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The development of computational models for simulating tumor growth and response to treatment has gained significant momentum during the last few decades. At the dawn of the era of personalized medicine, providing insight into complex mechanisms involved in cancer and contributing to patient-specific therapy optimization constitute particularly inspiring pursuits. The in silico oncology community is facing the great challenge of effectively translating simulation models into clinical practice, which presupposes a thorough sensitivity analysis, adaptation and validation process based on real clinical data. In this paper, the behavior of a clinically-oriented, multiscale model of solid tumor response to chemotherapy is investigated, using the paradigm of nephroblastoma response to preoperative chemotherapy in the context of the SIOP/GPOH clinical trial. A sorting of the model's parameters according to the magnitude of their effect on the output has unveiled the relative importance of the corresponding biological mechanisms; major impact on the result of therapy is credited to the oxygenation and nutrient availability status of the tumor and the balance between the symmetric and asymmetric modes of stem cell division. The effect of a number of parameter combinations on the extent of chemotherapy-induced tumor shrinkage and on the tumor's growth rate are discussed. A real clinical case of nephroblastoma has served as a proof of principle study case, demonstrating the basics of an ongoing clinical adaptation and validation process. By using clinical data in conjunction with plausible values of model parameters, an excellent fit of the model to the available medical data of the selected nephroblastoma case has been achieved, in terms of both volume reduction and histological constitution of the tumor. In this context, the exploitation of multiscale clinical data drastically narrows the window of possible solutions to the clinical adaptation problem.

Objective This case study examined implementation of the National Health Services Standards (NHSSs) as a continuous quality improvement (CQI) process at three church-based health facilities in Papua New Guinea. This process was designed to improve quality of care and accredit the level three health centers to level four as district hospitals to provide a higher level of care. The aims of the paper are to critically examine driving and restraining forces in CQI implementation and analyses how power influences agenda setting for change. Methods Semi-structured interviews were conducted with nine managers and eight health workers as well as three focus group discussions with health workers from three rural church-based health facilities in Morobe and Madang provinces. They included senior, mid-level and frontline managers and medical doctors, health extension officers, nursing officers and community health workers. Thematic analysis was used as an inductive and deductive process in which applied force field analysis, leadership-member exchange (LMX) theory and agenda setting was applied. Results Qualitative analysis showed how internal and external factors created urgency for change. The CQI process was designed as a collective process. Power relations operated at and between various levels: the facilities, which supported or undermined the change process; between management whereby the national management supported the quality improvement agenda, but the regional management exercised positional power in form of inaction. Theoretical analysis identified the ‘missing bit in the middle’ shaped by policy actors who exercise power over policy formulation and constrained financial and technical resources. Analysis revealed how to reduce restraining forces and build on driving forces to establish a new equilibrium. Conclusion Multiple theories contributed to the analysis showing how to resolve problematic power relations by building high-quality, effective communication of senior leadership with mid-level management and reactivated broad collaborative processes at the health facilities. Addressing the ‘missing bit in the middle’ by agenda setting can improve implementation of the NHSSs as a quality improvement process. The paper concludes with learning for policy makers, managers and health workers by highlighting to pay close attention to institutional power dynamics and practices.

Rule-based languages such as Kappa excel in their support for handling the combinatorial complexities prevalent in many biological systems, including signalling pathways. But Kappa provides little structure for organising rules, and large models can therefore be hard to read and maintain. This paper introduces a high-level, modular extension of Kappa called LBS-κ. We demonstrate the constructs of the language through examples and three case studies: a chemotaxis switch ring, a MAPK cascade, and an insulin signalling pathway. We then provide a formal definition of LBS-κ through an abstract syntax and a translation to plain Kappa. The translation is implemented in a compiler tool which is available as a web application. We finally demonstrate how to increase the expressivity of LBS-κ through embedded scripts in a general-purpose programming language, a technique which we view as generally applicable to other domain specific languages.

