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Similar Microsatellite Allelic Distribution Between Anopheles darlingi Population Collected by Human Landing Catch or Mosquito Magnet Traps in French Guiana
No full textInternational audienceAnopheles darlingi is a major malaria vector in South America. Understanding its population dynamics is critical for designing effective vector control strategies. While various Anopheles collection methods exist, they may sample distinct populations. Microsatellite genotyping across nine loci was performed to characterize An. darlingi populations, which were collected in French Guiana between 6:30 p.m. and 7:00 a.m. using human landing catch (HLC) or Mosquito Magnet ® (MM) traps. Traps were arranged in a 3 × 3 Latin square design to minimize possible effects of geographical position. Pairwise F ST index and discriminant analyses of principal components (DAPC) were used to make comparisons. A total of 431 An. darlingi were analyzed. No significant genetic differentiation was observed between collection methods or time slots (F ST values non-significant, p > 0.25), with DAPC revealing a single genetic cluster. Despite documented phenotypic variations, no significant population structure was detected among An. darlingi sampled in a rural village in French Guiana via collection methods or time slots. These findings confirm that mosquitoes collected with these various methods or time slots are suitable for the molecular studies of An. darlingi in French Guiana. In this context, Mosquito Magnet ® traps could also represent an alternative to the now controversial human landing catch
Development of Molecular Digital Twins Based on Ambient Ionization Mass Spectrometry Imaging for Application in Cancer Surgery
No full textSummary Cancer surgery is a fundamental component of oncology treatment, its quality significantly impacts patient outcomes, influencing both relapse rates and survival. However, achieving this customization is contingent upon early collection of robust molecular data during surgery, providing accurate information for diagnosis, prognosis, and delineating surgical margins. The introduction of digital twin (DT) technology has recently opened a new era of precision and effectiveness in cancer surgery. Expanding from its successful implementations in the industrial sector, DT concept has evolved into a highly promising breakthrough in healthcare. Therefore, our study goal is on creating DT by using accurate and high-throughput molecular data obtained through mass spectrometry imaging. We developed a machine-learning-based pipeline that allow to depict infiltration of cancer cells into normal tissue that offer precise delineation of tumor margins thanks to SpiderMass. This process also enables the prediction of relative presence of bacterial strains in tumoral and healthy mammary glands
Tissue organization and maturation on multi-scale curvatures of the intestinal epithelium mimicked with microfabrication tools: Intestinal epithelial cells under variable curved substrates
No full textInternational audienc
Structural basis of human Mediator recruitment by the phosphorylated transcription factor Elk-1
No full textInternational audienceOne function of Mediator complex subunit MED23 is to mediate transcriptional activation by the phosphorylated transcription factor Elk-1, in response to the Ras-MAPK signaling pathway. Using cryogenic electron microscopy, we solve a 3.0 Å structure of human MED23 complexed with the phosphorylated activation domain of Elk-1. Elk-1 binds to MED23 via a hydrophobic sequence PSIHFWSTLS P P containing one phosphorylated residue (S383 p ), which forms a tight turn around the central Phenylalanine. Binding of Elk-1 induces allosteric changes in MED23 that propagate to the opposite face of the subunit, resulting in the dynamic behavior of a 19-residue segment, which alters the molecular surface of MED23. We design a specific MED23 mutation (G382F) that disrupts Elk-1 binding and consequently impairs Elk-1-dependent serum-induced activation of target genes in the Ras-Raf-MEK-ERK signaling pathway. The structure provides molecular details and insights into a Mediator subunit-transcription factor interface
Towards site-specific information on PET degrading enzymes using NMR near operational temperature
No full textInternational audiencePETases are enzymes that can break down the poly-ethylene terephthalate (PET) polymer in its constituent building blocks. This enzymatic recycling process offers a sustainable solution for producing new, high-quality plastics from previously used materials. NMR spectroscopy can help in understanding and ultimately improving these enzymes but is always confronted with the lengthy step of acquisition and interpretation of triple resonance spectra for the spectral assignment. Here, we explore whether this step can be made more efficient by recording the spectra directly at high temperature, which simultaneously corresponds to more realistic working conditions for the enzyme. Taking the inactive variant of LCCICCG as an example, we compare spectral quality at 30°C and 50°C, and find that the latter condition greatly improves the Signal-to-Noise (S/N) ratio of the standard triple resonance spectra. Going up to 60°C, we show that pulse sequences mainly used for the assignment of intrinsically disordered proteins (IDPs) also become feasible. As a result, we present a methodology enabling exhaustive backbone assignment based on a minimal set of triple resonance spectra acquired and analysed in less than two weeks. The assignment process hence can be completed on a time scale comparable to crystallography, bringing NMR in a favourable position to contribute to bio-structural studies on this family of highly thermostable PETases
Evolution of Blood Innate Immune Cell Phenotypes Following SARS-CoV-2 Infection in Hospitalized Patients with COVID-19.
