dataesr/scientific-paragraphs-categorization huggingface dataset:
ACKNOWLEDGMENTS We thank  David A. Haake  for rabbit antisera against FlaA2, GroEL, and LigA,  Kristel Lourdault  for the characterization of the ligA mutant, and  Karim Sebastien  for his help with guinea pig heart punctures. Gabriela Pretre is a recipient of a  Bernado Houssay grant. This work (including a postdoctoral grant) was funded by the  FUI   14  ( Fonds Unique Interministériel) COVALEPT and BPIFrance. Azad Eshghi  was funded by a  Carnot grant  from the  Institut Carnot-Pasteur Maladies Infectieuses.
CLN from mice orally infected with 10 9 B. melitensis per mouse for 15 days were prepared for flow cytometry. Total CLN cell numbers were analyzed for the respective percentages (A) or absolute numbers (B) of dendritic cells (F4/80 -CD11c high MHCII int and F4/80 -CD11c int MHCII high ), CD11b high macrophages/monocytes (F4/80 -Ly6c + , F4/ 80 + Ly6c + and F4/80 + Ly6c -) and neutrophils (CD11b high Ly6G + ). (C) shows a representative contour plot of respective populations from a mock-infected or Brucella-infected mouse on CD19 -Ly6G -CD11b high (F4/80 vs. Ly6c) or CD19 -CD11b low/int F4/80 -NK1. 1 -cells (CD11c vs. MHCII). Populations shown in (A) were analyzed for their median fluorescence of (D) CD11b, (E) CD11c and (F) MHCII. Data represent mean and SEM of pooled results from two independent experiments with a total of 8 (mock-infected) and 9 (infected) mice per group.
Funding was provided by  Fondation pour la recherche Médicale  to AM; Institut National Pour la santé et la  Recherche Médicale  to  JPG BM JLM ;  Centre National de la Recherche Scientifique  to  JPG BM JLM ;  Agence Nationale de la Recherche  to  JPG KvB. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The first two issues have been resolved  (Price et al. , 2011; Stallard et al. , 2011)  through work supported by the UK National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs) thereby leaving only the definition of evident toxicity to be determined. To this end, the NC3Rs launched a global initiative involving 20 organisations with the aim of making evident toxicity more objective and transferable between laboratories. The group shared data on the clinical signs recorded during acute inhalation studies for 172 substances, the majority of which fell under the category of dusts and mists (from completed studies held in the archives of participating laboratories), and determined which signs have high positive predictive value (PPV) for severe toxicity or death at the next highest concentration (as described below).
Clinical signs recording system and data collection A clinical signs recording system was developed with the expertise of the working group and piloted at four UK CROs to record the clinical signs observed in individual animals during acute inhalation studies. A code was assigned to each clinical sign observed. The trial was extended to collect data on the clinical signs observed in individual animals during acute inhalation studies conducted at six international laboratories for classification and labelling purposes. Table  2  lists the clinical signs and codes included in the clinical signs lexicon. Data on the clinical signs observed in individual animals in acute inhalation studies for 172 substances, carried out at two or more concentrations, were provided by six international laboratories.
These data were from either LC 50 or ATC tests, but since the monitoring procedure is the same as for the FCP (i. e. daily monitoring of clinical signs for 14 days) they could be used to evaluate evident toxicity relevant for the FCP protocol. However, as detailed below, various exclusion criteria were applied to the data to make them more relevant to the FCP. Information was also collected on the type of substance (gas, dust, or vapour), as well as the test performed (LC 50 or ATC), and the outcome of the study (e. g. further testing or GHS classification) (Table  3 ). Although listing the severity of each clinical sign was an option in the survey, this was not recorded systematically, and, with the exception of body weight loss, for the sake of consistency was not further considered in the analysis of evident toxicity.
