[A study on the dual use of e-cigarettes and cigarettes among adolescents in Shandong Province]

Objective: To understand the current status and its associated factors of dual use of e-cigarettes and cigarettes among adolescents in Shandong Province and explore the reasons for dual use behavior. Methods: A self-administered survey was conducted among 7 999 middle school students who were selected by stratified multi-stage cluster sample method. Data were weighted and analyzed by the SPSS 25.0 complex program. Results: In Shandong Province, the prevalence rates of attempting and current dual use of e-cigarettes and cigarettes among adolescents appeared as 7.7% and 1.3%, respectively. Male, friends smoking, and secondhand smoke exposure in the past 7 days were risk factors for dual use. Compared with cigarette smokers, dual users have no differences in cognition and behavior in quitting smoking (P>0.05). The main reason for dual users to smoke e-cigarettes was curiosity. Conclusions: Dual use of e-cigarettes and cigarettes is common among adolescents in Shandong Province, and its influencing factors are similar to traditional cigarettes. Dual use is not a transitional stage for smoking cessation. Dual users are more likely to continue smoking in the future, which should be paid attention and concern.

Biomechanical Consequences of Walking with the Suspended Backpacks

OBJECTIVE

This article aimed to investigate the biomechanical mechanisms underlying the energetic advantages of the suspended backpacks during load carriage.

METHODS

In this study, we examined eight adults walking with a 15 kg load at 5 km/h with a designed suspended backpack, in which the load could be switched to locked and suspended with four combinations of stiffness. Mechanical work and metabolic cost were measured during load carriage.

RESULTS

The results showed that the suspended backpacks led to an average reduction of 23.35% in positive work, 24.77% in negative work, and a 12.51% decrease in metabolic cost across all suspended load conditions. Notably, the decreased mechanical work predominantly occurred during single support (averaging 84.19% and 71.16% for positive and negative work, respectively), rather than during double support.

CONCLUSION

Walking with the suspended backpack induced a phase shift between body movement and load movement, altering the human-load interaction. This adjustment caused the body and load to move against each other, resulting in flatter trajectories of the human-load system center of mass (COM) velocities and corresponding profiles in ground reaction forces (GRFs), along with reduced vertical excursions of the trunk. Consequently, this interplay led to flatter trajectories in mechanical work rate and reduced mechanical work, ultimately contributing to the observed reduction in energetic expenditure.

SIGNIFICANCE

Understanding these mechanisms is essential for the development of more effective load-carrying devices and strategies in various applications, particularly for enhancing walking abilities during load carriage.

A Probability Fusion Approach for Foot Placement Prediction in Complex Terrains

Prediction of foot placement presents great potential in better assisting the walking of people with lower-limb disability in daily terrains. Previous researches mainly focus on foot placement prediction in level ground walking, however these methods cannot be applied to daily complex terrains including ramps, stairs, and level ground with obstacles. To predict foot placement in complex terrains, this paper presents a probability fusion approach for foot placement prediction in complex terrains which consists of two parts: model training and foot placement prediction. In the first part, a deep learning model is trained on augmented data to predict the probability distribution of preliminary foot placement. In the second part, environmental information and human walking constraints are used to calculate the feasible area, and finally the feasible area is fused with the probability distribution of preliminary foot placement to predict the foot placement in complex terrains. The proposed method can predict the foot placement of next step in complex terrains when heel-off is detected. Experiments (including structured terrains experiments and complex terrains experiments) show that the root mean square error (RMSE) of prediction is 8.19 ± 1.20 cm, which is less than 8% of the average stride length, and the landing feasible area accuracy (LFAA) of prediction is 95.11 ± 3.09%. Comparing with existing foot placement prediction studies, the method proposed in this paper achieves faster and more accurate prediction in complex terrains.

Neural Correlation of EEG and Eye Movement in Natural Grasping Intention Estimation

Decoding the user's natural grasp intent enhances the application of wearable robots, improving the daily lives of individuals with disabilities. Electroencephalogram (EEG) and eye movements are two natural representations when users generate grasp intent in their minds, with current studies decoding human intent by fusing EEG and eye movement signals. However, the neural correlation between these two signals remains unclear. Thus, this paper aims to explore the consistency between EEG and eye movement in natural grasping intention estimation. Specifically, six grasp intent pairs are decoded by combining feature vectors and utilizing the optimal classifier. Extensive experimental results indicate that the coupling between the EEG and eye movements intent patterns remains intact when the user generates a natural grasp intent, and concurrently, the EEG pattern is consistent with the eye movements pattern across the task pairs. Moreover, the findings reveal a solid connection between EEG and eye movements even when taking into account cortical EEG (originating from the visual cortex or motor cortex) and the presence of a suboptimal classifier. Overall, this work uncovers the coupling correlation between EEG and eye movements and provides a reference for intention estimation.

Fully Automatic Dual-Probe Lung Ultrasound Scanning Robot for Screening Triage

Two-dimensional lung ultrasound (LUS) has widely emerged as a rapid and noninvasive imaging tool for the detection and diagnosis of coronavirus disease 2019 (COVID-19). However, image differences will be magnified due to changes in ultrasound (US) imaging experience, such as US probe attitude control and force control, which will directly affect the diagnosis results. In addition, the risk of virus transmission between sonographer and patients is increased due to frequent physical contact. In this study, a fully automatic dual-probe US scanning robot for the acquisition of LUS images is proposed and developed. Furthermore, the trajectory was optimized based on the velocity look-ahead strategy, the stability of contact force of the system and the scanning efficiency were improved by 24.13% and 29.46%, respectively. Also, the control ability of the contact force of robotic automatic scanning was 34.14 times higher than that of traditional manual scanning, which significantly improves the smoothness of scanning. Importantly, there was no significant difference in image quality obtained by robotic automatic scanning and manual scanning. Furthermore, the scanning time for a single person is less than 4 min, which greatly improves the efficiency of screening triage of group COVID-19 diagnosis and suspected patients and reduces the risk of virus exposure and spread.

