Search

Global citizenship education (GCE) seeks to develop critical thinking and self-reflexivity and, crucially, to create feelings of belonging to a common humanity. Although the subjectivity of belonging has been widely recognized, gaps remain around the micro-level experiences and practices that foster global identities. This article addresses these questions through the analysis of the individual's lived experience on an international GCE programme. It will be argued that global belonging is a transformative process of self-identity, shaped primarily through shared sensorial experience where the unfamiliar becomes familiar. The senses here help to create new personal and shared norms building trust, bonds and belonging between individuals from different backgrounds. Thus, in order to understand the journey towards feelings of global belonging, we must look to the senses as key sites of transformation.

Abstract There is scarce data on energy expenditure in ill children with different degrees of malnutrition. This study aimed to determine resting energy expenditure (REE) trajectories in hospitalized malnourished children during and after hospitalization. We followed a cohort of children in Bangladesh and Malawi (2–23 months) with: no wasting (NW); moderate wasting (MW), severe wasting (SW), or edematous malnutrition (EM). REE was measured by indirect calorimetry at admission, discharge, 14-and-45-days post-discharge. 125 children (NW, n = 23; MW, n = 29; SW, n = 51; EM, n = 22), median age 9 (IQR 6, 14) months, provided 401 REE measurements. At admission, the REE of children with NW and MW was 67 (95% CI [58, 75]) and 70 (95% CI [63, 76]) kcal/kg/day, respectively, while REE in children with SW was higher, 79 kcal/kg/day (95% CI [74, 84], p = 0.018), than NW. REE in these groups was stable over time. In children with EM, REE increased from admission to discharge (65 kcal/kg/day, 95% CI [56, 73]) to 79 (95% CI [72, 86], p = 0.0014) and was stable hereafter. Predictive equations underestimated REE in 92% of participants at all time points. Recommended feeding targets during the acute phase of illness in severely malnourished children exceeded REE. Acutely ill malnourished children are at risk of being overfed when implementing current international guidelines.

Abstract Biomarker identification could help in deciphering endometriosis pathophysiology in addition to their use in the development of non invasive diagnostic and prognostic approaches, that are essential to greatly improve patient care. Despite extensive efforts, no single potential biomarker or combination has been clinically validated for endometriosis. Many studies have investigated endometriosis-associated biological markers in specific tissues, but an integrative approach across tissues is lacking. The aim of this review is to propose a comprehensive overview of identified biomarkers based on tissue or biological compartment, while taking into account endometriosis phenotypes (superficial, ovarian or deep, or rASRM stages), menstrual cycle phases, treatments and symptoms. We searched PubMed and Embase databases for articles matching the following criteria: 'endometriosis' present in the title and the associated term 'biomarkers' found as Medical Subject Headings (MeSH) terms or in all fields. We restricted to publications in English and on human populations. Relevant articles published between 01 January 2005 (when endometriosis phenotypes start to be described in papers) and 01 September 2022 were critically analysed and discussed. Four hundred forty seven articles on endometriosis biomarkers that included a control group without endometriosis and provided specific information on endometriosis phenotypes are included in this review. Presence of information or adjustment controlling for menstrual cycle phase, symptoms and treatments is highlighted, and the results are further summarized by biological compartment. The 9 biological compartments studied for endometriosis biomarker research are in order of frequency: peripheral blood, eutopic endometrium, peritoneal fluid, ovaries, urine, menstrual blood, saliva, feces and cervical mucus. Adjustments of results on disease phenotypes, cycle phases, treatments and symptoms are present in 70%, 29%, 3% and 6% of selected articles, respectively. A total of 1107 biomarkers were identified in these biological compartments. Of these, 74 were found in several biological compartments by at least two independent research teams and only 4 (TNF-a, MMP-9, TIMP-1 and miR-451) are detected in at least 3 tissues with cohorts of 30 women or more. Integrative analysis is a crucial step to highlight potential pitfalls behind the lack of success in the search for clinically relevant endometriosis biomarkers, and to illuminate the physiopathology of this disease. Graphical Abstract

