dataesr/scientific-paragraphs-categorization huggingface dataset:
At delivery, dietary habits and alcohol consumption during pregnancy and newborn's health data (including birth weight) were collected and a cord blood sample was obtained to document prenatal exposure to chlordecone and other environmental contaminants. At 7 years-old, the whole cohort of liveborn singleton children (N = 1033) were invited to participate in a clinical examination, 444 families could not be contacted, refused to participate, or were excluded for other reasons (Supplementary material; Figure  S1 ). At 7-years, 576 of the participating children underwent a neuropsychological evaluation. A maternal interview provided information concerning current health and past medical history, lifestyle, duration of breastfeeding, child behavior and other characteristics. Children's blood samples were also obtained at age 7.
Materials and methods: A pilot prospective study was conducted in 23 French onco-hematological centers from 2013 to 2017 (NCT01916057). Patients ≥ 18 y. o. suspected for CDC on abdominal conventional imaging (CT or MRI) were included. PET/CT and conventional imaging were performed at baseline and month 3 (M3). Follow-up was assessed until M12. The primary outcome measure was the global response at M3, i. e. , apyrexia and complete response to PET/CT. The secondary outcome measure consists in comparison between responses to PET/CT and conventional imaging at diagnosis and M3. Results: Among 52 included patients, 44 were evaluable (20 probable and 24 possible CDC); 86% had acute leukemia, 55% were male (median age 47 years). At diagnosis, 34% had fever and conventional imaging was always abnormal with microabscesses on liver and spleen in 66%, liver in 25%, spleen in 9%.
Study design and population CANHPARI was a multicenter pilot prospective interventional study designed to determine whether PET/CT is useful for treatment strategy for CDC. The study was registered on clinicaltrials. gov (NCT01916057) and approved by the ethic committee (CPP Ile de France 1, 2013-mai-13239). Eligible patients met the following criteria: aged ≥ 18 years with a malignancy or HSCT, and profound, i. e. , < 100 neutrophils/mm 3 , and prolonged, i. e. , ≥ 10 days, neutropenia; and CDC defined by multiple abscesses in liver and/or spleen observed on abdominal CT or MRI  (22). Exclusion criteria were described elsewhere  (22). After file assessment by an independent committee, consisting in two infectious disease specialists, two hematologists, and two nuclear medicine specialists, patients were excluded if they had liver and/or lesions from an origin other than candidiasis.
Acknowledgments The authors thank  Jeffrey Arsham  for editing the manuscript and the  Canhpari Study Group Members , first all participating clinicians who recruited patients in the study:  Fanny Lanternier  ( Hôpital Necker-Enfants Malades -APHP, Paris ),  Felipe Suarez  ( Hôpital Necker-Enfants Malades-APHP, Paris ),  Emmanuel Raffoux  ( Hôpital Saint-Louis-APHP, Paris ),  Jean-Pierre Marolleau  ( CHU Amiens ),  Aline Schmidt  ( CHU Angers ),  Ana Berceanu  ( CHU Besançon ),  Arnaud Pigneux  ( CHU Bordeaux ),  Sylvain Chantepie  ( CHU La Côte de Nacre-Caen ),  Johanna Konopacki  ( Hôpital militaire de.
Patient and clinical data A prospective study during January 2003-August 2011 recruited all consenting inpatients with suspected central nervous system (CNS) infection in Mahosot Hospital, Vientiane Capital, for whom diagnostic lumbar puncture was indicated in the opinion of the responsible physician. Patient history and examination findings were recorded on standardised forms and meningitis, meningoencephalitis and encephalitis were defined as previously described. 11 , 18 erebrospinal fluid (CSF) and sera were aliquoted and immediately stored at -80°C. All patient samples underwent a panel of laboratory tests including full blood count, biochemistry panel, culture and serologic and molecular assays for a range of bacteria, viruses, parasites and fungi. 11 HIV-1 and HIV-2 rapid diagnostic tests were performed when requested.
Autoantibody testing Data on the infectious disease aetiologies have been published. 11 utoantibodies were tested in available CSF and serum sam-ples from 134 patients: 92 patients without an identified infectious aetiology and 42 patients with a confirmed infectious diagnosis. In addition, sera from 55 healthy blood donor controls from Vientiane were tested. 1] [22]  Positive results were titrated to endpoint dilutions.
