROM AUTHOR]

Hydrothermal liquefaction (HTL) is a promising thermochemical technology for converting microalgae growing in aquatic habitats into fuels as well as high-value chemicals. Microalgae HTL polygeneration was carried out in order to reveal the evolution pathway of nitrogen during the HTL process. In this study, Spirulina with high protein content was subjected to hydrothermal treatment at 200–340 °C. The results show that 65.80–76.34 % of the nitrogen enters into the aqueous phase, while 12.96–34.00 % of the nitrogen is transferred to bio-oil. Ammonium ion is the main nitrogen-containing species in the aqueous phase, and the conversion of nitrogen in Spirulina reaches 11.72–51.18 %. The main nitrogen-containing compounds in bio-oil are cyclodipeptides and fatty acid amides respectively at 200–240 °C and 260–340 °C. Due to incomplete decomposition of Spirulina at 200–240 °C, 0.20–17.12 % of nitrogen is retained in the solid residue in the form of pyrrole-N, protein-N and quaternary-N. Understanding the evolution pathway of nitrogen during microalgae HTL polygeneration is conducive to achieving high-value utilization of microalgae. [Display omitted] • The nitrogen in Spirulina is distributed in the bio-oil, aqueous phase and solid residue. • Temperature has a significant effect on the distribution of nitrogen in the bio-oil. • The denitrification efficiency of bio-oil can be improved by removing the amino functional groups of fatty acid amides. • 65.80–76.34 % of the nitrogen in Spirulina is transferred to the aqueous phase. • The ammonium ions in the aqueous phase have the potential to be used for cultivating plants. [ABSTRACT FROM AUTHOR]

Most stochastic partial differential equations do not have explicit solutions. Recently, numerical schemes for stochastic partial differential equations are becoming more popular. In this paper, the convergence rate of numerical solutions for a class of hybrid neutral stochastic partial differential equations is studied. By using a Galerkin method, a spatial discretization of the model is first presented. Then a time discretization is given by using a stochastic exponential integrator. The convergence rate of the numerical solutions is obtained by tools of semigroup and stochastic analysis and some results in finite dimensions are generalized. [ABSTRACT FROM AUTHOR]

This article explores the application of deep neural networks (DNNs) for optimized backstepping control design in a category of stochastic nonlinear strict-feedback systems with unknown dynamics, focusing on prescribed performance. DNNs, distinguished by their ability to handle high-complexity functions and enhance function approximation, are employed to estimate unknown nonlinear functions. The weight updating strategy for each layer of DNNs is determined through a Lyapunov function analysis. Tomitigate potential issues such as the tracking error exploding at uncertain moments, prescribed performance control (PPC) is introduced to constrain the tracking error within a predetermined range. Subsequently, a novel optimal tracking control scheme, integrating the backstepping method and Hamilton–Jacobi–Bellman (HJB) equation, is presented. The results indicate that all signals in the closed-loop system are bounded in probability, and the tracking error is maintained within a set of predefined arbitrarily small residuals. Simulation outcomes affirm the efficacy of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the anti-synchronization in predefined-time for fuzzy inertial neural networks (FINNs) with mixed delays. In the light of predefined-time stability theorems, the FINNs can reach anti-synchronization by employing two distinctive bilayer predefined-time control inputs which the setting-time is a explicit value without considering on initial values that has a great improvement over other settlement times in previous researches. Based on Lyapunov stability theory, sufficient conditions are converted to a type of algebraic inequalities which are very concise and avoid complicated calculations. In the end, some numerical examples and applications are illustrated to validate reliability of proposed results here. [ABSTRACT FROM AUTHOR]