Regio- and Atroposelective Ring-Opening of 1H-Benzo[4,5]oxazolopyridinones.

The development of new methods for regio- and stereoselective activation of C-O bonds in ethers holds significant promise for synthetic chemistry, offering advantages in terms of environmental sustainability and economic efficiency. Moreover, the C-N atropisomers represent a fascinating and crucial chiral system, extensively found in natural products, pharmaceutical leads, and the frameworks of advanced materials. In this work, we have introduced a nickel-catalyzed regio- and enantioselective carbon-oxygen arylation reaction for atroposelective synthesis of N-arylisoquinoline-1,3(2H,4H)-diones. The high regioselectivity of C-O cleavage benefits from the high stability of the in situ formed (amido)ethenolate via oxidative addition. Additionally, the self-activation of the aryl C-O bond facilitates the reaction under mild conditions, leading to outstanding enantioselectivities. The diverse post-functionalizations of the axially chiral isoquinoline-1,3(2H,4H)-diones further highlighted the utility of this protocol in preparing valuable C-N atropisomers, including the chiral phosphine ligands.

Conjugation-Induced Spin Delocalization in Helical Chiral Carbon Radicals via Through-Bond and Through-Space Effects.

A class of highly stable hydrocarbon radicals with helical chirality are synthesized, which can be isolated and purified by routine column chromatography on silica gel. These carbon-centered radicals are stabilized by through-bond delocalization and intramolecular through-space conjugation, which is evidenced by Density Functional Theory (DFT) calculation. The high stability enables to directly modify the carbon radical via palladium-catalyzed cross-coupling with the radical being untapped. The structures and optoelectronic properties are investigated with a variety of experimental methods, including Electron Paramagnetic Resonance (EPR), Ultraviolet Visisble Near Infrared (UV-vis-NIR) measurements, Cyclic Voltammetry (CV), Thermogravimetry Analysis (TGA), Circular Dichroism (CD) spectra, High-Performance Liquid Chromatography (HPLC), and X-ray crystallographic analysis. DFT calculations indicated that the 9-anthryl helical radical is more stable than its tail-to-tail σ-dimer over 13.2 kJ mol-1 , which is consistent with experimental observations.

Photocontrolled Reversibly Chiral-Ordered Assembly Based on Cucurbituril.

Chirality transfer and regulation, accompanied by morphology transformation, arouse widespread interest for application in materials and biological science. Here, a photocontrolled supramolecular chiral switch is fabricated from chiral diphenylalanine (l-Phe-l-Phe, FF) modified with naphthalene (2), achiral dithienylethene (DTE) photoswitch (1), and cucurbit[8]uril (CB[8]). Chirality transfer from the chiral FF moiety of 2 to a charge-transfer (CT) heterodimer consisting of achiral guest 1 and achiral naphthalene (NP) in 2 has been unprecedented achieved via the encapsulation of CB[8]. On the contrary, chirality transfer from chiral FF to NP cannot be conducted in only guest 2. Crucially, induced circular dichroism of the heterodimer can be further modulated by distinct light, attributing to reversible photoisomerization of the DTE. Meanwhile, topological nanostructures are changed from one-dimensional (1D) nanofibers to two-dimensional (2D) nanosheets in the orderly assembling process of the heterodimer, which further achieved reversible interconversion between 2D nanosheets and 1D nanorods with tunable-induced chirality stimulated by diverse light.

Unified approach for applications of oscillatory associative-memory networks with error-free retrieval.

Given a set of standard binary patterns and a defective pattern, the binary pattern retrieval task is to find the closest pattern to the defective one among these standard patterns. The associative-memory network of Kuramoto oscillators consisting of a Hebbian coupling term and a second-order Fourier term can be applied to this task. When the memorized patterns stored in the Hebbian coupling are mutually orthogonal, recent studies show that the network is capable of distinguishing the memorized patterns from most other patterns. However, the orthogonality usually fails in real situations. In this paper, we present a unified approach for the application of this model in pattern retrieval problems with any general set of standard patterns. By subgrouping the standard patterns and employing an orthogonal lift of each subgroup, this approach makes use of the theory in the case of mutually orthogonal memorized patterns. In particular, the error-free retrieval can be guaranteed, which requires that the retrieved pattern must coincide with one of the standard patterns. As illustrative simulations, pattern retrieval tests for partly sheltered Arabic number symbols are presented.

