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CO2 methanation is regarded as an efficient method for upgrading CO2 to fuels and reducing environmental impacts of greenhouse gas emission. In this study, we developed Ni/ La2O2CO3 low temperature CO2 methanation catalysts by tuning the metal-support interaction via changing the morphology of catalyst supports. La2O2CO3 supports with various morphologies including nanotriangles (La2O2CO3-T), nanorods (La2O2CO3-R), and nanoparticles (La2O2CO3-P), were synthesized as the supports of Ni catalysts for CO2 methanation reaction. The CO2 methanation performance of the synthesized Ni/La2O2CO3 catalysts was found to be markedly superior to that of conventional Ni/SiO2 catalysts with the following orders: Ni/La2O2CO3-T > Ni/La2O2CO3-R > Ni/La2O2CO3-P > Ni/SiO2. In the comparative characterization of Ni/La2O2CO3 catalysts with various morphologies, TEM and H2-TPR results reveal that the Ni/La2O2CO3-T catalysts exhibit better dispersion of Ni nanoparticles and higher reducibility. Moreover, X-ray photoelectron spectroscopy (XPS), O2 and H2 temperature programmed desorption (O2-TPD, H2-TPD) results indicate that the Ni/La2O2CO3-T catalysts possess a lower oxygen vacancy formation energy leading to a higher concentration of interfacial oxygen vacancies, which enhances the adsorption hydrogen at these interfacial oxygen vacancy sites. CO2-TPD results further reveal that Ni/La2O2CO3-T catalysts own higher concentration of medium basic sites, which promote the adsorption and activation of CO2. Consequently, Ni/La2O2CO3-T catalysts demonstrate superior low-temperature CO2 methanation activity by hydrogenation of CO2 adsorbed as surface carbonates on the La2O2CO3 surfaces with hydrogen spilled over from the Ni surfaces via the interfacial oxygen vacancies to the catalyst support. [ABSTRACT FROM AUTHOR]

Monitoring anti-drug antibodies (ADAs) to infliximab and adalimumab is critical to treatment management in various autoimmune disorders. The growing need for proactive therapeutic monitoring further requires the detection of ADAs in the presence of measurable concentrations of infliximab or adalimumab. To provide robust analytical assays for clinical application, we evaluated two automated immunoassays developed using ImmunoCAP™ technology and based on the bridging format to measure serum ADAs to infliximab and adalimumab respectively. Without an acid-dissociation step, these research prototype assays can detect a positive control monoclonal ADA towards infliximab and adalimumab, ranging from < 25 ng/ml to 10,000 ng/mL. Both assays exhibit imprecision less than 20% at different ADA titer levels and can distinguish ADAs towards different drug targets. In method comparison using authentic patient samples, the quantitative results of the ADA assays are not directly comparable to two existing clinical immunoassays for ADAs (correlation coefficient rs = 0.673 for infliximab ADAs; rs = 0.510 for adalimumab ADAs), presumably due to the lack of commutable ADA standards and the polyclonal nature of ADAs. Nevertheless, there is qualitative agreement between the methods when evaluating putative positive and negative patient samples (overall agreement 0.83 for infliximab ADAs; 0.76 for adalimumab ADAs). Biotin and high levels of rheumatoid factors may interfere with the performance of the automated assays due to competitive binding with the biotinylated drug and non-specific formation of bridging complexes. The two ImmunoCAP assays can provide new analytical methods for proactive therapeutic monitoring of adalimumab and infliximab. [ABSTRACT FROM AUTHOR]

Modern cloud-native OLAP databases adopt a storage-disaggregation architecture that separates the management of computation and storage. A major bottleneck in such an architecture is the network connecting the computation and storage layers. Computation pushdown is a promising solution to tackle this issue, which offloads some computation tasks to the storage layer to reduce network traffic. This paper presents FlexPushdownDB (FPDB), where we revisit the design of computation pushdown in a storage-disaggregation architecture, and then introduce several optimizations to further accelerate query processing. First, FPDB supports hybrid query execution, which combines local computation on cached data and computation pushdown to cloud storage at a fine granularity. Within the cache, FPDB uses a novel Weighted-LFU cache replacement policy that takes into account the cost of pushdown computation. Second, we design adaptive pushdown as a new mechanism to avoid throttling the storage-layer computation during pushdown, which pushes the request back to the computation layer at runtime if the storage-layer computational resource is insufficient. Finally, we derive a general principle to identify pushdown-amenable computational tasks, by summarizing common patterns of pushdown capabilities in existing systems, and further propose two new pushdown operators, namely, selection bitmap and distributed data shuffle. Evaluation on SSB and TPC-H shows each optimization can improve the performance by 2.2 × , 1.9 × , and 3 × respectively. [ABSTRACT FROM AUTHOR]