Introduction Bipolar disorder (BD) is a chronic and severe psychiatric disorder, characterized by the alternance of episodes of (hypo)-mania and major depression. Lithium (Li) is the first-line treatment for BD but unfortunately response to Li is highly variable: after at least two consecutive years of treatment, only a fraction of patients receiving Li will display significant improvement in the frequency and/or severity of mood recurrences. This interindividual variability of treatment response is difficult to predict, in the bipolar disorder context. This could be determined by genetic factors still misidentified by available genetic studies. In addition, no clinical or biological markers are available to reliably define eligibility criteria for a lithium treatment in bipolar disorder. A consequence is a long process of therapeutic trials (18-24 months) to phenotype Li response, delaying the stabilization. Objectives To identify objective biomarkers of the prophylactic response to lithium in order to improve patient care and propose therapeutic alternatives to patients who do not respond to lithium. Methods Using a genome-wide methylomic approach, and then logistic regressions incorporating as covariates the different types of treatments, we were able to identify differentially methylated regions (DMRs) whose methylation difference between responders and non-responders was not impacted by co-prescribed treatments. Then, we used Methylation Specific High-Resolution Melting (MS-HRM), a PCR based method than can be implemented in any medical laboratory at low cost and with minimal equipment, to estimate methylation proportion of 9 DMRs in 61 samples of bipolar patients. Results In the sample of 61 individuals with BD, the 9 MS-HRM-measured DMRs combined with clinical variables (age, sex, cigarette smoking status, lifetime number of hospitalizations, age at onset of BD, polarity at onset, psychotic symptoms at onset, family history of BD, lifetime alcohol/cannabis misuse, panic disorders, Li prescribed as the first mood stabilizer (vs 2nd or 3rd choice)) correctly classified 83,6% of individuals as good or non-responders (n=61, prophylactic response phenotype defined using the “Alda” scale). Excluding the partial responders, the percentage of correctly classified individuals is as high as 100% (n=43, 18 non responders and 25 responders). The AUC are respectively AUC=0.913 and AUC=1.0. Conclusions The MS-HMR method allow to identify the response status of individuals with BD with 9 DMR. These DMRs discriminate good from non-responders and can be used in combination with clinical variables. Disclosure of Interest None Declared

The beneficial effect of sodium-glucose cotransporter-2 inhibitors (SGLT2i) have been shown recently in numerous randomized controlled trials (RCT) and systematic reviews. According to KDIGO guidelines, SGLT2i currently represent a first choice for diabetic patients with chronic kidney disease (CKD). In addition, a recent meta-analysis of 13 large led by the ‘SGLT2 inhibitor Meta-Analysis Cardio-Renal Trialists’ Consortium’ (SMART-C) provided solid evidence of SGLT2i beneficial effects in CKD or in patients with heart failure, with and without diabetes. Collectively, the patients treated with SGLT2i had a decreased risk of CKD progression, acute kidney injury (AKI), end-stage kidney disease (ESKD) or death from heart failure. Whether these cardio-renal benefits should be extrapolated to kidney transplant recipients (KTR) needs to be assessed in further studies. In this article, we report recent data accumulated so far in the literature, looking at the efficacy and safety of SGLT2i in diabetic and non-diabetic KTR. We found encouraging data regarding the use of SGLT2i in KTR with diabetes. These agents appeared to be safe, and they reduced body weight and blood pressure in this group of patients. Potential effects on kidney graft function and survival are yet to be investigated.

Summary: Background: Growth faltering is well-recognized during acute childhood illness and growth acceleration during convalescence, with or without nutritional therapy, may occur. However, there are limited recent data on growth after hospitalization in low- and middle-income countries. Methods: We evaluated growth following hospitalization among children aged 2–23 months in sub-Saharan Africa and South Asia. Between November 2016 and January 2019, children were recruited at hospital admission and classified as: not-wasted (NW), moderately-wasted (MW), severely-wasted (SW), or having nutritional oedema (NO). We describe earlier (discharge to 45-days) and later (45- to 180-days) changes in length-for-age [LAZ], weight-for-age [WAZ], mid-upper arm circumference [MUACZ], weight-for-length [WLZ] z-scores, and clinical, nutritional, and socioeconomic correlates. Findings: We included 2472 children who survived to 180-days post-discharge: NW, 960 (39%); MW, 572 (23%); SW, 682 (28%); and NO, 258 (10%). During 180-days, LAZ decreased in NW (−0.27 [−0.36, −0.19]) and MW (−0.23 [−0.34, −0.11]). However, all groups increased WAZ (NW, 0.21 [95% CI: 0.11, 0.32]; MW, 0.57 [0.44, 0.71]; SW, 1.0 [0.88, 1.1] and NO, 1.3 [1.1, 1.5]) with greatest gains in the first 45-days. Of children underweight (

