Friend Emotional Support and Dynamics of Adolescent Socioemotional Problems.

Emotional support from friends is a crucial source of social support for adolescents, significantly influencing their psychological development. However, previous research has primarily focused on how this support correlates with general levels of socioemotional problems among adolescents, neglecting the significance of daily fluctuations in these problems. The aim of this study was to explore the relationship between friend emotional support and both the average and dynamic indicators of daily emotional and peer problems in adolescents. These dynamic indicators include within-domain dynamics-such as inertia, which reflects the temporal dependence of experiences, and volatility, which indicates within-person variance-and cross-domain dynamics, such as transactional effects, which measure the strength of concurrent or lagged associations between daily emotional and peer problems. Participants were 315 seventh-grade Chinese adolescents (Mage = 13.05 years, SD = 0.77 years; 48.3% girls). Adolescents reported on their friends' emotional support at baseline and then completed measures of daily emotion and peer problems over a 10-day period. Using dynamic structural equation models, the results revealed that higher levels of friend emotional support were associated with fewer daily socioemotional problems. This was evident both in terms of average levels and dynamic aspects, characterized by lower mean levels of daily emotional and peer problems, reduced inertia and volatility of these problems, and a weaker spillover effect from daily emotional issues to peer problems. These findings highlight the significant role of friend-emotional support in mitigating adolescents' daily socioemotional challenges.

The roles of the LpSTS and DLPFC in self-prioritization: A transcranial magnetic stimulation study.

The Self-Attention Network (SAN) has been proposed to describe the underlying neural mechanism of the self-prioritization effect, yet the roles of the key nodes in the SAN-the left posterior superior temporal sulcus (LpSTS) and the dorsolateral prefrontal cortex (DLPFC)-still need to be clarified. One hundred and nine participants were randomly assigned into the LpSTS group, the DLPFC group, or the sham group. We used the transcranial magnetic stimulation (TMS) technique to selectively disrupt the functions of the corresponding targeted region, and observed its impacts on self-prioritization effect based on the difference between the performance of the self-matching task before and after the targeted stimulation. We analyzed both model-free performance measures and HDDM-based performance measures for the self-matching task. The results showed that the inhibition of LpSTS could lead to reduced performance in processing self-related stimuli, which establishes a causal role for the LpSTS in self-related processing and provide direct evidence to support the SAN framework. However, the results of the DLPFC group from HDDM analysis were distinct from the results based on response efficiency. Our investigation further the understanding of the differentiated roles of key nodes in the SAN in supporting the self-salience in information processing.

Oil dispersion and aggregation with suspended particles in a wave tank.

Suspended particulate matter (SPM) in marine environments plays an important role in determining the fate of spilled oil via the generation of oil-particle aggregates (OPAs). A series of mesoscale wave tank experiments and sedimentation tests were conducted to fill the knowledge gap on how the turbulent mixing, temperature, and oil type affect the dispersion of spilled oil and properties of OPAs. Generally, the oil dispersing efficiency was significantly enhanced by high wave energy, which also led to effective oil sinking, large size of OPAs and wide distribution of trapped oil. Nonlinear fitting results indicated that the oil sinking efficiency followed an exponential growth over time. The effect of temperature on oil dispersion and formation of OPAs is primarily attributed to its influence on oil viscosity and interfacial tension. Viscous oils are more likely to interact with particles above 25 °C. However, below 20 °C, a specific oil viscosity that will bring about the maximum OPAs exists. Excessive oil viscosity will lead to a weak binding between oil and SPM and a centralized distribution of trapped oil. Furthermore, spilled oil with a high asphaltene can interact more effectively with particles. Our finding suggested that early prevention of offshore oil sinking is key in summer.

CRISPR/Cas and Argonaute-Based Biosensors for Pathogen Detection.

Over the past few decades, pathogens have posed a threat to human security, and rapid identification of pathogens should be one of the ideal methods to prevent major public health security outbreaks. Therefore, there is an urgent need for highly sensitive and specific approaches to identify and quantify pathogens. Clustered Regularly Interspaced Short Palindromic Repeats CRISPR/Cas systems and Argonaute (Ago) belong to the Microbial Defense Systems (MDS). The guided, programmable, and targeted activation of nucleases by both of them is leading the way to a new generation of pathogens detection. We compare these two nucleases in terms of similarities and differences. In addition, we discuss future challenges and prospects for the development of the CRISPR/Cas systems and Argonaute (Ago) biosensors, especially electrochemical biosensors. This review is expected to afford researchers entering this multidisciplinary field useful guidance and to provide inspiration for the development of more innovative electrochemical biosensors for pathogens detection.

Electrochemical signal amplification strategy based on trace metal ion modified WS2 for ultra-sensitive detection of miRNA-21.

Previous researches have suggested the potential correlation between the development of breast cancer and the concentration of miRNA-21 in serum. Theoretically the doping of multivalent metal ions in WS2 could bring higher electron transfer capacity, but this hasn't been proven. To fill this research gap, through one-pot method we prepared seven nanocomposite structures modified with different metal ions (Co2+, Ni2+, Mn2+, Zn2+, Fe3+, Cr3+, La3+). Characterization revealed that ammonia produced by hydrothermal urea exfoliated the multilayer graphene oxide (MGO) and provided a nitrogen source for doping reduction to form a 3D flower-like structure (NrGOF) with high specific surface area. Meanwhile, the modification of WS2 by Fe3+ not only enhanced its electrochemical conductivity but also gave the material an additional peroxidase activity centre. In the composite Fe3+-WS2/NrGOF-AgNPs, NrGOF is used as a conductive loading interface for WS2, while Fe3+ served as the catalytic and electron transfer centre for secondary amplification of the electrochemical signal. The experimental results showed that the sensing platform has a low limit of detection (LOD) of 1.18 aM for miRNA-21 in the concentration range of 10-17-10-12 M and has been successfully applied to the detection of real serum samples.