Acknowledgements: We thank the patients,  Bounthaphany Bounxouei  (Associate Professor and former Director) and the staff of  Mahosot Hospital , especially those of the  Microbiology Laboratory  and the wards, the late  Rattanaphone Phetsouvanh , and  Vayouly Vidhamaly ,  Konnie Bellingham ,  Kum Thong Wong ,  Rogier van Doorn ,  Guy Thwaites  and  Paul Turner , for their advice and technical help. We also thank  Bounnack Saysanasongkham  ( Associate Professor  and former Director of  Department of Health Care, Ministry of Health ) and  H. E. Bounkong Syhavong  ( Associate Professor  and former Minister of Health), Laos, for their kind help and support. The views expressed are those of the author(s) and not necessarily those of the  NHS , the  NIHR  or the  Department of Health ,  UBC , or Vancouver Coastal Health.
Funding: This work in Laos was supported by the  Wellcome Trust  [grant number  104079/Z/14/Z ]. SRI is supported by the  BMA   Research Grants -Vera Down grant  [2013] and  Margaret Temple  [2017],  Epilepsy Research UK  [P1201], the  Fulbright UK-US commission [MS Society  research award] and by the  NIHR Oxford Biomedical Research Centre. CEU is supported by the  Friedman Award for Scholars in Health  ( University of British Columbia, Canada ) and received salary support from the  UBC Division of Neurology (Vancouver, Canada ). AA-D is supported by the  Wellcome Trust  [ 205126/Z/16/Z ],  National Institute for Health Research (NIHR) Oxford and Oxford Health Biomedical Research Centres (BRC ) and by a  British Medical Association (BMA)  foundation for medical research Margaret Temple prize 2017.
This does not mean that the discovery of Asgard archaea was not a seminal breakthrough since these Archaea indeed provide exciting new data to understand the emergence of Eukarya. Phylogenetic analyses revealed that the odd distribution of some Eukaryotic Signature Proteins (ESPs) was most likely due to extensive LGT between Asgard and proto-eukaryotes  54. Studying these proteins will thus help us to reconstruct their history in the proto-eukaryotic lineage. The extensive LGT that we observed between Asgard archaea and proto-eukaryotes also suggests that these organisms were thriving together for a long time before LECA in the same environments, indicating that study of the Asgard archaea should shed light on the type of environment inhabited by our proto-eukaryotic ancestors. The first cultivated Asgard archaeon, Candidatus Prometheoarchaem synthrophicum, turned out to be dependent for growth on its physical association with a methanogenic archaeon  55.
From the analysis of 10,575 genomes, 381 protein markers, and "1. 16 trillions non gap amino-acids," the authors concluded that the branch that separates Archaea and Bacteria was much shorter than previously thought  56. In their published tree, this branch was indeed shorter than the branches separating some bacterial groups altogether. If this was correct, there was no longer a reason to separate Archaea from Bacteria, prokaryotes being reunified in one domain, as in the pre-Woese area. Looking even cursorily at the data supporting this claim, it was obvious that there were many flaws in this conclusion. The authors only included 6 of the 34 ribosomal proteins shared between the two domains in their data set of 381 proteins. They also included in their data set proteins that have been affected by LGT between Archaea and Bacteria.
This is, for instance, the case of DNA gyrase, which is a bacterial protein recruited by some Archaea (Ref. 50 nd references therein). This paper was indeed subsequently refuted by Moody and colleagues, who identified both LGT and hidden paralogy in the data set of Zhu and colleagues  49. They noticed that 14 trees include no archaea, something a priori unbelievable when the aim was to measure the distance between the two domains, and that 68 others contain less than 25% of the sampled archaea. Strikingly, the monophyly of Archaea and Bacteria (a prerequisite for this kind of analysis) was only recovered in 22 of the 381 published trees  49. This indicated that, as in the case of DNA gyrase, most of the 381 proteins were not present in LUCA but were transferred by LGT from one domain to the other.
