dataesr/scientific-paragraphs-categorization huggingface dataset:
In the 13 C{ 1 H} NMR data (J-MOD or DEPT-Q), reported signal multiplicities are related to C-F coupling. The following abbreviations were used to indicate the multiplicities: s (singlet), br s (broad singlet), d (doublet), t (triplet), q (quartet), quint (quintuplet), hept (heptuplet), m (multiplet). Diastereomeric ratios (dr) were determined by  19  F NMR. HRMS were recorded on an ESI-Q-TOF mass spectrometer using an electrospray source in positive mode. Optical rotations were measured at room temperature (c. a. 20 °C).
Acknowledgments We gratefully acknowledged the "région  Champagne-Ardenne" ("région Grand Est" at present ), the  "Université de Reims-Champagne Ardenne " and the  "Institut de Chimie Moléculaire de Reims"  for financial support (ABJ and ML). The  CNRS , the  Conseil Régional de Champagne-Ardenne  and the  EU-program FEDER  are acknowledged for the facilities of the analytical platform (PlAneT  CPER  project). We warmly thank  C. Machado  and  S. Lanthony  (HRMS),  Dr S. Chevreux  and  Dr C. Kowandy  (X-ray crystallographic structure determinations) as well as  A. Truchon  (technical assistance for the synthesis of few compounds). We also thank the  French Fluorine Network (GIS CNRS ).
Statistical analysis: A one-way analysis of variance (ANOVA) followed by the Tukey post hoc test were used to analyse statistical significance (p < 0. 05) using Xlstat software (Addinsoft 2020. XLSTAT statistical and data analysis solution. NEW York, USA). The analysis was carried out at least in triplicate. Principal component analysis (PCA) was performed on lawsone concentration calculated from every individual sample, temperature of the four regions (°C), rainfall parameters (mm) and distance from ocean (km).
Principal component analysis The quantitative data were again analyzed using Principal Component Analysis (PCA) with the aim to differentiate the samples from each other and evaluate which variables among temperature precipitation or distance from ocean, influences their location in the 2D space. The created dataset was composed by 12 observation (4 samples in biological triplicate) and 4 variables (distance from the Ocean, rainfall, mean temperature and content of lawsone). Score Plot obtained is showed in Figure  9 , PC1 represents a variability of 70. 9% and PC2: 17. 04% consequently this PCA shows 87. 94% of variability. As evidenced, samples are separated along first component in two main groups: first group, (in the highest negative values), is composed by samples collected in Errachidia and Tazarine, the second one, (in the highest positive values), by those collected in Zagora and Foum Zguid (Fig.
10 A  and B ). In order to evaluate the influence of each variable on the classification of the samples, the loading plot obtained for the same dataset was then studied and results are shown in Fig. 10 C. As shown, along the highest positive values of PC1 are located the regions with high mean temperature in the space corresponding to the samples collected in Foum Zguid and Zagora that showed. By contrast, the main information able to discriminate samples from Errachidia and Tazarine is due to the variable pluviometry which is located through the direction of the samples. Quantitative differences in the content of identified lawsone among samples collected in different geographical areas in south east of Morocco was clearly demonstrated and the variable temperature is a critical component that influences the content of lawsone and its concentration in the leaves of Lawsonia inermis L 14.
Selection of Studies The titles and abstracts of all the citations identified by the search strategy were independently screened for eligibility by two reviewers. After reaching a consensus, full texts of selected abstracts were screened. Included articles were reviewed for data extraction. Studies published in English, which reported PP elicitation and initiatives of PP implementation in healthcare decision making, were considered. Included studies were either primary research studies that prospectively collected PPs or specific patient-centered projects and guidelines related to the inclusion of PPs in decision making. Studies assessing PPs for shared decision making, i. e. , the process in which clinicians and patients work together to make decisions and select tests, treatments, and care plans  (18) , were excluded as not directly linked to heath policy decision making.
Data Extraction and Synthesis For each publication included, data extracted included the type of article, the region studied, the type of elicitation method used, the disease area, and the decision-making process engaged. Any relevant data related to the collection, use, or submission of PPs informing BRAs, HTAs, or drug pricing were retrieved. Attempts and initiatives at setting recommendations for the integration of PPs in the decision-making processes were also identified and classified by the decision-making process as well as institutional level engaged and geographical scope.
