OR-013 One Year Outdoor and Daytime Aerobic Dance Practice Increased Serum 25(OH)D3 and PTH, but Decreased FSH Level of Postmenopausal Women

Objective Vitamin D deficiency is widespread in postmenopausal women. It is verified that Vitamin D3 supplementation intake can improve the Vitamin D3 level of those Vitamin D deficiency patients. In addition to the exogenous intake, whether aerobic exercise plus sunshine could affect vitamin D level in postmenopausal women gained our attention.  Methods 16 postmenopausal women in Shanghai attended this test. They voluntarily participated in a one year aerobics plan, practicing Chinese traditional dance outdoor under sunshine for one hour from 9:30-10:30 am each day. Before and after one year practice, serum 25(OH)D, 25(OH)D3 and estradiol E2, follicle stimulating hormone(FSH), luteinizing hormone(LH), parathyroid hormone(PTH) of all participants were analyzed.  Results Before aerobics practice, serum 25(OH)D and 25(OH)D3 levels were 16.30±4.12(ng/ml) and 15.60±3.79(ng/ml). After one year practice, the data were significantly increased 19.50% (P=0.002) and 18.78% (P=0.002), separately. Before aerobics practice, the state of 25(OH)D level of 13 women was inadequacy (≤20.0ng/ml), 3 women was in lack status (20-30ng/ml). After one year practice, 9 women was inadequacy, 7 women in lack. The value of the chi square test was 4.747(P=0.029). After one year practice, serum PTH significantly increased, while FSH significantly decreased. E2 and LH had no significant variance before and after one year of aerobics practice.   Conclusions One year aerobics practice under sunshine could increase serum 25(OH)D level, and affected estrogen levels variably in postmenopausal women.

Effect of Exogenous Nitric Oxide on Postharvest Storage Quality of Hyacinth Bean

In order to study the effect of nitric oxide (NO) on the storage quality of hyacinth bean after harvest, sodium nitroprusside (SNP) was used as an exogenous NO donor in this study. Hyacinth bean was soaked in 0.2 mmol/L SNP solution or distilled water as control for 10 min and then stored at (20 ± 1) ℃ and 80%–90% relative humidity. Decay incidence, rust incidence, hardness, the contents of total soluble solids (TSS), malondialdehyde (MDA), flavonoids, total phenols and chlorophyll, and the activities of antioxidant enzymes (peroxidase (POD), polyphenol oxidase (PPO), phenylalanine ammoniase (PAL), catalase (CAT) and ascorbate peroxidase (APX)) were observed during the storage period. The results showed that exogenous NO treatment could inhibit the rot and rust, keep the color and hardness, and inhibit the degradation of TSS and chlorophyll in hyacinth bean, so that hyacinth bean could maintain good sensory quality. Exogenous NO treatment could also prevent the accumulation of MDA and increase the contents of total phenols and flavonoids. In addition, exogenous NO treatment maintained the activities of PAL, CAT and APX during storage, and inhibited the increase in the activities of POD and PPO, thereby enhancing the antioxidant capacity and delaying the maturation and senescence of hyacinth bean. In conclusion, exogenous NO treatment can delay the postharvest maturation and senescence, maintain the physiological quality during storage, and effectively prolong the shelf life of hyacinth bean

Reduced SV2A and GABAA_A receptor levels in the brains of type 2 diabetic rats revealed by [18^{18}F]SDM-8 and [18^{18}F]flumazenil PET

