Gestion des eaux à Bruxelles : enseignements des longues séries temporelles de données du système de télémétrie Flowbru

Les longues séries temporelles de données fournies par le réseau hydrométrique régional Flowbru (www.flowbru.be) offrent une nouvelle occasion de mieux comprendre le système hydrographique de Bruxelles. L'exploration et l'analyse de ces données, assorties de leur consolidation, de leur modélisation et de leur interprétation minutieuse, apportent un éclairage nouveau sur les performances du système d'assainissement. En premier lieu, le problème des infiltrations d'eau limpide parasite dans le réseau est abordé. De nouvelles méthodes sont mises au point pour calculer les volumes d'eau claire qui pénètrent quotidiennement dans l'ensemble de la zone traitée par la station d'épuration de Bruxelles-Nord. L'importance des variations saisonnières des infiltrations est mise en lumière, de même que les moyens de détecter ces variations dans les séries temporelles limnimétriques, de façon à repérer les canalisations sujettes à des infiltrations. L'étude porte ensuite sur l'accumulation des sédiments dans le principal collecteur de la Région bruxelloise, à savoir, le grand émissaire de la rive droite du canal. La dynamique de cette accumulation est examinée, puis une comparaison entre la situation actuelle et celle des années 1980 fait apparaître que le phénomène s'est fortement accentué au cours de ces dernières décennies. Les possibles causes et conséquences de cette accumulation sont enfin brièvement évoquées.De langdurig verzamelde gegevens, vrijgegeven door het regionaal hydrometrisch netwerk Flowbru (www.flowbru.be) vertegenwoordigen een nieuwe kans om kennis te vergaren over het hydrografisch systeem in Brussel. Via een combinatie van datamininganalyse, gegevensconsolidatie, modellen en diepgaande gegevensinterpretatie, worden nieuwe inzichten over de prestaties van het rioleringssysteem verkregen. Allereerst wordt het probleem van de infiltratie van parasitair helder water in het rioleringssysteem aangekaart. Een nieuwe methode werd ontwikkeld om de dagelijkse hoeveelheden geïnfiltreerd helder water te berekenen in de gehele zone die behandeld wordt door de rioolwaterzuiveringsinstallatie Brussel Noord (RWZI). We tonen de sterke seizoensgebonden infiltratieschommelingen en hoe dit patroon in limnimetrische tijdreeksen kan worden geïdentificeerd om de riolen waar de infiltratie gebeurt aan te duiden. In tweede instantie buigen we ons over de accumulatie van rioolsedimenten in de Brusselse hoofdcollector Rechteroever – de grootste riolering in het Brussels Gewest. De accumulatiedynamiek wordt besproken, en een vergelijking tussen de huidige situatie en die van de jaren 1980 toont de enorme stijging in sedimentaccumulatie in de afgelopen decennia. De mogelijke oorzaken en gevolgen van deze accumulatie worden kort besproken.The long time data series provided by the Flowbru regional hydrometric network (www.flowbru.be) represents a new opportunity to gain knowledge on the hydrographical system in Brussels. With a combination of data mining analysis, data consolidation, models and in-depth data interpretation, new insights on sewer system performance are obtained. First, the problem of the infiltration of parasitic clear water into the sewer system is addressed. A new methodology is developed to compute the daily volumes of clear water infiltrated in the entire zone treated by the Brussels-North Wastewater Treatment Plant (WWTP). We show the strong seasonal variation of infiltration and how this pattern can be identified in limnimetric time series to highlight sewers which are subject to infiltration. Secondly, the sewer sediment accumulation in the Brussels Right main collector – the largest sewer in the Brussels Region – is studied. The accumulation dynamics are discussed, and a comparison between the present situation and that of the 1980s shows the massive increase in sediment accumulation in recent decades. The potential causes and consequences of this accumulation are discussed briefly

Waterbeheer in Brussel: kennis vergaard via de langdurige gegevensreeksen van het gewestelijk telemetriesysteem Flowbru

