Identification of early symptoms of endometriosis through the analysis of online social networks: A social media study.

Objective: Endometriosis is a complex full-body inflammation disease with an average time to diagnosis of 7-10 years. Social networks give opportunity to patient to openly discuss about their condition, share experiences, and seek advice. Thus, data from social media may provide insightful data about patient's experience. This study aimed at applying a text-mining approach to online social networks in order to identify early signs associated with endometriosis. Methods: An automated exploration technique of online forums was performed to extract posts. After a cleaning step of the built corpus, we retrieved all symptoms evoked by women, and connected them to the MedDRA dictionary. Then, temporal markers allowed targeting only the earliest symptoms. The latter were those evoked near a marker of precocity. A co-occurrence approach was further applied to better account for the context of evocations. Results: Results were visualised using the graph-oriented database Neo4j. We collected 7148 discussions threads and 78,905 posts from 10 French forums. We extracted 41 groups of contextualised symptoms, including 20 groups of early symptoms associated with endometriosis. Among these groups of early symptoms, 13 were found to portray already known signs of endometriosis. The remaining 7 clusters of early symptoms were limb oedema, muscle pain, neuralgia, haematuria, vaginal itching, altered general condition (i.e. dizziness, fatigue, nausea) and hot flush. Conclusion: We pointed out some additional symptoms of endometriosis qualified as early symptoms, which can serve as a screening tool for prevention and/or treatment purpose. The present findings offer an opportunity for further exploration of early biological processes triggering this disease.

Beneficial Effects of Maternal Physical Activity during Pregnancy on Fetal, Newborn, and Child Health: Guidelines for Interventions during the Perinatal Period from the French National College of Midwives.

The objective of this work is to synthesize current knowledge about the effects of maternal physical activity during pregnancy on children's health. During the prenatal and postnatal periods, maternal physical activity has protective effects against the risks of macrosomia, obesity, and other associated cardiometabolic disorders. Even though longitudinal studies in humans are still necessary to validate them, these effects have been consistently observed in animal studies. A remarkable effect of maternal physical activity is its positive role on neurogenesis, language development, memory, and other cognitive functions related to learning.

Master's Degree in Health Data Science: Implementation and Assessment After Five Years.

Health data science is an emerging discipline that bridges computer science, statistics and health domain knowledge. This consists of taking advantage of the large volume of data, often complex, to extract information to improve decision-making. We have created a Master's degree in Health Data Science to meet the growing need for data scientists in companies and institutions. The training offers, over two years, courses covering computer science, mathematics and statistics, health and biology. With more than 60 professors and lecturers, a total of 835 hours of classes (not including the mandatory 5 months of internship per year), this curriculum has enrolled a total of 53 students today. The feedback from the students and alumni allowed us identifying new needs in terms of training, which may help us to adapt the program for the coming academic years. In particular, we will offer an additional module covering data management, from the edition of the clinical report form to the implementation of a data warehouse with an ETL process. Git and application lifecycle management will be included in programming courses or multidisciplinary projects.

Exploration of the core protein network under endometriosis symptomatology using a computational approach.

Background: Endometriosis is defined by implantation and invasive growth of endometrial tissue in extra-uterine locations causing heterogeneous symptoms, and a unique clinical picture for each patient. Understanding the complex biological mechanisms underlying these symptoms and the protein networks involved may be useful for early diagnosis and identification of pharmacological targets. Methods: In the present study, we combined three approaches (i) a text-mining analysis to perform a systematic search of proteins over existing literature, (ii) a functional enrichment analysis to identify the biological pathways in which proteins are most involved, and (iii) a protein-protein interaction (PPI) network to identify which proteins modulate the most strongly the symptomatology of endometriosis. Results: Two hundred seventy-eight proteins associated with endometriosis symptomatology in the scientific literature were extracted. Thirty-five proteins were selected according to degree and betweenness scores criteria. The most enriched biological pathways associated with these symptoms were (i) Interleukin-4 and Interleukin-13 signaling (p = 1.11 x 10-16), (ii) Signaling by Interleukins (p = 1.11 x 10-16), (iii) Cytokine signaling in Immune system (p = 1.11 x 10-16), and (iv) Interleukin-10 signaling (p = 5.66 x 10-15). Conclusion: Our study identified some key proteins with the ability to modulate endometriosis symptomatology. Our findings indicate that both pro- and anti-inflammatory biological pathways may play important roles in the symptomatology of endometriosis. This approach represents a genuine systemic method that may complement traditional experimental studies. The current data can be used to identify promising biomarkers for early diagnosis and potential therapeutic targets.

