Adult Attachment Styles Associated with Brain Activity in Response to Infant Faces in Nulliparous Women: An Event-Related Potentials Study

Adult attachment style is a key for understanding emotion regulation and feelings of security in human interactions as well as for the construction of the caregiving system. The caregiving system is a group of representations about affiliative behaviors, which is guided by the caregiver’s sensitivity and empathy, and is mature in young adulthood. Appropriate perception and interpretation of infant emotions is a crucial component of the formation of a secure attachment relationship between infant and caregiver. As attachment styles influence the ways in which people perceive emotional information, we examined how different attachment styles associated with brain response to the perception of infant facial expressions in nulliparous females with secure, anxious, and avoidant attachment styles. The event-related potentials of 65 nulliparous females were assessed during a facial recognition task with joy, neutral, and crying infant faces. The results showed that anxiously attached females exhibited larger N170 amplitudes than those with avoidant attachment in response to all infant faces. Regarding the P300 component, securely attached females showed larger amplitudes to all infant faces in comparison with avoidantly attached females. Moreover, anxiously attached females exhibited greater amplitudes than avoidantly attached females to only crying infant faces. In conclusion, the current results provide evidence that attachment style differences are associated with brain responses to the perception of infant faces. Furthermore, these findings further separate the psychological mechanisms underlying the caregiving behavior of those with anxious and avoidant attachment from secure attachment

Neuroprotective Effects and Mechanism of β

Emerging evidence suggests that activated astrocytes play important roles in AD, and β-asarone, a major component of Acorus tatarinowii Schott, was shown to be a potential therapeutic candidate for AD. While our previous study found that β-asarone could improve the cognitive function of rats hippocampally injected with Aβ, the effects of β-asarone on astrocytes remain unclear, and this study aimed to investigate these effects. A rat model of Aβ1–42 (10 μg) was established, and the rats were intragastrically treated with β-asarone at doses of 10, 20, and 30 mg/kg or donepezil at a dose of 0.75 mg/kg. The sham and model groups were intragastrically injected with an equal volume of saline. Animals were sacrificed on the 28th day after administration of the drugs. In addition, a cellular model of Aβ1–42 (1.1 μM, 6 h) was established, and cells were treated with β-asarone at doses of 0, 2.06, 6.17, 18.5, 55.6, and 166.7 μg/mL. β-Asarone improved cognitive impairment, alleviated Aβ deposition and hippocampal damage, and inhibited GFAP, AQP4, IL-1β, and TNF-α expression. These results suggested that β-asarone could alleviate the symptoms of AD by protecting astrocytes, possibly by inhibiting TNF-α and IL-1β secretion and then downregulating AQP4 expression

Pancreatic Transcription Factors Containing Protein Transduction Domains Drive Mouse Embryonic Stem Cells towards Endocrine Pancreas

Protein transduction domains (PTDs), such as the HIV1-TAT peptide, have been previously used to promote the uptake of proteins into a range of cell types, including stem cells. Here we generated pancreatic transcription factors containing PTD sequences and administered these to endoderm enriched mouse embryonic stem (ES) cells under conditions that were designed to mimic the pattern of expression of these factors in the developing pancreas. The ES cells were first cultured as embryoid bodies and treated with Activin A and Bone morphogenetic protein 4 (BMP4) to promote formation of definitive endoderm. Cells were subsequently plated as a monolayer and treated with different combinations of the modified recombinant transcription factors Pdx1 and MafA. The results demonstrate that each transcription factor was efficiently taken up by the cells, where they were localized in the nuclei. RT-qPCR was used to measure the expression levels of pancreatic markers. After the addition of Pdx1 alone for a period of five days, followed by the combination of Pdx1 and TAT-MafA in a second phase, up-regulation of insulin 1, insulin 2, Pdx1, Glut2, Pax4 and Nkx6.1 was observed. As assessed by immunocytochemistry, double positive insulin and Pdx1 cells were detected in the differentiated cultures. Although the pattern of pancreatic markers expression in these cultures was comparable to that of a mouse transformed β-cell line (MIN-6) and human islets, the expression levels of insulin observed in the differentiated ES cell cultures were several orders of magnitude lower. This suggests that, although PTD-TFs may prove useful in studying the role of exogenous TFs in the differentiation of ES cells towards islets and other pancreatic lineages, the amount of insulin generated is well below that required for therapeutically useful cells

Can Green Economy and Ecological Welfare Achieve Synergistic Development? The Perspective of the “Two Mountains” Theory

