dataesr/scientific-paragraphs-categorization huggingface dataset:
Discussion: This SR highlights the clinical knowledge gap in the use of melatonin for neuroprotection in NE despite supportive pre-clinical and animal data. There is a dearth of clinical data on longterm neurodevelopment outcome of melatonin therapy in NE. Melatonin's role as an additional supportive therapy in NE without HT requires further exploration in better designed clinical trials; currently, available evidence is from a small number of low-quality studies. The metaanalysis of melatonin as an adjunct therapy to HT in NE did not reveal benefit for mortality. However, caution must be exercised in the interpretation of this result due to the very small sample size, and this LOE is GRADED as very low. The strengths of this SR include a comprehensive search strategy across multiple databases and the evaluation of multiple clinically relevant outcomes.
Hence, melatonin should be administered as early as possible to achieve the therapeutic levels for better neuroprotection  19, 30. Although no definite melatonin neuroprotective protocol can be recommended presently, pre-clinical studies suggest a melatonin dose of 20-30mg/kg given as soon as possible, after birth. 31 Two relevant studies NCT03806816 (MELPRO trail) and NCT02621944 may be able to answer some of these pharmacokinetic, safety, and clinical outcome questions in the future. As melatonin is sparingly soluble in aqueous vehicles, solubility enhancers, such as ethanol, have been used, to obtain a solution with the desired concentration. The use of ethanol as an excipient could have been a confounding factor in previous pre-clinical  [32] [33] [34]  and clinical studies, including the study by Fulia 2001 included in this SR where melatonin was dissolved in a 1:90 mixture of ethanol:0.
MRI and EEG finding at follow up 4. Persistent Seizures disorder 5. Biomarkers of brain injury such as S100-B. The Medline, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL), LILACS, and Cochrane Central Register of Controlled Trials (CENTRAL) databases were searched applying the combinations of controlled vocabulary (e. g. , MeSH/Emtree) and free text words guided by our PICO parameters. No language restriction was applied. The details of search terms, including the search strategies for individual databases, are available in Supplemental Information. Google search has also been conducted to minimize publication bias. The search was conducted for the period between inception till 31 st May 2020. Data extraction: Author AKP conducted the initial search in all the databases, and the final list was assimilated.
3. 3 MRI and EEG finding at follow up 4. Persistent Seizures disorder 5. Biomarkers of brain injury such as S100-B. The Medline, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL), LILACS, and Cochrane Central Register of Controlled Trials (CENTRAL) databases were searched applying the combinations of controlled vocabulary (e. g. , MeSH/Emtree) and free text words guided by our PICO parameters. No language restriction was applied. The details of search terms, including the search strategies for individual databases, are available in Supplemental Information. Google search has also been conducted to minimize publication bias. The search was conducted for the period between inception till 31 st May 2020. Data extraction: Author AKP conducted the initial search in all the databases, and the final list was assimilated.
15  This was observed in the exhaustive population of cancer patients treated in the cancer center over a 6-year period, screening the patient records of the exhaustive database of patients with an FPC treated in a comprehensive cancer center, the Centre Léon Bérard (CLB). 16 n the present work, we explore the impact of ICIs on the reduction of the risk of SPC according to patient characteristics, different age groups and histotypes, exploring also the interaction with the administration of cytotoxic chemotherapy (CC) for the FPC. The incidence of SPCs was reduced in all subgroups after exposure to immunotherapy with ICIs and/or CC in this series of 46 829 patients.
Patients All patients, adults and children, diagnosed with a primary tumor in the CLB, Lyon, France, from January 2013 to December 2018 were considered in this work. Data from patients with a newly diagnosed malignant tumor or locally aggressive, rarely metastasizing tumors (e. g. giant cell tumor or bone or desmoid tumors) between January 2013 and December 2018 were collected. Only patients not opposed to the re-analysis of their anonymized health data within internal academic studies were included according to the standard operating procedures of the CLB and national and European Union (EU) legislation. Specifically, the study was approved by the national commission [CNIL Délibération number 2016-331 of 10 November 2016 (authorization number 1773637)] and by the local institutional review board of the CLB in May 2019.
