Distinct patterns of Internet and smartphone-related problems among adolescents by gender: Latent class analysis

Background and objectives The ubiquitous Internet connections by smartphones weakened the traditional boundaries between computers and mobile phones. We sought to explore whether smartphone-related problems differ from those of computer use according to gender using latent class analysis (LCA). Methods After informed consents, 555 Korean middle-school students completed surveys on gaming, Internet use, and smartphone usage patterns. They also completed various psychosocial instruments. LCA was performed for the whole group and by gender. In addition to ANOVA and χ2 tests, post-hoc tests were conducted to examine differences among the LCA subgroups. Results In the whole group (n = 555), four subtypes were identified: dual-problem users (49.5%), problematic Internet users (7.7%), problematic smartphone users (32.1%), and “healthy” users (10.6%). Dual-problem users scored highest for addictive behaviors and other psychopathologies. The gender-stratified LCA revealed three subtypes for each gender. With dual-problem and healthy subgroup as common, problematic Internet subgroup was classified in the males, whereas problematic smartphone subgroup was classified in the females in the gender-stratified LCA. Thus, distinct patterns were observed according to gender with higher proportion of dual-problem present in males. While gaming was associated with problematic Internet use in males, aggression and impulsivity demonstrated associations with problematic smartphone use in females. Conclusions An increase in the number of digital media-related problems was associated with worse outcomes in various psychosocial scales. Gaming may play a crucial role in males solely displaying Internet-related problems. The heightened impulsivity and aggression seen in our female problematic smartphone users requires further research

Macrophage Lamin A/C Regulates Inflammation and the Development of Obesity-Induced Insulin Resistance

Obesity-induced chronic low-grade inflammation, in particular in adipose tissue, contributes to the development of insulin resistance and type 2 diabetes. However, the mechanism by which obesity induces adipose tissue inflammation has not been completely elucidated. Recent studies suggest that alteration of the nuclear lamina is associated with age-associated chronic inflammation in humans and fly. These findings led us to investigate whether the nuclear lamina regulates obesity-mediated chronic inflammation. In this study, we show that lamin A/C mediates inflammation in macrophages. The gene and protein expression levels of lamin A/C are significantly increased in epididymal adipose tissues from obese rodent models and omental fat from obese human subjects compared to their lean controls. Flow cytometry and gene expression analyses reveal that the protein and gene expression levels of lamin A/C are increased in adipose tissue macrophages (ATMs) by obesity. We further show that ectopic overexpression of lamin A/C in macrophages spontaneously activates NF-κB, and increases the gene expression levels of proinflammatory genes, such as Il6, Tnf, Ccl2, and Nos2. Conversely, deletion of lamin A/C in macrophages reduces LPS-induced expression of these proinflammatory genes. Importantly, we find that myeloid cell-specific lamin A/C deficiency ameliorates obesity-induced insulin resistance and adipose tissue inflammation. Thus, our data suggest that lamin A/C mediates the activation of ATM inflammation by regulating NF-κB, thereby contributing to the development of obesity-induced insulin resistance

Cluster-specific nonignorably missing, endogenous, and continuous regressors in multilevel model for binary outcome

In multilevel regression models for observational clustered data, regressors can be correlated with cluster-level error components, namely endogenous, due to omitted cluster-level covariates, measurement error, and simultaneity. When endogeneity is ignored, regression coefficient estimators can be severely biased. To deal with endogeneity, instrument variable methods have been widely used. However, the instrument variable method often requires external instrument variables with certain conditions that cannot be verified empirically. Methods that use the within-cluster variations of the endogenous variable work under the restriction that either the outcome or the endogenous variable has a linear relationship with the cluster-level random effect. We propose a new method for binary outcome when it follows a logistic mixed-effects model and the endogenous variable is normally distributed but not linear in the random effect. The proposed estimator capitalizes on the nested data structure without requiring external instrument variables. We show that the proposed estimator is consistent and asymptotically normal. Furthermore, our method can be applied when the endogenous variable is missing in a cluster-specific nonignorable mechanism, without requiring that the missing mechanism be correctly specified. We evaluate the finite sample performance of the proposed approach via simulation and apply the method to a health care study using a San Diego inpatient dataset. Our study demonstrates that the clustered structure can be exploited to draw valid analysis of multilevel data with correlated effects

Robust inference using hierarchical likelihood approach for heavy-tailed longitudinal outcomes with missing data: An alternative to inverse probability weighted generalized estimating equations

