Lung transplantation for interstitial lung disease in idiopathic inflammatory myositis: A cohort study

Connective tissue disease; Idiopathic inflammatory myopathy; Interstitial lung diseaseEnfermedad del tejido conectivo; Miopatía inflamatoria idiopática; Enfermedad pulmonar intersticialMalaltia del teixit conjuntiu; Miopatia inflamatòria idiopàtica; Malaltia pulmonar intersticialIn patients with interstitial lung disease (ILD) complicating classical or amyopathic idio-pathic inflammatory myopathy (IIM), lung transplantation outcomes might be affected by the disease and treatments. Here, our objective was to assess survival and prog-nostic factors in lung transplant recipients with IIM-ILD. We retrospectively reviewed data for 64 patients who underwent lung transplantation between 2009 and 2021 at 19 European centers. Patient survival was the primary outcome. At transplantation, the median age was 53 [46–59] years, 35 (55%) patients were male, 31 (48%) had clas-sical IIM, 25 (39%) had rapidly progressive ILD, and 21 (33%) were in a high- priority transplant allocation program. Survival rates after 1, 3, and 5 years were 78%, 73%, and 70%, respectively. During follow-up (median, 33 [7–63] months), 23% of patients developed chronic lung allograft dysfunction. Compared to amyopathic IIM, classical IIM was characterized by longer disease duration, higher-intensity immunosuppres-sion before transplantation, and significantly worse posttransplantation survival. Five (8%) patients had a clinical IIM relapse, with mild manifestations. No patient expe-rienced ILD recurrence in the allograft. Posttransplantation survival in IIM-ILD was similar to that in international all- cause- transplantation registries. The main factor as-sociated with worse survival was a history of muscle involvement (classical IIM). In lung transplant recipients with idiopathic inflammatory myopathy, survival was similar to that in all-cause transplantation and was worse in patients with muscle involvement compared to those with the amyopathic disease

LITL at CLEF eHealth2016: recognizing entities in French biomedical documents

International audienceThis paper describes the participation of master's students (LITL programme, university of Toulouse) and their teachers to the CLEF eHealth 2016 campaign. Two runs were submitted for task 2 (multilingual information extraction) which consisted in the recognition and categorization of medical entities in French biomedical documents. The system used consists of a CRF classier based on a number of dierent features (POS tagging, generic word lists and syntactic parsing). In addition , several patterns were used on the CRF's output in order to extract more complex entities. The best run achieved high precision (0.640.78) but lower recall (0.320.40), with an overall F1-measure of 0.430.53

What do brain endocasts tell us? A comparative analysis of the accuracy of sulcal identification by experts and perspectives in palaeoanthropology

Palaeoneurology is a complex field as the object of study, the brain, does not fossilize. Studies rely therefore on the (brain) endocranial cast (often named endocast), the only available and reliable proxy for brain shape, size and details of surface. However, researchers debate whether or not specific marks found on endocasts correspond reliably to particular sulci and/or gyri of the brain that were imprinted in the braincase. The aim of this study is to measure the accuracy of sulcal identification through an experiment that reproduces the conditions that palaeoneurologists face when working with hominin endocasts. We asked 14 experts to manually identify well-known foldings in a proxy endocast that was obtained from an MRI of an actual in vivo Homo sapiens head. We observe clear differences in the results when comparing the non-corrected labels (the original labels proposed by each expert) with the corrected labels. This result illustrates that trying to reconstruct a sulcus following the very general known shape/position in the literature or from a mean specimen may induce a bias when looking at an endocast and trying to follow the marks observed there. We also observe that the identification of sulci appears to be better in the lower part of the endocast compared to the upper part. The results concerning specific anatomical traits have implications for highly debated topics in palaeoanthropology. Endocranial description of fossil specimens should in the future consider the variation in position and shape of sulci in addition to using models of mean brain shape. Moreover, it is clear from this study that researchers can perceive sulcal imprints with reasonably high accuracy, but their correct identification and labelling remains a challenge, particularly when dealing with extinct species for which we lack direct knowledge of the brain

Studies on the Cobalt Deficiency in Ruminants (III) : Effects of Thiamine, Glucose and Cobalamin Injection on the Metabolism of Cobalt-deficient Sheep

International audienceN-terminal acetylation is a common protein modification in eukaryotes associated with numerous cellular processes. Inherited mutations in NAA10, encoding the catalytic subunit of the major N-terminal acetylation complex NatA have been associated with diverse, syndromic X-linked recessive disorders, whereas de novo missense mutations have been reported in one male and one female individual with severe intellectual disability but otherwise unspecific phenotypes. Thus, the full genetic and clinical spectrum of NAA10 deficiency is yet to be delineated. We identified three different novel and one known missense mutation in NAA10, de novo in 11 females, and due to maternal germ line mosaicism in another girl and her more severely affected and deceased brother. In vitro enzymatic assays for the novel, recurrent mutations p.(Arg83Cys) and p.(Phe128Leu) revealed reduced catalytic activity. X-inactivation was random in five females. The core phenotype of X-linked NAA10-related N-terminal-acetyltransferase deficiency in both males and females includes developmental delay, severe intellectual disability, postnatal growth failure with severe microcephaly, and skeletal or cardiac anomalies. Genotype–phenotype correlations within and between both genders are complex and may include various factors such as location and nature of mutations, enzymatic stability and activity, and X-inactivation in females

De novo TBR1 variants cause a neurocognitive phenotype with ID and autistic traits:report of 25 new individuals and review of the literature

