DMF体系中Cu2O球晶的制备及形貌分析

以N,N-二甲基甲酰胺(DMF)为溶剂,通过改变铜源和表面活性剂,调控反应参数,溶剂热条件下制备了三维十字形、空心及实心的Cu₂O球晶。利用XRD、SEM等表征手段,分析探讨了工艺条件变化对Cu₂O球晶形貌的影响。研究表明,随着DMF浓度的增大,体系的还原能力增强,Cu⁺增多,溶液的过饱和度增大,Cu₂O晶体集合体形态由晶体结构控制的各向异性与对称性的球晶逐渐向各向同性球晶演变。十二烷基硫酸钠(SDS)、十六烷基三甲基溴化铵(CTAB)、聚乙烯吡咯烷酮(PVP)等表面活性剂有助于降低溶液的过饱和度,增加结晶质的表面扩散能力,有利于规则形态Cu₂O晶粒的形成。反应体系中,Cu(Ac)₂·H₂O水解生成的羧基与DMF中的甲酰基在高温下发生脱羧反应产生CO₂气体以及SDS发泡作用产生的气体是形成空心Cu₂O球晶的重要原因。     

Facile Synthesis of Porous Ag Crystals as SERS Sensor for Detection of Five Methamphetamine Analogs

Porous noble metal nanomaterials have attracted extensive attention due to their high specific surface area and surface plasmon resonance effect. However, it is difficult to form porous structures due to the high mobility and low reduction potential of noble metal precursors. In this article, we developed a facile method for preparing porous Ag with a controllable structure at room temperature. Two kinds of Ag crystals with different porous structures were successfully prepared by using AgCl cubes as sacrificial templates. Through the galvanic replacement reaction of Zn and AgCl, Ag crystals with a sponge-like porous structure were successfully prepared. Additionally, using NaBH₄ as the reducing agent, we prepared granular porous Ag cubes by optimizing the amount of reducing agent. Both the sponge-like and granular porous Ag cubes have clean and accessible surfaces. In addition, we used the prepared two porous Ag cubes as substrate materials for SERS detection of five kinds of methamphetamine analogs. The experimental results show that the enhancement effect of granular porous Ag is better than that of sponge-like porous Ag. Furthermore, we probed the hot spot distribution of granular porous Ag by Raman mapping. By using granular porous Ag as the substrate material, we have achieved trace detection of 5 kinds of methamphetamine analogs including Ephedrine, Amphetamine, N-Methyl-1-(benzofuran-5-yl)propan-2-amine (5-MAPB), N-Methyl-1-(4-methoxyphenyl)propan-2-amine (PMMA) and N-Methyl-1-(4-fluorophenyl)propan-2-amine (4-FMA). Furthermore, to achieve qualitative differentiation of analogs with similar structures we performed density functional theoretical (DFT) calculations on the Raman spectra of the above analogs. The DFT calculations provided the vibrational frequencies, Raman activities, and normal mode assignment for each analog, enabling the qualitative differentiation of the above analogs.     

DNA Interaction,DNA Photocleavage,Photocytotoxicity In Vitro,and Molecular Docking of Naphthyl-Appended Ruthenium Complexes

With the development of metal-based drugs, Ru(II) compounds present potential applications of PDT (photodynamic therapy) and anticancer reagents. We herein synthesized two naphthyl-appended ruthenium complexes by the combination of the ligand with naphthyl and bipyridyl. The DNA affinities, photocleavage abilities, and photocytotoxicity were studied by various spectral methods, viscosity measurement, theoretical computation method, gel electrophoresis, and MTT method. Two complexes exhibited strong interaction with calf thymus DNA by intercalation. Production of singlet oxygen (¹O₂) led to obvious DNA photocleavage activities of two complexes under 365 nm light. Furthermore, two complexes displayed obvious photocytotoxicity and low dark cytotoxicity towards Hela, A549, and A375 cells.     

The Intervention of Prebiotics on Depression via the Gut–Brain Axis

The imbalance of intestinal microbiota can cause the accumulation of endotoxin in the main circulation system of the human body, which has a great impact on human health. Increased work and life pressure have led to a rise in the number of people falling into depression, which has also reduced their quality of life. The gut–brain axis (GBA) is closely related to the pathological basis of depression, and intestinal microbiota can improve depressive symptoms through GBA. Previous studies have proven that prebiotics can modulate intestinal microbiota and thus participate in human health regulation. We reviewed the regulatory mechanism of intestinal microbiota on depression through GBA, and discussed the effects of prebiotics, including plant polysaccharides and polyphenols on the regulation of intestinal microbiota, providing new clues for the prevention and treatment of depression.     

Prisoner’s Dilemma Game with Cooperation-Defection Dominance Strategies on Correlational Multilayer Networks

As multilayer networks are widely applied in modern society, numerous studies have shown the impact of a multilayer network structure and the network nature on the proportion of cooperators in the network. In this paper, we use Barabási–Albert scale-free networks (BA) and Watts and Strogatz networks (WS) to build a multilayer network structure, and we propose a new strategy-updating rule called “cooperation-defection dominance”, which can be likened to dominant and recessive traits in biogenetics. With the newly constructed multilayer network structure and the strategy-updating rules, based on the simulation results, we find that in the BA-BA network, the cooperation dominance strategy can make the networks with different rs show a cooperative trend, while the defection dominance strategy only has an obvious effect on the network cooperation with a larger r. When the BA network is connected to the WS network, we find that the effect of strategy on the proportion of cooperators in the network decreases, and the main influencing factor is the structure of the network. In the three-layer network, the cooperation dominance strategy has a greater impact on the BA network, and the proportion of the cooperators is enhanced more than under the natural evolution strategy, but the promotion effect is still smaller than that of the two-layer BA network because of the WS network. Under the defection dominance strategy, the WS layer appears different from the first two strategies, and we conclude through simulation that when the payoff parameter is at the middle level, its cooperator proportion will be suppressed, and we deduce that the proportion of cooperators and defectors, as well as the payoff, play an important role.     

