dataesr/scientific-paragraphs-categorization huggingface dataset:
3% Triton X-100, sections were incubated with appropriate secondary antibody conjugated to AlexaFluor for 2 h at room temperature. In certain experiments, sections from DRG and spinal cord were incubated with a biotinylated IB4 (1:500) followed by incubation with streptavidin-conjugated to AlexaFluor 555  (1:2000). Images were collected under either a DV Elite fluorescent microscope (GE Healthcare) and SoftWoRx software (GE Healthcare), or a Leica TCS SP5II confocal microscope and LAS AF Lite software (Leica Microsystems). ImageJ (National Institute of Health) was also used to measure the size of DRG neurons.
Data were collected through an Axopatch-2B amplifier or Multiclamp 700B (Axon CNS, Molecular Devices) with program pClamp 10. 4 (Molecular Devices). Slices were continuously perfused with oxygenated ACSF at a flow rate of 2 ml/min with peristaltic pump or through reservoirs by gravity feeding. Field potential (EPSP) was recorded using a glass microelectrode filled with ACSF (resistance: 1-3 M⍀) or 2 M NaCl internal solution composed as 140 mM KGlu, 1 mM K-EGTA, 0. 1 mM CaCl 2 , 2 mM MgSO 4 , 10 mM HEPES. Approximately 10 min of stable baseline was recorded before drug application. Biphasic current pulses (0. 2 ms duration for 1 phase, 0. 4 ms in total) were delivered in 10 s intervals through a concentric bipolar stimulating electrode (FHC) placed in the middle of stratum radiatum to stimulate the Schaffer collateral fibers.
Signals were digitized at 20 kHz and not filtered. Input/output curves were obtained for each slice using stimulus intensity from threshold (usually 0. 02 mA) to a maximum of 0. 4 mA. Test pulse intensities were adjusted to evoke EPSP ϳ35% of maximal response. The slope of EPSP was measured from the initial phase of negative wave. The inhibition ratio was calculated as percentage of the value after application of drugs in comparison with the value of control (before drug application). Each data point was measured as the average of three consecutive traces. Data were analyzed with Pclamp 10. 4, Microsoft Excel, StatView 5. 0. , and presented as mean Ϯ SEM. One-way ANOVA was used for multiple group comparison. Preparation of DRG neurons. Mouse DRG neurons were prepared from 1-to 2-month-old NOP-eGFP mice.
2 mM), penicillin G sodium (0. 3 mM), and gentamycin (0. 1 mM) at 21°C. Whole-cell voltage-clamp recordings were performed on large size (diameter, 30 -40 m) mouse DRG neurons after acutely dissociation. All experiments were performed at room temperature (ϳ21°C). Whole-cell patch-clamp recordings were made using a MultiClamp 700B amplifier and analyzed offline with pCLAMP10. 4 software (Axon CNS, Molecular Devices). For current-clamp recording, the external solution was a modified Kreb's solution specified above. The internal solution was composed of 65 mM KCl, 80 mM KF, 5 mM KOH, 10 mM EGTA, 2 mM MgATP (pH 7. 35-7. 4 adjusted with KOH, and the osmolality verified as 295 mOsm/kg). Recording electrodes were pulled by P-87 puller (Sutter Instrument). The tip of resistance was 3-4 M⍀ in bath and the series resistance was Ͻ10 M⍀ after whole-cell configuration.
N/OFQ (1 M) was applied through a local perfusion system with the opening of the tube located ϳ150 m from the cell. Statistical Analyses. Baseline values for tail-flick latency before drug administration were analyzed by one-way ANOVA using mouse genotype as a between factor. The same approach was used for qPCR data. Thermal nociception data were analyzed by using three-way ANOVA with mouse genotype and drug treatment (SR16835) as between-subject factors and time course of morphine effect (0, 30, and 60 min) as a within-subject factor. The level of significance was set at p Յ 0. 05. Student Newman-Keuls post hoc tests were used where appropriate.
