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Maternal anthropometric measurements in pregnancy and child neurocognitive and behavioral development at 1 and 6 years of age – a cohort study in Benin, Sub-Saharan Africa
No full textInternational audienceBackgroundMaternal malnutrition, especially obesity, is hypothesized to impact offspring neurodevelopment, but less is known in sub-Saharan Africa where undernutrition is highly prevalent.ObjectiveThis study aimed to investigate the association between maternal nutritional status during pregnancy and neurocognitive and behavioral development in children at age one and six years, in a mother-child cohort from Benin.MethodsThis prospective cohort study included surviving singletons born to pregnant women in Allada, Benin. Cognitive and motor functions of 747 and 574 children were assessed at one and six years of age, respectively, in addition to behavioral difficulties and attention deficit and hyperactivity disorders. Statistical analysis using multiple linear regression models tested main associations, potential mediating factors were additionally adjusted for.Results17%, 72.5%, 7.7% and 2.5% of women were estimated to be underweight, normal weight, overweight and obese before pregnancy, respectively. Women who were underweight had a higher median weight gain [240 (170 – 300)] over the course of pregnancy, compared to normal BMI women [210 (160 – 260)], and overweight/obese women [150 (110 – 240)]. After exclusion of obese women, pre-pregnancy BMI was significantly associated with a higher motor scores (0.26, 95%CI 0.002-0.53) and cognitive scores (0.37, 95%CI 0.02-0.72) after adjustment for confounding factors. There was no association between gestational weight gain and offspring neurodevelopment at one and six years of age. There was no association between maternal BMI and gestational weight gain and behavior and attention deficit and hyperactivity disorders at six years of age.ConclusionsOur study suggests that poor maternal nutritional status before pregnancy may impair short- and long-term neurocognition in children in the Beninese context. Undernutrition in childhood has great impact and efforts to adequate prevention for both child and maternal undernutrition should be enforced in low- and middle-income countries
Seven-Coordinate Lanthanide Bis-Halide Bis-Tetrathiometallate Complexes: A Compelling Platform for Luminescent and Magnetic Properties
No full textInternational audienceTo harness the unique luminescent and magnetic properties of lanthanides, precise control over their coordination sphere is essential, whether to minimize deactivation processes or maximize magnetic anisotropy. The traditional approaches rely on the use of large organic ligands bearing strong atom donors to enforce low coordination numbers of Ln ions. Herein we explored an alternative approach, constraining low coordination numbers via a better control of the primary coordination sphere of the Ln center using fully inorganic sulfur-based ligands, tetrathiotungstates. This strategy led to the preparation of an isostructural series of 13 rare-earth complexes, [NEt(4)](3)[LnCl(2)(MeCN){(μ-S)(2)WS(2)}(2)] (1Ln, Ln = Ce-Yb and Y). The unusually low coordination numbers (CN = 7) observed here in the absence of sterically bulky or rigid chelating ligands was rationalized using buried volume analysis. We highlight the potential of this new ligand set for luminescent and single-molecule magnets applications by investigating the properties of 1Yb and 1Dy complexes, respectively
HC(3)As, the simplest arsadiyne
No full textInternational audience1-Arsabutadiyne (2-propynylidynearsine, HC(3)As), is efficiently produced by photolysis of propynylarsine isolated in solid argon. The observed infrared absorption spectra and predicted molecular parameters of HC(3)As and HC(3)P show significant similarities, but large differences compared to HC(3)N
Nivolumab in Metastatic Clear-cell Renal Cell Carcinoma: An Integrative Biomarker Analysis from the NIVOREN GETUG-AFU 26 Phase 2 Study
No full textInternational audienceNivolumab improved survival in patients with refractory metastatic clear-cell renal cell carcinoma (ccRCC), but no reliable biomarker of activity has been identified. We conducted a real-world phase 2 trial of nivolumab in patients progressing after one or more vascular endothelial growth factor (VEGF) receptor-directed therapies, which included an integrated translational programme. Candidate tissue and circulating biomarkers were assessed using immunoassays and gene expression profiling. Overall, 720 patients were treated, with activity and safety in line with pivotal trial data. Exploration of tissue architecture showed that the presence of tertiary lymphoid structures, CD8+ lymphocytes, and CD163+ macrophage infiltration at the invasive margin were all marginally associated with longer progression-free survival, similarly to PD-1 expression on immune cells. Expression of hypoxia-related marker VEGF on tumour cells was however strongly associated with shorter progression-free and overall survival. Recapitulation of microenvironment composition based on gene expression signatures showed that patients harbouring a high tumour lymphocyte infiltration, concomitantly to low infiltration of neutrophil and non-immune stromal cells, had improved response to nivolumab. Conversely, circulating cytokines related to protumoral inflammation interleukin (IL)-6 and IL-8 were independently associated with shorter progression-free and overall survival. Overall, immune and angiogenic features helped inform outcomes to nivolumab. Circulating factors were best potential predictors for immunotherapy activity in ccRCC
