dataesr/scientific-paragraphs-categorization huggingface dataset:
Here one deals with a short baseline experiments, L = 541 m, and the grounds for describing these oscillations are not as established. Short baseline oscillation phenomena, if they exist, involve sterile neutrinos with large values of the ∆m 2 , in the eV 2 range. But this value, hence the electron neutrinos energy distribution, is uncertain. We remind that our smearing procedure depends on this distribution. Assuming as an example that it followed the muon neutrino one we have applied the smearing procedure to the experimental MiniBooNE distribution. The data present a low energy anomaly with an excess of low reconstructed energy electron events. After our smearing procedure the excess of low energy electron neutrino events which raises a problem in the oscillation models, is pushed towards higher energy, making it possibly compatible with oscillation models.
As an illustration we compare in Fig. 5  the smeared curve with the T2K best fit, which has a mass value ∆m 2 32 = 2. 65 10 -3 eV 2 and the unsmeared curve with the best fit value ∆m 2 32 = 2. 43 10 -3 eV 2 of Ref. [16]. The equivalence only holds in the first peak region but it is likely to that the inclusion of the reconstruction effects the analysis of the T2K disappearance data will result in a slight increase of the mass value. This investigation will be the object of a future work, following the approach of  [17, 18]. We will see that in the MiniBooNE case the equivalence between the introduction of the reconstruction effect and a lowering of the mass value in the unsmeared situation can be total. Turning now to the electron events distribution we display it in Fig. 6    FIG. 5 : (Color online) The smeared distribution, D rec (E ν ), with the T2K two-flavor best fit  [11]  and the unsmeared curve, σ(E νµ )Φ νµ (E νµ ), with the best fit value of Ref.
The influence of the smearing effect on the data, which goes in the right direction to account for the low energy anomaly, is the main message of our study of the MiniBooNE data and it should have an influence in the analysis of the data. This being said, there is an additional problem which naturally comes to mind: the MiniBooNE muon neutrino beam contains a background of electron neutrinos which also undergo quasielastic events. These have to be evaluated and subtracted from the observed total number of electron events in order to extract the oscillation ones. These background electron events should be subject to the same reconstruction effects than the ones of the oscillated beam. This problem will be discussed in the following under the assumption that this background is evaluated in the same way as the oscillation events, namely from the knowledge of the electron neutrino background energy distribution and the "quasielastic" ν e cross section.
Acknowledgments We are grateful to  Carlo Giunti  and  Raymond Stora  for interesting discussions. We also thank  Geralyn Zeller  for useful information on the MiniBooNE data analysis. One of us (M. M. ) acknowledges the hospitality of the CERN theory division where part of this work was done. This work was partially supported by the  Communauté Française de Belgique  ( Actions de Recherche Concertées).
The twelve NP2 T spectra were imported into the MALDI BioTyper software (version 2. 0, Bruker) and analyzed by standard pattern matching (with default parameter settings) against the main spectra of 4, 706 bacteria, including spectra from one validly published species of Nosocomiicoccus, used as reference data in the BioTyper database. A score enabled the presumptive identification and discrimination of the tested species from those in a database: a score > 2 with a validly published species enabled the identification at the species level; and a score < 1. 7 did not enable any identification. For strain NP2 T , no significant score was obtained, suggesting that our isolate was not a member of any known species (Figures  4  and 5 ).
Genome project history The organism was selected for sequencing on the basis of its phylogenetic position and 16S rRNA similarity to other members of the genus Nosocomiicoccus, and is part of a "culturomics" study of the human digestive flora aiming at isolating all bacterial species within human feces. It was the first genome of a Nosocomiicoccus species and the first genome of Nosocomiicoccus massiliensis sp. nov. A summary of the project information is shown in Table  3. The Genbank accession number is CAVG00000000 and consists of 154 contigs. Table  3  shows the project information and its association with MIGS version 2. 0 compliance  [37]. Growth conditions and DNA isolation N. massiliensis sp. nov. strain NP2 T , (= CSURP246 = DSM 26222), was grown aerobically on M17 agar medium at 37°C.