Automated Twitter Extraction and Visual Analytics with Dashboards: Development and First Experimentations.

Information found in the social media may help to set up infoveillance and track epidemics, identify high-risk behaviours, or assess trends or feelings about a subject or event. We developed a dashboard to enable novice users to easily and autonomously extract and analyze data from Twitter. Eleven users tested the dashboard and considered the tool to be highly usable and useful. They were able to conduct the research they wanted and appreciated being able to use this tool without having to program.

Jupyter Notebooks for Introducing Data Science to Novice Users.

Data science is a bridge discipline involving computer science, statistics, and knowledge of the health field. We developed a Jupyter Notebook to enable novice users to easily and autonomously analyze data from social networks. We conducted an experimentation with non-programmer students. They had to adapt a R Notebook and complete 14 questions and to perform descriptive analyses. The average rate of correct answers was 90.7. Jupyter Notebook enabled novice users to easily and autonomously analyze data from Twitter.

Physical activity, screen time and the COVID-19 school closures in Europe - An observational study in 10 countries.

To date, few data on how the COVID-19 pandemic and restrictions affected children's physical activity in Europe have been published. This study examined the prevalence and correlates of physical activity and screen time from a large sample of European children during the COVID-19 pandemic to inform strategies and provide adequate mitigation measures. An online survey was conducted using convenience sampling from 15 May to 22 June, 2020. Parents were eligible if they resided in one of the survey countries and their children aged 6-18 years. 8395 children were included (median age [IQR], 13 [10-15] years; 47% boys; 57.6% urban residents; 15.5% in self-isolation). Approximately two-thirds followed structured routines (66.4% [95%CI, 65.4-67.4]), and more than half were active during online P.E. (56.6% [95%CI, 55.5-57.6]). 19.0% (95%CI, 18.2-19.9) met the WHO Global physical activity recommendation. Total screen time in excess of 2 h/day was highly prevalent (weekdays: 69.5% [95%CI, 68.5-70.5]; weekend: 63.8% [95%CI, 62.7-64.8]). Playing outdoors more than 2 h/day, following a daily routine and being active in online P.E. increased the odds of healthy levels of physical activity and screen time, particularly in mildly affected countries. In severely affected countries, online P.E. contributed most to meet screen time recommendation, whereas outdoor play was most important for adequate physical activity. Promoting safe and responsible outdoor activities, safeguarding P.E. lessons during distance learning and setting pre-planned, consistent daily routines are important in helping children maintain healthy active lifestyle in pandemic situation. These factors should be prioritised by policymakers, schools and parents. HighlightsTo our knowledge, our data provide the first multi-national estimates on physical activity and total screen time in European children roughly two months after COVID-19 was declared a global pandemic.Only 1 in 5 children met the WHO Global physical activity recommendations.Under pandemic conditions, parents should set pre-planned, consistent daily routines and integrate at least 2-hours outdoor activities into the daily schedule, preferable on each day. Schools should make P.E. lessons a priority. Decision makers should mandate online P.E. be delivered by schools during distance learning. Closing outdoor facilities for PA should be considered only as the last resort during lockdowns.

From SIR to SEAIRD: A novel data-driven modeling approach based on the Grey-box System Theory to predict the dynamics of COVID-19.