The utilization of coal gasification slag as a resource is a crucial aspect of the sustainable development of the chemical industry. Coal gasification fine slag (CGFS) contains abundant sources of silicon and aluminum, making it suitable for the preparation of high-value zeolite materials. In this study, coal gasification fine slag was utilized as a raw material, and different Si/Al ratios of zeolite were obtained through a graded preparation method using mother liquor cycle technology. Initially, P-type zeolite/carbon composites (P/C composites) with a low silicon-aluminum ratio (5.2) were prepared. Subsequently, high value-added ZSM-5 zeolite with a high silicon-aluminum ratio (156.6) was synthesized. Its crystallinity, purity, and specific surface area surpassed those of commercial ZSM-5 quality. The desiliconization liquid was efficiently circulated to utilize silicon source, sodium source, and water effectively. Finally, solid waste served as raw material for hydrothermal synthesis of nano-ZSM-5 zeolite using the nano seed emulsion addition method. This technical approach achieves "quasi-zero" emission for coal gasification fine slag while synthesizing high-quality zeolite that holds excellent prospects for industrial solid waste treatment. [ABSTRACT FROM AUTHOR]

A hydrothermal synthesis method was developed to produce high crystallinity ZSM-5 zeolite using coal gasification coarse slag (CGCS) as the raw material. Instead of the expensive NaOH(s.), Na2SiO3(s.) was utilized to activate, depolymerize, and recombine Si and Al elements in the CGCS. The mother liquor circulation technology was employed to recover and reuse raw materials and residual reagents (Na2SiO3(aq.) and TPABr), reducing waste emissions and enhancing resource utilization efficiency. The synthesized ZSM-5 had a specific surface area of 455.675 m2 g−1, pore volume of 0.284 cm3 g−1, and pore diameter of 2.496 nm. The influence of various factors on the morphology and crystallinity of ZSM-5 was investigated, resulting in the production of ZSM-5 with higher specific surface area and pore volume. Adsorption experiments showed that WU-ZSM-5 exhibited a removal efficiency of 85% for ammonia nitrogen (NH4+-N(aq.)), validating its effectiveness in coal chemical wastewater purification. The mother liquor recycling technology enabled zero-emission utilization of solid waste resources and improved the utilization rate of alkali and template to 90%. These results demonstrate the potential application of the developed method in the efficient treatment of coal chemical wastewater. [ABSTRACT FROM AUTHOR]

Rough set theory is a mathematical tool widely employed in various fields to handle uncertainty. Feature selection, as an essential and independent research area within rough set theory, aims to identify a small subset of important features by eliminating irrelevant, redundant, or noisy ones. In human life, data characteristics constantly change over time and other factors, resulting in ordered datasets with varying features. However, existing feature extraction methods are not suitable for handling such datasets since they do not consider previous reduction results when features change and need to be recomputed, leading to significant time consumption. To address this issue, the incremental attribute reduction algorithm utilizes prior reduction results effectively reducing computation time. Motivated by this approach, this paper investigates incremental feature selection algorithms for ordered datasets with changing features. Firstly, we discuss the dominant matrix and the dominance conditional entropy while introducing update principles for the new dominant matrix and dominance diagonal matrix when features change. Subsequently, we propose two incremental feature selection algorithms for adding (IFS-A) or deleting (IFS-D) features in ordered data set. Additionally, nine UCI datasets are utilized to evaluate the performance of our proposed algorithm. The experimental results validate that the average classification accuracy of IFS-A and IFS-D under four classifiers on twelve datasets is 82.05% and 80.75%, which increases by 5.48% and 3.68% respectively compared with the original data. [ABSTRACT FROM AUTHOR]

The blue and white porcelain produced in Jingdezhen during China's Yuan Dynasty is an outstanding cultural heritage of ceramic art that has attracted wide attention for its identification. However, the traditional visual identification method is susceptible to misjudgment, thermoluminescence dating damages the samples, and the methods based on chemical analysis are limited by the accuracy and specificity of the elemental features. In this paper, we address the identification challenge by using machine learning techniques combined with portable X-ray Fluorescence Spectrometer (pXRF) analysis. We collect a large dataset of chemical compositions of Yuan blue and white porcelain from Jingdezhen using pXRF, and propose a graph anomaly detection method based on gradient attention map (GRAM) to identify the porcelain from different dynasties. We treat the porcelain produced in the Yuan dynasty as normal samples and those from other dynasties as abnormal samples. For GRAM, we merely train the variational graph autoencoder (VGAE) model with normal graphs and then use its encoder to extract graph features and compute the anomaly scores by utilizing the GRAM of the graph representations with respect to the node feature embeddings. Finally, we compare GRAM with state-of-the-art graph anomaly detection techniques and show that it achieves superior performance. [ABSTRACT FROM AUTHOR]

