Socioeconomic inequalities in obesity among Korean women aged 19-79 years: the 2016 Korean Study of Women’s Health-Related Issues

OBJECTIVES While the prevalence of obesity in Asian women has remained stagnant, studies of socioeconomic inequalities in obesity among Asian women are scarce. This study aimed to examine the recent prevalence of obesity in Korean women aged between 19 years and 79 years and to analyze socioeconomic inequalities in obesity. METHODS Data were derived from the 2016 Korean Study of Women’s Health-Related Issues. The chi-square test and logistic regression analysis were used to analyze the associations between socioeconomic factors and obesity using Asian standard body mass index (BMI) categories: low (<18.5 kg/m2 ), normal (18.5-22.9 kg/m2 ), overweight (23.0-24.9 kg/m2 ), and obese (≥25.0 kg/ m2 ). As inequality-specific indicators, the slope index of inequality (SII) and relative index of inequality (RII) were calculated, with adjustment for age and self-reported health status. RESULTS Korean women were classified into the following BMI categories: underweight (5.3%), normal weight (59.1%), overweight (21.2%), and obese (14.4%). The SII and RII revealed substantial inequalities in obesity in favor of more urbanized women (SII, 4.5; RII, 1.4) and against of women who were highly educated (SII, -16.7; RII, 0.3). Subgroup analysis revealed inequalities in obesity according to household income among younger women and according to urbanization among women aged 65-79 years. CONCLUSIONS Clear educational inequalities in obesity existed in Korean women. Reverse inequalities in urbanization were also apparent in older women. Developing strategies to address the multiple observed inequalities in obesity among Korean women may prove essential for effectively reducing the burden of this disease

Regulation of cAMP and GSK3 signaling pathways contributes to the neuronal conversion of glioma

Glioma is the most malignant type of primary central nervous system tumors, and has an extremely poor prognosis. One potential therapeutic approach is to induce the terminal differentiation of glioma through the forced expression of pro-neural factors. Our goal is to show the proof of concept of the neuronal conversion of C6 glioma through the combined action of small molecules. We investigated the various changes in gene expression, cell-specific marker expression, signaling pathways, physiological characteristics, and morphology in glioma after combination treatment with two small molecules (CHIR99021, a glycogen synthase kinase 3 [GSK3] inhibitor and forskolin, a cyclic adenosine monophosphate [cAMP] activator). Here, we show that the combined action of CHIR99021 and forskolin converted malignant glioma into fully differentiated neurons with no malignant characteristics; inhibited the proliferation of malignant glioma; and significantly down-regulated gene ontology and gene expression profiles related to cell division, gliogenesis, and angiogenesis in small molecule-induced neurons. In vivo, the combined action of CHIR99021 and forskolin markedly delayed neurological deficits and significantly reduced the tumor volume. We suggest that reprogramming technology may be a potential treatment strategy replacing the therapeutic paradigm of traditional treatment of malignant glioma, and a combination molecule comprising a GSK3 inhibitor and a cAMP inducer could be the next generation of anticancer drugs

The thalamic mGluR1-PLC??4 pathway is critical in sleep architecture

The transition from wakefulness to a nonrapid eye movement (NREM) sleep state at the onset of sleep involves a transition from low-voltage, high-frequency irregular electroencephalography (EEG) waveforms to large-amplitude, low-frequency EEG waveforms accompanying synchronized oscillatory activity in the thalamocortical circuit. The thalamocortical circuit consists of reciprocal connections between the thalamus and cortex. The cortex sends strong excitatory feedback to the thalamus, however the function of which is unclear. In this study, we investigated the role of the thalamic metabotropic glutamate receptor 1 (mGluR1)-phospholipase C ??4 (PLC??4) pathway in sleep control in PLC??4-deficient (PLC??4-/-) mice. The thalamic mGluR1-PLC??4 pathway contains synapses that receive corticothalamic inputs. In PLC??4-/- mice, the transition from wakefulness to the NREM sleep state was stimulated, and the NREM sleep state was stabilized, which resulted in increased NREM sleep. The power density of delta (??) waves increased in parallel with the increased NREM sleep. These sleep phenotypes in PLC??4-/- mice were consistent in TC-restricted PLC??4 knockdown mice. Moreover, in vitro intrathalamic oscillations were greatly enhanced in the PLC??4-/- slices. The results of our study showed that thalamic mGluR1-PLC??4 pathway was critical in controlling sleep architecture.ope

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Public Debt, Corruption and Sustainable Economic Growth

There are many studies that look into the relationship between public debt and economic growth. It is hard to find, however, research addressing the role of corruption between these two variables. Noticing this vacancy in current literature, we strive to investigate the effect of corruption on the relationship between public debt and economic growth. For this purpose, the pooled ordinary least squares (OLS), fixed effects models and the dynamic panel generalized method of moments (GMM) models (Arellano-Bond, 1991) are estimated with data of 77 countries from 1990 to 2014. The empirical results show that the interaction term between public debt and corruption is statistically significant. This confirms the hypothesis that the effect of public debt on economic growth is a function of corruption. The sign of the marginal effect is negative in corrupt countries, but public debt enhances economic growth within countries that are not corrupt, i.e., highly transparent

Interpreting Chemical Structures of Compounds in Crude Oil Based on the Tandem Mass Spectra of Standard Compounds Obtained at the Same Normalized Collision Energy