Effect of emodin combined with cisplatin on the invasion and migration of HepG2 hepatoma cells

Cisplatin is the leading chemotherapy agent for advanced liver cancer. However, the resistance to cisplatin in liver cancer reduces its efficacy. A potential strategy to increase its effectiveness and reduce toxicity is to combine cisplatin with 1,3,8-trihydroxy-6-methylanthraquinone (emodin). In this study, we examined the effects of emodin combined with cisplatin on the invasion and migration of HepG2 cells and analyzed the role of emodin. The effects of cisplatin, emodin and their combination were assessed in HepG2 cells. Proliferation, invasion and migration of HepG2 cells were examined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT), scar and Transwell assays. The gelatinase spectrum and an ELISA detected the expression of matrix metallopeptidase 2 (MMP-2) and matrix metallopeptidase 9 (MMP-9). The expression of E-cadherin and vimentin was detected by immunofluorescence and Western blots. Emodin inhibited cell invasion and migration in HepG2 hepatoma cells, increased E-cadherin expression, decreased vimentin, MMP-2, and MMP-9 expression. The combination of emodin and cisplatin-induced a more significant effect in a dose-dependent manner. In this study, we found that emodin inhibited hepatocellular carcinoma (HCC) metastasis. Compared with either cisplatin or emodin alone, the combination of both showed a more significant synergistic effect. Emodin can enhance the sensitivity of HepG2 HCC cells to cisplatin by inhibiting epithelial-mesenchymal transition, and thus, play a role in preventing recurrence and metastasis in HCC.

An Intelligent Rehabilitation Assessment Method for Stroke Patients based on Lower Limb Exoskeleton Robot

The 6-min walk distance (6MWD) and the Fugl-Meyer assessment lower-limb subscale (FMA-LE) of the stroke patients provide the critical evaluation standards for the effect of training and guidance of the training programs. However, gait assessment for stroke patients typically relies on manual observation and table scoring, which raises concerns about wasted manpower and subjective observation results. To address this issue, this paper proposes an intelligent rehabilitation assessment method (IRAM) for rehabilitation assessment of the stroke patients based on sensor data of the lower limb exoskeleton robot. Firstly, the feature parameters of the patient were collected, including age, height, and duration, etc. The sensor data of the exoskeleton robot were also collected, including joint angle, joint velocity, and joint torque, etc. Secondly, a gait feature model was constructed to deduce the walking gait parameters of the patient according to the sensor data of the exoskeleton, including the support phase to swing phase ratio, step length and leg lift height of the patient, etc. Then, the 6MWD and FMA-LE values were collected by traditional methods, feature parameters, gait parameters and human-machine interaction parameters (joint torque) of the patient were adopted to train the rehabilitation assessment model. Finally, the assessment model was trained by a machine-learning based algorithm. The new stroke patients' the 6MWD and FMA-LE values can be predicted by the trained model. The experimental results present that the prediction accuracy for the 6MWD and FMA-LE values reach to 85.19% and 92.66%, respectively.

[Clinical analysis of multiple myeloma with second primary malignancies and multiple myeloma secondary to malignancies]

Objective: To compare the clinical characteristics and survival outcomes of multiple myeloma (MM) with second primary malignancies (SPMs) and MM secondary to malignancies. Methods: The clinical data of MM patients diagnosed and treated in Beijing Chaoyang Hospital, Capital Medical University from January 2002 to January 2021 were included. The patients were divided into two groups: MM with SPMs group and MM secondary to malignancies group. The gender, age at first diagnosis, classification, stage, type of combined malignant tumor and the treatment were analyzed. The clinical characteristics and survival differences were compared between the two groups. Results: There were 20 patients in the MM with SPMs group, 9 males and 11 females, aged [M(Q₁,Q₃)] 61.5(56.8, 68.0)years, and the overall survival (OS) was 49.5(32, 58) months, while the time to death from secondary tumor was 12(4,21)months. There were 29 patients in the MM secondary to malignancies group, 13 males and 16 females, aged 64.0(57.0, 71.0)years, and the OS was 97(61, 171) months, while the time to death from secondary MM was 32(18, 47) months. The time from patients diagnosed with MM to SPMs was 37(18, 50) months, which was significantly earlier than that of MM secondary to malignancies [53(31,117) months](P=0.016). The type of tumor was also different between the two groups (P<0.001). In the group of MM with SPMs, the most common type of SPMs was hematopoietic malignancies (12/20, 60.0%), whereas in the group of MM secondary to malignancies, MM was most often secondary to genitourinary malignancies (13/29, 44.8%) (P<0.001). Conclusions: Both MM with SPMs and MM secondary to malignancies can affect the survival of patients. Secondary hematological malignancies account for a high proportion of the second tumors in MM patients, while genitourinary malignancies account for a high proportion of malignant tumors associated with MM.

[The prognostic value of dynamic minimal residual disease after autologous hematopoietic stem cell transplantation in patients with multiple myeloma in novel-agent era]

Objective: To investigate the clinical prognostic value of dynamic minimal residual disease (MRD) after autologous hematopoietic stem cell transplantation (AHSCT) in patients with multiple myeloma (MM). Methods: Patients with MM who underwent AHSCT in Beijing Chao-Yang Hospital from February 2016 to December 2019 were enrolled in this study. All the patients in the study had complete baseline data at the diagnosis. AHSCT was performed after induction chemotherapy. Response evaluation was performed after induction therapy. All the patients were assessed at approximately 100 days after AHSCT. Bone marrow MRD by NGF was performed every three months and dynamically monitored for at least 12 months. All the patients were divided into different groups according to cytogenetics and MRD status. Survivals in different groups were analyzed by IBM SPSS 22.0 statistical software. Results: A total of 150 patients with MM were enrolled in this study at last, including 66 patients in the cytogenetic standard risk group and 84 patients in the cytogenetic high-risk group. The median age was 54 years (range 30-68 years) and 87 male patients (58.0%) was in the study. The median follow-up was 36 months (range 16-72 months). Patients in the standard-risk group had better clinical prognosis than those in the high-risk group [median PFS in the standard-risk group was not achieved, and median PFS in the high-risk group was 45 months (P<0.001); median OS of both groups was not reached, and the estimated 3-year OS rate of the standard-risk group and the high-risk group was 95.2% and 78.9%, respectively (P=0.001)]. According to MRD status of patients, patients in each group were divided into three subgroups: persistent positive (Ppos), transient negative (Tneg) and persistent negative (Pneg). The median OS and median PFS of all subgroups in the standard-risk group was not reached (P=0.324 and P=0.086). In high-risk group, the median OS of MRD Pneg subgroup was not reached, and the estimated 3-year OS rate was 100%; The median OS of MRD Ppos subgroup was 52 months, and MRD Tneg subgroup only 31 months (P=0.002); the median PFS of MRD Pneg group was not reached, and the estimated 3-year PFS rate was 85.4%; median PFS of MRD Ppos subgroup was 40 months, and MRD Tneg subgroup only 17 months (P=0.001). Conclusions: MRD Pneg might overcome the adverse prognosis of MM patients with high-risk cytogenetics. However, MRD Tneg might be a poor prognostic factor for the patients with cytogenetic high-risk MM.

