dataesr/scientific-paragraphs-categorization huggingface dataset:
Models trained with TerraClimate variables performed best, statistically, for D. reticulatus. For both species, models built with bioclimatic variables were consistently among the lowest performing, especially when used in conjunction with RF (Figs. 2, 3 ). They also predicted the highest proportion of Europe as suitable for I. ricinus. For both I. ricinus (X 2 = 9. 05; df = 3; P = 0. 03) and D. reticulatus (X 2 = 11. 35; df = 3; P = 0. 01), the areas predicted as suitable were influenced by the explanatory variables, as each set captured different portions of their niches (Additional file 7, 8). For both species, maps produced with MODIS variables had a coarser appearance, while the suitability of ticks using the interpolated datasets had a smoother gradient of suitability across Europe. Models trained with MODIS variables also had an artefactual line across northern Scandinavia, due to cloud, ice and snow cover, which interrupted suitability predictions  [64, 65].
Models trained with TerraClimate data from the extent of Europe and run using a MaxEnt modelling algorithm best described the current distribution of both I. ricinus and D. reticulatus. For I. ricinus, large regions of Central and Western Europe were considered suitable with decreasing suitability towards the Northern and Eastern Regions. There were limitations in the ability to capture the distribution for particular regions; for example, the suitability in Eastern Finland is likely greater than presented, as well as the northern region of Spain. For D. reticulatus, the area predicted as suitable is more conservative compared to their expected range, especially in Southern Europe. However, the high predicted climatic suitability in Germany and Poland accurately reflects the high abundance of D.
Discussion This study aimed to compare multiple modelling approaches in their ability to capture the niche of two important tick species in Europe, I. ricinus and D. reticulatus, to assess their potential usefulness in predicting spatial variability in the climate suitability. Using an array of modelling approaches and datasets, and three validation/verification methods, it was possible to identify the most useful model for each species, balancing statistical performance and plausibility. However, the overall evaluation showed that the performance and predictive ability of SDMs is highly dependent on the modelling algorithm and input variables and, although some models were broadly accurate in some regions, there was limited success in defining the species distribution to a localised level using any modelling approach (Figs.
2, 3, 4  and 5 ). This work also demonstrates the importance of using different validation techniques when assessing the overall performance of SDMs. The predictive performance of each modelling approach was dependent on the validation technique used. There were differences when considering the internal vs. external validation here, showing the importance of considering both. Independent validation provides the benefit of assessing the predictive ability of the model against an external dataset, but this is often omitted from SDM studies  [55, 66, 67]. The use of reliable citizen science may assist in the generation of more independent datasets for SDM validation  [55]. Furthermore, as shown here (especially for RF models), models may perform well statistically, but the resultant accuracy of the maps generated may be poor.
Inspection of the predictive performance of the model by local experts can be helpful in this respect  [60]. The uncertainty index also highlighted regions of unreliability in the predictions. Model evaluation therefore should be based on multiple validation metrics and techniques, adding confidence to SDM conclusions. The influence of modelling algorithm shows that there is not necessarily an ideal approach for all species. Within SDM literature, MaxEnt is often used without considering alternatives  [68]. However, recent interest in this area has shown that the choice of algorithm can heavily influence the predictive ability of the SDM, and this is dependent on the species occurrence data and training extent  [17, 42]. For example, here RF produced plausible predictions for D. reticulatus but overfitted and underestimated suitability of Europe to I.
First, although there has been a recent increase in the use of satellite imagery in vector and vector-borne disease modelling, it often has a short temporal range (2000-present) and contains artefacts due to cloud, ice and snow cover  [64, 65]  (Additional files 7, 8). In contrast, the interpolated datasets are easily downloaded, span a greater temporal range (1970present depending on the source) and are free from the aforementioned artefacts  [73] [74] [75]. Furthermore, interpolated datasets have a greater range of variables available which can be used to describe the environmental constraints on the species, such as vapour pressure and deficit  [8, 10]. The main limitation of interpolated data is that it is derived from networks of ground weather stations and hence there are inherent issues associated with collinearity  [76].