Effective translation of data to inform real-time patient care is lacking in addiction inpatient settings. The current study presents the optimization of an assessment report that is used by clinicians to individualize treatment. A multi-aim, iterative approach was taken, utilizing an implementation science perspective to arrive at a final version of the assessment report. This occurred at a small inpatient addiction treatment facility. Participants were all available clinical staff (N = 7; female = 71%). A quantitative survey was used for aims 1 and 2 to, respectively, assess motives and context around the report as well as evaluate its design. Aim 3 focused on optimization via semi-structured interviews. Descriptive and modified content analyses were utilized appropriately across aims. This resulted in five versions of the assessment report being created between February 2021 and August 2022, the most recent of which was adapted into patients’ electronic medical records. We discuss each version of the report in depth, including clinicians’ iterative feedback and researchers’ perceived barriers to this translational process. The response rate was 64.3%. The current study highlights a replicable approach for optimizing the translation of assessment data into treatment for patients with disorders of addiction as well as an assessment report that could be utilized by similar facilities with a naturally low sample size.

Spectrometers play a decisive role in the education of A-level and/or under-graduate students in the field of natural sciences. They are capable to demonstrate atomic emission, transmission, reflection and fluorescence spectra, but can be used for wavelength filtering, as well. Here, we present a do-it-yourself spectrometer setup based on a Czerny--Turner design that (a) can be used for all measurement types with one and the same setup and (b) is capable to spectrally resolve atomic emission lines. We use LEGO® bricks for the optomechanical construction and combine it with affordable, but high-quality optical components and linear array based on a charge-coupled device (CCD). A modular design is implemented and allows for a quick change between the various measurement techniques, but also fosters the technological understanding of the underlying systems' optical design.

Jessica L Bourdon,1 Sidney Judson,1 Gabriella Caporaso,1 Monica F Wright,2 Taylor Fields,1 Nehal P Vadhan,3 Jon Morgenstern4 1Center for Addiction Science, Wellbridge Addiction Treatment and Research, Calverton, NY, USA; 2Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA; 3Institute of Behavioral Science, Feinstein Institutes for Medical Research, Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempsted, NY, USA; 4Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempsted, NY, USACorrespondence: Jessica L Bourdon, Center for Addiction Science, Wellbridge Addiction Treatment and Research, 525 Jan Way, Calverton, NY, 11933, USA, Email jbourdon@wellbridge.orgBackground: Quality training is an oft-cited barrier to effective implementation and ongoing delivery of high-quality evidence-based practice (EBP) across fields. This is especially true in the addiction field, but there is little cited evidence for optimal methods to improve EBP in inpatient addiction facilities with minimal resources.Objective: The current paper focuses on evaluating the state of our facility’s group CBT manual and clinical training on the manual in a “realistic” (ie, non-RCT, non-grant-funded) inpatient addiction treatment setting.Methods: Five full-time clinicians volunteered to take part in the study (woman = 60%; Mage = 36.20 years). The study involved a mix of semi-structured interviews and surveys designed to measure seven outcomes (barriers, feasibility, useability, appropriateness, acceptability, burden, trialability).Results: Three themes emerged from the data that impacted the group CBT manual: training, timing, and functionality. Addressing these themes allowed for a new, optimal manual and training procedure to be put into place.Conclusion: The current study highlights that under-resourced inpatient addiction facilities can still methodically utilize implementation approaches to study their EBP, namely CBT. Such an approach will ensure that the highest quality care is being delivered to patients and actively addresses known training barriers that prevent proper EBP delivery.Plain Language Summary: Quality training is a barrier when implementing evidenced-based practice to treat substance use disorders.CBT is a manualized evidence-based practice that is performed at inpatient addiction facilities.An evaluation of the CBT manual was made by an inpatient addiction facility to identify barriers of implementation of EBPs.Identified barriers included training, timing, and functionality.Keywords: cognitive behavioral therapy, addiction, evidence-based practice, inpatient, substance use disorders

