PLOS ONE: [sortOrder=DATE_NEWEST_FIRST, sort=Date, newest first, q=subject:"Electronics"]PLOShttps://journals.plos.org/plosone/webmaster@plos.orgaccelerating the publication of peer-reviewed sciencehttps://journals.plos.org/plosone/search/feed/atom?sortOrder=DATE_NEWEST_FIRST&unformattedQuery=subject:%22Electronics%22&sort=Date,+newest+firstAll PLOS articles are Open Access.https://journals.plos.org/plosone/resource/img/favicon.icohttps://journals.plos.org/plosone/resource/img/favicon.ico2024-03-28T08:48:02ZCombining diaries and accelerometers to explain change in physical activity during a lifestyle intervention for adults with pre-diabetes: A PREVIEW sub-studyLeon KlosGareth StrattonKelly A. MackintoshMelitta A. McNarryMikael FogelholmMathijs DrummenIan MacdonaldJ. Alfredo MartinezSantiago Navas-CarreteroTeodora Handjieva-DarlenskaGeorgi BogdanovNicholas GantSally D. PoppittMarta P. SilvestreJennie Brand-MillerRoslyn MuirheadWolfgang SchlichtMaija Huttunen-LenzShannon BrodieElli JaloMargriet Westerterp-PlantengaTanja AdamPia Siig VestentoftHeikki TikkanenJonas S. QuistAnne RabenNils Swindell10.1371/journal.pone.03006462024-03-21T14:00:00Z2024-03-21T14:00:00Z<p>by Leon Klos, Gareth Stratton, Kelly A. Mackintosh, Melitta A. McNarry, Mikael Fogelholm, Mathijs Drummen, Ian Macdonald, J. Alfredo Martinez, Santiago Navas-Carretero, Teodora Handjieva-Darlenska, Georgi Bogdanov, Nicholas Gant, Sally D. Poppitt, Marta P. Silvestre, Jennie Brand-Miller, Roslyn Muirhead, Wolfgang Schlicht, Maija Huttunen-Lenz, Shannon Brodie, Elli Jalo, Margriet Westerterp-Plantenga, Tanja Adam, Pia Siig Vestentoft, Heikki Tikkanen, Jonas S. Quist, Anne Raben, Nils Swindell</p>
Self-report and device-based measures of physical activity (PA) both have unique strengths and limitations; combining these measures should provide complementary and comprehensive insights to PA behaviours. Therefore, we aim to 1) identify PA clusters and clusters of change in PA based on self-reported daily activities and 2) assess differences in device-based PA between clusters in a lifestyle intervention, the PREVIEW diabetes prevention study. In total, 232 participants with overweight and prediabetes (147 women; 55.9 ± 9.5yrs; BMI ≥25 kg·m<sup>-2</sup>; impaired fasting glucose and/or impaired glucose tolerance) were clustered using a partitioning around medoids algorithm based on self-reported daily activities before a lifestyle intervention and their changes after 6 and 12 months. Device-assessed PA levels (PAL), sedentary time (SED), light PA (LPA), and moderate-to-vigorous PA (MVPA) were assessed using ActiSleep+ accelerometers and compared between clusters using (multivariate) analyses of covariance. At baseline, the self-reported “walking and housework” cluster had significantly higher PAL, MVPA and LPA, and less SED than the “inactive” cluster. LPA was higher only among the “cycling” cluster. There was no difference in the device-based measures between the “social-sports” and “inactive” clusters. Looking at the changes after 6 months, the “increased walking” cluster showed the greatest increase in PAL while the “increased cycling” cluster accumulated the highest amount of LPA. The “increased housework” and “increased supervised sports” reported least favourable changes in device-based PA. After 12 months, there was only minor change in activities between the “increased walking and cycling”, “no change” and “increased supervised sports” clusters, with no significant differences in device-based measures. Combining self-report and device-based measures provides better insights into the behaviours that change during an intervention. Walking and cycling may be suitable activities to increase PA in adults with prediabetes.Enhancing electric vehicle charging performance through series-series topology resonance-coupled wireless power transferNadir BenaliaIdriss BenlalouiKouider LaroussiAhmad ElkhatebDaniel Eutyche Mbadjoun WapetAmmar M. HassanMohamed Metwally Mahmoud10.1371/journal.pone.03005502024-03-21T14:00:00Z2024-03-21T14:00:00Z<p>by Nadir Benalia, Idriss Benlaloui, Kouider Laroussi, Ahmad Elkhateb, Daniel Eutyche Mbadjoun Wapet, Ammar M. Hassan, Mohamed Metwally Mahmoud</p>
