Supported Lipid Bilayer Platform for Characterizing the Membrane-Disruptive Behaviors of Triton X-100 and Potential Detergent Replacements

Triton X-100 (TX-100) is a widely used detergent to prevent viral contamination of manufactured biologicals and biopharmaceuticals, and acts by disrupting membrane-enveloped virus particles. However, environmental concerns about ecotoxic byproducts are leading to TX-100 phase out and there is an outstanding need to identify functionally equivalent detergents that can potentially replace TX-100. To date, a few detergent candidates have been identified based on viral inactivation studies, while direct mechanistic comparison of TX-100 and potential replacements from a biophysical interaction perspective is warranted. Herein, we employed a supported lipid bilayer (SLB) platform to comparatively evaluate the membrane-disruptive properties of TX-100 and a potential replacement, Simulsol SL 11W (SL-11W), and identified key mechanistic differences in terms of how the two detergents interact with phospholipid membranes. Quartz crystal microbalance-dissipation (QCM-D) measurements revealed that TX-100 was more potent and induced rapid, irreversible, and complete membrane solubilization, whereas SL-11W caused more gradual, reversible membrane budding and did not induce extensive membrane solubilization. The results further demonstrated that TX-100 and SL-11W both exhibit concentration-dependent interaction behaviors and were only active at or above their respective critical micelle concentration (CMC) values. Collectively, our findings demonstrate that TX-100 and SL-11W have distinct membrane-disruptive effects in terms of potency, mechanism of action, and interaction kinetics, and the SLB platform approach can support the development of biophysical assays to efficiently test potential TX-100 replacements.

High-Capacity Robust Behavioral Steganography Method Based on Timestamp Modulation across Social Internet of Things

Social Internet of Things (SIoT) is an emerging field that combines IoT and Internet, which can provide many novel and convenient application scenarios but still faces challenges in data privacy protection. In this paper, we propose a robust behavioral steganography method with high embedding capacity across social networks based on timestamp modulation. Firstly, the IoT devices on the sending end modulate the secret message to be embedded into a timestamp by using the common property on social networks. Secondly, the accounts of multiple social networks are used as the vertices, and the timestamp mapping relationship generated by the interaction behaviors between them is used as the edges to construct a directed secret message graph across social networks. Then, the frequency of interaction behaviors generated by users of mainstream social networks is analyzed; the corresponding timestamps and social networks are used to implement interaction behaviors based on the secret message graph and the frequency of interaction behaviors. Next, we analyze the frequency of interaction behaviors generated by users in mainstream social networks, implement the interaction behaviors according to the secret message graph and the frequency of interaction behaviors in the corresponding timestamps and social networks, and combine the redundant mapping control to complete the embedding of secret message. Finally, the receiver constructs the timestamp mapping relationship through the shared account, key, and other parameters to achieve the extraction of secret message. The algorithm is robust and does not have the problem that existing multimedia-based steganography methods are difficult to extract the embedded messages completely. Compared with existing graph theory-based social network steganography methods, using timestamps and behaviors frequencies to hide message in multiple social networks increases the cost of detecting covert communication and improves concealment of steganography. At the same time, the algorithm uses a directed secret message graph to increase the number of bits carried by each behavior and improves the embedding capacity. A large number of tests have been conducted on mainstream social networks such as Facebook, Twitter, and Weibo. The results show that the proposed method successfully distributes secret message to multiple social networks and achieves complete extraction of embedded message at the receiving end. The embedding capacity is increased by 1.98–4.89 times compared with the existing methods SSN, NGTASS, and SGSIR.

The Expenses Needed for the Effect of Restricted Group Sandplay on Interpersonal Sensitivity in College Students

This study aims to investigate the intervention effect of group sandplay on the interpersonal sensitivity of college students and analyze the relationship between the theme and interactive behavior characteristics and the intervention effect of group sandplay especially during the period of COVID-19. Sixty college students were randomly assigned to the experimental group (group sandplay) or the control group (neutral task interventions). The results showed that the interpersonal sensitivity level of the experimental group was significantly lower than that of the control group. For the experimental group, the variation in the interpersonal sensitivity level was significantly negatively correlated with the change in warm, supportive behavior during group sandplay interaction. These findings suggest that group sandplay is effective in improving the interpersonal sensitivity level of college students, and this effect can be positively predicted by warm and supportive interaction behaviors in group sandplay.

Parent Coaching Behaviors Used Within an Adaptive Responsive Teaching Intervention

The coaching service delivery model is often implemented within parent-mediated interventions for infants at an elevated likelihood of autism spectrum disorder. However, less is known about the exact coaching behaviors used within intervention sessions. Therefore, we examined the coaching behaviors implemented within the adaptive responsive teaching intervention. We also investigated the associations between coaching behaviors and parent education levels and the associations between the coaching behaviors and a parent outcome, that is, parent responsiveness. Results indicated that the interventionists demonstrated joint interaction and child-focused behaviors the most frequently. The interventionists much less frequently demonstrated guided practice, caregiver practice, and problem-solving behaviors. The use of joint interaction behaviors was positively associated with parent education levels, whereas the use of child-focused behaviors was negatively associated with parent education level. More information sharing by the interventionists predicted a greater change in parent responsiveness, whereas more child-focused behaviors predicted less change in parent responsiveness.

Emotional Contagion in the Online Depression Community

Negative emotions are prevalent in the online depression community (ODC), which potentially puts members at risk, according to the theory of emotional contagion. However, emotional contagion in the ODC has not been confirmed. The generalized estimating equation (GEE) was used to verify the extent of emotional contagion using data from 1548 sample users in China’s popular ODC. During interaction, the emotional themes were analyzed according to language use. The diurnal patterns of the interaction behaviors were also analyzed. We identified the susceptible groups and analyzed their characteristics. The results confirmed the occurrence of emotional contagion in ODC, that is, the extent to which the user’s emotion was affected by the received emotion. Our study also found that when positive emotional contagion occurred, the replies contained more hopefulness, and when negative emotional contagion occurred, the replies contained more hopelessness and fear. Second, positive emotions were easier to spread, and people with higher activity in ODC were more susceptible. In addition, nighttime was an active period for user interaction. The results can help community managers and support groups take measures to promote the spread of positive emotions and reduce the spread of negative emotions.

Tagging active neurons by soma-targeted Cal-Light

Verifying causal effects of neural circuits is essential for proving direct a circuit-behavior relationship. However, techniques for tagging only active neurons with high spatiotemporal precision remain at the beginning stages. Here we developed the soma-targeted Cal-Light (ST-Cal-Light) which selectively converts somatic calcium rise triggered by action potentials into gene expression. Such modification simultaneously increases the signal-to-noise ratio (SNR) of reporter gene expression and reduces the light requirement for successful labeling. Because of the enhanced efficacy, the ST-Cal-Light enables the tagging of functionally engaged neurons in various forms of behaviors, including context-dependent fear conditioning, lever-pressing choice behavior, and social interaction behaviors. We also targeted kainic acid-sensitive neuronal populations in the hippocampus which subsequently suppressed seizure symptoms, suggesting its applicability in controlling disease-related neurons. Furthermore, the generation of a conditional ST-Cal-Light knock-in (KI) mouse provides an opportunity to tag active neurons in a region- or cell-type specific manner via crossing with other Cre-driver lines. Thus, the versatile ST-Cal-Light system links somatic action potentials to behaviors with high temporal precision, and ultimately allows functional circuit dissection at a single cell resolution.