dataesr/scientific-paragraphs-categorization huggingface dataset:
Results Taking into account what has been elaborated in the previous section, it can be concluded that any microneedle design process should include, at least in the early stages, a structural finite element analysis to characterize its mechanical resistance in order to ensure that no failure is going to occur during the insertion process. Further, this mechanical performance needs to be carefully analyzed to accurately predict the penetration efficiency of the MN patch to determine if the obtained value is suitable for the particular drug delivery or sample extraction application it has been intended for. With the aim of facilitating and automating the MN design process based on FEM simulation, a MATLAB tool has been developed following the workflow depicted in Figure  2. The first step consists of defining the structure for the MN.
Once the MN structure has been geometrically defined and correctly modeled, it is ready for FEM simulation. In our case, we have selected the aforementioned ANSYS Mechanical APDL environment to develop a basic static analysis where the insertion pressure of 3. 18 MPa is fixed as the main axial load. After retrieving the resulting stress data from this postprocessor module of the simulation, another structural analysis is configured for a subsequent simulation step: a linear buckling analysis. When ANSYS has finished both, the von Mises stresses and top displacements are retrieved and stored to display them on an appropriate panel of the designed MATLAB tool.
MATLAB Graphical User Interface (GUI) This MN design tool has been developed with the objective of minimizing the effort required not only to build an accurate-enough model of the structure for further FEM characterization but also to evaluate the importance of geometrical parameters on the mechanical strength of microneedles. In this subsection, the MATLAB-based tool is described, focusing on its features and graphical interface. An example of conical hollow MN has been chosen to better illustrate practical use of the different options provided by the tool. Figure  3  shows the main screen of the graphical interface of the program, divided in two sections. On the left, the configuration panel can be easily distinguished, with all its menus for definition of the model and generation of the batch file, ready for simulation.
In this case, the parameter can be manually established via a slider bar that has a default value of 400 µm, as can be seen in Figure  5. Moving down in the left side panel, the next two sliders permit the selection of the base and tip area of the MN. As the geometries included in the tool database are symmetrical in the X and Y axes, defining the area implies and automatic selection of the radius or side length. The first dimension that can be selected is the MN length or height, that has been limited between 100 μm and 1000 μm, which is an average range for microneedles intended for ISF sampling or drug delivery applications. In this case, the parameter can be manually established via a slider bar that has a default value of 400 μm, as can be seen in Figure  5. Moving down in the left side panel, the next two sliders permit the selection of the base and tip area of the MN.
As the geometries included in the tool database are symmetrical in the X and Y axes, defining the area implies and automatic selection of the radius or side length. The next slider bar permits choosing the meshing size, from 1 (not recommended for its inaccuracy) to 10 (longer computing time). Nevertheless, to deliver basic simulations and obtain preliminary results, a medium-low mesh size of 4 is selected by default. As this tool is intended for solid and hollow MN design, there are two additional slider bars for selection of the hole or bore dimension and position, as shown in Figure  3. The default value for all the topologies is a null bore radius; i. e. , a solid MN will be modeled if not specified otherwise. Definition of the limits for the slider that permits configuring the bore radius are linked with the value selected for the tip area in such a way that, in case of a centered hole (null offset), this will be circumscribed in the tip area.
With the exemption of the MN shape, the rest of the table cells are editable, permitting manual insertion of the values via keyboard and an automatic update of the bar positions. There is a summary table below the spinners and text field for selection of the array options (Figure  7 ), where all the aforementioned modelling parameters are included. With the exemption of the MN shape, the rest of the table cells are editable, permitting manual insertion of the values via keyboard and an automatic update of the bar positions. Once the whole structure of the MN has been configured, the "Generate Batch" button runs the MATLAB script that exports all the selected options to an ANSYS batch file including not only this dataset but also all the necessary instructions to run automatically both the static and linear buckling analyses.