The current electric vehicles (EVs) market is experiencing significant expansion, underscoring the need to address challenges associated with the limited driving range of EVs. A primary focus in this context is the improvement of the wireless charging process. To contribute to this research area, this study introduces a circular spiral coil design that incorporates transceiver coils. First, an in-depth analysis is conducted using Ansys Maxwell software to assess the effectiveness of the proposed solution through the magnetic field distribution, inductance properties, and mutual inductance between receiver and transmitter coils. In the next step, a direct shielding technique is applied, integrating a ferrite core bar to reduce power leakage and enhance power transmission efficiency. The ferrite magnetic shielding guides magnetic field lines, resulting in a significant reduction in flux leakage and improved power transmission. Lastly, a magnetic resonance series (SS) compensation wireless system is developed to achieve high coupling efficiency and superior performance. The system’s effectiveness is evaluated through co-simulation using Ansys Simplorer software. The results confirm the effectiveness of the proposed solution, showing its ability to transmit 3.6 kilowatts with a success rate approaching 99%. This contribution significantly advances the development of wireless charging systems for electric vehicles, addressing concerns and promoting global adoption.Solid waste management practices and challenges in Besisahar municipality, NepalMahendra AryalSanju Adhikary10.1371/journal.pone.02927582024-03-21T14:00:00Z2024-03-21T14:00:00Z<p>by Mahendra Aryal, Sanju Adhikary</p>
This study is a comprehensive assessment of the waste management system in Besisahar municipality. Information and some data have been collected from the municipality of Besisahar, followed by interviews with municipal officials responsible for waste management, stakeholders, waste workers, and residents. A total of 230 households, 20 schools, 10 government and private offices, 10 financial institutions, 60 commercial hotels, restaurants, and shops, and 20 medical shops and healthcare institutions, were selected in this study by random sampling. An extensive field study was conducted within all municipal wards and at dump sites. The results indicated that 42.14% of solid waste was collected through door-to-door collection services, 5.87% was mismanaged in open public places, 11.21% was used as compost manure, and the rest was discarded on riverbanks, dug up, and burned. A large component of the characterization of household waste consisted of organic waste (68.03%), followed by paper/paper products (8.13%), agricultural waste (5.5%), plastic (5.21%), construction (3.81%), textile (2.72%), metals (0.54%), glass (1.01%), rubber (0.10%), electronic (0.05%), pharmaceutical (0.1%) and others (4.78%) in the Besishahar municipality. Solid waste generation was found to be at 197.604 g/capita/day, as revealed by cluster sampling in 230 households. Around 4.285 tons-solid waste/day were generated in urban areas, while 16.13 tons-solid waste/day was estimated for the whole municipality. An important correlation between the parameters of solid waste was found by statistical analysis. Currently, solid waste is dumped on riverbanks, open fields, and springs, creating environmental and health hazards. The findings of this study will be useful to Besisahar municipality and its stakeholders in forming policies that facilitate waste management practices in this region and promote sustainable waste management systems.Strategic styles of hardware product development could accelerate commercialization in cleantech startupsErin LooneyAndré BuscariolliMaria C. YangGeoffrey RaymondTonio BuonassisiIan Marius Peters10.1371/journal.pstr.00001012024-03-20T14:00:00Z2024-03-20T14:00:00Z<p>by Erin Looney, André Buscariolli, Maria C. Yang, Geoffrey Raymond, Tonio Buonassisi, Ian Marius Peters</p>