Common compartmental modeling for COVID-19 is based on a priori knowledge and numerous assumptions. Additionally, they do not systematically incorporate asymptomatic cases. Our study aimed at providing a framework for data-driven approaches, by leveraging the strengths of the grey-box system theory or grey-box identification, known for its robustness in problem solving under partial, incomplete, or uncertain data. Empirical data on confirmed cases and deaths, extracted from an open source repository were used to develop the SEAIRD compartment model. Adjustments were made to fit current knowledge on the COVID-19 behavior. The model was implemented and solved using an Ordinary Differential Equation solver and an optimization tool. A cross-validation technique was applied, and the coefficient of determination R 2 was computed in order to evaluate the goodness-of-fit of the model. Key epidemiological parameters were finally estimated and we provided the rationale for the construction of SEAIRD model. When applied to Brazil's cases, SEAIRD produced an excellent agreement to the data, with an R 2 ≥ 90%. The probability of COVID-19 transmission was generally high (≥ 95%). On the basis of a 20-day modeling data, the incidence rate of COVID-19 was as low as 3 infected cases per 100,000 exposed persons in Brazil and France. Within the same time frame, the fatality rate of COVID-19 was the highest in France (16.4%) followed by Brazil (6.9%), and the lowest in Russia (≤ 1%). SEAIRD represents an asset for modeling infectious diseases in their dynamical stable phase, especially for new viruses when pathophysiology knowledge is very limited. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10489-021-02379-2.

Automatic Exploitation of YouTube Data: A Study of Videos Published by a French YouTuber During COVID-19 Quarantine in France.

The objective of this study was to test the feasibility of automatically extracting and exploiting data from the YouTube platform, with a focus on the videos produced by the French YouTuber HugoDécrypte during COVID-19 quarantine in France. For this, we used the YouTube API, which allows the automatic collection of data and meta-data of videos. We have identified the main topics addressed in the comments of the videos and assessed their polarity. Our results provide insights on topics trends over the course of the quarantine and highlight users sentiment towards on-going events. The method can be expanded to large video sets to automatically analyse high amount of user-produced data.

A multivalued agent-based model for the study of noncommunicable diseases.

This paper aims to test and illustrate the utility and extensibility of an existing model, SimNCD (Simulation of NonCommunicable Diseases). It also proposes a way to include questionnaires - widely used in epidemiology - in the individual's reasoning mechanism in order to identify his/her attitude and personal choices. SimNCD is a formal agent-based model. It helps researchers and health practitioners study and simulate the complex dynamics of noncommunicable diseases. It models individuals that evolve within a social network, and behave while engaging in activities offered by their physical environment. The literature strongly supports the influence of the individual's behavioral choices on their health, particularly, the acquirement and maintainability of noncommunicable diseases. Therefore, we propose to extend SimNCD in order to acquire the agents with a reasoning process that allows them to choose the activities to practice. Thus, we model their attitude via preferences that are modeled based on the available literature and expressed with the linguistic 2-tuple method. Our solution also employs a multi-attribute decision-making method. We specify the proposed solution in the study of childhood obesity and use it to predict children's corpulence variations in different scenarios.

Body Weight Status and Sleep Disturbances During Pregnancy: Does Adherence to Gestational Weight Gain Guidelines Matter?

BACKGROUND: To determine the effect of preconception body mass index (BMI) and/or gestational weight gain (GWG) on the occurrence of sleep disorders over the whole pregnancy. METHODS: A sample of 2,366 pregnant women, recruited in their 1st trimester (TM), was evaluated until delivery for their sleeping characteristics, using the Pittsburgh Sleep Quality Index (PSQI). Mixed or multinomial logistic modeling was applied, as appropriate. RESULTS: When compared with TM 1, PSQI score was the lowest at TM 2 (ß = -1.03; 95% CI: -1.17 to -0.89) and highest in TM 3 (ß = 0.27; 95% CI: 0.10-0.45). Obese (ß = 0.48; 95% CI: 0.17-0.78) and overweight women (ß = 0.24; 95% CI: 0.00-0.48) exhibited an overall greater PSQI than normal-weight women over the whole pregnancy. When sociodemographic factors were accounted for, the effect size was reduced by 25% among obese women (ß = 0.36; 95% CI: 0.06-0.68), but was no more not significant in overweight women (ß = 0.06; 95% CI: -0.17 to 0.30). Both obese and overweight women still exhibited, although at a lower extend, a greater PSQI than normal-weight women. Further adjustment for GWG had no effect on these observations. Obese women almost had a four-fold increased risk (OR = 3.89; 95% CI: 2.50-6.06) of being snorers in the three TMs. While GWG had only a minor effect (aOR = 3.83; 95% CI: 2.43-6.03), sociodemographic factors increased the odds of being habitual snorer (aOR = 4.04; 95% CI: 2.57-6.35). CONCLUSIONS: High prepregnancy BMI together with sociodemographic correlates appear as the most critical for sleep disturbances across pregnancy. GWG is of marginal importance, especially regarding snoring. These findings confirm the importance of considering the initial body weight status of women in tailoring sleep hygiene advises irrespective of the recommendations for weight gain during pregnancy. The results also underscore the need to providing as early as possible during a pregnancy, supportive tools to ethnic minorities, multiparous, and women from deprived socioeconomic neighborhoods.