We examine methods appropriate for heavy-tailed longitudinal outcomes with possibly missing data. Generalized estimating equations (GEEs) have been widely used in longitudinal studies when data are not heavy-tailed and, in general, are valid only when data are missing completely at random. Robins et al. (1995) showed how inverse probability weighting in such settings (IPW-GEE) can extend validity to data that are missing at random. When data are completely observed, Preisser and Qaqish (1999) proposed the use of robust GEE methods to handle outliers. A natural extension of this to the setting with missing data is to combine these two methods. One alternative for the same setting is to use hierarchical (h-) likelihood (Lee et al., 2006). Here we compare this approach with that of IPW-GEE for heavy-tailed data in the missing data context. (C) 2012 Elsevier B.V. All rights reserved

A Practical Roadmap for the Path Planning of Mobile Robots in Rectilinear Environments

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Radiation-Induced Lung Fibrosis: Preclinical Animal Models and Therapeutic Strategies

Radiation-induced lung injury (RILI), including acute radiation pneumonitis and chronic radiation-induced lung fibrosis, is the most common side effect of radiation therapy. RILI is a complicated process that causes the accumulation, proliferation, and differentiation of fibroblasts and, finally, results in excessive extracellular matrix deposition. Currently, there are no approved treatment options for patients with radiation-induced pulmonary fibrosis (RIPF) partly due to the absence of effective targets. Current research advances include the development of small animal models reflecting modern radiotherapy, an understanding of the molecular basis of RIPF, and the identification of candidate drugs for prevention and treatment. Insights provided by this research have resulted in increased interest in disease progression and prognosis, the development of novel anti-fibrotic agents, and a more targeted approach to the treatment of RIPF

Scorpionate Catalysts for Coupling CO2 and Epoxides to Cyclic Carbonates: A Rational Design Approach for Organocatalysts

Novel scorpionate-type organocatalysts capable of effectively coupling carbon dioxide and epoxides under mild conditions to afford cyclic propylene carbonates were developed. On the basis of a combined experimental and computational study, a precise mechanistic proposal was developed and rational optimization strategies were identified. The epoxide ring-opening, which requires an iodide as a nucleophile, was enhanced by utilizing an immonium functionality that can form an ion pair with iodide, making the ring opening process intramolecular. The CO2 activation and cyclic carbonate formation were catalyzed by the concerted action of two hydrogen bonds originating from two phenolic groups placed at the claw positions of the scorpionate scaffold. Electronic tuning of the hydrogen bond donors allowed to identify a new catalyst that can deliver >90% yield for a variety of epoxide substrates within 7 h at room temperature under a CO2 pressure of only 10 bar, and is highly recyclable © 2018 American Chemical Societ

Scorpionate Catalysts for Coupling CO₂ and Epoxides to Cyclic Carbonates: A Rational Design Approach for Organocatalysts

Novel scorpionate-type organocatalysts capable of effectively coupling carbon dioxide and epoxides under mild conditions to afford cyclic propylene carbonates were developed. On the basis of a combined experimental and computational study, a precise mechanistic proposal was developed and rational optimization strategies were identified. The epoxide ring-opening, which requires an iodide as a nucleophile, was enhanced by utilizing an immonium functionality that can form an ion pair with iodide, making the ring-opening process intramolecular. The CO₂ activation and cyclic carbonate formation were catalyzed by the concerted action of two hydrogen bonds originating from two phenolic groups placed at the claw positions of the scorpionate scaffold. Electronic tuning of the hydrogen bond donors allowed to identify a new catalyst that can deliver >90% yield for a variety of epoxide substrates within 7 h at room temperature under a CO₂ pressure of only 10 bar, and is highly recyclable

Scorpionate Catalysts for Coupling CO₂ and Epoxides to Cyclic Carbonates: A Rational Design Approach for Organocatalysts

Novel scorpionate-type organocatalysts capable of effectively coupling carbon dioxide and epoxides under mild conditions to afford cyclic propylene carbonates were developed. On the basis of a combined experimental and computational study, a precise mechanistic proposal was developed and rational optimization strategies were identified. The epoxide ring-opening, which requires an iodide as a nucleophile, was enhanced by utilizing an immonium functionality that can form an ion pair with iodide, making the ring-opening process intramolecular. The CO₂ activation and cyclic carbonate formation were catalyzed by the concerted action of two hydrogen bonds originating from two phenolic groups placed at the claw positions of the scorpionate scaffold. Electronic tuning of the hydrogen bond donors allowed to identify a new catalyst that can deliver >90% yield for a variety of epoxide substrates within 7 h at room temperature under a CO₂ pressure of only 10 bar, and is highly recyclable