Master’s Degree in Health Data Science: Implementation and Assessment After Five Years

International audienceHealth data science is an emerging discipline that bridges computer science, statistics and health domain knowledge. This consists of taking advantage of the large volume of data, often complex, to extract information to improve decision-making. We have created a Master’s degree in Health Data Science to meet the growing need for data scientists in companies and institutions. The training offers, over two years, courses covering computer science, mathematics and statistics, health and biology. With more than 60 professors and lecturers, a total of 835 hours of classes (not including the mandatory 5 months of internship per year), this curriculum has enrolled a total of 53 students today. The feedback from the students and alumni allowed us identifying new needs in terms of training, which may help us to adapt the program for the coming academic years. In particular, we will offer an additional module covering data management, from the edition of the clinical report form to the implementation of a data warehouse with an ETL process. Git and application lifecycle management will be included in programming courses or multidisciplinary projects

Master’s Degree in Health Data Science: Implementation and Assessment After Five Years

International audienceHealth data science is an emerging discipline that bridges computer science, statistics and health domain knowledge. This consists of taking advantage of the large volume of data, often complex, to extract information to improve decision-making. We have created a Master’s degree in Health Data Science to meet the growing need for data scientists in companies and institutions. The training offers, over two years, courses covering computer science, mathematics and statistics, health and biology. With more than 60 professors and lecturers, a total of 835 hours of classes (not including the mandatory 5 months of internship per year), this curriculum has enrolled a total of 53 students today. The feedback from the students and alumni allowed us identifying new needs in terms of training, which may help us to adapt the program for the coming academic years. In particular, we will offer an additional module covering data management, from the edition of the clinical report form to the implementation of a data warehouse with an ETL process. Git and application lifecycle management will be included in programming courses or multidisciplinary projects

Standardized Description of the Feature Extraction Process to Transform Raw Data Into Meaningful Information for Enhancing Data Reuse: Consensus Study

International audienceBackground Despite the many opportunities data reuse offers, its implementation presents many difficulties, and raw data cannot be reused directly. Information is not always directly available in the source database and needs to be computed afterwards with raw data for defining an algorithm. Objective The main purpose of this article is to present a standardized description of the steps and transformations required during the feature extraction process when conducting retrospective observational studies. A secondary objective is to identify how the features could be stored in the schema of a data warehouse. Methods This study involved the following 3 main steps: (1) the collection of relevant study cases related to feature extraction and based on the automatic and secondary use of data; (2) the standardized description of raw data, steps, and transformations, which were common to the study cases; and (3) the identification of an appropriate table to store the features in the Observation Medical Outcomes Partnership (OMOP) common data model (CDM). Results We interviewed 10 researchers from 3 French university hospitals and a national institution, who were involved in 8 retrospective and observational studies. Based on these studies, 2 states (track and feature) and 2 transformations (track definition and track aggregation) emerged. “Track” is a time-dependent signal or period of interest, defined by a statistical unit, a value, and 2 milestones (a start event and an end event). “Feature” is time-independent high-level information with dimensionality identical to the statistical unit of the study, defined by a label and a value. The time dimension has become implicit in the value or name of the variable. We propose the 2 tables “TRACK” and “FEATURE” to store variables obtained in feature extraction and extend the OMOP CDM. Conclusions We propose a standardized description of the feature extraction process. The process combined the 2 steps of track definition and track aggregation. By dividing the feature extraction into these 2 steps, difficulty was managed during track definition. The standardization of tracks requires great expertise with regard to the data, but allows the application of an infinite number of complex transformations. On the contrary, track aggregation is a very simple operation with a finite number of possibilities. A complete description of these steps could enhance the reproducibility of retrospective studies

DEET potentiates the carbamate-induced anticholinesterase effect in insect DUM neurons.