Harmonisation of the dataset Since archived data were collected from a number of laboratories there was some variation in the original terminology and signs recorded. Consequently a retrospective, harmonised list of clinical signs was agreed upon by all members of the working group for the purposes of analysis, and appropriate re-coding was made where needed. For example rales (dry) and rales (moist) were reassigned to code RN (noisy respiration). Varying descriptions of gait (shuffling, splayed, tiptoe) were grouped and assigned code AG (abnormal gait). Loose faeces and diarrhoea were deemed equivalent. Fig. 3. Fixed concentration procedure (FCP) method for dusts and mists for an example starting concentration of 5 mg/L  (Price et al. , 2010). Please note, the draft test guideline specifies that substances are tested at fixed concentrations that form the upper limit of the GHS categories.
Data analysis The data were analysed to determine whether there were any clinical signs (or combination of signs) observed in animals at a lower concentration that could predict toxicity at the next or higher concentration. Although evident toxicity is defined in the guideline as that which 'predicts deaths in a majority of animals at the next higher concentration', thereby enabling classification according to Outcome B in Fig. 3 , toxicity enabling classification according to Outcome A specifies only 2 or more deaths per group of 5, i. e. 40% or more. In view of this inconsistency, we agreed to define evident toxicity as that which predicts 'toxicity' at the higher concentration, itself defined as death, or severe toxicity requiring euthanasia, in two or more out of five animals. Since the dataset included studies that were conducted according to both the LC 50 and ATC protocols, there was wide variation in the concentration levels and intervals used.
The fold changes in concentrations for the FCP protocol range from two to ten-fold, depending on the substance class, while the fold changes in concentrations in the data set varied from 1. 02 to 20-fold. Therefore in this analysis tests were restricted to those with a two or greater fold difference in concentration between the lower and the higher exposure (Fig. S1 ). The parameters used to analyse the dataset are the positive predictive values (PPV), the specificity, the sensitivity and the false positive or negative rates where: ▪ PPV is defined as the proportion of times that the presence of the clinical sign at the lower concentration is predictive of toxicity at the next highest concentration ▪ Sensitivity is defined as the proportion of 'toxicities' (death of two or more animals) at the higher concentration that are associated with the clinical sign at the lower concentration ▪ Specificity is defined as the proportion of non-toxicity that is associated with the absence of the clinical sign at the lower concentration ▪ The false positive rate is the proportion of times that the presence of the clinical sign at the lower concentration does not predict toxicity at the next highest concentration (therefore 1-PPV) ▪ The false negative rate is the proportion of the times that the absence of the clinical sign at the lower concentration is associated with toxicity at the next highest concentration In the context of the FCP test, high values of PPV are required to avoid false positives that would lead to a more severe (but incorrect) GHS classification.
Properties of the original dataset The original data set of tests on 188 substances included 511 pairs of studies on 4638 animals. These included information from a variety of procedures (LC 50 and ATC) and concentrations tested, depending on the type of substance tested. All studies were carried out in rat (typically 5 males and 5 females, although there were a small number of studies with fewer or greater numbers of animals per group) and animals were usually exposed to the inhalation substance for 4 h and then monitored daily for 14 days. In studies conducted for a longer period (21 or 28 days), only the data from the first 14 days was included in the analysis. Studies that used fewer than 5 males or 5 females were excluded from further analysis, as were data within studies in which the foldchange in exposure from one concentration to the next higher was less than two.
Final dataset for analysis The full dataset with the properties listed in 2. 3 consisted of 427 pairs of studies. Of these, 268 pairs of studies had no deaths at the lower concentration, and it is this subset which is the subject of the following analysis. Fig. S1  shows the concentration ratios for the 268 pairs of studies included in the final dataset for analysis. The majority of pairs had a concentration ratio in the range of >2 to 5 (80%), with a large proportion of studies with a concentration ratio of >2 to 3 (39%). A smaller proportion of studies had concentration ratios of 5 or more (20%). Concentration ratios in excess of 10 were seen less frequently (8%).
