Predicting the catalytic activities of transition metal (Cr, Fe, Co, Ni) complexes towards ethylene polymerization by machine learning.

The study aims to execute machine learning (ML) method for building an intelligent prediction system for catalytic activities of a relatively big dataset of 1056 transition metal complex precatalysts in ethylene polymerization. Among 14 different algorithms, the CatBoost ensemble model provides the best prediction with the correlation coefficient (R2 ) values of 0.999 for training set and 0.834 for external test set. The interpretation of the obtained model indicates that the catalytic activity is highly correlated with number of atom, conjugated degree in the ligand framework, and charge distributions. Correspondingly, 10 novel complexes are designed and predicted with higher catalytic activities. This work shows the potential application of the ML method as a high-precision tool for designing advanced catalysts for ethylene polymerization.

Improving Interface Matching in MOF-on-MOF S-Scheme Heterojunction through π-π Conjugation for Boosting Photoelectric Response.

Accelerating the migration of interfacial carriers in a heterojunction is of paramount importance for driving high-performance photoelectric responses. However, the inferior contact area and large resistance at the interface limit the eventual photoelectric performance. Herein, we fabricated an S-scheme heterojunction involving a 2D/2D dual-metalloporphyrin metal-organic framework with metal-center-regulated CuTCPP(Cu)/CuTCPP(Fe) through electrostatic self-assembly. The ultrathin nanosheet-like architectures reduce the carrier migration distance, while the similar porphyrin backbones promote reasonable interface matching through π-π conjugation, thereby inhibiting the recombination of photogenerated carriers. Furthermore, the metal-center-regulated S-scheme band alignments create a giant built-in electric field, which provides a huge driving force for efficient carrier separation and migration. Coupling with the biomimetic catalytic activity of CuTCPP(Fe), the resultant heterojunction was utilized to construct photoelectrochemical uric acid biosensors. This work provides a general strategy to enhance photoelectric responses by engineering the interfacial structure of heterojunctions.

Catalytic Activity of 2-Imino-1,10-phenthrolyl Fe/Co Complexes via Linear Machine Learning.

In anticipation of the correlations between catalyst structures and their properties, the catalytic activities of 2-imino-1,10-phenanthrolyl iron and cobalt metal complexes are quantitatively investigated via linear machine learning (ML) algorithms. Comparatively, the Ridge Regression (RR) model has captured more robust predictive performance compared with other linear algorithms, with a correlation coefficient value of R2= 0.952 and a cross-validation value of Q2= 0.871. It shows that different algorithms select distinct types of descriptors, depending on the importance of descriptors. Through the interpretation of the RR model, the catalytic activity is potentially related to the steric effect of substituents and negative charged groups. This study refines descriptor selection for accurate modeling, providing insights into the variation principle of catalytic activity.

Anisotropic Dual S-Scheme Heterojunctions Mimic Natural Photosynthetic System for Boosting Photoelectric Response.

The design of heterojunctions that mimic natural photosynthetic systems holds great promise for enhancing photoelectric response. However, the limited interfacial space charge layer (SCL) often fails to provide sufficient driving force for the directional migration of inner charge carriers. Drawing inspiration from the electron transport chain (ETC) in natural photosynthesis system, we developed a novel anisotropic dual S-scheme heterojunction artificial photosynthetic system composed of Bi2O3-BiOBr-AgI for the first time, with Bi2O3 and AgI selectively distributed along the bicrystal facets of BiOBr. Compared to traditional semiconductors, the anisotropic carrier migration in BiOBr overcomes the recombination resulting from thermodynamic diffusion, thereby establishing a potential ETC for the directional migration of inner charge carriers. Importantly, this pioneering bioinspired design overcomes the limitations imposed by the limited distribution of SCL in heterojunctions, resulting in a remarkable 55-fold enhancement in photoelectric performance. Leveraging the etching of thiols on Ag-based materials, this dual S-scheme heterojunction is further employed in the construction of photoelectrochemical sensors for the detection of acetylcholinesterase and organophosphorus pesticides.

Superhydrophobic 3D-Assembled Metallic Nanoparticles for Trace Chemical Enrichment in SERS Sensing.