This, and the possibility that species may adapt to local climatic conditions (e. g. as has been demonstrated with I. ricinus  [77, 78] ), suggests that if researchers require more localised, sensitive tick predictions, regional SDM may be more appropriate  [14, 79, 80]. Nevertheless, the validation completed here demonstrates that broadly accurate models can be developed for larger regions, which may be useful for larger scale climate impact assessments. The use of singular climatic datasets, such as those used here, may not fully capture the environmental niche of the ticks. Although relative humidity and temperature are key variables influencing tick presence, habitat and host variables are also important determinants  [79, 80]. For example, the sandy west coast of Denmark had greater predicted suitability for I.
ricinus compared to the wooded eastern regions of Denmark when models were trained with bioclimatic variables, which is the opposite of the known distribution of I. ricinus in this region  [79]. These local discrepancies could result from the lack of habitat variables. The inclusion of additional variables such as host distribution or abundance, vegetation cover and soil type may increase the accuracy of SDM at local levels  [79, 80]. However, these data are often not freely available at high resolution across the whole extent of Europe and, more importantly, cannot be used in predicting future suitability because of the uncertainty in anthropogenic changes, extreme weather events and host distributions  [81] [82] [83]. As SDMs work by defining the species occurrence dataset in environmental spaces, inaccuracies in this dataset may cause erroneous results.
Availability of data and materials Occurrence datasets used for model development are available in the supplementary material. The occurrence datasets and explanatory variable datasets used for model development and internal validation are available under a GPL-3 licence from  [89]. Request to access and reuse the secondary datasets used for external validation must be made directly to the authors of the primary research. The ODMAP (Overview, Data, Model, Assessment, Prediction) protocol for reporting SDM was completed (Additional file 9: Text S1)  [90]. The R scripts are available upon request to the corresponding or senior author.
Study Design, Setting, and Participants This was a monocentric study that employed a prospective randomized controlled clinical trial design with two groups-an experimental group (EG) and a control group (CG). The observer was blinded. The study protocol, including details of randomization and intervention, as well as the statistical analysis plan, was registered at http://ClinicalTrials. gov (accessed on 4 April 2013) (NCT01822938) and published previously  [14]. This study was conducted in Limoges, France, with participants recruited from the physical medicine and rehabilitation services at the hospital center. The study adhered to the Good Clinical Practice Guidelines of the Declaration of Helsinki and followed the CONSORT 2010 statements for randomized trials of non-pharmacological treatments.
Assessments were performed at baseline (T0), 6 months (T1), and 12 months (T2), the first patient was enrolled on 29 April 2013, and the last end-of-trial consultation was conducted on 17 January 2018. Each patient participated in the study for 12 months, and the total duration of the research was 4 years, 8 months, and 18 days. All subjects who met the eligibility criteria provided written informed consent in accordance with the study protocol. Using a secure internet connection, participants were randomly allocated (in blocks of variable size) to either an EG that received regular personalized coaching on PA or a CG that received standard care. The randomization process was guaranteed through an individual user ID and password, as well as encrypted data transmission to the randomization platform of the Clinical Research Unit of the Limoges University Hospital.
Acknowledgments: We would like to thank the following team members for contributing to the success of this trial: the  Limoges University Hospital Centre  and all the members of the Rehabilitation Physical Medicine service; the  Biostatistics Department of the Limoges University Hospital (CEBIMER) ; the stroke mobile team HEMIPASS 87 and particularly  David Bernikier ; the  Limousin Regional Council  for its financial support for this project; all the patients who agreed to participate in this study.
Statistical analyses Data are presented as mean ± SD. Normality and homogeneity of variance for all data were checked with the Shapiro-Wilk and Levene's tests, respectively. For statistical analyses, an analysis of covariance (ANCOVA), with group as a between-subject comparator (SG and CG), and baseline data as a covariate, was computed due to significant baseline differentials across all baseline values between the two groups. Bonferroni post hoc tests were used if main effects or interactions were identified. This method has been proposed as the most sufficient statistical approach for the analysis of continuous outcomes   1 ). All analyses were performed using Statistical Package for Social Sciences (SPSS) version 24. 0 (SPSS Inc. , Chicago, Illinois, USA).
