dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical Design of Experiment (DoE) for Baicalin Glucosylation Optimization A Central-Composite-Face-Centered (CCF) design was applied to optimize the yield and the total glucoside content during the α-glucosylation of baicalin with CGTase. Modde ® Go 13. 0. 1 software (Sartorius, Aubagne, France) allowed us to design and analyze the CCF. Table  5  presents the variables and the levels employed, and Table  2  describes factors' values for each experiment. CGTase volume is expressed in % (v/v) of commercial preparation in the reaction medium. The volume was set at 15 mL and duration at 16 h to ensure stabilization of the glucosylation reaction. Two responses were studied: total baicalin glucoside content (mM) and molar yield expressed as baicalin glucoside content/initial baicalin concentration.
Thermal Performance Curves The relationship between developmental rate and temperature is usually characterized using experimental data. These data are obtained through experiments in which individuals or groups of individuals are reared at constant temperatures, and the time taken to reach a given life stage is measured. In this study, data on mean development times at different constant temperatures were manually extracted from published studies. Table  1  describes the references from which the data were extracted, together with the experimental designs of each study (i. e. , the species considered, the region where the insects were sampled, the temperatures tested, and the life stages). Because development time for each larval instar was not described separately in all studies, we pooled the developmental times of the larval stage into one life stage to approximate the development time of the complete larval stage.
However, we checked the absence of a study effect on mean development rates in each study with ANOVAs for the four species to verify that we were able to relate development rate to temperature for each life stage of the four species, and predict individual development times at different constant temperatures. Three development rate models were selected overall from the eleven based on AIC and biological assumptions (briere1_99, kontodimas_04, and perf2_11; Table  3 ). Among the eleven fits, no models were excluded based on an AIC difference higher than 10, suggesting no important differences in goodness-of-fit between model adjustments. We selected adjustments with ∆ AIC ≤ 2. The best models were then selected after discarding models with outliers in thermal thresholds. Complete descriptions of AIC and biological trait values are available on a GitHub repository (https://github.
Temperature Scenarios To study the impact of global warming on pest development, we retrieved temperature data to quantify development rates in current and future conditions, using the development models. We retrieved temperature data from the IPCC Working Group I Interactive Atlas  [79, 80] , which provides the mean monthly temperatures predicted by multiple global circulation models (GCM) for historical climate  (35 GCMs)  and two scenarios for the future, SSP1-2. 6 (32 GCMs) and SSP5-8. 5 (34 GCMs). SSP1-2. 6 is a scenario whereby global warming remains below 2 °C relatively to 1850-1900, with zero net CO 2 emissions after 2050, and is described as a low-emission reference scenario. SSP5-8. 5 is a scenario without supplementary climate policies, where CO 2 emissions nearly double from present levels by 2050, and corresponds to a high-emission scenario.
Each scenario is described in depth in Chapter 1 of the IPCC WGI report  [81]. The IPCC WGI Interactive Atlas provides the monthly mean temperatures aggregated over the reference regions defined for the IPCC 6th Assessment Report  [81, 82]  for each available GCM. We determined a region for each species based on the location in the studies from which development rate data were extracted (Table  2 ). Because S. nonagrioides individuals were collected in Greece, Spain and Morocco, we used temperature data for the Mediterranean region (MED). For O. nubilalis, as individuals were collected in North America, we used temperature data for the East-North America region (ENA). For C. partellus and B. fusca, as individuals were collected in Kenya and South Africa, we used data for the South-Eastern Africa region (SEAF).
To obtain temperature data representative of current and future conditions, we computed the mean of each month of the year over the period 1990-2014 for current conditions, and 2081-2100 for future conditions, for each region, and each GCM projection. To assess the impact of increasing temperatures on pest development, we used mean monthly temperatures projected by Global Circulation Models under different scenarios. The temporal scale of the temperature projections we used does not represent daily fluctuations in temperature. While there is an increase in mean temperatures, we have no information about the increase in temperature fluctuations that could also impact performance negatively  [83]. When average temperatures for broader temporal scales (e. g. , monthly mean temperature) approach the optimal temperature, average temperatures for narrower temporal scales (e.