A Supervised-Reinforced Successive Training Framework for a Fuzzy Inference System and Its Application in Robotic Odor Source Searching

Fuzzy inference systems have been widely applied in robotic control. Previous studies proposed various methods to tune the fuzzy rules and the parameters of the membership functions (MFs). Training the systems with only supervised learning requires a large amount of input-output data, and the performance of the trained system is confined by that of the target system. Training the systems with only reinforcement learning (RL) does not require prior knowledge but is time-consuming, and the initialization of the system remains a problem. In this paper, a supervised-reinforced successive training framework is proposed for a multi-continuous-output fuzzy inference system (MCOFIS). The parameters of the fuzzy inference system are first tuned by a limited number of input-output data from an existing controller with supervised training and then are utilized to initialize the system in the reinforcement training stage. The proposed framework is applied in a robotic odor source searching task and the evaluation results demonstrate that the performance of the fuzzy inference system trained by the successive framework is superior to the systems trained by only supervised learning or RL. The system trained by the proposed framework can achieve around a 10% higher success rate compared to the systems trained by only supervised learning or RL.

Unsupervised Sim-to-Real Adaptation for Environmental Recognition in Assistive Walking

Powered lower-limb prostheses with vision sensors are expected to restore amputees' mobility in various environments with supervised learning-based environmental recognition. Due to the sim-to-real gap, such as real-world unstructured terrains and the perspective and performance limitations of vision sensor, simulated data cannot meet the requirement for supervised learning. To mitigate this gap, this paper presents an unsupervised sim-to-real adaptation method to accurately classify five common real-world (level ground, stair ascent, stair descent, ramp ascent and ramp descent) and assist amputee's terrain-adaptive locomotion. In this study, augmented simulated environments are generated from a virtual camera perspective to better simulate the real world. Then, unsupervised domain adaptation is incorporated to train the proposed adaptation network consisting of a feature extractor and two classifiers is trained on simulated data and unlabeled real-world data to minimize domain shift between source domain (simulation) and target domain (real world). To interpret the classification mechanism visually, essential features of different terrains extracted by the network are visualized. The classification results in walking experiments indicate that the average accuracy on eight subjects reaches (98.06% ± 0.71%) and (95.91% ± 1.09%) in indoor and outdoor environments respectively, which is close to the result of supervised learning using both type of labeled data (98.37% and 97.05%). The promising results demonstrate that the proposed method is expected to realize accurate real-world environmental classification and successful sim-to-real transfer.

[An analysis on senior pupil's tobacco use and exposure in Shandong province in 2012 and 2019]

Objective: To analyze the changes in tobacco use and exposure in primary school students in Shandong province in 2012 and 2019. Methods: A multi-stage stratified cluster random sampling method was used in the survey. In 2012 and 2019, 5 861 and 4 021 students from 3 different cities of Shandong province were selected as the study population. The questionnaire was filled anonymously by the subjects. χ² test was conducted to compare the difference of groups. Results: In 2012 and 2019, the rate of attempting smoking among pupils under this study in Shandong province were 6.0％and 6.3%, respectively, while the current smoking rate were 1.2％and 2.3%, respectively. The sex ratio of male and female students attempting to smoke was 2.56∶1 in 2012 and 1.31∶1 in 2019. The sex ratio of current smoking rate was 2.43∶1 and 2.00∶1, respectively in 2012 and in 2019. The rate of tobacco exposure in the public places was 50.5％and 41.4%, respectively. The rate of tobacco exposure in family was 49.7% and 46.4%, respectively. Two rates of tobacco exposure decreased, but the reduction in family (3.3%) was far less than that in public places (9.1%). In 2019, the rate of tobacco exposure in family was higher than that in public places. Conclusions: The tobacco exposure rate declined in senior pupils in Shandong province. However, the situation is still grim for the current smoking rate, growth trend of girls tobacco use, and tobacco exposure in family.

Gait Phase Subdivision and Leg Stiffness Estimation during Stair Climbing

Leg stiffness is considered a prevalent parameter used in data analysis of leg locomotion during different gaits, such as walking, running, and hopping. Quantification of the change in support leg stiffness during stair ascent and descent will enhance our understanding of complex stair climbing gait dynamics. The purpose of this study is to investigate a methodology to estimate leg stiffness during stair climbing and subdivide the stair climbing gait cycle. Leg stiffness was determined as the ratio of changes in ground reaction force in the direction of the support leg Fl (leg force) to the respective changes in length Ll during the entire stance phase. Eight subjects ascended and descended an instrumented staircase at different cadences. In this study, the changes of leg force and length (force-length curve) are described as the leg stiffness curve, the slope of which represents the normalized stiffness during stair climbing. The stair ascent and descent gait cycles were subdivided based on the negative and positive work fluctuations of the center-of-mass (CoM) work rate curve and the characteristics of leg stiffness. We found that the leg stiffness curve consists of several segments in which the force-length relationship was similarly linear and the stiffness value was relatively constant; the phase divided by the leg stiffness curve corresponds to the phase divided by the CoM work rate curve. The results of this study may guide biomimetic control strategies for a wearable lower-extremity robot for the entire stance phase during stair climbing.