The performance of surface-enhanced Raman spectroscopy (SERS) is determined by the interaction between highly diluted analytes and boosted localized electromagnetic fields in nanovolumes. Although superhydrophobic surfaces are developed for analyte enrichment, i.e., to concentrate and transfer analytes toward a specific position, it is still challenging to realize reproducible, uniform, and sensitive superhydrophobic SERS substrates over large scales, representing a major barrier for practical sensing applications. To overcome this challenge, a superhydrophobic SERS chip that combines 3D-assembled gold nanoparticles on nanoporous substrates is proposed, for a strong localized field, with superhydrophobic surface treatment for analyte enrichment. Intriguingly, by concentrating droplets in the volume of 40 µL, the sensitivity of 1 nm is demonstrated using 1,2-bis(4-pyridyl)-ethylene molecules. In addition, this unique chip demonstrates a relative standard deviation (RSD) of 2.2% in chip-to-chip reproducibility for detection of fentanyl at 1 µg mL-1 concentration, revealing its potential for quantitative sensing of chemicals and drugs. Furthermore, the trace analysis of fentanyl and fentanyl-heroin mixture in human saliva is realized after a simple pretreatment process. This superhydrophobic chip paves the way toward on-site and real-time drug sensing to tackle many societal issues like drug abuse and the opioid crisis.

Catalytic Performance of Cobalt(II) Polyethylene Catalysts with Sterically Hindered Dibenzopyranyl Substituents Studied by Experimental and MLR Methods.

Given the great importance of cobalt catalysts supported by benchmark bis(imino)pyridine in the (oligo)polymerization, a series of dibenzopyran-incorporated symmetrical 2,6-bis(imino) pyridyl cobalt complexes (Co1-Co5) are designed and prepared using a one-pot template approach. The structures of the resulting complexes are well characterized by a number of techniques. After activation with either methylaluminoxane (MAO) or modified MAO (MMAO), the complexes Co1-Co4 are highly active for ethylene polymerization with a maximum activity of up to 7.36 × 106 g (PE) mol-1 (Co) h-1 and produced highly linear polyethylene with narrow molecular weight distributions, while Co5 is completely inactive under the standard conditions. Particularly, complex Co3 affords polyethylene with high molecular weights of 85.02 and 79.85 kg mol-1 in the presence of MAO and MMAO, respectively. The 1H and 13C NMR spectroscopy revealed the existence of vinyl end groups in the resulting polyethylene, highlighting the predominant involvement of the ß-H elimination reaction in the chain-termination process. To investigate the mechanism underlying the variation of catalytic activities as a function of substituents, multiple linear regression (MLR) analysis was performed, showing the key role of open cone angle (θ) and effective net charge (Q) on catalytic activity.

The Quantitative Influence of Coordinated Halogen Atoms on the Catalytic Performance of Bisiminoacenaphthylnickel Complexes in Ethylene Polymerization.

In experiments, nickel bromine complexes usually show a better catalytic performance in ethylene polymerization compared to their nickel chlorine analogues. Therefore, the present modeling study has been performed to investigate the effect of coordinated halogen atoms on the catalytic performances of two bisiminoacenaphthyl nickel systems, namely, Ni-Br and Ni-Cl. By using the multiple linear regression analysis (MLRA), the catalytic activity can be well predicted by the descriptors of effective net charge (Qeff ) and bite angle (ß), with correlation coefficient R2 values over 0.91. Meanwhile, the molecular weights of polyethylene are predicted by the descriptors of Qeff and open cone angle (θ). The calculated contributions of each descriptor show that the electronic effect is the predominant factor in Ni-Br system, while the steric effect becomes the dominant factor in Ni-Cl system. The different determined effect is expected to the main reason for the different catalytic performance between two Ni systems.

Prediction of catalytic activities of bis(imino)pyridine metal complexes by machine learning.

This work demonstrates the potential of machine learning (ML) method to predict catalytic activity of transition metal complex precatalyst toward ethylene polymerization. For this purpose, 294 complexes and 15 molecular descriptors were selected to build the artificial neural network (ANN) model. The catalytic activity can be well predicted by the obtained ANN model, which was further validated by external complexes. Boruta algorithm was employed to explicitly decipher the importance of descriptors, illustrating the conjugated bond structure, and bulky substitutions are favorable for catalytic activity. The present work indicates that ML could give useful guidance for the new design of homogenous polyolefin catalyst.

Catalytic performance of bis(imino)pyridine Fe/Co complexes toward ethylene polymerization by 2D-/3D-QSPR modeling.

The two-dimensional and three-dimensional quantitative structure-property relationship (2D- and 3D-QSPR) approaches are applied to investigate the catalytic performance for a total data set of 55 bis(imino)pryridine iron and cobalt complexes, including the catalytic activity, molecular weight, and melting temperature of the product. The obtained models for the catalytic performance of interest exhibit good results by both 2D- and 3D-QSPR modeling, meanwhile higher predictive and validation powers observed in the 3D type. The modeling results indicate that the bulky substituents on ortho-position of the singular side phenyl ring and positive charge on para-position of the phenyl ring within the ligand are favorable to catalytic activity, while unfavorable to the molecular weight of product. Based on the obtained QSPR models, four new complexes are designed and predicted with good catalytic activity and very high molecular weight, which are in good agreement with our recent experimental report. © 2019 Wiley Periodicals, Inc.