Genome annotation Open Reading Frames (ORFs) were predicted using Prodigal  [38]  with default parameters but the predicted ORFs were excluded if they were spanning a sequencing gap region. The predicted bacterial protein sequences were searched against the GenBank database  [39]  and the Clusters of Orthologous Groups (COG) databases using BLASTP. The tRNAScanSE tool  [40]  was used to find tRNA genes, whereas ribosomal RNAs were found by using RNAmmer  [41]  and BLASTn against the GenBank database. Lipoprotein signal peptides and numbers of transmembrane helices were predicted using SignalP  [42]  and TMHMM  [43]  respectively. ORFans were identified if their BLASTP E-value was lower than 1e -03 for alignment length greater than 80 amino acids. If alignment lengths were smaller than 80 amino acids, we used an E-value of 1e-05.
Such parameter thresholds have already been used in previous works to define ORFans. To estimate the mean level of nucleotide sequence similarity at the genome level between N. massiliensis and three other members of the family Staphylococcaceae (Table  6 ), we used the Average Genomic Identity of Orthologous gene Sequences (AGIOS) home-made software. Briefly, this software combines the Proteinortho software (version 1. 4)  [44]  for detecting orthologous proteins between genomes compared two by two, then retrieves the corresponding genes and determines the mean percentage of nucleotide sequence identity among orthologous ORFs using the Needleman-Wunsch global alignment algorithm. Nosocomiicoccus massiliensis strain NP2 T was compared to Macrococcus caseolyticus strain JCSC5402 (GenBank accession number NC_011999), Staphylococcus pseudointermedius strain ED 99 (NC_017568), and Salinicoccus albus strain DSM 19776 (ARQJ00000000).
Genome comparison of Nosocomiicoccus massiliensis with Macrococcus caseolyticus, Staphylococcus pseudointermedius and Salinicoccus albus We compared the genome of N. massiliensis strain NP2 T , with those of M. caseolyticus strain JCSC5402 (GenBank accession number NC_011999) and S. pseudointermedius strain ED 99 (NC_017568), and S. albus strain DSM 19776 (ARQJ00000000 However, the distribution of genes into COG categories was not entirely similar in the four genomes (Figure  7 ). The nucleotide sequence identity ranged from 64. 75 to 69. 80% among the genera. Table  6  summarizes the numbers of orthologous genes and the average percentage of nucleotide sequence identity between the different genomes studied.
Cells are susceptible to amoxicillin, imipenem, rifampicin, vancomycin doxycycline and gentamicin but resistant to trimethoprim/sulfamethoxazole, metronidazole and ciprofloxacine. The G+C content of the genome is 36. 40%. The 16S rRNA and genome sequences are deposited in Genbank under accession numbers JX424771 and CAVG00000000, respectively. The type strain NP2 T (= CSUR P246 = DSM 26222) was isolated from the fecal flora of an AIDSinfected patient living in Marseille, France.
The use of human urine as a diagnostic tool has many advantages, such as ease of sample acquisition and noninvasiveness. However, the discovery of novel biomarkers, as well as biomarker patterns, in urine is hindered mainly by a lack of comparable datasets. To fill this gap, we assembled a new urinary fingerprint database. Here, we report the establishment of a human urinary proteomic fingerprint database using urine from 200 individuals analysed by SELDI-TOF (surface enhanced laser desorption ionisation-time of flight) mass spectrometry (MS) on several chip surfaces (SEND, HP50, NP20, Q10, CM10, and IMAC30). The database currently lists 2490 unique peaks/ion species from 1172 nonredundant SELDI analyses in the mass range of 1500 to 150000. All unprocessed mass spectrometric scans are available as ".
These studies have used methodologies ranging from traditional 2D gel electrophoresis alone  [11]  or coupled with mass spectrometry (2-DE-MS)  [12] , immunohistochemistry  [13] , liquid chromatography mass spectrometry (LC-MS)  [14] , and surface enhanced laser desorption ionisation-time of flight mass spectrometry (SELDI-TOF-MS)  [15] [16] [17]. In complex disease processes, the identification of biomarkers is key to developing novel therapeutic target molecules. Identification of the most robust urinary biomarkers will be enhanced by collating and correlating data from other published and current studies. Currently there are a number of urinary databases available. The majority consists of lists of identified proteins derived from tryptic digests analysed by LC-MS/MS, such as MAPU  [18]  and Sys-BodyFluid  [19]  and does not cover naturally occurring mass-centric molecular entities.
