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Abstract Here, we present a new method for evaluating questions on chemical reactions in the context of remote education. This method can be used when binary grading is not sufficient as some tolerance may be acceptable. In order to determine a grade, the developed workflow uses the pairwise similarity assessment of two considered reactions, each encoded by a single molecular graph with the help of the Condensed Graph of Reaction (CGR) approach. This workflow is part of the ChemMoodle project and is implemented as a Moodle Plugin. It uses the Chemdoodle engine for reaction drawing and visualization and communicates with a REST server calculating the similarity score using ISIDA fragment descriptors. The plugin is open-source, accessible in GitHub ( https://github.com/Laboratoire-de-Chemoinformatique/moodle-qtype_reacsimilarity ) and on the Moodle plugin store ( https://moodle.org/plugins/qtype_reacsimilarity?lang=en ). Both similarity measures and fragmentation can be configured. Scientific contribution This work introduces an open-source method for evaluating chemical reaction questions within Moodle using the CGR approach. Our contribution provides a nuanced grading mechanism that accommodates acceptable tolerances in reaction assessments, enhancing the accuracy and flexibility of the grading process.

Using two independent speckle imaging systems based on the recently published LSOCI method operating in contact mode on the skin, we assess the reproducibility of in vivo measurements and conduct an inter-instrument comparison. To this aim, we propose a calibration method to handle each imaging system as a comprehensive unit, which includes the laser source, optics, and camera. Key to our method is the introduction of a new index that quantifies the departure of the temporal contrast observed in vivo from the spatial contrast scattered from a reference static element generating a circular Gaussian speckle field. Using such near-real-time calibration method, we demonstrate that the microcirculation images produced by 2 different instruments exhibit high accuracy and stability, with microcirculation activity values in excellent agreement, thereby paving the way for clinical applications.

Abstract Background DNA methylation (DNAm) plays an important role in lipid metabolism, however, no epigenome-wide association study (EWAS) of lipid levels has been conducted among childhood cancer survivors. Here, we performed EWAS analysis with longitudinally collected blood lipid data from survivors in the St. Jude lifetime cohort study. Methods Among 2052 childhood cancer survivors of European ancestry (EA) and 370 survivors of African ancestry (AA), four types of blood lipids, including high-density lipoprotein (HDL), low-density lipoprotein (LDL), total cholesterol (TC), and triglycerides (TG), were measured during follow-up beyond 5-years from childhood cancer diagnosis. For the exposure EWAS (i.e., lipids measured before blood draw for DNAm), the DNAm level was an outcome variable and each of the blood lipid level was an exposure variable; vice versa for the outcome EWAS (i.e., lipids measured after blood draw for DNAm). Results Among EA survivors, we identified 43 lipid-associated CpGs in the HDL (n = 7), TC (n = 3), and TG (n = 33) exposure EWAS, and 106 lipid-associated CpGs in the HDL (n = 5), LDL (n = 3), TC (n = 4), and TG (n = 94) outcome EWAS. Among AA survivors, we identified 15 lipid-associated CpGs in TG exposure (n = 6), HDL (n = 1), LDL (n = 1), TG (n = 5) and TC (n = 2) outcome EWAS with epigenome-wide significance (P 70%) between EA and AA survivors, highlighting differences in DNAm markers of blood lipids between populations with diverse genetic ancestry. Ten lipid-associated CpGs were cis-expression quantitative trait methylation with their DNAm levels associated with the expression of corresponding genes, out of which seven were negatively associated. Conclusions We identified distinct signatures of DNAm for blood lipids as exposures or outcomes and between EA and AA survivors, revealing additional genes involved in lipid metabolism and potential novel targets for controlling blood lipids in childhood cancer survivors.

Abstract We report a novel approach for grading chemical structure drawings for remote teaching, integrated into the Moodle platform. Typically, existing online platforms use a binary grading system, which often fails to give a nuanced evaluation of the answers given by the students. Therefore, such platforms are unevenly adapted to different disciplines. This is particularly true in the case of chemical structures, where most questions simply cannot be evaluated on a true/false basis. Specifically, a strict comparison of candidate and expected chemical structures is not sufficient when some tolerance is deemed acceptable. To overcome this limitation, we have developed a grading workflow based on the pairwise similarity score of two considered chemical structures. This workflow is implemented as a Moodle plugin, using the Chemdoodle engine for drawing structures and communicating with a REST server to compute the similarity score using molecular descriptors. The plugin ( https://github.com/Laboratoire-de-Chemoinformatique/moodle-qtype_molsimilarity ) is easily adaptable to any academic user; both embedding and similarity measures can be configured.

This paper proposes to use methods for compressing the temporal profiles of Sentinel-1 images, in order to be able to evaluate and analyze the richness of the temporal dynamics, both on a glacier and on a watershed. We propose to use unsupervised deep learning to auto-encode the temporal information in 3 dimensions, allowing to use the three descriptors as three RGB components to produce a colored composition synthesizing the information. We compare this Convolutional AutoEncoder (CAE) approach with a dimensionality reduction based on a Principal Component Analysis (PCA) of the temporal profiles. The two methods, CAE and PCA, are applied to a time series over the Kyagar Glacier before and after a surge event, and on an alpine watershed to compare the differences in dynamic evolution associated with different terrain classes with and without snow. On the one hand, on the glacier, the stacks of 10 images used are too short for CAE to extract more than two really significant axes. On the other hand, with longer profiles available over the alpine watershed, the CAE is interesting to improve the clustering results obtained from the decomposition.

Using two independent speckle imaging systems based on the recently published LSOCI method operating in contact mode on the skin, we assess the reproducibility of in vivo measurements and conduct an inter-instrument comparison. To this aim, we propose a calibration method to handle each imaging system as a comprehensive unit, which includes the laser source, optics, and camera. Key to our method is the introduction of a new index that quantifies the departure of the temporal contrast observed in vivo from the spatial contrast scattered from a reference static element generating a circular Gaussian speckle field. Using such near-real-time calibration method, we demonstrate that the microcirculation images produced by 2 different instruments exhibit high accuracy and stability, with microcirculation activity values in excellent agreement, thereby paving the way for clinical applications. [ABSTRACT FROM AUTHOR]

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