Data Paper: HotPig, a behavioural dataset of pigs under heat stress
No full textInternational audienceThe widespread use of videos in modern indoor livestock facilities coupled with the availability of efficient and low-cost computer vision algorithms provides strong incentives for continuously monitoring farm animal behaviour. Deciphering how pigs behave when experiencing prolonged heat stress is particularly important for animal welfare, as it helps us to better understand how animals use various thermoregulation and heat dissipation mechanisms. Data were collected on 24 pigs that were video-monitored day and night under two contrasted conditions: thermoneutral (TN, 22 °C) and heat stress (HS, 32 °C). All pigs were housed individually and had free access to an automatic feeder delivering pellets four times a day, and to water. After acquisition, videos were processed using YOLOv11, a real-time object detection algorithm that uses a convolutional neural network (CNN), to extract the following behavioural traits: drinking, willingness to eat, lying down, standing up, moving around, curiosity towards the littermate housed in the neighbouring pen, and contact between the two animals (cuddling). A minute frequency sampling rate was applied (each minute corresponds to 150 frames processed) for a continuous period of 16 days, spanning the two different thermal conditions (9 days on TN, 6 days on HS, 1 day back to TN). Consistency with the automatic electronic feeder’s data (also provided) was thoroughly checked. The dataset allows quantitative criterion to be analysed to decipher inter-individual differences in animal behaviour and their dynamic adaptation to heat stress. This dataset can be used to train any machine learning methods for behaviour prediction from videos in conventional growing pigs
Estimating the reduction in genetic diversity from background selection under non-equilibrium demography and partial selfing
No full textInternational audienceThe effect of natural selection on linked sites has been suggested to be a major determinant of genetic diversity. While it is in principle possible to estimate this effect from genome sequence data, interactions between selection, demography and inbreeding are expected to make inference less reliable. Here we investigate whether the genome-wide reduction in diversity due to background selection (B¯) can be accurately estimated when populations are at demographic non-equilibrium and/or reproduce by partial self-fertilisation. We show that the classic-BGS model is surprisingly robust to both demographic non-equilibrium and low rates of selfing, although both processes do lead to biased estimation of the distribution of fitness effects (DFE) of deleterious mutations. A high rate of selfing leads to poor estimation of both B¯ and DFE parameters. We propose an alternative approach where background selection, demography and partial selfing are jointly estimated from windowed site frequency spectra. This approach resolves most of the bias observed under the classic-BGS model and can also generate estimates of past demography that account for the effect of background selection and partial selfing. We apply the approach to genome sequence data from Capsella grandiflora and C. orientalis, which have contrasting mating systems and display a forty-fold difference in nucleotide diversity. Our results suggest that background selection has a weak effect on levels of genetic diversity in the outcrosser C. grandiflora B¯=0.89) and a more substantial effect in the predominantly selfing species C. orientalis B¯=0.44), but that background selection alone cannot explain their disparity in genetic diversity
Weed control provided by seed predators saves 20 % crop yield in cereal fields
No full textInternational audienceAlthough many herbicide active substances have been banned, and while weed infestation is a major threat to crop productivity, the extent to which natural weed control provided by seed predators can help farmers manage weed communities remains unknown. The contribution of seed predators to crop productivity through weed control was quantified, and it was assessed whether farming systems such as conservation agriculture played a role in bolstering their impact. A total of 112 seed predator-exclusion cages were set up in 28 cereal fields in France (14 pairs of plots, in which one plot was managed under conservation agriculture and the other under conventional agriculture). Weed emergence and biomass were surveyed, crop yield was measured, and the main seed predators—carabid beetles and rodents—were sampled. A 20 % reduction in yield loss due to weeds was found to be caused by seed predator activity, which was extrapolated to an economic gain of 285 €/ha. However, a whole 60 % of the maximum crop yield potential reached in the absence of weeds remains lost. Moreover, while conservation agriculture enhances weed control, this does not translate into increased crop yield. This study demonstrates the tangible importance of considering seed predators for weed control but highlights the need to combine this approach with other weed control practices or to substantially redesign cropping systems to enhance the beneficial effects of biodiversity on crop productivity