STRENGTHS AND LIMITATIONS OF THIS REVIEW To the authors' knowledge, this is the first review summarizing existing PP studies informing treatment preferences for health policy decision making as well as relating attempts and initiatives for inclusion of these PPs in BRAs, HTAs, and pricing and reimbursement decisions. The work also does well to define and categorize the various PP elicitation tools. When results of the review are interpreted, limitations should be considered. Despite the willingness of investigating the implementation of PPs in policy decision making, the authors did not review HTA and BRA reports to directly look for utilization and consideration of PPs. Another limitation is the restriction of the search to only the PubMed database and to only English publications, which may have resulted in unaccounted for publications relevant to the search objectives, such as countryspecific guidance in native languages for PP inclusion in decisionmaking processes.
HPLC Analyses The preservation of curcumin incorporated in the nanoliposomes was determined by centrifugation of nanoliposomes at 10,000× g for 10 min and the supernatant was assayed by HPLC at 425 nm to follow curcumin and 280 nm to follow its degradation products, by dissolving in methanol. Curcumin concentration was determined via a reverse-phase HPLC system (Shimadzu, Kyoto, Japan), that is equipped with an auto-injector, a quaternary pump, a UV-Vis photodiode array detector, a Zorbex SB-C18 column, and the LabSolutions data software.
UV-Visible Absorbance Measurements Curcumin's absorbance was measured from 200 to 800 nm on a Shimadzu UV1605 spectrophotometer for the different liposome formulations, with various initial amounts of curcumin. Liposomes solutions were centrifuged at 10,000 rpm for 10 min and the supernatant was dissolved 1:20 in methanol. Maximal absorbance was determined for each formulation after different steps of the elaboration process (sonication, filtration, and extrusion) and each preparation was reproduced three times. Data were compared to a standard solution of curcumin in methanol.
256 scans were performed per sample. Spectra were analyzed thanks to ACD/Labs NMR Processor software. Fourier transform was applied with EM (1 Hz) treatment, phasing, and baseline correction. Chemical shift calibration was performed thanks to the HOD peak. In 2D NMR experiments, the nuclear Overhauser effect (NOE) 2D spectra were obtained with a 256 × 1024 resolution. Data were first extracted, and the different slices were saved. They have been normalized to be compared with the 1 H NMR spectrum and follow peaks intensity evolution when correlated. Peak attribution is detailed below.
Statistical analysis For the descriptive statistics were calculated the central tendency and dispersion parameters and some proper charts were made. The descriptive analysis was run in the Microsoft Excel program. The statistical tests were performed using the SPSSv17 program. The Mann -Whitney test was chosen for the case when there are two different groups, the ANOVA one Way test was used for more than two groups and the ANOVA bi-factorial test without replication was chosen when there are more than two times moments. The confidence level is set at =0. 05.
Results an discussions Table  1  shows the characteristics of the tablets used in this study, and Tables  2 3 4 show the amount of magnesium found in tablets, in UW and SIF, during the validity period, as well as at 6 and at 12 months after the expiry date of the studied product. https://doi. org/10. 37358/RC. 20  In the beginning of the analysis, a descriptive statistic was run, in order to characterize the database and obtain as much information as possible. After this characterization, the study hypothesis can be formulated. So, for the descriptive analysis, the central tendency and dispersion parameters for the quantity of magnesium in validity period, in UW and SIF (Table  5 ), were calculated, and the magnesium compounds used, magnesium concentrations/validity period and excipients were plotted (Figure  1 ).
Analysis of ground CDs Scanning electron microscopy (SEM) SEM enables particle size evolution upon grinding to be monitored. The SEM images in Figure  1  show the surface topography changes of polycrystalline β-CD for six different milling times. As can be seen from Figure  1 , the powder particles experience comminution and decrease in size over time and after grinding for 10 min, β-CD displays microsized particles (Figure  1c ). Longer grinding times led to particles with sizes below 300 nm in diameter (Figure  1d  and Figure  1e ). The spherical morphology could be deduced from the Solidicity program incorporated in the ImageJ software  [22]. However, further grinding up to 297 min did not lead to further changes in either the morphology or the size of the β-CD particles (Figure  1f ). From the SEM images and the inspection with the ImageJ software, we also calculated the granulometric composition of the β-CD particles against the grinding time (Figure  2 ).