Abstract Background Growth studies rely on longitudinal measurements, typically represented as trajectories. However, anthropometry is prone to errors that can generate outliers. While various methods are available for detecting outlier measurements, a gold standard has yet to be identified, and there is no established method for outlying trajectories. Thus, outlier types and their effects on growth pattern detection still need to be investigated. This work aimed to assess the performance of six methods at detecting different types of outliers, propose two novel methods for outlier trajectory detection and evaluate how outliers affect growth pattern detection. Methods We included 393 healthy infants from The Applied Research Group for Kids (TARGet Kids!) cohort and 1651 children with severe malnutrition from the co-trimoxazole prophylaxis clinical trial. We injected outliers of three types and six intensities and applied four outlier detection methods for measurements (model-based and World Health Organization cut-offs-based) and two for trajectories. We also assessed growth pattern detection before and after outlier injection using time series clustering and latent class mixed models. Error type, intensity, and population affected method performance. Results Model-based outlier detection methods performed best for measurements with precision between 5.72-99.89%, especially for low and moderate error intensities. The clustering-based outlier trajectory method had high precision of 14.93-99.12%. Combining methods improved the detection rate to 21.82% in outlier measurements. Finally, when comparing growth groups with and without outliers, the outliers were shown to alter group membership by 57.9 -79.04%. Conclusions World Health Organization cut-off-based techniques were shown to perform well in few very particular cases (extreme errors of high intensity), while model-based techniques performed well, especially for moderate errors of low intensity. Clustering-based outlier trajectory detection performed exceptionally well across all types and intensities of errors, indicating a potential strategic change in how outliers in growth data are viewed. Finally, the importance of detecting outliers was shown, given its impact on children growth studies, as demonstrated by comparing results of growth group detection.

Abstract Background Melanoma is the deadliest type of skin cancer and despite improvements in treatment outcomes, melanoma claimed 57,043 lives in 2020. In most malignancies, p53 mutation rates are above 50% and provide prognostic indications. However, in melanoma where less than a quarter of cases harbour a p53 mutation, the significance of the tumour suppressor may be questioned. Instead, p53 isoforms, which modulate p53’s canonical function, may be of greater clinical importance. Methods The expression of p53 isoforms was evaluated in 123 melanoma specimens by immunohistochemistry using p53 isoform-specific antibodies (DO-1, KJC8, KJC40, and KJC133). To determine whether TP53 mutations may be driving p53 isoform expression, TP53 was sequenced in 30 FFPE melanoma samples. Results The C-terminally truncated p53β isoforms (KJC8) were found to be the most highly expressed p53 isoforms compared to all other isoforms. Further, elevated KJC8 staining was found to correlate with reduced probability of melanoma-specific survival, while KJC40 staining (Δ40p53) positively correlated with reduced melanoma thickness. TAp53 isoforms (p53 retaining both transactivation domains, DO-1), were the second highest p53 isoforms expressed across all samples. Elevated DO-1 staining was also associated with worse survival outcomes and more advanced stages of cancer. Given that the isoforms are likely to work in concert, composite isoform profiles were generated. Composite biomarker profiles revealed that elevated TAp53 (DO-1) and p53β (KJC8) expression, accompanied by low Δ40p53 (KJC40) and Δ133p53 (KJC133) expression was associated with the worst survival outcomes. Supporting the lack of predictive biomarker potential of TP53 in melanoma, no clinicopathological or p53 isoform expression associations could be linked to TP53 status. Conclusions Given the lack of prognostic biomarker potential derived from TP53 status, this study highlights how p53 isoform expression might progress this field and, pending further validation, may provide additional information to treating oncologists that might be factored into treatment decisions.