Stereoselective Synthesis Axially Chiral Arylnitriles through Base-Induced Chirality-Relay ß-Carbon Elimination of α-Hydroxyl Ketoxime Esters.

We report herein a point-to-axial chirality transfer reaction of α-hydroxyl oxime esters for the synthesis of axially chiral arylnitriles. The reaction proceeds smoothly through a base-promoted retro-benzoin condensation reaction of α-hydroxyl oxime esters, where the axial chirality is created via the C-C bond cleavage based on a proper distorted conformation of the biaryl structure induced by its stereogenic carbon center.

Dirhodium(II)/Phosphine Catalyst with Chiral Environment at Bridging Site and Its Application in Enantioselective Atropisomer Synthesis.

A dirhodium(II)/phosphine catalyst with a chiral environment at the bridging site was developed for the asymmetric arylation of phenanthrene-9,10-diones with arylboronic acids. In contrast to the classic chiral bridging carboxylic acid (or derivatives) ligand strategy of bimetallic dirhodium(II) catalysis, in this reaction, tuning both axial and bridging ligands realized the first Rh2(OAc)4/phosphine-catalyzed highly enantioselective carbonyl addition reaction. The kinetic analysis reveals that dirhodium(II) and arylboronic acid follow the first-order kinetics, while phenanthrene-9,10-dione is zeroth-order. These data supported the proposed catalytic cycle, where the key intermediate in the rate-determining step involved the dirhodium(II) complex and arylboronic acid. Finally, axially chiral biaryls were prepared based on a newly developed oxidative ring-opening reaction of α-hydroxyl ketones with a base and molecular oxygen, which featured a central-to-axial chirality transfer radical ß-scission step.

Atroposelective Three-Component Coupling of Cyclic Diaryliodoniums and Sodium Cyanate Enabled by the Dual-Role of Phenol.

A copper-catalyzed atroposelective ring-opening reaction of cyclic diaryliodoniums, sodium cyanate (NaOCN) and phenols is reported. The reaction chemoselectively affords axially chiral carbamates by sequential coupling of cyclic diaryliodonium and NaOCN, followed by phenol. Mechanistic investigations revealed that phenol is not only a reagent to trap highly active intermediate isocyanates, but it also activates the copper catalyst as a standby ligand. The carbamates were readily transformed into highly functionalized urea derivatives within a simple nucleophilic substitution reaction.

Synthesis of Atropisomers with Biaryl and Vinylaryl Chirality via Pd-Catalyzed Point-to-Axial Chirality Transfer Ring-Opening Reaction.

A palladium-catalyzed domino cyclization/ring-opening reaction between 8H-indeno[1,2-c]thiophen-8-ols and N-(2-bromophenyl)propiolamide derivatives is reported. The reaction features a highly stereospecific point chirality to axial chirality transfer process, which enables the synthesis of molecules containing two chiral axes from the compounds with only one stereogenic center.

Torsional strain inversed chemoselectivity in a Pd-catalyzed atroposelective carbonylation reaction of dibenzothiophenium.

A palladium-catalyzed enantioselective ring-opening/carbonylation of cyclic diarylsulfonium salts is reported. In comparison to thioethers, the sulfonium salts displayed high reactivity and enabled the reaction to be performed under mild conditions (room temperature). The steric repulsion of the two non-hydrogen substituents adjacent to the axis led cyclic diarylsulfonium salts to be distorted, which enabled the ring-opening reaction to proceed with significant preference for breaking the exocyclic C-S bond.

A second-order accelerated neurodynamic approach for distributed convex optimization.

Based on the theories of inertial systems, a second-order accelerated neurodynamic approach is designed to solve a distributed convex optimization with inequality and set constraints. Most of the existing approaches for distributed convex optimization problems are usually first-order ones, and it is usually hard to analyze the convergence rate for the state solution of those first-order approaches. Due to the control design for the acceleration, the second-order neurodynamic approaches can often achieve faster convergence rate. Moreover, the existing second-order approaches are mostly designed to solve unconstrained distributed convex optimization problems, and are not suitable for solving constrained distributed convex optimization problems. It is acquired that the state solution of the designed neurodynamic approach in this paper converges to the optimal solution of the considered distributed convex optimization problem. An error function which demonstrates the performance of the designed neurodynamic approach, has a superquadratic convergence. Several numerical examples are provided to show the effectiveness of the presented second-order accelerated neurodynamic approach.