Combinations and co-occurrence of signs Test data were examined for the presence of combinations of signs i. e. one animal or more with either of sign A or sign B at the lower exposure. All possible combinations of 2 signs were considered but the gains in sensitivity were small because of the strong co-occurrence of signs i. e. signs are not truly independent of each other. Similarly, inclusion of a third or fourth sign had progressively lesser impact on any parameter. The presence of any one of the three most highly predictive signs (hypoactivity, body weight loss and irregular respiration) in at least one animal had a PPV of nearly 91%, predicting 52% (sensitivity) of the toxicity that occurred at the higher concentration with only a 9% false positive rate (Table  10 ), which compares favourably with the false positive rate of a single death at the lower concentration.
that was then piloted by four different CROs before applying it to the whole data set. Even so, there was some ambiguity and variation in detail in the responses that were provided (such as indications of severity) and some judgement had to be applied in the interests of harmonisation. Where any reclassification was proposed, this was always agreed with the originating organisation. In the dataset that had no deaths at the lower concentration, and regardless of what clinical signs were noted, toxicity occurred in 77% of the studies at the next higher concentration. Therefore, the use of clinical signs other than death to define evident toxicity clearly has to have a PPV greater than this to have any potential value. What lower limit of the PPV above 77% is acceptable is determined by attitudes to false positive rates, and in this there is likely to be some diversity of opinion between safety, commercial and 3Rs perspectives.
, 2013). Secondly, the presence of T (tremors) also satisfies the need to avoid false positives but it is less commonly observed with a sensitivity of only 3. 8%. We propose that the observation of any of these four signs indicates evident toxicity. Thirdly, there is a further group of signs with PPVs in excess of 77%, but with lower values of the lower 95% confidence limit, whose utility is further compromised in some instances by lower specificity and limited sensitivity. It is therefore a matter of debate whether the presence of these signs would be accepted as evident toxicity. In view of the complications inherent in using historical data, it would be ideal to collect a prospective dataset in which the clinical signs to be monitored had been agreed in advance, and include additional information on severity in order to strengthen the case for including the third category of signs as indicators of evident toxicity.
Please note, we recommended that a limit of 10% body weight is used, since this was the lowest quantifiable limit in the dataset, and body weight loss in excess of 10% (from pre-dosing weight on day 0) was shown to be highly predictive of toxicity at the next highest concentration. Therefore the recommendations for the FCP protocol are as follows: ▪ A sighting study using one male and one female rat at each concentration should be undertaken and subsequent testing conducted in the more sensitive sex, or in females if no difference in sensitivity between sexes is observed  (Stallard et al. , 2011). ▪ If 2 or more deaths occur in the main study, substance classification can be made or further testing should be carried out at the concentration level below that tested, depending on the starting concentration or previous concentrations tested (Fig.
Data handling and analysis All study data are available in the supplemental material (see Additional file 2). Absolute data are expressed as median (range). Datasets were complete for most variables except for four serum biochemistry variables where small numbers of results were missing: alkaline phosphatase (pre-weight-loss: 1 result), glucose (preweight-loss: 2 results; post-weight-loss: 3 results), phosphate (pre-weight-loss: 1 result), potassium (postweight-loss: 2 results), and free thyroxine (post-weightloss: 2 results). There were no other missing data for any variable. Given the small numbers of missing data points, no correction was made in statistical analysis. For each dog, the daily intake of all essential nutrients was calculated, based upon their food allocation and the average nutrient content of the diet (Table  1 ).
Statistical analyses were performed with computer software (Stats Direct version 2. 6. 8, Stats Direct Ltd), with the level of significance set at P < 0. 05 for two-sided analyses. Given that there were no known previous studies examining adequacy of essential nutrient intake in obese dogs undergoing weight loss, it was not possible to perform a meaningful power calculation. Instead, as many dogs as possible were enrolled that the met the eligibility criteria. The Shapiro-Wilk test was used to assess all data sets and, because many were not normally distributed, non-parametric tests were used in preliminary analyses. These included the signed ranks test, the Mann-Whitney U test, Kendall's rank correlation, and Fisher's exact test. In addition, simple and multiple regression analysis was used to determine associations between variables, and the Shapiro-Wilk test was also used to confirm that the distribution of the residuals of each regression model followed a normal distribution.
