Highly Sensitive Electrochemical Immunosensor Based on Mesoporous PdPt Nanoparticles Anchored on a Three-dimensional PANI@CNTs Network as Nanozyme Labels

In this study, a novel strategy to amplify electrochemical signals by mesoporous PdPt nanoparticles with core-shell structures anchored on a three-dimensional PANI@CNTs network as nanozyme labels (PdPt/PANI@CNTs) was proposed for the sensitive monitoring of α-fetoprotein (AFP, Ag). First, the mesoporous PdPt nanoparticles prepared by a facile chemical reduction method had excellent biocompatibility with biomolecules, which could capture a large amount of AFP-Ab₂ (Ab₂) and exhibit plentiful pores to entrap more thionine (Thi) into mesoporous PdPt nanoparticles with enhanced loading and abundant active sites. Furthermore, the resulting mesoporous PdPt nanoparticles were abundantly dotted on the surface of a three-dimensional PANI@CNTs network with excellent conductivity and a high specific surface area through the bonding of the amino group to form PdPt/PANI@CNTs nanozyme labels. Most importantly, the as-prepared PdPt/PANI@CNTs nanozyme labels exhibited unexpected enzyme-like activity towards the reduction of hydrogen peroxide owing to the highly indexed facets, enhancing the current response to realize signal amplification. In view of the advantages of nanozyme labels and the involvement of gold nanoparticles (AuNPs, which behave as electrode materials) for the sensitive determination of AFP, the as-developed immunosensor could obtain a dynamic working range of 0.001 ng mL^−1–100.0 ng mL⁻¹ at a detection limit of 0.33 pg mL⁻¹ via DPV (at 3σ). Furthermore, the nanozyme-based electrochemical immunosensor exhibited remarkable analytical performance, which brought about feasible ideas for disease diagnosis in the future.     

Biomarkers based on multiplatform comprehensive analysis: A systematic analysis of Geng-Nian-Shu in perimenopausal syndrome

Although Geng-Nian-Shu has been shown to be clinically effective in perimenopausal syndrome, its active components and mechanism have not yet been elucidated. To demonstrate the mechanism-based biomarkers of Geng-Nian-Shu in treating perimenopausal syndrome, a total of 135 chemical constituents including 52 prototype blood constituents were identified via high-performance liquid chromatography-quadrupole-time of flight/mass spectrometry. Then, network pharmacology showed significant enrichment for the PhosphoInositide-3 Kinase/Akt pathway, suggesting that it may be the main regulatory pathway for the Geng-Nian-Shu treatment of the perimenopausal syndrome. Subsequently, multivariate analysis was performed between the Geng-Nian-Shu sham-treated and Geng-Nian-Shu ovariectomy-treated groups and further screened out 18 prototype blood constituents by correlation analysis with plasma estrogen levels to identify potential biomarkers associated with Geng-Nian-Shu treat the ovariectomy-induced perimenopausal syndrome. Finally, the results of pharmacological experimental verification and Pearson correlation analysis indicated that catalpol, ligustilide, paeoniflorin, and gallic acid were selected as biomarkers of Geng-Nian-Shu which were strongly and positively correlated with PhosphoInositide-3 Kinase/Akt signaling pathway. In this study, based on high-performance liquid chromatography-quadrupole-time of flight/mass spectrometry combined with pharmacodynamics, network pharmacology, pharmacology, and other disciplines, we explored the effects and mechanisms of Geng-Nian-Shu in the treatment of perimenopausal syndrome at multiple levels. Using multiplatform technology to investigate the role of Geng-Nian-Shu represents a new strategy for the selection and verification of biomarkers of Geng-Nian-Shu and provides a basis for further development and utilization of Geng-Nian-Shu.     

Electrical Stimulation of Human Mesenchymal Stem Cells on Conductive Substrates Promotes Neural Priming

Electrical stimulation (ES) within a conductive scaffold is potentially beneficial in encouraging the differentiation of stem cells toward a neuronal phenotype. To improve stem cell-based regenerative therapies, it is essential to use electroconductive scaffolds with appropriate stiffnesses to regulate the amount and location of ES delivery. Herein, biodegradable electroconductive substrates with different stiffnesses are fabricated from chitosan-grafted-polyaniline (CS-g-PANI) copolymers. Human mesenchymal stem cells (hMSCs) cultured on soft conductive scaffolds show a morphological change with significant filopodial elongation after electrically stimulated culture along with upregulation of neuronal markers and downregulation of glial markers. Compared to stiff conductive scaffolds and non-conductive CS scaffolds, soft conductive CS-g-PANI scaffolds promote increased expression of microtubule-associated protein 2 (MAP2) and neurofilament heavy chain (NF-H) after application of ES. At the same time, there is a decrease in the expression of the glial markers glial fibrillary acidic protein (GFAP) and vimentin after ES. Furthermore, the elevation of intracellular calcium [Ca²⁺] during spontaneous, cell-generated Ca²⁺ transients further suggests that electric field stimulation of hMSCs cultured on conductive substrates can promote a neural-like phenotype. The findings suggest that the combination of the soft conductive CS-g-PANI substrate and ES is a promising new tool for enhancing neuronal tissue engineering outcomes.     

