Bis(4-amino­benzene­sulfonato-κO)bis­(propane-1,3-diamine-κ2 N,N′)copper(II) dihydrate

In the title compound, [Cu(C3H10N2)2(C6H6NO3S)2]·2H2O, the CuII atom lies on an inversion center and is hexa­coordinated by four N atoms from two 1,3-diamino­propane ligands and two O atoms from two 4-amino­benzene­sulfonate ligands in a trans arrangement, displaying a distorted and axially elongated octa­hedral coordination geometry, with the O atoms at the axial positions. A three-dimensional network is formed in the crystal structure through O—H⋯O, N—H⋯O and N—H⋯N hydrogen bonds

Quantum Alternating Operator Ansatz for Solving the Minimum Exact Cover Problem

The minimum exact cover (MEC) is a common combinatorial optimization problem, with wide applications in tail-assignment and vehicle routing. In this paper, we adopt quantum alternating operator ansatz (QAOA+) to solve MEC problem. In detail, to obtain a trivial feasible solution, we first transform MEC into a constrained optimization problem with two objective functions. Then, we adopt the linear weighted sum method to solve the above constrained optimization problem and construct the corresponding target Hamiltonian. Finally, to improve the performance of this algorithm, we adopt parameters fixing strategy to simulate, where the experimental instances are 6, 8, and 10 qubits. The numerical results show that the solution can be obtained with high probability when level $p$ of the algorithm is low. Besides, we optimize the quantum circuit by removing single-qubit rotating gates $R_Z$. We found that the number of quantum gates is reduced by $np$ for $p$-level optimized circuit. Furthermore, $p$-level optimized circuit only needs $p$ parameters, which can achieve an experimental effect similar to original circuit with $2p$ parameters

Organochlorinated pesticides expedite the enzymatic degradation of DNA

Extracellular DNA in the environment may play important roles in genetic diversity and biological evolution. However, the influence of environmental persistent organic contaminants such as organochlorinated pesticides (e.g., hexachlorocyclohexanes [HCHs]) on the enzymatic degradation of extracellular DNA has not been elucidated. In this study, we observed expedited enzymatic degradation of extracellular DNA in the presence of α-HCH, β-HCH and γ-HCH. The HCH-expedited DNA degradation was not due to increased deoxyribonuclease I (DNase I) activity. Our spectroscopic and computational results indicate that HCHs bound to DNA bases (most likely guanine) via Van der Waals forces and halogen bonds. This binding increased the helicity and accumulation of DNA base pairs, leading to a more compact DNA structure that exposed more sites susceptible to DNase I and thus expedited DNA degradation. This study provided insight into the genotoxicity and ecotoxicity of pesticides and improved our understanding of DNA persistence in contaminated environments

Variational quantum algorithm-preserving feasible space for solving the uncapacitated facility location problem

The Quantum Alternating Operator Ansatz (QAOA+) is one of the Variational Quantum Algorithm (VQA) specifically developed to tackle combinatorial optimization problems by exploring the feasible space in search of a target solution. For constrained optimization problems with unconstrained variables, which we call Unconstrained-Variables Problems (UVPs), the mixed operators in the QAOA+ circuit are applied to the constrained variables, while the single-qubit rotating gates $R_X$ operate on the unconstrained variables. The expressibility of this circuit is limited by the shortage of two-qubit gates and the parameter sharing in the $R_X$, which consequently impacts the performance of QAOA+ for solving UVPs. Therefore, it is crucial to develop a suitable ansatz for UVPs. In this paper, we propose the Variational Quantum Algorithm-Preserving Feasible Space (VQA-PFS) ansatz, exemplified by the Uncapacitated Facility Location Problem (UFLP), that applies mixed operators on constrained variables while employing Hardware-Efficient Ansatz (HEA) on unconstrained variables. The numerical results demonstrate that VQA-PFS significantly enhances the success probability and exhibits faster convergence compared to QAOA+, Quantum Approximation Optimization Algorithm (QAOA), and HEA. Furthermore, VQA-PFS reduces the circuit depth dramatically in comparison to QAOA+ and QAOA. Our algorithm is general and instructive in tackling UVPs

Multilevel leapfrogging initialization for quantum approximate optimization algorithm

The quantum approximate optimization algorithm (QAOA) is a prospective hybrid quantum-classical algorithm widely used to solve combinatorial optimization problems. However, the external parameter optimization required in QAOA tends to consume extensive resources to find the optimal parameters of the parameterized quantum circuit, which may be the bottleneck of QAOA. To meet this challenge, we first propose multilevel leapfrogging learning (M-Leap) that can be extended to quantum reinforcement learning, quantum circuit design, and other domains. M-Leap incrementally increases the circuit depth during optimization and predicts the initial parameters at level $p+r$ ($r>1$) based on the optimized parameters at level $p$, cutting down the optimization rounds. Then, we propose a multilevel leapfrogging-interpolation strategy (MLI) for initializing optimizations by combining M-Leap with the interpolation technique. We benchmark its performance on the Maxcut problem. Compared with the Interpolation-based strategy (INTERP), MLI cuts down at least half the number of rounds of optimization for the classical outer learning loop. Remarkably, the simulation results demonstrate that the running time of MLI is 1/3 of INTERP when MLI gets quasi-optimal solutions. In addition, we present the greedy-MLI strategy by introducing multi-start, which is an extension of MLI. The simulation results show that greedy-MLI can get a higher average performance than the remaining two methods. With their efficiency to find the quasi-optima in a fraction of costs, our methods may shed light in other quantum algorithms