Archaea were again underrepresented in many trees with very low diversity. I have also looked at the data and arrived at a similar conclusion. Using as criteria the fact that Archaea and Bacteria should be separated by long branches and that both domains should be represented by a reasonable collection of distantly related phylums, I found that only 15-20 of the 355 "LUCA" proteins in the data set of Weiss and colleagues were probably present in LUCA (unpublished observations). One can conclude that the proteome of LUCA is still on the table. One can wonder why the papers supporting fusion scenarios between Archaea and Bacteria for the origin of eukaryotes or claiming that the branch between Archaea and Bacteria is vanishing were published in first-rate journals and received substantial press coverage.
This is probably because they perpetuate the prokaryote/eukaryote paradigm, which remains so precious to many biologists. The term prokaryote is still widely used and some authors even continue to use the term archaebacteria. Unfortunately, the confusion will remain with the new nomenclature proposed in the Genome Taxonomy DataBase (GTDB) since they include "bacteria" in the name of two major new archaeal phyla "Halobacteriota" and "Methanobacteriota"  60. Notably, this is based on the strict rules of the International Code of Nomenclature of "Prokaryotes" that still does not discriminate between Archaea and Bacteria. In my opinion, the renewal of the prokaryote/eukaryote paradigm is an unfortunate byproduct of the genomic and metagenomic era. Archaeal and bacterial genomes are indeed very similar (small, compact, organized in operon, etc.
CONCLUSION Three years before his death, Carl Woese wrote: "the 'prokaryote era' is fast drawing to a close, and many microbiologists (especially the younger ones) are no longer structured in their thinking by the prokaryote notion" 6. Unfortunately, this was too optimistic since the prokaryotic notion is again on the rise and the Eocyte (Asgard) scenario is now the new paradigm. Most scientists working on Archaea work within the framework of this paradigm, even when the data move in the other direction. For instance, whereas Asgard viruses detected are typical for archaeal viruses, some authors emphasize the eukaryotic features of Asgard Caudoviricetes (head and tailed viruses), although these features are also present in some bacterial Caudovircetes  63, 64. Interestingly, Jüttner and Ferreira-Cerca recently reported that all Asgard archaea, except Odinarchaea, have unlinked tRNA genes  65.
In conclusion, I think that most of Carl Woese proposals turned out to be right; LUCA was most likely a much simpler organism than modern organisms (although not as simple as he suggested) and the living except viruses, can be adequately represented by a trinity: Archaea, Bacteria, and Eukarya. The tree of life topology preferred by Carl Woese, with Archaea and Eukarya being sister groups, is most likely the right one, even if this is not yet recognized today. In the summary of this essay, I wrote that most of Carl Woese's ideas will probably be recognized in the future. This means that Carl Woese is still ahead of our time. This is possibly an optimistic view, but I really think that our present knowledge in molecular biology and critical analysis of already published phylogenetic data are sufficient to bet in favor of Woese's tree.
To characterize the whole bacterial diversity, DNA blood samples were typed using a high-throughput bacterial 16S rDNA (rrs) sequencing approach (bacterial barcoding, as described in  (12) ). Bacteria were characterized as operational taxonomic unit (OTU) and amplicon sequence variants (ASV), and taxonomically assigned using the Silva database (https://www. arb-silva. de/). Examination of OTUs and ASVs revealed the presence of Anaplasma sequences in one DNA sample. No OTU and ASV assigned to the Anaplasma genus or to the Anaplasmataceae family was detected in the 362 other samples. We further conducted two independent Anaplasma-specific PCR assays targeting a region of the 16S rDNA gene (544 bp) and the 23S-5S (ITS2) intergenic region (423 bp) following Calchi 2020  (13) , and obtained amplicons of correct sizes for the positive sample.
The Sanger sequencing of amplicons obtained with each pair of primers each confirmed the presence of Anaplasma. These sequences have been deposited on GenBank (accession numbers: ///pending///). We used BLAST (http://www. ncbi. nlm. nih. gov/blast/Blast. cgi) to compare these 16S rDNA and ITS2 nucleotide sequences with Anaplasma sequences available in GenBank. None of the nucleotide sequences observed in this study is 100% identical to known Anaplasma sequences. The 16S rRNA sequence showed highest identities with Anaplasma found in wild fauna of Brazil, including an Anaplasma sp. detected in Amblyomma coelebs ticks collected on South American coatis, Nasua nasua (99. 8%; GenBank MT019560), another Anaplasma sp. of black rats, Rattus rattus (99. 8%; GenBank KY391803), and Candidatus Anaplasma amazonensis (13) of brown-throated sloths, Bradypus variegatus, and of two-toed sloths, Choloepus didactylus (99.