g. , daily mean temperature) can be expected to fluctuate within a range overlapping the optimum temperature and approaching the maximum critical threshold, resulting in increased development times or null development, together with the associated stress for the species [84]. Although a higher temporal resolution would have allowed for finer predictions, monthly average temperatures allowed us to draw general conclusions about the impact of warming temperatures. Complete temperature datasets were retrieved from the IPCC WGI Interactive Atlas GitHub repository (https://github. com/IPCC-WG1/Atlas, accessed on 11 October 2022). The entire process, from TPC fitting to development time predictions and temperature data treatment, was completed using R version 4. 2. 1  [85] , the devRate package  [86]  for TPCs and individual-based models, along with the targets package  [87]  to ensure result reproducibility.
Discussion To predict the immature development time of four maize stemborers, we adjusted mathematical models to relate development rate and temperature for each life stage of each species, using nonlinear regressions on aggregated average development rate data measured at constant temperatures extracted from the literature. We estimated higher CT max values for the egg and larval stages of O. nubilalis and S. nonagrioides, resulting in larger thermal ranges. This is in line with previous studies that have established a relationship between latitude and thermal range, explained by the fact that species at higher latitudes are confronted with wider thermal variations  [33]. In this study, the two species with greater thermal range are found at higher latitudes, i. e. , S. nonagrioides and O.
Data Availability Statement: Publicly available datasets were analyzed in this study. All results of this study can be reproduced using the Github repository (https://github. com/bapt-regnier/ stemBorerCC, accessed on 2 December 2022 ) under a GPL v3 licence. The scripts on this repository use R version 4. 2. 1 and the targets package version 0. 13. 5 to ensure reproducibility.
Data analysis Standard formulas were used with MedCalc  [10]  to determine the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV)  [11]. Cohen's kappa coefficient (k) and McNemar's test were performed to determine the concordance and discordance between the RT-RAA assays and real-time RT-PCR-based method. The values of Cohen's kappa coefficients were interpreted according to Landis and Koch  [12]  and calculated using the online Graphpad version. The McNemar test was calculated via https://epitools. ausvet. com. au/mcnemar. A P-value <0. 05 was considered to be statistically significant.
Performance of the deployed isothermal amplification assays In total, 3231 samples were identified at study sites (Fig. 1 ) to validate the assays. After data curation, the N gene assay results were evaluated with a total of 1890 negative samples and 580 positive samples and the RdRP gene assay with a total of 2326 negative samples and 868 positive samples (supplementary file #3 displaying sample flowchart and raw data). The RdRP gene assay showed an overall PPV of 0. 92 and a NPV of 0. 88. The N gene assay showed an overall PPV of 0. 93 and a NPV 0. 88. The sensitivity of both RT-RAA assays varied depending on the sample Ct values (Table  1 ). Real-time RT-PCR positive samples with high viral load (Ct <30) showed the best results with 90. 8% and 81. 8% overall sensitivities for the RdRP and N gene RT-RAA assays, respectively.
tion of the converter target did not allow for a measurement of the spectrum of the electrons impinging on it. The expected spectrum of the bremsstrahlung gamma-ray beam produced during the interaction of such electron beams with a 1 mm tantalum converter was modeled using the Monte Carlo (MC) particle tracking code Geant4  [30, 31]. The whole geometry presented in Fig. 1  along with 1 × 10 8 primary LWFA electrons, sampled from the average electron spectrum shown in Fig. 2 , were generated as input for the MC simulations. To show the effect of the propagation through the whole experimental setup, up to the entrance of the gammaray spectrometer, we show in Fig. 3  the predicted gamma-ray spectrum at the rear surface of the converter target (solid blue) and the one entering the spectrometer (dashed orange).
In conclusion, we report on the first high-resolution and on-shot measurement of the spectrum of high-flux GeV-scale photon beams. Our experimental results confirm, in good agreement with numerical modeling, the possibility of performing single-shot measurements of the gamma-ray spectra with a high signal-to-noise and ≈10% energy resolution. Simple scalings with magnet strength and particle energy suggest that percent-level energy resolution can be readily achieved. We envisage that this diagnostic technique will provide key data in strong-field QED experiments such as E-320 and LUXE. The experimental data used to generate the results shown here is openly available at Zenodo  [36]. particle position x can be related to its energy E using the magnetic dispersion relation for a detector a distance z D from the rear of a magnet of length z M and field strength B: E (x) eB • z M x z M 2 + z D , (A1) assuming E eBz M.