Hardware-based startups risk having longer times-to-market, deterring investment in the clean technologies that are critical to a sustainable future. We interviewed 55 leaders at hardware startups, 20 of which are cleantech, mapped their development timelines, and found prototyping to be the longest development step (median of 19 weeks per prototype) regardless of prototype complexity or iteration. Qualitative interview analysis reveals the prototyping team’s choice of development style is a major factor affecting timeline. We define two development styles: natural and structured, typified by free-form exploration and rule-based execution, respectively. On average, natural development takes 35% less time than structured, and is thus preferred for early iterations, but adopting structure at strategic points is needed for timely commercialization. Critical points of transition to a structured style include adding new team members or engaging external partners, which demand clear communication and expectations. When pivoting to a new product or market, returning to a natural style is beneficial.Statistical segmentation model for accurate electrode positioning in Parkinson’s deep brain stimulation based on clinical low-resolution image data and electrophysiologyIgor VargaEduard BaksteinGreydon GilmoreJaromir MayDaniel Novak10.1371/journal.pone.02983202024-03-14T14:00:00Z2024-03-14T14:00:00Z<p>by Igor Varga, Eduard Bakstein, Greydon Gilmore, Jaromir May, Daniel Novak</p>
Background <p>Deep Brain Stimulation (DBS), applying chronic electrical stimulation of subcortical structures, is a clinical intervention applied in major neurologic disorders. In order to achieve a good clinical effect, accurate electrode placement is necessary. The primary localisation is typically based on presurgical MRI imaging, often followed by intra-operative electrophysiology recording to increase the accuracy and to compensate for brain shift, especially in cases where the surgical target is small, and there is low contrast: e.g., in Parkinson’s disease (PD) and in its common target, the subthalamic nucleus (STN).</p> Methods <p>We propose a novel, fully automatic method for intra-operative surgical navigation. First, the surgical target is segmented in presurgical MRI images using a statistical shape-intensity model. Next, automated alignment with intra-operatively recorded microelectrode recordings is performed using a probabilistic model of STN electrophysiology. We apply the method to a dataset of 120 PD patients with clinical T2 1.5T images, of which 48 also had available microelectrode recordings (MER).</p> Results <p>The proposed segmentation method achieved STN segmentation accuracy around dice = 0.60 compared to manual segmentation. This is comparable to the state-of-the-art on low-resolution clinical MRI data. When combined with electrophysiology-based alignment, we achieved an accuracy of 0.85 for correctly including recording sites of STN-labelled MERs in the final STN volume.</p> Conclusion <p>The proposed method combines image-based segmentation of the subthalamic nucleus with microelectrode recordings to estimate their mutual location during the surgery in a fully automated process. Apart from its potential use in clinical targeting, the method can be used to map electrophysiological properties to specific parts of the basal ganglia structures and their vicinity.</p>Relative income concerns and smoking behaviour: The role of unobserved heterogeneityAlpaslan AkayAsena Caner10.1371/journal.pone.02953332024-03-14T14:00:00Z2024-03-14T14:00:00Z<p>by Alpaslan Akay, Asena Caner</p>
Status or relative concerns (as in the idiom ‘keeping up with the Joneses’) can lead to negative feelings such as stress and anxiety. One key question is whether these concerns relate to daily smoking behaviour. The conjecture is that status concerns and the accompanying stress and anxiety might be associated with a higher likelihood of smoking and a higher number of cigarettes smoked, generating a higher instant physical reward and reducing the stress and anxiety. The literature aiming to identify this relationship focuses mostly on a single cross section of individuals, ignoring potential differences in unobserved characteristics of smokers and non-smokers (e.g., genetic factors, personality differences, parental smoking during childhood). This paper investigates the role of unobserved individual characteristics on this relationship, which has not been done in previous studies. Using a long panel data of smoking information in Germany and a variety of panel data model specifications, we show that there is no statistically significant association between relative income concerns and the likelihood of smoking or