Statistical analysis The statistical analyses were performed using SPSS version 25. 0 (IBM Inc. , Armonk, NY, USA). Frequency statistics were performed to characterize the sample. Data are presented as mean (standard deviation) for continuous variables and frequency counts (%) for categorical variables. The characteristics of persons with and without DM were compared using the independent sample t-tests for continuous variables or χ 2 tests for categorical variables. The normality of variable distribution was diagnosed with a Kolmogorov-Smirnov test with Lilliefors correction, and the homogeneity of variances was checked with Levene's test. Multivariable data analytical methods were employed. The association of DM with FL was evaluated using logistic regression models with FL as the dichotomous outcome.
Strengths and limitation This study contributes to understanding how PA, chronic diseases, and pain impact FL among older persons with DM. The key strength is that the analysis used a large and representative sample of communitydwelling older adults in a novel SSA context where the link between DM and FL is poorly understood. Indeed, a valid tool was used to quantify FL. However, our findings should be considered in the context of several limitations. DM was self-reported and our analysis did not consider the severity of DM and thus under-reporting and misclassification are likely. The cross-sectional design utilized in this study did not establish causal inferences. Future research would benefit from longitudinal data to validate these findings. The measurement of our key variables was based on retrospective self-reports and thus potentially introducing recall and social desirability bias into the findings.
Statistical Analysis The Graph Pad Prism 9. 5. 1 (733) software (Graph Pad Software, Inc. , La Jolla, CA, USA) was used in order to perform the statistical analysis. The variables were expressed as follows: quantitative as mean values (MV) ± standard deviation (SD) and categorical data as percentages. Chi-squared test was used to compare groups, when categorical variables were analyzed. The unpaired t-test was calculated, with confidence interval CI = 95%, p ≤ 0. 05 being considered statistically significant. The nonparametric Pearson's correlation test was performed with the calculation of "r" coefficient in order to assess the magnitude and direction of correlations. The relationship between variables was expressed as an equation of linear regression and graphs were consecutively drawn. Multivariate analysis was consecutively used to estimate the relationship between some independent variables either clinical data or biological parameters and one dependent variable represented by PVT.
Methods This was a subset analysis of data from ASPECT-NP, a randomized, double-blind, non-inferiority trial (ClinicalTrials. gov NCT02070757). Adults with vHABP/VABP were randomized 1:1 to 3 g ceftolozane/tazobactam or 1 g meropenem every 8 h for 8-14 days. Outcomes in participants with a baseline respiratory component of the Sequential Organ Failure Assessment (SOFA) score (R-SOFA) ≥ 2 (indicative of severe respiratory failure), cardiovascular component of the SOFA score (CV-SOFA) ≥ 2 (indicative of shock), or R-SOFA ≥ 2 plus CV-SOFA ≥ 2 were compared by treatment arm. The efficacy endpoint of primary interest was 28-day all-cause mortality. Clinical response, time to death, and microbiologic response were also evaluated.
Study design overview ASPECT-NP (protocol MK-7625A-008, ClinicalTrials. gov NCT02070757) was a phase 3, randomized, controlled, double-blind, multicenter, non-inferiority trial. Mechanically ventilated adults (≥ 18 years old) with nosocomial pneumonia were randomized 1:1, stratified by diagnosis (vHABP or VABP) and age (< 65 or ≥ 65 years old), to receive ceftolozane/tazobactam 3 g intravenously (IV) every 8 h or meropenem 1 g IV every 8 h, both adjusted for renal impairment. The study drugs were administered IV over 1 h for a duration of 8-14 days. Adjunctive linezolid 600 mg IV every 12 h (or a suitable alternative) was required for all participants until baseline lower respiratory tract (LRT) cultures confirmed the absence of Staphylococcus aureus. Adjunctive empirical therapy with amikacin 15 mg/kg IV daily was permitted for the first 72 h at study sites with ≥ 15% meropenem-resistant P.
