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Metformin used as adjuvant therapy in youth with T1D and elevated BMI decreased total daily insulin dose (TDID) and insulin resistance, although hemoglobin A1c (A1c) did not change. Yet, the factors that are associated with greater benefit from metformin are not well known. Here, we tested whether baseline measures predict response to metformin in youth with T1D and increased BMI-z score. We analyzed publicly available data from the metformin treatment arm of the T1D Exchange Metformin Study (NCT01881828) , with 61 adolescents (median age 15.3 yrs, range 12-18.9; 36% males; 72% non-Hispanic Whites, 98% overweight or obese; median diabetes duration 7.4 yrs, range 1.7-15) . We assessed baseline age, sex, diabetes duration, race/ethnicity, BMI z-score, waist circumference, body fat percentage (BF%) measured by Dual-energy X-ray Absorptiometry (DXA) scan and serum adipokines. Outcome measures included changes in A1c, TDID and BF% at 13 and 26 weeks (wks) . After adjusting for baseline values, multiple linear regression models were used to identify predictors for the outcomes. Decreases in TDID at 13 and 26 wks showed a significant negative association with baseline leptin (p=0.0008, p=0.004, respectively) . Decreases in BF% at 26 wks were positively associated with baseline BMI z-score (p=0.03) and negatively associated with baseline BF% (p=0.0002) . Increase in A1c at 26 wks trended towards a positive association with baseline BF% (p=0.07) and a negative association with baseline adiponectin (p=0.06) . Compared to females, males showed a significant reduction in BF% at 26 wks (p Disclosure J.Wang: None. S.Barua: None. M.Tosur: Advisory Panel; Provention Bio, Inc. M.J.Redondo: Advisory Panel; Provention Bio, Inc. H.M.Ismail: n/a.

The gap between predicted brain age using magnetic resonance imaging (MRI) and chronological age may serve as a biomarker for early-stage neurodegeneration. However, owing to the lack of large longitudinal studies, it has been challenging to validate this link. We aimed to investigate the utility of such a gap as a risk biomarker for incident dementia using a deep learning approach for predicting brain age based on MRI-derived gray matter (GM). We built a convolutional neural network (CNN) model to predict brain age trained on 3,688 dementia-free participants of the Rotterdam Study (mean age 66 ± 11 y, 55% women). Logistic regressions and Cox proportional hazards were used to assess the association of the age gap with incident dementia, adjusted for age, sex, intracranial volume, GM volume, hippocampal volume, white matter hyperintensities, years of education, and APOE ε4 allele carriership. Additionally, we computed the attention maps, which shows which regions are important for age prediction. Logistic regression and Cox proportional hazard models showed that the age gap was significantly related to incident dementia (odds ratio [OR] = 1.11 and 95% confidence intervals [CI] = 1.05–1.16; hazard ratio [HR] = 1.11, and 95% CI = 1.06–1.15, respectively). Attention maps indicated that GM density around the amygdala and hippocampi primarily drove the age estimation. We showed that the gap between predicted and chronological brain age is a biomarker, complimentary to those that are known, associated with risk of dementia, and could possibly be used for early-stage dementia risk screening.

Big data disrupts everything it touches, but automotive is probably one of the top industries that enjoy and leverage the benefits. The Automotive Big Data Pipeline (ABDP) is a big data pipeline base on the automotive use case and is required to scale up agile and high performance in real-time or in batch. Nonetheless, there’re many alternative infrastructure designs but lack of knowledge, which fits the best for the automotive domain. It leads this paper into a question: What kinds of infrastructure design could provide better performance for the ABDP?In this paper, we introduce two well-known infrastructure designs called Hyper-Converged infrastructure (HCI) and Disaggregated Hyper-Converged infrastructure (DHCI). HCI combines standard data center hardware using locally attached storage resources to create fast, common building blocks. However, does single standard hardware fit all the requirements? DHCI scale independently from compute and storage provides an option. It provides a more cost-efficient and flexible solution; however, there is no comparison from the performance point of view. Therefore, to address it, our objective is to conduct an empirical performance comparison to see which one performs better.The experiment result shows that DHCI performs almost the same as HCI on CPU utilization, memory, and network consumption. However, regarding storage and running time metrics, DHCI performs slightly higher storage throughput, IOPs, and less running time than HCI.

