Studying biological science does not lead to adoption of a healthy lifestyle

Aims: The lifestyle and physical activity (PA) habits of young people play a key role in the prevention of cardiovascular and metabolic diseases at older ages. The current generation of biological science students at university holds promise for better future medicine and medical technology. However, their physical fitness and lifestyle are often ignored. Methods: Lifestyle, PAs and common risk factors for cardiovascular disease before, and at, university were collected from 408 students using self-completed, anonymous surveys between the academic years of 2017 and 2019 from the School of Biological Sciences, University of Reading. Statistical analysis was performed using SAS® 9.4 software. Results: Among the 408 participants, 134 were male and 274 were female with a mean (SD) age of 19.6 (2.24). Approximately 19% of participants consumed alcohol beyond the safe limit of <14 units/week (112 g/week). Among them, 65% were males. Before university, 47% of students failed to meet the UK National Physical Activity Guidelines (NPAG) which increased to 56% during university with males exhibiting a steeper incline. Compared to their lifestyles before university, more students had insufficient sleep and displayed greater sedentariness during university. Moreover, 16% of students declared no engagement in PA which was greater than the value of 12% before university. Fitness perceptions worsened by 11% during university particularly for females. Statistical analysis revealed that gender, BMI and fitness perceptions were significantly correlated with PA levels. The most prevalent explanation for inadequacy in meeting NPAG was insufficient time. Conclusion: Compared to their pre-university lifestyles, biological science students at university are more likely to adopt unhealthier behaviours with less time for exercise and prolonged sedentary behaviours, which increases the risk for cardiovascular diseases. It is important to raise awareness of their fitness perceptions and to encourage health-promoting programmes at university

A convolutional neural network based deep learning methodology for recognition of partial discharge patterns from high voltage cables

It is a great challenge to differentiate partial discharge (PD) induced by different types of insulation defects in high-voltage cables. Some types of PD signals have very similar characteristics and are specifically difficult to differentiate, even for the most experienced specialists. To overcome the challenge, a convolutional neural network (CNN)-based deep learning methodology for PD pattern recognition is presented in this paper. First, PD testing for five types of artificial defects in ethylene-propylene-rubber cables is carried out in high voltage laboratory to generate signals containing PD data. Second, 3500 sets of PD transient pulses are extracted, and then 33 kinds of PD features are established. The third stage applies a CNN to the data; typical CNN architecture and the key factors which affect the CNN-based pattern recognition accuracy are described. Factors discussed include the number of the network layers, convolutional kernel size, activation function, and pooling method. This paper presents a flowchart of the CNN-based PD pattern recognition method and an evaluation with 3500 sets of PD samples. Finally, the CNN-based pattern recognition results are shown and the proposed method is compared with two more traditional analysis methods, i.e., support vector machine (SVM) and back propagation neural network (BPNN). The results show that the proposed CNN method has higher pattern recognition accuracy than SVM and BPNN, and that the novel method is especially effective for PD type recognition in cases of signals of high similarity, which is applicable for industrial applications

Recognition of 16–18-year-old adolescents for guiding physical activity interventions: a cross-sectional study

Adolescence is a rapid life stage requiring special attention wherein personal autonomy is developed to govern independent lifestyles. Unhealthy lifestyles are integral to prevailing adolescent physical inactivity patterns. Understudied 16–18-year-olds were investigated to establish physical activity prevalences and influencing health-related lifestyle factors. Adolescents were recruited randomly across 2017–2019 from Farnborough College of Technology and North Kent College, UK. Demographic and health-related lifestyle information were gathered anonymously and analysed using SAS® 9.4 software. Among the 414 adolescents included (48.3% male and 51.7% female), the mean (standard deviation (SD)) age was 16.9 (0.77). Approximately 15.2% smoked and 20.8% were overweight/obese. There were 54.8% perceiving themselves unfit and 33.3% spent >4 h/day on leisure-time screen-based activity. Around 80.4% failed to meet the recommended fruit/vegetable daily intake and 90.1% failed to satisfy UK National Physical Activity Guidelines, particularly females (p = 0.0202). Physical activity levels were significantly associated with gender, body mass index, smoking status, leisure sedentary screen-time, fruit/vegetable consumption and fitness perceptions. Those who were female, overweight/obese, non-smoking, having poor fitness perceptions, consuming low fruit/vegetables and engaging in excess screen-based sedentariness were the groups with lowest physical activity levels. Steering physical activity-oriented health interventions toward these at-risk groups in colleges may reduce the UK’s burden of adolescent obesity