Glyphosate is a widely used active ingredient in agricultural herbicides, inhibiting the biosynthesis of aromatic amino acids in plants by targeting their shikimate pathway. Our gut microbiota also facilitates the shikimate pathway, making it a vulnerable target when encountering glyphosate. Dysbiosis in the gut microbiota may impair the gut–brain axis, bringing neurological outcomes. To evaluate the neurotoxicity and biochemical changes attributed to glyphosate, we exposed mice with the reference dose (RfD) set by the U.S. EPA (1.75 mg/Kg-BW/day) and its hundred-time-equivalence (175 mg/Kg-BW/day) chronically via drinking water, then compared a series of neurobehaviors and their fecal/serum metabolomic profile against the non-exposed vehicles (n = 10/dosing group). There was little alteration in the neurobehavior, including motor activities, social approach, and conditioned fear, under glyphosate exposure. Metabolomic differences attributed to glyphosate were observed in the feces, corresponding to 68 and 29 identified metabolites with dysregulation in the higher and lower dose groups, respectively, compared to the vehicle-control. There were less alterations observed in the serum metabolome. Under 175 mg/Kg-BW/day of glyphosate exposure, the aromatic amino acids (phenylalanine, tryptophan, and tyrosine) were reduced in the feces but not in the serum of mice. We further focused on how tryptophan metabolism was dysregulated based on the pathway analysis, and identified the indole-derivatives were more altered compared to the serotonin and kynurenine derivatives. Together, we obtained a three-dimensional data set that records neurobehavioral, fecal metabolic, and serum biomolecular dynamics caused by glyphosate exposure at two different doses. Our data showed that even under the high dose of glyphosate irrelevant to human exposure, there were little evidence that supported the impairment of the gut–brain axis. [ABSTRACT FROM AUTHOR]

The viscoelastic behavior in the frequency domain of crosslinked polystyrene (CPS) with two different degrees of crosslinking is characterized and modeled. A viscoelastic model from a relaxation perspective (VR model) was established considering different relaxation spectra. The relaxation spectrum is described by the distribution function of relaxation times in the VR model. The fitting quality of the VR model based on the distribution function corresponding to the Kohlrausch–Williams–Watts function is much higher than that of the conventional Zener model, but slightly lower than that of the fractional-derivative Kelvin–Voigt (FKV) model. The fitting quality of the VR model based on the distribution function corresponding to the Cole–Cole (CC) function is much better than that of the VR model with other distribution functions. This shows that the CC distribution function can better describe the relaxation spectrum of the CPS. Although the modulus expression of the Cole–Cole relaxation function is mathematically consistent with FKV, the VR model with the CC distribution function shows its superiority in having a definite physical meaning. The effect of the degree of crosslinking on the model parameters is analyzed. A higher equilibrium modulus, longer relaxation time, and narrower distribution of relaxation times are observed for CPS2.5 with a higher degree of crosslinking. The result shows that the viscoelastic behavior in the frequency domain of the crosslinked polymer can be well described through the VR model, which is applied by the distribution function of relaxation times. [ABSTRACT FROM AUTHOR]

The increasing cost of fishmeal (FM) with limited supply and the continuous development of aquaculture necessitate more economical FM substitutes. This study aimed to appraise the effects of dietary methanotroph (Methylococcus capsulatus, Bath) bacteria meal, a kind of methane-utilizing bacteria protein (MBP), replacing fishmeal on the growth and feed utilization, serum biochemical parameters, antioxidant status, and digestive enzyme activities of Pacific white shrimp (Litopenaeus vannamei). Seven isonitrogenous and isoenergetic diets were designed with 0%, 6.89%, 13.92%, 21.09%, 28.40%, 35.85%, and 43.46% MBP replacing FM, and fed to Pacific white shrimp (mean initial weight 0.27 ± 0.02 g) for 8 weeks. The shrimp fed with 28.40%, 35.85%, and 43.46% MBP diets showed significantly higher weight gain and specific growth rate compared to the control group (P < 0.05), while the other MBP diets had no significant effect on the growth performance (P > 0.05). No statistical differences were found in the activities of digestive enzymes in the stomach, hepatopancreas, and midgut among shrimp fed the dietary treatments (P > 0.05). Furthermore, antioxidant parameters in serum and hepatopancreas showed no significant differences among all the groups (P > 0.05). In conclusion, it was revealed that MBP replacing from 28.40 to 43.46% FM in the diet with appropriate supplementation of essential amino acids significantly improved the growth of Pacific white shrimp without adverse effects on feed utilization, digestive enzyme activities, physiological condition, and antioxidant status. This study provides a reference for replacing FM with MBP in the diet of Pacific white shrimp. [ABSTRACT FROM AUTHOR]

