Relation between psychosocial variables and the glycemic control of patients with type 2 diabetes: A cross-sectional and prospective study

<p>Abstract</p> <p>Background</p> <p>This cross-sectional and prospective study used a variety of psychological inventories to evaluate the relationship between psychosocial factors and the glycemic control of patients with type 2 diabetes.</p> <p>Methods</p> <p>Participants were 304 patients with type 2 diabetes who were treated as outpatients at diabetes clinics. All participants were assessed for HbA_1cand completed the following self-report psychological inventories: 1) Diabetes Treatment Satisfaction Questionnaire (DTSQ), 2) Problem Areas in Diabetes Survey (PAID), 3) Well-being Questionnaire 12 (W-BQ12), 4) Self-Esteem Scale (SES), 5) Social Support Scale, and 6) Self-Efficacy Scale. HbA_1cwas again measured one year later. The relationships between the psychosocial variables obtained by analysis of the psychological inventories and baseline or one-year follow-up HbA_1cwere determined.</p> <p>Results</p> <p>Baseline HbA_1cwas significantly correlated with age, diet treatment regimen, number of microvascular complication of diabetes, and the total scores of DTSQ, W-BQ12, PAID, SES and the Self-Efficacy Scale. Hierarchical stepwise multiple regression revealed that significant predictors of baseline HbA_1cwere total DTSQ and PAID scores, along with age, diet treatment regimen, and number of microvascular complication of diabetes after adjustment for demographic, clinical and other psychosocial variables. Two hundred and ninety patients (95.4% of 304) were followed and assessed one year after baseline. Hierarchical stepwise multiple regression analysis showed the significant predictors of follow-up HbA_1cto be total DTSQ and PAID scores, along with age and diet treatment regimen. However, the correlation between baseline and follow-up HbA_1cwas so high that the only other variable to retain significance was diet treatment regimen once baseline HbA_1cwas included in the regression of follow-up HbA_1c.</p> <p>Conclusion</p> <p>The DTSQ and the PAID predicted both current and future HbA_1cto a similar and significant degree in patients with type 2 diabetes.</p

Pressure Effect on Transport Properties of EuNi(Si1-xGex)3 Compounds

AbstractThe compounds of EuNi(Si1−xGex)3 order antiferromagnetically. At the temperature TC below the Ńeel temperature TN, EuNiSi3 (x = 0) shows an additional magnetic transition into ferro-magnetic state. TN decreases monotonously with increasing the Ge composition x. The Curie temperature TC decreases rapidly with increasing x and vanishes at the critical composition x ≈ 0.3. We have measured the electrical resistivity and thermopower of EuNi(Si0.8Ge0.2)3, which is a compound near to the boundary between the ferromagnetic and antiferromagnetic ground states in the phase diagram for EuNi(Si1−xGex)3 system, under pressures up to 1.8GPa at temperatures from 2 to 300K. The anomalies in ρ(T) and S(T) curves of EuNi(Si0.8Ge0.2)3 are observed at TC = 16K and TN = 34K at ambient pressure. Both TC and TN increase linearly with increasing pressure. The temperature variations of ρ and S of EuNi(Si0.8Ge0.2)3 at P = 1.8GPa are almost the same as those of EuNi(Si0.9Ge0.1)3 (x=0.1) at ambient pressure, revealing that the effect of pressure on TN and TC is the same as that of the increase of Si concentration. The pressure and atomic composition dependences of the magnetic transition temperatures TN and TC can be expressed by using the Grüneisen parameters. These results indicate that the changes of TN and TC are attributed to the change of atomic volume induced by the applying pressure or the atomic substitution

Effects of Metabotropic Glutamate Receptor 3 Genotype on Phonetic Mismatch Negativity