TBR1, a T-box transcription factor expressed in the cerebral cortex, regulates the expression of several candidate genes for autism spectrum disorders (ASD). Although TBR1 has been reported as a high-confidence risk gene for ASD and intellectual disability (ID) in functional and clinical reports since 2011, TBR1 has only recently been recorded as a human disease gene in the OMIM database. Currently, the neurodevelopmental disorders and structural brain anomalies associated with TBR1 variants are not well characterized. Through international data sharing, we collected data from 25 unreported individuals and compared them with data from the literature. We evaluated structural brain anomalies in seven individuals by analysis of MRI images, and compared these with anomalies observed in TBR1 mutant mice. The phenotype included ID in all individuals, associated to autistic traits in 76% of them. No recognizable facial phenotype could be identified. MRI analysis revealed a reduction of the anterior commissure and suggested new features including dysplastic hippocampus and subtle neocortical dysgenesis. This report supports the role of TBR1 in ID associated with autistic traits and suggests new structural brain malformations in humans. We hope this work will help geneticists to interpret TBR1 variants and diagnose ASD probands

Effects of induced rumination on body dissatisfaction: Is there any difference between men and women?

BACKGROUND AND OBJECTIVES: Rumination is a factor in the development and maintenance of body dissatisfaction. However, no study has yet investigated the impact of the type of rumination on body image. The first aim of this study was to examine whether the induction of analytic-abstract vs. concrete-experiential rumination affects body dissatisfaction following an induction of negative body image. The second objective was to examine gender differences in these effects. METHODS: Following induction of negative body image, 102 university undergraduates were randomly assigned to one of three experimental conditions-distraction, concrete rumination or abstract rumination. RESULTS: As expected, there were significant main effects of gender and condition, and a significant interaction between gender and condition on change in body dissatisfaction. In women abstract rumination predicted the highest increase in body dissatisfaction, whereas concrete rumination predicted the highest increase in body dissatisfaction in men. LIMITATIONS: Given that our sample consisted of undergraduate students, our findings cannot be generalized to clinical sample suffering from eating disorder. CONCLUSIONS: The different types of rumination seem to impact differentially body dissatisfaction in men and women

Model of a Reversible heat Pump for Part Load Energy Based Optimization Design.

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Transforming a Diamagnetic Ordered Mesoporous Silica Monolith into a Room Temperature Permanent Magnet through Multiscale Control of the Magnetic Properties

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Water table height maps prediction from passive surface-wave dispersion using deep learning

International audienceMonitoring underground water reservoirs is challenging due to limited spatial and temporal observations. This study presents an innovative approach utilizing supervised deep learning (DL), specifically a multilayer perceptron (MLP), and continuous passive-Multichannel Analysis of Surface Waves (passive-MASW) for constructing 2D water table height maps. The study site, geologically well-constrained, features two 20-meter-deep piezometers and a permanent 2D geophone array capturing train-induced surface waves. For each point of the 2D array, dispersion curves (DCs), displaying Rayleigh-wave phase velocities (VR) across a frequency range of 5 to 50 Hz, have been computed each day between December 2022 and September 2023. In the present study, these DCs are sampled in wavelengths ranging from 4.5 to 10.5 m in order to focus the monitoring on the expected water table depths. All VR data around one of the two piezometers is used to train the MLP model. Water table heights are then predicted across the entire geophone array, generating daily 2D piezometric maps. Model's performance is tested through cross-validation and comparisons with water table data at the second piezometer. Model’s efficiency is quantified with the root-mean-square error (RMSE) and the coefficient of determination (R²). A R² is estimated above 80 % for data surrounding the training piezometer and above 55 % for data surrounding the test piezometer. Additionally, the RMSE is impressively low at 0.03 m at both piezometers. Results showcase the effectiveness of DL in generating predictions of water table heights from passive-MASW data. This research contributes to advancing our understanding of subsurface hydrological dynamics, providing a valuable tool for water resource management and environmental monitoring. The ability to predict 2D piezometric maps from a single piezometer is particularly noteworthy, offering a practical and efficient solution for monitoring water table variations across broader spatial extents

Physics-guided deep learning model for daily groundwater table maps estimation using passive surface-wave dispersion

International audienceMonitoring groundwater tables (GWTs) is challenging due to limited spatial and temporal observations. This study presents an innovative approach utilizing supervised deep learning, specifically a Multilayer Perceptron (MLP), and continuous passive-Multichannel Analysis of Surface Waves (passive-MASW) for constructing 2D GWT level maps. The study site, geologically well-constrained, features two 20-meter-deep piezometers and a permanent 2D geophone array capturing train-induced surface waves. For each point of the 2D array, dispersion curves (DCs), displaying Rayleigh-wave phase velocities (V_R) across a frequency range of 5 to 50 Hz, have been computed each day between December 2022 and September 2023. In the present study, these DCs are resampled in wavelengths ranging from 4 to 15~m in order to focus the monitoring on the expected GWT levels (between -1 and -5 m). Nine months of daily V_R data around one of the two piezometers is used to train the MLP model. GWT levels are then estimated across the entire geophone array, generating daily 2D GWT maps. Model’s performance is tested through cross-validation and comparisons with GWT level data at the second piezometer. Model’s efficiency is quantified with the root-mean-square error (RMSE) and the coefficient of determination (R²). The R² is estimated at 80% for data surrounding the training piezometer, and at 68% for data surrounding the test piezometer. Additionally, the RMSE is impressively low at 0.03 m at both piezometers. Results showcase the effectiveness of DL in estimating GWT level maps from passive-MASW data, offering a practical and efficient monitoring solution across broader spatial extents