Physical activity during pregnancy and infant's birth weight: results from the 3D Birth Cohort.

AIM: To evaluate the association between maternal physical activity and infant's birth weight or risk of inappropriate weight for gestational age (GA), and whether this association differs by infant's sex, maternal body mass index (BMI) or pregnancy complications in a prospective cohort study. METHODS: 1913 pregnant women from the 3D Birth Cohort (Québec, Canada) completed the Pregnancy Physical Activity Questionnaire at each trimester. Energy expenditure (metabolic equivalent of task (MET)*hours/week) for total activity, sports and exercise and vigorous intensity activities was calculated. The associations with birth weight and risk of inappropriate weight for GA were evaluated by regression modelling. Interactions were tested with infant's sex, maternal prepregnancy BMI, gestational diabetes, hypertensive disorders and prematurity. RESULTS: Each 1 MET/hours/week increase in sports and exercise in the first trimester was associated with a 2.5 g reduction in infant's birth weight (95% CI -4.8 to -0.3) but was not associated with the risk of small weight for GA. In contrast, although not significant, a 17% reduction in the risk of large weight for GA was observed with increasing sports and exercise. Furthermore, in women with subsequent pre-eclampsia (but not normotensive or hypertensive women), each 1 MET/hours/week increment spent in any vigorous exercise in the first trimester reduced the infant's birth weight by 19.8 g (95% CI -35.2 to -4.3). CONCLUSIONS: Pregnant women with higher sports and exercise levels in the first trimester delivered infants with a lower birth weight. The risk of reducing infant's birth weight with vigorous exercise in women who develop pre-eclampsia later in pregnancy requires evaluation.

Physical Education in a Thermal Spa Resort to Maintain an Active Lifestyle at Home: A One-Year Self-Controlled Follow-Up Pilot Study.

The self-controlled follow-up pilot study was set up to examine the maintenance of engagement in physical activity by a group of older adults in a thermal spa resort, as a consequence of the inclusion of additional physical education sessions within their usual care offers. A cohort of 42 participants (70.4 ± 4.5 years) underwent three weeks of thermal treatment with additional physical education (PE) sessions. Measurements were established during the intervention in 2 periods (baseline and final thermal treatment evaluation) and 4 periods of measurements in the follow-up (+15 days, +2 months, +6 months, and +1 year). Physical measures (anthropometrics, flexibility, and 6-minute walk test) and intrapersonal and psychosocial factors as well as health-related quality of life (HQOL) and physical activity (PA) were self-reported by participants. Only HQOL and PA were assessed during the follow-up. One year after a 3-week PE session combined with the usual thermal care, 64% of the participants exhibited a higher volume of PA than at baseline. The components of the HQOL changed during the follow-up. This strategy to maintain PA engagement appears to be feasible in a population of thermal care older adults. This work demonstrates the feasibility of a study conducted to maintain physical activity engagement after a thermal treatment.

Can we identify termination of resuscitation criteria in cardiac arrest due to drowning: results from the French national out-of-hospital cardiac arrest registry.

