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Selfie-editing behavior has become a great popularity globally. Due to the widespread prevalence of selfie-related behaviors, it is of great significance to explore the negative consequences of selfie-related behaviors. However, evidence concerning the underlying psychological mechanisms, and potential gender differences in the relationship between selfie editing and self-objectification, are scarce. Two studies were conducted to examine the promoting effect of selfie editing on self-objectification and the mediating role of body surveillance. Potential gender differences were also examined. In Study 1, an online correlational study with 342 participants was conducted. In Study 2, an experimental study was conducted, 136 college students were instructed to take and edit a selfie or object photo. We found that both a greater frequency of selfie editing and selfie-editing (vs. object-editing) behavior shortly induced in the lab were associated with increased self-objectification. In addition, body surveillance mediated the association. Furthermore, there was no gender difference. Findings from the current study shed insights into the psychological risks of selfie editing on self-perception of body image and enrich our understanding of the antecedents of self-objectification. Implications for research on objectification theory, selfie editing, and women's well-being were discussed. [ABSTRACT FROM AUTHOR]

Rationale: Clinically, chronic postsurgical pain (CPSP) is very common. Many CPSP patients may experience depression. Thus far, little is known about the mechanism of the comorbidity of CPSP and depression. Ketamine has been confirmed to possess analgesic and rapid antidepressant effects, but it is unclear whether ketamine can relieve the comorbidity of CPSP and depression. Objectives: The present study evaluated the effects of ketamine in rats with the comorbidity of CPSP and depression. Methods: We induced CPSP in rats by thoracotomy and screened for rats with or without depression-like phenotype by hierarchical cluster analysis based on the results of depression-related behavioral experiments. Subsequently, rats were intraperitoneally injected with ketamine (20 mg/kg) and were evaluated by mechanical withdrawal threshold, cold hyperalgesia test, sucrose preference test, forced swimming test, and open field test. The inflammatory-related cytokines (IL-1, IL-6, TNF-α, nuclear factor-kappaB), oxidative stress parameters (superoxide dismutase, malondialdehyde, glutathione, catalase), and brain-derived neurotrophic factor (BDNF) in rat hippocampus were detected. Results: In the hippocampus of rats with the comorbidity of CPSP and depression, IL-1, IL-6, TNF-α, nuclear factor-kappaB, and malondialdehyde were significantly increased, while superoxide dismutase, glutathione, catalase, and BDNF were significantly decreased. Ketamine relieved depression but did not attenuate hyperalgesia in CPSP rats. Additionally, ketamine reduced proinflammatory cytokines, inhibited oxidative stress, and elevated BDNF levels in rat hippocampus. Conclusions: Ketamine can rapidly relieve CPSP-induced depression in rats, which may be related to the reduction of proinflammatory cytokines, regulating oxidative stress and increasing BDNF in the hippocampus. [ABSTRACT FROM AUTHOR]

The logistic regression and statistical index models are applied and verified for landslide susceptibility mapping in Daguan County, Yunnan Province, China, by means of the geographic information system (GIS). A detailed landslide inventory map was prepared by literatures, aerial photographs, and supported by field works. Fifteen landslide-conditioning factors were considered: slope angle, slope aspect, curvature, plan curvature, profile curvature, altitude, STI, SPI, and TWI were derived from digital elevation model; NDVI was extracted from Landsat ETM7; rainfall was obtained from local rainfall data; distance to faults, distance to roads, and distance to rivers were created from a 1:25,000 scale topographic map; the lithology was extracted from geological map. Using these factors, the landslide susceptibility maps were prepared by LR and SI models. The accuracy of the results was verified by using existing landslide locations. The statistical index model had a predictive rate of 81.02%, which is more accurate prediction in comparison with logistic regression model (80.29%). The models can be used to land-use planning in the study area. [ABSTRACT FROM AUTHOR]