The study of security and privacy in vehicular ad hoc networks (VANETs) has become a hot topic that is wide open to discussion. As the quintessence of this aspect, authentication schemes deployed in VANETs play a substantial role in providing secure communication among vehicles and the surrounding infrastructures. Many researchers have proposed a variety of schemes related to information verification and computation efficiency in VANETs. In 2018, Kazemi et al. proposed an evaluation and improvement work towards Azees et al.’s efficient anonymous authentication with conditional privacy-preserving (EAAP) scheme for VANETs. They claimed that the EAAP suffered from replaying attacks, impersonation attacks, modification attacks, and cannot provide unlinkability. However, we also found out if Kazemi et al.’s scheme suffered from the unlinkability issue that leads to a forgery attack. An adversary can link two or more messages sent by the same user by applying Euclid’s algorithm and derives the user’s authentication key. To remedy the issue, in this paper, we proposed an improvement by encrypting the message using a shared secret key between sender and receiver and apply a Nonce in the final message to guarantee the unlinkability between disseminated messages.

Surgery induced inflammation is a potent promoter of tumour recurrence and metastasis in colorectal cancer. The recently discovered family of Nox enzymes represent a major source of endogenous reactive oxygen species (ROS) and are now heavily implicated in tumour cell metastasis. Interestingly, Nox enzymes can be 'purposefully' activated by inflammatory cytokines and growth factors which are present in abundance in the peri-operative window. As colon cancer cells express Nox enzymes and Toll-like receptor 4 (TLR-4), we hypothesised that LPS may potentiate the ability of colon cancer cells to metastasise via Nox enzyme mediated redox signalling. In support of this hypothesis, this paper demonstrates that LPS induces a significant, transient increase of endogenous ROS in SW480, SW620 and CT-26 colon cancer cells. This increase in LPS-induced ROS activity is completely abrogated by a Nox inhibitor, diphenyleneiodonium (DPI), Nox1 siRNA and an NF-κB inhibitor, Dihydrochloride. A significant increase in Nox1 and Nox2 protein expression occurs following LPS treatment. Inhibition of NF-κB also attenuates the increase of Nox1 and Nox2 protein expression. The sub-cellular location of LPS-induced ROS generation lies mainly in the endoplasmic reticulum. LPS activates the PI3K/Akt pathway via Nox generated ROS and this signal is inhibited by DPI. This LPS activated Nox mechanism facilitates a significant increase in SW480 colon cancer cell adhesion to collagen I, which is inhibited by DPI, Nox1 siRNA and a PI3K inhibitor. Altogether, these data suggest that the LPS-Nox1 redox signalling axis plays a crucial role in facilitation of colon cancer cell adhesion, thus increasing the metastatic potential of colon cancer cells. Nox1 may represent a valuable target in which to prevent colon cancer metastasis.

In recent years, formalization and reasoning of topological relations have become a hot topic as a means to generate knowledge about the relations between spatial objects at the conceptual and geometrical levels. These mechanisms have been widely used in spatial data query, spatial data mining, evaluation of equivalence and similarity in a spatial scene, as well as for consistency assessment of the topological relations of multi-resolution spatial databases. The concept of computational fuzzy topological space is applied to simple fuzzy regions to efficiently and more accurately solve fuzzy topological relations. Thus, extending the existing research and improving upon the previous work, this paper presents a new method to describe fuzzy topological relations between simple spatial regions in Geographic Information Sciences (GIS) and Artificial Intelligence (AI). Firstly, we propose a new definition for simple fuzzy line segments and simple fuzzy regions based on the computational fuzzy topology. And then, based on the new definitions, we also propose a new combinational reasoning method to compute the topological relations between simple fuzzy regions, moreover, this study has discovered that there are (1) 23 different topological relations between a simple crisp region and a simple fuzzy region; (2) 152 different topological relations between two simple fuzzy regions. In the end, we have discussed some examples to demonstrate the validity of the new method, through comparisons with existing fuzzy models, we showed that the proposed method can compute more than the existing models, as it is more expressive than the existing fuzzy models.