More recently, a urinary database, combining chromatographic reverse-phase retention times and m/z values, has been established  [20]. The Mosaiques database  [21, 22]  consists of naturally occurring protein and peptide patterns detected by capillary electrophoresis MS (CE-MS) from more than 3600 individuals, covering mainly an m/z range of 800 to 3000. However, databases that give access to unprocessed data files are not available but would be the most useful resource with which to compare and validate novel datasets. It is also prudent, especially in urinary proteome research, to remember that any peak in any MS scan profile might be derived from the same molecule (differing only in either its fragmentation or posttranslational modifications). This differentiation might be lost in an MS/MS screen, where proteolytic processing of the samples might alter the original protein/peptide signatures and intensities.
The main advantages of the SELDI technology are its ease of use including little or no sample preparation, high reproducibility, high volume throughput in a minimum of time, with proven methodology over time for the numerous diseases studied, whereas MELDI might require further development before it can be generally applied. The main limitations of the SELDI technology lie with the instrumentation where poor resolution on older instruments led to difficult reproducibility and sometimes questionable results. However, we have chosen a more modern technology (see Section 2). A number of reviews list the issues and compares the various MS-based methods in urinary research  [25] [26] [27]. Utilizing data from both our own and published studies, we have established the urinary proteome fingerprint database UPdb, which will be publically available as a repository for SELDI-MS data and as a reference for scientists to probe the urinary proteome for proteins implicated in disease processes.
Materials and Methods 2. 1. Urine Samples. Urine samples were obtained from 86 cancer patients, 93 noncancer controls, and 21 patients with a previous history of cancer but were diagnosed as cancer-free 6 to 18 months after resectional surgery. Summary participant demographics are shown in Table  1 , and full details are provided as part of the database. The cancer sample urines were collected just prior to surgery. One-third of the cancer patients were diagnosed with pancreatic tumours, approximately one-third had oesophageal cancer, approximately one-sixth had malignancies of the oesophagogastric junction (OGJ), and approximately one-sixth suffered from gastric cancer. All procedures were approved by the local research ethics committee. Written informed consent was obtained. The study conformed to the standards set by the Declaration of Helsinki.
All urine samples were stored at -40 ∘ C. 2. 2. SELDI-TOF MS. 0. 1 mL human urine was applied directly to preconditioned SELDI ProteinChip arrays (Bio-Rad Laboratories Inc. ) (NP20, H50, SEND, Q10, CM10 and IMAC30), as recommended by the manufacturer, in a ProteinChip bioprocessor and incubated with 0. 1 mL binding buffer where appropriate. The chip-spots were washed with 0. 2 mL binding buffer three times and air-dried, followed by application of emitter matrix (alpha-cyano-4hydroxycinnamic acid (CHCA) or sinapinic acid (SPA)). The arrays were read twice, one at low laser settings (focused on 100-50,000 Da m/z) and one at high laser settings (focused on 1000-200,000 Da m/z), on a ProteinChip Enterprise System PCS4000 (BioRad Laboratories Inc. ), SELDI-TOF instrument, and spectral data collected over an average of 588 shots per spot using ProteinChip Data Manager software.
500 13. 000 13. 500 Table  1 : General overview of the study cohort. 200 patient urine specimens were analysed in this study, derived from 93 healthy individuals (control), 86 cancer patients (cancer), and urine samples from 21 cancer patients 6 months to 1. 5 years after surgery (followup). The cancertypes of the 86 cancer patients are listed on the right. display a certain degree of heterogeneity, which is easily overcome by increasing the number of analysed samples. Using a 20% threshold for peaks commonly found in any sample, 31. 7% of all molecules are present using the IMAC30 (Cu 2+ ) chip-type, 25. 2% using CM10, and 23. 5% using HP50 surfaces. These low numbers are partially due to the various disease states and are higher by comparing samples from healthy control specimens. Normalising on total ion count and aligning all spectra from individual chip-types resulted in the catalog of 2490 detected peaks, which are fully listed in the database (Figure  2 ).