1%; GenBankMT199827). All other Anaplasma species showed identities <99%. The ITS2 sequences showed highest nucleotide identity with Cand. Anaplasma amazonensis of Brazilian brown-throated sloths and two-toed sloths (96. 8%; GenBankMT267354), and lower identities with other Anaplasma species or strains (<92%). On account of these distinct genetic traits, we propose the designation Cand. Anaplasma sparouinii for this novel bacterium. The specific name refers to the Sparouine River where the infected patient lived. We conducted phylogenetic analyses based on these 16S rDNA and ITS2 nucleotide sequences using the maximum-likelihood (ML) method. We obtained trees of similar topologies with a robust clustering of Cand. Anaplasma sparouinii with some Anaplasma associated with Brazilian wild fauna: Cand.
Acknowledgments We thank the medical staff health centers in French Guiana, especially the one in  Grand Santi  and the field team that collected the data ( Louise Hureau-Mutricy ,  Audrey Godin ,  Mylène Cebe ,  Alan Ribeiro ). The research was supported by funding from  'Investissements d'Avenir ' grants managed by the  Agence Nationale de la Recherche  ( ANR, France, Laboratoire d'Excellence CEBA, ref. ANR-10-LABX-25-01 ).
Material and methods We combined a regional epidemiological model of MAP spread between dairy cattle herds with a trade movement rewiring algorithm to manipulate observed trade movements between herds and render them risk-based. Animal movements and herd demography are derived from observed data in Brittany, western France. The model is stochastic, individual-based, and in discrete time, with a time-step of one week. The code is available under the Apache 2. 0 license (Sup. Mat. §5). This model was used to compare the regional spread of MAP when using observed trade movements versus a rewiring algorithm rendering trade movements risk-based. We identified herds that had a very high probability of being MAP-free (i. e. , with a very low-risk status). We assessed the extent to which decreasing the risk of these herds purchasing infected animals had an impact on the regional spread of MAP.
Cattle demographic and movements We used data from Brittany (western France) from 2005 to 2013. This area is characterized by a high density of dairy cattle (85 % of cows are dairy cows). We focused on farms with over 15 dairy breeding females, assumed to be professional dairy farms. French dairy herds are mainly composed of females since breeding is based on artificial insemination instead of bulls. Thus, we considered only dairy or crossedbred females, neglecting fattening activities often conducted in a different area of the farm. As a result, we selected 12,857 dairy cattle herds and 919,304 trade movements. We calculated herd size and demographic parameters (calf mortality, culling rate per age group and per parity for cows, and births) using the comprehensive French database of cattle detention and trade movements (Table  S3 ).
This database records the life history of all dairy cattle from birth to death, including trade movements between farms. Each animal is defined by a unique ID number, breed, date and farm of birth, sex, and all the farms it has belonged to over its life, as well as the cause and date of entry into each farm (birth, purchase), and the cause and date of exit from each farm (death, sale). Herd size was calibrated to 1 January 2005. Births were calculated per week per herd. Other demographic parameters were calibrated for each herd-year. We also used these data to build the trade network, in which nodes are farms and links are trade relationships. This network is directed (trade is not symmetric), weighted (the number of animals exchanged varies among pairs of farms) and time-varying (animal transactions occur at specific times).
Between-herd epidemiological model We applied the epidemiological model to the population and infection dynamics in each of the 12,857 herds selected in the data. Trade movements connect herds in a data-driven manner. When an animal is sold in the observed database, an animal in the same age group is picked at random in the selling herd and sent to the purchasing herd. Hence, only the infection status of the traded animal is random, but the date and type of movement are data-driven. External purchases also can be a source of MAP. We considered that these movements are associated with a similar risk as movements occurring among herds of the modelled metapopulation, assuming the modelled metapopulation belongs to a larger production area implementing similar control options. To do so, we considered that the probability of purchasing an infected animal from outside equals the average proportion in the modelled metapopulation of infected animals in the age group of the purchased animal.