The ins and outs of male breast and anterior chest wall lesions from childhood to adulthood

Physiological and pathological processes arising from the breast and anterior chest wall may share similar clinical presentations because of the small volume of male breasts. Therefore, imaging is frequently required to localise and characterise the lesion and guide biopsy when radiological findings are equivocal or suspicious. Mammography or digital breast tomosynthesis (DBT) and ultrasound are the mainstays of breast imaging work-up. Other imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI) and positron-emission tomography (PET) can sometimes augment the investigation and aid treatment planning. This article reviews the key imaging features of a wide spectrum of benign and malignant conditions that involve the male breast and anterior chest wall across various age groups. Familiarisation with the salient radiological findings is essential for reaching an accurate diagnosis and optimising management.

Proximal policy optimization with model-based methods

Model-free reinforcement learning methods have successfully been applied to practical applications such as decision-making problems in Atari games. However, these methods have inherent shortcomings, such as a high variance and low sample efficiency. To improve the policy performance and sample efficiency of model-free reinforcement learning, we propose proximal policy optimization with model-based methods (PPOMM), a fusion method of both model-based and model-free reinforcement learning. PPOMM not only considers the information of past experience but also the prediction information of the future state. PPOMM adds the information of the next state to the objective function of the proximal policy optimization (PPO) algorithm through a model-based method. This method uses two components to optimize the policy: the error of PPO and the error of model-based reinforcement learning. We use the latter to optimize a latent transition model and predict the information of the next state. For most games, this method outperforms the state-of-the-art PPO algorithm when we evaluate across 49 Atari games in the Arcade Learning Environment (ALE). The experimental results show that PPOMM performs better or the same as the original algorithm in 33 games.

A Probability Distribution Model-Based Approach for Foot Placement Prediction in the Early Swing Phase With a Wearable IMU Sensor

Predicting the next foot placement of humans during walking can help improve compliant interactions between humans and walking aid robots. Previous studies have focused on foot placement estimation with wearable inertial sensors after heel-strike, but few have predicted foot placements in advance during the early swing phase. In this study, a Bayesian inference-based foot placement prediction approach was proposed. Possible foot placements were modeled as a probability distribution grid map. With selected foot motion feature events detected sequentially in the early swing phase, the foot placement probability map could be updated iteratively using the feature models we built. The weighted center of the probability distribution was regarded as the predicted foot placement. Prediction errors were evaluated with collected walking data sets. When testing with the data from inertial measurement units, the prediction errors were (5.46 cm ± 10.89 cm, -0.83 cm ± 10.56 cm) for cross-velocity walking data and (-4.99 cm ± 12.31 cm, -11.27 cm ± 7.74 cm) for cross-subject-cross-velocity walking data. The results were comparable to previous works yet the prediction could be made earlier. For the subject who walked with more stable gaits, the prediction error can be further decreased. The proposed foot placement prediction approach can be utilized to help walking aid robots adjust their pose before each heel-strike event during walking, which will make human-robot interactions more compliant. This study is also expected to inspire additional probabilistic gait analysis works.

The alarmin interleukin-1α causes preterm birth through the NLRP3 inflammasome

Sterile intra-amniotic inflammation is a clinical condition frequently observed in women with preterm labor and birth, the leading cause of neonatal morbidity and mortality worldwide. Growing evidence suggests that alarmins found in amniotic fluid, such as interleukin (IL)-1α, are central initiators of sterile intra-amniotic inflammation. However, the causal link between elevated intra-amniotic concentrations of IL-1α and preterm birth has yet to be established. Herein, using an animal model of ultrasound-guided intra-amniotic injection of IL-1α, we show that elevated concentrations of IL-1α cause preterm birth and neonatal mortality. Additionally, using immunoblotting techniques and a specific immunoassay, we report that the intra-amniotic administration of IL-1α induces activation of the NOD-like receptor family, pyrin domain containing 3 (NLRP3) inflammasome in the fetal membranes, but not in the decidua, as evidenced by a concomitant increase in the protein levels of NLRP3, active caspase-1, and IL-1β. Lastly, using Nlrp3-/- mice, we demonstrate that the deficiency of this inflammasome sensor molecule reduces the rates of preterm birth and neonatal mortality caused by the intra-amniotic injection of IL-1α. Collectively, these results demonstrate a causal link between elevated IL-1α concentrations in the amniotic cavity and preterm birth as well as adverse neonatal outcomes, a pathological process that is mediated by the NLRP3 inflammasome. These findings shed light on the mechanisms underlying sterile intra-amniotic inflammation and provide further evidence that this clinical condition can potentially be treated by targeting the NLRP3 inflammasome.

[Survey on tobacco use and associated factors in population in Shandong province, 2016-2017]

Objective: To understand the status of tobacco use and related influencing factors in population in Shandong province. Methods: Stratified multi-stage cluster sampling was used to select respondents from 216 villages (communities) of 36 districts (counties) in Shandong province. Influencing factors on smoking were analyzed by logistic regression model. Results: The adequate sample size was 6 271 participants. After complex weighted, the current smoking prevalence was 23.93%,45.58% in males and 1.18% in females. The Public's smoking rates varied widely among different groups in the population. 45-64 age group had the highest smoking rate (25.07%). Smoking rates were substantially different in education levels, with the highest in junior high school (28.94%). The rate was higher in the rural area (24.98%) than that in the urban areas (23.08%). The average daily smoking rate was 20.23%. The average age of initiating smoking was 21.21 years. The average daily cigarette intake was 16.31 cigarettes. Among all the former and current smokers, the quitting rate was 20.79%. Multiple logistic regression model analysis showed that gender, age, occupation, region, and health knowledge score were correlated with smoking behavior. The current smoking rate of men was much higher than that of women (OR=49.625, 95%CI: 37.832-65.093). The current smoking rate in 45-64 age group was higher than that in the 15-24 age group (OR=1.830, 95%CI: 1.048-3.194). The current smoking rate of medical (OR=0.403, 95%CI: 0.187-0.866) and retired personnel (OR=0.648, 95%CI: 0.481-0.873) were lower than those engaging in agriculture, forestry, animal husbandry and the fishery ,respectively. The prevalence of residents living in the central part showed lower rate on current smoking than that in the eastern region (OR=0.724, 95%CI: 0.606-0.865). The current smoking prevalence of smoke hazard in 1-3 score group was higher than that in the group with 4-6 score (OR=1.432, 95%CI: 1.240-1.654). Conclusions: Smoking rate in adults in Shandong remained stable and at a high level. Comprehensive intervention measures such as tobacco control and health education should be carried out to reduce the smoking rate.

