dataesr/scientific-paragraphs-categorization huggingface dataset:
Discussion The main objective of this study was to evaluate the tolerance to adhesive biofilms containing prebiotics and sodium alginate in patients with pSS and hyposialia. The secondary objectives were to obtain initial efficacy data regarding the clinical effectiveness of such biofilms in improvement of signs and symptoms related to dry mouth and to assess potential changes in the oral microbiota. Tolerance to prebiotic and sodium alginate biofilms was assessed by the patients (VAS 66. 7 and 87. 6, respectively) and by the practitioner (90 and 100%, respectively). Estimation of the absolute changes in the VAS scores at the beginning and end of each treatment period highlighted an improvement in the VAS for mouth dryness for the sodium alginate biofilm versus prebiotic biofilm, while no difference in the VAS scores was observed for other parameters.
Results Of the 212 identified articles, 15 retrospective studies and one prospective uncontrolled study met our inclusion criteria. Three studies reported findings from national databases. The males/females ratio is 9/1. Mean age was 60. 3 years, which was younger compared to other laryngeal malignancies. The alcohol, cigarette overuse and the HPV status of patients were lacking in most studies. Glottis and supraglottis were the most common anatomical locations, corresponding to 78. 7% and 12. 4% of cases, respectively. The main therapeutic approaches consisted of surgery, radiotherapy, surgery followed by radiotherapy. Treatments reported 5-year overall survival and diseasespecific survival of 86. 3 and 90. 8, respectively. The 5-and 10-year local control rate were 83. 6 and 72. 6, respectively.
Search strategy The paper search was carried out by three independent authors (JRL and SH) with PubMED, Scopus, and Cochrane Library databases. The databases were screened for abstracts and titles referring to the description of features of LVC patients. Authors analyzed full texts of the selected papers. Results of the search strategy were reviewed for relevance and the reference lists were examined for additional pertinent studies. Any discrepancies in synthesized data were discussed and resolved by the remaining co-authors. The following MeSH/keywords were considered: 'larynx'; 'laryngeal'; 'cancer'; 'verrucous'; 'carcinoma'; 'treatment'; 'survival'; 'outcomes'.
Results A total of 212 articles were identified. Among them, 16 studies published between 1976 and 2020 met our inclusion criteria (Fig. 1 )  [3, 8, 12, [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26]. Two studies were excluded because overlapping with other case-series  [27, 28]. Fifteen studies were retrospective (EL: IV) and there was a prospective uncontrolled study (EL: III) (Table  1 ). Three studies reported findings from national databases, i. e. the Slovenian national database  [22] , national cancer database  [25] , and surveillance, epidemiology, and end results (SEER)  [3]. There would be potential overlaps between the two U. S. database studies  [3, 25]  but authors did not investigate similar findings. The present systematic review reported the features of 948 patients with LVC (Table  2 ).
Therapeutic strategies From retrospective studies published between 1976 and 2020, the main therapeutic approaches consisted of surgery, radiotherapy, surgery followed by radiotherapy or chemotherapy (Table  3 ). Various surgical approaches were reported, including type I-IV cordectomy, partial or total laryngectomy. At the exception of the study of Huang et al. [24]  most authors favored surgery for the treatment. Anaplastic transformation of LVC was investigated in 5 studies and reported in 3 cases  [8, 12, 16, 21, 24] , accounting for 2. 1% of cases (3/140). The three reported cases occurred in the seventies and eighties. The radiotherapy effectiveness was reported in two studies  [16, 24]. Hagen et al. included data from 12 LVC patients. Among them, 2 were treated with radiotherapy, which failed in one case (50%)  [16].
Moreover, there was no large-cohort database study comparing the prevalence of alcohol, tobacco, and HPV outcomes between LVC and LSCC, which limits the improvement of etiological knowledge. In this review, we reported that glottis is the main anatomical region of the LVC development, which may be an element supporting the better oncological outcomes of LVC compared to LSCC  [3]. Indeed, glottic carcinomas are commonly diagnosed faster than supraglottic carcinomas according to the rapid impairments of voice quality  [29]. From an oncological point of view, the glottic location may support the higher prevalence of earlystage tumors (cT1 and cT2) in LVC compared to LSCC patients  [3]  and the differences in survival outcomes. The investigations dedicated to the biology of LVC are rare  [30, 31].
From a therapeutic standpoint, surgery has long time been considered as the main therapeutic option. The OS, DSS and RFS rates of studies included in the present review were better in surgery groups compared to radiation groups, which corroborated findings of previous systematic review  [2]  or large database studies  [3, 25]. However, most case-series of patients treated with radiotherapy included data from 1970 to 2000. The radiotherapy techniques have considerably improved since the seventies, which led to higher OS, DSS, and RFS rates in patients treated after 2000 for laryngeal malignancies  [33, 34]. Thus, the lowest effectiveness of radiotherapy in the management of LVC must be considered with prudence according to the lack of recent controlled study, the low number of patients treated with radiation in the past decade and the potential differences in patient profiles treated with radiotherapy versus surgery.