Acknowledgments This work was supported by  DGR  ( 2009-SGR-1003 ) and  MICINN  ( FIS2012-394-C02-01 )(RR), and  NSF  grant  CHE-1112564  (JTH). Supporting Information Available: Discussion of the procedure to obtain, from the instantaneous positions and velocities of a molecule, the corresponding translational, rotational and vibrational velocities. This material is available free of charge via the Internet at http://pubs. acs. org.
Acknowledgements We wish to thank  Jacques Villain  and  Hélène Bouchiat  for having given us the opportunity to present our work in this dossier of Comptes rendus Physique dedicated to the memory of  Jacques Friedel. We would also like to associate several colleagues and students who have participated at some point in the elaboration of the tight-binding model presented in this article:  Ricardo-Guirado López  for his contribution to the magnetism of transition metal clusters,  Andrzej Oleś  for his expertise in the  Hartree-Fock Hamiltonian and Coulomb interaction ,  Gabriel Autès  for the implementation of Green function formalism in the context of electronic transport using our magnetic TB model,  Chu Chun Fu  and  Romain Soulairol  for introducing us to the complex world of magnetism and defects in Fe-Cr alloys,  Timo Schena  for his contribution to the implementation of  Dzyaloshinskii-Moriya  interaction in a TB scheme,  Dongzhe Li  and  Alexander Smogunov  for their important contribution to the modelling of magneto-crystalline anisotropy in transition-metal nanostructures.
Acknowledgments. The authors especially acknowledge the contributions of  Dr Teresa Aguado , who coordinated MVP-related activities at World Health Organization (WHO) headquarters in Geneva from the inception of the project in 2001 until her retirement in 2012. Disclaimers. 1) The authors and editors alone are responsible for the views expressed in this publication and they do not necessarily represent the views, decisions, or policies of the institutions with which they are affiliated; 2) The designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of PATH or the WHO concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.
Finally, the ANM method needs a starting point. In our case, a periodic orbit of the underlying linear system can be used as a first point (one orbit) for initiating continuation. The reader is referred to  [4] [5] [6] , for the details concerning the principle and the implementation of the ANM in the classical quadratic framework. The MANLAB interactive package  [20] , which supports the proposed ANM continuation algorithm including bifurcation detection and branch switching, has been used to solve this quadratic algebraic system. Note that to reduce the numerical cost of the ANM, Fast Fourier Transform (FFT) algorithm has been implemented to compute efficiently the quadratic term Q ðU; UÞ with a passage in the time domain as in the Alternating Frequency-Time HBM method.
, x ar ). Conversely, given a conjunction of positive atoms ϕ, we denote by D ϕ its canonical database, that is the structure with domain the variables of ϕ and whose tuples are precisely those that are atoms of ϕ. Let A and B be structures. A homomorphism h from A to B is a map from A to B such that for every relational symbol R of arity r and every r-tuple (a 1 , a 2 ,. , a r ) of elements of A such that R(a 1 , a 2 ,. , a r ) holds in A we have that R(h(a 1 ), h(a 2 ),. , h(a r )) holds in B. The product A ⊗ B is the structure with domain A × B such that for every relational symbol R of arity r and every r-tuples (a 1 , a 2 ,. , a r ) of elements of A and (b 1 , b 2 ,. , b r ) of elements of B, we have that R (a 1 , b 1 ), (a 2 , b 2 ),. , (a r , b r ) holds in A ⊗ B iff both R(a 1 , a 2 ,.
, π(x m ) ∈ B, the map h π is a homomorphism from D ψ (the canonical database) to A, where h π (x) := π(x) , if x is a universal variable; and, σ x ( π| Yx ) , otherwise. (Here, Y x denotes the set of universal variables preceding x and π| Yx the restriction of π to Y x. ) Clearly, A |= ϕ iff the existential player has a winning strategy in the (A, ϕ)-game against the so-called full (rectangular) adversary A × A ×. × A (which we will denote hereafter by A m ). We say that an adversary B of length m dominates an adversary B of length m when B ⊆ B. Note that B ⊆ B and A |= ϕ B implies A |= ϕ B. We will also consider sets of adversaries of the same length, denoted by uppercase greek letters as in Ω m ; and, sequences thereof, which we denote with bold uppercase greek letters as in Ω = Ω m m∈N.