While a rapid decrease in size was observed over the first 10 min of grinding, a slight variation on the particle size was noticed when the grinding of β-CD was left to occur over longer times, suggesting that shear, friction, and collision effects did not anymore affect the β-CD particle size and morphology over time. In fact, crystal breaking reduced the particle size up to some critical threshold, as a result of the equilibrium between comminution and aggregation. From the SEM images and using the ImageJ software, we were able to determine the size of the β-CD particles and the calculated Feret mean diameter (mean value of the Feret diameters over all orientations, i. e. , 0-180°) are collected in Table  1.
Scanning electron microscopy Scanning electron microscopy (SEM) images were recorded on a SEM JEOL JSM-7800F LV instrument at 3. 0 kV. The powder was deposited on a carbon-coated copper grid. The particle size distributions were determined from the measurement of ca. 225 particles found in an arbitrarily chosen area of the images using the ImageJ software (version 1. 4. 3. 67) [32]. After calibrating from the scale of the SEM images, the software provides the Feret diameter.
Data collection and laboratory methods The study started in Myanmar in May 2013, followed by Vietnam in November 2013, Cambodia in July 2015 and Lao PDR in April 2016. Data were collected through community-wide surveys at baseline, and then every three months. Surveys were preceded by a community census to re-enumerate the study population and to provide intensive community engagement in order to improve high coverage  [10] [11] [12] [13] [14]. Information collected included demographics, bednet use, duration of stay in the forest, and adverse events. Malaria prevalence at each survey was assessed by quantitative uPCR. 3 mL of blood was taken from participants older than 4 years old, and 0. 5 mL from younger children. The blood samples were stored in cool boxes in the field for about 5-6 hours before being separated in the local laboratories and then kept in -20˚C freezers.
Statistical analysis The changes of prevalence of P. vivax infection at the separate surveys were assessed by a difference-in-difference (DiD) approach for which we fitted a logistic model that incorporated effect modification between the intervention groups and the time period of the survey. We assessed these differences between baseline and each follow-up time point (month 3, 6, 9, and 12) with the exception of month 12 data from Myanmar (where for logistic reasons the crossover MDA in control villages had to be conducted on M9 instead of M12). None of the parameters in the DiD analysis was constrained to zero. The cumulative uPCR-derived incidence of P. vivax parasitaemias over the 12-month period was assessed using a survival analysis approach in which participants were censored when diagnosed, lost to follow-up, end of the observation period, which ever came first.
falciparum infections after 12 months  [3]. A more regional approach to targeted malaria elimination including MDA would be required to reduce the risk of re-importation of Plasmodium infections. 3) The prevalence estimate at month 12 could be an underestimated due to the absence of data from Myanmar (where for logistic reasons the evaluation was conducted at month 9). In every site, except Laos, the prevalence of P. vivax increased between month 6 and 12 in the intervention villages  [6]. 4) Entomological aspects were only evaluated in one study site  [28]. Entomological data from more study sites may have helped to gain further insights into malaria transmission dynamics. 5) We sampled study participants in quarterly intervals. More frequent sampling would have provided a better understanding of the persistence of infections.
The studies were approved by the Cambodian National Ethics Committee for Health Research (0029 NECHR, dated 04 Mar 2013), the Institute of Malariology, Parasitology and Entomology in Ho Chi Minh City (185/HDDD dated 15 May 2013), the Institute of Malariology, Parasitology and Entomology in Qui Nhon (dated 14 Oct 2013), the Lao National Ethics Committee for Health Research (Ref No 013-2015/NECHR), Government of the Lao PDR and the Oxford Tropical Research Ethics Committee (1015-13, dated 29 Apr 2013). Individual informed consent was obtained from each participant or parent/guardian in the case on minors. A fingerprint was obtained for illiterate participants countersigned by a literate witness. (ClinicalTrials. gov Identifier: NCT01872702).
Acknowledgments We thank first and foremost the study communities who kindly agreed to participate in this project. We thank the members of the trials steering committee for their support:  Prof. David Lalloo  (Chair,  Liverpool School of Tropical Medicine, UK) ,  Prof. Decha Tangseefa  ( Thammasat University, Bangkok, Thailand ),  Prof. Mike Parker  ( Ethox Centre at the University of Oxford, UK ),  Phan Kim Son  ( Lay member, Ho Chi Minh City, Vietnam ). We thank the members of the data safety monitoring board:  Prof Ric Price  ( Menzies, Darwin, Australia );  Prof. Sarah Walker  ( Clinical trials Unit, MRC, UK );  Prof. Amir Hossain  ( Chittagong Medical College, Bangladesh ) and the medical monitor,  Prof. Susanna J Dunachie.
