dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements I would like to thank the facilities for the study of the specimens offered by the  Institut Catal a de Paleoecologia Humana i Evoluci o Social ; the curators of the  Museo Nacional de Ciencias Naturales (MNCN)  of the  Consejo Superior de Investigaciones Científicas (CSIC) ,  Susana Fraile  and  Angel Luis Garvía ; the willingness to share unpublished data and discuss results shown by  Jan van der Made  ( MNCN, CSIC ) and  Alfonso Arribas  ( Estaci  on paleontol  ogica Valle del río Fardes ,  Instituto Geol ogico y Minero de España ); the revision of the manuscript by  Nuria García  ( Universidad Complutense de Madrid ). D. F. is supported by the  Ayuda del Programa de Formaci on de Profesorado Universitario  ( FPU20/03389 ) and this work is part of the PhD thesis in the  Programa de Doctorado en Biología  at the  Universidad Complutense de Madrid.
J. M. -M. has been funded by the  Agencia Estatal de Investigaci on-European Regional Development Fund of the European Union  ( CGL2017-82654-P ,  AEI/FEDER-UE)  and the  Generalitat de Catalunya ( CERCA Program ). J. M. -M. is also member of the consolidated research group  2017 SGR 116  ( AGAUR ,  Generalitat de Catalunya). A. Pineda  is supported by the  LATEUROPE  project (Grant agreement  ID 101052653 ) that has received funding from the  European Research Council (ERC)  under the  European Union 's  HORIZON1. 1 research program. The  Barranc de la Boella  fieldwork is supported by the  Ajuntament de la Canonja and Departament de Cultura of Generalitat de Catalunya  ( CLT009/ 18/00053 ). This research has been funded by  Ministerio de Ciencia e Innovaci  on,  PID2021-122356NB-I00. The  Institut Catal a de Paleoecologia Humana i Evoluci o Social (IPHES-CERCA)  has received.
2021). To observe how efficient might be the solar flux might be in controlling the exosphere of Mercury and the Moon, one approach is to image the diurnal and annual variabilities of the exosphere. It needs, however, a large set of observations and the help of models taking into account all possible mechanisms at the origin of the alkali atoms in the exospheres (see  Leblanc et al. 2022). For example, waiting for the BepiColombo nominal mission, when we will have in situ detection and global imaging of the Na distributions  (Milillo et al. 2020) , we need more ground-based observations to obtain a more complete dataset for the investigation of the dawn-dusk Mercury's seasonal variability  (Milillo et al. 2021). In fact, ground-based observations with dawn/dusk view at all True Anomaly Angle (TAA, i.
Study design and cohort population In this retrospective study, patients were selected among the retrospective French Epidemiological Strategy and Medical Economics (ESME) mBC database. The ESME mBC database (NCT03275311), composed of 18 French Comprehensive Cancer Centers, was launched by UNICANCER in 2014 and built from existing information systems, treatment databases and patient's electronic medical records with homogenous on-site collected information. Among the 22463 patients registered in the ESME mBC cohort between January 1st, 2008 and December the 31, 2016, patients experiencing isolated CNS progression (either CNS metastases occurrence or progression if already present at diagnosis) under pertuzumab and trastuzumab as rst-line systemic therapy for HER2-positive mBC were identi ed.
Data collection Patients' characteristics (age at diagnosis, sex, medical history of early BC and treatment), tumors' characteristics (type of metastases, number of metastatic sites, ER status, median disease-free interval from early breast cancer if concerned) and treatment's strategy (type of systemic and CNS targeted therapy) were reported from patient's electronic medical records, patient hospitalization records and pharmacy records. Given the multicentric nature of the data collection, all coding procedures were prede ned by the data manager and all data were centralized within each center using a shared anonymous format. The present analysis was approved by an independent ethics committee (Comité De Protection Des Personnes Sud-Est II-2015-79). No formal dedicated informed consent was required but all patients had approved the re-use of their electronically recorded data.
Aspergillus series Versicolores are molds distributed among 17 species, commonly found in our environment, and responsible for infections. Since 2022, a new taxonomy has grouped them into 4 major lineages: A. versicolor, A. subversicolor, A. sydowii, and A. creber. Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) could be a faster and more cost-effective alternative to molecular techniques for identifying them by developing a local database. To evaluate this technique, 30 isolates from Aspergillus series Versicolores were used. A total of 59 main spectra profiles (MSPs) were created in the local database. This protocol enabled accurate identification of 100% of the extracted isolates, of which 97% (29/30) were correctly identified with a log score ≥ 2.