When the button is pressed, the path of the subsequent batch file appears underneath, as shown in Figure  8 , so that the designer could check and execute separately its different modules if desired. Moreover, with the aim of facilitating and simplifying the simulation process, especially to non-expert users of AN-SYS, if both the MATLAB app and ANSYS program are going to run on the same computer, the tool provides the command lines to directly copy (via the "Copy" button), paste and run the FEM simulation. It is worth mentioning that, in this first stage of development of the tool, a material selection option is not provided. Silicon is the manufacturing material considered for all the designs, in such a way that its Young's modulus, yield stress, Poisson's factor and density are values included by default in the batch file for simulation.
Once the whole structure of the MN has been configured, the "Generate Batch" button runs the MATLAB script that exports all the selected options to an ANSYS batch file including not only this dataset but also all the necessary instructions to run automatically both the static and linear buckling analyses. When the button is pressed, the path of the subsequent batch file appears underneath, as shown in Figure  8 , so that the designer could check and execute separately its different modules if desired. Moreover, with the aim of facilitating and simplifying the simulation process, especially to non-expert users of ANSYS, if both the MATLAB app and ANSYS program are going to run on the same computer, the tool provides the command lines to directly copy (via the "Copy" button), paste and run the FEM simulation.
Once the whole structure of the MN has been configured, the "Generate Batch" button runs the MATLAB script that exports all the selected options to an ANSYS batch file including not only this dataset but also all the necessary instructions to run automatically both the static and linear buckling analyses. When the button is pressed, the path of the subsequent batch file appears underneath, as shown in Figure  8 , so that the designer could check and execute separately its different modules if desired. Moreover, with the aim of facilitating and simplifying the simulation process, especially to non-expert users of AN-SYS, if both the MATLAB app and ANSYS program are going to run on the same computer, the tool provides the command lines to directly copy (via the "Copy" button), paste and run the FEM simulation.
Our proposal provides not only that feature but also the additional possibility of exporting and automatically simulating the structure of the MN, including material properties and meshing options, together with loading and boundary conditions. In addition, our MATLAB tool collects the simulation results so that analytical and/or experimental results could be easily compared, taking advantage of the high computing capacity of MATLAB software. Another advantage of utilizing the proposed design tool is developing a dynamic simulation of the insertion process by combining the generated model for the microneedle or array with a previously created model of the skin. However, one of the fields of future work that have been foreseen is integrating two selecTable 3D models for the skin among the simulation options.
In this way, a correct performance could be ensured before considering any future extension. For that reason, only those topologies that present symmetry in both the X and Y axis and a single height parameter were chosen for the current version. Therefore, all of them can be modeled on the basis of only three values, corresponding to the height and the tip and base areas. Among the most common topologies that can be found in the literature, the tapered-cone and the cylinder with beveled tip would be the next geometries selected to be included in the database of the tool. From the point of view of programming requirements, they are relatively easy structures to be modeled, but they would need additional configuration parameters, such as the height of the base cylinder and the tip angle, respectively.
Conclusions This paper presents a detailed review of the latest published proposals where an FEMbased analysis on microneedles has been included. The purpose of this 5-year review was establishing the minimum set of features needed for a software tool intended for automation of a common microneedle design process based on mechanical characterization. This objective has been successfully achieved by developing a MATLAB design tool that permits definition of CAD models for commonly used microneedle geometries. Additionally, the proposal provides the additional feature of automated exportation of the MN structure and direct simulation by an FEM-based software of basic static and linear buckling analyses. In order for this simulation to be performed, the batch file generated by the tool for FEM analysis includes significant data, such as MN dimensions, material properties, meshing and loading options and boundary conditions.
Acknowledgements Financial support from the  CNRS  and the  Agence Nationale de la Recherche  ( ANR-JCJC-2020-CDI-DEOX ) is gratefully acknowledged. Y. Y and R. T thanks the the  CSC (China Scholarship Council)  for a doctoral fellowship. Y. Y thank  Alexis Taponard  ( ICBMS Lyon ) for assistance for CV measurements.