Protective effect of omeprazole on gastric mucosal of cirrhotic portal hypertension rats

AbstractObjectiveTo observe the protective effect of omeprazole on gastric mucosal of cirrhotic portal hypertension rats.MethodsAll rats were randomly divided into normal control group, cirrhosis and treatment group. Thioacetamide was used to establish rat model of cirrhotic portal hypertension. The necrotic tissue of gastric mucosa ulcer focus, degree of neutrophils infiltration at the ulcer margin, portal pressure, portal venous flow, abdominal aortic pressure, abdominal aortic blood flow at front end, gastric mucosal blood flow (GMBF), glycoprotein (GP) of gastric mucosa, basal acid secretion, H+back -diffusion, gastric mucosal damage index, NO, prostaglandin E2(PGE2) and tumor necrosis factor-α (TNF-α) were determined respectively, and the pathological changes of gastric mucosa were also observed by microscope.ResultsCompared with cirrhosis group and the control group, the ulcer bottom necrotic material, gastric neutrophil infiltration and UI of the treatment group were all decreased significantly (P<0.01), GMBF value, GP values, serum NO, PGE2, TNF-α were all significantly increased.ConclusionsOmeprazole has an important protective effect on gastric mucosal and it can increase gastric mucosal blood flow and related to many factors

The role of globular heads of the C1q receptor in HPV 16 E2-induced human cervical squamous carcinoma cell apoptosis is associated with p38 MAPK/JNK activation

BACKGROUND Human papillomavirus type 16 (HPV 16) E2 protein is a multifunctional DNA-binding protein. HPV 16 E2 regulates many biological responses, including DNA replication, gene expression, and apoptosis. The purpose of this study was to investigate the relationship among the receptor for globular heads of the human C1q (gC1qR) gene expression, HPV 16 E2 transfection and apoptosis regulation in human cervical squamous carcinoma cells (C33a and SiHa). METHODS gC1qR expression was examined in C33a and SiHa cells using real-time PCR and Western blot analysis. Apoptosis of C33a and SiHa cells was assessed by flow cytometry. C33a and SiHa cell viability, migration and proliferation were detected using the water-soluble tetrazolium salt (WST-1) assay, a transwell assay and 3H-thymidine incorporation into DNA (3H-TdR), respectively. RESULTS C33a and SiHa cells that were transfected with a vector encoding HPV 16 E2 displayed significantly increased gC1qR gene expression and p38 mitogen-activated protein kinase (p38 MAPK)/c-jun N-terminal kinase (JNK) activation as well as up-regulation of cellular apoptosis, which was abrogated by the addition of gC1qR small interfering RNA (siRNA). Furthermore, the changes in C33a and SiHa cell viability, migration and proliferation that were observed upon HPV 16 E2 transfection were abrogated by SB203580 (a p38 MAPK inhibitor) or SP600125 (a JNK inhibitor) treatment. CONCLUSION These data support a mechanism whereby HPV 16 E2 induces apoptosis by silencing the gC1qR gene or inhibiting p38 MAPK/JNK signalling in cervical squamous cell carcinoma.This study was supported by grants from the National Natural Science Foundation of China (No. 81000251) and the Nanjing Medical Science and Technique Development Foundation

Screening of prognostic biomarkers for endometrial carcinoma based on a ceRNA network

Objective This study aims to reveal the regulation network of lncRNAs-miRNAs-mRNA in endometrial carcinoma (EC), to investigate the underlying mechanisms of EC occurrence and progression, to screen prognostic biomarkers. Methods RNA-seq and miRNA-seq data of endometrial carcinoma were downloaded from the TCGA database. Edge.R package was used to screen differentially expressed genes. A database was searched to determine differentially expressed lncRNA-miRNA and miRNA-mRNA pairs, to construct the topological network of ceRNA, and to elucidate the key RNAs that are for a prognosis of survival. Results We screened out 2632 mRNAs, 1178 lncRNAs and 189 miRNAs that were differentially expressed. The constructed ceRNA network included 97 lncRNAs, 20 miRNAs and 73 mRNAs. Analyzing network genes for associations with prognosies revealed 169 prognosis-associated RNAs, including 92 lncRNAs, 16miRNAs and 61 mRNAs. Conclusion Our results reveal new potential mechanisms underlying the carcinogenesis and progression of endometrial carcinoma