the number of cigarettes smoked among the overall population. We find a positive and significant relationship only among people who smoked at least one cigarette in the past. A 10% appreciation in the income of comparable other individuals relates to about 3.5 more cigarettes per month among these people. Importantly, failing to allow for the unobserved influences of smoking leads to three times larger estimates than when using models with unobserved factors correlating to the income and smoking behaviour. The results are robust with respect to alternative assumptions and specifications where we use different functional forms of unobserved heterogeneity, definitions of relative concerns, incomes, and reference groups.End-to-end deep learning approach to mouse behavior classification from cortex-wide calcium imagingTakehiro AjiokaNobuhiro NakaiOkito YamashitaToru Takumi10.1371/journal.pcbi.10110742024-03-13T14:00:00Z2024-03-13T14:00:00Z<p>by Takehiro Ajioka, Nobuhiro Nakai, Okito Yamashita, Toru Takumi</p>
Deep learning is a powerful tool for neural decoding, broadly applied to systems neuroscience and clinical studies. Interpretable and transparent models that can explain neural decoding for intended behaviors are crucial to identifying essential features of deep learning decoders in brain activity. In this study, we examine the performance of deep learning to classify mouse behavioral states from mesoscopic cortex-wide calcium imaging data. Our convolutional neural network (CNN)-based end-to-end decoder combined with recurrent neural network (RNN) classifies the behavioral states with high accuracy and robustness to individual differences on temporal scales of sub-seconds. Using the CNN-RNN decoder, we identify that the forelimb and hindlimb areas in the somatosensory cortex significantly contribute to behavioral classification. Our findings imply that the end-to-end approach has the potential to be an interpretable deep learning method with unbiased visualization of critical brain regions.Validity, reliability, and readability of single-item and short physical activity questionnaires for use in surveillance: A systematic reviewAntonina TcymbalSven MessingRachel MaitRoberto Galindo PerezTaiyeba AkterIvo RakovacPeter GeliusKarim Abu-Omar10.1371/journal.pone.03000032024-03-12T14:00:00Z2024-03-12T14:00:00Z<p>by Antonina Tcymbal, Sven Messing, Rachel Mait, Roberto Galindo Perez, Taiyeba Akter, Ivo Rakovac, Peter Gelius, Karim Abu-Omar</p>
Background <p>Accurate and fast measurement of physical activity is important for surveillance. Even though many physical activity questionnaires (PAQ) are currently used in research, it is unclear which of them is the most reliable, valid, and easy to use. This systematic review aimed to identify existing brief PAQs, describe and compare their measurement properties, and assess their level of readability.</p> Methods <p>We performed a systematic review based on the PRISMA statement. Literature searches were conducted in six scientific databases. Articles were included if they evaluated validity and/or reliability of brief (i.e., with a maximum of three questions) physical activity or exercise questionnaires intended for healthy adults. Due to the heterogeneity of studies, data were summarized narratively. The level of readability was calculated according to the Flesch-Kincaid formula.</p> Results <p>In total, 35 articles published in English or Spanish were included, evaluating 32 distinct brief PAQs. The studies indicated moderate to good levels of reliability for the PAQs. However, the majority of results showed weak validity when validated against device-based measurements and demonstrated weak to moderate validity when validated against other PAQs. Most of the assessed PAQs met the criterion of being "short," allowing respondents to complete them in less than one minute either by themselves or with an interviewer. However, only 17 questionnaires had a readability level that indicates that the PAQ is easy to understand for the majority of the population.