Purpose Socioeconomic inequality in return to work after cancer treatment and rehabilitation have been documented, but less is known about its causes. This paper investigates the role played by breast cancer stage at diagnosis and comorbidity. Methods We used the comprehensive Danish Cancer Registry to follow 7372 women aged 30-60, who were in the labour force when diagnosed with breast cancer in 2000-06 and survived at least three years. Controls were 213,276 women without breast cancer. Inequalities in employment outlook were estimated as interaction effects in linear regression between educational attainment and disease on employment. Results There is significant interaction between education and breast cancer, but it is only marginally affected by including stage and comorbidity in the regression models. Education, breast cancer stage, and comorbidity all have strong effects on later employment, and a considerable amount of the educational effect is mediated by comorbidity and pre-cancer labour market participation and income. Conclusion The result of the study is negative in the sense that the stronger effect of breast cancer on employment among low-educated compared to highly educated individuals is not explained by cancer stage or comorbidity. The fact that comorbidity has little impact on inequality may be due to a different social patterning of most comorbidity compared to breast cancer.

BackgroundOne approach considered for reducing health care spending is to narrow the gap in spending between high- and low-spending areas. The goal would be to reduce spending in the high areas to similar levels achieved in areas that use health care more efficiently. This paper examined the degree to which high-spending areas remain high-spending and which types of service lead to convergence or divergence in spending in New York State.MethodsThis analysis utilized publicly available data on county-level spending trends for the Medicare fee-for-service population from 2007 to 2016. The study applied methods previously used to evaluate changes in the regional variation of health care spending nationally to county-level data within New York.ResultsThe spread of health care spending converged slightly over the ten-year period analyzed. There was also evidence for regression to the mean-effects and changes in the relative rankings of spending across counties during this time. While there was strong evidence for convergence, many high-spending counties in 2007 remained high-spending in 2016. There were also differences in which services drove spending variation at the national level compared to within New York.ConclusionsThese findings point to counties with consistently high spending as a potential focus for health care cost-control efforts. Moreover, efforts to reduce unwarranted variation in spending may need to be tailored to the circumstances of particular regions as there are geographic differences in which services drive spending variation. Regression to the mean effects also have important implications for the specifications of alternative provider payment models, such as accountable care organizations, which promote convergence in spending by utilizing spending targets.

Rising migration numbers and the resulting increase in economic and sociocultural heterogeneity in societies all over the world are theorised to put pressure on the sustainable use of common-pool resources [CPRs]. Increased heterogeneity is argued to decrease trust and diversify interests between resource users, leading to overuse and decline of natural and man-made CPRs. The aim of this paper is to understand cooperative behaviour under economic and sociocultural heterogeneity in CPRs, through the analyses of experimental data including 344 subjects from the United Kingdom and the Netherlands, and 144 subjects from India. Multilevel regression, ordinal logistic regression, linear conditional-contribution profiles [LCPs] and agent-based models [ABMs] are used to analyse and replicate experimental outcomes on the micro- and macro-level. Results show that the combination of economic and sociocultural heterogeneity affects cooperation negatively when the decision-situation is perceived as unfair, but that neither economic nor sociocultural heterogeneity on themselves affect cooperation negatively. Economic heterogeneity is even found to affect cooperation positively relative to homogeneity. Player type classification based on LCP scores shows that experimental outcomes can be interpreted with player types, and ABM simulations validate the experimental results by replicating the main outcomes.

China is shifting from the stage of large-scale bridge construction to the stage of equal emphasis on the construction and maintenance of bridges. The problems of low efficiency and high cost in bridge inspection are becoming more and more prominent, which threaten people’s life safety. In this paper, the deterioration state prediction model of concrete beam bridge under Boosting DT C5.0 was established as the basis, and optimization suggestions were put forward in terms of bridge inspection standards and processes, which aims to perfect the bridge inspection mechanism, realize the fine management of the bridge and prolong the service life of the bridge. Research shows that: first, the bridge inspection standard with a single index should be improved into the bridge inspection standard with multiple indexes, so as to scientifically determine the bridges that need to be inspected and optimize the allocation of maintenance resources. Second, the bridge deterioration state prediction model is used to add a screening mechanism for the bridge in the inspection plan, which can effectively reduce the workload of bridge inspection and enhance the inspection efficiency. Third, the deterioration phenomenon of coexistence between adjacent traffic assets should be fully considered and the linkage inspection mechanism of adjacent traffic assets should be established to improve the effect of bridge inspection.