/Diabetology (London, UK) Hypoparathyroidism PEs Salmon calcitonin (Phase III: NCT00959764) Tarsa Therapeutics (Philadelphia, PA, USA) Osteoporosis, Postmenopausal pH modulator Leuprolide (Phase II: NCT05096065) Enteris Biopharm (Boonton, NJ, USA) Endometriosis PE, pH modulator, and enzyme inhibitor.
Backgrounds: The Covid-19 pandemic offered a unique opportunity to investigate trends in hospitalizations related to psychoactive substance intoxication, since the usual health burden of social use at parties and gatherings was likely to be decreased during lockdowns and curfew periods. Since young adults are the main users of psychoactive substances for experimental and recreational purposes, this study identified and compared hospitalization trends in young adults and adults over 30 years old. Methods: This national cohort study was conducted using the French hospital discharge database. An interrupted time-series analysis for the period between 2014 and 2020 was performed in two groups: young (age 18-29) and other adults (30 + ) to ascertain the trends in the monthly incidence of hospitalization related to psychoactive substance intoxication (opiates, cocaine, benzodiazepines, psychostimulants, alcohol and cannabis).
Data source This study was conducted by using the French national database of the Programme de Médicalisation des Systems d'Information (PMSI). The PMSI initially served to analyze hospital activity and assist in the planning of healthcare. Since 2004, it has been used for health resource allocation with the implementation of activity-based funding policy estimates. Although not initially designed for epidemiologic research, it was rapidly considered as an important source of information on hospitalizations and has been used in various studies  ( Daveluy et al. , 2012 ; de Léotoing et al. , 2018 ). The PMSI database contains administrative (age, sex, unique patient identifier) and medical information through diagnostic codes according to the 10th revision of the World Health Organization International Classification of Diseases (ICD-10), adapted for the PMSI as primary diagnoses (the reason why the patient was admitted to hospital) and the associated significant diagnoses (complications and morbidities that could have an impact on the course of the hospitalization)  ( Quan et al.
Study design and study population This national historic cohort study included all patients aged 18 years and over and hospitalized in France for psychoactive substance intoxication with a discharge date between 1st January 2014 and 31st December 2020. Stays of interest, i. e. admission (including short stays in emergency departments) and not just presentation to the hospital, were identified through the main or significant associated diagnoses coded in the PMSI database that referred to intoxication by opiates (T403, T401, T402, F110, T404), cocaine (T405, F140), benzodiazepines (T424), psychostimulants (T436), alcohol (F100, T51) and cannabis (F12). Benzodiazepines were considered as they are often misused with or without other substances  ( O'brien, 2005 ; Votaw et al. , 2019 ). As the focus was on stays, it was not necessary to handle duplicate patients for this analysis.
Statistical analyses Monthly incidence of hospitalizations that occurred in the context of psychoactive substance intoxication was computed over the years 2014 to 2020. An interrupted time-series analysis  ( Mathieu et al. , 2022 )  was performed in each group to ascertain whether trends in the monthly incidence of these hospitalizations changed during the lockdowns. We used the Unobserved Components Model to predict the monthly incidence of hospitalizations associated with psychoactive substance intoxication in 2020 on the basis of the monthly incidences observed over the previous years (2014 to 2019). The prediction was compared to monthly incidences that were really observed during the pandemic (from 2020/01/01 -2020/10/30), using SAS 9. 4 PROC UCM Software®. The six years of anteriority guaranteed a robust prediction of the model.
Limitations and strengths This is the first study to assess the nationwide impact of the COVID-19 pandemic on hospitalizations for acute psychoactive substance intoxication according to age. A particular strength is the monitoring of the incidence of hospitalization, which provides an appraisal of the impact of psychoactive substance use on healthcare. Data was collected by using a national hospital database, which provided a large sample size and inclusion of the general population. However, psychiatric hospitalization data was not included, so the harmful effects of psychoactive substance use may have been underestimated. In addition, an inherent limitation of the codes used is the lack of precision and the risk of formulation errors. For example, more precise information for benzodiazepines would have thrown light on their involvement in suicide attempts.