</p> Conclusions <p>This review identified a variety of brief PAQs, but most of them were evaluated in only a single study. Validity and reliability of short and long questionnaires are found to be at a comparable level, short PAQs can be recommended for use in surveillance systems. However, the methods used to assess measurement properties varied widely across studies, limiting the comparability between different PAQs and making it challenging to identify a single tool as the most suitable. None of the evaluated brief PAQs allowed for the measurement of whether a person fulfills current WHO physical activity guidelines. Future development or adaptation of PAQs should prioritize readability as an important factor to enhance their usability.</p>Development of a multi-wear-site, deep learning-based physical activity intensity classification algorithm using raw acceleration dataJohan Y. Y. NgJoni H. ZhangStanley S. HuiGuanxian JiangFung YauJames ChengAmy S. Ha10.1371/journal.pone.02992952024-03-07T14:00:00Z2024-03-07T14:00:00Z<p>by Johan Y. Y. Ng, Joni H. Zhang, Stanley S. Hui, Guanxian Jiang, Fung Yau, James Cheng, Amy S. Ha</p>
Background <p>Accelerometers are widely adopted in research and consumer devices as a tool to measure physical activity. However, existing algorithms used to estimate activity intensity are wear-site-specific. Non-compliance to wear instructions may lead to misspecifications. In this study, we developed deep neural network models to classify device placement and activity intensity based on raw acceleration data. Performances of these models were evaluated by making comparisons to the ground truth and results derived from existing count-based algorithms.</p> Methods <p>54 participants (26 adults 26.9±8.7 years; 28 children, 12.1±2.3 years) completed a series of activity tasks in a laboratory with accelerometers attached to each of their hip, wrist, and chest. Their metabolic rates at rest and during activity periods were measured using the portable COSMED K5; data were then converted to metabolic equivalents, and used as the ground truth for activity intensity. Deep neutral networks using the Long Short-Term Memory approach were trained and evaluated based on raw acceleration data collected from accelerometers. Models to classify wear-site and activity intensity, respectively, were evaluated.</p> Results <p>The trained models correctly classified wear-sites and activity intensities over 90% of the time, which outperformed count-based algorithms (wear-site correctly specified: 83% to 85%; wear-site misspecified: 64% to 75%). When additional parameters of age, height and weight of participants were specified, the accuracy of some prediction models surpassed 95%.</p> Conclusions <p>Results of the study suggest that accelerometer placement could be determined prospectively, and non-wear-site-specific algorithms had satisfactory accuracies. The performances, in terms of intensity classification, of these models also exceeded typical count-based algorithms. Without being restricted to one specific wear-site, research protocols for accelerometers wear could allow more autonomy to participants, which may in turn improve their acceptance and compliance to wear protocols, and in turn more accurate results.</p>Diagnosis of human brucellosis: Systematic review and meta-analysisMariana Lourenço FreireTália Santana Machado de AssisSarah Nascimento SilvaGláucia Cota10.1371/journal.pntd.00120302024-03-07T14:00:00Z2024-03-07T14:00:00Z<p>by Mariana Lourenço Freire, Tália Santana Machado de Assis, Sarah Nascimento Silva, Gláucia Cota</p>
Background <p>Brucellosis, a widely spread zoonotic disease, poses significant diagnostic challenges due to its non-specific symptoms and underreporting. Timely and accurate diagnosis is crucial for effective patient management and public health control. However, a comprehensive comparative review of available diagnostic tests is lacking.</p> Methodology/Principal findings <p>This systematic review addressed the following question: ‘What is the accuracy of the available tests to confirm human brucellosis?’ Two independent reviewers examined articles published up to January 2023. The review included original studies reporting symptomatic patients with brucellosis suspicion, through any index test, with sensitivity and/or specificity as outcomes. As exclusion criteria were considered: sample size smaller than 10 patients, studies focusing on complicated brucellosis, and those lacking essential information about index or comparator tests. Sensitivity and specificity were assessed, with consideration for the index test, and ‘culture’ and ‘culture and standard tube agglutination test (SAT)’ were used as reference standards. Bias assessment and certainty of evidence were carried out using the QUADAS-2 and GRADE tools, respectively. A total of 38 studies reporting diagnostic test performance for human brucellosis were included. However, the evidence available is limited, and significant variability was observed among studies. Regarding the reference test, culture and/or SAT are deemed more appropriate than culture alone. Rose Bengal, IgG/IgM ELISA, and PCR exhibited equally high performances, indicating superior overall diagnostic accuracy, with very low certainty of the evidence.</p> Conclusions/Significance <p>This systematic review underscores the potential of the Rose Bengal test, IgG/IgM ELISA, and PCR as promising diagnostic tools for brucellosis. However, the successful implementation and recommendations for their use should consider the local context and available resources. The findings highlight the pressing need for standardization, improved reporting, and ongoing advancements in test development to enhance the accuracy and accessibility of brucellosis diagnosis.</p>Underwater object detection method based on learnable query recall mechanism and lightweight adapterXi LinXixia HuangLe Wang10.1371/journal.pone.02987392024-02-28T14:00:00Z2024-02-28T14:00:00Z<p>by Xi Lin, Xixia Huang, Le Wang</p>
With the rapid development of ocean observation technology, underwater object detection has begun to occupy an essential position in the fields of aquaculture, environmental monitoring, marine science, etc. However, due to the problems unique to underwater images such as severe noise, blurred objects, and multi-scale, deep learning-based target detection algorithms lack sufficient capabilities to cope with these challenges. To address these issues, we improve DETR to make it well suited for underwater scenarios. First, a simple and effective learnable query recall mechanism is proposed to mitigate the effect of noise and can significantly improve the detection performance of the object. Second, for underwater small and irregular object detection, a lightweight adapter is designed to provide multi-scale features for the encoding and decoding stages. Third, the regression mechanism of the bounding box is optimized using the combination loss of smooth <i>L</i><sub>1</sub> and CIoU. Finally, we validate the designed network against other state-of-the-art methods on the RUOD dataset. The experimental results show that the proposed method is effective.Open-source milligram-scale, four channel, automated protein purification systemRobert R. PuccinelliSamia S. SamaCaroline M. WorthingtonAndreas S. PuschnikJohn E. PakRafael Gómez-Sjöberg10.1371/journal.pone.02978792024-02-23T14:00:00Z2024-02-23T14:00:00Z<p>by Robert R. Puccinelli, Samia S. Sama, Caroline M. Worthington, Andreas S. Puschnik, John E. Pak, Rafael Gómez-Sjöberg</p>
Liquid chromatography purification of multiple recombinant proteins, in parallel, could catalyze research and discovery if the processes are fast and approach the robustness of traditional, “one-protein-at-a-time” purification. Here, we report an automated, four channel chromatography platform that we have designed and validated for parallelized protein purification at milligram scales. The device can purify up to four proteins (each with its own single column), has inputs for up to eight buffers or solvents that can be directed to any of the four columns via a network of software-driven valves, and includes an automated fraction collector with ten positions for 1.5 or 5.0 mL collection tubes and four positions for 50 mL collection tubes for each column output. The control software can be accessed either via Python scripting, giving users full access to all steps of the purification process, or via a simple-to-navigate touch screen graphical user interface that does not require knowledge of the command line or any programming language. Using our instrument, we report milligram-scale, parallelized, single-column purification of a panel of mammalian cell expressed coronavirus (SARS-CoV-2, HCoV-229E, HCoV-OC43, HCoV-229E) trimeric Spike and monomeric Receptor Binding Domain (RBD) antigens, and monoclonal