Abstract Background Children admitted to hospital with complicated severe malnutrition (CSM) have high mortality despite compliance with standard WHO management guidelines. Limited data suggests a relationship between intestinal dysfunction and poor prognosis in CSM, but this has not been explicitly studied. This study aimed to evaluate the role of intestinal disturbances in CSM mortality. Methods A case-control study nested within a randomized control trial was conducted among children hospitalized with CSM in Kenya and Malawi. Children who died (cases, n = 68) were compared with those who were discharged, propensity matched to the cases on age, HIV and nutritional status (controls, n = 68) on fecal metabolomics that targeted about 70 commonly measured metabolites, and enteropathy markers: fecal myeloperoxidase (MPO), fecal calprotectin, and circulating intestinal fatty acid binding protein (I-FABP). Results The fecal metabolomes of cases show specific reductions in amino acids, monosaccharides, and microbial fermentation products, when compared to controls. SCFA levels did not differ between groups. The overall fecal metabolomics signature moderately differentiates cases from controls (AUC = 0.72). Enteropathy markers do not differ between groups overall, although serum I-FABP is elevated in cases in a sensitivity analysis among non-edematous children. Integrative analysis with systemic data suggests an indirect role of intestinal inflammation in the causal path of mortality. Conclusions Intestinal disturbances appear to have an indirect association with acute mortality. Findings of the study improve our understanding of pathophysiological pathways underlying mortality of children with CSM.

Abstract Background The impact of a perturbation, over-expression, or repression of a key node on an organism, can be modelled based on a regulatory and/or metabolic network. Integration of these two networks could improve our global understanding of biological mechanisms triggered by a perturbation. This study focuses on improving the modelling of the regulatory network to facilitate a possible integration with the metabolic network. Previously proposed methods that study this problem fail to deal with a real-size regulatory network, computing predictions sensitive to perturbation and quantifying the predicted species behaviour more finely. Results To address previously mentioned limitations, we develop a new method based on Answer Set Programming, MajS. It takes a regulatory network and a discrete partial set of observations as input. MajS tests the consistency between the input data, proposes minimal repairs on the network to establish consistency, and finally computes weighted and signed predictions over the network species. We tested MajS by comparing the HIF-1 signalling pathway with two gene-expression datasets. Our results show that MajS can predict 100% of unobserved species. When comparing MajS with two similar (discrete and quantitative) tools, we observed that compared with the discrete tool, MajS proposes a better coverage of the unobserved species, is more sensitive to system perturbations, and proposes predictions closer to real data. Compared to the quantitative tool, MajS provides more refined discrete predictions that agree with the dynamic proposed by the quantitative tool. Conclusions MajS is a new method to test the consistency between a regulatory network and a dataset that provides computational predictions on unobserved network species. It provides fine-grained discrete predictions by outputting the weight of the predicted sign as a piece of additional information. MajS’ output, thanks to its weight, could easily be integrated with metabolic network modelling.

Le programme de recherche Participe 3.0 vise à accompagner huit jeunes adultes autistes dyscommunicants vers un habitat inclusif partagé, par l’introduction d’outils de réalité virtuelle consacrés à la préparation du repas (Fuchs, 2018; Cherix et al., 2019). Il s’agit d’analyser comment, en contexte d’éducation/formation, un environnement immersif 3D peut favoriser l’attention et les interactions pour un public aux percepts langagiers et psychosensoriels caractéristiques (Bogdashina, 2020; Mottron, 2004). Les recherches attestent que les outils numériques peuvent encourager l’engagement dans l'activité, au sens de Leontiev (1975/2022), d’enfants avec autisme (Bourgueil et al., 2015; Mercier et al., 2022). Mais qu’en est-il, lors de l’immersion au sein de capsules de réalité virtuelle, de leur capacité visuoattentionnelle et praxique, inhérente au couplage perception-action? Dans quelle mesure ces technologies immersives pourraient-elles minorer les troubles attentionnels, déficit cognitif fréquemment rapporté, et favoriser l’engagement dans l’activité? Les résultats montrent l’importance d’un scénario pédagogique conçu en démarche collaborative, centré sur l’utilisateur (Guffroy et al., 2017; Bourdon, 2021) pour majorer la participation et l’attention, et étayer les apprentissages d’apprenants dyscommunicants. Ils mettent en lumière la pertinence d’artefacts immersifs, au sein d’un environnement capacitant, pour acquérir une autonomie progressive (Rocque et al., 2001).