CRiBAC: Community-centric role interaction based access control model

As one of the most efficient solutions to complex and large-scale problems, multi-agent cooperation has been in the limelight for the past few decades. Recently, many research projects have focused on context-aware cooperation to dynamically provide complex services. As cooperation in the multi-agent systems (MASs) becomes more common, guaranteeing the security of such cooperation takes on even greater importance. However, existing security models do not reflect the agents' unique features, including cooperation and context-awareness. In this paper, we propose a Community-based Role interaction-based Access Control model (CRiBAC) to allow secure cooperation in MASs. To do this, we refine and extend our preliminary RiBAC model, which was proposed earlier to support secure interactions among agents, by introducing a new concept of interaction permission, and then extend it to CRiBAC to support community-based cooperation among agents. We analyze potential problems related to interaction permissions and propose two approaches to address them. We also propose an administration model to facilitate administration of CRiBAC policies. Finally, we present the implementation of a prototype system based on a sample scenario to assess the proposed work and show its feasibility. © 2012 Elsevier Ltd. All rights reserved

Exploration of alcohol consumption behaviours and health-related influencing factors of young adults in the UK

Hazardous alcohol consumption is ranked above illicit drug use with regards to health deterioration and social and economic burden. This study sought to clarify the factors influencing alcohol consumption and its prevalence in young adults. Demographics, alcohol consumption and lifestyle information were gathered via anonymous questionnaires during 2011–2019, crossing Reading, Surrey and Farnborough universities, UK. Controlling for confounders, a multinomial logistic regression was performed using SAS® 9.4 software. A total of 1440 students (43.5% males, 56.5% females; 54.4% Caucasians) with a mean (SD) age of 19.9 (2.73) were included. Among them, 68.9% consumed alcohol frequently and 31.7% had �12 units/week. Statistical analysis revealed that males consumed twice more alcohol than females, odds ratio (OR) 1.67 (95% confidence interval (CI) = 1.34–2.09), p-value < 0.01. Caucasians consumed up to five times more alcohol than other ethnicities, OR 4.55 (3.57–5.56), p-value < 0.01. Smokers consumed three times more alcohol than non-smokers, OR 2.69 (1.82, 3.99), p-value < 0.01. In general, the levels of alcohol consumption were positively associated with the levels of physical activity, OR 2.00 (1.17–3.42), p-value < 0.05 and negatively associated with recreational sedentary screen-time activities in males, OR 0.31 (0.12–0.86), p-value = 0.03. Focusing alcohol interventions toward Caucasians, smokers and physically active students, particularly males, may guide university strategies to reduce alcohol-related societal harm and risks of morbidity and mortality

Nox2 dependent redox-regulation of Akt and ERK1/2 to promote left ventricular hypertrophy in dietary obesity of mice

Background A Nox2 containing NADPH oxidase (Nox2) is involved in the global oxidative stress found in dietary obesity and metabolic disorders. However, the effects of high fat diet (HFD) on cardiac Nox2 activation and signaling in left ventricular hypertrophy (LVH) remain unknown. Methods Left ventricular (LV) tissues isolated from C57BL/6J wild-type (WT) and Nox2 knockout (Nox2KO) mice (11 months old, n = 6 per group) after 4 months of HFD treatment were used. Cardiomyocyte sizes were measured digitally on LV cross-sections. The levels of cardiac reactive oxygen species (ROS) production was determined using lucigenin-chemiluminescence and in situ dihydroethidium (DHE) fluorescence. The levels of Nox subunit expression and redox signaling were examined by immunoblotting and immunofluorescence. Results In comparison to WT normal chow diet control hearts, WT HFD hearts had 1.8-fold increases in cardiomyocyte size, a sign of cardiac hypertrophy, and this was accompanied with ≥2-fold increase in the levels of ROS production, Nox2 expression and the phosphorylation of Akt and ERK1/2. Increased ROS production measured in HFD heart homogenates was inhibited to control levels by Tiron (a cell membrane permeable O2•−scavenger), diphenyleneiodonium (DPI, a flavohaemoprotein inhibitor) and Nox2 ds-tat (a Nox2 assembly inhibitor). However, all of these abnormalities were significantly reduced or absent in Nox2KO hearts under the same HFD. Conclusions Nox2 activation in response to dietary obesity and metabolic disorders plays a key role in cardiac oxidative stress, aberrant redox signaling and cardiomyocyte hypertrophy. Knockout of Nox2 protects hearts from oxidative damage associated with obesity and metabolic disorders