Effects of chemical dispersant on the surface properties of kaolin and aggregation with spilled oil.

After oil spills occur, dispersed oil droplets can collide with suspended particles in the water column to form the oil-mineral aggregate (OMA) and settle to the seafloor. However, only a few studies have concerned the effect of chemical dispersant on this process. In this paper, the mechanism by which dispersant affects the surface properties of kaolin and the viscosity and oil-seawater interfacial tension (IFTow) of Roncador crude oil were separately investigated by small-scale tests. The results indicated that the presence of dispersant impairs the zeta potential and enhances the hydrophobicity of kaolin. The viscosity of Roncador crude oil rose slightly as the dosage of dispersant increased, while IFTow decreased significantly. Furthermore, the oil dispersion and OMA formation at different dispersant-to-oil ratio (DOR) were evaluated in a wave tank. When DOR was less than 1:40, the effect of dispersant on the dispersion of spilled oil was not obvious. With the increasing DOR, the effect became more pronounced, and the adhesion between oil droplets and kaolin was inhibited. The size ratio between oil droplets and particles is the significant factor for OMA formation. The closer the oil-mineral size ratio is to 1, the more difficultly the OMA forms.

Performance of dispersed oil and suspended sediment during the oil-sediment aggregation process.

Oil-sediment aggregation is an important transport and transformation process of spilled oil, which has been considered as a pathway of spill remediation. This work focused on the individual performance of dispersed oil and sediment during the aggregation process. Dispersion of three oils was first tested and validated in a water tank. An approach of estimating the mass variation of the sediment that has participated in forming the oil-sediment aggregates (OSAs) has been developed by density analysis. Results indicated that the density of the formed OSAs increases during the aggregation. In the context of remediation, it takes longer for sediment to reach equilibrium than for dispersed oil, especially under high mixing energy at a large sediment concentration, which results in the formation of dense OSAs, as well as high aggregation degree and rate. Roncador oil possesses a relatively high capability of capturing sediment to form dense OSAs, especially at an initial sediment concentration of over 150 mg/L. Oil sinking efficiency and the characteristic change rate of aggregated oil mass seem to be proportional to oil dispersion efficiency, and decrease with the mean size of dispersed oil droplets. The process of aggregation can further promote the dispersion of oil into water column. This study also provides fundamental data for the formation kinetics of OSAs.

Thionine-functionalized three-dimensional carbon nanomaterial-based aptasensor for analysis of Aß oligomers in serum.

How to sensitively detect early biomarkers of Alzheimer's disease (AD) is nowadays, one of the major challenges. In this work, Aß oligomers (AßO), one of the AD biomarkers, was analyzed using an electrochemical aptasensor, which was prepared based on thionine (Th) - functionalized three - dimensional carbon nanomaterials (reduced graphene oxide (rGO) and multi-wall carbon nanotubes (MWCNTs)) immobilized DNA-aptamer. Th, a positively charged planar aromatic molecule, form many π - π conjugated structures with rGO and MWCNTs, then improving the structural stability, electron transfer and the capacitive properties of Th-rGO-MWCNTs nanocomposites. Under the optimal conditions, differential pulse voltammetry (DPV) current responses decreased with the increase of AßO concentration. The obtained AßO aptasensor presented a wide linear range of 0.0443 pM-443.00 pM and limit of detection (LOD) was 10 fM. Meanwhile, AßO aptasensor displayed remarkable stability and selectivity. It has a great potential for early diagnosis of AD in human real serum samples.

Effect of the concentration and size of suspended particulate matter on oil-particle aggregation.

After spill, the dispersed oil droplets may collide with suspended particulate matter in the water column to form oil-particle aggregates (OPAs) in turbulent environments. It may be an effective pathway to stabilize the oil by taking advantage of the particulate matter to clean up the contaminated waters. A theoretical model in Payne et al. (2003) is adopted to describe the oil-particle aggregation, and a solution method is proposed and validated against a group of experiments. The effect of the particle size and mass concentration on the aggregation has been examined quantitatively in detail. The particles and the oil droplets are consumed at a fixed ratio. Under the same mass concentration, smaller particles can trap more oil droplets, while larger particles tend to interact more quickly with the oil. The oil-particle aggregation rate and the oil trapping efficiency mainly depend on the particle concentration. The theoretical model is applied to predict the decrease of the dispersed oil in nearshore environments, based on the parameters obtained from the experiments. It is efficient to promote the oil-particle aggregation by increasing the particle concentration in the closed bay. In the open sea, the decrease of the dispersed oil can be effectively enhanced by increasing the particle concentration when it is below 0.50 kg/m3. The information presented in this paper can serve to predict the fate of the dispersed oil in coastal waters and provide technical support for oil spill management strategies.

Effects of physical parameters and chemical dispersant on the formation of oil-particle aggregates (OPAs) in marine environments.

Floating oil and sediments can interact to form oil-particle aggregates (OPAs) in marine environments. Laboratory batch experiments were conducted to investigate the effects of the concentration and size of sediment, temperature, oil types and chemical dispersant on the formation of OPAs. The results showed that the mass of OPAs and oil-particle aggregation rate are mainly related to the sediment concentration. Under the same mass concentration, more oil droplets can be trapped by smaller particles. Nevertheless, larger particles tend to interact more quickly with oil droplets. The effect of temperature on the formation of OPAs is substantially attributed to its influence on oil viscosity, and there is a threshold for oil viscosity which will bring about the maximum OPAs. Spilled oil with a high asphaltene can interact more effectively with the sediments. Appropriate addition of chemical dispersant is favorable for the formation of OPAs while excess addition will inhibit it.