Acknowledgements The authors thank the patients and their families and caregivers for participating in this study, along with all investigators and site personnel. They also thank  Dorothy McCoy, PharmD ,  BCPS, BCIDP , for medical writing assistance,  Dominik J. Wolf, MSc , for his insightful comments during the development of the manuscript, and  Michele McColgan , BA, for editorial assistance; all are employees of  Merck Sharp & Dohme LLC , a subsidiary of  Merck & Co. , Inc. , Rahway, NJ,  USA. Hospital Foundation  and has received consulting fees and honoraria from  MSD ,  Pfizer , and  Shionogi. J-FT  participated on an advisory board for  MSD ,  Pfizer , and  Shionogi  on treatment of HAP/VAP; has received research grants, consulting fees, honoraria, and travel support from MSD; was past chairman of the  ESCMID Study Group for Infections in Critically Ill Patients-ESGCIP ; and is the principal investigator of  BICCS (national research program  ( RCT BICCS PHRC 18-0316 ) on the benefit of Continuous infusion and combination therapy on the treatment of severe Gram-negative infections, including pneumonia.
Statistical analysis PRISM (GraphPad Software, San Diego, CA, USA) was used for statistical calculations. Sample sizes for behavioral and electrophysiology experiments were chosen based on previous reports  [35, 37, 45]. A posteriori sensitivity power analyses performed using G*Power 3. 1 indicated that the chosen sample size allows detection of a small effect (f = 0. 165 to 0. 23) for coat state evaluation, a medium effect (f = 0. 474) for hyperthermia and western blot analysis (f = 0. 4 to 0. 468), and a medium to large effect for behavioral (f = 0. 317 to 0. 52) and electrophysiology (d = 0. 53 to 0. 635) experiments and for HPLC analysis (d = 0. 61 to 1. 75), with 80% power assuming a 5% significance. Sucrose preference, social interaction, object location, elevated-O maze, Western blot experiments and HPLC analysis after tryptophan supplementation were analyzed using two-way ANOVA followed by Tukey's, Sidak's or Dunnett's post-hoc tests.
Coat state, weight, and 5-HT1A receptor sensitivity were analyzed using repeated two-way ANOVA. HPLC analysis in basal conditions, depression z-scores and western blot experiments after tryptophan supplementation were analyzed using unpaired Student's t-tests. DRN 5-HT neuron firing data did not pass normality and were analyzed using Mann-Whitney tests. Statistical significance was set at P < 0. 05. Detailed statistics and sample size are given in supplementary tables.
ACKNOWLEDGEMENTS We thank  F. Machulka  at the rodent phenotyping facility of  Neuroscience Paris Seine  for expert assistance with animal care and  Jean-François Gilles  at the imaging facility of  Institut de Biologie Paris-Seine  for help with immunofluorescence imaging. Financial support was provided by the  Agence Nationale de la Recherche  ( ANR-13-SAMENTA-0003-01 ),  Institut National de la Santéet de la Recherche Medicale (Inserm) ,  Centre National de la Recherche Scientifique (CNRS) , and  Sorbonne Université. The authors declare no conflict of interest.
11 Holter monitoring was performed using SpiderView recorders and analysed using the SyneScope software (ELA Medical, Microport Group, Paris, France). The following data available on Holter analysis were collected: the standard deviation of all RR intervals (SDNN), the root of the mean squared differences of successive RR intervals (RMSSD), the percentage of consecutive RR intervals with difference over 50 ms (pNN50), and the mean diurnal and nocturnal heart rate. In order to avoid any effect of the heart rate on SDNN, we calculated for each patient the coefficient of variation of SDNN (CV-SDNN = SDNN/mean RR). All RR intervals excepted those including premature ventricular contractions were considered for the calculation of the previously described parameters. The primary endpoint was rehospitalization for acute heart failure (HFrH).