Extracting electronic patient records with the ConSoRe tool The electronic patient records (EPR) of the patients of the CLB matching the inclusion criteria and diagnosed from January 2013 to December 2018 were first extracted for structured data, e. g. age sex, histological types of cancers, dates of diagnosis. The EPR system of the CLB includes a standard set of data [e. g. tumor(s) characteristics, staging, first treatments, dates, follow-up], but other information such as subsequent lines of treatment may be present only in unstructured data formats. For these, the EPRs were extracted with the ConSoRe tool  15  (https://www. swordgroup. com/en/news/projet-consore). ConSoRe is an academic data analytics solution aggregating diverse forms of structured and unstructured data extracted from EPR and structuring cancer management for all patients.
ConSoRe uses natural language processing to search aggregated data and perform advanced data mining. Both cancers and locally aggressive tumors that rarely (<5%) metastasized, typically desmoid tumors or giant cell tumors of the bones, were added. The characteristics extracted included: sex, age, dates, histotype and stages of first and second cancers, surgery, chemotherapy, radiotherapy (RT) and immunotherapy for the first cancer, relapse (and date) of the first cancer, date of last news and date of death. The extracted relevant structured data was integrated into Excel files. Of the 2119 patients, 1455 (68. 7%) with SPCs identified by the ConSoRe program had their SPCs formally declared by their responsible physician in the EPR. In addition to this Con-SoRe extraction, 2818 EPRs were manually screened to confirm immunotherapy use for the FPC and/or for the presence/absence of a diagnosis of SPC.
An analysis of the genomic and molecular characteristics of these SPCs occurring after immunotherapy is ongoing. This study has several limitations. Part of the data was collected through an automatic extraction using natural language processing of the EPR. To ensure the quality of data extracted through this screening, a second, manual, screening of 2818 files was thus carried out by the team on all patients who received immunotherapy and on those where the diagnosis of SPC had not been formally declared by the physician in charge. Only six additional SPCs were identified by this procedure. Another limitation is that the follow-up of the series is 19 months; indeed further analysis will be required in the same series in the years to come to determine whether our results point to a reduction of the incidence or only to a prolonged delay to diagnosis.
Specific analysis of given histological subtypes will be required in the future. Though consistent for each individual year here, this early reduction in the risk of SPC requires validation from other large series and datasets. This is a large, exhaustive, but single-center study that needs to be confirmed using other exhaustive databases of EPRs of comprehensive cancer centers. It must be stressed that this study is not a clinical trial and additional series are needed to confirm this observation. These results have potentially important consequences, in particular in adolescents and young adults cured of the first cancer and in whom SPCs are important causes of death. Their long life expectancy may expose a high cumulative risk of second primary malignancy. Several studies have explored the immunological environment of premalignant lesions and indicate the presence of active immune responses.
27, 28, 30, 31 ltogether, these results collected in a large exhaustive database of 46 829-patient population treated in a comprehensive cancer center indicates that the risk of SPC is reduced in the years following the treatment of the cancer when immunotherapy with ICIs is used for the treatment of the first cancer. These results are consistent in all age groups, for all histotypes and in each of the different years of this study. A longer follow-up will be needed to determine whether this reduction of incidence of SPC is maintained over time. If these observations are confirmed, these results open a novel area of clinical research in tertiary prevention for cancer patients, which could test an active prevention of SPCs in a population of patients at high risk, such as those with germline predisposition to cancer or with long term exposure to carcinogens such as smoking.
ANR-10-LABX-0061 ];  PIA Institut Convergence François Rabelais PLAsCAN  [grant number PLAsCAN,  17-CONV-0002 ];  RHU4   DEPGYN  [grant number  ANR-18-RHUS-0009 ];  EURACAN  [grant number  EC 739521 ]; Association DAM's (no grant number); la  Fondation ARC  (no grant number);  Infosarcome  (no grant number);  Ligue de L'Ain Contre le Cancer  (no grant number) and  La Ligue Contre le Cancer  (no grant number). DISCLOSURE DP: research grant: MSDAVENIR; honoraria:  Roche ,  BMS, MSD, AstraZeneca ; travel:  AstraZeneca. AF: grants, personal fees and nonfinancial support from  ROCHE, AZ ,  Pfizer ,  MSD ,  BMS. JF: grants, personal fees and nonfinancial support from  AZ ,  MSD ,  BMS ,  Merck Serono, Biogen ,  Rakuten ,  Roche ,  Servier. OT:  Roche ,  AstraZeneca ,  Novartis ,  Pfizer ,  MSD ,  BMS ,  Sandoz.