PURPOSE: Type 2 diabetes mellitus (T2DM) is associated with a greater risk of Alzheimer's disease. Synaptic impairment and protein aggregates have been reported in the brains of T2DM models. Here, we assessed whether neurodegenerative changes in synaptic vesicle 2 A (SV2A), γ-aminobutyric acid type A (GABA$_A$) receptor, amyloid-β, tau and receptor for advanced glycosylation end product (RAGE) can be detected in vivo in T2DM rats. Methods: Positron emission tomography (PET) using [$^{18}$F]SDM-8 (SV2A), [$^{18}$F]flumazenil (GABA$_A$ receptor), [$^{18}$F]florbetapir (amyloid-β), [$^{18}$F]PM-PBB3 (tau), and [$^{18}$F]FPS-ZM1 (RAGE) was carried out in 12-month-old diabetic Zucker diabetic fatty (ZDF) and SpragueDawley (SD) rats. Immunofluorescence staining, Thioflavin S staining, proteomic profiling and pathway analysis were performed on the brain tissues of ZDF and SD rats. Results: Reduced cortical [$^{18}$F]SDM-8 uptake and cortical and hippocampal [$^{18}$F]flumazenil uptake were observed in 12-month-old ZDF rats compared to SD rats. The regional uptake of [$^{18}$F]florbetapir and [$^{18}$F]PM-PBB3 was comparable in the brains of 12-month-old ZDF and SD rats. Immunofluorescence staining revealed Thioflavin S-negative, phospho-tau-positive inclusions in the cortex and hypothalamus in the brains of ZDF rats and the absence of amyloid-beta deposits. The level of GABA$_A$ receptors was lower in the cortex of ZDF rats than SD rats. Proteomic analysis further demonstrated that, compared with SD rats, synaptic-related proteins and pathways were downregulated in the hippocampus of ZDF rats. Conclusion: These findings provide in vivo evidence for regional reductions in SV2A and GABA$_A$ receptor levels in the brains of aged T2DM ZDF rats

The impact of the Wenchuan earthquake on early puberty: a natural experiment

Background The factors influencing pubertal timing have gained much attention due to a secular trend toward earlier pubertal onset in many countries. However, no studies have investigated the association between the Great earthquake and early puberty. We aimed to assess whether the Wenchuan earthquake is associated with early puberty, in both boys and girls. Methods We used data from two circles of a survey on reproductive health in China to explore the impact of the Wenchuan earthquake on early puberty , and a total of 9,785 adolescents (4,830 boys, 49.36%) aged 12–20 years from 29 schools in eight provinces were recruited. Wenchuan earthquake exposure was defined as those Sichuan students who had not experienced oigarche/menarche before May 12, 2008. Early puberty was identified as a reported onset of oigarche/menarche at 11 years or earlier. We tested the association between the Wenchuan earthquake and early puberty in boys and girls. Then, subgroup analysis stratified by the age at earthquake exposure also was performed. Results In total, 8,883 adolescents (4,543 boys, 51.14%) with a mean (SD) age of 15.13 (1.81) were included in the final sample. In general, children exposed to the earthquake had three times greater risk of early puberty (boys, RR [95% CI] = 3.18 [2.21–4.57]; girls: RR [95%CI] =3.16 [2.65–3.78]). Subgroup analysis showed that the adjusted RR was 1.90 [1.19–3.03] for boys and 2.22 [1.75–2.80] for girls. Earthquake exposure predicted almost a fourfold (RR [95%CI] = 3.91 [1.31–11.72]) increased risk of early puberty in preschool girls, whereas the increase was about twofold (RR [95%CI] = 2.09 [1.65–2.64]) in schoolgirls. Among boys, only older age at earthquake exposure was linked to early puberty (RR [95%CI] = 1.93 [1.18–3.16]). Conclusions Wenchuan earthquake exposure increased the risk of early puberty in boys and girls, and preschoolers were more at risk than schoolchildren. The implications are relevant to support policies for those survivors, especially children, to better rebuild after disasters

Focus on Point: Parallel Multiscale Feature Aggregation for Lane Key Points Detection

Lane detection, as a basic environmental perception task, plays a significant role in the safety of automatic driving. Modern lane detection methods have obtained a better performance in most scenarios, but many are unsatisfactory in various scenarios, with a weak appearance (e.g., serious vehicle occlusion, dark shadows, ambiguous markings, etc.), and have issues in simplifying model predictions and flexibly detecting lanes of a non-fixed structure and number. In this work, we abstracted the lane lines as a series of discrete key points and proposed a lane detection method of parallel multi-scale feature aggregation based on key points, FPLane. The main task of FPLane is to focus on the precise location of key points in the global lanes and aggregate the global detection results into the local geometric modeling of lane lines by using the idea of association embedding. Furthermore, this work proposes the parallel Multi-scale Feature Aggregation network (MFANet) in FPLane integrating the context information of multi-scale feature mappings to take full advantage of the prior information of adjacent positions. In addition, MFANet incorporates the Double-headed Attention Feature Fusion Up-sampling module, which can facilitate the network to accurately recognize and detect objects under extreme scale variation. Finally, our method is tested on Tusimple and CULane lane detection datasets; the results show that the proposed method outperforms the current mainstream methods: the accuracy and F1-score of the model are 96.82% and 75.6%, respectively, and the real-time detection efficiency of the model can maintain 28 ms