Funding for the  TME  project was obtained from  Wellcome Trust  ( 101148/Z/13/Z ) to NJW and the  Bill and Melinda Gates Foundation  ( OPP1081420 ) to AMD. The funder provided support including salaries for authors [KP, TJP,RT, TP, BA, LvS ], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the 'author contributions' section. ". JAS is funded by an  Australian   NHMRC Senior Research Fellowship   1104975. We declare that none of authors in this paper is employed by commercial company.
Contact angle (CA) measurements. The advancing contact angles were measured on the skin surface using the Portative Goniometer PGX+ (ScanGaule, Gravigny, France) connected to the PGPlus® software. Measurements were performed at room temperature (20±1. 5°C). Advancing contact angle was determined as follows: first a small water drop was deposited on the skin surface; then the drop volume was increased by adding successively five drops until a final drop volume of 6µL was reached. An image was acquired at each drop deposition resulting in five pictures and the value of each CA was determined by the software program  27. The advancing contact angle corresponds to the highest CA value among the five pictures. The measurements were repeated at least four times for each application zone and an average of these four measurements was calculated.
Data analysis All the values were reported in tables and graphs as mean ± standard deviation (SD). Statistical analysis of differences was performed using XLSTAT software from Addinsoft (version 2012. 1. 01). As sufficient data were obtained to confirm the normality  28  , one or two-factor analyses of variance (ANOVA) were performed on instrumental data to evaluate the effect of the residual film on the skin properties depending on the formulation applied on the skin. When discrimination between products was significant (p<0. 05), the mean scores obtained were compared using the Fisher multiple.
9 min prior to the next injection. LC-HRMS analyses were carried out in full-scan and targeted MS/MS mode in positive ionization. Full-scan analysis operated at a mass resolution of 40,000 full width at half maximum (FWHM) over a mass-to-charge ratio (m/z) ranging from 800 to 1200 with a scan rate of 1 spectrum/s. Targeted MS/MS was performed in a collision induced dissociation (CID) cell at 45,000 FWHM over the scan rage from m/z 50 to 1200 with a scan rate of 10 spectra/s and a scan rate of 3 spectra/s applying three different collision energies in order to have a good fragmentation pathway. A reference mass of m/z 922. 0099 (hexakisphosphazine) was continuously monitored during the entire run. Acquisition was controlled by MassHunter software (Agilent technologies, CA, USA). Raw data were processed with Agilent MassHunter Qualitative Analysis software (version B.
07. 00, service pack 1) using the Find by Formula (FbF) algorithm screening with a Personal Compound Database and Library (PDCL) created by the Phycotoxins Laboratory (IFREMER, Nantes, France). Source conditions were as follows: gas temperature, 250 • C; gas flow, 16 L/min; nebulizer, 15 psi; sheath gas temperature, 400 • C; sheath gas flow, 12 L/min; capillary voltage, 5000 V, and nozzle voltage, 1000 V. The instrument was calibrated, using the Agilent tuning mix, in positive ionization mode before each analysis.
Acknowledgments: Thanks to all technicians of Regional Fisheries Management- Madeira Government ,  Divisão de Serviços de Investigação -Direção Regional de Pescas (DSI-DRP) , to  Natural Park of Madeira and to Nature's Wardens of Selvagens Islands  for their efforts and contribution obtaining fish samples. C-CTX1 standard was kindly provided by  Robert W. Dickey  (previously,  U. S. Food and Drug Administration)  via  Ronald Manger  ( Fred Hutchinson Cancer Research Center, Seattle, WA, USA ).
Post-sepsis Immunosuppression Despite the absence of clinical trials directly targeting JAK-STAT during post-sepsis immunosuppression until now, this track must be kept in view. Indeed, treatments currently in therapeutic trials in the field of sepsis impact on the JAK-STAT pathways to mediate their effect. IL-7, which aims at restoring post-sepsis immunity  [100]  by promoting CD4 + T cells survival, and which entered Phase II clinical studies in this perspective (e. g. , NCT03821038 i ), upregulates Bcl-2 by phosphorylating STAT5. As the IL-7 signaling pathway involves STAT5, phosphorylated STAT5 could be a convenient theranostic marker to follow and evaluate IL-7 effects, particularly in T lymphocytes  [101]  to monitor the treatment of sepsis-induced immunosuppression. Moreover, nanoparticles can target T cells (Figure  3B ) via the anti-PD1 (programmed cell death 1) pembrolizumab  [97] , which also acts as an antiapoptotic agent on T cells.