00. Some MSPs recorded as Aspergillus versicolor in the supplier's database could lead to false identifications as they did not match with the correct lineages. Although the local database is still limited in the number and diversity of species of Aspergillus series Versicolores, it is sufficiently effective for correct lineage identification according to the latest taxonomic revision, and better than the MALDI-TOF MS supplier's database. This technology could improve the speed and accuracy of routine fungal identification for these species.
creber, A. cvjetkovicii, A. jensenii, A. puulaauensis, A. tennesseensis, and A. venenatus)  [17]. Although molecular and morphological identification methods have been useful for the identification of Aspergillus series Versicolores, they have some limitations, particularly with regard to their similarity, intraspecific variability  [18] , and basic local alignment search tool (BLAST) similarity searches using different genes, which result in different identifications  [17]. Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) has become the reference technique for the rapid identification and classification of microorganisms, including fungi  [19] [20] [21]. Several MALDI-TOF MS systems are available worldwide, such as the Bruker Biotyper, but their database may not be able to distinguish closely related species within the Aspergillus series Versicolores.
First of all, the lack of completeness of these databases and their late updates in relation to taxonomic revisions may simply explain the misidentifications. Thus, several studies have reported difficulties in identifying rare Aspergillus species using the Bruker database  [22] [23] [24]. Moreover, for Aspergillus species of the Versicolores series, their high level of intraspecific variability can result in overlapping mass spectra, making it difficult to distinguish between species. To overcome the weaknesses of the databases provided by MALDI-TOF MS suppliers, it is possible to generate local databases. Several teams have demonstrated their usefulness for correct species identification, in particular for Achromobacter  [25] , Clostridia [26], and lice  [27]. The objective of this study was to evaluate the interest of spectrometric identification of Aspergillus species of the Versicolores series by creating a local database at the University Hospital of Caen.
Clinical and Environmental Isolates The 30 isolates used to develop the local mass spectrometry local database are described in Table  1. They were obtained from clinical samples received at the Mycology Laboratory of the Caen University Hospital (France) and from environmental samples collected by the ToxEMAC team, which has the largest French collection of Aspergillus isolates of the Versicolores series. We evaluated 8 species of the series, some of which were represented by a single isolate, such as A. amoenus, A. fructus, A. protuberus, A. puulaauensis, and A. tabacinus, while others were represented by multiple isolates (A. creber, n = 10; A. jensenii, n = 4; A. sydowii, n = 11). All isolates were preserved in the ToxEMAC mycological bank (stored at -80 • C).
Spectral Acquisition Data acquisition was carried out according to Bruker recommendations (MALDI Biotyper: creation of MSP Protocol V1. 4, Janvier 2021). Spectra acquisition was performed with Microflex LT/SH MALDI-TOF MS (Bruker Daltonics GmbH, Bremen, Germany) using linear positive mode with mass range m/z 2000 to 20,000, and an acceleration voltage of 20 kV by the AutoXecute function of Flexcontrol v3. 4 software (Bruker Daltonics GmbH, Bremen, Germany) with the "MBT_Autox" method (accumulation = 240 shots). The calibration of the MALDI-TOF MS was automatically performed using a bacterial test standard (BTS) deposit (Bruker Daltonics GmbH, Bremen, Germany) for mass calibration according to the manufacturer's instructions. Spectra were acquired 3 times on each deposit, resulting in 24 spectra by the extract.
Quality Control Data were imported and analyzed using flexAnalysis software v3. 4 (Bruker Daltonics GmbH, Bremen, Germany). All spectra were represented with baseline subtraction, smoothing, and automatic scaling on the y-axis. First, the mass accuracy of the BTS was checked (mass deviation < 300 ppm for each peak). Then, the 24 spectra were checked to meet 2 objectives between 6000 and 7000 m/z to eliminate outliers' peaks or flatline spectra, and to ensure that the mass deviation between the smallest mass spectrum and the largest mass spectrum was a maximum of 500 ppm. The supplier recommends a minimum of 20 out of 24 spectra that meet the quality requirements described above.