Dogs and outcome of weight loss During the study timeframe, a total of 149 dogs were enrolled in a weight loss regime and potentially eligible for study recruitment. Of these, 82 dogs reached their target weight, and the period of weight management was at least 182 days in 52 dogs. Of these 52 dogs, 40 had been fed a single type of dry food (Table  1 ). After excluding dogs that were not euthyroid, were not on concurrent medication, or had incomplete clinical data (laboratory and DEXA scan results), a final group of 27 dogs were eligible for inclusion. These dogs represented a range of ages, breeds and sexes (Table  2 ), and the median period of weight loss was 293 days (range 182-674 days). All dogs remained well throughout, and no dietrelated abnormalities were noted on physical examination, before, during, and after the period of weight loss.
Discussion In the current study, we have assessed the intake of essential nutrients for obese dogs during a period of controlled weight loss using a purpose-formulated diet. The intake of most essential nutrients exceeded NRC 2006 RA cut-offs. Although intake was less than RA or MR for some nutrients, all dogs remained healthy, showing no clinical signs of nutrient deficiency. It is important to note that RAs include a safety margin to take into account predicted nutrient bioavailability, and the actual bioavailability of individual nutrients might be higher than assumed in NRC 2006. The significance of dogs having intakes less than MR for some nutrients during weight loss is not known. Firstly, it is possible that requirements for essential nutrients might actually change when dogs are subjected to energy restriction, although Data are expressed as median (range), number of results above reference range, and number below reference range P values quoted for Wilcoxon signed ranks test comparing pre-and post-weight-loss measurements.
Further, no signs were noted pertaining to liver disease, and clinicopathological markers of biliary system disturbance (e. g. bilirubin, and liver enzyme activity) were unchanged after weight loss. Finally, given the requirement of both methionine and cysteine for protein synthesis, the effect of daily intake on change in lean tissue mass and also serum albumin concentration were assessed, and no associations were seen with either. Nonetheless, as with choline, supplementing methionine and cysteine in the current diet by 15 % would ensure that daily intake is greater than NRC MR. Such a reformulation would be sensible until further data are available clarifying the safety of intakes of the level in the current study. There were a number of other nutrients where intake was less than the RA suggested by the NRC  [15].
These included tryptophan, magnesium, and potassium. The significance of these observations is not known since intake was always above MR throughout weight loss, there were no signs of deficiency for any of these nutrients, and no association was seen with changes in lean tissue or serum albumin. As with all studies, a number of limitations exist. Firstly, the data were collected retrospectively, and dogs included were drawn from a larger population. Given the eligibility criteria used, and most notably the duration of the weight loss period, a number of dogs were excluded since they reached target weight within 6 months. Other dogs were excluded because different weight loss diets had been used, clinical data were missing, the dogs either had another disease, or they were on concurrent drug therapy.
For instance, plasma nutrient status was not measured. However, such a study has recently been performed, in a similar cohort of dogs  [18] , which demonstrated no change in the plasma concentrations of most key nutrients during weight loss. A final limitation relates to generalisability of the data to canine weight loss programmes in general. Given the use of client-owned dogs, results should be broadly representative of weight loss programmes using this or similar diets in practice although, since the final population was small, subtle individual issues with a particular breed or dog type might have been missed. Further, the population came from a referral clinic and so might not be typical of the usual dogs undergoing weight management. Moreover, only a single weight loss diet was used and, thus, findings might not be generalisable to other weight loss diets, especially those from other manufacturers.