De langdurig verzamelde gegevens, vrijgegeven door het regionaal hydrometrisch netwerk Flowbru (http://www.flowbru.be) vertegenwoordigen een nieuwe kans om kennis te vergaren over het hydrografisch systeem in Brussel. Via een combinatie van datamininganalyse, gegevensconsolidatie, modellen en diepgaande gegevensinterpretatie, worden nieuwe inzichten over de prestaties van het rioleringssysteem verkregen. Allereerst wordt het probleem van de infiltratie van parasitair helder water in het rioleringssysteem aangekaart. Een nieuwe methode werd ontwikkeld om de dagelijkse hoeveelheden geïnfiltreerd helder water te berekenen in de gehele zone die behandeld wordt door de rioolwaterzuiveringsinstallatie Brussel Noord (RWZI). We tonen de sterke seizoensgebonden infiltratieschommelingen en hoe dit patroon in limnimetrische tijdreeksen kan worden geïdentificeerd om de riolen waar de infiltratie gebeurt aan te duiden. In tweede instantie buigen we ons over de accumulatie van rioolsedimenten in de Brusselse hoofdcollector Rechteroever – de grootste riolering in het Brussels Gewest. De accumulatiedynamiek wordt besproken, en een vergelijking tussen de huidige situatie en die van de jaren 1980 toont de enorme stijging in sedimentaccumulatie in de afgelopen decennia. De mogelijke oorzaken en gevolgen van deze accumulatie worden kort besproken.Les longues séries temporelles de données fournies par le réseau hydrométrique régional Flowbru (www.flowbru.be) offrent une nouvelle occasion de mieux comprendre le système hydrographique de Bruxelles. L’exploration et l’analyse de ces données, assorties de leur consolidation, de leur modélisation et de leur interprétation minutieuse, apportent un éclairage nouveau sur les performances du système d’assainissement. En premier lieu, le problème des infiltrations d’eau limpide parasite dans le réseau est abordé. De nouvelles méthodes sont mises au point pour calculer les volumes d’eau claire qui pénètrent quotidiennement dans l’ensemble de la zone traitée par la station d’épuration de Bruxelles-Nord. L’importance des variations saisonnières des infiltrations est mise en lumière, de même que les moyens de détecter ces variations dans les séries temporelles limnimétriques, de façon à repérer les canalisations sujettes à des infiltrations. L’étude porte ensuite sur l’accumulation des sédiments dans le principal collecteur de la Région bruxelloise, à savoir, le grand émissaire de la rive droite du canal. La dynamique de cette accumulation est examinée, puis une comparaison entre la situation actuelle et celle des années 1980 fait apparaître que le phénomène s’est fortement accentué au cours de ces dernières décennies. Les possibles causes et conséquences de cette accumulation sont enfin brièvement évoquées.The long time data series provided by the Flowbru regional hydrometric network (www.flowbru.be) represents a new opportunity to gain knowledge on the hydrographical system in Brussels. With a combination of data mining analysis, data consolidation, models and in-depth data interpretation, new insights on sewer system performance are obtained. First, the problem of the infiltration of parasitic clear water into the sewer system is addressed. A new methodology is developed to compute the daily volumes of clear water infiltrated in the entire zone treated by the Brussels-North Wastewater Treatment Plant (WWTP). We show the strong seasonal variation of infiltration and how this pattern can be identified in limnimetric time series to highlight sewers which are subject to infiltration. Secondly, the sewer sediment accumulation in the Brussels Right main collector – the largest sewer in the Brussels Region – is studied. The accumulation dynamics are discussed, and a comparison between the present situation and that of the 1980s shows the massive increase in sediment accumulation in recent decades. The potential causes and consequences of this accumulation are discussed briefly