Nonlinear Holographic All-Dielectric Metasurfaces.

Nonlinear holographic metasurfaces have been intensively studied due to their potentials in practical applications. So far, nonlinear holographic metasurfaces have only been realized with plasmonic nanoantennas, suffering from high absorption loss and low damage threshold. Herein we propose and experimentally demonstrate a novel mechanism for nonlinear holographic metasurfaces. In contrast with conventional studies, the all-dielectric metasurface is composed of C-shaped Si nanoantennas. The incident laser is enhanced by their fundamental resonance, whereas the generated third-harmonic generation (THG) signals are redistributed to the air gap region via the higher order resonance, significantly reducing the absorption loss at short wavelength and resulting in an enhancement factor as high as 230. After introducing abrupt phase changes from 0 to 2π to the C elements, high-efficiency cyan and blue THG holograms have been experimentally generated with the Si metasurface for the very first time. This research shall shed light on the advances of nonlinear all-dielectric metasurfaces.

Transmissive structural color filters using vertically coupled aluminum nanohole/nanodisk array with a triangular-lattice.

We demonstrate a configuration to generate transmissive structural colors through triangular-lattice square nanohole arrays in aluminum (Al) film with Al nanodisks on the bottom of the nanoholes. By using a simple nanofabrication process, colors covering the entire visible light with different brightness and saturation are achieved by tuning both the period of arrays and the size of nanoholes. The optical behaviors of the structures are systematically investigated by both experimental and theoretical methods. The results indicate that the localized surface plasmon resonance of nanohole arrays plays the key role in the extraordinary transmission and meanwhile the coupling of disks and holes is also of importance for the enhanced transmission. With the wide color gamut, these kinds of vertically coupled Al nanohole/nanodisk arrays show the capabilities for high-resolution full-color printing. Compared to existing transmissive plasmonic color filters, the configuration in this work has the advantages of a simple fabrication process and using cheap aluminum materials.

Catalytic Activities of Bis(pentamethylene)pyridyl(Fe/Co) Complex Analogues in Ethylene Polymerization by Modeling Method.

The catalytic activities of α,α'-bisimino-2,3:5,6-bis(pentamethylene)pyridyl(Fe/Co) chloride analogue complexes are quantitatively investigated by the multiple linear regression analysis (MLRA) method. From the point of view of the electronic and steric effects, seven structural descriptors are selected and calculated, including the Hammett constant ( F), effective net charge ( Qeff), energy difference (Δ E), HOMO-LUMO energy gap (Δε1, Δε2), open cone angle (θ), and bite angle (ß). In order to get better model, the fitting analyses are carried out by using the combinations of four, three, two, and single descriptors. The calculation results show quite good correlation results. By using two descriptors ( Qeff, ß), the catalytic activities for both the Fe and Co complexes individually and also the variation between Fe and Co (Fe-Co) analogue system can be well predicted with correlation coefficient values over 0.934. It is found that the effective net charge ( Qeff) plays the dominant role in determining the catalytic activities for Fe and Co complexes. Furthermore, the lower values of catalytic activities in Co complexes are mainly attributed to the decreasing values of Qeff.

Bacterial Interactomes: Interacting Protein Partners Share Similar Function and Are Validated in Independent Assays More Frequently Than Previously Reported.

Numerous affinity purification-mass spectrometry (AP-MS) and yeast two-hybrid screens have each defined thousands of pairwise protein-protein interactions (PPIs), most of which are between functionally unrelated proteins. The accuracy of these networks, however, is under debate. Here, we present an AP-MS survey of the bacterium Desulfovibrio vulgaris together with a critical reanalysis of nine published bacterial yeast two-hybrid and AP-MS screens. We have identified 459 high confidence PPIs from D. vulgaris and 391 from Escherichia coli Compared with the nine published interactomes, our two networks are smaller, are much less highly connected, and have significantly lower false discovery rates. In addition, our interactomes are much more enriched in protein pairs that are encoded in the same operon, have similar functions, and are reproducibly detected in other physical interaction assays than the pairs reported in prior studies. Our work establishes more stringent benchmarks for the properties of protein interactomes and suggests that bona fide PPIs much more frequently involve protein partners that are annotated with similar functions or that can be validated in independent assays than earlier studies suggested.