antibodies targeting SARS-CoV-2 Spike (S) and Influenza Hemagglutinin (HA). We include a detailed hardware build guide, and have made the controlling software open source, to allow others to build and customize their own protein purifier systems.Protocol for an observational study of working conditions and musculoskeletal health in Swedish online retail warehousing from the perspective of sex/gender and place of birthJennie A. JacksonSvend Erik MathiassenKlara RydströmKristina Johansson10.1371/journal.pone.02975692024-02-23T14:00:00Z2024-02-23T14:00:00Z<p>by Jennie A. Jackson, Svend Erik Mathiassen, Klara Rydström, Kristina Johansson</p>
European and International sustainable development agendas aim to reduce inequalities in working conditions and work-related health, yet disparate occupational health outcomes are evident between both men and women and domestic- and foreign-born workers. In Sweden, major growth in online retail warehousing has increased occupational opportunities for foreign-born workers. The rapid change has left research lagging on working conditions, i.e., employment conditions, facility design, work organisation, physical and psychosocial work environment conditions, and their effects on worker health. Further, no known studies have considered patterns of inequality related to these factors. The overall aim of this study is to describe working conditions and musculoskeletal health in online retail warehousing, determine the extent to which differences exist related to sex/gender and place of birth (as a proxy for race/ethnicity), and examine factors at the organisational and individual levels to understand why any differences exist. Three online retail warehouses, each employing 50–150 operations workers performing receiving, order picking, order packing and dispatching tasks will be recruited. Warehouses will, to the extent possible, differ in their extent of digital technology use. Employment conditions, facility design (including digital tool use), work organisation, physical and psychosocial work environment conditions and worker health will be assessed by survey, interview and technical measurements. Analysis of quantitative data stratified by sex and place of birth will consider the extent to which inequalities exist. Focus group interviews with operations employees and in-depth interviews with managers, union and health and safety representatives will be conducted to assess how employee working conditions and musculoskeletal health are related to inequality regimes of sex/gender and/or race/ethnicity in organisational processes and practices in online retail warehousing. The study is pre-registered with the Open Science Framework. This study will describe working conditions and health in online retail warehouse workers and consider the extent to which patterns of inequality exist based on sex/gender and place of birth.Sedentary behaviour (especially accumulation pattern) has an independent negative impact on skeletal muscle size and architecture in community-dwelling older adultsJorgen A. WullemsHans DegensSabine M. P. VerschuerenChristopher I. MorseDale M. GrantGladys L. Onambélé-Pearson10.1371/journal.pone.02945552024-02-23T14:00:00Z2024-02-23T14:00:00Z<p>by Jorgen A. Wullems, Hans Degens, Sabine M. P. Verschueren, Christopher I. Morse, Dale M. Grant, Gladys L. Onambélé-Pearson</p>
Prolonged sedentary behaviour (SB) i.e. longer bouts, is suggested to have a range of negative health effects, independent of habitual light and medium-to-vigorous physical activity (LIPA or MVPA). Any effect on musculoskeletal size, architecture or morphology has seldom been reported in older adults. Moreover, no study has yet determined if any association would persist following adjustment for covariates. Therefore, the aim of the present study was to investigate the associations between SB, and properties of the <i>Gastrocnemius Medialis</i> (GM) muscle, in a cross-sectional sample of older adults using compositional data analysis. 