Interventions for extrinsic aging can be implemented, but these must address photoaging, which is the primary cause of extrinsic aging. Pigmentation due to photoaging depends on the duration and intensity of sun exposure. This study investigated the relationship between adipose-derived mesenchymal stem cells (ASCs) and photoaging pigmentation, and the underlying mechanism of action by establishing a photoaging pigmentation model using various treatments and exposure options in a guinea pigs. The energy dose of each UVB irradiation was 120 mJ/cm2 and the total dose of irradiation was 360 mJ/cm2. After successfully establishing the photoaging model, ASCs (1×106) in an balanced salt solution (0.9 ml), balanced salt solution (0.9 ml), and bFGF (9 μg) mixed with an balanced salt solution (0.9 ml) were injected intradermally in ten guinea pigs. ELISA, macroscopic skin and histological observations, and Masson–Fontana staining were done. At 2 and 4 weeks post-injection, noticeable changes were observed. Guinea pigs receiving ASCs injections displayed significantly lower visible skin scores while the melanin content continued to decrease. Somewhat improved histopathological morphology, including epidermal thinning, dermal thickening, and little inflammatory cell infiltration was observed immediately after and up to 4 weeks of ASCs injection. Melanocortin 1 receptor (MC1R) and alpha-melanocyte test hormone (alpha-MSH) levels reduced significantly, and basic fibroblast growth factor (bFGF) levels increased significantly immediately after and up to 4 weeks of ASCs injection. The MC1R and alpha-MSH levels reduced significantly immediately after and up to 4 weeks of bFGF injection. Briefly, intradermal ASCs injection can notably eliminate pigmentation in a guinea pig photoaging pigmentation model. This may be related to the fact that bFGF secreted by ASCs lowers MC1R and alpha-MSH levels, blocks the cAMP signalling pathway, and inhibits melanin synthesis. This finding may present new options for treating photoaging pigmentation. Level of Evidence: N/A. [ABSTRACT FROM AUTHOR]

Molecular-imprinted polymers (MIPs) are generally considered as substituents for natural antibodies. MIPs synthesis needs to select appropriate functional monomers. Because of its strong interaction with the template, antibody–antigen complexes can be formed before polymerization. In this paper, myoglobin (Mb)-imprinted polymers with a new sulphoxide monomer (2-(methylsulphonyl) ethyl acrylate, MSEA) as functional monomers were successfully prepared via electrochemically mediated atom transfer radical polymerization (eATRP). At the same time, to solve the problems of low selectivity and large template size limitations, the Mb-imprinted polymers were prepared on the surface of Au electrode decorated with three-dimensional foam graphene (FG) and nano Au (nAu). Cyclic voltammetry, electrochemical impedance spectroscopy, scanning electron microscope and X-ray photoelectron spectroscopy were used to characterize the Au electrode modified with Mb-imprinted polymer (Au/FG/nAu/MIPMSEA). The prepared Au/FG/nAu/MIPMSEA electrode was used as an electrochemical sensor to detect Mb. The results of experiments showed that the proposed biosensor had good selectivity, reproducibility, repeatability and stability. The linear response range was from 1.0 × 10−12 to 1.0 × 10−1 mg·l−1, and the detection limit was 1.21 × 10−13 mg·l−1 (S/N = 3). Compared with other methods for detecting Mb, the sensor had a wider detection range and lower detection limit. [ABSTRACT FROM AUTHOR]

Monoclonal antibodies targeting the programmed cell death-1/ programmed cell death-ligand 1 (PD-1/PD-L1) immune checkpoint have achieved enormous success in cancer immunotherapy. But the antibody-based immunotherapies carry a number of unavoidable deficiencies such as poor pharmacokinetic properties and immunogenicity. Small-molecule PD-1/PD-L1 inhibitors offer the superiority of complementarity with monoclonal antibodies and represent an appealing alternative. A novel series of isoxazole-containing biphenyl compounds were designed, synthesized and evaluated as PD-1/PD-L1 inhibitors in this paper. The structure–activity relationship of the novel synthesized compounds indicated that the ring-closure strategy of introducing isoxazole could be employed and the 3-cyanobenzyl group was significant for the inhibitory activity against the PD-1/PD-L1 protein–protein interactions. Molecular docking studies were performed to help understand the binding mode of the small-molecule inhibitor with the PD-L1 dimer. In particular, compound II-12 was a promising anti-PD-1/PD-L1 inhibitor with the IC50 value of 23.0 nM, providing valuable information for future drug development. [ABSTRACT FROM AUTHOR]