Such T cell-targeted nanoparticles could be loaded with IL-7 (Figure  4 ). During sepsis-induced immunosuppression, cellular exhaustion also involves macrophages, and CD206-targeted NPs could be proposed for M1 reprogramming  [95] , which enables the use of phosphorylated STAT3 as a theranostic marker  [102]  (Figure  2 ). In addition to using the status (phosphorylation) of JAK-STAT proteins as biomarkers, JAK-STAT inhibitors may be an adjuvant treatment for immunomodulators, especially during post-sepsis immunoparalysis (Figure  2 ). This strategy is inspired by recent therapeutic trials in oncology, in which STAT3 inhibitors such as sunitinib or axitinib were combined with the anti-PD1 nivolumab in Phase I and II studies (NCT03277924 ii , NCT03172754 iii ) to prevent MDSC-mediated immune escape  [103].
Indeed, some therapeutic targets in post-sepsis immunosuppression are common with oncology, especially the immune checkpoint molecules PD1 and cytotoxic T lymphocyte-associated antigen (CTLA)4: anti-PD1 and anti-CTLA4 both improve survival in humans with malignant diseases; they also increase survival in mice during post-sepsis immunosuppression  [104]. Moreover, the  anti-PD1 nivolumab is already being tested for its capacity to relieve sepsis-induced immunosuppression in a Phase I study (NCT02960854 iv ). The demonstrated role of MDSCs in the resistance to immunotherapy in cancer patients  [103]  suggests that an association of nivolumab with STAT3 inhibitors could be relevant in future trials to control sepsis-induced immunosuppression. Similarly with the cell-targeted strategies considered for the hyperinflammatory phase, MDSCs could be targeted by nanoparticles, which would minimize the side-effects of JAK-STAT inhibitors.
Acknowledgments Work in our laboratory is supported by grants from the  Agence Nationale de la Recherche (ANR)  ( ANR-11-LABX-0070_TRANSPLANTEX ),  INSERM  ( UMR_S 1109 ), the  Institut Universitaire de France (IUF) , the  University of Strasbourg (IDEX UNISTRA) , the  European regional development fund (European Union )  INTERREG V program  (project n°3. 2 TRIDIAG), and  MSD-Avenir  grant AUTOGEN. Research work in our intensive care unit is supported by grants from  ADIRAL Assistance  and from the  French Eastern Interregional Group of Clinical Research and Innovation (GIRCI Est ; appel à projet « jeunes chercheurs », APJ 2018). Resources i https://clinicaltrials. gov/ct2/show/NCT03821038 ii https://clinicaltrials. gov/ct2/show/NCT03277924 iii https://clinicaltrials. gov/ct2/show/NCT03172754 iv https://clinicaltrials.
It is therefore of some interest to know the solubility of amygdalin in different mixtures of solvents. On the other hand, the knowledge of the solubility behavior in different solvent systems is of high importance in the pharmaceutical industry as it influences the drug efficacy and its pharmacokinetics  [20]. Solubility data are also useful for drug purification, refining procedures, and method development  [21] [22] [23]. For the above-mentioned reasons, the solubility and solution thermodynamics of amygdalin in pure and solvent mixtures are quite essential and must be determined. The binary water and ethanol mixtures are the most versatile and most used solvent systems for these previous purposes  [24] [25] [26] [27]. Thus, the goals of this study were  (1)  to extend the database on the solubility of amygdalin in several ethanol (1) + water (2) mixtures over a temperature range of 298.
Conclusions The solubilities of amygdalin in {ethanol (1) + water (2)} mixtures were determined at different temperatures. The maximum solubility was obtained in 0. 4-mole fraction of ethanol at 328. 15 K and the lowest one in pure ethanol at 293. 15 K. The amygdalin solubility was calculated using the van't Hoff, Jouyban-Acree-van't Hoff, and Buchowski--Ksiazczak models, the data obtained using the Jouyban-Acree-van't Hoff model showing important deviations with respect to experimental.