The sources of psychoactive substances were unknown, and there was no specific information on prescribed medication. Motivations and contexts of psychoactive substance use were not recorded in the database. Finally, during the lockdowns and the pandemic period, people avoided going to hospital as they were afraid of contracting the virus  ( Frank, 2022 ; Morgand et al. , 2022 ). Hence, the study may have underestimated the monthly incidence of severe psychoactive substance intoxication over this period. However, patients with acute psychoactive substance intoxication and without hospitalization were less likely to present with severe conditions.
Data analysis Raw data files from DESI-and MALDI-MSI experiments were converted to imzML files  (Schramm et al. , 2012)  using the "RAW + UDP to IMZML" software (v1. 6R170; TransMIT, Bremen, Germany), and MS images were generated using MSiReader v1. 01  (Bokhart et al. , 2018)  using a mass tolerance of 5 ppm. All MS images were normalized to the Total Ion Current (TIC) and the color scale was adjusted to provide the best possible representation of the compounds of interest. Every MS image of reserpine, rescinamine and their intermediates are summed images of m/z values corresponding to the protonated analytes as well as their sodium and potassium adducts (Table  1 ). Two primary metabolites, phosphatidylcholine 34:2 (PC (34:2)) ([C 42 H 80 NO 8 P + K] + , m/z 796. 52532) and di-hexose ([C 12 H 22 O 11 + K] + , m/z 381.
Acknowledgements This research was funded by the  EU   Horizon 2020 research and innovation program  ( MIAMi  project grant agreement No. 814645 ). Support for MALDI imaging instrumentation from the  Carlsberg Foundation  and The  Danish Council for Independent Research|Medical Sciences  (grant no. DFF -4002-00391 ) is gratefully acknowledged. Illustrations were drawn by  Debbie Maizels ,  Zoobotanica Scientific Illustration. N. B. was supported by a grant from the  VILLUM Foundation, Denmark  (grant no. 19151 ).
Screening Data Processing Different plasma samples spiked with the 53 selected compounds at the concentration of 200 µg L -1 as well as a blank plasma sample were prepared and analysed (n = 6). Different data processing parameters were studied in order to detect all the compounds in the spiked plasma samples and none in the blank sample. Concerning the identification criteria, the first two major criteria tested were the presence of the high-resolution precursor ion mass and the isotopic pattern. The main limitation of this setting was the inability to discriminate isomeric compounds, such as 6-monoacetylmorphine and naloxone, morphine and norcodeine, O-demethylvenlafaxine, and tramadol. To overcome this problem, a DDA acquisition was set up. In DDA mode, in the first step, the mass spectrometer selected the most intense ions; then, in a second step, they were fragmented and analysed.
Screening Data Processing TraceFinder Forensic 5. 1 was used for LC-MS control, library management, acquisition, and processing. Precursor peaks (m/z) were detected with a minimal ratio signal-to-noise threshold of 10 a. u. and a mass tolerance of 5 parts per million (ppm); retention time, fragment ions, isotopic pattern, and library search were selected for confirmation as follows: for retention time, the option "ignore if not defined" was selected, and window override was 60 s; -for isotopic pattern, the fit threshold was 70 a. u. , with a mass tolerance of 5 ppm and an intensity deviation tolerance of 30%; -for fragment ions, the option "ignore if not defined" was selected, the minimum number of fragments was one, the intensity threshold was 5000 a. u. , the product mass tolerance was 10 mmu, and the MS order was MS 2 ; -for general library NIST settings, MS order was MS 2 and isolation width was used; for the NIST setting, search type selected was MS/MS, and options "ignore precursor", "use all peak matching", "reverse search", and presearch "off" were selected; a probability threshold of 10 a.
Conclusions In this work, we described the development and validation of a large-scale HRMS toxicology screening on both whole blood and plasma. The method acquisition used was a full-scan DDA with an inclusion list of more than 1000 compounds. Sample work-up consisted of a straightforward deproteinisation with only 100 µL of plasma or whole blood. Validation was carried out according to international guidelines and the current literature. This new test is now successfully applied to routine clinical and forensic toxicology analyses. In the coming future, further development and validation of this assay will be performed in urine and other matrices. In addition, the data acquisition can be adapted to allow for the detection of new unknown compounds such as synthetic cannabinoids by using Compound Discoverer (ThermoFisher Scientific, San Jose, CA, USA).