[Prevalence and associated factors regarding electronic cigarette smoking among adults in Shandong province]

Objective: To understand the awareness, current or past behavior on electronic cigarette smoking (ECS) and associated factors, among adults aged ≥15 years old in Shandong province. Relationship between ECS and cessation of smoking was also studied. Methods: Using the global standard questionnaire, a cross-sectional survey was conducted among 6 401 adults selected by stratified multi-stage cluster sample method. Electronic data was collected by handheld computer. Data were weighted and analyzed by SPSS 19.0 complex program. Results: The prevalence rates of awareness, ever or current smoking of e-cigarettes appeared as 37.6%, 3.8% and 0.6% respectively. Data from logistic regression analysis showed that risk factors for ECS were living in urban area, at younger age, being current or former cigarettes smoker and with knowledge on the risks of smoking or being encouraged to stop smoking. Among the electronic cigarettes smokers, those who tried to quit smoking (30.1%) had a significantly higher rate than that of the non-smokers (19.5%) (P<0.05), however, the successful quitting rate was much lower than that in the non-ECS users (P<0.05). Conclusions: Rates on the awareness and uptake of electronic cigarettes are on the rise. It is necessary to strengthen and standardize the monitoring programs to provide evidence for setting up targeting intervention strategies.

A model to predict ground reaction force for elastically-suspended backpacks

BACKGROUND

Leg muscle fatigue is the most important factor that affects walking endurance. Considering the legs act as actuators in alternate contact with the ground during walking, the ground reaction force (GRF) of each leg can indirectly reflect the strength of leg muscles. However, it is not clear how the elastically-suspended backpack (ESB) affects GRF of each leg during human level walking.

RESEARCH QUESTION

How is ESB related in GRF of each leg during walking, and how do multiple variables (stiffness and damping of ESB, load mass, walking speed) affect GRF?

METHODS

An extended bipedal walking model (EBW) with a spring-mass-damping system was proposed to predict the GRF of each leg. In order to evaluate the prediction effect of the model, seven healthy subjects were recruited to attend the experiments using our backpack prototype and the GRFs data was compared. Each subject walked under 12 conditions (load states: locked or unlocked, walking speed: 3.6 km/h, 4.0 km/h, 4.5 km/h, 5.0 km/h, 5.5 km/h, 6.0 km/h).

RESULTS

Results showed that the model could quantitatively predict experimental GRFs over the whole gait cycle (R²≥0.9628) and the characteristic forces (two peak forces and one trough force) were close to the experimental data (average predicted accuracy 93.7 %). The model can reflect relationships between variables and GRF. The relationships showed that an apparent tradeoff exists among the three characteristic forces, and the ESB can produce positive or negative effect under different variables.

SIGNIFICANCE

This work could help us understand the experimental GRF phenomena, especially the contradictory experimental phenomenon caused by the different parameters. It could also help designers optimize structural parameters of ESB for excellent effects on human. The ESBs with excellent performance can be wildly used in military and tourism.

1141 Daytime Napping Trajectory Over Time And Its Association With Cognitive Aging: A 13-year Community-based Longitudinal Study Of Older Adults

Introduction

Daytime napping is common in elderly adults and has been associated with cognitive impairment. Prior studies have assessed napping at one time point, making it difficult to examine the longitudinal progression of napping and its association with cognitive aging. We examined objectively measured daytime napping longitudinally across different stages of Alzheimer’s disease (AD): from no cognitive impairment (NCI), to mild cognitive impairment (MCI), and to Alzheimer’s dementia.

Methods

We studied 1,066 participants (female: 810; age: 81.0±7.3 [SD]) in the Rush Memory and Aging Project who have been followed for up to 13 years. Motor activities of up to 10 days were recorded annually and used to assess napping objectively. We defined daytime napping episodes as segments between 10AM and 7PM with continuous zero-activity for ≥10min but &lt;1h (to avoid off-wrist periods). Segments that were &lt;5min apart were merged. Cognitive and clinical evaluations were administered annually to render a clinical diagnostic classification of NCI, MCI, or Alzheimer’s dementia. To examine how napping duration and frequency change with the progression of AD, we performed linear mixed-effects models with 2 change points anchored at the diagnoses of MCI and AD while adjusted for age, sex, and education.

Results

At baseline, participants had 1.44±0.04 (mean±standard error) naps with an accumulated duration of 35.0±1.1 min per day. Napping duration increased by 5.2±0.3 min and frequency increased by 0.21±0.01 times every year (both p&lt;0.0001). The rate of increase was more than doubled after MCI diagnosis with an annual increase of 11.4±0.7 min in duration and 0.40±0.02 times in frequency (both p&lt;0.0001); these were doubled further after AD diagnosis with an annual change of 26.3±3.1 min in duration and 0.84±0.08 times in frequency (both p&lt;0.0001).

Conclusion

Daytime napping duration and frequency increase with aging, and the increase was accelerated with AD progression.

Support

This work was supported by NIH grants RF1AG064312, RF1AG059867, R01AG017917, and R01AG56352.

1145 Longitudinal Association Between Circadian Activity Rhythms And Risk Of Incident Parkinson’s Disease In Older Men

Introduction

Disruption in circadian activity rhythms are very common in older adults, particularly among those with neurodegenerative diseases. However, the longitudinal association between circadian disruption and subsequent risk of developing neurodegenerative diseases, including Parkinson’s disease (PD), is unclear.

Methods

We examined rest-activity rhythms in 2930 community-dwelling older men (mean age 76.3 ± 5.5 years) without PD and followed them for incident PD over the next 11 years. 24-h rest-activity rhythm parameters (amplitude, mesor, robustness, acrophase) were generated by wrist actigraphy-extended cosinor analysis. Incident PD cases were identified based on physician-diagnosed PD between 2005 and 2016. Logistic regression was used to determine the association between quartiles of rest-activity parameters and risk of incident PD.

