dataesr/scientific-paragraphs-categorization huggingface dataset:
Database Search A total of 666 records were identified, including five references from other sources. After removal of duplicates, 605 records were eligible for selection, of which 83 corresponded to the inclusion criteria. All records screened (n = 605) are listed in the Supplementary Materials (List S3). After the full-text review, 18 articles were excluded, and 65 studies were included in the analysis (Figure  1 ). Due to the broad content of this scoping review, seven different categories emerged after reading the articles reporting the 65 studies: testing (cancer screening in nursing homes and decision-making process surrounding further investigations for cancer diagnosis), treatment (specificities of older cancer patients and nursing home residents, cancer management in nursing homes, and oncological treatment outcomes in this age group), symptoms (including the impact of cognitive impairment and pain management on these), advanced care planning (factors associated with do-not-resuscitate decisions of nursing home residents, disease trajectories, and implication of nurses in these decisions), end of life (mortality in nursing homes and palliative care), nursing home care (philosophy of care and transitions between this setting and hospitals), and education (strategies and facilitators for continuing education in nursing homes).
The characteristics of the studies included are described in the Supplementary Materials (Tables  S4-S10 ). Of the 65 studies included, 11 were qualitative studies, 1 used mixed methods, and 53 were quantitative studies. Four studies were original or a secondary analysis of a randomized controlled trial. Thirty-two studies extracted data from medical records or administrative databases (Minimum-Data Set (MDS), for example), and 33 studies used different types of surveys (paper-or web-based self-administrated questionnaires, open or directed interviews).
Molecular Dynamics DPD simulations were performed using the Materials Studio software (Materials Studio 2017, Biovia, Dassault Systèmes, Lyon, France, 2016). For the water molecules (W), a coarse graining approach was used, in which one bead represents 3 molecules of water. The radius of the water bead was set to 3. 23 Å and its molecular mass to 54 Da. Pam 1 CSK 4 molecules were constructed using 5 different types of beads: lysine (K), serine (S), modified cysteine (C), modified glycerol (G) and five C 3 H 6 fatty acid units (F). Pam 3 CSK 4 molecules were constructed using the same C, S, K and F beads. PLA molecules were constructed as linear repetitions of 70 units of lactic acid monomers (LA) n. Vitamin E molecules were constructed using 2 different types of beads: one for the chromanol double cycle (CHR), and 3 beads (each composed of 5 carbon atoms) for the fatty acid chain (C5).
All the different kinds of beads used for our calculations are summarized in Figure  1. For the calculations, all the solubility parameters δi were calculated with the Materials Studio software using either the Synthia module for the beads presented as polymers (LA, F, C5), or models constructed with the Amorphous Cell module for the beads presented as monomers in the simulation. For the models constructed as amorphous cells, all the calculations were performed with the Forcite module using the COMPASS II  [51, 52]  force field for atom parameters and partial charges. After a preliminary geometry optimization phase, a preliminary short equilibration run of dynamics with NVT parameters was performed (500 steps), followed by a longer production run with NVE parameters (5000 steps). The corresponding solubility parameters were then used to calculate the Flory-Huggins interaction parameters χij for the corresponding binary mixtures, which were calculated using the relation χij = (v/RT)(δi -δj) 2 where R is the gas constant, T the absolute temperature and v is the mean volume per mole of the two corresponding components  [47].
The molar volume for each component was determined using the Molecular Operating Environment software (MOE 2017, Chemical Computing Group, Köln, Germany). The Flory-Huggins interaction parameters were then converted into DPD repulsion parameters aij, which were obtained using the relation aij = 25 + 3. 50 ×χij  [46]. All the DPD repulsion parameters used are summarized in Tables  1  and 2. For the calculations, all the solubility parameters δ i were calculated with the Materials Studio software using either the Synthia module for the beads presented as polymers (LA, F, C5), or models constructed with the Amorphous Cell module for the beads presented as monomers in the simulation. For the models constructed as amorphous cells, all the calculations were performed with the Forcite module using the COMPASS II  [51, 52]  force field for atom parameters and partial charges.