Vanadium NMR Chemical Shifts of (Imido)vanadium(V) Dichloride Complexes with Imidazolin-2-iminato and Imidazolidin-2-iminato Ligands: Cooperation with Quantum-Chemical Calculations and Multiple Linear Regression Analyses.

The NMR chemical shifts of vanadium (51V) in (imido)vanadium(V) dichloride complexes with imidazolin-2-iminato and imidazolidin-2-iminato ligands were calculated by the density functional theory (DFT) method with GIAO. The calculated 51V NMR chemical shifts were analyzed by the multiple linear regression (MLR) analysis (MLRA) method with a series of calculated molecular properties. Some of calculated NMR chemical shifts were incorrect using the optimized molecular geometries of the X-ray structures. After the global minimum geometries of all of the molecules were determined, the trend of the observed chemical shifts was well reproduced by the present DFT method. The MLRA method was performed to investigate the correlation between the 51V NMR chemical shift and the natural charge, band energy gap, and Wiberg bond index of the V═N bond. The 51V NMR chemical shifts obtained with the present MLR model were well reproduced with a correlation coefficient of 0.97.

Overweight, gestational weight gain and elevated fasting plasma glucose and their association with macrosomia in chinese pregnant women.

To provide a current estimation of overweight, gestational weight gain(GWG), elevated fasting plasma glucose (FPG) in pregnant women in Kunshan, China and investigate their association with macrosomia using recommendations of IOM and International Association of Diabetes and Pregnancy Study Groups. We conducted a population-based retrospective study and analyzed routine data from Kunshan Maternity and Child Care Surveillance System of 27,322 women with singleton full-term birth from 2006 to 2010. The prevalence of maternal overweight at early pregnancy according to WHO BMI categories (BMI: 25.0-29.9 kg/m(2)) or the cutoffs for Chinese (BMI:24.0-27.9 kg/m(2)), elevated FPG (≥5.1 mmol/L) were estimated. Proportions of women with GWG below, within and above 2009 IOM recommendations were used to evaluate the adequacy of GWG. The association between maternal overweight, GWG, elevated FPG and macrosomia was analyzed by multiple logistic regression. The prevalence of maternal overweight was 8.9 % according to WHO BMI categories and 11.9 % according to Chinese cutoffs. The rate of elevated FPG at first prenatal visit was 19.4 %. Overweight women gained, on average, 12.2 ± 5.3 or 13.0 ± 5.2 (kg) during gestation, 57.1 or 63.93 % of which had excessive weight gain above IOM recommendations (6.8-11.4 kg) according to WHO BMI categories or Chinese cutoffs, respectively. Maternal overweight, GWG and elevated FPG were positively and significantly associated with macrosomia after adjusting for maternal age and gestational weeks at delivery. Maternal overweight, excessive weight gain, elevated FPG are common in the Chinese population in Kunshan. These metabolic risk factors associated with macrosomia should be controlled under the recommendations for Chinese pregnant population.

Highly efficient vortex generation at the nanoscale.

Control of the angular momentum of light at the nanoscale is critical for many applications of subwavelength photonics, such as high-capacity optical communications devices, super-resolution imaging and optical trapping. However, conventional approaches to generate optical vortices suffer from either low efficiency or relatively large device footprints. Here we show a new strategy for vortex generation at the nanoscale that surpasses single-pixel phase control. We reveal that interaction between neighbouring nanopillars of a meta-quadrumer can tailor both the intensity and phase of the transmitted light. Consequently, a subwavelength nanopillar quadrumer is sufficient to cover a 2lπ phase change, thus efficiently converting incident light into high-purity optical vortices with different topological charges l. Benefiting from the nanoscale footprint of the meta-quadrumers, we demonstrate high-density vortex beam arrays and high-dimensional information encryption, bringing a new degree of freedom to many designs of meta-devices.

Human ß-defensin-1 affects the mammalian target of rapamycin pathway and autophagy in colon cancer cells through long non-coding RNA TCONS_00014506.