However, it is a strategic decision that should be critically reviewed in terms of sustainability. This is also true for the choice of the database management system (DBMS), in case no central database operation group or service is available on site. User experience User experience is a major factor that should be considered early in a LIMS decision process. In a strictly workflow-driven LIMS, users always have to follow a step-by-step procedure determined by a rigid process. In contrast, a free navigation user concept allows more flexibility; however, it requires a higher training level to ensure quality. The user interface ideally would be selfexplanatory or offer context-specific help. Access to particular functionality is most often attached to user roles, e. g. scientist, animal care taker, manager etc.
Example 1: Mouse Informatics Group, Wellcome Trust Sanger Institute (WTSI), UK The WTSI Mouse Database has been in existence for about 8 years and covers all aspects of high-throughput mouse production including mouse husbandry, freezing and thawing of cryogenic resources, phenotyping (data and images), data visualisation, reporting and export of resources (both mice and phenotypic data) all under strict UK Home Office licensing. At any given point, it is possible to generate full cage accounting on a per-month basis. This will show how many cages have been used per month attributed to which financial cost code. Users are also able to see how many cages have been used per-week/month per line. The LIMS is built and maintained by a core team of 7 developers using Java and the Spring Framework and has an active user base over 200 scientists, technicians and managers across the institute.
The underlying database is currently holding just over 50,000 live mice and over its lifetime has tracked more than 2 million. Our system is available as a fully hosted, web-delivered service (like Gmail). An organisation can, for a yearly fee, have full access to a LIMS system based on the one developed at WTSI. This allows customer organisations to make use of the features of the WTSI software but without having to purchase servers and database licences of their own, or have dedicated support staff to maintain and backup their data. Our LIMS solution is hosted in two geographically diverse data centres to provide high availability and resilience to failure. The LIMS application has been security audited, and access to customer's data is protected by a number of tried and tested mechanisms.
g. X-ray, or can be embedded within other LIMS pages where they can support the collection of required metadata, e. g. CRISPR/Cas Concentration. By expanding the capability outside of just collecting phenotypic data, we can empower the LIMS users to create and modify their own data collection requirements as the scientific technology and techniques advance over time. A further extension to the collection of the data is that these forms can be reported out by creating ''Oracle views''. Views are simply the representation of SQL statements that are stored in memory, so that they can be easily re-used. These are created in the database by joining a mouse level report, which contains all the standardised mouse information (Gender, Genotype, Genetic Background etc. ), and the particular columns recorded in a form.
This also enables us to plan a couple of modules of work ahead of time, meaning that the up-front business analysis can be done before development begins. The benefit of this is that in most cases, the specification of what is required for the user has been thought about for a good length of time and is relatively clear. The actual development is agile in nature so that as the work progresses the key user/stakeholder (who we meet a couple of times a week) can respond to issues or functionality and the resulting changes can be implemented quickly with very little impact. Example 2: Japan Mouse Clinic (JMC), RIKEN Bioresource Center, Japan Japan Mouse Clinic (JMC) has been set up in 2008  (Wakana et al. 2009 ) by the expansion of the mouse phenotyping platform of the large-scale ENU Mutagenesis Program in RIKEN in which operations had been managed by a LIMS termed as Mutagenesis Universal Support DataBase (MUSDB)  (Masuya et al.
2004 ). In JMC, data operations in the data capturing (mouse husbandry, colony management, cryopreservation of sperms and eggs, data capturing from the phenotyping platform, genotyping of polymorphic markers and linkage analysis of phenotype and genetic makers) are supported by MUSDB. The statistical phenotype data analysis pipeline is provided by the independent software application, termed as ''Pheno-Pub''  (Suzuki et al. 2013)  which supports a series of data-handling and Web-publication tasks in the large-scale phenotyping. In addition, Web-publications of the experimental SOPs are supported by a protocol database, termed as ''SDOP-DB''  (Tanaka et al. 2010). From 2011, JMC participated in the IMPC as one of the primary phenotyping pipelines for IKMC mutant lines. In 2013, JMC decided to replace its LIMS from MUSDB to the modified version of WTSI Mouse Database (described above).