基于LSTM的浮选钼精矿品位软测量模型

战略性稀有金属钼矿品位低,组分复杂、嵌布粒度细等特点,其有价金属分离回收难。浮选作为微细粒钼矿分离回收的主要选矿方法之一,其浮选钼精矿品位一直是选厂的关键性产品指标。国内大多数选厂采取轮班制采样,人工化验得到精矿品位结果,但此方式严重滞后于浮选工艺,难以满足对生产过程进行实时监测和操作指导。LSTM是一种特殊的循环神经网络,引入门机制有效的传递或选择性遗忘长时间序列中的信息,解决RNN中的长期依赖、梯度消失和爆炸问题。本文分析整理东坡选厂中各平台源数据,结合选厂浮选工艺及机理,筛选出多个影响浮选钼精矿品位的变量作为模型输入;将输入变量进行异常值判定,缺失值填充和数据降噪等数据预处理,建立高质量浮选钼精矿品位数据库;软测量模型采用PyCharm软件编码,使用BatchNorm批量规范化处理样本数据,加入Dropout正则化防止过拟合,建立基于LSTM的浮选钼精矿品位软测量模型,通过前向传播算法更新神经网络结构参数,并于Linear模型和CNN模型的预测性能指标结果比较。结果表明：基于LSTM的浮选钼精矿品位软测量模型预测准确度高,样本数据误差波动平稳,浮动范围小,模型泛化能力强,模型平均绝对百分比误差MAPE为1.13%,均方根误差RMSE为0.7049%,决定系数R2为0.8763,实现了浮选钼精矿品位的在线预测。     

A way of constructing translation network operators by Bernstein operators

In the present paper,we provide a way of constructing translation network operators by Bernstein-Durrmeyer operators.     

含有五个反馈权值的二维细胞神经网络可实现Mosaic模式

研究一类含有五个反馈权值二维细胞神经网络系统,以系统的输出反馈权值及阈值为参数构成参数空间,引入几何方法,将此空间分解分块成有限个区域,当输出反馈权值及阈值在某一区域上时,给出系统具有M osaic解所有可能的输出函数M osaic模式的充要条件.     

稀土萃取分离过程软测量方法的研究

分析了稀土组分含量在线检测技术进展缓慢的原因,分析了稀土萃取分离过程机制,找出影响稀土组分含量检测的主要因素,确定辅助变量。利用从包钢稀土厂采集的数据通过newrb函数创建径向基网络来实现稀土组分含量的软测量。文中通过流程图详细阐述了建模方法,采用50组样本数据对所建立的模型进行计算机仿真验证,仿真结果证明了模型的可行性。     

Simultaneous Titration of Ternary Mixtures of Pb(II), Cd(II) and Cu(II) with Potentiometric Electronic Tongue Detection

An automatic titration method is reported to resolve ternary mixtures of transition metals (Pb²⁺, Cd²⁺ and Cu²⁺) employing electronic tongue detection and a reduced number of pre‐defined additions of EDTA titrant. Sensors used were PVC membrane selective electrodes with generic response to heavy‐metals, plus an artificial neural network response model. Detection limits obtained were ca. 1 mg L^?1 for the three target ions and reproducibilities 3.0 % for Pb²⁺, 4.1 % for Cd²⁺ and 5.2 % for Cu²⁺. The system was applied to contaminated soil samples and high accuracy was obtained for the determination of Pb²⁺. In the determination Cd²⁺ and Cu²⁺, sample matrix showed a significant effect.     

Development of models for prediction of the antioxidant activity of derivatives of natural compounds

Antioxidants are important for maintaining the appropriate balance between oxidizing and reducing species in the body and thus preventing oxidative stress. Many natural compounds are being screened for their possible antioxidant activity. It was found that a mushroom pigment Norbadione A, which is a pulvinic acid derivative, shows an antioxidant activity; the same was found for other pulvinic acid derivatives and structurally related coumarines. Based on the results of in vitro studies performed on these compounds as a part of this study quantitative structure–activity relationship (QSAR) predictive models were constructed using multiple linear regression, counter-propagation artificial neural networks and support vector regression (SVR). The models have been developed in accordance with current QSAR guidelines, including the assessment of the models applicability domains. A new approach for the graphical evaluation of the applicability domain for SVR models is suggested. The developed models show sufficient predictive abilities for the screening of virtual libraries for new potential antioxidants.     

Selective Template Removal by Thermal Depolymerization to Obtain Mesostructured Molybdenum Oxycarbide

The carbon content of mesostructured organic‐inorganic hybrid material of a cylindrical block copolymer template of poly(2‐vinylpyridine)‐block‐poly(allyl methacrylate) (P2VP‐b‐PAMA) and ammonium paramolybdate (APM) could be reduced by thermal depolymerization. By calcination in vacuo at 320 °C the PAMA core can be completely removed while the remaining P2VP brush preserves the mesostructure. The P2VP‐APM composite can then be carburized in‐situ to MoO_xC_y in a second pyrolysis step without any additional carbon source but P2VP. The molybdenum oxycarbide nanotubes obtained, form hierarchically porous non‐woven structures, which were tested as catalyst in the decomposition of NH₃. They proved to be catalytically active at temperatures above 450 °C. The activation energy was estimated from an Arrhenius Plot to be 127 kJ · mol^–1.