This pilot study was conducted to assess the utility of using a health insurance database for the automated detection of waterborne outbreaks of acute gastroenteritis (AGE). The weekly number of AGE cases for which the patient consulted a doctor (cAGE) was derived from this database for 1,543 towns in three French districts during the 2009-2012 period. The method we used is based on a spatial comparison of incidence rates and of their time trends between the target town and the district. Each municipality was tested, week by week, for the entire study period. Overall, 193 clusters were identified, 10% of the municipalities were involved in at least one cluster and less than 2% in several. We can infer that nationwide more than 1,000 clusters involving 30,000 cases of cAGE each year may be linked to tap water.
Small-scale clusters, difficult to identify in the field, probably go unnoticed. Improvement in the surveillance of the risk of waterborne diseases thus requires an increased capacity to detect AGE case clusters (Figure  2 ). The development of medical-administrative databases provides an opportunity to do so. Since 2009, Sniiram (a national medical information database)  (Tuppin et al. )  has been used to produce a daily estimate of the number of AGE cases seen by doctors (cAGE) (Bounoure et al. ) throughout France, at the scale of the municipality. InVS already uses this indicator to validate and retrospectively characterize outbreaks reported or suspected by local health authorities  (Rambaud et al. ). This new approach to the surveillance of waterborne disease risks in France uses Sniiram to search routinely for cAGE case clusters.
Health data The method of identifying cAGE cases from Sniiram data was   Gironde. The Puy-de-Dôme has fewer towns, and a higher percentage of them have small populations (Table  1 ). The number of events involving accidental microbiological pollution of the water supply in these sectors is close to the national mean, and did not differ significantly between these districts  (Beaudeau ). The distributed water is mainly of underground origin in the three districts, as 99. 1% of the water supply network use this type of resource in Isère, compared with 99. 2% in Gironde and 98. 1% in Puy-de-Dôme. Distributed water meets the microbiological standards for more than 95% of the supplied population in Isère and Gironde, and for more than 90% in Puy-de-Dôme.
described earlier (Bounoure et al. ). The Sniiram database covers the French population almost exhaustively and makes it possible to obtain individual medical consultation data on a same-day basis, localized to the patient's town of residence. Cases with consultations more than 50 km from their home are excluded. A survey of the customers of several pharmacies (Bounoure et al. ) estimated this method's sensitivity and specificity at 0. 89, compared with cAGE cases seen by a doctor certifying the diagnosis according to the consensus syndrome definition (Majowicz et al. ). Cumulative cases per town are tallied weekly (Monday to Sunday), before the search for clusters. A weekly observation period fits the duration of waterborne disease outbreaks (1-3 weeks) better and avoid the effects.
Background: Artemisinin-resistant Plasmodium falciparum has emerged in the Greater Mekong sub-region and poses a major global public health threat. Slow parasite clearance is a key clinical manifestation of reduced susceptibility to artemisinin. This study was designed to establish the baseline values for clearance in patients from Sub-Saharan African countries with uncomplicated malaria treated with artemisinin-based combination therapies (ACTs). Methods: A literature review in PubMed was conducted in March 2013 to identify all prospective clinical trials (uncontrolled trials, controlled trials and randomized controlled trials), including ACTs conducted in Sub-Saharan Africa, between 1960 and 2012. Individual patient data from these studies were shared with the WorldWide Antimalarial Resistance Network (WWARN) and pooled using an a priori statistical analytical plan.
Identification of studies for potential inclusion Individual patient data A literature review was conducted in PubMed in March 2013 and updated in 2014 to identify all published clinical trials of antimalarials since 1960. All antimalarial clinical trials published since 1960 were identified by the application of the key terms ((malaria OR plasmod*) AND (amodiaquine OR atovaquone OR artemisinin OR arteether OR artesunate OR artemether OR artemotil OR azithromycin OR artekin OR chloroquine OR chlorproguanil OR cycloguanil OR clindamycin OR coartem OR dapsone OR dihydroartemisinin OR duo-cotecxin OR doxycycline OR halofantrine OR lumefantrine OR lariam OR malarone OR mefloquine OR naphthoquine OR naphthoquinone OR piperaquine OR primaquine OR proguanil OR pyrimethamine OR pyronaridine OR quinidine OR quinine OR riamet OR sulphadoxine OR tetracycline OR tafenoquine)) through the PubMed library.