Automated segmentation and labeling of subcutaneous mouse implants at 14.1T

Magnetic resonance imaging (MRI) is a valuable tool for studying subcutaneous implants in rodents, providing non-invasive insight into biomaterial conformability and longitudinal characterization. However, considerable variability in existing image analysis techniques, manual segmentation and labeling, as well as the lack of reference atlases as opposed to brain imaging, all render the manual implant segmentation task tedious and extremely time-consuming. To this end, the development of automated and robust segmentation pipelines is a necessary addition to the tools available in rodent imaging research. In this work, we presented and compared commonly used image processing contrast-based segmentation approaches—namely, Canny edge detection, Otsu’s single and multi-threshold methods, and a combination of the latter with morphological operators—with more recently introduced convolutional neural network (CNN-) based models, such as the U-Net and nnU-Net (“no-new-net”). These fully automated end-to-end state-of-the-art neural architectures have shown great promise in online segmentation challenges. We adapted them to the implant segmentation task in mice MRI, with both 2D and 3D implementations. Our results demonstrated the superiority of the 3D nnU-Net model, which is able to robustly segment the implants with an average Dice accuracy of 0.915, and an acceptable absolute volume prediction error of 5.74%. Additionally, we provide researchers in the field with an automated segmentation pipeline in Python, leveraging these CNN-based implementations, and allowing to drastically reduce the manual labeling time from approximately 90 min to less than 5 min (292.959 s ± 6.49 s, N = 30 predictions). The latter addresses the bottleneck of constrained animal experimental time in pre-clinical rodent research

Classification of degenerative parkinsonism subtypes by support-vector-machine analysis and striatal 123I-FP-CIT indices.

OBJECTIVES: To provide an automated classification method for degenerative parkinsonian syndromes (PS) based on semiquantitative 123I-FP-CIT SPECT striatal indices and support-vector-machine (SVM) analysis. METHODS: 123I-FP-CIT SPECT was performed at a single-center level on 370 individuals with PS, including 280 patients with Parkinson's disease (PD), 21 with multiple system atrophy-parkinsonian type (MSA-P), 41 with progressive supranuclear palsy (PSP) and 28 with corticobasal syndrome (CBS) (mean age 70.3 years, 47% female, mean disease duration at scan 1.4 year), as well as 208 age- and gender-matched control subjects. Striatal volumes-of-interest (VOIs) uptake, VOIs asymmetry indices (AIs) and caudate/putamen (C/P) ratio were used as input for SVM individual classification using fivefold cross-validation. RESULTS: Univariate analyses showed significantly lower VOIs uptake, higher striatal AI and C/P ratio for each PS in comparison to controls (all p  70% accuracy. Overall, striatal AI and C/P ratio on the more affected side had the highest weighting factors. CONCLUSION: Semiquantitative 123I-FP-CIT SPECT striatal evaluation combined with SVM represents a promising approach to disentangle PD from non-degenerative conditions and from atypical PS at the early stage

Prevalence and incidence of postpartum depression and environmental factors: the IGEDEPP cohort

Background: IGEDEPP (Interaction of Gene and Environment of Depression during PostPartum) is a prospective multicenter cohort study of 3,310 Caucasian women who gave birth between 2011 and 2016, with follow-up until one year postpartum. The aim of the current study is to describe the cohort and estimate the prevalence and cumulative incidence of early and late postpartum depression (PPD). Methods: Socio-demographic data, personal and family psychiatric history, as well as stressful life events during childhood and pregnancy were evaluated at baseline. Early and late PPD were assessed at 8 weeks and 1 year postpartum respectively, using DSM-5 criteria. Results: The prevalence of early PPD was 8.3% (95%CI 7.3-9.3), and late PPD 12.9% (95%CI 11.5-14.2), resulting in an 8-week cumulative incidence of 8.5% (95%CI 7.4-9.6) and a one-year cumulative incidence of PPD of 18.1% (95%CI: 17.1-19.2). Nearly half of the cohort (N=1571, 47.5%) had a history of at least one psychiatric or addictive disorder, primarily depressive disorder (35%). Almost 300 women in the cohort (9.0%) reported childhood trauma. During pregnancy, 47.7% women experienced a stressful event, 30.2% in the first 8 weeks and 43.9% between 8 weeks and one year postpartum. Nearly one in five women reported at least one stressful postpartum event at 8 weeks. Conclusion: Incident depressive episodes affected nearly one in five women during the first year postpartum. Most women had stressful perinatal events. Further IGEDEPP studies will aim to disentangle the impact of childhood and pregnancy-related stressful events on postpartum mental disorders.Comment: 34 pages, 6 table

Maternal and perinatal outcomes following pre-Delta, Delta, and Omicron SARS-CoV-2 variants infection among unvaccinated pregnant women in France and Switzerland: a prospective cohort study using the COVI-PREG registry.