BackgroundThere is ample evidence that most children do not perform enough physical activity (PA). To address this major public health problem, the French government implemented 30 minutes of daily PA (DPA) at schools but did not provide any supplemental resources or concrete guidance. Considering both children’s interest in video games and the need for teachers to complete their curriculum, the use of a learning-based exergame that combines PA and learning appears particularly relevant. ObjectiveThe first objective of this study was to evaluate the feasibility of implementing 30 minutes of DPA through exergaming among school-age children. The second objective was to examine the effects of an exergaming program on physical literacy, academic learning, and soft skills (motivation, self-efficacy, and concentration). MethodsThis interventional study had a pre-post design and used the Play LÜ exergame platform. The study included 79 children with a mean age of 8.9 (SD 1.2) years from grade 2 (7 years old) to grade 5 (11 years old). Play LÜ requires players to throw balls against a wall to reach a target or to activate an object and provides an interactive game area for educational activities linked to specific learning themes. After a 4-session familiarization phase during which the teachers chose to prioritize mathematics learning in 30-minute DPA sessions, students took part in DPA sessions over a period of 3 weeks with Play LÜ and a motor skills circuit behind the LÜ setup to keep them continuously active. All sessions were carried out by PA specialists. Each session started with a warm-up using the Grööve application, continued with main activities promoting mathematics learning adapted to each grade level, and ended with a 3-minute meditation for returning to a calm and serene state using the Gaïa application. Before (T0) and after (T1) the program, students completed a self-evaluation booklet to assess their levels of physical literacy, academic performance, and soft skills. ResultsThe implementation of this exergaming program was welcomed by the school’s administration, teaching staff, and parents. After the program, we observed increased scores for physical literacy (difference +2.6, percentage change +3.6%; W=933.0; P=.002; rrb=−0.39, 95% CI −0.58 to −0.16) and motivation in mathematics (+0.7, +9.8%; W=381.5; P=.005; rrb=−0.44, 95% CI −0.66 to −0.16). In addition, it is important to note that some measures progressed differently across learning levels and age groups. ConclusionsThe study results indicate positive impacts of learning-based exergaming on physical literacy and motivation in mathematics among school-age children.

Giving birth prematurely is a traumatic event that has many consequences for the mother but also for her baby and their family. Studies have shown that about a quarter of these mothers will suffer from post-traumatic stress disorder (PTSD) as a result. This study aims to identify internal personality factors associated with the development of PTSD in mothers who gave birth before 33 weeks. The results revealed significant correlations between two personality dimensions (neuroticism and extraversion) and the likeliness of developing PTSD in mothers who gave birth prematurely. Neuroticism is positively liked with the disorder while extraversion is negatively correlated with it. Studies should now focus on early detection of PTSD and better interventions for these mothers.

Neutrophils are the most abundant innate immune cells. Multiple mechanisms allow them to engage a wide range of metabolic pathways for biosynthesis and bioenergetics for mediating biological processes such as development in the bone marrow and antimicrobial activity such as ROS production and NET formation, inflammation and tissue repair. We first discuss recent work on neutrophil development and functions and the metabolic processes to regulate granulopoiesis, neutrophil migration and trafficking as well as effector functions. We then discuss metabolic syndromes with impaired neutrophil functions that are influenced by genetic and environmental factors of nutrient availability and usage. Here, we particularly focus on the role of specific macronutrients, such as glucose, fatty acids, and protein, as well as micronutrients such as vitamin B3, in regulating neutrophil biology and how this regulation impacts host health. A special section of this review primarily discusses that the ways nutrient deficiencies could impact neutrophil biology and increase infection susceptibility. We emphasize biochemical approaches to explore neutrophil metabolism in relation to development and functions. Lastly, we discuss opportunities and challenges to neutrophil-centered therapeutic approaches in immune-driven diseases and highlight unanswered questions to guide future discoveries.