Vickers microhardness was measured using a diamond pyramid applied to a polished surface of an alloy sample at 1000 g load for 15 s. Phase analysis was conducted using X-ray diffraction under Cu K α1 radiation in the 2θ range of 10 to 140 • , as well as with the use of an electron backscatter diffraction (EBSD) technique. Microstructure and local chemical analysis were studied using scanning electron microscopy (SEM) equipped with backscatter electron (BSE) and energy dispersive spectroscopy (EDS) and EBSD detectors. Local crystal structure analysis was carried out by transmission electron microscopy (TEM), employing electron diffraction techniques on a sample that was extracted from the bulk using a conventional lift-out technique within a focused ion beam (FIB) microscope. Equilibrium phase diagrams for the studied alloys were calculated based on the CAL-PHAD method, using ThermoCalc software and the TCHEA4 thermodynamic database developed by ThermoCalc  [7] , and Pandat software and the PanNb2020 database developed by CompuTherm, LLC  [5, 8, 9].
Effect of Re on the Microstructure and Phase Composition In order to interpret the effect of Re additions on the microstructure evolution of the studied alloys, the experimental results were compared with the respective phase diagrams calculated using the CALPHAD approach. Results of first principal calculations for stable and metastable phases available at the Materials Project website  [12] , as well as already available phase diagrams  [13, 14] , were also used in the analysis. Thermo-Calc software and the TCHEA4. 1 database, as well as Pandat software and the PanNb2020 database, were used for CALPHAD calculations. The results are shown in Figures  14 15 16 , and a detailed analysis is given below.
It can be seen that both databases agree with each other when predicting (a) the formation of a single BCC1 phase after solidification, (b) approximately the same solidus temperature, and (c) approximately the same solvus temperature for the BCC2 phase. The main disagreement between the TCHEA4. 1 and PanNb2020 databases is in predicting different types of Re-rich phases. In particular, TCHEA4. 1 predicts the presence of a ReZr 2 sigma phase below 967 • C, while PanNb2020 predicts a hexagonal C14 Laves phase below 1656 • C. Formation of the ReZr 2 sigma phase by a peritectic reaction at 1900 • C and the ZrRe 2 Laves phase by a peritectic reaction at 2450 • C in the binary Re-Zr system was previously reported by Savitskii et al. [16, 17]. First principle calculations show that the ReZr 2 sigma phase is metastable, while ZrRe 2 is thermodynamically stable in the binary Re-Zr system  [18].
According to TCHEA4. 1, Nb and Ti additions suppress the formation of the sigma phase to below 1000 • C and completely suppress formation of the Laves phase. On the other hand, according PanNb2020, Nb and Ti additions completely suppress formation of the sigma phase in favor of a ternary Zr(Re, Nb) 2 Laves phase. Caution is needed in comparing CALPHAD predictions with the present experimental data, as the former represent equilibrium conditions and the latter represent a short annealing at a high temperature (1400 • C/3 h) during HIP, followed by a controlled cooling rate. Nevertheless, when the CALPHAD results are compared to the experimental data, it is found that neither database predicts a secondary phase with the FCC structure. It is likely that this phase forms in ternary or even quaternary systems and is absent in the TCHEA4.
1 and PanNb2020 databases, which often emphasize binary data. As a result, ThermoCalc and Pandat instead minimize the energy among the other available phases; and Pandat gives a better agreement with the experiments. Indeed, the Re-rich secondphase particles have a composition and volume fraction similar to the calculated ternary Laves phase at ~1200-1250 • C. Moreover, the microstructure of deformed samples indicates that the second-phase particles are more likely to be present at 1000 • C, while according to TCHEA4. 1, the alloy should be a single-phase BCC structure at this temperature. However, EBSD and TEM results indicate that the second phase has a FCC crystal structure, with a rather large lattice parameter (a = 0. 756 nm), while PanNb2020 predicts a hexagonal (C14) Laves phase. On the other hand, a first principle analysis of the Nb-Ti-Re system predicts the presence of a stable NbTiRe 2 Heusler phase, with the space group Fm3m (225) and the lattice parameter a = 0.