ACKNOWLEDGMENTS G. S. wishes to acknowledge support from the  Engineering and Physical Sciences Research Council (EPSRC)  via grants  EP/T021659/1 ,  EP/V044397/1 , and  EP/V049186/1. The authors are grateful for the support of the  Apollon team  and for useful discussions with members of the E-320 and LUXE collaborations. G. S. devised the idea and its experimental incarnation, with help from K. F. , N. C. , and M. J. V. S. The experimental campaign was carried out by N. C. , K. F. , C. B. , R. C. , L. C. , S. D. D. , I. M. , L. R. , O. V. A. W. , A. S. , and B. C. , led by M. J. V. S. and L. T. D. K. F. carried out the numerical simulations and N. C. , E. G. , and K. F. analyzed the data. The manuscript was written by G. S. , K. F. , N. C. , and E. G. , with help from all the authors.
There are limited real-world data on the use of botulinum toxin type A (BoNT-A) in patients with multiple sclerosis (MS). Accordingly, this nationwide, population-based, retrospective cohort study aimed to describe BoNT-A treatment trends in patients with MS between 2014 and 2020 in France. This study extracted data from the French National Hospital Discharge Database (Programme de Médicalisation des Systèmes d'Information, PMSI) covering the entire French population. Among 105,206 patients coded with MS, we identified those who received ≥1 BoNT-A injection, administered within striated muscle for MS-related spasticity and/or within the detrusor smooth muscle for neurogenic detrusor overactivity (NDO). A total of 8427 patients (8. 0%) received BoNT-A injections for spasticity, 52. 9% of whom received ≥3 BoNT-A injections with 61.
Moreover, in countries such as the United States and Canada, BoNT-A use may be limited by patient costs and insurance coverage  [13]. This is, however, not the case in France, where patients with MS are covered for 100% of their healthcare costs  [14]. In this context, the present study, based on the real-world analysis of the French National Hospital Discharge Database (Programme de Médicalisation des Systèmes d'Information, PMSI) covering the entire French population, aims to describe the trends in BoNT-A use among patients with MS between 2014 and 2020.
BoNT-A for MS-Related Spasticity A total of 8427 patients with MS (8. 0%) received at least one BoNT-A injection between 2014 and 2020 within striated muscles for the treatment of spasticity. More than half of these BoNT-A-treated patients (4461/8427; 52. 9%) received at least three BoNT-A injections. Men with MS were more likely to be treated with BoNT-A for spasticity (10. 8% versus 6. 8%; p < 0. 0001). Regarding age, the highest rate of BoNT-A use for spasticity among patients with MS was reported in the 40-59-year age group (10. 3%) (Figure  2A ). In total, there were 42,147 BoNT-A injections for spasticity recorded in the PMSI database among the patients with MS. There was a steady increase in the number of administered BoNT-A injections within striated muscles between 2014 and 2019 (Figure  3A ).
Discussion There are currently very limited published data on the clinical use of BoNT-A therapy in patients with MS  [15]. Our 7-year longitudinal analysis of the comprehensive French PMSI database extends the literature on this aspect by highlighting a broad range of BoNT-A treatment practices between 2014 and 2020 in this patient population. The present study included a total of 105,206 patients with MS, 23. 6% of whom were coded as having spasticity. This figure may be lower compared to other prevalence studies  [16] [17] [18]. In a cross-sectional, registry-based study from the United States conducted in 20,380 patients with MS, 84% of the patients experienced some form of spasticity, with the severity ranging from minimal (31%) to total (4%)  [16]. Similar results were obtained in a cross-sectional survey study from the United Kingdom, which reported spasticity in 85.
Overall, individualised and flexible treatment intervals of BoNT-A tailored to individual clinical needs may be important to reduce patient and carer burden  [26] [27] [28]. There were limitations to the present study, inherent to retrospective analyses of electronic health records, including potential bias, missing data, and coding errors, as coding was made by the treating physicians and hence relies solely on physicians' accuracy in selecting medical codes. There is also a potential for the misclassification of MS disease status. Furthermore, we did not have access to the data regarding BoNT-A dosage or effectiveness. In addition, this study did not examine the correlation between BoNT-A use and clinical and demographic variables, because the use of the anonymised PMSI database does not allow the performance of a cross-check analysis of clinical data.