The application of multi-objective optimisation to evolutionary robotics is receiving increasing attention. A survey of the literature reveals the different possibilities it offers to improve the automatic design of efficient and adaptive robotic systems, and points to the successful demonstrations available for both task-specific and task-agnostic approaches (i.e. with or without reference to the specific design problem to be tackled). However, the advantages of multi-objective approaches over single-objective ones have not been clearly spelled out and experimentally demonstrated. This paper fills this gap for task-specific approaches: starting from well-known results in multi-objective optimisation, we discuss how to tackle commonly recognised problems in evolutionary robotics. In particular, we show that multi-objective optimisation (i) allows evolving a more varied set of behaviours by exploring multiple trade-offs of the objectives to optimise, (ii) supports the evolution of the desired behaviour through the introduction of objectives as proxies, (iii) avoids the premature convergence to local optima possibly introduced by multi-component fitness functions, and (iv) solves the bootstrap problem exploiting ancillary objectives to guide evolution in the early phases. We present an experimental demonstration of these benefits in three different case studies: maze navigation in a single robot domain, flocking in a swarm robotics context, and a strictly collaborative task in collective robotics. Copyright, SCOPUS: ar.j, info:eu-repo/semantics/published

BackgroundEstimating the number of genes in human genome has been long an important problem in computational biology. With the new conception of considering human as a super-organism, it is also interesting to estimate the number of genes in this human super-organism.Principal findingsWe presented our estimation of gene numbers in the human gut bacterial community, the largest microbial community inside the human super-organism. We got 552,700 unique genes from 202 complete human gut bacteria genomes. Then, a novel gene counting model was built to check the total number of genes by combining culture-independent sequence data and those complete genomes. 16S rRNAs were used to construct a three-level tree and different counting methods were introduced for the three levels: strain-to-species, species-to-genus, and genus-and-up. The model estimates that the total number of genes is about 9,000,000 after those with identity percentage of 97% or up were merged.ConclusionBy combining completed genomes currently available and culture-independent sequencing data, we built a model to estimate the number of genes in human gut bacterial community. The total number of genes is estimated to be about 9 million. Although this number is huge, we believe it is underestimated. This is an initial step to tackle this gene counting problem for the human super-organism. It will still be an open problem in the near future. The list of genomes used in this paper can be found in the supplementary table.

Social media represent an important source of news for many users. They are, however, affected by misinformation and they might be playing a role in the growth of political polarization. In this paper, we create an agent based model to investigate how policing content and backlash on social media (i.e. conflict) can lead to an increase in polarization for both users and news sources. Our model is an advancement over previously proposed models because it allows us to study the polarization of both users and news sources, the evolution of the audience connections between users and sources, and it makes more realistic assumptions about the starting conditions of the system. We find that the tendency of users and sources to avoid policing, backlash and conflict in general can increase polarization online. Specifically polarization comes from the ease of sharing political posts, intolerance for opposing points of view causing backlash and policing, and volatility in changing one’s opinion when faced with new information. On the other hand, it seems that the integrity of a news source in trying to resist the backlash and policing has little effect.

The AIDS is a chronic disease and the researchers still exert their high efforts to reach the cure of HIV infection. The most common treatment is the antiretroviral therapy (cART) and the virus can be more effected if the patients stop using cART. The other problem is that the CD8+ T cells might be exhausted by persistent immune activation by cART. This paper introduces fractional-order into a mathematical model of HIV infection combining with stem cell therapy and control the infection by the immune system cells (CD8+ T cells). The paper introduced the numerical solutions for the mathematical model. The results show that the stem cell therapy with the activation of immune system cells might causes the cure for a HIV patient. This results are consistent with medical studies. Also, we proposed the effect of the fractional order (α) on the figures of the components.