3 NbTiZr at 800 • C. The earlier study also explored a phenomenological correlation between RT yield strength and T m (see Figure  4a  in  [22] ), and no clear trend was shown for multi-phase microstructures. In the present work, CALPHAD predictions of T m differed by less than 200 • C for all four alloys using the two different databases. This small difference in T m , and the lack of a strong influence of m on the strength in multi-phase RCCAs, suggests that this did not make a major contribution to the observed changes in the RT properties with Re additions. The metallic atomic radius of Re (r Re = 137. 5 pm) is smaller than all the other elements in the presently studied alloys (r Ti = 146. 2 pm, r Nb = r Ta = 143 pm, r Zr = 160. 2 pm)  [23, 24]  Furthermore, the shear modulus of Re (G Re = 178 GPa) is much larger than the other elements (G Ti = 44 GPa, G Zr = 33 GPa, G Nb = 38 GPa, G Ta = 69 GPa)  [25, 26].
Since transduction events cannot be identified unambiguously from the genome sequences, we searched for prophage acquisition events, i. e. , for the transfer of temperate phages from one bacterial genome to another. We found that 97% of the strains were lysogens, with 86% being poly-lysogens, in line with our previous results in a much smaller dataset  [25]. In total, 9,886 prophages were identified in the genomes. Their genes account for 16,319 families (19. 5%) of the species pangenome (Fig  1B ). We then measured the gene repertoire relatedness weighted by sequence identity (wGRR) between all pairs of prophages. The wGRR is a measure of genetic similarity that amounts to 0 if there are no homologs between two genomes, and one if all genes of the smaller genome have a homolog with 100% identity in the other genome.
Capsule inactivation follows specific paths, might be driven by phage predation, and spurs HGT We sought to investigate whether the aforementioned swaps occur by an intermediary step where cells have inactivated capsule loci. To do so, we first established the frequency of inactivated capsular loci. We used the Kaptive software to detect missing genes, expected to be encoded in capsule loci found on a single contig. We also used the Kaptive database of capsular proteins to detect pseudogenes using protein-DNA alignments in all genomes. We found 55 missing genes and 447 pseudogenes, among 9% of the loci. The frequency of pseudogenes was not correlated with the quality of the genome assembly (see "Identification of capsule pseudogenes and inactive capsule loci"), and all genomes had at least a part of the capsule locus.
To confirm these results, we made several controls. To show that this is not simply an effect of gene length, we normalized the inactivation frequency by gene length and found the same relationship (S4A Fig, p = 0. 005, R 2 = 0. 7). To check that this was not a mutation hotspot induced by simple sequence repeats, which are prone to polymerase-slippageinduced mutations and sequencing errors, we searched for mono-and di-nucleotide tracts. We found that their frequency in the commonly inactivated pair wcaJ/wbaP was smaller than in the rarely mutated group of genes wzc/wzx/wzy (S4B Fig). Finally, we verified that our analysis was not impacted by a higher allelic diversity in these genes in the reference database. We found that the most genetically diverse genes were not the most inactivated (S4C Fig).
After 3 days, non-capsulated clones emerged in 22 out of 24 populations from 8 different ancestral strains. We isolated one non-capsulated clone for Illumina sequencing from each population and searched for the inactivating mutations with the same pipeline as for the genomic dataset. We also compared our method with two popular tools used to detect new mutations in evolved isolates, breseq  [37]  and snippy, which rely on read mapping onto a reference genome. All 3 approaches yielded comparable conclusions, although some mutations were not found by all 3. Overall, 13 out of the 16 inactivated or deleted genes found by our method were also identified by either breseq, snippy, or both. Read mapping approaches detected other types of mutations, like intergenic mutations, and few mutations in the rest of the genome, which are not detectable by our targeted approach (https://doi.