After a preliminary geometry optimization phase, a preliminary short equilibration run of dynamics with NVT parameters was performed (500 steps), followed by a longer production run with NVE parameters (5000 steps). The corresponding solubility parameters were then used to calculate the Flory-Huggins interaction parameters χ ij for the corresponding binary mixtures, which were calculated using the relation 2 where R is the gas constant, T the absolute temperature and v is the mean volume per mole of the two corresponding components  [47]. The molar volume for each component was determined using the Molecular Operating Environment software (MOE 2017, Chemical Computing Group, Köln, Germany). The Flory-Huggins interaction parameters were then converted into DPD repulsion parameters a ij , which were obtained using the relation a ij = 25 + 3.
Behavior of Pam 1 CSK 4 and Pam 3 CSK 4 at Increasing Concentrations In order to validate our approach and the used simulation parameters, we confronted the molecular behavior of Pam 3 CSK 4 and Pam 1 CSK 4 in a series of experiments, using each molecule separately in an aqueous environment at increasing concentrations, without any PLA molecules. Thus, we performed DPD simulations using the Materials Studio software. This non-atomistic kind of simulation is particularly well-adapted to large systems. We started all of these simulations in 280 Å periodic cubic boxes with randomly distributed molecules mixed with water. After an initial geometric optimization, we started the DPD experiments for a total simulation time of 10 ns, which is a sufficient time to observe the formation of micelles  [47] , and in this case allows one to reach a stable state.
Funding: This research received financial support from the  ANR, France  ( Agence Nationale de la Recherche)  with the research program  ANR-20-COVI-000/CovidNanoMed  to BV and ML, and  ANRS  funding to BV ( ECTZ 62760 ). MB got a PhD funding from  DGA  ( Direction Générale de l'Armement, France ). DDC got a PhD funding from  ANRT  through a Cifre convention.
Quantification was performed using precursor ion data obtained with a mass extraction window of ±5 ppm. Fragment and residual precursor ion acquisitions at ramped collision energies were evaluated as additional analyte identifiers. In parallel, UHPLC-MS/MS analysis showed comparable precision and bias. Viaene et al. also compared a triple-quadrupole and a quadrupole time-of-flight mass analyzer to quantify 16 opioids in human plasma  [11]. They concluded that the most efficient system depends on the compound and even the concentration and that the best calibration model often differs by compounds and method.
For the substitution of 3-and 5positions, we considered aryl/heteroaryl(amino) groups. In order to assess the ability of this scaffold to interact the ATP-binding pocket of PKCγ, we performed a molecular modeling study using a PKCγ model generated by sequence homology from an X-ray crystal structure of highly homologous PKCβ available in the Protein Data Bank (PDB ID: 2I0E; no crystal structure of PKCγ available in the PDB). Then, we used an automated docking protocol of a virtual library of 255 pyridin-2(1H)-ones. This work led us to foresee the general structure A depicted in Figure  1 , of a pyridin-2(1H)-one core substituted at the 3-and 5-positions by aryl/heteroaryl and phenylamino groups, respectively. This article reports the synthesis of a series of pyridin-2(1H)-one derivatives and their identification as potent anti-allodynic agents in rodent models of MA.
5 ± 0. 7 μM (mean ± SD). S1  for screening values. The black square indicates the kinome region containing protein kinases evaluated in a second screening (Fig. 5 , Table  S2 ). The tree was generated using the Kinome Render software, and the illustration reproduced courtesy of Cell Signaling Technology, Inc. (www. cellsignal. com) [30]. Next, we evaluated the selectivity of compound 69 toward another panel containing all four p38 MAPK isoforms, ERK1, ERK2 as well as other protein kinases close to p38α MAPK in the kinome phylogenetic tree (Fig. 5 , Table  S2 ). In addition, compound 67 that also exhibited strong anti-allodynic activity was also evaluated in this screening. The results showed that 69 was selective of p38α MAPK over the other protein kinases tested in this panel, including p38 MAPK isoforms.