105 healthy older adults (73±6y) wore a thigh mounted tri-axial accelerometer for seven consecutive days, and underwent ultrasound [e.g. muscle length (L<sub>m</sub>), anatomical cross-sectional area (ACSA), muscle volume (V<sub>M</sub>), fascicle length (L<sub>F</sub>), & physiological cross-sectional area (PCSA)], body composition (e.g. DEXA) and health (e.g. medical history) assessments. In-unadjusted models, SB time was negatively associated with ACSA at 75% of L<sub>m</sub> (R<sup>2</sup><sub>adj</sub> = 0.085), V<sub>M</sub> (R<sup>2</sup><sub>adj</sub> = 0.020), and PCSA (R<sup>2</sup><sub>adj</sub> = 0.039). Standing was positively associated with pennation angle (R<sup>2</sup><sub>adj</sub> = 0.110), which persisted following co-variate adjustment (R<sup>2</sup><sub>adj</sub> = 0.296). In fully adjusted models, both SB & LIPA time were associated with ACSA at 75% of L<sub>m</sub> (Both R<sup>2</sup><sub>adj</sub> = 0.393). Standing and light activity time were also associated with L<sub>F</sub>, V<sub>M</sub>, & PCSA (R<sup>2</sup><sub>adj</sub> 0.116–0.573). In fully adjusted models, SB pattern parameters (i.e. the manner in which sedentary behaviour is accumulated daily throughout waking hours such as the timing, duration and frequency of sedentary bouts), were associated with <i>GM</i> muscle properties (R<sup>2</sup><sub>adj</sub> 0.156–0.564) including L<sub>M</sub>, L<sub>F</sub>, and V<sub>M</sub>. The pattern, rather than accumulated daily SB time, was associated with the size and architecture of the <i>GM</i>. Our results suggest that regardless of co-existing habitual physical activities, SB bouts should be kept short and frequently interrupted to offset some of the deleterious ageing-related muscle architecture characteristics changes.Accelerometer-measured 24-hour movement behaviours over 7 days in Malaysian children and adolescents: A cross-sectional studySophia M. BradyRuth SalwayJeevitha MariapunLouise MillardAmutha RamadasHussein RizalAndy SkinnerChris StoneLaura JohnsonTin Tin SuMiranda E. G. Armstrong10.1371/journal.pone.02971022024-02-20T14:00:00Z2024-02-20T14:00:00Z<p>by Sophia M. Brady, Ruth Salway, Jeevitha Mariapun, Louise Millard, Amutha Ramadas, Hussein Rizal, Andy Skinner, Chris Stone, Laura Johnson, Tin Tin Su, Miranda E. G. Armstrong</p>
Background <p>Quantifying movement behaviours over 24-hours enables the combined effects of and inter-relations between sleep, sedentary time and physical activity (PA) to be understood. This is the first study describing 24-hour movement behaviours in school-aged children and adolescents in South-East Asia. Further aims were to investigate between-participant differences in movement behaviours by demographic characteristics and timing of data collection during Ramadan and COVID-19 restrictions.</p> Methods <p>Data came from the South-East Asia Community Observatory health surveillance cohort, 2021–2022. Children aged 7–18 years within selected households in Segamat, Malaysia wore an Axivity AX6 accelerometer on their wrist for 24 hours/day over 7 days, completed the PAQ-C questionnaire, and demographic information was obtained. Accelerometer data was processed using GGIR to determine time spent asleep, inactive, in light-intensity PA (LPA) and moderate-to-vigorous PA (MVPA). Differences in accelerometer-measured PA by demographic characteristics (sex, age, ethnicity, socioeconomic group) were explored using univariate linear regression. Differences between data collected during vs outside Ramadan or during vs after COVID-19 restrictions, were investigated through univariate and multiple linear regressions, adjusted for age, sex and ethnicity.</p> Results <p>The 491 participants providing accelerometer data spent 8.2 (95% confidence interval (CI) = 7.9–8.4) hours/day asleep, 12.4 (95% CI = 12.2–12.7) hours/day inactive, 2.8 (95% CI = 2.7–2.9) hours/day in LPA, and 33.0 (95% CI = 31.0–35.1) minutes/day in MVPA. Greater PA and less time inactive were observed in boys vs girls, children vs adolescents, Indian and Chinese vs Malay children and higher income vs lower income households. Data collection during Ramadan or during COVID-19 restrictions were not associated with MVPA engagement after adjustment for demographic characteristics.</p> Conclusions <p>Demographic characteristics remained the strongest correlates of accelerometer-measured 24-hour movement behaviours in Malaysian children and adolescents. Future studies should seek to understand why predominantly girls, adolescents and children from Malay ethnicities have particularly low movement behaviours within Malaysia.</p>