We found 35 such loci, accounting for approximately 0. 9% of the dataset (for example, a wzc_KL1 allele in an otherwise KL2 loci), with only one occurrence of a wcaJ allele belonging to another CLT, and none for wbaP. Finally, the analysis of recombination tracts detailed above reveals frequent replacement of the entire locus between galF and ugd by recombination (S1 Fig,  scenario 3 ). Since reacquisition of the capsule function might often require HGT, we enquired if capsule inactivation was associated with higher rates of HGT. Indeed, the number of genes gained by HGT per branch of the phylogenetic tree is higher in branches where the capsule was inactivated than in the others (2-sample Wilcoxon test, p < 0. 0001, Fig  4A ), even if these branches have similar sizes (S6 Fig). We compared the number of phages and conjugative systems acquired in the branches where capsules were inactivated against the other branches.
Genomes We used the PanACoTa tool to generate the dataset of genomes  [64]. We downloaded all the 5,805 genome assemblies labeled as Klebsiella pneumoniae sensu stricto (Kpn) from NCBI RefSeq (accessed on October 10, 2018). We removed lower-quality assemblies by excluding genomes with L90>100. The pairwise genetic distances between all remaining genomes of the species was calculated by order of assembly quality (L90) using MASH  [65]. Strains that were too divergent (MASH distance >6%) to the reference strain or too similar (<0. 0001) to other strains were removed from further analysis. The latter tend to have identical capsule serotypes, and their exclusion does not eliminate serotype swap events. This resulted in a dataset of 3,980 strains which were re-annotated with prokka (v1. 13. 3)   [66]  to use consistent annotations in all genomes.
Erroneous species annotations in the GenBank files were corrected using Kleborate (https://github. com/katholt/Kleborate). This step identified 22 Klebsiella quasipneumoniae subspecies similipneumoniae (Kqs) genomes that were used to root the species tree and excluded from further analyses. The accession number for each analyzed genome is presented in https://doi. org/10. 6084/m9. figshare. 14673156, along with all the annotations identified in this study.
Pan-and persistent genome The pangenome is the full repertoire of homologous gene families in a species. We inferred the pangenome with the connected-component clustering algorithm of MMSeqs2 (release 5)  [67]  with pairwise bidirectional coverage >0. 8 and sequence identity >0. 8. The persistent genome was built from the pangenome, with a persistence threshold of 99%, meaning that a gene family must be present in single copy in at least 3,940 genomes to be considered persistent. Among the 82,730 gene families of the Kpn pangenome, there were 1,431 gene families present in 99% of the genomes, including the Kqs. We used mlplasmids to identify the "plasmid" contigs (default parameters, species "Klebsiella pneumoniae"  [68] ). To identify the pangenome of capsular loci present in the Kaptive database, we used the same method as above, but we lowered the sequence identity threshold to >0.
We did not use the gamma correction because of branch length scaling issues, which were 10 times longer than with simpler models, and is related to an optimization problem with big datasets in IQ-TREE. The tree is very well supported, since the average ultra-fast bootstrap support value was 97. 6% and the median was 100%. We placed the Kpn species root according to the outgroup formed by the 22 Kqs strains. The tree, along with Kleborate annotations, can be visualized and manipulated in https:// microreact. org/project/kk6mmVEDfa1o3pGQSCobdH/9f09a4c3.
Capsule locus typing We used Kaptive  [17]  with default options and the "K locus primary reference" to identify the CLT of strains. The predicted CLT is assigned a confidence level, which relies on the overall alignment to the reference CLT, the allelic composition of the locus, and its fragmentation level. We assigned the CLT to "unknown" when the confidence level of Kaptive was indicated as "none" or "low," as suggested by the authors of the software. This only represented 7. 9% of the genomes. After this filtering, we simply considered that 2 CLT are the same if they are both annotated with the same KLx name.
Identification of capsule pseudogenes and inactive capsule loci We first compiled the list of missing expected genes from Kaptive, which is only computed by Kaptive for capsule loci encoded in a single contig. Then, we used the Kaptive reference database of Kpn capsule loci to retrieve capsule reference genes for all the identified serotypes. We searched for sequence similarity between the proteins of the reference dataset and the 3,980 genome assemblies using blastp and tblastn (v. 2. 9. 0)  [73]. We then searched for the following indications of pseudogenization: stop codons resulting in protein truncation, frameshift mutations, insertions, and deletions (https://doi. org/10. 6084/m9. figshare. 14673153). Truncated and frameshifted coding sequences covering at least 80% of the original protein in the same reading frame were considered functional.