No full textInternational audienceInnate immune cells appear to have an important implication in the resolution and/or the aggravation of the COVID-19 pathogenesis after infection with SARS-CoV-2. To better appreciate the role of these cells during COVID-19, changes in blood eosinophil, the neutrophil and monocyte count, and levels of surface protein markers have been reported. However, analyses at several timepoints of multiple surface markers on granulocytes and monocytes over a period of one month after a SARS-CoV-2 infection are missing. Therefore, in this study, we performed blood eosinophil, neutrophil, and monocyte phenotyping using a list of surface proteins and flow cytometry during a period of 30 days after the hospitalization of patients with severe SARS-CoV-2 infections. Blood cell counts were reported at seven different timepoints over the 30-day period as well as measures of multiple mediators in serum using a targeted multiplex assay approach. Our results indicate a 95% drop in the blood eosinophil count by D1, with eosinophils displaying a phenotype defined as CD69/CD63/CD125high and CCR3/CD44low during the early phases of hospitalization. Conversely, by D7 the neutrophil count increased significantly and displayed an immature, activated, and immunosuppressive phenotype (i.e., 3% of CD10/CD16low and CD10lowCD177high, 6.7% of CD11bhighCD62Llow, and 1.6% of CD16highCD62Llow), corroborated by enhanced serum proteins that are markers of neutrophil activation. Finally, our results suggest a rapid recruitment of non-classical monocytes leaving CD163/CD64high and CD32low monocytes in circulation during the very early phase. In conclusion, our study reveals potential very early roles for eosinophils and monocytes in the pathogenesis of COVID-19 with a likely reprogramming of eosinophils in the bone marrow. The exact roles of the pro-inflammatory neutrophils and the functions of the eosinophils and the monocytes, as well as these innate immune cell types, interplays need to be further investigated
Diagnostic relevance of SH2B3 mutations in suspected myeloid malignancies and acute leukemia: insights from a large-scale NGS-based screening study
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Maternal high-fat diet during lactation reduces sialylated milk oligosaccharides and shapes early-life microbiota in rat offspring
No full textInternational audienceHuman milk oligosaccharides (HMOs) promote the development of the infant gut microbiota, notably through the growth of beneficial bacteria. However, the interaction between maternal diet, HMOs and the offspring's gut microbiota remains incompletely understood. We hypothesize that a high-fat (HF) diet influences the composition of HMOs and shapes gut microbiota in offspring. In lactating rat mothers fed with a HF or a low-fat (LF) diet, we measured at mid-lactation, the levels of milk sialylated oligosaccharides (SL-MOs) and the expression of enzymes for synthesizing SL-MOs in the mammary gland. In rat pups from LF or HF mothers, we analysed the caecal microbiota and measured levels of faecal short-chain fatty acids (SCFAs). In addition, in humans, we quantified 24 HMOs in the colostrum of lean and obese mothers. In rat mothers, HF feeding significantly reduced the breast milk 6′SL level but not the 3′SL one and increased the gene-expression level of the St3Gal1 enzyme in the mammary gland. In HF rat pups, the caecal microbiota was drastically modified with increases in α- and β-diversities as well as in the abundance of Parabacteroides and Lachnospiraceae. Levels of faecal SCFAs including acetate, butyrate, isobutyrate, valerate and isovalerate were also increased in HF pups. In humans, maternal obesity only slightly increased DFLNHa concentration in the colostrum. In conclusion, our data suggest that a hyperlipidic diet during lactation may reduce the level of sialylated oligosaccharides in breast milk and alter the abundance of several groups of bacteria in the infant's gut. We also demonstrated that, in humans, obesity did not highly affect levels of HMOs in the colostrum reinforcing previous findings suggesting that being overweight does not influence drastically the HMO profile in breast milk
Engaging Undergraduate Medical Students with Introductory Research Training via an Educational Escape Room: A Mixed-Methods Evaluation of Engagement and Perception.