The database structure also allows the storage and retrieval of information relating to the MS environment, pre-and subfractionation methods, chromatography setups, studied diseases, and other data. Peak-specific data, such as identified biomarker, statistical information, and, if known, identified proteins, are provided. The database covers the mass range of 1500 to 150000 for SELDI spectra and consists of averaged and median m/z, intensities and measurement specific data. All 1172 spectra (raw data files) are available Table  2 : Overview of SELDI-TOF spectra available as part of the database. Spectra were recorded using low laser energy desorption (m/z range 1500 to 25000) and high laser energy desorption (m/z range 20000 to 150000) from 200 nonredundant samples. Peak clusters common in all spectra of one chip-type were analysed using a 5% signal-to-noise cutoff, and numbers of peaks found in at least 10% or 20% of all spectra were counted.
for download in ". xml" format from the PADB website at http://www. PADB. org/. Initial literature data mining led to the identification of 29 additional urinary datasets, which were incorporated into our database (Table  3 ). These sets are based on several MS platforms, ranging from SELDI and MALDI to CE-MS and CE-MALDI. The median mass of each individual MS technology, based on the identified peaks per technique, shows that both MALDI and CE-MS favor smaller compounds and peptides, whereas SELDI has an advantage in the higher mass range, albeit with a lower resolution of measured peaks. In total, the database covers a mass range of 800 to 200000 m/z or Da since most peaks using these technologies will have a charge of one. Currently, of these 3924 peaks, 39 are associated with identified proteins.
Conclusions UPdb is accessible and downloadable through the PADB initiative at http://www. PADB. org/updb/updb. html. This platform should be used as a global resource to share and exchange primary data derived from SELDI-, MALDI-, MELDI-, CE-, LC-, and other TOF-MS analyses in urinary research. We encourage other laboratories to contribute to UPdb by submitting high quality MS spectra from human urine samples. We envisage providing full linkage of the identified m/z species to the large-scale screening resource (LSSR) database (in preparation), which will list molecules identified by MS or other large-scale proteomic methods by their protein or gene names and will also contain a substantial database of identified peptide sequences relating to the proteins listed.
Background: Klebsiella pneumoniae is one of the most important pathogens responsible for nosocomial outbreaks worldwide. Epidemiological analyses are useful in determining the extent of an outbreak and in elucidating the sources and the spread of infections. The aim of this study was to investigate the epidemiological spread of K. pneumoniae strains using a MALDI-TOF MS approach. Methods: Five hundred and thirty-five strains of K. pneumoniae were collected between January 2008 and March 2011 from hospitals in France and Algeria and were identified using MALDI-TOF. Antibiotic resistance patterns were investigated. Clinical and epidemiological data were recorded in an Excel file, including clustering obtained from the MSP dendrogram, and were analyzed using PASW Statistics software. Results: Antibiotic susceptibility and phenotypic tests of the 535 isolates showed the presence of six resistance profiles distributed unequally between the two countries.
Data Mining Analysis of Klebsiella pneumoniae MSP Dendrogram The MSP dendrogram revealed five distinct clusters according to an arbitrary cut-off at the distance level of 500 (Figure  1 ). Data mining analysis of the five clusters using PASW 17. 0 software showed that K. pneumoniae strains isolated in Algerian hospitals (Tlemcen, Sidi Bel Abbes, Oran, Annaba) were significantly associated with respiratory tract infections and ESBL phenotype in the fifth cluster (p,0. 0001), whereas K. pneumoniae strains isolated in Marseille hospitals were significantly associated with urinary tract infections and wild type phenotype in the first, the second and the fourth clusters (p,0. 0001). K. pneumoniae strains isolated in Angers hospitals were associated with urinary tract infections and wild type phenotype in the fourth cluster (p,0.
0001)). The monthly distribution of K. pneumoniae strains for the January 2008 -March 2011 period was determined by PASW 17. 0 software according to clusters. Strains from Angers and Algerian hospitals were significantly correlated with winter (January-March) (p,0. 0001), whereas, strains from Marseille hospital were associated with spring (April-June) (p,0. 0001). No seasonal variation was associated with strains from Nice hospital.
Furthermore, these molecular methods are costly and timeconsuming to obtain results and introduce delays when attempting to limit the spread of K. pneumoniae clones  [36]. For instance, only a few hours are required to obtain results by MALDI-TOF MS, whereas several days are necessary to collect MLST data  [37]. In addition, the cost of MALDI-TOF MS instrumentation is comparable to that of a sequencing machine, but running costs and consumables are considerably lower than for these methods  [38]. Barbuddhe   [20]. Thus, MALDI-TOF MS combined with a statistical classification strategy is appropriate for studies of local epidemiology and global population structure when compared to a local database from clinical strains. It is a powerful epidemiological method and is sufficiently reproducible and sensitive enough to rapidly survey the evolution of existing or emerging phenotypes with reduced financial and human costs  [39].