The development of the resistive switching cross-point array as the next-generation platform for high-density storage, in-memory computing and neuromorphic computing heavily relies on the improvement of the two component devices, volatile selector and nonvolatile memory, which have distinct operating current requirements. The perennial current-volatility dilemma that has been widely faced in various device implementations remains a major bottleneck. Here, we show that the device based on electrochemically active, low-thermal conductivity and low-melting temperature semiconducting tellurium filament can solve this dilemma, being able to function as either selector or memory in respective desired current ranges. Furthermore, we demonstrate one-selector-one-resistor behavior in a tandem of two identical Te-based devices, indicating the potential of Te-based device as a universal array building block. These nonconventional phenomena can be understood from a combination of unique electrical-thermal properties in Te. Preliminary device optimization efforts also indicate large and unique design space for Te-based resistive switching devices. Resistive switching devices have great promise for a wide variety of technological applications. Here, Yang et al demonstrate that electrochemically induced tellurium filament can give rise to resistive switching, and show that devices based on this can provide a number of advantages compared to metallic filament-based devices. [ABSTRACT FROM AUTHOR]

The mammalian gut harbors a complex and dynamic microbial ecosystem: the microbiota. While emerging studies support that microbiota regulates brain function with a few molecular cues suggested, the overall biochemical landscape of the "microbiota-gut-brain axis" remains largely unclear. Here we use high-coverage metabolomics to comparatively profile feces, blood sera, and cerebral cortical brain tissues of germ-free C57BL/6 mice and their age-matched conventionally raised counterparts. Results revealed for all three matrices metabolomic signatures owing to microbiota, yielding hundreds of identified metabolites including 533 altered for feces, 231 for sera, and 58 for brain with numerous significantly enriched pathways involving aromatic amino acids and neurotransmitters. Multicompartmental comparative analyses single out microbiota-derived metabolites potentially implicated in interorgan transport and the gut-brain axis, as exemplified by indoxyl sulfate and trimethylamine-N-oxide. Gender-specific characteristics of these landscapes are discussed. Our findings may be valuable for future research probing microbial influences on host metabolism and gut-brain communication. The gut microbiota harbours neuroactive potential with links to neurological disorders. Here, the authors apply global metabolomics with an integrated annotation strategy to comparatively profile fecal, blood serum and cerebral cortical brain tissues of eight-week-old germ-free mice vs. age-matched specific-pathogen-free mice, providing a snapshot of the metabolome status linked to the gut-brain axis. [ABSTRACT FROM AUTHOR]

Background: Early detection is critical in limiting the spread of 2019 novel coronavirus (COVID-19). Although previous data revealed characteristics of GI symptoms in COVID-19, for patients with only GI symptoms onset, their diagnostic process and potential transmission risk are still unclear. Methods: We retrospectively reviewed 205 COVID-19 cases from January 16 to March 30, 2020, in Renmin Hospital of Wuhan University. All patients were confirmed by virus nuclei acid tests. The clinical features and laboratory and chest tomographic (CT) data were recorded and analyzed. Results: A total of 171 patients with classic symptoms (group A) and 34 patients with only GI symptoms (group B) were included. In patients with classical COVID-19 symptoms, GI symptoms occurred more frequently in severe cases compared to non-severe cases (20/43 vs. 91/128, respectively, p < 0.05). In group B, 91.2% (31/34) patients were non-severe, while 73.5% (25/34) patients had obvious infiltrates in their first CT scans. Compared to group A, group B patients had a prolonged time to clinic services (5.0 days vs. 2.6 days, p < 0.01) and a longer time to a positive viral swab normalized to the time of admission (6.9 days vs. 3.3 days, respectively, p < 0.01). Two patients in group B had family clusters of SARS-CoV-2 infection. Conclusion: Patients with only GI symptoms of COVID-19 may take a longer time to present to healthcare services and receive a confirmed diagnosis. In areas where infection is rampant, physicians must remain vigilant of patients presenting with acute gastrointestinal symptoms and should do appropriate personal protective equipment. [ABSTRACT FROM AUTHOR]

