Enhancing crystal structure prediction by combining computational and experimental data via graph networks

Crystal structure prediction (CSP) stands as a powerful tool in materials science, driving the discovery and design of innovative materials. However, existing CSP methods heavily rely on formation enthalpies derived from density functional theory (DFT) calculations, often overlooking differences between DFT and experimental values. Moreover, material synthesis is intricately influenced by factors such as kinetics and experimental conditions. To overcome these limitations, a novel collaborative approach was proposed for CSP that combines DFT with experimental data, utilizing advanced deep learning models and optimization algorithms. We illustrate the capability to predict formation enthalpies that closely align with actual experimental observations through the transfer learning on experimental data. By incorporating experimental synthesizable information of crystals, our model is capable of reverse engineering crystal structures that can be synthesized in experiments. Applying the model to 17 representative compounds, the results indicate that the model can accurately identify experimentally synthesized structures with high precision. Moreover, the obtained formation enthalpies and lattice constants closely align with experimental values, underscoring the model's effectiveness. The synergistic approach between theoretical and experimental data bridges the longstanding disparities between theoretical predictions and experimental results, thereby alleviating the demand for extensive and costly experimental trials

Activation of Nrf2 by Sulforaphane Inhibits High Glucose-Induced Progression of Pancreatic Cancer via AMPK Dependent Signaling

Background/Aims: Sulforaphane (SFN) is known for its potent bioactive properties, such as anti-inflammatory and anti-tumor effects. However, its anti-tumor effect on pancreatic cancer is still poorly understood. In the present study, we explored the therapeutic potential of SFN for pancreatic cancer and disclosed the underlying mechanism. Methods: Panc-1 and MiaPaca-2 cell lines were used in vitro. The biological function of SFN in pancreatic cancer was measured using EdU staining, colony formation, apoptosis, migration and invasion assays. Reactive oxygen species (ROS) production was measured using 2’-7’-Dichlorofluorescein diacetate (DCF-DA) fluorometric analysis. Western blotting and immunofluorescence were used to measure the protein levels of p-AMPK and epithelial-mesenchymal transition (EMT) pathway-related proteins, and cellular translocation of nuclear factor erythroid 2-related factor 2 (Nrf2). Nude mice and transgenic pancreatic cancer mouse model were used to measure the therapeutic potential of SFN on pancreatic cancer. Results: SFN can inhibit pancreatic cancer cell growth， promote apoptosis, curb colony formation and temper the migratory and invasion ability of pancreatic cancer cells. Mechanistically, excessive ROS production induced by SFN activated AMPK signaling and promoted the translocation of Nrf2, resulting in cell viability inhibition of pancreatic cancer. Pretreatment with compound C, a small molecular inhibitor of AMPK signaling, reversed the subcellular translocation of Nrf2 and rescued cell invasion ability. With nude mice and pancreatic cancer transgenic mouse, we identified SFN could inhibit tumor progression, with smaller tumor size and slower tumor progression in SFN treatment group. Conclusion: Our study not only elucidates the mechanism of SFN-induced inhibition of pancreatic cancer in both normal and high glucose condition, but also testifies the dual-role of ROS in pancreatic cancer progression. Collectively, our research suggests that SFN may serve as a potential therapeutic choice for pancreatic cancer

Enhancing the Carbon Monoxide Oxidation Performance through Surface Defect Enrichment of Ceria-Based Supports for Platinum Catalyst.

Effective synthesis and application of single-atom catalysts on supports lacking enough defects remain a significant challenge in environmental catalysis. Herein, we present a universal defect-enrichment strategy to increase the surface defects of CeO2-based supports through H2 reduction pretreatment. The Pt catalysts supported by defective CeO2-based supports, including CeO2, CeZrOx, and CeO2/Al2O3 (CA), exhibit much higher Pt dispersion and CO oxidation activity upon reduction activation compared to their counterpart catalysts without defect enrichment. Specifically, Pt is present as embedded single atoms on the CA support with enriched surface defects (CA-HD) based on which the highly active catalyst showing embedded Pt clusters (PtC) with the bottom layer of Pt atoms substituting the Ce cations in the CeO2 surface lattice can be obtained through reduction activation. Embedded PtC can better facilitate CO adsorption and promote O2 activation at PtC-CeO2 interfaces, thereby contributing to the superior low-temperature CO oxidation activity of the Pt/CA-HD catalyst after activation

Enhancing the Carbon Monoxide Oxidation Performance through Surface Defect Enrichment of Ceria-Based Supports for Platinum Catalyst

Effective synthesis and application of single-atom catalysts on supports lacking enough defects remain a significant challenge in environmental catalysis. Herein, we present a universal defect-enrichment strategy to increase the surface defects of CeO2-based supports through H2 reduction pretreatment. The Pt catalysts supported by defective CeO2-based supports, including CeO2, CeZrOx, and CeO2/Al2O3 (CA), exhibit much higher Pt dispersion and CO oxidation activity upon reduction activation compared to their counterpart catalysts without defect enrichment. Specifically, Pt is present as embedded single atoms on the CA support with enriched surface defects (CA-HD) based on which the highly active catalyst showing embedded Pt clusters (PtC) with the bottom layer of Pt atoms substituting the Ce cations in the CeO2 surface lattice can be obtained through reduction activation. Embedded PtC can better facilitate CO adsorption and promote O2 activation at PtC–CeO2 interfaces, thereby contributing to the superior low-temperature CO oxidation activity of the Pt/CA-HD catalyst after activation