RATIONALE, AIMS AND OBJECTIVES: The aim of this study was to describe the cohort of persons having experiences fatal and non-fatal drowning events, registered in the French cardiac arrest registry and to identify termination of resuscitation criteria. METHODS: We performed a prospective multicenter study based on data from French cardiac arrest registry database. All patients with cardiac arrest after drowning (CAD) recorded between July 2011 and November 2014 were included. The population description was carried out by medians [interquartile ranges (IQR)] or frequencies. The characteristics were compared in terms of the primary endpoint (alive vs dead at hospital admission) using chi-square or Fisher's exact and the Mann-Whitney U test. The predictive model was carried out using the multivariate logistic regression. RESULTS: The analysis included 234 CAD. The majority of patients were adults (83.6%) and males (64.5%). Most of the submersions occurred out of home (75.6%). We recorded 66.7% of incidents in fresh water. About a third of CAD was witnessed of which 33.8% had an immediate basic life support. Most of CAD patients received an advanced cardiac life support (87.2%). The median Mobile Medical Team response time was 22 [15-30] minutes. At hospital, 40.6% of patients were alive. Twenty one patients (9.0%) were discharged alive. Among them, 17 had a good neurological outcome. Faster interventions generally resulted in higher survival chances (Mobile Medical Team response time OR: 0.960[0.925; 0.996]; P = 0.0.031; no flow duration OR: 0.535[0.313; 0.913]; P = 0.022) if associated with ventilation (OR: 6.742[2.043; 22.250]; P = 0.002). Age (OR: 0.971[0.955; 0.988]; P = 0.001) and location outside (OR: 0.203[0.064; 0.625]; P = 0.007) are the other criteria of our model. CONCLUSIONS: The model is helpful to highlight explanative variables concerning CAD patients' outcome. The next step is the validation of these five factors by a larger study. Prevention and public training to lifesaving behaviours must be considered as priorities in French public health programmes.

Fuzzy logic for characterizing the moderate intensity of physical activity in children.

OBJECTIVES: The aim of this study was to better characterize the moderate intensity of PA among children by applying fuzzy logic as the most appropriate analytical approach. In this perspective, the 6-MWT was selected as a pertinent exercise modality, which covers as a whole, this intensity level. DESIGN: Methodological study. METHODS: Fuzzy logic was applied to accelerometer output obtained on 46 children aged 9-11 years. A fuzzy subset A was defined from the reference set E using a membership function (degree of truth). To adequately tap the moderate PA, a core of X¯±σ and a support of X¯±2σ (with X¯ the mean, and σ the standard deviation of the distribution) were selected. RESULTS: The walking speed during the exercise averaged 6.1±0.6kmh(-1) and the mean HR was 135±14bpm. The movement count (419±127 to 433±148 counts) exhibited no significant changes during the test. A value of 260 counts per 5-s (i.e., 3120cpm) had equally 50% of degree of truth to encompass both "light" and "moderate" intensities of PA. Results suggest that the cut-point of >2296cpm covers a low PA at 100% and a moderate PA at 0%. CONCLUSIONS: Fuzzy logic provides a robust basis to processing accelerometer data, and brings a reliable solution to the concern about the in-between of PA intensities. Its application to calibration studies should not support the use of a cut-point of about 2000cpm in children, and linguistic variables should now be preferred to numbered data in defining PA intensities.

Adding anthropometric measures of regional adiposity to BMI improves prediction of cardiometabolic, inflammatory and adipokines profiles in youths: a cross-sectional study.

BACKGROUND: Paediatric research analysing the relationship between the easy-to-use anthropometric measures for adiposity and cardiometabolic risk factors remains highly controversial in youth. Several studies suggest that only body mass index (BMI), a measure of relative weight, constitutes an accurate predictor, whereas others highlight the potential role of waist-to-hip ratio (WHR), waist circumference (Waist C), and waist-to-height ratio (WHtR). In this study, we examined the effectiveness of adding anthropometric measures of body fat distribution (Waist C Z Score, WHR Z Score and/or WHtR) to BMI Z Score to predict cardiometabolic risk factors in overweight and obese youth. We also examined the consistency of these associations with the "total fat mass + trunk/legs fat mass" and/or the "total fat mass + trunk fat mass" combinations, as assessed by dual energy X-ray absorptiometry (DXA), the gold standard measurement of body composition. METHODS: Anthropometric and DXA measurements of total and regional adiposity, as well as a comprehensive assessment of cardiometabolic, inflammatory and adipokines profiles were performed in 203 overweight and obese 7-17 year-old youths from the Paediatrics Clinic, Centre Hospitalier de Luxembourg. RESULTS: Adding only one anthropometric surrogate of regional fat to BMI Z Score improved the prediction of insulin resistance (WHR Z Score, R(2): 45.9%. Waist C Z Score, R(2): 45.5%), HDL-cholesterol (WHR Z Score, R(2): 9.6%. Waist C Z Score, R(2): 10.8%. WHtR, R(2): 6.5%), triglycerides (WHR Z Score, R(2): 11.7%. Waist C Z Score, R(2): 12.2%), adiponectin (WHR Z Score, R(2): 14.3%. Waist C Z Score, R(2): 17.7%), CRP (WHR Z Score, R(2): 18.2%. WHtR, R(2): 23.3%), systolic (WHtR, R(2): 22.4%), diastolic blood pressure (WHtR, R(2): 20%) and fibrinogen (WHtR, R(2): 21.8%). Moreover, WHR Z Score, Waist C Z Score and/or WHtR showed an independent significant contribution according to these models. These results were in line with the DXA findings. CONCLUSIONS: Adding anthropometric measures of regional adiposity to BMI Z Score improves the prediction of cardiometabolic, inflammatory and adipokines profiles in youth.

