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BackgroundThe association between physical fitness performance tests and anthropometric indices is not clear. The study aims to explore the association between physical fitness performance and anthropometric indices in Taiwanese community-dwelling adults. This may help in monitoring anthropometric indices to improve physical fitness.MethodsWe recruited 2216 participants aged 23–64 years between 2014 and 2017. Physical fitness performance, including abdominal muscular endurance (60-s sit-up test), flexibility (sit-and-reach test), and cardiorespiratory endurance (3-min step test), was evaluated in all participants. The association of the physical fitness performance and anthropometric indices, including body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR), was analyzed using linear regression, with adjustments for age and gender.ResultsBody mass index was negatively associated with abdominal muscular endurance (p < 0.001) and cardiorespiratory endurance (p < 0.001). Neither BMI, WC, WHR, nor WHtR were significantly associated with flexibility. Abdominal muscle endurance, flexibility, and cardiorespiratory endurance were significantly lower in obese participants when obesity was defined using a BMI of ≥27, 30, and 35 kg/m2. Participants with central obesity that was defined as WC ≥ 90 cm in men and 80 cm in women and WHtR ≥ 0.6 had lower abdominal muscular endurance than those without central obesity.ConclusionBody mass index is associated with abdominal muscular endurance and cardiorespiratory endurance in a reverse J-shaped manner. None of the anthropometric indices are significantly associated with flexibility. Obesity defined by BMI is linked to worse physical fitness performance and obesity defined using WHtR is linked to lower abdominal muscular endurance in Taiwanese community-dwelling adults.

BackgroundThe extent and depth of BK polyomavirus (BKPyV) infection in renal allograft correlate with prognosis. This study was designed to evaluate the value of urinary sediment double-immunostaining for predicting BKPyV infection in proximal tubular epithelium.Materials and methodsA total of 76 urine sediment cell blocks, as well as the corresponding transplanted kidney tissues with BK polyomavirus associated-nephropathy (BKPyVAN), were evaluated by automatic double-immunostaining with anti-58-kDa Golgi protein (58K, a proximal renal tubular marker) + anti-SV40-T and anti-homogentisate 1, 2-dioxygenase (HGD, a renal tubular marker) + anti-SV40-T.ResultsImmunohistochemical staining demonstrated that 58K was expressed in proximal tubular epithelium but not in distal tubular epithelium or transitional epithelium. Of the 76 patients, 28 (36.8%) had urinary 58K(+)/SV40-T(+) cells and HGD(+)/SV40-T(+) cells, 41 (53.9%) had only HGD(+)/SV40-T(+) cells, one (1.3%) had only 58K(+)/SV40-T(+) cells, and six (7.9%) had only 58K(−)/HGD(−)/SV40-T(+) cells. The presence of urinary 58K(+)/SV40-T(+) cells was correlated with BKPyV infection in proximal tubular epithelium (P < 0.001, r = 0.806). The mean extent of SV40-T staining was significantly more extensive in patients with urinary 58K(+)/SV40-T(+) cells than those without urinary 58K(+)/SV40-T(+) cells (21.4 vs. 12.0%, P < 0.001). The positive predictive value, negative predictive value, sensitivity, and specificity of urinary 58K(+)/SV40-T(+) cells for predicting BKPyV infection in proximal tubular epithelium were 89.7% (95% CI: 71.5–97.3%), 91.5% (95% CI: 78.7–97.2%), 86.7% (95% CI: 68.4–95.6%), and 93.5% (95% CI: 81.1–98.3%), respectively.ConclusionUrinary sediment double-immunostaining with anti-58K and anti-SV40-T is valuable for predicting the extent and depth of BKPyV infection in renal allograft.