Enantioselective conjunctive cross-coupling of enyne-derived boronate complexes occurs with 1,4 addition of the electrophile and migrating group across the π system. This reaction pathway furnishes α-boryl allenes as the reaction product. In the presence of a chiral catalyst, both the central and axial chirality of the product can be controlled during product formation.

Completing a construction project on time and within budget is of great importance in the construction industry. To achieve this goal, a construction plan satisfying the time and cost constraints is crucial. While a rich amount of literature on the time-cost trade-off scheduling and time/cost optimization scheduling has been presented, developing a construction plan for the time and cost-constrained construction project has not been fully explored. This study presented a hierarchical task network (HTN) based construction planning model to fill this gap. First of all, a knowledge formalism catering to the HTN planning was provided to accommodate the construction planning knowledge. Then, the planning process was explained in detail, including temporal reasoning used to sequence the construction activities, and backtracking evasion mechanism used to avoid the trouble of backtracking due to inappropriate selection of execution modes for construction activities. Finally, two sets of comparisons based on a fictional construction project were performed, the results of which demonstrate that the time and budget constraints have an impact on the section of execution modes for construction methods, and the proposed planning model can develop construction plan that satisfies the specified deadline and budget limitations effectively regardless of the existing of backtracking. First published online 8 April 2019

Key PointsQuestionIs the gap between brain age predicted from MRI and chronological age associated with incident dementia in a general population of Dutch adults?FindingsBrain age was predicted using a deep learning model, using MRI-derived grey matter density maps. In a population based study including 5496 participants, the observed gap was significantly associated with the risk of dementia.MeaningThe gap between MRI-brain predicted and chronological age is potentially a biomarker for dementia risk screening.AbstractImportanceThe gap between predicted brain age using magnetic resonance imaging (MRI) and chronological age may serve as biomarker for early-stage neurodegeneration and potentially as a risk indicator for dementia. However, owing to the lack of large longitudinal studies, it has been challenging to validate this link.ObjectiveWe aimed to investigate the utility of such a gap as a risk biomarker for incident dementia in a general Dutch population, using a deep learning approach for predicting brain age based on MRI-derived grey matter maps.DesignData was collected from participants of the cohort-based Rotterdam Study who underwent brain magnetic resonance imaging between 2006 and 2015. This study was performed in a longitudinal setting and all participant were followed up for incident dementia until 2016.SettingThe Rotterdam Study is a prospective population-based study, initiated in 1990 in the suburb Ommoord of in Rotterdam, the Netherlands.ParticipantsAt baseline, 5496 dementia- and stroke-free participants (mean age 64.67±9.82, 54.73% women) were scanned and screened for incident dementia. During 6.66±2.46 years of follow-up, 159 people developed dementia.Main outcomes and measuresWe built a convolutional neural network (CNN) model to predict brain age based on its MRI. Model prediction performance was measured in mean absolute error (MAE). Reproducibility of prediction was tested using the intraclass correlation coefficient (ICC) computed on a subset of 80 subjects. Logistic regressions and Cox proportional hazards were used to assess the association of the age gap with incident dementia, adjusted for years of education, ApoEε4 allele carriership, grey matter volume and intracranial volume. Additionally, we computed the attention maps of CNN, which shows which brain regions are important for age prediction.ResultsMAE of brain age prediction was 4.45±3.59 years and ICC was 0.97 (95% confidence interval CI=0.96-0.98). Logistic regression and Cox proportional hazards models showed that the age gap was significantly related to incident dementia (odds ratio OR=1.11 and 95% confidence intervals CI=1.05-1.16; hazard ratio HR=1.11 and 95% CI=1.06-1.15, respectively). Attention maps indicated that grey matter density around the amygdalae and hippocampi primarily drive the age estimation.Conclusion and relevanceWe show that the gap between predicted and chronological brain age is a biomarker associated with risk of dementia development. This suggests that it can be used as a biomarker, complimentary to those that are known, for dementia risk screening.