Creation of MSP Each MSP was created from a minimum of 20 spectra of the same extract using the "MSP creation" function of MaldiBioTyper Compass Explorer ® v4. 1 software with standard parameters (maximum mass error for each raw spectrum, 2000 Da; desired mass error for the MSP, 200 Da; minimum desired frequency for a peak, 25%; maximum number of peaks for MSP creation, 70). The MSP created was then compared with the Bruker database to avoid any risk of contamination or errors in molecular or phenotypic identification. When a MSP was created, we attempted to obtain a second MSP with two additional days of incubation to obtain MSPs with both young and mature colonies for each of these isolates. The MSPs created were used to generate a new local database named "Fungi CAEN".
Evaluation of MSP Library Performance The 30 isolates were tested using the extraction protocol for filamentous fungi from the manufacturer's instructions. The spectra generated were compared with the two combined databases (Bruker-Daltonics MALDI Biotyper Filamentous Fungi (V4, August 2021) containing 856 MSPs and "Fungi CAEN" containing 59 MSPs). We used the Bruker user manual to interpret the logarithmic score results: high-confidence identification (≥2. 00), low-confidence identification (1. 70-1. 99), and no possible organism identification (<1. 70). We also used three clinical isolates, firstly identified as A. versicolor using the "Filamentous Fungi" Bruker database, which were then identified using PCR sequencing as described above and tested against our local database in order to evaluate its performance because these isolates were not included in our local database.
There was no third attempt for this medium due to a lack of time to reconduct them manually. Incubation times were longer on average, with three days for A. amoenus, A. fructus, and A. sydowii, between eight and nine days for A. jensenii, between nine and twelve days for A. creber, and up to fourteen days for A. puulaauensis. There were not enough spectra for A. protuberus to be included in the database on this culture medium (Table  2 ). We observed only failures on the CZA medium. Finally, we tested the liquid SAB medium for the isolates most difficult to extract from SAB, MEA, and CZA media (no MSP obtained or only one from SAB medium): three MSPs were generated from the eight extracted isolates tested (two A. creber isolates and one A. puulaauensis isolate) (Table  2 ). The easiest species to extract was A.
Characteristics of the Local Database The thirty isolates, from eight different Aspergillus species of the Versicolores series, were used to create the local spectrometric database, generating fifty-nine MSPs: three for A. amoenus, nineteen for A. creber, two for A. fructus, six for A. jensenii, one for A. protuberus, three for A. puulaauensis, twenty-three for A. sydowii, and two for A. tabacinus. We were able to create MSPs with both young and mature colonies for only four isolates (two A. sydowii, one A. creber, and one A. amoenus) (Table  2 ). Of the 1416 spectra obtained from these 59 MSPs, 130 were eliminated during a visual analysis of the identification spectra due to insufficient quality or obvious dissimilarity with the other replicates. We were able to obtain a MSP from mature colonies for only four isolates (i.
e. , 4/30, 13% of isolates): two A. sydowii isolates on an SAB medium (A. sydowii lineage), and A. amoenus and A. creber on an MEA medium (A. creber lineage). Thus, there were two MSPs in the database for those species on SAB and MEA medium (Table  2 ). For all other species, no conclusive results were obtained from mature colonies (difficult to collect due to low metabolism). In total, we obtained 32 MSPs from the SAB medium, 24 MSPs from the MEA medium, 0 MSPs from the CZA medium, and 3 MSPs from the SAB liquid (Table  2 ). Regarding the characteristics of the spectra, we obtained peaks ranging from 3 to 15 kDa in molecular weight. The analysis was carried out between 6000 and 7000 m/z, as the most characteristic and intense ions of the fungal macromolecule profile were detected in this range.
Evaluation of the Local Database Performance and Comparison with the Bruker Database To verify our database, each MSP created was post-analyzed against the Bruker and the local databases. Regarding the latter, species identification was correct for 100% of the clinical and environmental isolates extracted. A total of 97% of isolates (29/30) were correctly identified with a log score ≥2. 00 (Table  3 ). Only one isolate (isolate 28) was identified with a score of 1. 98 as A. versicolor with the Bruker database and as A. sydowii with a score of 1. 97 with our database. It should be noted that other species were also identified with a log score ≥2. 00 (Table  3 ). Species with only one isolate, such as A. amoenus, A. fructus, A. protuberus, or A. tabacinus from the A. versicolor lineage of the 2022 taxonomic revision, matched with several species of this lineage due to the absence of MSPs in the database.