Results

78 (2.7%) men developed PD during 11 years of follow-up. The risk of PD increased with decreasing circadian amplitude (strength of the rhythm), mesor (mean level of activity) or robustness (how closely activity follows a cosine 24h pattern); p for trend across quartiles &lt;0.05. After accounting for demographics, clinic site, education, depressive symptoms, body mass index, physical activity, benzodiazepine use, alcohol, caffeine, smoking, comorbidities and baseline cognition, those in the lowest quartile of amplitude, mesor or robustness had approximately three times the risk of developing PD compared to those in the highest quartile of amplitude [ORs (95% CI)= 3.11 (1.54-6.29)], mesor [3.04 (1.54-6.01)] and robustness [2.65 (1.24-5.66)]. The association remained after further adjustment for nighttime sleep disturbances and sleep duration. These associations were somewhat attenuated, but the pattern remained similar after excluding PD cases developed within 2 years after baseline. Acrophase was not significantly associated with risk of PD.

Conclusion

Older men with reduced circadian rhythmicity had an increased risk of incident PD over 11 years. Circadian disruption in the elderly may represent an important prodrome or risk factor for PD. Randomized trials should evaluate whether strategies to improve circadian function impact risk of PD.

Support

This work was supported by the NIA, NIAMS, NCATS, NIH Roadmap for Medical Research and the NHLBI under the grant numbers: U01AG027810, U01AG042124, U01AG042139, U01AG042140, U01AG042143, U01AG042145, U01AG042168, U01AR066160, UL1TR000128, R01HL071194, R01HL070848, R01HL070847, R01HL070842, R01HL070841, R01HL070837, R01HL070838, and R01HL070839.

1135 Longer And More Frequent Naps Predict Incident Alzheimer’s Dementia In Community-based Older Adults

Introduction

Excessive napping duration has been associated with cognitive decline. The effect of napping frequency is less understood, and little is known about the development of Alzheimer’s dementia associated with napping. We tested whether longer or more frequent naps in the elderly are linked to the development of incident Alzheimer’s dementia.

Methods

We studied 1,180 older adults (age: 81.0±7.3 [SD]) in the Rush Memory and Aging Project who have been followed for up to 14 years. Motor activities of up to 10 days were recorded at baseline to assess napping characteristics objectively. We defined daytime napping episodes as motor activity segments between 10AM and 7PM with continuous zero-activity for ≥10min but &lt;1h (to avoid off-wrist periods). Segments that were &lt;5min apart were merged. Alzheimer’s dementia diagnosis was determined using the criteria of the National Institute of Neurological and Communicative Disorders and Strone and the Alzheimer’s Disease and Related Disorders Association. Cox proportional hazards models were performed to examine the associations of daily napping duration and frequency with incident AD.

Results

Of 1,180 non-demented participants at baseline (including 264 with mild cognitive impairment), 277 developed Alzheimer’s dementia within 5.74±3.36 years. On average, participants napped for 38.3±1.0 (SE) min and1.56±0.04 (SE) times per day at baseline. After adjustment for age, sex, and education, every 30-min increase in daily napping duration was associated with a 20% increase in the risk of incident AD (95% confidence interval [CI]: 9%-31%; p=0.0002). One more nap per day was associated with a 19% increase in the risk of AD (95% CI: 8%-30%; p=0.0003). These associations remained after further adjustment for total sleep time.

Conclusion

Longer and more frequent daytime naps predict a higher risk of incident Alzheimer’s dementia. Future studies are needed to examine specific underlying mechanisms.

Support

This work was supported by NIH grants RF1AG064312, RF1AG059867, R01AG017917, and R01AG56352.

1152 Genetic Risk Of Alzheimer’S Disease Is Linked To Short Sleep Duration

Introduction

Sleep disturbances including short sleep duration are common in older adults, especially in those with Alzheimer’s disease (AD). However, it is unclear to what extent sleep duration is a manifestation of AD disease process. We examined whether genetic variants related to AD influence sleep duration in middle-aged and older adults and estimated the causal effects of AD on sleep duration using a mendelian randomization (MR) analysis.

Methods

We examined 406,687 UK Biobank participants with Caucasian genetic ancestry who self-reported sleep duration at baseline (2006-2010). Sleep duration was assessed by asking: “About how many hours sleep do you get in every 24 hours? (please include naps).” A genetic risk score for AD (AD-GRS) was calculated as a weighted sum of 23 previously identified AD-related single nucleotide polymorphisms in individuals of European ancestry. We evaluated whether AD-GRS predicted sleep duration using linear regression, adjusting for age, sex and principle components for genetic ancestry. We also stratified the analysis by age at baseline (≤55y or &gt;55y) and conducted a MR analysis to estimate the effect of AD (ICD-9/10 codes for AD/dementia diagnosis) on sleep duration.

Results

The participants (aged 56.91±8.00y) had an average sleep duration of 7.2 (Standard deviation [SD]=1.1) hours and AD-GRS of 0.11 (SD=0.40) (range: -1.15~1.85). Higher AD-GRS score predicted shorter sleep duration (b= -0.013, 95%CI:-0.022,-0.005), mainly among those aged over 55y (b= -0.023, 95%CI:-0.034,-0.012) and not in those 55y or younger (b= 0.006, 95%CI:-0.012,0.013); p for interaction by age=0.02. MR analysis using AD-GRS as an instrumental variable suggested that AD was associated with 1.76 hrs (b=-1.76, -2.62~ -0.90) shorter sleep duration in those aged &gt;55y.

Conclusion

Using a novel analytical approach, we found that higher genetic risk for AD predicted shorter sleep duration among older adults. This suggests shared genetic pathways; the biologic processes that lead to AD may also affect sleep duration.

Support

Dr. Leng received support from the National Institute on Aging (NIA) 1K99AG056598, and from GBHI, Alzheimer’s Association, and Alzheimer’s Society (GBHI ALZ UK-19-591141).