Synthesis of 2-Hydroxy-2'-aroyl-1,1'-biaryls via Oxidative Ring-Opening of 9H-Fluoren-9-ols.

An Oxone-mediated oxidative ring-opening reaction of 4,5-disubstituted 9H-fluoren-9-ols by cleavage of a carbon-carbon bond is reported. 2-Hydroxy-2'-aroyl-1,1'-biaryls can be efficiently prepared by simply heating the mixture of fluoren-9-ols, Oxone, and 1,1,1,3,3,3-hexafluoroisopropanol at 60 °C for 4 h. The persulfate-involved ring-expansion processes were proposed and supported by the DFT calculations.

Ring-Expansion Strategy for α-Aryl Azahelicene Construction: Building Blocks for Optoelectronic Materials.

An acid-mediated rapid synthesis of α-aryl azahelicenes via C-C bond cleavage of helical 9H-fluoren-9-ols is reported. The newly introduced aryl ring and pyridine moieties provide an excellent opportunity to further tune the properties of azahelicences: i.e., photoluminescence. The novel α-aryl azahelicenes showcase high circularly polarized luminescence (CPL) efficiencies (4.5 × 10-3) as well as CPL brightness (BCPL), reaching 7.39 M-1 cm-1, which indicates a potential application as chiral emitters.

Construction of Axial Chirality and Silicon-Stereogenic Center via Rh-Catalyzed Asymmetric Ring-Opening of Silafluorenes.

A rhodium-catalyzed enantioselective ring-opening/acylation of silafluorenes is reported. The newly developed bulky phosphoramidite ligand, in combination with methanol as the additive, enabled the reaction to create one axial chirality and one silicon-stereogenic center in a highly selective manner by only cleavage of one Si-C bond.

Catalytic asymmetric C-Si bond activation via torsional strain-promoted Rh-catalyzed aryl-Narasaka acylation.

Atropisomers are important organic frameworks in bioactive natural products, drugs as well as chiral catalysts. Meanwhile, silanols display unique properties compared to their alcohol analogs, however, the catalytic synthesis of atropisomers bearing silanol groups is challenging. Here, we show a rhodium-catalyzed torsional strain-promoted asymmetric ring-opening reaction for the synthesis of α-silyl biaryl atropisomers. The reaction features a dynamic kinetic resolution of C(Ar)-Si bond cleavage, whose stereochemistry was controlled by a phosphoramidite ligand derived from (S)-3-methyl-1-((2,4,6-triisopropylphenyl)sulfonyl)piperazine. This work is a demonstration of an aryl-Narasaka acylation, where the C(Ar)-Si bond cleavage is promoted by the torsional strain of α, α'-disubstituted silafluorene.

Projected Neural Network for a Class of Non-Lipschitz Optimization Problems With Linear Constraints.

In this article, we consider a class of nonsmooth, nonconvex, and non-Lipschitz optimization problems, which have wide applications in sparse optimization. We generalize the Clarke stationary point and define a kind of generalized stationary point of the problems with a stronger optimal capability. Based on the smoothing method, we propose a projected neural network for solving this kind of optimization problem. Under the condition that the level set of objective function in the feasible region is bounded, we prove that the solution of the proposed neural network is globally existent and bounded. The uniqueness of the solution of the proposed network is also analyzed. When the feasible region is bounded, any accumulation point of the proposed neural network is a generalized stationary point of the optimization model. Based on some suitable conditions, any solution of the proposed neural network is asymptotic convergent to one stationary point. In particular, we give some deep analysis on the proposed network for solving a special class of the non-Lipschitz optimization problem, which indicates a lower bound property and the unify identification for the nonzero elements of all accumulation points. Finally, some numerical results are presented to show the efficiency of the proposed neural network for solving some kinds of sparse optimization models.

A generalized neural network for distributed nonsmooth optimization with inequality constraint.