However, isolates of A. fructus, A. protuberus, and A. tabacinus matched also with other lineages such as A. sydowii, A. puulaauensis, and A. creber, but with a log score <2. 00. For the A. creber lineage, A. creber isolates mainly matched with A. creber and sometimes with A. puulaauensis, which belong to the same lineage; A. jensenii and A. puulaauensis isolates matched with all three species of the A. creber lineage. For the A. sydowii lineage, all isolates matched with A. sydowii except for one (isolate 27), which matched once with A. amoenus (with a log score ≥2. 00), which does not belong to the same lineage. If we consider all the identification profiles of the 30 isolates (30 × 10 = 300), 273 were associated with the local database and 27 with the Bruker database. According to the 2022 taxonomic revision, the "Fungi CAEN" local database showed 97.
1% correct identification at the lineage level (265/273) and 78. 8% (215/273) at the species level, with a log score ≥1. 70. With a log score ≥2. 00, better results were obtained, with a correct match of 99. 6% (224/225) at the lineage level and 82. 7% (186/225) at the species level (Table  3 ). Concerning the performance of the Bruker database in relation to the thirty isolates tested, A. versicolor 120227_14 ETL was identified for A. amoenus, A. fructus, A. protuberus, and A. tabacinus; A. versicolor 392 UGB and A. versicolor D_16_256_8_1 LLH for A. amoenus and A. fructus; A. versicolor 1343 MPA for A. amoenus, A. fructus, and A. sydowii (six times); A. versicolor F51 LLH for A. creber (six times) and A. puulaauensis; A. versicolor DSM 63292 DSM only for A. creber; and A. sydowii 2008_141783 MUZ and A.
versicolor 2009_137364 MUZ only for A. sydowii (Table  3 ). Thus, the "Filamentous Fungi" Bruker database showed a correct identification of 44. 4% (12/27) at the lineage level (corresponding only to A. versicolor and A. sydowii lineages) and 0. 7% (2/27) at the species level (corresponding only to A. versicolor and A. sydowii species), with a log score ≥1. 70. With a log score ≥2. 00, the correct identification rate decreased to 33. 3% (6/18) at the lineage level and 0% (0/18) at the species level (Table  3 ). The Aspergillus versicolor strains in the Bruker database did not always correspond to the A. versicolor species, according to the new taxonomic revisions. It is difficult to know to which species exactly these reference strains can be identified; it is likely that A. versicolor F51 LLH and A.
15), and A. versicolor 392 UGB (2. 04) from the Bruker database and A. tabacinus (2. 30) from the local database. For one isolate (isolate 21), all ten profiles were below the organism identification threshold (<1. 70) but matched with A. sydowii from the local database (seven profiles) and A. versicolor 2009_137364 MUZ, A. versicolor 1343 MPA, and A. sydowii 2008_141783 MUZ from the Bruker database (three profiles). No spectrum was detected for the remaining nine isolates. In addition, three clinical isolates previously identified as A. versicolor in the Bruker database and then identified by PCR sequencing as A. sydowii, A. tabacinus, and A. creber, were tested in our local database. A. sydowii matched 100% to A. sydowii from the "Fungi CAEN" database with a score ≥2. 00 (four profiles ≥ 2.
00 and six profiles between 1. 70 and 2. 00). A. tabacinus matched with A. tabacinus (1. 97), A. fructus (1. 92 and 1. 76), A. protuberus (1. 90), and A. amoenus (1. 84) from our "Fungi CAEN" database; and A. versicolor 120227_14 ETL (2. 26), A. versicolor 392 UGB (1. 98), A. versicolor D_16_256_8_1 LLH (1. 93), A. versicolor DSM 63292 DSM (1. 77), and A. sydowii F68 RLH (1. 88) from the Bruker database. A. creber matched to A. creber (seven profiles ≥ 2. 00 and one profile between 1. 70 and 2. 00) from "Fungi CAEN" and A. versicolor F51 LLH (2. 18) and A. versicolor DSM 63292 DSM (1. 99) from the Bruker database. Finally, the "Fungi CAEN" local database showed 100% correct identification at the lineage level (23/23) and 82. 6% (19/23) at the species level, with a log score ≥ 1. 70, whereas the Bruker database showed a correct identification of 57.