BACKGROUND SARS-CoV-2 positive pregnant women are at higher risk of adverse outcomes, but little evidence is available on how variants impact that risk. We aim to evaluate maternal and perinatal outcomes among unvaccinated pregnant women that tested positive for SARS-CoV-2, stratified by pre-Delta, Delta, and Omicron periods. METHODS This prospective study enrolled women from March 2020 to September 2022. Exposure to the different SARS-CoV-2 variants was defined by their periods of predominance. The primary outcome was severe maternal adverse outcome defined as either intensive care unit admission, acute respiratory distress syndrome, advanced oxygen supplementation, or maternal death. The secondary outcomes were preterm birth and other perinatal outcomes. FINDINGS Overall, 1402, 262, and 391 SARS-CoV-2 positive pregnant women were enrolled during the pre-Delta, Delta, and Omicron periods respectively. Severe maternal adverse outcome was reported in 3.4% (n = 947/1402; 95% confidence intervals (95%CI) 2.5-4.5), 6.5% (n = 7/262; 95%CI 3.8-10.2), and 1.0% (n = 4/391; 95%CI 0.3-2.6) of women during the pre-Delta, Delta, and Omicron periods. The risk of severe maternal adverse outcome was higher during the Delta vs pre-Delta period (adjusted risk ratio (aRR) = 1.8; 95%CI 1.1-3.2) and lower during the Omicron vs pre-Delta period (aRR = 0.3; 95%CI, 0.1-0.8). The risks of hospitalization for COVID-19 were 12.6% (n = 176/1402; 95%CI 10.9-14.4), 17.2% (n = 45/262; 95%CI 12.8-22.3), and 12.5% (n = 49/391; 95%CI 9.4-16.2), during the pre-Delta, Delta, and Omicron period, respectively. Pregnancy complications occurred after SARS-CoV-2 exposure in 30.0% (n = 363/1212; 95%CI 27.4-32.6), 35.2% (n = 83/236; 95%CI 29.1-41.6), and 30.3% (n = 105/347; 95%CI 25.5-35.4) of patients during the pre-Delta, Delta, and Omicron periods, respectively. Stillbirths were reported in 0.5% (n = 6/1159; 95%CI 0.2-1.1), 2.8% (n = 6/210; 95%CI 1.0-6.0), and 0.9% (n = 2/213; 95%CI 0.1-3.4) or patients during the pre-Delta, Delta, and Omicron periods respectively. INTERPRETATION The Delta period was associated with a higher risk of severe maternal adverse outcome and the Omicron period with a lower risk of severe adverse outcome compared to pre-Delta era. The reported risk of hospitalization was high during the Omicron period and should not be trivialized. FUNDING Swiss Federal Office of Public Health, Fondation CHUV

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist)

Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.</p

Maternal outcomes and risk factors for COVID-19 severity among pregnant women.

Pregnant women may be at higher risk of severe complications associated with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which may lead to obstetrical complications. We performed a case control study comparing pregnant women with severe coronavirus disease 19 (cases) to pregnant women with a milder form (controls) enrolled in the COVI-Preg international registry cohort between March 24 and July 26, 2020. Risk factors for severity, obstetrical and immediate neonatal outcomes were assessed. A total of 926 pregnant women with a positive test for SARS-CoV-2 were included, among which 92 (9.9%) presented with severe COVID-19 disease. Risk factors for severe maternal outcomes were pulmonary comorbidities [aOR 4.3, 95% CI 1.9-9.5], hypertensive disorders [aOR 2.7, 95% CI 1.0-7.0] and diabetes [aOR2.2, 95% CI 1.1-4.5]. Pregnant women with severe maternal outcomes were at higher risk of caesarean section [70.7% (n = 53/75)], preterm delivery [62.7% (n = 32/51)] and newborns requiring admission to the neonatal intensive care unit [41.3% (n = 31/75)]. In this study, several risk factors for developing severe complications of SARS-CoV-2 infection among pregnant women were identified including pulmonary comorbidities, hypertensive disorders and diabetes. Obstetrical and neonatal outcomes appear to be influenced by the severity of maternal disease