BACKGROUND: The genetic and molecular basis of glutamatergic dysfunction is one key to understand schizophrenia, with the identification of an intermediate phenotype being an essential step. Mismatch negativity (MMN) or its magnetic counterpart, magnetic mismatch field (MMF) is an index of preattentive change detection processes in the auditory cortex and is generated through glutamatergic neurotransmission. We have previously shown that MMN/MMF in response to phoneme change is markedly reduced in schizophrenia. Variations in metabotropic glutamate receptor (GRM3) may be associated with schizophrenia, and has been shown to affect cortical function. Here we investigated the effect of GRM3 genotypes on phonetic MMF in healthy men. METHODS: MMF in response to phoneme change was recorded using magnetoencephalography in 41 right-handed healthy Japanese men. Based on previous genetic association studies in schizophrenia, 4 candidate SNPs (rs6465084, rs2299225, rs1468412, rs274622) were genotyped. RESULTS: GRM3 rs274622 genotype variations significantly predicted MMF strengths (p = 0.009), with C carriers exhibiting significantly larger MMF strengths in both hemispheres compared to the TT subjects. CONCLUSIONS: These results suggest that variations in GRM3 genotype modulate the auditory cortical response to phoneme change in humans. MMN/MMF, particularly those in response to speech sounds, may be a promising and sensitive intermediate phenotype for clarifying glutamatergic dysfunction in schizophrenia

DeepDyve: Dynamic Verification for Deep Neural Networks

Deep neural networks (DNNs) have become one of the enabling technologies in many safety-critical applications, e.g., autonomous driving and medical image analysis. DNN systems, however, suffer from various kinds of threats, such as adversarial example attacks and fault injection attacks. While there are many defense methods proposed against maliciously crafted inputs, solutions against faults presented in the DNN system itself (e.g., parameters and calculations) are far less explored. In this paper, we develop a novel lightweight fault-tolerant solution for DNN-based systems, namely DeepDyve, which employs pre-trained neural networks that are far simpler and smaller than the original DNN for dynamic verification. The key to enabling such lightweight checking is that the smaller neural network only needs to produce approximate results for the initial task without sacrificing fault coverage much. We develop efficient and effective architecture and task exploration techniques to achieve optimized risk/overhead trade-off in DeepDyve. Experimental results show that DeepDyve can reduce 90% of the risks at around 10% overhead

Safety information mining: What can NLP do in a disaster

Abstract This paper describes efforts of NLP researchers to create a system to aid the relief efforts during the 2011 East Japan Earthquake. Specifically, we created a system to mine information regarding the safety of people in the disaster-stricken area from Twitter, a massive yet highly unorganized information source. We describe the large scale collaborative effort to rapidly create robust and effective systems for word segmentation, named entity recognition, and tweet classification. As a result of our efforts, we were able to effectively deliver new information about the safety of over 100 people in the disasterstricken area to a central repository for safety information

Oleophobic/Adhesive Janus Self-Standing Films Modified with Bifurcated Short Fluorocarbon Chains as Transparent Oil Stain-Free Coating with Attachability

Oil stains negatively affect the performances of our belongings and industrial equipment. However, conventional oleophobic coatings contain complex nanostructures or long fluoroalkyl chains, which are environmentally unsafe and limit their applications. In addition, the integration of film transparency, flexibility, and oleophobicity represent extremely challenging tasks. Herein, we report self-standing oleophobic/adhesive Janus membranes with flexibility and transparency, which were composed of environmentally low impact materials: poly­(vinyl alcohol) (PVA)/SiO₂ nanoparticle composites modified with bifurcated short fluorocarbon chains via the sol–gel method. The optimized coating performed the oleophobicity (oleic acid sliding angle = 27.9°) and reduced more than 50% of oil adhesion on glass substrate. It also maintained its transparency (93.13% at wavelength of 550 nm) after the exposure to oil mist. Moreover, the coatings were able to attach to various substrates to provide them an oleophobicity. Our results demonstrate the important role to develop oleophobic coating materials with low environmental impact