Recently, Reeve et al. used MALDI-TOF MS technology to characterize 40 environmental isolates of Aspergillus series Versicolores  [29]. They found consistent identifications with the Bruker database, identifying A. versicolor 2009_137364 MUZ and A. versicolor F51 LLH, which did not belong to the same spectral-linkage groups. In our database, A. versicolor 2009_137364 MUZ and A. versicolor F51 LLH matched with A. sydowii and A. creber, respectively. Masih et al. evaluated the performance of MALDI-TOF MS for the identification of different and rare Aspergillus, including A. versicolor and A. sydowii  [30]. The Bruker database identified only eight (38%) of the twenty-three rare Aspergillus isolates compared with 95% for their local mycology database. Alanio et al. demonstrated the usefulness of MALDI-TOF MS for the identification of different Aspergillus species: 138 out of 140 (98.
It is important to note that while this study focused on Aspergillus sections Fumigati, Flavi, Nigri, and Terrei, it also included Aspergillus series Versicolores, with the species A. creber, A. sydowii, and A. tabacinus each represented by one isolate. Species identification was obtained for one hundred and ninety-one isolates (95. 5%), and only nine (4. 5%) could not be identified at the species level, grown on solid or liquid media  [22]. We have created the very first local MALDI-TOF MS database for the different species of Aspergillus series Versicolores from French clinical and environmental isolates. Following the new taxonomic classification system for Aspergillus series Versicolores, published by Sklenář et al. in 2022, our results correspond perfectly to this new taxonomy with a correct identification rate of 97.
1% at the lineage level compared to the "Filamentous Fungi" Bruker database, which achieved a correct identification of only 44. 4%. Despite the lack of isolates for some species, we managed to identify the main lineages of this new taxonomy (A. sydowii, A. creber, and A. versicolor)  [17]. As far as supplier databases are concerned, it would be wise to rename the reference spectra "Aspergillus series Versicolores" instead of "Aspergillus versicolor", until the taxonomic revision has been integrated. Nevertheless, our local database still has some limitations. First, some species were rarely found in clinical or environmental samples, and were therefore represented by a single isolate: A. amoenus, A. fructus, A. protuberus, A. puulaauensis, and A. tabacinus. All these isolates belong to the A.
versicolor lineage in the new 2022 taxonomy, except A. puulaauensis, which belongs to the A. creber lineage. The isolates tested in this study come exclusively from France, particularly Normandy, and some species were absent from our database, notably the A. subversicolor lineage in the new 2022 taxonomy. Given the numerous samples in different biotopes over time in this geographical area (indoor air of different homes, hospital air, agricultural environment, and human clinical samples), we can still conclude that our collection of Aspergillus series Versicolores is representative of the local fungal ecology  [18]. Five species were represented by a single isolate and nine species were not present in our database, which may explain the lack of intraspecific variability in the database and why the MALDI-TOF MS technique may not be able to differentiate them from other species  [17, 32].
Therefore, it will be necessary to include additional isolates belonging to these species or new species when they become available in order to expand the database and improve its reliability. Only four MSPs were created from mature colonies (two A. sydowii, one A. creber, and one A. amoenus). As their spectra show no differences, it is unnecessary to generate spectra at variable growth times for these species. The method recommended by Bruker for the identification of fungi is the full-extraction protocol. Some studies have also optimized this protocol to improve sensitivity  [33, 34] , while some research teams have suggested the utilization of alternate matrix types, including sinapinic acid or 3,4-dihydroxycinnamic acid  [20]. Even if it is difficult to change the matrix in a medical diagnostic laboratory subject to accreditation, these proposals are promising.
[32]. Our database is therefore effective for complete identification of the lineage according to the latest taxonomic revision, but not of the species. Another limitation is the lack of reference spectra or misidentified reference spectra in commercial databases for some species within Aspergillus series Versicolores. This can result in misidentification or no identification, which may require additional confirmatory tests, such as DNA sequencing  [22] [23] [24]. Finally, the accuracy of MALDI-TOF MS can be affected by the quality of sample preparation, age of culture, and growing conditions  [35].