No full textInternational audienceBackground: Early exposure to research methodology is essential in medical education, yet many students show limited motivation to engage with non-clinical content. Gamified strategies such as educational escape rooms (EERs) may help improve engagement, but few studies have explored their feasibility at scale or evaluated their impact beyond student satisfaction.Objective: To assess the feasibility, engagement, and perceived educational value of a large-scale escape room specifically designed to introduce third-year medical students to the principles of diagnostic test evaluation.Methods: We developed a low-cost immersive escape room based on a fictional diagnostic accuracy study, with six puzzles mapped to five predefined learning objectives: (1) identifying key components of a diagnostic study protocol, (2) selecting an appropriate gold-standard test, (3) defining a relevant study population, (4) building and interpreting a contingency table, and (5) critically appraising diagnostic metrics in context. The intervention was deployed to an entire class of third-year medical students across 12 sessions between March and April 2023. Each session included 60 minutes of gameplay and a 45-minute debriefing. Students completed pre-/post-intervention questionnaires assessing their knowledge of diagnostic test evaluation and perceptions of research training. Descriptive statistics and paired t-tests were used to evaluate score changes; univariate linear regressions assessed associations with demographics. Free-text comments were analyzed using Reinert's hierarchical classification.Results: Among 530 participants, 490 completed the full evaluation. Many participants had limited prior exposure to escape rooms (206/490, 42% had never participated), and most reported low initial confidence with critical appraisal of scientific articles. All student teams completed the scenario, with a mean completion time of 53 (±4) minutes. Mean overall knowledge scores increased from 62/100 (±1) before to 82/100 (±2) after the activity (+32%, p<0.001). Gains were observed across all learning objectives and were not influenced by age, sex, or prior experience. Students rated the EER as highly entertaining (9.1±1.1/10) and educational (8.2±1.5/10). Following the intervention, 87% (393/452) felt more comfortable with critical appraisal of diagnostic test studies, and 79% (357/452) considered the escape room format highly appropriate for an introductory session. Thematic analysis of open-ended feedback identified six clusters, including engagement, teamwork, and perceived usefulness of the pedagogical approach. Word clouds showed a marked shift from negative to positive attitudes toward research training.Conclusions: This study demonstrates the feasibility and enthusiastic reception of a large-scale, reusable escape room aimed at teaching the fundamental principles of diagnostic test evaluation to undergraduate medical students. While not designed to cover the broader spectrum of research designs or methods, the intervention successfully addressed targeted objectives within a specific area of research appraisal. This approach may serve as a valuable entry point to engage students with evidence-based reasoning and pave the way for deeper exploration of medical research methodology
Sparse factor analysis for categorical data with the group-sparse generalized singular value decomposition
No full textInternational audienceCorrespondence analysis, multiple correspondence analysis, and their discriminant counterparts (i.e., discriminant simple correspondence analysis and discriminant multiple correspondence analysis) are methods of choice for analyzing multivariate categorical data. In these methods, variables are integrated into optimal components computed as linear combinations whose weights are obtained from a generalized singular value decomposition (GSVD) that integrates specific metric constraints on the rows and columns of the original data matrix. The weights of the linear combinations are, in turn, used to interpret the components, and this interpretation is facilitated when components are 1) pairwise orthogonal and 2) when the values of the weights are either large or small but not intermediate—a configuration called a simple or a sparse structure. To obtain such simple configurations, the optimization problem solved by the GSVD is extended to include new constraints that implement component orthogonality and sparse weights. Because multiple correspondence analysis represents qualitative variables by a set of binary columns in the data matrix, an additional group constraint is added to the optimization problem in order to sparsify the whole set of columns representing one qualitative variable. This method—called group-sparse GSVD (gsGSVD)—integrates these constraints in a new algorithm via an iterative projection scheme onto the intersection of subspaces where each subspace implements a specific constraint. This algorithm is described in details, and we show how it can be adapted to the sparsification of simple and multiple correspondence analysis (as well as their barycentric discriminant analysis versions). This algorithm is illustrated with the analysis of four different data sets—each illustrating the sparsification of a particular CA-based method