Given the impact of spasticity and NDO on the day-to-day lives of people with MS, studying the clinical and demographic factors that may influence BoNT-A treatment patterns is warranted. Lastly, we did not evaluate BoNT-A use according to MS subtypes (i. e. , relapsing remitting MS, secondary progressive MS, and primary progressive MS), as the French version of ICD-10 does not make the distinction between the different MS subtypes. Our study is however strengthened by the use of the PMSI national database covering the entire population of France (over 66 million people), which enabled the inclusion of almost all the patients with MS in France, thus minimising the risk for selection bias. Another strength of this study is the long observation period with exhaustive data collection on the trends in the use of BoNT-A, administered both within striated muscle and the detrusor smooth muscle.
Study Design and Data Source This was a nationwide, population-based, retrospective cohort study, using data extracted between 2014 and 2020 from the PMSI database, which covers the whole French population, corresponding to over 66 million persons. The PMSI database contains individualised and comprehensive data on all hospital stays in conventional medical units, rehabilitation units, homecare units, and psychiatric institutions in France. The PMSI database also contains patient information on medical diagnoses, costly drugs, and implantable medical devices administered during each hospital stay. In the present study, medical diagnoses were coded according to the ICD-10 and medical procedures according to the French Joint Classification of Medical Procedures (Classification Commune des Actes Médicaux, CCAM).
Study Population and Botulinum Toxin Injections Patients diagnosed with MS, throughout France, between 2014 and 2020 were included in this study. The ICD-10 code used for MS diagnosis was "G35". Among patients coded with MS, we searched the PMSI database to identify those with MS-related spasticity, using the following ICD-10 codes: "G81. 1", "G82. 1", and "G82. 4". We also searched the PMSI database to identify patients coded with MS who received at least one BoNT-A injection for spasticity between 2014 and 2020, using the following CCAM codes: "PCLB002" and "PCLB003". Both codes refer to a single session of BoNT-A injection(s) within striated muscles, with or without electromyographic guidance (003 and 002, respectively). We further searched the PMSI database to identify patients coded with MS who received at least one BoNT-A injection between 2014 and 2020 for the treatment of NDO.
Outcomes Among patients with MS, we assessed the prevalence of spasticity, which was defined as the number of patients with MS coded with spasticity between 2014 and 2020 divided by the total number of patients coded with MS during the same period. Other evaluated outcomes in patients coded with MS-related spasticity were the number and proportion of patients who received at least one BoNT-A injection within striated muscles between 2014 and 2020, the number and proportion of patients who received at least three BoNT-A injections between 2014 and 2020, and the time interval between two BoNT-A injections administered within striated muscles. In addition, in order to reduce immortal time bias attributable to retrospectively entered data in the PMSI database, trends in BoNT-A use were evaluated in patients coded with MS-related spasticity who initiated BoNT-A therapy between 2015 and 2020.
, 2020; Guerrero-Juarez et al. , 2019; Storer et al. , 2020). However, few studies have investigated bone healing at the single cell level and these studies have focused on cultured cells or late stages of bone repair  (Julien et al. , 2022; Sivaraj et al. , 2022). A complete dataset of periosteum and bone regeneration to decipher the mechanisms of pSSPC activation and regulation is lacking. Here, we created a single-nuclei atlas of the periosteum and its response to bone fracture. We generated single nuclei RNAseq (snRNAseq) datasets from the uninjured periosteum and from the periosteum and hematoma/callus at days 3, 5 and 7 post-tibial fracture. Our analyses thoroughly describe the heterogeneity of the periosteum at steady state and the steps of pSSPC activation after injury. We show that pSSPC represent a unique SSPC population that can provide osteoblasts and chondrocytes for bone repair by first generating a common injury-induced fibrogenic cell population that engage into osteogenesis or chondrogenesis.