The compartment model analysis using medical imaging data is the well-established but extremely time consuming technique for quantifying the changes in microvascular physiology of targeted organs in clinical patients after antivascular therapies. In this paper, we present a first graphics processing unit-accelerated method for compartmental modeling of medical imaging data. Using this approach, we performed the analysis of dynamic contrast-enhanced magnetic resonance imaging data from bevacizumab-treated glioblastoma patients in less than one minute per slice without losing accuracy. This approach reduced the computation time by more than 120-fold comparing to a central processing unit-based method that performed the analogous analysis steps in serial and more than 17-fold comparing to the algorithm that optimized for central processing unit computation. The method developed in this study could be of significant utility in reducing the computational times required to assess tumor physiology from dynamic contrast-enhanced magnetic resonance imaging data in preclinical and clinical development of antivascular therapies and related fields.

This paper presents the software application ORION (All-sky camera geOmetry calibRation from star positIONs). This software has been developed with the aim of providing geometrical calibration to all-sky cameras, i.e. assess which sky coordinates (zenith and azimuth angles) correspond to each camera pixel. It is useful to locate bodies over the celestial vault, like stars and planets, in the camera images. The user needs to feed ORION with a set of cloud-free sky images captured at night-time for obtaining the calibration matrices. ORION searches the position of various stars in the sky images. This search can be automatic or manual. The sky coordinates of the stars and the corresponding pixel positions in the camera images are used together to determine the calibration matrices. The calibration is based on three parameters: the pixel position of the sky zenith in the image; the shift angle of the azimuth viewed by the camera with respect to the real North; and the relationship between the sky zenith angle and the pixel radial distance regards to the sky zenith in the image. In addition, ORION includes other features to facilitate its use, such as the check of the accuracy of the calibration. An example of ORION application is shown, obtaining the calibration matrices for a set of images and studying the accuracy of the calibration to predict a star position. Accuracy is about 9.0 arcmin for the analyzed example using a camera with average resolution of 5.4 arcmin/pixel (about 1.7 pixels).

Background The prevalence of stunting in South Sulawesi and West Sulawesi Province is relatively high. Studies reveal various household, parental, and child factors are associated with stunting. This paper aimed to determine the determinants of stunting among children under five in South and West Sulawesi Province using the 2013 and 2018 Indonesia Basic Health Survey. Methods This study was a secondary data analysis using the 2013 and 2018 Indonesian Basic Health Surveys. The unit of analysis was children under five years, and the study obtained 3641 and 4423 children in South Sulawesi Province from the 2013 and 2018 Indonesia Basic Health Survey, respectively, and 804 and 1059 children from the 2013 and 2018 Indonesia Basic Health Survey in West Sulawesi Province, respectively. The multivariable poisson regression model was conducted to determine the determinants of stunting. Results The results showed that the mean age of children in South Sulawesi and West Sulawesi Province was 31.1 months and 30.8 months, respectively, on 2013 survey compare to 29.6 months and 29.1 months on the 2018 survey. The determinants of stunting in children under five in South Sulawesi Province in 2013 survey were household with two children under five (APR:1.24; 95% CI: 1.1–1.3; p-value = 0.006), maternal BMI (APR: 1.1; 95% CI: 1.03–1.1; p-value = Conclusions The determinants of stunting in children under five in South Sulawesi Province are number of children under five in the household, maternal education, maternal weight, maternal height, maternal BMI, child’s age, and birthweight. Meanwhile, the determinants of stunting in children under five in West Sulawesi were wealth, maternal education, maternal weight, maternal BMI,, child’s age, child’s sex, and history of acute respiratory infection. Hence, intervention on household and child levels as well as maternal sociodemographic factors need to be addressed.

Knowledge of contagion among economies is a relevant issue in economics. The canonical model of contagion is an alternative in this case. Given the existence of endogenous variables in the model, instrumental variables can be used to decrease the bias of the OLS estimator. In the presence of heteroskedastic disturbances this paper proposes the use of conditional volatilities as instruments. Simulation is used to show that the homoscedastic and heteroskedastic estimators which use them as instruments have small bias. These estimators are preferable in comparison with the OLS estimator and their asymptotic distribution can be used to construct confidence intervals.