Compound 67 exhibited the same selectivity profile. Its IC50 toward p38α MAPK was determined and found to be in the micromolar range with a value of 3. 0 ± 0. 1 µM (mean ± SD). Figure  5. Compounds 67 and 69 were evaluated at the International Center For Kinase Profiling (ICKP, Dundee, Scotland) toward a panel of 13 protein kinases. The results were expressed as the mean percentage of residual activity at 1 µM concentration (duplicate assays). Blue disks: ≥ 90%, red disk: 59%, for both compounds. See Table  S2  for screening values. The tree was generated using the Kinome Render software, and the illustration reproduced courtesy of Cell Signaling Technology, Inc. (www. cellsignal. com) [30]. Hence, compound 69 appears as a highly selective inhibitor of p38α MAPK when considering the panel of 62 protein kinases evaluated.
4  Following establishment of infection, test drugs were administered on day 7 or 8. Parasitemia was determined using real-time quantitative polymerase chain reaction (PCR), as previously described. 7 Artemether-lumefantrine (Riamet ® , Novartis) was administered for recrudescence and as rescue therapy at the study end (Figure  1 ). Frequent blood samples were collected for drug pharmacokinetics and safety biochemistry and hematology laboratory assessments. Participants were confined and monitored for at least 36 hours post-drug administration with ambulatory follow-up until at least day 36. Retrospective microRNA-122 (miR-122) testing-a safety biomarker for liver cell damage  8  -was performed for all participants in Study QP15C01 (ClinicalTrials. gov NCT02543086). Briefly, RNA was extracted from plasma using the QiAzol extraction method (Qiagen, Valencia, CA), and quantitative PCR analysis was conducted in accordance with the manufacturers' protocols (Biomark HD System, Fluidigm, San Francisco, CA).
For cDNA synthesis of plasma, the input was 3 μL of the RNA preparations in a 5-μL reaction using Megaplex RT Primers Pool A (Life Technologies Corporation, Pleasanton, CA), with addition of a reverse transcriptase primer for mmu-miR-293 for normalization of miR-122 values. This method was validated with a limit of detection threshold value (Ct) for miR-122 of 23 Ct. Data collection. Individual participant demographic data and parasitemia and liver enzyme test results were assembled from study statistical outputs. Baseline values for liver enzyme tests and total bilirubin were recorded on days -2 to 0, before parasite inoculation. Parasitemia levels were determined on day 7 or 8 following inoculation, before treatment with NCE or piperaquine. Peak liver function tests, peak bilirubin, and peak parasitemia were defined as the highest value occurring after day 0.
1 × ULN). In Study QP16C04, MMV390048 40 mg (Cohort B1) or 80 mg (Cohort B2) was administered on day 8, with a 2,800 parasite inoculum. In Cohort B1 (n = 7), there were no ALT/AST elevations of grade 2 or higher. In Cohort B2 (n = 8), three participants showed ALT elevations; one severe (R502: 13. 0 × ULN; WHO grade 4) and two moderate (grade 2, R503: 4. 4 × ULN; R505: 2. 9 × ULN). This might appear to be a simple dose-response, with ALT/AST elevations more frequent at the higher MMV390048 dose. However, the same doses (40 and 80 mg) were tested in a Phase I study in healthy participants (ClinicalTrials. gov identifier: NCT02230579). In this case, there was no increase in ALT, with values similar to those obtained with placebo (Figure  5 ). This suggests that ALT increases were not a simple dose-response effect but related to the combination of malaria and drug.