[Study on the relationship between smoking behavior and health literacy among grade 4-6 primary students in Shandong province]

Objective: To investigate the associations between smoking and literacy on health among 4-6 grade primary school students. Methods: A questionnaire survey was conducted to research on health literacy and smoking among 4-6 grade pupils in Shandong province, through a multi-stage stratified cluster random sampling method. Sociodemographic characteristics, health literacy level and smoking rate were collected from respondents. Binary logistic regression analysis was used to evaluate the association of smoking and health literacy. Results: A total of 9 240 questionnaires were distributed, with the rate of valid response as 99.7%. The current smoking rate of the students was 2.6%, on higher in boys (3.1%) than in girls (2.0%). 60.8% of 4-6 grade students were found to have adequate health literacy level. Levels of literacy health in both boy and girl school students appeared 56.7% and 64.9%, respectively. Results indicated that health literacy in smokers (14.4%) was lower than that in non-smokers (62.0%). Results from the binary logistic regression analysis showed that the independent influencing factors would include grade, father's education level, economic situation of the family, self-assessment on the school record and literacy on health (P<0.01). After controlling the other independent variables, the smoking rate was 8.62 (1/0.116) times in students with low literacy level on health, than those with high literacy level. Conclusions: Literacy on health was significantly associated with smoking in the 4-6 grade pupils of Shandong province.

An Occlusion-Aware Framework for Real-Time 3D Pose Tracking

Random forest-based methods for 3D temporal tracking over an image sequence have gained increasing prominence in recent years. They do not require object's texture and only use the raw depth images and previous pose as input, which makes them especially suitable for textureless objects. These methods learn a built-in occlusion handling from predetermined occlusion patterns, which are not always able to model the real case. Besides, the input of random forest is mixed with more and more outliers as the occlusion deepens. In this paper, we propose an occlusion-aware framework capable of real-time and robust 3D pose tracking from RGB-D images. To this end, the proposed framework is anchored in the random forest-based learning strategy, referred to as RFtracker. We aim to enhance its performance from two aspects: integrated local refinement of random forest on one side, and online rendering based occlusion handling on the other. In order to eliminate the inconsistency between learning and prediction of RFtracker, a local refinement step is embedded to guide random forest towards the optimal regression. Furthermore, we present an online rendering-based occlusion handling to improve the robustness against dynamic occlusion. Meanwhile, a lightweight convolutional neural network-based motion-compensated (CMC) module is designed to cope with fast motion and inevitable physical delay caused by imaging frequency and data transmission. Finally, experiments show that our proposed framework can cope better with heavily-occluded scenes than RFtracker and preserve the real-time performance.

Daytime napping, sleep duration and increased 8-year risk of type 2 diabetes in a British population

BACKGROUND AND AIMS

Few studies have prospectively examined the relationship between daytime napping and risk of type 2 diabetes. We aimed to study the effects of daytime napping and the joint effects of napping and sleep duration in predicting type 2 diabetes risk in a middle- to older-aged British population.

METHODS AND RESULTS

In 1998-2000, 13 465 individuals with no known diabetes participating in the European Prospective Investigation into Cancer-Norfolk study reported daytime napping habit and 24-h sleep duration. Incident type 2 diabetes cases were identified through multiple data sources until 31 July 2006. After adjustment for age and sex, daytime napping was associated with a 58% higher diabetes risk. Further adjustment for education, marital status, smoking, alcohol intake, physical activity, comorbidities and hypnotic drug use had little influence on the association, but additional adjustment for BMI and Waist Circumference attenuated the Odds ratio (OR) (95% CI) to 1.30 (1.01, 1.69). The adjusted ORs (95% CI) associated with short and long sleep duration were 1.46 (1.10, 1.90) and 1.64 (1.16, 2.32), respectively. When sleep duration and daytime napping were examined together, the risk of developing diabetes more than doubled for those who took day naps and had less than 6 h of sleep, compared to those who did not nap and had 6-8 h of sleep.

CONCLUSION

Daytime napping was associated with an increased risk of type 2 diabetes, particularly when combined with short sleep duration. Further physiological studies are needed to confirm the interaction between different domains of sleep in relation to diabetes risk.

Role of mitophagy regulated by Parkin/DJ-1 in remote ischemic postconditioning-induced mitigation of focal cerebral ischemia-reperfusion

OBJECTIVE

We evaluated the role of mitophagy controlled by Parkin/DJ-1 in remote ischemic post conditioning-induced mitigation of focal cerebral ischemia-reperfusion (I/R) injury in rats.

MATERIALS AND METHODS

Ninety adult male rats were randomly assigned into 5 groups including a sham operation group (S) and ischemia-reperfusion group (I/R). Focal cerebral I/R was induced by right middle cerebral artery occlusion (MCAO). I/R+remote ischemic postconditioning (I/R+RIPoC), I/R+RIPoC+ mitophagy inhibitor Mdivi-1 (I/R+RIPoC+M), and I/R+RIPoC+ normal saline (I/R+RIPoC+NS) groups all received 3 cycles of 10 minutes reperfusion followed by 10 minutes ischemia in bilateral femoral arteries at the beginning of cerebral reperfusion. I/R+RIPoC+M received mitochondrial division inhibitor (Mdivi-1) before ischemia and after 24h of reperfusion, neurological deficit scores (NDSs) were measured and rats were then sacrificed. Brain was removed and size of the infarct was determined. Apoptosis index and LC3-II/I ratio, Parkin/DJ-1 proteins expression, SOD activity, MDA and 15-F2t-Isoprostane content in cerebral ischemic penumbra were studied. Linear correlation between Parkin/DJ-1 proteins expression and LC3-II/I ratio and cerebral infarct size were analyzed.

RESULTS

In experimental groups the NDSs, percentage of cerebral infarct size, apoptosis index, LC3-II/I ratio, MDA and 15-F2t-Isoprostane content significantly increased and Parkin/DJ-1 proteins were up-regulated (p<0.05). In I/R+RIPoC and I/R+RIPoC+NS groups, NDSs, percentage of cerebral infarct size, apoptosis index, MDA and 15-F2t-Isoprostane content decreased significantly while LC3-II/I ratio and SOD activity increased compared to I/R group. Parkin/DJ-1 proteins were up-regulated in I/R+RIPoC, I/R+RIPoC+NS and I/R+RIPoC+M groups (p<0.05). LC3-II/I ratio and SOD activity significantly decreased (p<0.05). Parkin/DJ-1 proteins expression didn't changed in I/R+RIPoC+M group (p>0.05). The Parkin/DJ-1 proteins expression were positively correlated with LC3-II/I ratio, and negatively correlated with cerebral infarct size (p<0.05).