This paper presents the first empirical investigation that compares Euler and linear diagrams when they are used to represent set cardinality. A common approach is to use area-proportional Euler diagrams but linear diagrams can exploit length-proportional straight-lines for the same purpose. Another common approach is to use numerical annotations. We first conducted two empirical studies, one on Euler diagrams and the other on linear diagrams. These suggest that area-proportional Euler diagrams with numerical annotations and length-proportional linear diagrams without numerical annotations support significantly better task performance. We then conducted a third study to investigate which of these two notations should be used in practice. This suggests that area-proportional Euler diagrams with numerical annotations most effectively supports task performance and so should be used to visualize set cardinalities. However, these studies focused on data that can be visualized reasonably accurately using circles and the results should be taken as valid within that context. Future work needs to determine whether the results generalize both to when circles cannot be used and for other ways of encoding cardinality information.

This paper addresses patient-reported outcomes (PROs) and telemonitoring in congestive heart failure (CHF), both increasingly important topics. The interest in CHF trials is shifting from hard end-points such as hospitalization and mortality, to softer end-points such health-related quality of life. However, the relation of these softer end-points to objective parameters is not well studied. Telemonitoring is suitable for collecting both patient-reported outcomes and objective parameters. Most telemonitoring studies, however, do not take full advantage of the available sensor technology and intelligent data analysis. The Chiron clinical observational study was performed among 24 CHF patients (17 men and 7 women, age 62.9 ± 9.4 years, 15 NYHA class II and 9 class III, 10 of ishaemic, aetiology, 6 dilated, 2 valvular, and 6 of multiple aetiologies or cardiomyopathy) in Italy and UK. A large number of physiological and ambient parameters were collected by wearable and other devices, together with PROs describing how well the patients felt, over 1,086 days of observation. The resulting data were mined for relations between the objective parameters and the PROs. The objective parameters (humidity, ambient temperature, blood pressure, SpO2, and sweeting intensity) could predict the PROs with accuracies up to 86% and AUC up to 0.83, making this the first report providing evidence for ambient and physiological parameters to be objectively related to PROs in CHF patients. We also analyzed the relations in the predictive models, gaining some insights into what affects the feeling of health, which was also generally not attempted in previous investigations. The paper strongly points to the possibility of using PROs as primary end-points in future trials.

Traditional saliency detection algorithms lack object semantic character, and the segmentation algorithms cannot highlight the saliency of the segmentation regions. In order to compensate for the defects of these two algorithms, the salient object segmentation model, which is a novel combination of two algorithms, is established in this paper. With the help of a priori knowledge of image boundary background traits, the K-means++ algorithm is used to cluster the pixels for each region; in line with the sensitivity of the human eye to color and with its attention mechanism, the joint probability distribution of the regional contrast ratio and spatial saliency is established. The selection of the salient area is based on the probabilities, for which the region boundary is taken as the initial curve, and the level-set algorithm is used to perform the salient object segmentation of the image. The curve convergence condition is established according to the confidence level for the segmented region, thus avoiding over-convergence of the segmentation curve. With this method, the salient region boundary is adjacent to the object contour, so the curve evolution time is shorter, and compared with the traditional Li algorithm, the proposed algorithm has higher segmentation evaluation scores, with the additional benefit of emphasizing the importance of the object.

Evaluation of brainstem pathways with diffusion tensor imaging (DTI) and tractography may provide insights into pathophysiologies associated with dysfunction of key brainstem circuits. However, identification of these tracts has been elusive, with relatively few in vivo human studies to date. In this paper we proposed an automated approach for reconstructing nine brainstem fiber trajectories of pathways that might be involved in pain modulation. We first performed native-space manual tractography of these fibers in a small normative cohort of participants and confirmed the anatomical precision of the results using existing anatomical literature. Second, region-of-interest pairs were manually defined at each extracted fiber’s termini and nonlinearly warped to a standard anatomical brain template to create an atlas of the region-of-interest pairs. The resulting atlas was then transformed non-linearly into the native space of 17 veteran patients’ brains for automated brainstem tractography. Lastly, we assessed the relationships between the integrity levels of the obtained fiber bundles and pain severity levels. Fractional anisotropy (FA) measures derived using automated tractography reflected the respective tracts’ FA levels obtained via manual tractography. A significant inverse relationship between FA and pain levels was detected within the automatically derived dorsal and medial longitudinal fasciculi of the brainstem. This study demonstrates the utility of DTI in exploring brainstem circuitries involved in pain processing. In this context, the described automated approach is a viable alternative to the time-consuming manual tractography. The physiological and functional relevance of the measures derived from automated tractography is evidenced by their relationships with individual pain severities.