<p>A) Dorsal view <i>camera lucida</i> drawing of typical DUM neuron morphology revealed by anterograde cobalt staining performed on a soma located along the midline of the cockroach terminal abdominal ganglion (TAG) of the nerve cord. A, anterior; P, posterior; scale bar 120μm. B) Light micrograph of the whole cell patch-clamp technique adapted on the isolated DUM neuron cell body obtained after enzymatic digestion and mechanical dissociation of the TAG. C) Anticholinesterase effects of the carbamate, propoxur, the anticholinesterase compound BW284c51 and the repellent DEET on the duration of the ACh-induced inward currents (measured at 50% of the maximum current amplitudes) obtained in whole-cell voltage-clamp at a steady-state holding potential of -50 mV. D) Comparative bar graph summarizing the anticholinesterase effect of the specific inhibitor BW284c51 (100nM) and the carbamate, propoxur (prop) (100nM) measured on the duration of the ACh-induced inward currents (measured at 50% of the maximum current amplitudes) obtained in whole-cell voltage-clamp at a steady-state holding potential of -50 mV. E) Concentration-dependent inhibition of the residual AChE activity determined spectrophotometrically induced by propoxur and expressed as percentage of initial activity (i. e., without propoxur). The curve represents the best fit to the data points according to the Hill equation yielding the corresponding IC₅₀ (i.e., the concentration of propoxur that produces 50% inhibition of the AChE enzymatic activity) as illustrated in the comparative bar graph shown <i>in inset</i>. This indicates that isolated DUM neurons express functional AChE. F) Bar graph summarizing the unexpected concentration-dependent effect of DEET on the ACh-induced inward current duration. At low concentration (10nM), DEET produces a more important anticholinesterase effect than those observed with higher concentrations (i.e., 100nM and 1μM). By contrast, DEET (1μM) do not produce any effect on the carbachol(CCh)-induced current. G) Comparative bar graph illustrating the anticholinesterase effects of DEET (10nM) and propoxur (100nM) tested alone and in combination (DEET/propoxur). Pretreatment of DUM neuron with low concentration of DEET (10nM), for 15 minutes, strongly potentiates the propoxur-induced anticholinesterase effect. H) Comparative bar graph showing that synergistic effect between DEET and propoxur is only observed at low concentration of DEET (i. e., 10nM) and not with higher concentration (i. e., 1μM). I) Semi-logarithmic concentration-response curves for the anticholinesterase effect induced by propoxur applied alone and in the presence of 10nM DEET. The sigmoid curves represent the best fit to the mean data points according to the Hill equation yielding the corresponding IC₅₀ of 2.10^-8M and 6.10^-8M estimated for DEET and propoxur applied in combination and for propoxur applied alone, respectively. Number of experiments varies from 10 to 16 cells. Data are means ± S.E.M. ** and ***, values significantly different, <i>p</i> < 0.01 and <i>p</i><0.001, respectively; ns, not significant (<i>p</i> > 0.05).</p

Synergism between DEET and propoxur occurs through a positive allosteric-like modulation of insect M1/M3 muscarinic receptors and intracellular calcium-dependent signaling pathways.