This translated into a significantly increased relative risk of ALT elevations with acetaminophen doses > 6 g versus lower doses or no acetaminophen (Table  4 ). Notably, relative risk further increased  among participants with acetaminophen doses > 6 g and parasitemia > 10,000 parasites/mL blood (Table  4 ). Following the initial cases of ALT/AST elevations in studies QP13C14 and QP15C01, further investigation of samples from Study QP15C01 (cipargamin) showed an apparent temporal correlation between acetaminophen dosing and acetaminophen adduct levels (Supplemental Figure  3 ). However, the observed acetaminophen adduct levels (£ 0. 1 μmol/L) were not in the range associated with clinically relevant liver toxicity. Piperaquine. Piperaquine data were examined because it has no known DILI risk, despite extensive use in acute uncomplicated malaria.
DISCUSSION OF PRIOR EVIDENCE FOR LIVER ENZYME ELEVATIONS IN VOLUNTEER INFECTION STUDIES To further examine possible explanations for increased liver enzymes in the IBSM studies, we considered previous reports of ALT/AST elevations in VISs. This was not a formal systematic data review but aimed to extend the discussion of the observed liver enzyme elevations in the QIMRB IBSM studies. Relevant articles were identified by consultation with experts and investigators involved in VIS models. Also, a search was conducted of PubMed citations between June 1960 and September 2018 with the terms: challenge, inoculation, IBSM, CHMI, sporozoites, liver, toxicity, hepatotoxicity, malaria, aminotransferase, transaminases, challenge, and Plasmodium. Authors were not contacted for data sharing. Induced blood-stage malaria studies.
Enhanced consent should highlight the potential severity of ALT/AST elevations and the consequences of withholding key information. Where an NCE is to be administered, alcohol, drugs of abuse, and more generally other medication, should be strictly avoided during the study and the follow-up period if possible. Alcohol and drugs of abuse screening tests with immediate reading (breath tests and urine dipstick, respectively) should be performed not just at screening, but at key time points, for example, pre-inoculation or pre-dose. Participants with a positive test should be withdrawn from the study, but will need treatment with a standard antimalarial if already inoculated with malaria. Control group and comparable data from Phase I studies. A control arm, including either placebo or a registered antimalarial, would allow assessment of drug-dependent ALT/ AST elevations versus those caused by model conditions.
5] [86]  Biomarkers should be measured in the entire cohort, that is, including participants with and without elevated ALT/AST values, to allow comparison. Presentation of study results to standard format. Summarized laboratory safety data with standardized severity gradings, along with parasitemia levels, malaria clinical score, and concomitant medications for all VIS participants should be included in preliminary datasets provided to the Safety Review Team, presented in clinical study reports, and published with manuscripts as Supplementary Data. Publications should state the adverse event severity grading system used. For any participants with elevated ALT/AST, all key parameters should be fully documented/reported, including the time course of changes in liver enzymes, parasitemia, medications received, malaria clinical score, and pharmacokinetic/pharmacodynamic data.
Acknowledgments: We acknowledge the contributions of  Gerd A. Kullak-Ublick ,  John Pears ,  Michael Merz , and  Karen I. Barnes  for reviewing the manuscript and input during discussions with  Terry Shapiro ,  Charles Wells ,  Isaie Reuling ,  Sophie Biguenet , and  Stephan Duparc. We also thank  Ria Woo  and  Emilie Rossignol  for their dedicated support in collating the data used in this analysis and  Peter O'Rourke  for statistical advice. The trials described in this study are.