Another therapeutic option would be to target astrocytes directly. As mentioned, these cells are responsible for the maintenance of glutamate homeostasis. They recycle glutamate via its uptake by high-affinity Na +dependent glutamate transporters (e. g. , excitatory amino acid transporter 2 -EAAT2) and its conversion into glutamine  [34]. A class of β-lactam antibiotics has been identified as promoting the expression of glutamate transporters and enhancing glutamate uptake by astrocytes  [35]. Ceftriaxone was shown to not only stimulate glutamate uptake but also boost glucose utilization (and the concomitant [ 18 F]FDG-PET signal) in astrocytes  [8]. Ceftriaxone has been investigated as a potential treatment for excitatory events that occur in the brain of amyotrophic lateral sclerosis patients (NCT00349622; NCT00718393)  [36].
Methods We used data from the Etude Longitudinale Française depuis l'Enfance (ELFE) cohort study. Participating mothers gave birth in 2011 in a representative sample of 320 maternity hospitals in mainland France. Inclusion criteria were single or twin livebirths born after at least 33 weeks' gestation; mother's age at least 18 years; no plans to leave metropolitan France within 3 years. Mothers were interviewed face-to-face shortly after the child's birth. Fathers and mothers were both interviewed by telephone 2 months after the child's birth, reporting whether the father had the right to paternity leave and if yes, if he had taken or intended to take it. We used the Edinburgh Postnatal Depression Scale to assess post-partum depression among fathers and mothers at 2 months. Logistic regression models, using survey-weighted data and adjusted for confounders using inverse probability weights, yielded odds ratios (ORs).
Mothers were interviewed face-to-face shortly after the child's birth. Then, fathers and mothers were both interviewed by telephone 2 months after the child's birth. Attrition rates in the ELFE cohort were low, with a mean of 4•4% of mothers or fathers not completing the questionnaire for each wave of data collection. Compared with participating mothers, those who did not complete the questionnaire at 2 months were more likely to be younger than 25 years at the time of the child's birth, have no university degree, be unemployed or out of the labour force, have been born outside of France, or be single mothers. 12 The groups did not differ in parity, maternal health status before or after pregnancy, type of birth, or mean birthweight. Ethics approvals for data collection in maternity units and for each data collection wave during follow-up were obtained from the national advisory committee on information processing in health research, the national data protection authority, and, in case of invasive data collection such as biological.
Research in context Evidence before this study We searched Google Scholar, PubMed, and Science Direct databases for articles published in English and French between Jan 1, 2000, and Feb 1, 2022, using the search terms "paternity leave (family leave, parental leave)" and "depression (postpartum depression, mental health). " Narrowing our search to articles looking at paid paternity leave with no risk of job loss, we found only two articles specifically focusing on paid paternity leave and maternal or parental depression, with most articles focusing on the effect of mothers taking family leave. Studies have shown that paternity leave uptake is associated with fathers' involvement in family activities, chores, and bonding with the child, but evidence of the relationship with parental post-partum depression is scarce.
Statistical analysis Using data  13, 14  that were weighted to be representative of all families in which the father was eligible for paternity leave in 2011 in metropolitan France, we tested the association between paternity leave uptake and parental post-partum depression (mothers' and fathers' post-partum depression) at 2 months after the child's birth. Mothers had 4•2% missing data on covariates and fathers had 2•3%. For each of the two study samples, missing data were imputed using fully conditional specification. 24 As per Von Hippel's two-stage procedure, 14 imputed datasets were recommended and generated for each sample. 24 We did Bivariate analyses to test differences between the three exposure groups using χ² tests and Kruskal-Wallis tests, and we calculated global p values. Additionally, we did pairwise comparison χ² tests, in which each category in the exposure variable was compared with the other categories, and we calculated p values.
Lastly, we did a sensitivity analysis, using the same approach that has been outlined for the primary analysis (appendix pp 16-17), to assess the association between paternity leave uptake and mothers' post-partum depression among mothers whose partners also provided information on post-partum depression. No differences were observed from the primary results (appendix pp 16-17). Data management, statistical analyses, and GBM balance plots were done using SAS (version 9. 4) and R studio (version 4. 0. 5). Forest plots were created using Microsoft Excel (2016) Python (version 3. 6. 9).