Background: Depression is associated with inflammation and Alzheimer's disease (AD). However, detailed molecular mechanisms linking mood, neuroinflammation and AD remain unclear. Although changes in peripheral inflammatory factors such as Interleukin 18 (IL18), and AD-associated amyloid-β (Aβ) peptides have been linked to depression, a solid relationship between these factors in depressive disorder has yet to be established. This study aims to further determine whether plasma IL18, Aβ40, Aβ42, and the AD-associated tangle component Tau, as well as IL18 single nucleotide polymorphisms (SNPs) may be biomarkers for depression. Methods: We measured plasma IL18, Aβ40, Aβ42, and Tau in 64 depressive patients and 75 healthy controls, and characterized genotypes of three IL18 SNPs (rs187238, rs1946518 and rs1946519) in these subjects. Comparisons between depressive patients and controls were carried out in males, in females or in combination. Regression analyses were conducted to examine the correlation between these parameters. Results: We found that none of the plasma levels of IL18, Aβ40, Aβ42, and Tau, the ratio of Aβ42/Aβ40, and the genotypes of IL18 SNPs were significantly different between combined depressive patients and combined healthy controls, or between male depressive patients and male controls. However, IL18 levels were less in females than in males in healthy people and were significantly increased in female depressive patients compared to female controls. Moreover, IL18 and standardized IL18 were correlated with standardized Aβ42/Aβ40 ratio and standardized Tau in depressive patients. Conclusions: Plasma IL18 may be a potential biomarker for depression in women. Keywords: Alzheimer's disease, Amyloid-β, Depression, Inflammation, Interleukin 18, Tau

Abstract The abuse of antibiotics and following rapidly increasing of antibiotic-resistant pathogens is the serious threat to our society. Natural products from microorganism are regarded as the important substitution antimicrobial agents of antibiotics. We isolated a new strain, Bacillus sp. GFP-2, from the Chiloscyllium plagiosum (Whitespotted bamboo shark) intestine, which showed great inhibitory effects on the growth of both Gram-positive and Gram-negative bacteria. Additionally, the growth of salmon was effectively promoted when fed with inactivated strain GFP-2 as the inhibition agent of pathogenic bacteria. The genes encoding antimicrobial peptides like LCI, YFGAP and hGAPDH and gene clusters for secondary metabolites and bacteriocins, such as difficidin, bacillibactin, bacilysin, surfactin, butirosin, macrolactin, bacillaene, fengycin, lanthipeptides and LCI, were predicted in the genome of Bacillus sp. GFP-2, which might be expressed and contribute to the antimicrobial activities of this strain. The gene encoding β-1,3-1,4-glucanase was successfully cloned from the genome and this protein was detected in the culture supernatant of Bacillus sp. GFP-2 by the antibody produced in rabbit immunized with the recombinant β-1,3-1,4-glucanase, indicating that this strain could express β-1,3-1,4-glucanase, which might partially contribute to its antimicrobial activities. This study can enhance a better understanding of the mechanism of antimicrobial activities in genus Bacillus and provide a useful material for the biotechnology study in antimicrobial agent development.

Red blood cell (RBC) storage solution is used for suspending and preserving RBCs for later use in in vitro immunohematology testing. Proper RBC preservation is crucial for obtaining accurate results in RBC phenotyping and pretransfusion antibody screening tests. Haemolysis or RBC antigen degradation during storage can result in inaccurate RBC phenotyping, thereby decreasing the sensitivity of pretransfusion antibody screening and identification assays. The conventional RBC storage solutions usually contain adenosine, adenine, and antibiotics. We designed an RBC storage solution and determined whether it could preserve RBC integrity for 70 days. The new storage solution has a different formula from that of the conventional solution—in particular, it is strengthened with polyethylene glycol (PEG). The extent of haemolysis and hemagglutination reactivity of the RBC antigen systems, Rh, Duffy, Kidd, Lewis, MNS, P1, and the rare antigen Mia (which has a low prevalence antigen in most parts of the world but a higher prevalence in Taiwan), in the new RBC storage solution was compared with that of the conventionally preserved RBC storage solution. The RBCs preserved in the new solution for 70 days retained a similar haemolysis grade as those preserved in the control solution for 28 days. Although both solutions largely preserved RBC antigenicity, the decline in RBC hemagglutination scores in new solution often occurred later than that in the control solution in most antigen phenotyping assays, especially labile antigens such as D, P1, and M. The new solution reduces haemolysis more effectively and preserves antigenicity throughout the 70-day storage period. Moreover, Mia antigen is more stable in the experimental group. [ABSTRACT FROM AUTHOR]