BackgroundPromoting physical activity (PA) for university students is essential as PA levels decrease during the transition from secondary to higher education. Providing technology-supported university courses targeting students’ PA levels may be a viable option to combat the problem. However, it is still unclear how and what technologies should be implemented in university courses to promote PA. This study aims to create a series of design principles for technology-supported physical education courses that aim to increase university students’ PA knowledge, motivation and levels.MethodThe proposed methodology underpinning the research program is a seven-phase design-based research (DBR) approach, with the seven phases encompassed in four sequential studies. These four studies are a systematic review, a qualitative focus group study, a pilot study, and a randomised controlled trial (RCT) study. The protocol paper aims to detail the plan for conducting the four studies in a comprehensive and transparent manner, thus contributing to the methodological evidence base in this field.DiscussionDesign principles generated from this project will contribute to the growing evidence focusing on effective design and implementation features. Future practitioners can also use these to develop physical education courses that aim to promote university students’ physical activity levels, knowledge, and motivation.Ethical considerationThis project has obtained ethical approval from the University of Sydney Human Research Ethics Committee (Project No. 2021/071; Project No. 2021/935). The randomised controlled trial protocol is registered at the Australian New Zealand Clinical Trials Registry (ANZCTR).Trial registrationthe RCT registry number: ACTRN12622000712707, 18/05/2022

Background Although studies in Nigeria showed the efficacy of intermittent preventive treatment using sulfadoxine-pyrimethamine (IPT-SP) in preventing malaria in pregnancy among Nigerian women there is still poor implementation of the intervention in Nigeria. Methods A mixed method study was conducted in Bwari Area Council, Nigeria in 2018. The quantitative part of the study is presented and discussed in this paper. Pregnant women were interviewed using a validated interviewer-administered questionnaire and observations of current practice were performed. Results A total of 422 pregnant women were recruited into the study (mean age, 26 years) with the majority being married women (90.3%). Most respondents (68.5%) did not know who could take IPT-SP and 58.5% of respondents did not know when and how many times IPT-SP should be taken during pregnancy. Nearly all participants (99.5%) did not take SP at the facility under direct observation of the health worker. None of the facilities had free SP and all respondents paid for SP through the Drug Revolving Fund. The knowledge of the use of SP was significantly influenced by respondents’ parity, ward of residence, antenatal clinic (ANC) attendance history and education. Respondents who had tertiary and secondary education were 8.3 (95% CI: 1.01–68.27) times more likely to use IPT-SP than those without formal education. Conclusion Most women who attend ANC in Bwari Area council did not receive IPT-SP as per the national guidelines. The unavailability of logistics (SP, Water and Cup) on a regular basis, the cost of the SP, poor knowledge of the importance of IPT in malaria prevention, and the non-implementation of the administration of SP under direct observation were factors influencing the use of IPT-SP. Outcomes could be enhanced through the provision of measures to address identified gaps by this study.

Even though mRNA expression levels are commonly used as a proxy for estimating functional differences that occur at the protein level, the relation between mRNA and protein expression is not well established. Further, no study to date has tested whether the evolutionary differences in mRNA expression observed between species reflect those observed in protein expression. Since a large proportion of mRNA expression differences observed between mammalian species appears to have no functional consequences for the phenotype, it is conceivable that many or most mRNA expression differences are not reflected at the protein level. If this is true, then differences in protein expression may largely reflect functional adaptations observed in species phenotypes. In this paper, we present the first direct comparison of mRNA and protein expression differences seen between humans and chimpanzees. We reproducibly find a significant positive correlation between mRNA expression and protein expression differences. This correlation is comparable in magnitude to that found between mRNA and protein expression changes at different developmental stages or in different physiological conditions within one species. Noticeably, this correlation is mainly due to genes with large expression differences between species. Our study opens the door to a new level of understanding of regulatory evolution and poses many new questions that remain to be answered.