In this paper, a generalized neural network with a novel auxiliary function is proposed to solve a distributed non-differentiable optimization over a multi-agent network. The constructed auxiliary function can ensure that the state solution of proposed neural network is bounded, and enters the inequality constraint set in finite time. Furthermore, the proposed neural network is demonstrated to reach consensus and ultimately converges to the optimal solution under several mild assumptions. Compared with the existing methods, the neural network proposed in this paper has a simple structure with a low amount of state variables, and does not depend on projection operator method for constrained distributed optimization. Finally, two numerical simulations and an application in power system are delineated to show the characteristics and practicability of the presented neural network.

Synthesis of Bridged Biaryl Atropisomers via Sequential Cu- and Pd-Catalyzed Asymmetric Ring Opening and Cyclization.

Bridged biaryl atropisomers are important units in bioactive molecules. A synthesis of lactone-bridged biaryl atropisomers was realized by a Cu-catalyzed asymmetric ring-opening/acyoxylation of cyclic diaryliodoniums, followed by a palladium-catalyzed diastereoselective cyclization. It was found that a catalytic amount of Cu(OTf)2 served as an additive to promote the palladium-catalyzed Heck cyclization.

Neural network for nonsmooth pseudoconvex optimization with general convex constraints.

In this paper, a one-layer recurrent neural network is proposed for solving a class of nonsmooth, pseudoconvex optimization problems with general convex constraints. Based on the smoothing method, we construct a new regularization function, which does not depend on any information of the feasible region. Thanks to the special structure of the regularization function, we prove the global existence, uniqueness and "slow solution" character of the state of the proposed neural network. Moreover, the state solution of the proposed network is proved to be convergent to the feasible region in finite time and to the optimal solution set of the related optimization problem subsequently. In particular, the convergence of the state to an exact optimal solution is also considered in this paper. Numerical examples with simulation results are given to show the efficiency and good characteristics of the proposed network. In addition, some preliminary theoretical analysis and application of the proposed network for a wider class of dynamic portfolio optimization are included.

Development of a novel anti-human aspartyl-(asparaginyl) ß-hydroxylase monoclonal antibody with diagnostic and therapeutic potential.

Human aspartyl-(asparaginyl)-ß-hydroxylase (HAAH) has recently been the subject of several studies, as it was previously observed to be overexpressed in numerous types of carcinoma cells and tissues in patient tumor samples. HAAH has been implicated in tumor invasion and metastasis, indicating that it may be an important target and biomarker for tumor diagnosis and treatment. However, the immunological tools currently available for the study of this protein, including monoclonal antibodies, are limited, as is the present knowledge regarding the role of HAAH in tumor therapy and diagnosis. In the present study, a recombinant C-terminal domain of HAAH was expressed in Pichia pastoris and a novel monoclonal antibody (mAb) targeting HAAH (HAAH-C) was constructed. Immunofluorescence and antibody-dependent cellular cytotoxicity (ADCC) assays were used to demonstrate the specificity and ADCC activity of this antibody. The results demonstrated that this anti-C-terminal HAAH mAB, in combination with an existing anti-N terminal HAAH mAb, exhibited a high response to native HAAH from carcinoma cell culture supernatant, as measured with a double antibody sandwich enzyme-linked immunosorbent assay. This validated novel mAB-HAAH-C may prompt further studies into the underlying mechanisms of HAAH, and the exploration of its potential in tumor diagnosis and therapy.

A One-Layer Recurrent Neural Network for Pseudoconvex Optimization Problems With Equality and Inequality Constraints.

Pseudoconvex optimization problem, as an important nonconvex optimization problem, plays an important role in scientific and engineering applications. In this paper, a recurrent one-layer neural network is proposed for solving the pseudoconvex optimization problem with equality and inequality constraints. It is proved that from any initial state, the state of the proposed neural network reaches the feasible region in finite time and stays there thereafter. It is also proved that the state of the proposed neural network is convergent to an optimal solution of the related problem. Compared with the related existing recurrent neural networks for the pseudoconvex optimization problems, the proposed neural network in this paper does not need the penalty parameters and has a better convergence. Meanwhile, the proposed neural network is used to solve three nonsmooth optimization problems, and we make some detailed comparisons with the known related conclusions. In the end, some numerical examples are provided to illustrate the effectiveness of the performance of the proposed neural network.