General Experimental Procedures HRESIMS measurements used an Agilent 6546 Accurate-Mass Q-TOF, hyphenated with a 1290 Agilent Infinity II LC system (Agilent, Palo Alto, CA, USA). The chromatographic system was fitted with a Zorbax RRHD Eclipse Plus C18 column (2. 1 × 50 mm, 1. 8 μm). 1 H and 13 C NMR data were recorded on an AM-500 (500 MHz) Bruker 700 MHz NMR.
General Experimental Procedures HRESIMS measurements used an Agilent 6546 Accurate-Mass Q-TOF, hyphenated with a 1290 Agilent Infinity II LC system (Agilent, Palo Alto, CA, USA). The chromatographic system was fitted with a Zorbax RRHD Eclipse Plus C 18 column (2. 1 × 50 mm, 1. 8 µm). 1 H and 13 C NMR data were recorded on an AM-500 (500 MHz) Bruker 700 MHz NMR spectrometer (Bruker Daltonics, Bremen, Germany) using TFA-d or DMSO-d 6 as solvent (Euriso-Top, Saint-Aubin, France). Pandamine  (1). White amorphous solid; mp = 256.
Consistent with previously related published X-ray structures, the p-phencyclopeptine nucleus of pandamine adopts the trans, trans configuration in the crystal, which is related to the geometry of the two amides, with the carbonyls pointing towards opposite sides of the macrocycle (Figure  S15D ). Single-crystal X-ray diffraction data, data collection and structure refinement details are summarized in Table  S1. Crystallographic data for structure 1 have been deposited in the Cambridge Crystallographic Data Centre database (deposition number CCDC 2235441). Copies of the data can be obtained free of charge from the CCDC at www. ccdc. cam. ac. uk (accessed on 15 February 2023).
Acknowledgments: This study was supported by a sponsorship from  Université Paris-Saclay  and  CNRS. The authors are indebted to  Marc Litaudon  for having kindly provided the full-text of references 1 and 2. The authors gratefully acknowledge  Solenn Ferron  (ISCR,  UMR CNRS 6226 ,  Université de Rennes) ,  Guillaume Bernadat  and  Mehdi Beniddir (BioCIS ,  UMR CNRS 8076 ,  Université Paris-Saclay ) for fruitful discussion.
Drug release monitored by TDA Drug saturated SEDDS preconcentrates were prepared as described in section 2. 4. After 24 h, preconcentrates were diluted 100-fold with demineralized water at 37 • C, vortexed and immediately placed in the capillary electrophoresis instrument's carrousel at 37 • C for imminent injection to get the t incubation = 0 h TDA data point. The TDA experimental setup was the same as described in section 2. 3. 3. The drug release was followed by UV detection at 375 nm for quercetin and 420 nm for curcumin for 24 h. The experimental peak area, proportional to the injected amount of soluble drug, was measured by peak integration and the average hydrodynamic diameter was calculated for each run as described in the previous TDA section. Each sample was mobilized by the corresponding formulation without the model drug in a dilution of 1:100.
Acknowledgements The  Centre for International Cooperation and Mobility (ICM)  of the  Austrian Agency for Education and Internationalisation (OeAD-GmbH)  has selected this project for support (Project No  FR 13/2020 ). The financial support was provided by the  Federal Ministry of Education, Science and Research (BMBWF). The authors would like to acknowledge this support as well as the support of the  French Ministry of Foreign Affairs (MAEE)  and the  French Ministry for Higher Education and Research (MESR)  (Project  PHC AMADEUS 2020 N • 44090VA ). A. M. Jörgensen  received a doctoral scholarship for the promotion of young researchers at the  Leopold-Franzens-University Innsbruck.