CONCLUSIONS

Remote Ischemic Post Conditioning (RIPoC) promoted the mitophagy via up-regulation of Parkin/DJ-1 proteins expression and inhibiting the oxidative stress responses, thus mitigating focal cerebral I/R injury in rats.

MiR-873 regulates ERα transcriptional activity and tamoxifen resistance via targeting CDK3 in breast cancer cells

miRNAs (microRNAs) are frequently and aberrantly expressed in many cancers. MiR-873 has been revealed to be downregulated in colorectal cancer and glioblastoma. However, its function remains unclear. Here we report that miR-873 is downregulated in breast tumor compared with normal tissue. Enforced expression of miR-873 decreases the transcriptional activity of ER (estrogen receptor)-α but not ERβ through the modulation of ERα phosphorylation in ER-positive breast cancer cells. We also found that miR-873 inhibits breast cancer cell proliferation and tumor growth in nude mice. Reporter gene assays revealed cyclin-dependent kinase 3 (CDK3) as a direct target of miR-873. CDK3 was shown to be overexpressed in breast cancer and phosphorylate ERα at Ser104/116 and Ser118. Furthermore, we found that Mir-873 inhibits ER activity and cell growth via targeting CDK3. Interestingly, miR-873 was observed to be downregulated in tamoxifen-resistant MCF-7/TamR cells, while CDK3 is overexpressed in these cells. More importantly, re-expression of miR-873 reversed tamoxifen resistance in MCF-7/TamR cells. Our data demonstrate that miR-873 is a novel tumor suppressor in ER-positive breast cancer and a potential therapeutic approach for treatment of tamoxifen-resistant breast cancer.

Probing limits on spatial resolution using nonlinear optical effects and nonclassical light

Using a simple optical setup to detect and characterize transmission gratings in the far field, we demonstrate that going beyond the diffraction limit is not possible using linear interaction of nonclassical illumination with the target grating. We also confirm that nonlinear optical interactions with the target grating, or with the optical medium around it, do allow improvement in resolution.

The association between social stress and global cognitive function in a population-based study: the European Prospective Investigation into Cancer (EPIC)-Norfolk study

BACKGROUND

Stress is thought to exert both positive and negative effects on cognition, but the precise cognitive effects of social stress and individuals' response to stress remain unclear. We aimed to investigate the association between different measures of social stress and cognitive function in a middle- to older-aged population using data from the European Prospective Investigation into Cancer (EPIC)-Norfolk study.

METHOD

Participants completed a comprehensive assessment of lifetime social adversity between 1993 and 1997 and the short form of the Mini Mental State Examination (SF-MMSE), an assessment of global cognitive function, during the third health check between 2004 and 2011 (a median of 10.5 years later). A low MMSE score was defined as a score in the bottom quartile (20-26).

RESULTS

Completed MMSE scores and stress measures were available for 5129 participants aged 48-90 years. Participants who reported that their lives had been more stressful over the previous 10 years were significantly more likely to have low MMSE scores [odds ratio (OR) 1.14, 95% confidence interval (CI) 1.04-1.24 per unit increase in perceived stress], independently of sociodemographic factors, physical and emotional health. The effects were restricted to the highest level of stress and the association was stronger among participants with a lower educational level. Adaptation following life event experiences also seemed to be associated with MMSE scores after adjusting for sociodemographic factors, but the association was attenuated with further adjustment.

CONCLUSIONS

In this generally high-functioning population, individuals' interpretations and responses to stressful events, rather than the events themselves, were associated with cognitive function.

Characterization of the carbonic anhydrases 15b expressed in PGCs during early zebrafish development

The main function of carbonic anhydrases is to regulate acid-base balance. In the present study, the zebrafish CA15b sequence was identified from the National Center for Biotechnology Information database (accession No. NM_213182). The 1716 base pair full-length cDNA of CA15b was obtained by 3' and 5'-rapid amplification of cDNA ends analysis. It was expressed (reverse transcription polymerase chain reaction and Western blot analysis) in the ovary, heart, brain, and muscle, but not in testis or liver. Based on in situ hybridization, CA15b mRNA was transcribed in the ooplasm of stage I to stage II oocytes, in the cortex of stage III oocytes, and along the periphery of stage IV oocytes. Furthermore, this protein was localized (immunohistochemistry) in the plasma membrane of oocytes. Based on whole-mount in situ hybridization, CA15b mRNA was present in every blastomere of embryos from one-cell to blastula stages. Strong signals of the transcripts were present along cleavage furrows of two- and eight-cell stage embryos, which subsequently condensed into four clusters of cells during the blastula stage. During subsequent stages, the four groups of CA15b-expressing cells appeared to move toward the dorsal side of the embryos, clustered into two groups on either side of the midline, and remained visible as they migrated toward the region of the gonad in embryos at 24 hours postfertilization. Expression patterns of CA15b were similar to those of vasa, a marker of primordial germ cells. Thus, we hypothesized that CA15b might be necessary for development of primordial germ cells and female germ cells in zebrafish.

QSAR studies on imidazopyrazine derivatives as Aurora A kinase inhibitors

Aurora kinases have emerged as attractive targets for the development of novel anti-cancer agents. A combined study of molecular docking, pharmacophore modelling and 3D-QSAR was performed on a series of imidazo [1, 2-a] pyrazines as novel Aurora kinase inhibitors to gain insights into the structural determinants and their structure-activity relationship. An ensemble of conformations based on molecular docking was used for PHASE pharmacophore studies. The developed best-fitted pharmacophore model was validated by diverse chemotypes of Aurora A kinase inhibitors and was consistent with the structural requirements for the docked binding mechanism. Subsequently, the pharmacophore-based alignment was used to develop PHASE and comparative molecular similarity indices analysis (CoMSIA) 3D-QSAR models. The best CoMSIA model showed good statistics (q (2 )= 0.567, r (2 )= 0.992), and the predictive ability of the model was validated using an external test set of 13 compounds giving a satisfactory prediction ([Formula: see text]). The 3D contour maps provided insight into the binding mechanism and highlighted key structural features that are essential to the inhibitory activity. Based on the PHASE and CoMSIA 3D-QSAR results, a set of novel Aurora A inhibitors were designed that showed excellent potencies.