Development of a laser capture microscope-based single-cell-type proteomics tool for studying proteomes of individual cell layers of plant roots

Single-cell-type proteomics provides the capability to revealing the genomic and proteomics information at cell-level resolution. However, the methodology for this type of research has not been well-developed. This paper reports developing a workflow of laser capture microdissection (LCM) followed by gel-liquid chromatography-tandem mass spectrometry (GeLC-MS/MS)-based proteomics analysis for the identification of proteomes contained in individual cell layers of tomato roots. Thin-sections (~10-μm thick, 10 sections per root tip) were prepared for root tips of tomato germinating seedlings. Epidermal and cortical cells (5000–7000 cells per tissue type) were isolated under a LCM microscope. Proteins were isolated and then separated by SDS–polyacrylamide gel electrophoresis followed by in-gel-tryptic digestion. The MS and MS/MS spectra generated using nanoLC-MS/MS analysis of the tryptic peptides were searched against ITAG2.4 tomato protein database to identify proteins contained in each single-cell-type sample. Based on the biological functions, proteins with proven functions in root hair development were identified in epidermal cells but not in the cortical cells. Several of these proteins were found in Al-treated roots only. The results demonstrated that the cell-type-specific proteome is relevant for tissue-specific functions in tomato roots. Increasing the coverage of proteomes and reducing the inevitable cross-contamination from adjacent cell layers, in both vertical and cross directions when cells are isolated from slides prepared using intact root tips, are the major challenges using the technology in proteomics analysis of plant roots

The Al-induced proteomes of epidermal and outer cortical cells in root apex of cherry tomato \u27LA 2710\u27

This paper reports a laser capture microdissection-tandem mass tag-quantitative proteomics analysis of Al-sensitive cells in root tips. Cherry tomato (Solanum lycopersicum var. cerasiforme ‘LA2710’) seedlings were treated under 15 μM Al3+ activity for 13 d. Root-tip longitudinal fresh frozen tissue sections of 10 μm thickness were prepared. The Al-sensitive root zone and cells were determined using histochemical analysis of root-tips and micro-sections. A procedure for collecting the Al-sensitive cells using laser capture microdissection-protein extraction-tandem mass tag-proteomics analysis was developed. Proteomics analysis of 18 μg protein/sample with three biological replicates per treatment condition identified 3879 quantifiable proteins each associated with two or more unique peptides. Quantified proteins constituted a broad range of Kyoto Encyclopedia of Genes and Genomes pathways when searched in the annotated tomato genome. Differentially expressed proteins between the Al-treated and non-Al treated control conditions were identified, including 128 Al-up-regulated and 32 Al-down-regulated proteins. Analysis of functional pathways and protein-protein interaction networks showed that the Al-down-regulated proteins are involved in transcription and translation, and the Al-up-regulated proteins are associated with antioxidant and detoxification and protein quality control processes. The proteomics data are available via ProteomeXchange with identifier PXD010459 under project title ‘LCM-quantitative proteomics analysis of Al-sensitive tomato root cells’. Significance This paper presents an efficient laser capture microdissection-tandem mass tag-quantitative proteomics analysis platform for the analysis of Al sensitive root cells. The analytical procedure has a broad application for proteomics analysis of spatially separated cells from complex tissues. This study has provided a comprehensive proteomics dataset expressed in the epidermal and outer-cortical cells at root-tip transition zone of Al-treated tomato seedlings. The proteomes from the Al-sensitive root cells are valuable resources for understanding and improving Al tolerance in plants