Objective: Breast cancer (BC) is the most common type of malignant tumor and the most common cause of cancer-related mortality among women. Metabolic reprogramming is considered a hallmark of cancer, and the study of BC metabolism may be the key to the development of new strategies for diagnosis and treatment. In this study, we aimed to explore the potential metabolites and gene biomarkers for BC through the integration of metabolomics and transcriptomic data, which could further understand BC tumor biology.Methods: Transcriptome dataset GSE139038 was downloaded to explore the differentially expressed genes (DEGs) between BC and normal control (NC) samples. Metabolomics dataset MTBLS326 was downloaded and preprocessed to obtain altered metabolites. Then, the principal component analysis (PCA) and linear models were used to reveal DEGs-metabolites relations. Finally, the pathway enrichment analysis of altered metabolites was performed.Results: A total of 280 DEGs and eight metabolites were explored between BC and NC samples. The liner module analysis investigated 28 DEGs-metabolites interactions including WASP family member 3 (WASF3)-lactate, ras-related protein Rab-7B (RAB7B)-lactate, and methyltransferase-like 7A (METTL7A)-pyruvate. Finally, pathways analysis showed that these metabolites (such as lactate and pyruvate) were mainly enriched in pathways like disorders of the Krebs cycle.Conclusions: Combining with the transcriptomic and metabolomics data, we found that lactate, pyruvate, WASF3, RAB7B, and METTL7A might be used as novel biomarkers and potential therapeutic targets for BC. In addition, the disorders of the Krebs cycle pathway might affect the progression of BC. [ABSTRACT FROM AUTHOR]

Hemoglobin (Hb)-imprinted poly(ionic liquid)s (HIPILs) were prepared on the surface of Au electrode modified with gold nanodendrites (Au/ND/HIPILs). HIPILs were synthesized with 1-vinyl-3-propyl imidazole sulfonate ionic liquids as functional monomers via electrochemically mediated atom transfer radical polymerization (eATRP) catalyzed by Hb. The Au/ND/HIPILs electrode was examined by cyclic voltammetry (CV), scanning electron microscope (SEM), and X-ray photoelectron spectroscopy (XPS). The Au/ND/HIPILs electrode was also used as an electrochemical sensor to determine Hb by differential pulse voltammetry (DPV). Under the optimal conditions, the detection range of Hb was from 1.0 × 10−14 to 1.0 × 10−4 mg/mL with a limit of detection of 5.22 × 10−15 mg/mL (S/N = 3). Compared with other methods, the sensor based on poly(ionic liquid)s had the broader linear range and lower detection limit. [ABSTRACT FROM AUTHOR]

In this study, we propose a novel approach to balance exploitation and exploration. The proposed approach is the Evolutionary Swarm Intelligence (ESI) optimizer, which combines an exploration-biased strategy with an exploitation-biased operator. The algorithm is built based on the collective behavior of biological groups, imitating their intelligence behavior. The biological evolutionary process, inspired by genetic algorithms, is applied to every individual in the algorithm. Both swarm intelligence and genetic algorithms have been widely used in practical problems, and their reliability has been proven. ESI is characterized by both spatial group intelligence behavior and temporal biological evolution. To test the performance of ESI, we used a classic test set from IEEE CEC2017 and 22 practical problems from IEEE CEC2011. The popular training tests of the dendritic neuron model were also included in the control trials. We compared ESI with some typical swarm intelligence algorithms and classic algorithms to evaluate its performance and ability to solve practical problems. The experimental results show that ESI outperforms other algorithms in terms of basic performance and the ability to solve practical problems. [ABSTRACT FROM AUTHOR]

Nesfatin-1 is a hypothalamic anorexigenic peptide processed from nucleobindin 2 (NUCB2). Central and peripheral administration of NUCB2/nesfatin-1 enhances glucose metabolism and insulin release. NUCB2/nesfatin-1 is also localized in pancreatic islets, while its function remains unknown. To explore the role of pancreatic β-cell-produced NUCB2/nesfatin-1, we developed pancreatic β-cell-specific NUCB2 knockout (βNUCB2 KO) mice and NUCB2 gene knockdown (shNUCB2) MIN6 β-cell line. In βNUCB2 KO mice, casual blood glucose was elevated from 12 weeks of age. In a glucose tolerance test at 12 weeks, insulin secretion at 15 min was reduced and blood glucose at 2 h increased in βNUCB2 KO mice fasted 8 h. In islets isolated from βNUCB2 KO mice, high glucose-stimulated insulin secretion (GSIS) was impaired. In shNUCB2 MIN6 cells, GSIS was reduced and UCP-2 mRNA expression was elevated. These results show impaired GSIS possibly associated with UCP-2 overexpression in NUCB2-silenced β-cells, suggesting that β-cell-produced NUCB2/nesfatin-1 maintains GSIS and thereby glycemia. [ABSTRACT FROM AUTHOR]