[19] Italy Rome 1996 Retrospective IV 31 Surgery and RT Damm et al. [20] Germany Cologne 1997 Retrospective IV 21 Surgery McCaffrey et al. [21] U. S. A Rochester 1998 Retrospective IV 52 Surgery and RT Strojan et al. [22] Slovenia National database 2006 Retrospective IV 30 Surgery, RT and CT Hod et al. [23] Israel Tel Aviv 2009 Retrospective IV 18 Surgery and RT Huang et al. [24] Canada Toronto 2009 Retrospective IV 62 RT Dubal et al. [3] U. S. A SEER 2015 Retrospective IV 516 Surgery and RT Jayakrishnan et al. [25] U. S. A NCDB 2020 Retrospective IV 396 Surgery and RT.
Results Comparative genomics, including Average Nucleotide Identity, digital DNA-DNA hybridisation, and genome sequence-derived 16S rRNA gene sequence analysis revealed that TS-2 was confused with M. massiliense. Quantifying ancient and modern dental calculus metagenomic read counts yielded a positive correlation between Methanobrevibacter sp. YE315, the proxy-methanogen for M. massiliense in the Kraken2 database and P. piscolens (Pearson correlation test, p = 0. 23, P-value = 0. 026); whereas no such correlation was found with Fretibacterium fastidiosum (p = -0. 04, P-value = 0. 69) and Synergistetes phylum (p = -0. 0072, P-value = 0. 94) used as negative controls. Similar results were obtained with unclassi ed Methanobrevibacter, and the combined read counts of unclassi ed Methanobrevibacter and Methanobrevibacter sp.
massiliense-P. piscolens association unknown  (3). Recently, a dental calculus metagenomic study covering a time span from the Neolithic era to the present day was published in the journal Microbiome and provided a unique opportunity to investigate the antiquity of the association between M. massiliense and P. piscolens  (4). By analysing datasets from that study, we were able to con rm that this association between dental calculus dated back to the Neolithic period and continues to endure in contemporary populations.
Materials and methods Data collection. Comparative genomics included the M. massiliense reference genome (GenBank accession number: GCA_963082475) and TS-1, TS-2 and M. oralis metagenomic assembled genomes (MAGs) kindly provided by Granehäll et al. (4). Twelve closely related methanogen genomes, including Methanobrevibacter sp. YE315 as well as P. piscolens whole genome sequence (GenBank accession number: GCF_022846135. 1), were also included as outgroups (Additional le 1: Table  S1 ). Correlation analyses incorporated a dataset of sequence data extracted from 97 modern and ancient human dental calculuses used in the study by Granehäll et al. (4) (Additional le 2: Table  S1 ); 20 data sequences from dental calculus aDNA extracted from 20 individuals exhumed in Trentino, South Tyrol, Italy and covering the Neolithic to the Early Middle Ages, deposited in the European Nucleotide Archive (ENA) browser (https://www.
Comparative genomic analysis: Average nucleotide identity (ANI) was determined on 14 genomes and 11 MAGs using PYANI software version 0. 2. 7 with standard parameters. Genomic sequences exhibiting > 95% identity were deemed to represent the same genomic species  (13). DNA-DNA hybridization (dDDH) values calculated using Type (Strain) Genome Server (TYGS) online tool (https://tygs. dsmz. de/) (Additional le 1: Table  S2 ) delineated species using a 70% DDH value threshold  (14). 16S rRNA gene sequences were retrieved from M. massiliense, TS-1 and TS-2 MAGs after genome annotation using the DDBJ Fast Annotation and Submission Tool online platform (https://dfast. ddbj. nig. ac. jp) and BLASTed against NCBI GenBank database. A 16S rRNA gene sequence-based tree incorporated the rst 32 top hits and was designed following a two-step approach: sequences were rst aligned using MEGA's alignment tool to ensure proper alignment of homologous regions, then a neighbour-joining algorithm with standard parameters was used to generate the tree (Additional le 1, Tables S3, S4, S5).
The evolutionary history of M. massiliense and TS-2 was inferred using the maximum likelihood method based on the JTT matrix-based model and tree reliability was challenged by performing 1000 bootstrap replications, collapsing branches with < 50% bootstrap, for clarity. Taxonomic assignation. To determine the microbial composition of each sample data set, a taxonomic assignment was performed with metagenomic paired-end reads including blank sequencing data on https://www. bv-brc. org/, using Kraken2  (15) , which allowed taxonomic classi cation of metagenomic data based on the k-mer approach (Additional le 2: Table  S1 , S2, S5 to S11). Resulting taxonomic compositions were visualised in a Krona chart from the converted Kraken2 data and the report. txt outputs were used for interactive analysis of metagenomics and comparison using Pavian (16) (Additional le 2: Table  S1 , S2, S5 to S11).