9 × ULN) ULN) R104, grade 4, day 12 (13. 4 × ULN) R104, grade 4, day 12 (17. 3 × ULN) R105, grade 4, day 13 (11. 2 × ULN) R105, grade 3, day 13 (6. 3 × ULN) QP14C02 NCT02223871 ACT-451840 500 8 1,800 D7 007, grade 2, day 15 (3. 3 × ULN) 007, grade 1, day 10 (1. 5 × ULN) QP14C11 NCT02281344 MMV390048 20 6 1,800 D7 None None QP14C12 NCT02389348 OZ439 + DSM265 200+100 13 1,800 D7 R201, grade 3, day 23 (5. 3 × ULN) R201, grade 2, day 23 (3. 1 × ULN) (n = 8) and R204, grade 2, day 12 (3. 7 × ULN) R204, grade 2, day 12 (3. 9 × ULN) 200+50 R103, grade 2, day 28 (3. 6 × ULN) R103, grade 4, day 28 (10. 9 × ULN) (n = 5) QP14C21 NCT02431637 Piperaquine 480 6 2,800 D7 None None QP15C01 NCT02543086 Cipargamin + 10 on D8 8 1,800 D8 5108, grade 4, day 20 (24. 1 × ULN) 5108, grade 4, day 20 (11. 1 × ULN) piperaquine 960 on D11-15 5101, grade 3, day 15 (5.
2 × ULN) 5101, grade 1, day 15 (2. 2 × ULN) 5103, grade 2, day 16 (4. 7 × ULN) 5103, grade 2, day 16 (2. 7 × ULN) QP15C05 NCT02431650 Piperaquine + 480 11 2,800 D7 R110, grade 3, day 15 (9. 3 × ULN) R110, grade 3, day 15 (5. 7 × ULN) OZ439 R109, grade 2, day 17 (4. 2 × ULN) R109, grade 1, day 10 (2. 3 × ULN) or primaquine † QP15C20 NCT02867059 SJ733 150 (n = 7) 15 2,800, Cohort 1 D8 R101(G), grade 4, day 15 (14. 6 × ULN) R101(G), grade 3, day 15 (8. 3 × and 600 ULN) (n = 10) ‡ 2,300, Cohort 2 R102, grade 3, day 16 (6. 3 × ULN) R102, grade 2, day 16 (3. 0 × ULN) R107, grade 2, day 20 (4. 2 × ULN) R107, normal (1. 0 × ULN) R208, grade 2, day 10 (3. 0 × ULN) R208, grade 1, day 10 (1. 6 × ULN) QP16C04 NCT02783833 MMV390048 40 (n = 7) 15 2,800 D8 R502, grade 4, day 13 (13. 0 × ULN) R502, grade 3, day 13 (8.
0 × ULN) and 80 R503, grade 2, day 10 (4. 4 × ULN) R503, grade 2, day 9 (2. 9 × ULN) (n = 8) R505, grade 2, day 17 (2. 9 × ULN) R505, normal (1. 2 × ULN) ALT = alanine aminotransferase; AST = aspartate aminotransferase; ULN = upper limit of normal. The WHO severity grading was used for ALT and AST: grade 1, 1. 25-2. 5 ×ULN (mild); grade 2, 2. 5-5×ULN(moderate); grade 3, 5. 1-10 ×ULN (severe); and grade 4, > 10 ×ULN (very severe). * The trials described in this study are registered at ClinicalTrials. gov, with identifiers beginning with NCT or at http://www. anzctr. org. au with identifiers beginning with ACTRN. Cipargamin was previously known as KAE609.
Further studies are therefore required to investigate the correlation between the presence of P. minimum and the TTX content in bivalves. The gastropod sample with a TTX concentration between LOD and LOQ (17 ET2M 773) was sampled in November 2017 in a natural whelk bed situated in the English Channel (west of the Cotentin Peninsula), close to Rimains Island near the town of Cancale. Comparing the GPS data with French coastal maps allowed us to estimate the mean water depth of this site  [37]. Depths vary greatly depending on the tidal coefficients (between 3. 5 and 17 m). The mean depth was estimated at about 10 m at that sampling site. Sampling was generally carried out at depth greater than 15 m and sometimes at more than 40 m. Among all the whelk samples, the 17 ET2M 773 sample was collected at the greatest depth as was sample 18 ET2M 137 (TTX result below the LOD of the method).