Conclusion We believe that our preliminary results should be expanded and confirmed with more strains obtained from different countries. To the best of our knowledge, this is the first study that analyzes the epidemiology of a large series of K. pneumoniae clinical isolates using MALDI-TOF MS application. We suggest the creation of a local database that is updated regularly to survey for the presence of abnormal phenotypes at the strain level. If a particular phenotype is detected, a real time genome sequencing approach could then be performed to investigate the origin and specific features of the strain. We believe that this methodology could be used routinely in clinical microbiology laboratories as a surveillance tool for hospital epidemiology studies to prevent outbreaks and dissemination of pathogens in hospital settings.
Klebsiella pneumoniae Identification using MALDI-TOF MS Isolates were plated on Trypticase Soy Agar (BioMerieux) and incubated for 24 h at 37uC. One single colony from each isolate was deposited on a MALDI-TOF MTP 384 target plate (Bruker Daltonics, Bremen, Germany) in four replicates to minimize random effects. Two microliters of matrix solution (saturated acyano-4-hydroxycinnamic acid, 50% acetonitrile, 2. 5% trifluoroacetic acid) were then added and allowed to co-crystallize with the sample. Analysis was performed in a MALDI-TOF MS spectrometer (337 nm) (Autoflex; Bruker Daltonics) with FLEX control software (Bruker Daltonics). Ions were accelerated in the positive ion mode with an accelerating voltage of 20 kV. The pulsed extraction of ions was optimized for 1000 Da. The software employed, Bruker Biotyper 2.
0 (Bruker Daltonics), automatically acquired spectra with fuzzy control of the laser intensity and analyzed them by standard pattern matching against the spectra of 2881 species used as reference data. After comparing the unknown spectra with all reference spectra in the database, the log scores were ranked. Values of. 1. 9 were required for secure identification at the species level, and values between 1. 9 and 1. 7 were required for secure identification at the genus level.
Statistical Analysis Clinical and epidemiological data were recorded in an Excel file (Microsoft, Redmond, WA, USA), including the clustering obtained using the MSP dendrogram generated by the Biotyper software (version 2; Bruker Daltonics), and were analyzed using PASW Statistics software version 17. 0 (SPSS Inc. , Chicago, IL, USA). Dependent variable series were analyzed using Expert Modeler, which automatically generates the best-fitting model. The chi-square analysis was used also to compare proportions using the same software, and P values ,0. 05 were considered to be statistically significant. Statistical analyses were conducted using Epi Info version 6 (Centers for Disease Control and Prevention, Atlanta, GA, USA).
Multilocus Sequence Typing Randomly, 28 strains distributed in the five clusters were selected to perform the full MLST as described previously using seven housekeeping genes, including gapA, infB, mdh, pgi, phoE, rpoB and tonB  [34]. The MLST database for K. pneumoniae can be found at http://www. pasteur. fr. Based on the allelic profiles, the evolutionary relationship between isolates was assessed by the minimal spanning tree (MST) algorithm in Bionumerics (Applied Maths, NV St-Martens-Latem, Belgium). A stringent definition of 6/7 shared alleles was used to define clonal complexes (single locus variants only).
Vietnam, for instance, has a broad range of organizations which are affiliated with the party-state and officially classified as civil society organizations (CSOs)  (Bach Tan Sinh, in this volume)  and, at 51 per cent of eligible women, has the highest membership in women's groups worldwide (primarily because of its high level of formal participation in the Vietnam Women's Union, which is discussed more extensively in this volume)  (World Values Survey Database 1999 -2004 , cited in: UNIFEM (2008: 19) ). In the same vein, Cambodia has, since the 1990s, witnessed a huge expansion of non-governmental Grasping discourses, researching practices 3 state' and basically described a 'social order of citizenship'  (Kumar 1993: 376f. ). More than a millennium later, Thomas  Hobbes (1588 Hobbes ( -1679) )  defined civil society as, in the words of  Ehrenberg (2011: 19) , 'the arena in which interest-bearing individuals pursued their private goals', and argued that it was the sovereign state which was tasked with controlling this segment of society.