In this study, the tandem mass spectra of 25 standard compounds, obtained at a normalized collision energy of 50, were used to investigate the structures of crude oil. The product ion distributions of these standard compounds were dependent on the number and length of their alkyl side chains. Long alkyl side chains (C_<i>n</i>H_2<i>n</i>, <i>n</i> ≥ 5) were easily lost during molecular collision, leaving behind methyl groups on the aromatic cores. In contrast, compounds with short interlinking alkyl chains (C_<i>n</i>H_2<i>n</i>, <i>n</i> ≤ 1) were not significantly fragmented, and a decrease in the double bond equivalent (DBE) value was observed when compounds had saturated rings. Based on the derived observations, the possible structures of S₁-class compounds with DBE values of 6, 7, 8, and 9 were suggested. It was also determined that, in the tandem mass spectra of crude oil fractions, (1) a series of peaks separated by CH₂ groups were generated from isomers with different numbers of alky side chains, (2) the number of methyl groups left after molecular collision was positively correlated to the quantity of branched molecules, and (3) significant fragmentation did not occur for aromatic cores linked by short alkyl chains (C_<i>n</i>H_2<i>n</i>, <i>n</i> ≥ 2), and hence, archipelago structures with short alkyl linkage could not be excluded based solely on tandem mass spectra. This study clearly shows that a systematic analytical approach using a well-defined set of standard compounds combined with tandem mass spectrometry can significantly improve our understanding on the chemical structures of crude oil compounds

Experiences of using clinical pathways in hospitals: Perspectives of quality improvement personnel

Abstract Aim This study aimed to explore the experiences of quality improvement personnel in implementing clinical pathways (CPs) in Korean hospitals. Design A qualitative study using focus‐group interviews was conducted with healthcare professionals in charge of CP development and management in hospitals. Methods Sixteen quality improvement personnel from eight tertiary and seven general hospitals were recruited using purposive sampling. The verbatim transcribed data were analysed using qualitative content analysis. Results Three key themes emerged: (1) the primary focus of CP development on surgeries through concerted efforts between management and frontline healthcare professionals; (2) CP fidelity management using indicators and feedback to relevant staff or departments; and (3) positive outcomes, despite concerns about system safety. The factors affecting CP use included availability of clinical evidence, flexibility of CPs, top management and clinical leadership, physicians' perceptions of CPs, computerized support systems, and external policies and regulations

Brain Age Prediction Using Multi-Hop Graph Attention Combined with Convolutional Neural Network

Convolutional neural networks (CNNs) have been used widely to predict biological brain age based on brain magnetic resonance (MR) images. However, CNNs focus mainly on spatially local features and their aggregates and barely on the connective information between distant regions. To overcome this issue, we propose a novel multi-hop graph attention (MGA) module that exploits both the local and global connections of image features when combined with CNNs. After insertion between convolutional layers, MGA first converts the convolution-derived feature map into graph-structured data by using patch embedding and embedding-distance-based scoring. Multi-hop connections between the graph nodes are modeled by using the Markov chain process. After performing multi-hop graph attention, MGA re-converts the graph into an updated feature map and transfers it to the next convolutional layer. We combined the MGA module with sSE (spatial squeeze and excitation)-ResNet18 for our final prediction model (MGA-sSE-ResNet18) and performed various hyperparameter evaluations to identify the optimal parameter combinations. With 2788 three-dimensional T1-weighted MR images of healthy subjects, we verified the effectiveness of MGA-sSE-ResNet18 with comparisons to four established, general-purpose CNNs and two representative brain age prediction models. The proposed model yielded an optimal performance with a mean absolute error of 2.822 years and Pearson’s correlation coefficient (PCC) of 0.968, demonstrating the potential of the MGA module to improve the accuracy of brain age prediction

Estradiol and progesterone regulate NUCB2/nesfatin-1 expression and function in GH3 pituitary cells and THESC endometrial cells

ABSTRACTEstradiol (E2) and progesterone (P4) are essential sex steroid hormones that play critical roles in the pituitary gland and uterus. Recently, nesfatin-1, a polypeptide hormone that regulates appetite and energy homeostasis in the hypothalamus, was found to be expressed in the pituitary gland and uterus. In this study, we aimed to investigate the relationship between these two steroid hormones and the expression and function of nesfatin-1 in the pituitary gland and uterus using GH3 cells, a lacto-somatotroph cell line, and THESC cells, an endometrial stromal cell line. First, we verified the presence of nesfatin-1 and nesfatin-1 binding sites in GH3 and THESC cells. E2 increased the mRNA expression of NUCB2, the gene encoding the nesfatin-1 protein, in GH3 cells, while P4 had no significant effect. In THESC cells, NUCB2 mRNA expression was decreased by E2 but increased by P4. In addition, nesfatin-1 significantly increased growth hormone (GH) and prolactin (PRL) mRNA expression in GH3 cells, and E2 enhanced this effect. In THESC cells, nesfatin-1 significantly increased the mRNA expression of insulin-like growth factor binding protein 1 (IGFBP1) and PRL, which are decidualization marker genes, and P4 further enhanced this effect. These results suggest that nesfatin-1 may act as a local regulator of GH and PRL production in the pituitary gland and decidualization in the uterus, modulating its effects in response to E2 and P4