Where a specific site was not reported in the manuscript, the capital city of the country was used as the default location. Countries were grouped into four sub-regions: East; West; Central; and South Africa, as reported in the WHO World malaria report 2014  [1]. All research groups in the systematic review were contacted to share the entire dataset of their study with WWARN. Those who had contributed studies previously to the WWARN data repository were also invited to participate and asked whether they were aware of any unpublished or ongoing clinical trials involving ACTs, and these additional unpublished studies were also requested. Studies were included in the meta-analysis provided that they were: i) prospective clinical efficacy studies of uncomplicated P. falciparum (either alone or mixed infections with P.
vivax); ii) clinical trials conducted in SSA with one of the following three ACTs: artemether-lumefantrine (AL) (six-dose), dihydroartemisinin-piperaquine (DP) and one of the three formulations of artesunate-amodiaquine (AS-AQ): fixed dose combination (ASAQ-FDC), non-fixed dose combination in a loose formulation (ASAQloose NFDC) or non-fixed dose combination in a co-blister formulation (ASAQ-coblistered NFDC); and iii) parasitaemia was sampled at least on days 2 (48 hours) and 3 (72 hours) following treatment. Individual study protocols were available for all trials included, either from the publication or as a metafile submitted with the raw data. All data were uploaded to the WWARN repository and standardized using a methodology described in the clinical module data management and statistical analysis plan  [31].
Assessment of risk of potential bias In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the risk of bias within studies was assessed based on: 1) study design (randomization, sequence generation, blinding); 2) microscopy methodologies for parasite quantification; and 3) the proportion of patients with (a) missing outcomes (missing outcome on days 2 and 3) and (b) missing baseline covariates (age, temperature, haemoglobin/haematocrit). To assess whether the non-availability of some individual participant data could have biased the results, we extracted data on PPRs from studies not providing individual patient data and performed a two-stage meta-analysis of proportions using logit transformation; a continuity correction of 0. 5 was applied to studies with zero cell count using meta package.
In Miandrivazo (Madagascar), the reported PPR was 10. 3 % in 2006  [51]  but less than 1 % in a subsequent trial in the same region (Tsiroanomandidy)  [52]. In Yaoundé, a PPR of 30 % was reported in 2005  [53] ; however, in a study conducted at the same site 7 years later  [54] , the PPR was 2. 9 % (95 % CI: 3. 7-27. 2, 2/68) suggesting that the high PPR observed in our dataset could have been an artefact. High day 3 PPR does not necessarily relate to a change in parasite susceptibility to artemisinin; other factors, such as declining immunity  [55] , poor drug quality  [56]  and variable quality of microscopy  [57]  can play major roles. Studies with more intense blood sampling are needed in areas of delayed parasite clearance  [10, 12]. These will require better definition of the parasite clearance, complementary in vitro testing  [58]  and molecular analysis  [13]  to rule out any change in artemisinin susceptibility.
Our analysis has a number of limitations. First, the literature search was limited to prospective clinical trials indexed in PubMed and some relevant studies may have been overlooked. However, we actively looked for relevant trials (unpublished) and the research groups contacted represent the majority of the malaria community, which is relatively small and highly interactive. It is highly unlikely that any studies were missed. The assessment of publication bias (PB) showed that effect sizes were symmetrical suggesting low risk of bias in studies included. Of the 140 trials identified, individual patient data were available for inclusion for 71 of the published studies (50. 7 %). To address this potential bias, included studies were compared with the published studies that were not available.
There were no apparent differences in patient population and/or outcomes between the studies included and those where individual patient data were not available. Reassuringly, the results from twostage meta-analyses, which combined studies with and without individual patient data, were also similar to the results obtained from studies where only individual patient data were available, suggesting that systematic attrition bias was unlikely. A second issue is that, although the days of follow-up were recorded in the studies, the actual time of blood collection was not. Daily samples were taken over a range of times and the interval between days is likely to have varied significantly from the desired 24-, 48-or 72-hour timelines. Third, the data used rely on quantitative microscopy and quality control on microscopy procedures were reported in only 60 % of the studies.
