Multilevel and Multicomponent Layer-by-Layer Assembly for the Fabrication of Nanofibrillar Films

In this study, we demonstrate multilevel and multicomponent layer-by-layer (LbL) assembly as a convenient and generally applicable method for the fabrication of nanofibrillar films by exploiting the dynamic nature of polymeric complexes. The alternate deposition of poly(allylamine hydrochloride)–methyl red (PAH-MR) complexes with poly(acrylic acid) (PAA) produces nanofibrillar PAH-MR/PAA films, which involves the disassembly of PAH-MR complexes, the subsequent assembly of PAH with PAA, and the PAA-induced assembly of MR molecules into MR nanofibrils via a π–π stacking interaction. The aqueous solution of weak polyelectrolyte PAA with a low solution pH plays an important role in fabricating nanofibrillar PAH-MR/PAA films because proton transfer from acidic PAA to MR molecules induces the formation of MR nanofibrils. The generality of the multilevel and multicomponent LbL assembly is verified by alternate assembly of complexes of 1-pyrenylbutyric acid (PYA) and PAH with PAA to fabricate PAH-PYA/PAA films with organized nanofibrillar structures. Unlike the traditional static LbL assembly, the multilevel and multicomponent LbL assembly is dynamic and more flexible and powerful in controlling the interfacial assembly process and in fabricating composite films with sophisticated structures. These characteristics of multilevel and multicomponent LbL assembly will enrich the functionalities of the LbL-assembled films

Wrapped: An R package for circular data - Fig 5

<p>Relative error of the approximate PDF (top left), and CDF (top right). Central processing unit time for 100 computations of the approximate PDF (bottom left), and CDF (right left).</p

Histograms of 100 random numbers generated from the wrapped beta normal (four plots in the top left), wrapped skew normal (four plots in the top right) wrapped asymmetric Laplace (four plots in the bottom left) and wrapped skew <i>t</i> type 3 (four plots in the bottom right) distributions for selected parameter values.

<p>Histograms of 100 random numbers generated from the wrapped beta normal (four plots in the top left), wrapped skew normal (four plots in the top right) wrapped asymmetric Laplace (four plots in the bottom left) and wrapped skew <i>t</i> type 3 (four plots in the bottom right) distributions for selected parameter values.</p

Elevated Pb(II) Release from the Reduction of Pb(IV) Corrosion Product PbO₂ Induced by Bromide-Catalyzed Monochloramine Decomposition

The stability of Pb­(IV) corrosion product PbO₂ has been linked to lead contamination in chloraminated drinking water. Recent studies have shown that autodecomposition of monochloramine (NH₂Cl) can cause lead release from PbO₂ via reductive dissolution. Bromide (Br^–) is a known catalyst for NH₂Cl decomposition. In this study, we investigated whether Br^–-catalyzed NH₂Cl decomposition could further enhance lead release from PbO_2. Our results showed that Br^–_catalyzed NH₂Cl decomposition did accelerate the reduction of PbO₂, and the rate was enhanced by the lower pH value, higher Br^–, and NH₂Cl concentrations. A single linear correlation was found between the amount of NH₂Cl decomposed and the amount of total Pb­(II) released either in the absence or presence of Br^–, suggesting that Br^–-catalyzed NH₂Cl decomposition and NH₂Cl autodecomposition may generate the same intermediate toward PbO₂ reduction. The kinetics of total Pb­(II) release can be successfully modeled by considering the overall rate of NH₂Cl decomposition with NOH as the reactive intermediate responsible for PbO₂ reduction. Our findings suggested that special attentions on lead contamination should be paid to systems with PbO₂ scales and high Br^–-containing source waters when switching disinfectant from free chlorine to monochloramine

CDFs of the wrapped beta normal (four plots in the top left), wrapped skew normal (four plots in the top right) wrapped asymmetric Laplace (four plots in the bottom left) and wrapped skew <i>t</i> type 3 (four plots in the bottom right) distributions for selected parameter values.

<p>CDFs of the wrapped beta normal (four plots in the top left), wrapped skew normal (four plots in the top right) wrapped asymmetric Laplace (four plots in the bottom left) and wrapped skew <i>t</i> type 3 (four plots in the bottom right) distributions for selected parameter values.</p

Global Phosphoproteomic Analysis of Insulin/Akt/mTORC1/S6K Signaling in Rat Hepatocytes

Insulin resistance is a hallmark of type 2 diabetes. Although multiple genetic and physiological factors interact to cause insulin resistance, deregulated signaling by phosphorylation is a common underlying mechanism. In particular, the specific phosphorylation-dependent regulatory mechanisms and signaling outputs of insulin are poorly understood in hepatocytes, which represents one of the most important insulin-responsive cell types. Using primary rat hepatocytes as a model system, we performed reductive dimethylation (ReDi)-based quantitative mass spectrometric analysis and characterized the phosphoproteome that is regulated by insulin as well as its key downstream kinases including Akt, mTORC1, and S6K. We identified a total of 12 294 unique, confidently localized phosphorylation sites and 3805 phosphorylated proteins in this single cell type. Detailed bioinformatic analysis on each individual data set identified both known and previously unrecognized targets of this key insulin downstream effector pathway. Furthermore, integrated analysis of the hepatic Akt/mTORC1/S6K signaling axis allowed the delineation of the substrate specificity of several close-related kinases within the insulin signaling pathway. We expect that the data sets will serve as an invaluable resource, providing the foundation for future hypothesis-driven research that helps delineate the molecular mechanisms that underlie the pathogenesis of type 2 diabetes and related metabolic syndrome