Physical activity in the prevention of childhood obesity.

The current high prevalence of childhood obesity and its co-morbidities is concomitant with a low level of physical activity and an abundance of sedentary pastimes for Westernised children. To increase the participation of a majority of children in a sustained physical activity, interventions require a fair understanding and consideration of the influences of this behaviour, especially as children are overweight or obese. Basically, the physical activity behaviour of children depends on biological, sociocultural and psychosocial factors and their interplay. The recent literature lends support to the fact that some psychosocial factors such as self-efficacy and physical competence may be solid anchor points upon which to improve the participation of overweight and obese children in free-living physical activity. Thus, interventionists should first concentrate on improving these personal dimensions around which physiological and environmental factors might revolve. The development of motor skills may be a good means for enhancing the self-image of obese children.

Compliance of children in northern France with physical activity recommendations.

AIMS: This study examined the compliance of French children with physical activity (PA) guidelines, using objective assessments of PA. METHODS: The study involved 252 children aged 9.9 +/- 0.9 years, with mean height and weight of 1.39 +/- 0.08 m and 35.8 +/- 8.8 kg, respectively. Their usual PA was evaluated during a week using an Actigraph accelerometer. RESULTS: The time spent in a moderate-to-vigorous PA (MVPA) ranged from 142 +/- 44 min x d(-1) to 25 +/- 18 min/day according to the cut-offs used. Boys were significantly more active than girls (p < or = .001). Overweight/obese children spent significantly less time in MVPA as determined with cut-off points at 3200 cpm (-26%) or 3600 cpm (-35%) (p < .01). Between 5% (8% of boys vs 1% of girls, p < .0001) and 9% (14% of boys vs 3% of girls, p < .0001) of children probably met the PA guidelines. No relationships were found with socioeconomic status. CONCLUSIONS: This high proportion of insufficiently active children (> 90%), together with the relatively high proportion of overweight children in this area, advocates a more aggressive PA promotion project, which should target all children whatever their social origins.

Maturity negates the gender-related difference in physical activity among youth. Is this equally justified whatever the accelerometer cut-off point used?

OBJECTIVES: To examine the consistency in findings about the influence of maturity on the gender-difference in moderate-to-vigorous physical activity (MVPA) of children using different cut-off points for MVPA. DESIGN: Cross-sectional observation study. METHODS: The sample involved 253 children (139 boys) of 9.9±0.9 years. Their physical activity was evaluated using an Actigraph accelerometer. The biological age of children was determined with their estimated age at the peak height velocity, and maturity categories were gender-specific defined. RESULTS: Boys spent more time in MVPA than girls (P<0.0001), and no maturity-related differences were obtained on the whole sample. It was only among boys that differences were found between maturity groups with cut-off points of 3000 cpm (P=0.034), 3200 cpm (P=0.024), and 3600 cpm (P=0.011). At a given maturity level, boys spent significantly more time in MVPA than girls, except with the cut-off point of 1000 cpm (P=0.07). There were higher proportions of sufficiently active boys, but significances were reached only with cut-off points above 3000 cpm. There were no maturity-related differences in the proportion of sufficiently active children as MVPA was computed using cut-off points of 1000 cpm, 2000 cpm or 3000 cpm. CONCLUSIONS: The role of maturity in the gender-difference in MVPA seems unclear as one another cut-off point is used among children. Even if a relatively greater consistency was found with the three cut-off points above 3000 cpm, data comparison may require a conversion system until a consensus is reached about the exact value to be used among children.