<p>A) Bath application of 10nM DEET increases intracellular free calcium concentration ([Ca²⁺]_i) in Fura-2 loaded DUM neurons (<i>inset</i> 2). Note that, under control condition, calcium spark-like events are detected (<i>inset</i> 1). B) Pretreatment with 1μM atropine, a specific antagonist of muscarinic receptors (mAChRs), completely blocks the enhancement of [Ca²⁺]_i produced by 10nM DEET, indicating the involvement of mAChRs. C) Bar graph summarizing the inhibitory effect of M1 and M3 mAChR antagonists pirenzepine (PZP) and 4-DAMP, respectively, on the synergism between DEET and propoxur. D) Bar graph illustrating that TMB-8 (100μM) also completely blocks the synergism between DEET and propoxur. E,F) Characterization of the intracellular calcium-dependent molecular events involved in the synergistic action of DEET on the propoxur-induced anticholinesterase effect. Intracellular application of 0.5mM W7, the calmodulin inhibitor and 50nM calmodulin (CaM) inhibit the positive potentiating effect of DEET on the toxic activity of propoxur. By contrast, KN-62 (10μM), which binds to CaM kinase II and blocks its activation by calmodulin, does not produce any effect (E). If pretreatment with 10μM of U73122, an inhibitor of PI-PLC known to regulate AChE activity, partially counteracts the effect of 0.5mM W7, application of the PI-PLC activator, <i>m</i>-3M3FBS (10μM) produces similar inhibition of the synergism between DEET and propoxur to that of observed with W7 tested alone (F). G) Modulation of the maximum amplitude of muscarine-elicited currents <i>versus</i> the concentration of DEET applied. The limited window of DEET concentration within which a maximum response potentiating effect is observed, is around 10nM (G). For higher DEET concentrations, the sensitizing effect is counteracted and eventually outweighed by an inhibitory action of DEET. Inset illustrates the semi-logarithmic dose-response curve for the muscarine-induced current applied by pressure ejection. Arrow indicates that the maximum current amplitude is obtained for pressure ejection duration of 500ms. H) DEET induces a transient concentration-dependent [Ca²⁺]i rise in Fura-2-loaded DUM neuron cell bodies. The changes in [Ca²⁺]_i response amplitudes and the window of concentrations for DEET action were very similar with those illustrated in 2G. <b>(I)</b> Bath application of MT-7 (30nM), which is known to bind on M1 mAChR allosteric site, partially reversed the inhibitory effect observed for high concentration of DEET. Number of experiments varies from 8 to 13 cells. Data are means ± S.E.M. *, ** and ***, values significantly different, <i>p</i> < 0.05, <i>p</i> < 0.01 and <i>p</i> < 0.001, respectively. ns, not significant (<i>p</i> > 0.05). Scale bar: 20μm.</p

Orthosteric and allosteric binding sites of mammal M1 and M3 muscarinic receptors.

<p>In all panels, the M1 and M3 mAChRs orthosteric and allosteric binding sites are shown with the ligand DEET in green. Residues observed in vicinity of DEET in M1 mAChR orthosteric site (A) and allosteric region (B) and in M3 mAChR orthosteric site (C) and allosteric site (D) are shown in licorice representations. The following colour coding for transmembrane helices used: TM1—orange, TM2—green, TM3—dark blue, TM4—yellow, TM5—red, TM6—magenta, TM7—light blue.</p

DEET interacts with mammal M1 and M3 muscarinic receptors.

<p>The functional properties of DEET are investigated using CHO cells expressing human M1 (hM1) and M3 (hM3) mAChR subtypes. A) Dose-dependent inhibition of [³H]-NMS binding to M1 and M3 human muscarinic ACh receptor (mAChR) subtypes by DEET. The results are expressed as the ratio of the specific [³H]-NMS binding measured with (B) or without DEET (Bo). B-C) Signals acquired for calcium fluorescence after the addition at 20 sec of carbamylcholine (CCh) (300nM) and DEET (1mM) on CHO-hM1 cells (n = 3). DEET inhibition of the Ca²⁺ mobilization after pretreatment of the cells with increasing concentrations of DEET (3nM to 3 mM), followed by a sub-maximal concentration of CCh (100 nM) (C). D-E) <i>in silico</i> Docking of DEET into human M1 and rat M3 mAChRs. The two binding regions (allosteric and orthosteric sites) of DEET molecules (green) in human M1 mAChR are represented (D). In red are shown residues of a M1 mAChR monomer interacting with MT-7 loops previously indentified. Analogous interaction residues from the second M1 mAChR monomer are indicated in blue (D) close to the hypothetical M1 mAChR allosteric site occupied by DEET. The <i>in silico</i> docking results to rat M3 mAChR crystal structure 4DAJ (E) also show that DEET binds on two distinct sites (allosteric and orthosteric sites). Ten DEET poses from each group located in both sites are shown in green. The following colour coding for transmembrane helices used: TM1—orange, TM2—green, TM3—dark blue, TM4—yellow, TM5—red, TM6—magenta, TM7—light blue. ECL, extracellular loop.</p