Erythromycin (ERY) molecular imprinted polymer was prepared on the surface of Au electrode modified with Ni and Au nanoclusters (MIP/AuNCs/Ni/Au) via metal-free visible-light-induced atom transfer radical polymerization, which was very easy, controllable, and environmentally benign. MIP/AuNCs/Ni/Au was examined by energy dispersive spectrometer (EDS), scanning electron microscope (SEM), cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS). Further, MIP/AuNCs/Ni/Au was successfully used for the determination of ERY by differential pulse voltammetry (DPV). Under the optimal conditions, MIP/AuNCs/Ni/Au gave a linear correlation over the ERY concentration from 1.0 × 10−8 to 1.0 × 10−1 mg/L with the detection limit of 3.2 × 10−9 mg/L (S/N = 3). Comparing with the similar sensors, the larger linear range and lower detection limit indicated the promising prospect of this electrochemical sensor. Hence, this study was of great importance for the polymer-modified electrodes and the sensitive detection of ERY. [ABSTRACT FROM AUTHOR]

An adaptive dynamic surface control (DSC) scheme is proposed for the multi-input multi-output attitude control of near-space hypersonic vehicles (NHV). The proposed control strategy can improve the control performance of NHV despite uncertainties and external disturbances. The proposed controller combines dynamic surface control and radial basis function neural network (RBFNN) and is designed to control the longitudinal dynamics of NHV. The DSC technique is used to handle the problem of “explosion of complexity” inherent to the conventional backstepping method. RBFNN is used to approximate the unknown nonlinear function, and a robustness component is introduced in the controller to cancel the influence of compound disturbance and improve robustness and adaptation of the system. Simulation results show that the proposed strategy possesses good robustness and fast response. [ABSTRACT FROM AUTHOR]

Mitogen-activated protein kinase/mitogen-activated protein kinase kinase1 plays a key role in the Ras/Raf/MEK/ERK signaling pathway associated with cell growth, differentiation and development. In an effort to identify novel mitogen-activated protein kinase kinase1 inhibitors, an efficient multistep virtual screening approach was presented, including ligand-based pharmacophore (Hypo1) screening, physicochemical property filtering, and validated optimal docking analysis. Finally, six compounds were purchased and tested for their inhibitory activities in kinetics studies and cellular assays. Among them, compound M4 exhibited potent inhibition against mitogen-activated protein kinase kinase1 (IC = 3.5 μM) and modest proliferation inhibition in human HT-29 colon tumor line (IC = 13.6 μM) and human melanoma A375 cell line (IC = 16.2 μM). Taken together, our virtual screening might be useful for the mitogen-activated protein kinase kinase1 inhibitor research and M4 represents a new scaffold deserving further structural optimization for the treatment of mitogen-activated protein kinase kinase1-associated cancers. Graphical Abstract: A ligand-based pharmacophore of MEK1 inhibitors was constructed and validated, then used to screen the SPECS compound library combined with optimal molecular docking (Glide XP), followed by biochemical and cellular assays. [ABSTRACT FROM AUTHOR]

Bromodomain-containing protein is involved in many essential cellular processes, such as chromosomes for cell cycle progression, cellular viability and embryonic stem cell regulation, which plays a significant role in cancers and lysine acetylation. However, there is no information available regarding the discovery for structurally novel existing BRD4(1) inhibitors up to date. Therefore, we collected reported compounds from GSK library to generate ligand-based pharmacophore and used 11 BRD4(1)-inhibitor co-crystal structures to establish our structure-based pharmacophore for multiple virtual screening of potent BRD4(1) inhibitors. These results may provide important information for further design and optimization of novel BRD4(1) inhibitors in cancer treatment. The results of this study will not only provide a better understanding of BRD4(1) inhibitors interaction, but will also assist the development of new potent hits for BRD4(1). [ABSTRACT FROM AUTHOR]