Accurate traffic flow parameters are the supporting data for analyzing traffic flow characteristics. Vehicle detection using traffic surveillance pictures is a typical method for gathering traffic flow characteristics in urban traffic scenes. In complicated lighting conditions at night, however, neither classical nor deep-learning-based image processing algorithms can provide adequate detection results. This study proposes a fusion technique combining millimeter-wave radar data with image data to compensate for the lack of image-based vehicle detection under complicated lighting to complete all-day parameters collection. The proposed method is based on an object detector named CenterNet. Taking this network as the cornerstone, we fused millimeter-wave radar data into it to improve the robustness of vehicle detection and reduce the time-consuming postcalculation of traffic flow parameters collection. We collected a new dataset to train the proposed method, which consists of 1000 natural daytime images and 1000 simulated nighttime images with a total of 23094 vehicles counted, where the simulated nighttime images are generated by a style translator named CycleGAN to reduce labeling workload. Another four datasets of 2400 images containing 20161 vehicles were collected to test the proposed method. The experimental results show that the method proposed has good adaptability and robustness at natural daytime and nighttime scenes., Author(s): Shaojie Jin [1]; Ying Gao [1]; Shoucai Jing [1]; Fei Hui (corresponding author) [1]; Xiangmo Zhao [1]; Jianzhen Liu [2] 1. Introduction Traffic flow parameters are the most fundamental [...]

Lane changing is an important scenario in traffic environments, and accurate prediction of lane-changing behavior is essential to ensure traffic and driver safety. To achieve this goal, a vehicle lane-changing prediction model based on game theory and deep learning is developed. In the game theory component, the interaction between vehicles during lane changing is analyzed according to the running state of the vehicle, with the probability of lane changing as its output. For the deep-learning component, long short-term memory and a convolutional neural network are used to extract and learn data features during the lane-changing process as well as combine the output of the game theory component to obtain the prediction result of whether the vehicle will change lanes. By using an open-source traffic dataset to train and verify the proposed model, the verification results show that the prediction accuracy can reach 94.56% within 0.4s of lane-changing operation and that the model can achieve timely and accurate prediction of the lane-changing behavior of vehicles., Author(s): Shuo Jia [1]; Fei Hui (corresponding author) [1]; Cheng Wei [1]; Xiangmo Zhao [1]; Jianbei Liu [2] 1. Introduction Drivers' driving operations are closely related to road traffic safety; [...]

Vehicle platooning is a perspective technique for intelligent transportation systems (ITS). Connected and automated vehicles (CAVs) use dedicated short-range communication (DSRC) to form a convoy, in which the following vehicles can receive the information from their preceding vehicles to achieve safe automated driving and maintain a short headway. Consequently, a vehicle platoon can improve traffic safety and efficiency, further reducing fuel consumption. However, emergency braking inevitably occurs when the platoon meets an accident or a sudden mechanical failure. It is more critical when the wireless communication got delays. Therefore, “how to predefine a minimum safe distance (MSD) considering communication delay” is a challenging issue. To this end, a series of field tests were carried out to measure the communication delay of IEEE 802.11p that is the underlying protocol of DSRC. Subsequently, MSD is modeled and analyzed when the platoon travels at accelerating, cruising, and decelerating states. More importantly, the results of field tests are applied in the models to investigate the impact of communication delay on MSD in practice. The simulation results verify that the proposed model can effectively maintain the platooning vehicles' safety even if emergency braking happens with certain communication delays., Author(s): Mengyan Hu [1]; Xiangmo Zhao [1]; Fei Hui [1]; Bin Tian (corresponding author) [1]; Zhigang Xu [1]; Xinrui Zhang [1] 1. Introduction Nowadays, roadway traffic continues to cause congestion, [...]

A correct lane-changing plays a crucial role in traffic safety. Predicting the lane-changing behavior of a driver can improve the driving safety significantly. In this paper, a hybrid neural network prediction model based on recurrent neural network (RNN) and fully connected neural network (FC) is proposed to predict lane-changing behavior accurately and improve the prospective time of prediction. The dynamic time window is proposed to extract the lane-changing features which include driver physiological data, vehicle kinematics data, and driver kinematics data. The effectiveness of the proposed model is validated through the experiments in real traffic scenarios. Besides, the proposed model is compared with five prediction models, and the results show that the proposed prediction model can effectively predict the lane-changing behavior more accurate and earlier than the other models. The proposed model achieves the prediction accuracy of 93.5% and improves the prospective time of prediction by about 2.1s on average., Author(s): Cheng Wei [1]; Fei Hui (corresponding author) [1]; Asad J. Khattak [1,2] 1. Introduction Driver lane-changing behavior is a key factor in driving safety. An improper lane-changing behavior may [...]