China’s high-speed economic growth and severe environmental problems have resulted in a poor Environmental Performance Index and have affected China’s sustainable development and ecological welfare improvement. Therefore, exploring whether there is a certain relationship between the two and their influencing factors is an important way and a breakthrough to solve the problems regarding green economic progress and ecological welfare enhancement. To this end, by using the undesirable slack-based measure (SBM) model, this paper measures the ecological welfare performance and the green economic efficiency of 11 cities in Zhejiang Province, China, from 2000 to 2019. Through the methods of spatiotemporal evolution, coefficient of variation, coupling coordination degree, and the Tobit model, we found that: (1) The development trend of urban green economic efficiency and ecological welfare performance were both in a “U” shape that first fell and then rose; (2) The coupling coordination degree between green economic efficiency and ecological welfare performance showed a wave-like upward trend as a whole and most cities have entered a more advanced coupling coordination stage during the study period. The coefficient of variation revealed a downward trend; (3) The urbanization level, industrial structure, and government investment can promote the regional coordinated development, while the industrialization degree and the opening level had a negative impact on it; (4) The “Two Mountains” theory was beneficial to the improvement of regional urban green economic efficiency and ecological welfare performance and their coordinated development both in theory and practice. Finally, according to the findings, we offer relevant suggestions on making good use of the country’s preferential policies and informatization means from the perspective of the regional coordinated development

Evolutionary Game—Theoretic Approach for Analyzing User Privacy Disclosure Behavior in Online Health Communities

Privacy disclosure is one of the most common user information behaviors in online health communities. Under the premise of implementing privacy protection strategies in online health communities, promoting user privacy disclosure behavior can result in a “win–win” scenario for users and online health communities. Combining the real situation and evolutionary game theory, in this study, we first constructed an evolutionary game model of privacy disclosure behavior with users and online health communities as the main participants. Then, we solved the replication dynamic equations for both parties and analyzed the evolutionary stable strategies (ESSs) in different scenarios. Finally, we adopted MATLAB for numerical simulations to verify the accuracy of the model. Studies show that: (1) factors such as medical service support and community rewards that users receive after disclosing their private personal information affect user game strategy; and (2) the additional costs of the online health communities implementing the “positive protection” strategy and the expected loss related to the privacy leakage risk affect the online health communities’ game strategy. In this regard, this paper puts forward the following suggestions in order to optimize the benefits of both sets of participants: the explicit benefits of users should be improved, the internal environment of the communities should be optimized, the additional costs of the “positive protection” strategy should be reduced, and penalties for privacy leakages should be increased

Adult Attachment Affects Neural Response to Preference-Inferring in Ambiguous Scenarios: Evidence From an fMRI Study

Humans are highly social animals, and the ability to cater to the preferences of other individuals is encouraged by society. Preference-inferring is an important aspect of the theory of mind (TOM). Many previous studies have shown that attachment style is closely related to TOM ability. However, little is known about the effects of adult attachment style on preferences inferring under different levels of certainty. Here, we investigated how adult attachment style affects neural activity underlying preferences inferred under different levels of certainty by using functional magnetic resonance imaging (fMRI). The fMRI results demonstrated that adult attachment influenced the activation of anterior insula (AI) and inferior parietal lobule (IPL) in response to ambiguous preference-inferring. More specifically, in the ambiguous preference condition, the avoidant attached groups exhibited a significantly enhanced activation than secure and anxious attached groups in left IPL; the anxious attached groups exhibited a significantly reduced activation secure attached group in left IPL. In addition, the anxious attached groups exhibited a significantly reduced activation than secure and avoidant attached groups in left AI. These results were also further confirmed by the subsequent PPI analysis. The results from current study suggest that, under ambiguous situations, the avoidant attached individuals show lower sensitivity to the preference of other individuals and need to invest more cognitive resources for preference-reasoning; while compared with avoidant attached group, the anxious attached individuals express high tolerance for uncertainty and a higher ToM proficiency. Results from the current study imply that differences in preference-inferring under ambiguous conditions associated with different levels of individual attachment may explain the differences in interpersonal interaction

Inferring cancer common and specific gene networks via multi-layer joint graphical model

Cancer is a complex disease caused primarily by genetic variants. Reconstructing gene networks within tumors is essential for understanding the functional regulatory mechanisms of carcinogenesis. Advances in high-throughput sequencing technologies have provided tremendous opportunities for inferring gene networks via computational approaches. However, due to the heterogeneity of the same cancer type and the similarities between different cancer types, it remains a challenge to systematically investigate the commonalities and specificities between gene networks of different cancer types, which is a crucial step towards precision cancer diagnosis and treatment. In this study, we propose a new sparse regularized multi-layer decomposition graphical model to jointly estimate the gene networks of multiple cancer types. Our model can handle various types of gene expression data and decomposes each cancer-type-specific network into three components, i.e., globally shared, partially shared and cancer-type-unique components. By identifying the globally and partially shared gene network components, our model can explore the heterogeneous similarities between different cancer types, and our identified cancer-type-unique components can help to reveal the regulatory mechanisms unique to each cancer type. Extensive experiments on synthetic data illustrate the effectiveness of our model in joint estimation of multiple gene networks. We also apply our model to two real data sets to infer the gene networks of multiple cancer subtypes or cell lines. By analyzing our estimated globally shared, partially shared, and cancer-type-unique components, we identified a number of important genes associated with common and specific regulatory mechanisms across different cancer types