Reversible Actuation of Polyelectrolyte Films: Expansion-Induced Mechanical Force Enables <i>cis–trans</i> Isomerization of Azobenzenes

Fabrication of light-driven actuators that can prolong their deformation without constant irradiation poses a challenge. This study shows the preparation of polymeric actuators that are capable of reversible bending/unbending movements and prolonging their bending deformation without UV irradiation by releasing thermally cross-linked azobenzene-containing polyelectrolyte films with a limited free volume from substrates. Layer-by-layer assembly of poly­{1–4­[4-(3-carboxy-4-hydroxyphenylazo)­benzenesulfonamido]-1,2-ethanediyl sodium salt} (PAZO)–poly­(acrylic acid) (PAA) complexes (noted as PAZO–PAA) with poly­(allylamine hydrochloride) (PAH) produces azobenzene-containing PAZO–PAA/PAH films. UV irradiation induces <i>trans–cis</i> isomerization of azobenzenes and allows large-scale bending deformation of the actuators. The actuators prolong the bending deformation even under visible light irradiation because the <i>cis–trans</i> back isomerization of azobenzenes is inhibited by the limited free volume in the actuators. Unbending of actuators is attained by exposing the actuators to a humid environment at room temperature. Film expansion in a humid environment produces a mechanical force that is sufficiently strong to enable the <i>cis–trans</i> back isomerization of azobenzenes and restore the bent actuators to their original configuration. The capability of the force produced by film expansion for <i>cis–trans</i> azobenzene isomerization can be helpful for designing novel polymeric actuators

Additional file 1 of Novel cuproptosis-related prognostic gene profiles in preeclampsia

Supplementary Material 1: The raw material of validation of differential expression of copper death genes in human placental tissue using RT qPCR technolog

Reversible Actuation of Polyelectrolyte Films: Expansion-Induced Mechanical Force Enables <i>cis–trans</i> Isomerization of Azobenzenes

Fabrication of light-driven actuators that can prolong their deformation without constant irradiation poses a challenge. This study shows the preparation of polymeric actuators that are capable of reversible bending/unbending movements and prolonging their bending deformation without UV irradiation by releasing thermally cross-linked azobenzene-containing polyelectrolyte films with a limited free volume from substrates. Layer-by-layer assembly of poly­{1–4­[4-(3-carboxy-4-hydroxyphenylazo)­benzenesulfonamido]-1,2-ethanediyl sodium salt} (PAZO)–poly­(acrylic acid) (PAA) complexes (noted as PAZO–PAA) with poly­(allylamine hydrochloride) (PAH) produces azobenzene-containing PAZO–PAA/PAH films. UV irradiation induces <i>trans–cis</i> isomerization of azobenzenes and allows large-scale bending deformation of the actuators. The actuators prolong the bending deformation even under visible light irradiation because the <i>cis–trans</i> back isomerization of azobenzenes is inhibited by the limited free volume in the actuators. Unbending of actuators is attained by exposing the actuators to a humid environment at room temperature. Film expansion in a humid environment produces a mechanical force that is sufficiently strong to enable the <i>cis–trans</i> back isomerization of azobenzenes and restore the bent actuators to their original configuration. The capability of the force produced by film expansion for <i>cis–trans</i> azobenzene isomerization can be helpful for designing novel polymeric actuators

Table1_EFMSDTI: Drug-target interaction prediction based on an efficient fusion of multi-source data.XLSX

Accurate identification of Drug Target Interactions (DTIs) is of great significance for understanding the mechanism of drug treatment and discovering new drugs for disease treatment. Currently, computational methods of DTIs prediction that combine drug and target multi-source data can effectively reduce the cost and time of drug development. However, in multi-source data processing, the contribution of different source data to DTIs is often not considered. Therefore, how to make full use of the contribution of different source data to predict DTIs for efficient fusion is the key to improving the prediction accuracy of DTIs. In this paper, considering the contribution of different source data to DTIs prediction, a DTIs prediction approach based on an effective fusion of drug and target multi-source data is proposed, named EFMSDTI. EFMSDTI first builds 15 similarity networks based on multi-source information networks classified as topological and semantic graphs of drugs and targets according to their biological characteristics. Then, the multi-networks are fused by selective and entropy weighting based on similarity network fusion (SNF) according to their contribution to DTIs prediction. The deep neural networks model learns the embedding of low-dimensional vectors of drugs and targets. Finally, the LightGBM algorithm based on Gradient Boosting Decision Tree (GBDT) is used to complete DTIs prediction. Experimental results show that EFMSDTI has better performance (AUROC and AUPR are 0.982) than several state-of-the-art algorithms. Also, it has a good effect on analyzing the top 1000 prediction results, while 990 of the first 1000DTIs were confirmed. Code and data are available at https://github.com/meng-jie/EFMSDTI.</p