Synthesis,Characterization and Application of Amine-Functionalized Hierarchically Micro-Mesoporous Silicon Composites for CO2 Capture in Flue Gas

An efficient CO₂ adsorbent with a hierarchically micro-mesoporous structure and a large number of amine groups was fabricated by a two-step synthesis technique. Its structural properties, surface groups, thermal stability and CO₂ adsorption performance were fully investigated. The analysis results show that the prepared CO₂ adsorbent has a specific hierarchically micro-mesoporous structure and highly uniformly dispersed amine groups that are favorable for the adsorption of CO₂. At the same time, the CO₂ adsorption capacity of the prepared adsorbent can reach a maximum of 3.32 mmol-CO₂/g-adsorbent in the actual flue gas temperature range of 303–343 K. In addition, the kinetic analysis results indicate that both the adsorption process and the desorption process have rapid adsorption/desorption rates. Finally, the fitting of the CO₂ adsorption/desorption experimental data by Avrami’s fractional kinetic model shows that the CO₂ adsorption rate is mainly controlled by the intra-particle diffusion rate, and the temperature has little effect on the adsorption rate.     

A List-Ranking Framework Based on Linear and Non-Linear Fusion for Recommendation from Implicit Feedback

Although most list-ranking frameworks are based on multilayer perceptrons (MLP), they still face limitations within the method itself in the field of recommender systems in two respects: (1) MLP suffer from overfitting when dealing with sparse vectors. At the same time, the model itself tends to learn in-depth features of user–item interaction behavior but ignores some low-rank and shallow information present in the matrix. (2) Existing ranking methods cannot effectively deal with the problem of ranking between items with the same rating value and the problem of inconsistent independence in reality. We propose a list ranking framework based on linear and non-linear fusion for recommendation from implicit feedback, named RBLF. First, the model uses dense vectors to represent users and items through one-hot encoding and embedding. Second, to jointly learn shallow and deep user–item interaction, we use the interaction grabbing layer to capture the user–item interaction behavior through dense vectors of users and items. Finally, RBLF uses the Bayesian collaborative ranking to better fit the characteristics of implicit feedback. Eventually, the experiments show that the performance of RBLF obtains a significant improvement.     

Improved Stretchable and Sensitive Fe Nanowire-Based Strain Sensor by Optimizing Areal Density of Nanowire Network

Flexible strain sensors, when considering high sensitivity and a large strain range, have become a key requirement for current robotic applications. However, it is still a thorny issue to take both factors into consideration at the same time. Here, we report a sandwich-structured strain sensor based on Fe nanowires (Fe NWs) that has a high GF (37–53) while taking into account a large strain range (15–57.5%), low hysteresis (2.45%), stability, and low cost with an areal density of Fe NWs of 4.4 mg/cm². Additionally, the relationship between the contact point of the conductive network, the output resistance, and the areal density of the sensing unit is analyzed. Microscopically, the contact points of the conductive network directly affect the sensor output resistance distribution, thereby affecting the gauge factor (GF) of the sensor. Macroscopically, the areal density and the output resistivity of the strain sensor have the opposite percolation theory, which affects its linearity performance. At the same time, there is a positive correlation between the areal density and the contact point: when the stretching amount is constant, it theoretically shows that the areal density affects the GF. When the areal density reaches this percolation threshold range, the sensing performance is the best. This will lay the foundation for rapid applications in wearable robots.     

Spiking patterns of a hippocampus model in electric fields

We develop a model of CA3 neurons embedded in a resistive array to mimic the effects of electric fields from a new perspective. Effects of DC and sinusoidal electric fields on firing patterns in CA3 neurons are investigated in this study. The firing patterns can be switched from no firing pattern to burst or from burst to fast periodic firing pattern with the increase of DC electric field intensity. It is also found that the firing activities are sensitive to the frequency and amplitude of the sinusoidal electric field. Different phase-locking states and chaotic firing regions are observed in the parameter space of frequency and amplitude. These findings are qualitatively in accordance with the results of relevant experimental and numerical studies. It is implied that the external or endogenous electric field can modulate the neural code in the brain. Furthermore, it is helpful to develop control strategies based on electric fields to control neural diseases such as epilepsy.     

Rapid Detection of Five Estrogens Added Illegally to Dietary Supplements by Combining TLC with Raman Imaging Microscope

Estrogens added illegally to dietary supplements are hazardous to human health. Traditional detection and analysis methods have many limitations, and we have developed an assay that combines thin-layer chromatography with Raman imaging microscopy (TLC-RIM). The five estrogens (estrone, estradiol, estriol, ethinyl estradiol, and diethylstilbestrol) were initially separated by TLC, then detected by area scanning Raman imaging with a 532 nm laser under a microscope. Raman spectra were obtained for each estrogen, which were used for detecting estrogen illegally added to botanical dietary supplements. The LOD of each estrogen was 0.4, 1.0, 0.8, 0.2, and 0.2 mg/mL, respectively. The matrix in the real sample did not interfere with the detection of estrogens. The method was fast, sensitive, stable, specific, and reliable.