In this work, we report the synthesis of an three-dimensional (3D) cone-shape CNT clusters (CCC) via chemical vapor deposition (CVD) with subsequent inductively coupled plasma (ICP) treatment. An innovative silicon decorated cone-shape CNT clusters (SCCC) is prepared by simply depositing amorphous silicon onto CCC via magnetron sputtering. The seamless connection between silicon decorated CNT cones and graphene facilitates the charge transfer in the system and suggests a binder-free technique of preparing lithium ion battery (LIB) anodes. Lithium ion batteries based on this novel 3D SCCC architecture demonstrates high reversible capacity of 1954 mAh g(-1) and excellent cycling stability (1200 mAh g(-1) capacity with ≈ 100% coulombic efficiency after 230 cycles).

Summary Treating patients with multiple oral leucoplakias (MOLs) who smoke is more difficult and complicated than treating those with single oral leucoplakia (SOL). Removing the aetiological factors causing MOL can effectively prevent its recurrence. The aim was to study the infection by and influences of Candida in smoking patients with MOLs. A retrospective study was conducted on 136 smoking patients who had clinicopathological OLs. Among these patients, 73 lesions in 31 patients were MOLs, while 105 patients had SOLs. All patients were treated by complete resection. All specimens were tested for epithelial dysplasia, and stained with periodic acid–Schiff reagent. The rate of MOL concurrence with candidal infection was higher than that of SOLs. The incidence of Candida associated with MOLs was higher for recurrent than for non-recurrent lesions. The disease-free time was shorter in MOL patients with candidal infection. Moreover, MOLs with candidal infection were more likely to have an increasing ratio to combine with epithelial dysplasia. Candida is an important risk factor in smoking patients with MOLs. Microscopic and fungal examinations of those lesions should permit a detailed diagnosis in such patients and for long-term predictive assessments.

Treating patients with multiple oral leucoplakias (MOLs) who smoke is more difficult and complicated than treating those with single oral leucoplakia (SOL). Removing the aetiological factors causing MOL can effectively prevent its recurrence. The aim was to study the infection by and influences of Candida in smoking patients with MOLs. A retrospective study was conducted on 136 smoking patients who had clinicopathological OLs. Among these patients, 73 lesions in 31 patients were MOLs, while 105 patients had SOLs. All patients were treated by complete resection. All specimens were tested for epithelial dysplasia, and stained with periodic acid-Schiff reagent. The rate of MOL concurrence with candidal infection was higher than that of SOLs. The incidence of Candida associated with MOLs was higher for recurrent than for non-recurrent lesions. The disease-free time was shorter in MOL patients with candidal infection. Moreover, MOLs with candidal infection were more likely to have an increasing ratio to combine with epithelial dysplasia. Candida is an important risk factor in smoking patients with MOLs. Microscopic and fungal examinations of those lesions should permit a detailed diagnosis in such patients and for long-term predictive assessments.

Triplet anisotropy decay techniques have been used to measure the internal flexibility and overall rotational motions of DNA over a time range of 15 ns to 200 microseconds. Nearly monodisperse DNA fragments with lengths varying from 65 to 600 base pairs were studied using the intercalating dye methylene blue as a triplet probe. The slow end-over-end tumbling of short DNA fragments (less than 165 base pairs) is as predicted for a rigid rod. As expected, a longer DNA fragment (600 base pairs) experiences slow segmental motions of its helix axis. At the earliest times, anisotropy decays more rapidly than expected for a rigid rod, suggesting that, when it is bound, methylene blue monitors fast internal motions of the helix. Since the rod-like end-over-end tumbling rules out fast bending motions (for short DNA fragments), the fast components of DNA anisotropy decay must be due to twisting motions of the helix, occurring with a time constant near 50 ns. The same techniques were used to measure the conformational flexibility of DNA in the nucleosome. It is concluded that, when the DNA helix is wrapped to form a nucleosome, it experiences substantial internal flexibility, occurring with a time constant near 30 ns. The amplitude and time-scale of this motion appear to be similar to that seen in the uncomplexed DNA helix.