Analysis and Optimization of the Vibration and Noise of a Double Planetary Gear Power Coupling Mechanism

As the key component of a hybrid electric vehicle (HEV), the dynamic performance of the power coupling mechanism is found to have a significant effect upon the vibration and noise of the whole vehicle. In this paper, a dynamic model with rigid and flexible bodies of a double planetary gear power coupling mechanism is established. Then, the characteristics of the bearing constraining forces in time domain and frequency domain are simulated and analysed. At the same time, the finite element model of the housing of the power coupling mechanism is established. Then, the vibration response of the housing is analysed under the excitation of the bearing constraining forces, and the vibration displacement of the housing surface is obtained. Furthermore, based on the vibration displacement of the housing surface, a prediction model of housing radiating noise is established. Then, the radiating noise characteristics of the housing and the acoustic contribution of each panel are analysed. Finally, the free damping structure and new stiffener structure are adopted to optimize the rear end cover of the housing. The optimization model based on the vibration acceleration of the rear end cover surface is established by applying K-S function and response surface method. Then, the optimization model is solved by applying the sequential quadratic programming to obtain the optimal structure of the housing. The optimization results demonstrate that the acoustic power level after optimization is decreased by 3.94 dB, 3.92 dB, 5.59 dB, and 2.84 dB at frequencies of 770 Hz, 870 Hz, 1650 Hz, and 2480 Hz, respectively. Therefore, the optimization effect of the housing structure is obvious, and this can be the theoretical basis and reference for reducing the vibration and noise of the power coupling mechanism

Parallel Array Bistable Stochastic Resonance System with Independent Input and Its Signal-to-Noise Ratio Improvement

We study the design enhancement of the bistable stochastic resonance (SR) performance on sinusoidal signal and Gaussian white noise. The bistable system is known to show an SR property; however the performance improvement is limited. Our work presents two main contributions: first, we proposed a parallel array bistable system with independent components and averaged output; second, we give a deduction of the output signal-to-noise ratio (SNR) for this system to show the performance. Our examples show the enhancement of the system and how different parameters influence the performance of the proposed parallel array

Coordinated Control for Driving Mode Switching of Hybrid Electric Vehicles

Taking a hybrid electric vehicle using double-row planetary gear power coupling mechanism as a research object, this study proposes a coordinated control algorithm of “torque distribution, engine torque monitoring, and motor torque compensation” in an attempt to realize coordinated control for driving mode switching. Characteristic analysis of the power coupling mechanism was carried out, and the control strategy model in MATLAB/Simulink was built. Subsequently, the analysis of mode switching from the electric mode into joint driving mode was simulated. In addition, a multibody dynamics model of the power coupling mechanism was established and the simulation analysis during mode switching process was carried out. The results show that the proposed coordinated control strategy serves to effectively reduce the torque fluctuation and the impact degree during the mode switching process and improve the ride comfort of the vehicle. In the meantime, the time-domain and frequency-domain characteristics of gear meshing force and bearing restraint force indicate that the mode switching process of the dynamic coupling mechanism is quite stable and this control strategy contributes to improving the characteristics such as vibration and noise

Alzheimer’s Disease Prediction via Brain Structural-Functional Deep Fusing Network

Fusing structural-functional images of the brain has shown great potential to analyze the deterioration of Alzheimer’s disease (AD). However, it is a big challenge to effectively fuse the correlated and complementary information from multimodal neuroimages. In this work, a novel model termed cross-modal transformer generative adversarial network (CT-GAN) is proposed to effectively fuse the functional and structural information contained in functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI). The CT-GAN can learn topological features and generate multimodal connectivity from multimodal imaging data in an efficient end-to-end manner. Moreover, the swapping bi-attention mechanism is designed to gradually align common features and effectively enhance the complementary features between modalities. By analyzing the generated connectivity features, the proposed model can identify AD-related brain connections. Evaluations on the public ADNI dataset show that the proposed CT-GAN can dramatically improve prediction performance and detect AD-related brain regions effectively. The proposed model also provides new insights into detecting AD-related abnormal neural circuits