Highly dispersed cobalt nanoparticles were incorporated into the ordered mesoporous carbon (OMC) via the ultrasonically assisted vacuum-pressure impregnation (UAVI) for CO hydrogenation. The as-synthesized samples were subjected to the characterization of N physisorption, HAADF-STEM, XRD, XPS, magnetic measurement, H chemisorption and Co zero field spin-echo NMR. It is found that the cobalt particles are exclusively distributed into the channels of OMC and the rigid frameworks significantly bridle the growth of active species to obtain ultrafine cobalt particles with size less than 4 nm. The highly dispersed cobalt nanoparticles perform superior catalytic performances during the CO hydrogenation as compared to the catalyst prepared by the conventional impregnation. The observed stability of novel catalysts outperforms the conventional one during the 96 h evaluation on stream due to the confinement effect to the sintering and conglomeration of active species. On the other hand, a typical structural sensitivity is also observed for the highly dispersed catalysts and the coordinative-unsaturated disordered stacking of cobalt atoms renders higher efficiency to improve CO turnover frequency. Besides, a high selectivity to mixed alcohols is also obtained for the highly dispersed catalysts and the yields of methane and methanol decrease gradually with increasing the particle size. Unfortunately, the highly dispersed particles also display a relatively high selectivity to CO. Graphical Abstract: Highly dispersed cobalt nanoparticles with size less than 4 nm were exclusively incorporated into the ordered mesoporous carbon by ultrasonically assisted vacuum-pressure impregnation. The high-surface-area and chemical inertness of carbonaceous substrates enable the ultrafine particles to outperform during CO hydrogenation.[Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Ordered mesoporous carbon supported cobalt-based catalysts (Co/MC) were synthesized via incipient wetness impregnation with different amounts of furfuryl alcohol (FA) as carbon precursor. The characterizations of obtained Co/MC were subjected to N adsorption, XRD, XPS, TEM, H-TPR, H-TPD and H-TPSR. The results indicate that the reducibility and dispersion of Co active species vary significantly due to the difference of FA amount. By simply tuning the FA content from 25 to 100 wt%, the reduction temperature of deriving metallic Co shifts gradually to lower. The catalytic performance of Co/MC was evaluated for Fischer-Tropsch (FT) synthesis. The observed FT activity exhibits a volcano-type curve with the amount of FA due to the effect of both reducibility and dispersion of active species. As the precursor concentration overweighs 50 wt%, the ability of CO to dissociate over the active surface and the selectivity to the C products level off after experiencing an initial increase. Substantially, the catalysts with higher concentration of FA render the larger crystallites having an average size of more than 6 nm, which facilitates the CO hydrogenation by way of carbon chain propagation. It seems that the sample with FA content of 50 wt% is optimum in terms of FT activity and C selectivity. Graphical Abstract: By simply tuning the carbon precursor furfuryl alcohol (FA) content from 25 to 100 wt%, the textural property of mesoporous carbon varies significantly, which further induces the different reducibility and dispersion of Co active species and the temperature of deriving metallic Co shifts gradually to lower. The catalytic performance of as-synthesized catalysts was evaluated for Fischer-Tropsch synthesis (FTS). The observed FT activity exhibits a volcano-type curve with the amount of FA due to the effect of both reducibility and dispersion of active species. At the FA concentration of support over 50 wt%, the selectivity to the C heavy molecular maintain invariant after experiencing an initial increase. It seems that the sample with respect to 50 wt% FA is optimum in terms of FT activity and C selectivity.[Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

The research focuses on the long-term sustainable monitoring of Terrestrial Water Storage Anomalies (TWSA), which is crucial for understanding water cycle processes and efficient regional water resource management. To address data gaps during the operation of GRACE (Gravity Recovery and Climate Experiment) and GRACE-FO (Follow-On) satellites, the research introduces a combined model of Bidirectional Long Short-Term Memory neural network (Bi-LSTM) with X-11 for rolling prediction of TWSA through the inversion of GRACE spherical harmonic coefficients. To assess the applicability of the combined model in various basins, we use TWSA data from January 2003 to December 2014 as training set, with TWSA data from January 2015 to December 2016 as a reference, and the missing month data in GRACE observations are filled using cubic spline interpolation. We compare the performance of the Autoregressive Integrated Moving Average (ARIMA) model, Long Short-Term Memory neural network (LSTM), Bi-LSTM, and the combined Bi-LSTM with X-11 model for model training and rolling prediction. Evaluation metrics include Root Mean Square Error (RMSE), standardized RMSE (R*), Pearson correlation coefficient (P), and Nash-Sutcliffe Efficiency coefficient (NSE). Results indicate that all four methods perform well in regions with strong periodicity. Among them, the Bi-LSTM with X-11 combined model shows the highest prediction accuracy and good generalization. In the Amazon River basin, the combined model achieves an RMSE of 4.7 cm, R*, of 0.305, P of 97.6%, and NSE of 0.903. For grid-scale predictions in large regions, the research focuses on Greenland and the Yangtze River basin. The Bi-LSTM with X-11 combined model significantly improves spatial smoothness and accuracy compared to Bi-LSTM, LSTM, and ARIMA in both regions. The average RMSE values for the combined model in Greenland and the Yangtze River basin are 3.1 cm and 4.4 cm, respectively. The combined model’s predicted TWSA demonstrates good correlation and NSE performance, outperforming the other three models in both regions, where their RMSE values exceed 4.1 cm and 6.3 cm. To sum up, the research suggests that the Bi-LSTM with X-11 combined model is effective for reconstructing TWSA during the data gaps in GRACE spherical harmonic coefficients. Additionally, this method can be used for effective recursive prediction of TWSA. [ABSTRACT FROM AUTHOR]