Geometric evaluation of a deep learning method for segmentation of urinary OARs on magnetic resonance imaging for prostate cancer radiotherapy
No full textInternational audienceIntroduction: While urinary organs at risk (OARs) such as the intraprostatic urethra and the bladder trigone are increasingly recognized as associated with severe genitourinary toxicity, their delineation in clinical practice is time consuming and probably associated with a large interobserver variability. The aim of this study was to propose a magnetic resonance (MR) deep learning segmentation of urinary OARs for prostate cancer (PCa) radiotherapy (RT), based on a validated atlas. Material and methods: In this multicentric study, a convolutional neural network (CNN) for image segmentation (nnU-Net) was trained and validated on three image datasets. Two datasets came from MR-linac devices (Unity (R), Elekta and MRIdian (R), Viewray), and one dataset came from the PROSTATEx database (MAGNETOM (R) Trio and Skyra, Siemens). Evaluation of the deep learning segmentation was performed using dice score coefficients (DSC), surface distance (SD) and Hausdorff distance. Results: A total of 265 MRI were analyzed. The mean DSC for all urinary structures was 0.88. The automatic segmentation model proved to be effective in the segmentation of the target volume and large OARs such as the bladder (mean DSC ranging of 0.95). Regarding urinary OARs, the mean DSC ranged between 0.50 and 0.68. The Hausdorff distance ranged between 4.0 mm to 10.3 mm for urinary OARs, highlighting local mismatches caused by large anatomical variations between patients. However, the SD ranged between 1.0 mm and 1.3 mm for urinary OARs, highlighting an overall good surface correlation for all organs. Conclusion: This multicentric study is the first to propose a nnU-Net deep learning model for the delineation of urinary OARs, that can be applied to various image dataset. Further work is needed to assess the dosimetric impact of such variations, in various clinical scenarios
French-Speaking Network of Pharmacogenetics (RNPGx) Recommendations for Gene Panel Analysis Through Genotyping or Sequencing in Pharmacogenetics
No full textInternational audienceBACKGROUND: The implementation of pharmacogenetics in clinical practice increasingly relies on multigene panels. OBJECTIVES: The objective of this study is to develop harmonized recommendations for the design and analytical implementation of multigene pharmacogenetic panels, defining clinically relevant genes and associated regions of interest (ROIs) based on evidence strength, therapeutic applicability, and compatibility with genotyping or sequencing technologies. METHODS: The French-Speaking Network of Pharmacogenetics (RNPGx) evaluated 81 candidate genes across five therapeutic domains (i.e., oncology and supportive care, anesthesia and pain management, cardiology, neurology and psychiatry and immunology and infectious diseases) using a structured, evidence-based scoring system. Each gene was evaluated using a 25-point scoring system integrating pharmacogenetic importance, regulatory and professional society recommendations, and expert consensus. For the genes ultimately selected for the core panel, clinically relevant regions of interest were defined and assigned to one of three analytical classes. Class 1 includes variants with established clinical actionability; Class 2 adds optional variants suitable for extended testing in specialized settings; and Class 3 covers broader genomic regions mainly intended for rare variant or structural analyses. RESULTS: A 28-gene core panel was retained. Class 1 included 76 prioritized variants (including CYP2D6 CNV variants), and Class 2 comprised 62 additional variants (with extended analysis for CYP2D6). Class 3 eligibility was retained for 18 genes. CONCLUSION: The RNPGx recommendations offer a harmonized and flexible framework for pharmacogenetic panel design and for the extraction and interpretation of pharmacogenetic data from whole-exome or whole-genome sequencing
Phthalate and halogeno-phthalates: Promising ligands for lanthanide coordination polymers for materials traceability
No full textInternational audiencePlastic waste recycling is a major challenge. Rigorous waste sorting is an essential step, and the use of luminescent markers could help to improve it. Hetero-lanthanide coordination polymers have proved their efficiency as luminescent markers for fight against counterfeiting. They could also constitute a solution to ensure plastics traceability. However, for this application, luminescence intensity of the markers must be optimized to enable their detection on a rapid sorting line. This review focuses on phthalates and halogeno-phthalates-based heterolanthanide coordination polymers because recent studies suggest that they can exhibit intense and tunable luminescence properties. After a structural analysis of the coordination polymers that have been reported to date, luminescent properties are described