BackgroundCongenital heart defects are common and occur in approximately 0.9% of births. In France, the registries cover approximately 20% of the population but not the entirety of France; therefore, we aimed to update the incidence data for congenital heart defects in France from 2013 to 2022 using the medico-administrative database PMSI-MCO (French Medical Information System Program in Medicine, Surgery, and Obstetrics). We aimed to compare the frequency of risk factors in a population with congenital heart defects and a reference population.MethodsFrom 2013 to 2022, we included children aged < 3 years diagnosed with congenital heart defects according to the International Classification of Diseases, 10th Revision, in the PMSI-MCO database. We compared them with a population without congenital defects on several medical data items (e.g., parity, gemellarity, and mortality rate). Bivariate and multivariate analyses compared children with congenital heart defects and children without congenital malformation.ResultsWe identified 83,879 children with congenital heart defects in France from 2013 to 2022 in the PMSI-MCO database and 7,739,840 children without such defects, including 7,218,952 without any congenital defects. We observed more deaths (7.49% vs. 0.68%, d = 0.59) and more twinning (8.67% vs. 1.23%, d = 0.35) among children with congenital heart defects. Multivariate analysis revealed an increased risk of congenital heart defects in male individuals (OR [odds ratio] 1.056, 95% CI [confidence interval] [1.039-1.076]) and cases of medically assisted reproduction (OR 1.115, 95% CI [1.045-1.189]) and a reduced risk in the case of multiparity (OR 0.921, 95% CI [0.905-0.938]).ConclusionsAccording to the PMSI-MCO database, the incidence of congenital heart defects in France from 2013 to 2022 is 1% of births. Congenital heart defects are more frequent in cases of prematurity, twinning, primiparity, male sex, and maternal age > 40 years.

Scots pine (Pinus sylvestris L.) is an evergreen coniferous tree with wide distribution and good growth performance in a range of habitats. Therefore, wood from P. sylvestris is produced in many managed forests and is frequently used in industry. Despite the importance of pine wood, we still do not fully understand its molecular structure what limits improvements in its processing. One of the basic features leading to variation in wood properties is the presence of earlywood and latewood which form annual growth rings. Here, we characterise biochemical traits that differentiate cell walls of earlywood and latewood in Scots pine. We discover that latewood is less recalcitrant to enzymatic digestion, with galactoglucomannan showing particularly pronounced difference in accessibility. Interestingly, characterisation of lignin reveals a higher proportion of coniferaldehydes in pine latewood and suggests the presence of a different linkage landscape in this wood type. With complementary analysis of wood polysaccharides this enabled us to propose the first detailed molecular model of earlywood and latewood and to conclude that the variation in lignin structure is likely the main determinant of differences in recalcitrance observed between the two wood types in pine. Our discoveries lay the foundation for improvements in industrial processes that use pine wood since we show clear pathways for increasing the efficiency of enzymatic processing of this renewable material. Our work will help guide future breeding of pine trees with desired timber properties and can help link molecular structure of softwood cell walls to function of the different types of xylem in conifers.

Predictive models for recovering from alcohol use disorder (AUD) and identifying related predisposition biomarkers can have a tremendous impact on addiction treatment outcomes and cost reduction. Our sample (N = 1376) included individuals of European (EA) and African (AA) ancestry from the Collaborative Study on the Genetics of Alcoholism (COGA) who were initially assessed as having AUD (DSM-5) and reassessed years later as either having AUD or in remission. To predict this difference in AUD recovery status, we analyzed the initial data using multimodal, multi-features machine learning applications including EEG source-level functional brain connectivity, Polygenic Risk Scores (PRS), medications, and demographic information. Sex and ancestry age-matched stratified analyses were performed with supervised linear Support Vector Machine application and were calculated twice, once when the ancestry was defined by self-report and once defined by genetic data. Multifeatured prediction models achieved higher accuracy scores than models based on a single domain and higher scores in male models when the ancestry was based on genetic data. The AA male group model with PRS, EEG functional connectivity, marital and employment status features achieved the highest accuracy of 86.04%. Several discriminative features were identified, including collections of PRS related to neuroticism, depression, aggression, years of education, and alcohol consumption phenotypes. Other discriminated features included being married, employed, medication, lower default mode network and fusiform connectivity, and higher insula connectivity. Results highlight the importance of increasing genetic homogeneity of analyzed groups, identifying sex, and ancestry-specific features to increase prediction scores revealing biomarkers related to AUD remission.