BACKGROUND: Colorectal cancer has a low 5-year survival rate and high mortality. Human ß-defensin-1 (hBD-1) may play an integral function in the innate immune system, contributing to the recognition and destruction of cancer cells. Long non-coding RNAs (lncRNAs) are involved in the process of cell differentiation and growth. AIM: To investigate the effect of hBD-1 on the mammalian target of rapamycin (mTOR) pathway and autophagy in human colon cancer SW620 cells. METHODS: CCK8 assay was utilized for the detection of cell proliferation and determination of the optimal drug concentration. Colony formation assay was employed to assess the effect of hBD-1 on SW620 cell proliferation. Bioinformatics was used to screen potentially biologically significant lncRNAs related to the mTOR pathway. Additionally, p-mTOR (Ser2448), Beclin1, and LC3II/I expression levels in SW620 cells were assessed through Western blot analysis. RESULTS: hBD-1 inhibited the proliferative ability of SW620 cells, as evidenced by the reduction in the colony formation capacity of SW620 cells upon exposure to hBD-1. hBD-1 decreased the expression of p-mTOR (Ser2448) protein and increased the expression of Beclin1 and LC3II/I protein. Furthermore, bioinformatics analysis identified seven lncRNAs (2 upregulated and 5 downregulated) related to the mTOR pathway. The lncRNA TCONS_00014506 was ultimately selected. Following the inhibition of the lncRNA TCONS_00014506, exposure to hBD-1 inhibited p-mTOR (Ser2448) and promoted Beclin1 and LC3II/I protein expression. CONCLUSION: hBD-1 inhibits the mTOR pathway and promotes autophagy by upregulating the expression of the lncRNA TCONS_00014506 in SW620 cells.

Chitosan-stabilized iron-copper nanoparticles for efficient removal of nitrate.

Chitosan-stabilized iron-copper nanomaterials (CS-nZVI/Cu) were successfully prepared and applied to the nitrate removal. Batch experiments were conducted to examine the effects of experimental parameters on nitrate removal, including Cu loading, CS-nZVI/Cu dosages, initial nitrate concentrations, and initial pHs. From the experimental date, it was concluded that CS-nZVI/Cu has a high nitrate removal efficiency, which can be more than 97%, respectively, at Cu loading = 5%, dosages of CS-nZVI/Cu = 3 g/L, initial nitrate concentrations of 30~120 mg/L, and initial pH values = 2~9. Additionally, the kinetic data for CS-nZVI/Cu were found to fit well with the first-order kinetic model with a rate constant of 0.15 (mg∙L)1-n/min, where n=1. The Langmuir model showed a good fit for NO3- removal, indicating that monolayer chemisorption occurred. The SEM and TEM analyses showed that the addition of chitosan resulted in improved dispersion of the CS-nZVI/Cu. The CS-nZVI/Cu nanomaterials have a more complete elliptical shape and are between 50 and 100 nm in size. The XRD analysis showed that the chitosan encapsulation reduced the oxidation of the iron component and the main product was Fe3O4. The FT-IR analysis showed that the immobilization of chitosan and the iron was accomplished by the ligand interaction. The nitrogen adsorption-desorption isotherm results showed that the CS-nZVI/Cu specific surface area and pore volume decreased significantly after the reaction. Adsorption, oxidation, and reduction are possible mechanisms for nitrate removal by CS-nZVI/Cu. The XPS analysis investigated the contribution of nZVI and Cu in the removal mechanism. Adding copper accelerates the reaction time and rate. In addition, nZVI played a vital role in reducing nitrate to N2. Based on these results, it looks like CS-nZVI/Cu could be a satisfactory material for nitrate removal.

Imaging-based intelligent spectrometer on a plasmonic rainbow chip.

Compact, lightweight, and on-chip spectrometers are required to develop portable and handheld sensing and analysis applications. However, the performance of these miniaturized systems is usually much lower than their benchtop laboratory counterparts due to oversimplified optical architectures. Here, we develop a compact plasmonic "rainbow" chip for rapid, accurate dual-functional spectroscopic sensing that can surpass conventional portable spectrometers under selected conditions. The nanostructure consists of one-dimensional or two-dimensional graded metallic gratings. By using a single image obtained by an ordinary camera, this compact system can accurately and precisely determine the spectroscopic and polarimetric information of the illumination spectrum. Assisted by suitably trained deep learning algorithms, we demonstrate the characterization of optical rotatory dispersion of glucose solutions at two-peak and three-peak narrowband illumination across the visible spectrum using just a single image. This system holds the potential for integration with smartphones and lab-on-a-chip systems to develop applications for in situ analysis.

Global functional atlas of Escherichia coli encompassing previously uncharacterized proteins.

One-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans). Many map to distant clades such as Archaea, suggesting involvement in basic prokaryotic traits, whereas others appear restricted to E. coli, including pathogenic strains. To elucidate the orphans' biological roles, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated gene products, whereas a machine-learning strategy based on network integration implicated the orphans in specific biological processes. We provide additional experimental evidence supporting orphan participation in protein synthesis, amino acid metabolism, biofilm formation, motility, and assembly of the bacterial cell envelope. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.