Learning implementation of a guideline based decision support system to improve hypertension treatment in primary care in China: pragmatic cluster randomised controlled trial

Objective: To evaluate the effectiveness of a clinical decision support system (CDSS) in improving the use of guideline accordant antihypertensive treatment in primary care settings in China. Design: Pragmatic, open label, cluster randomised trial. Setting: 94 primary care practices in four urban regions of China between August 2019 and July 2022: Luoyang (central China), Jining (east China), and Shenzhen (south China, including two regions). Participants: 94 practices were randomised (46 to CDSS, 48 to usual care). 12 137 participants with hypertension who used up to two classes of antihypertensives and had a systolic blood pressure <180 mm Hg and diastolic blood pressure <110 mm Hg were included. Interventions: Primary care practices were randomised to use an electronic health record based CDSS, which recommended a specific guideline accordant regimen for initiation, titration, or switching of antihypertensive (the intervention), or to use the same electronic health record without CDSS and provide treatment as usual (control). Main outcome measures: The primary outcome was the proportion of hypertension related visits during which an appropriate (guideline accordant) treatment was provided. Secondary outcomes were the average reduction in systolic blood pressure and proportion of participants with controlled blood pressure (<140/90 mm Hg) at the last scheduled follow-up. Safety outcomes were patient reported antihypertensive treatment related events, including syncope, injurious fall, symptomatic hypotension or systolic blood pressure <90 mm Hg, and bradycardia. Results: 5755 participants with 23 113 visits in the intervention group and 6382 participants with 27 868 visits in the control group were included. Mean age was 61 (standard deviation 13) years and 42.5% were women. During a median 11.6 months of follow-up, the proportion of visits at which appropriate treatment was given was higher in the intervention group than in the control group (77.8% (17 975/23 113) v 62.2% (17 328/27 868); absolute difference 15.2 percentage points (95% confidence interval (CI) 10.7 to 19.8); P<0.001; odds ratio 2.17 (95% CI 1.75 to 2.69); P<0.001). Compared with participants in the control group, those in the intervention group had a 1.6 mm Hg (95% CI −2.7 to −0.5) greater reduction in systolic blood pressure (−1.5 mm Hg v 0.3 mm Hg; P=0.006) and a 4.4 percentage point (95% CI −0.7 to 9.5) improvement in blood pressure control rate (69.0% (3415/4952) v 64.6% (3778/5845); P=0.07). Patient reported antihypertensive treatment related adverse effects were rare in both groups. Conclusions: Use of a CDSS in primary care in China improved the provision of guideline accordant antihypertensive treatment and led to a modest reduction in blood pressure. The CDSS offers a promising approach to delivering better care for hypertension, both safely and efficiently. Trial registration: ClinicalTrials.gov NCT03636334

Entomopathogenic Fungi on Hemiberlesia pitysophila

Hemiberlesia pitysophila Takagi is an extremely harmful exotic insect in forest to Pinus species, including Pinus massoniana. Using both morphological taxonomy and molecular phylogenetics, we identified 15 strains of entomogenous fungi, which belong to 9 genera with high diversities. Surprisingly, we found that five strains that were classified as species of Pestalotiopsis, which has been considered plant pathogens and endophytes, were the dominant entomopathogenic fungus of H. pitysophila. Molecular phylogenetic tree established by analyzing sequences of ribosomal DNA internal transcribed spacer showed that entomopathogenic Pestalotiopsis spp. were similar to plant Pestalotiopsis, but not to other pathogens and endophytes of its host plant P. massoniana. We were the first to isolate entomopathogenic Pestalotiopsis spp. from H. pitysophila. Our findings suggest a potential and promising method of H. pitysophila bio-control

Integral Equation Method for a Non-Selfadjoint Steklov Eigenvalue Problem

We propose a numerical method for a non-selfadjoint Steklov eigenvalue problem of the Helmholtz equation. The problem is formulated using boundary integrals. The Nyström method is employed to discretize the integral operators, which leads to a non-Hermitian generalized matrix eigenvalue problems. The spectral indicator method (SIM) is then applied to calculate the (complex) eigenvalues. The convergence is proved using the spectral approximation theory for (non-selfadjoint) compact operators. Numerical examples are presented for validation

Analysis of a Fourier–Galerkin Method for the Transmission Eigenvalue Problem based on a Boundary Integral Formulation

We consider the computation of the transmission eigenvalue problem based on a boundary integral formulation. The problem is formulated as the eigenvalue problem of a holomorphic Fredholm operator function. A Fourier–Galerkin method is proposed for the integral equations. The approximation properties of the associated discrete operators are analyzed and some convergence results of the eigenvalues are obtained. We present the details of the implementation and employ the spectral projection method to compute the eigenvalues. Numerical examples validate the effectiveness and accuracy of the proposed method