Since 2019, the French scheme for the monitoring of emerging toxins (EMERGTOX) continues to survey TTXs in bivalves in 11 mainland coastal areas. This study also provides TTXs data for gastropods. These results will be useful considering the lack of European data for this class of molluscs. This study also provided the first data on TTX distribution in whelks and should stimulate further investigation. This study acted on several EFSA recommendations  [9]. New European data on the occurrence of TTX and its analogues in bivalve molluscs and gastropods are now available. Our data for France complement those obtained in several neighbouring countries and thus enhance European databases.
In addition to TTX and its analogues, transitions for arginine (Arg) and hydroxy-arginine (OH-Arg) were incorporated in the method and monitored. These amino acids suppress the TTX response in MS  [21]. A mass resolution of 0. 7 Da (full width at half maximum) was set for the first and the third quadrupoles (Q1 and Q3). Instrument control and acquired data were handled by a computer equipped with TSQ Tune Master version 2. 6. 0, Xcalibur version 4. 1. 31. 9 and TraceFinder™ version 4. 1-EFS (Thermo Fisher Scientific). 1 Q: Quantitative transition; q: qualifier transition.
Acknowledgments: We would like to express our gratitude to the  Directorate General for Food (DGAl-French Ministry of Agriculture and Food)  for its facilitating role and without whom this work would have not been possible, and especially to  Pauline Favre  and  Mathilde Palussière. The authors sincerely acknowledge all the Resources and  Environment Laboratories (LER)  at  IFREMER  and the coordination of the  French programme for monitoring emerging toxins (EMERGTOX scheme ) for the collection of samples and for organizing the sampling campaigns. We also would to express our gratitude to the  REPHY-REPHYTOX  scheme, and in particular,  Maud Lemoine  and  Nadine Neaud Masson , for the information on hydrological and phytoplankton data discussed in this report. We extend special thanks to the  Metal and Mineral Trace Elements  ( ET2M ) unit at  ANSES  for providing gastropods and for preparing them.
Funding: R. J. is funded with a three-year PhD fellowship from  Région Occitanie and University of Toulouse. Our research in the domain of nanocarriers is funded by the  "Agence Nationale de la Recherche " (program  ANR-18-CE18-0011 ) and by the " Région Occitanie" (program D-SKIN , No. 2019-0019011695 ). The APC was funded by institutions (CNRS, INSERM, and the  University of Toulouse ).
The cost of each drug was estimated according to the French Medication Insurance database. Furthermore, patient's comorbidities were studied using Charlson's comorbidity index. In order to estimate the economic impact of PIM, we used the list of alternative appropriate drugs suggested by EU(7) PIM list and French National Health Authority. An incremental cost per patient was calculated by the difference in costs between PIMs and alternative drugs. Results: A total of 7768 lines of drug prescriptions were analyzed. The mean age was 87. 6 ± 7. 6 years. About 70% (n = 872) of residents received more than five drugs. We identified 959 residents (77. 3%) with at least one PIM. The mean cost of PIM was 0. 58 euros versus 0. 48 euros for alternatives. PIM substitution by alternatives led to save 12 centimes/resident/day.
Study Population We carried out a retrospective study on 19 nursing homes in the West Occitanie region. We only included nursing homes that have a dispensary in order to ensure we were only looking at establishments using medications with a price fixed at the national level. Nursing homes with in-house pharmacies were excluded from this study. For each resident, the following socio-demographic and clinical data were collected: -Age; -Sex; -Iso-Resource Group (IRG): IRG measures the degree of independence on a scale of 1 to 6 for an elderly person: IRG 1 corresponds to total dependency; -Medical history and comorbidities; -Long-term prescriptions and their dosages. We have excluded prescriptions involving medications indicated in acute pathologies (antibiotic therapies, etc. ). We have also excluded adjunctive drugs (e.