Accurate recording of the time of sampling, harmonizing microscopy procedures and appropriate quality control procedures could greatly improve the precision of the parasite clearance time  [11]. To facilitate this process, a new microscopy procedure has been developed recently to improve comparability of results between groups  [59]. Finally, no data on drug levels were available to assess whether patients achieved therapeutic blood concentrations. However, absorption of artemisinin derivatives in uncomplicated malaria is usually good and in the majority (89 %) of studies, drug administration was observed fully or partially by the clinical team. This large dataset provided a unique opportunity to identify a threshold for day 3 parasite positivity based upon African studies, below which artemisinin resistance is highly unlikely.
Neither Novartis or Eisai funded this specific study. RBL declares grants and personal fees from Boston Scientific, Allergan and Novartis, personal fees from BMS, Labrys Technologies, Electrocore and Alder Biopharmaceuticals, and grants, personal fees and stock options from eNeura. HB declares being an investigator for and on the advisory board of Janssen, an investigator for Lilly, Medivation, Merck, Sanofi, Servier and Tau Therapeutics, an advisory board member of Pfizer, Novartis, and Lundbeck, a consultant for Baxter, Lilly and Merck, and a consultant for and advisory board member of Nutricia. AL declares being a consultant for Janssen and honoraria or travel fees from Eli Lilly and Bial. There are no patents, products in development or marketed products to declare. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors.
Small changes to elements of this criterion, such as the threshold for impairment and the number of sub-threshold cognitive test results required, can greatly affect the prevalence of MCI found  [20]. A further issue is the use of only global scales by many studies, with limited forms of neuropsychological testing less likely than comprehensive test batteries to reliably identify MCI  [21]. We have recently developed an international consortium-Cohort Studies of Memory in an International Consortium (COSMIC)  [22] -which has brought together data from cohort studies of cognitive aging internationally. The goal of this study was to harmonize these data and apply uniform diagnostic criteria to more reliably estimate MCI prevalence across different geographical and ethnocultural regions. We present data from three studies in USA, four in Europe, two in Asia, and two in Australia.
Demographics Information included age, sex and education. Education data were harmonized by forming a variable with four categories: Less than high school completion; high school completion; technical or college diploma; university degree (as shown in S6 Table ). Note that we use the term college diploma in an international context, referring to courses of less duration and standard than a bachelor's degree that are typically provided by technical, applied, or more vocationally oriented institutions rather than universities. Each of the contributing studies helped determine how the data representing their local education system was best transformed to the four categories we used.
The adjusted test scores were then transformed to Z-scores using the mean and SD of the study sample as normative values. It has been argued and shown that more equivalent and accurate comparisons of cognitive performance between countries are facilitated by the use of country-specific norms  [40]. However, for many countries, including those represented by the studies contributing to this investigation, there are no published normative data available. Indeed, a survey of the COSMIC member studies shows that even when norms for particular cognitive tests are available they are often not age-appropriate for elderly samples. Thus, the largely incomplete availability of external norms helped determine our choice to use study-specific internal norms. After forming Zscores for the tests on the basis of these internal norms, composite scores for each domain were calculated as the mean of the Z-scores of the relevant component tests.
Classification of MCI MCI was classified using the four generally accepted criteria: absence of dementia, no or minimal functional impairment, subjective memory/cognitive complaint or concern, and objective cognitive impairment  [12]. Most studies reported making classifications of dementia using DSM-IV criteria (see S16 Table ). Note that a number of studies excluded any individuals with dementia at the recruitment stage of their study. Functional impairment was defined as dependence in two or more harmonized IADL items (the handling of missing data is detailed in S1 Text). Cognitive complaints or concerns were determined as above. Objective cognitive impairment for each cognitive domain was a score within the bottom 6. 681% of the scores for that domain within the relevant study's sample, which is the equivalent of impairment being defined as scores more than 1.