The fracture repair atlas To investigate the periosteal response to bone fracture, we collected injured periosteum with hematoma or calluses at days 3, 5 and 7 post-fracture, extracted the nuclei and processed them for snRNAseq (Fig. 2A ). We combined the datasets with the uninjured periosteum from Figure  1  and obtained a total of 6213 nuclei. The combined dataset was composed of 26 clusters corresponding to 10 cell populations: SSPCs (expressing Pi16), injury-induced fibrogenic cells (IIFC, expressing Postn), osteoblasts (expressing Ibsp), chondrocytes (expressing Col2a1), osteoclasts (expressing Ctsk), immune cells (expressing Ptprc), Schwann cells (expressing Mpz), endothelial cells (expressing Pecam1), pericyte/SMC (expressing Pdgfrb), and adipocytes (expressing Lpl) (Fig. 2B-C , Fig.
Periosteal SSPCs differentiate through a common injury-induced fibrogenic stage. To understand the differentiation and fate of pSSPCs after fracture, we analyzed the subset of SSPC, IIFC, chondrocyte and osteoblast clusters from the combined fracture dataset (Fig. 3A ). We performed pseudotime analysis to determine the differentiation trajectories, defining the starting point in the SSPC population, where the uninjured and undifferentiated cells clustered. We identified that SSPC response to fracture progresses in 3 stages starting from the SSPC population (expressing Ly6a, Cd34 and Dpp4), predominant in uninjured dataset (Fig. 3B-E ). Periosteal SSPCs then transition through a common injury-induced fibrogenic stage predominant at days 3 and 5 post-injury. Cells in this intermediate fibrogenic stage express high levels of extracellular matrix genes, such as Postn, Aspn and Tnc.
First, we described the heterogeneity of the periosteum at steady state. While previous studies performed scRNAseq on sorted periosteal cell populations, our dataset demonstrate the diversity of cell populations within the periosteum. We identified 5 fibroblast populations, as well as blood vessel and nerve-related cells. Among the fibroblast population, we identified one SSPC population of undifferentiated cells expressing markers such as Sca1 and Pi16, known to mark fibroblasts with stemness potential  (Buechler et al. , 2021). No markers previously described such as Ctsk, or Gli1 were fully specific of one cell cluster, suggesting that these markers may label heterogenous cell populations  (Debnath et al. , 2018; Jeffery et al. , 2022; Matthews et al. , 2021). After fracture, the composition of the periosteum changes drastically, with the appearance of IIFC and immune cells from day 3 post-fracture, and of chondrocytes and osteoblasts from day 5 postfracture.
Nuclei extraction Nuclei extraction protocol was adapted from  (G Martelotto, 2019; Santos et al. , 2021). We generated 4 datasets for this study: uninjured periosteum, periosteum and hematoma at days 3, 5 and 7 post-tibial fracture. The uninjured and day 3 post-fracture datasets were generated in duplicates. For uninjured periosteum, tibias from 4 mice were dissected free of muscle and surrounding tissues. The epiphyses were cut and the bone marrow flushed. The periosteum was scraped from the cortex using dissecting Chisel (10095-12, Fine Science Tools). For days 3, 5 and 7 post fracture, injured tibias from 4 to 9 mice were collected and the surrounded tissues were removed. The activated periosteum was scraped and collected with the hematoma. Collected tissues were minced and placed 5 min in ice-cold Nuclei Buffer (NUC101, Merck) before mechanical nuclei extraction using a glass douncer.
Single nuclei RNA sequencing The snRNA-seq libraries were generated using Chromium Single Cell Next GEM 3′ Library & Gel Bead Kit v. 3. 1 (10x Genomics) according to the manufacturer's protocol. Briefly, 10 000 to 20 000 nuclei were loaded in the 10x Chromium Controller to generate single-nuclei gel-beads in emulsion. After reverse transcription, gel-beads in emulsion were disrupted. Barcoded complementary DNA was isolated and amplified by PCR. Following fragmentation, end repair and A-tailing, sample indexes were added during index PCR. The purified libraries were sequenced on a Novaseq (Illumina) with 28 cycles of read 1, 8 cycles of i7 index and 91 cycles of read 2. Sequencing data were processed using the Cell Ranger Count pipeline and reads were mapped on the mm10 reference mouse genome with intronic and exonic sequences.