Comparing the observed and simulated distributions of the in and out-degree of the trade network showed that the impact of this simplification was low (Sup. Mat. §2, Fig. S1 ). In Brittany, dairy animals are mostly Holsteins, thus breed was not considered. Second, we distributed these movements according to the infection statuses of the selling and of the purchasing herds. Third, we identified high-risk movements (i. e. , those from highrisk to low-risk herds). We switched them as much as possible with a relevant alternative. Unused low-risk movements were performed as observed. Fourth, for high-risk movements that cannot be switched (i. e. , no relevant alternative available), the sold animal is culled and another animal is purchased from outside the modelled metapopulation with the same risk of being infected as in other movements coming from outside in the observed database.
Funding The  French Research Agency (ANR) , grant number  ANR-16-CE32-0007-01  ( CADENCE) ,  GDS Bretagne  and  INRAE  are acknowledged for providing financial support. The  Groupement de Défense Sanitaire de Bretagne  and the  French Ministry of Agriculture (DGAl)  are thanked for providing the movement data used in this work. This work was performed using HPC resources from  GENCI-[CINES/IDRIS/TGCC](Grant 2021-[A0100312468 ]).
In this contribution, OCT data are presented not only in the form of tomograms, but also as enface topography maps (h, i in Figs  6  and 7 ) of examination areas showing topography of the paint surface before and after the test of varnish removal. In order to generate such maps a surface pro le was extracted from 3D OCT data cube composed of 150 B-scans and collected after every cleaning step. Then the surface pro les obtained after cleaning are subtracted from the ones acquired before, which enable assessing the bulk of material removed in every step in a form of a differential maps  [5] , also coded in false colour scale (j in Figs  6  and 7 ). Here, for conciseness only maps obtained after the nal cleaning step are shown.
7 and 12x12 mm 2 test no. 9) were marked by 'windows' cut in Mylar foil. As the rst part of every test, before commencing actual cleaning, a FTIR spectrum was collected in the middle of the marked square area. The painting was then placed under the OCT head with a scanning beam projecting down and OCT data was collected. Afterwards, the solvent cleaning procedure was applied by rolling cotton swabs on the surface of varnish without moving of the OCT head (with 43 mm distance from the lens to the painting). Then the OCT data were collected again for the repeatability of scans and thus for a precise comparison between the scans obtained before and after this treatment step. Subsequently, the painting was transferred for FTIR analysis on the same marked area, and, for the next cleaning step, repositioned again under the OCT instrument.
This procedure was repeated for as many steps as necessary. Due to the relatively large size of the FTIR data collection spot (3mm) it was feasible to position the painting for repeated measurements within the designated foil window. For the OCT measurements, however, a micrometric scale precision is necessary for the comparison of tomograms and generation of differential maps from subsequent cleaning steps. Mechanical limiters were used for coarse positioning of the painting after relocation with precision of about 50 μm in X,Y directions but with no control in Z direction. Software matching of the B-scans taken from the OCT data collected before and after repositioning enabled achieving the desired micrometric alignment (better than the distance between B-scans in Y direction: 80 μm, better than twice the lateral resolution in X direction and better than twice the axial resolution in air in Z direction).
Conclusions As breast cancer is the most common cancer and the leading cause of mortality in women worldwide, there is an urgent need to develop new therapies targeting this aggressive malignancy. During the last few years, a growing novel list of personalized therapies has been approved for the treatment of breast cancer including alpelisib targeting PI3K, talazoparib and olaparib that target germline BRCA mutated breast cancer, and abemaciclib as a cell cycle inhibitor for patients with high Ki67  [138]. However, despite all these advancements that have led to a very new era of precision medicine in the management of breast cancer, more than 1800 women die every day from this cancer. Furthermore, when reviewing the ongoing clinical trials, we can find that, apart from Elacestrant, which is a novel oral estrogen degrader, there are no new breast cancer therapies entering human clinical trials according to clinicaltrials.
Practice-Based Learning and Improvement There are three milestones mapped to Practice Based Learning and Improvement (PBLI). Similar to the Neurology Milestones, these milestones assess the ability to use data and evidence in clinical practice, develop a learning plan, and engage in scholarly activity. The milestone on scholarly activity is listed as optional. Although not all fellowships require scholarship of their trainees, 100% of North American programs have fellows engage in some clinical research. 5 We believe the ability to assess trainees' scholarly pursuits is important to many programs.