As the Kraken2 database does not include M. massiliense and M. oralis representatives, taxonomic assignment based on these two species reference genomes (accession numbers GCA_963082475 and GCF_912073625. 1, respectively) identi ed the Methanobrevibacter species to which M. massiliense and M. oralis reference genome-sequences were assigned. We also con rmed the accurate taxonomic assignment of the P. piscolens genome (accession number: GCF_022846135. 1). Correlation analysis. The Pearson correlation test was used to estimate the strength of association in the number of Methanobrevibacter sp. Y315, unclassi ed Methanobrevibacter, and combined sum of reads assigned to Methanobrevibacter sp. Y315 and unclassi ed Methanobrevibacter read counts to match M. massiliense/TS-2 with P. piscolens read counts, as well as the association with the Synergistetes phylum and Fretibacterium fastidiosum (F.
fastidiosum) reads, used as negative controls (Additional le 2: Table  S2 ). Further, the same tests incorporated reads assigned to M. smithii to match M. oralis according to the Kraken2 taxonomic assignment of the M. oralis reference genome (accession number: GCF_912073625. 1). We also conducted a range of statistical analyses using diverse combinations of read counts from various Methanobrevibacter species, using a 5% cut-off value for alpha signi cance level. To interpret the Pearson correlation coe cient, we considered its value in relation to its direction and magnitude. Statistical analyses were performed using R software with appropriate functions for calculating the Pearson correlation coe cient and its associated P-value (Additional le 2: Tables  S3  and S4 ).
YE315 and M. smithii were used as proxies for M. massiliense and M. oralis, respectively, in the Kraken2 database (Additional le 2: Tables  S3  and S4 ). In other words, we conducted correlation analyses incorporating Methanobrevibacter sp. YE315 reads in place of M. massiliense, and unclassi ed Methanobrevibacter reads and combined reads of Methanobrevibacter sp. YE315 plus unclassi ed Methanobrevibacter. A signi cant positive correlation was established between Methanobrevibacter sp. YE315 and P. piscolens (p = 0. 23, P-value =. 026), while no correlation was observed with the Synergistetes phylum or F. fastidiosum (p = -0. 0072, Pvalue = 0. 94 and p = -0. 04, P-value = 0. 69, respectively). These ndings were reproduced when analysing both unclassi ed Methanobrevibacter reads and unclassi ed Methanobrevibacter reads combined with Methanobrevibacter sp.
Conclusions Genomic comparisons and phylogenetic analyses have provided strong evidence indicating that M. massiliense, which had been previously co-isolated with P. piscolens, is indeed the current named, cultured representative of TS-2. Statistical correlation analysis, based on a substantial dataset of metagenomic information, suggests that the association between M. massiliense and P. piscolens in dental calculus dated back to the Neolithic era, and that this association persists in a minority of modern European populations today.
These analyses can be combined with molecular and radiological data, generating a comprehensive dataset of outcome findings corroborating each other  [27]. As such, detailed immunohistochemical and histologic analysis of the bone cell and tissue responses to bone substitutes after implantation in vivo can contribute significantly to generating the required knowledge base for the evidence-based application of these bone substitutes in humans and for successful translation to the clinic. In this context, we previously developed a hard tissue histologic technique that enables visualizing osteoblasts that actively form and secrete an osseous matrix and induce its mineralization at the bone-bioceramic interface as well as in the pores of degrading bioactive bone substitutes at varying time points after the grafting procedure  [23, 28, 29].
Mayer's hematoxylin was utilized for counterstaining. Non-immunized mouse and rabbit IgG (PP54 and PP64) (Millipore, Billerica, MA, USA) served as negative controls. Histomorphometric analysis was carried out on a pair of sections 150 µm apart. A light microscope (BX-63), a digital camera, and CellSenseTM software (Olympus, Germany) were employed, and a square ROI 4 mm 2 in size was defined in two regions of each section: apically underneath the Schneiderian membrane and secondly in the central region of the cylindrical biopsy at a distance of 3 mm from the native bone of the alveolar crest (Figure  2 ). The bone area fraction, the graft material area fraction, and the bone-bioceramic contact were determined in both ROIs in order to characterize bone formation, the biodegradability of the bone grafting materials, and their bone bonding behavior, as described previously  [6, 23].
Data from each pair of sections were averaged. Furthermore, the immunohistochemically stained sections were subjected to semi-quantitative analysis as described previously  [23, 31, 32]. Analysis of the stained sections was carried out by two experienced investigators who were blinded to the staining. The cellular components analyzed were osteoblasts, osteocytes, and fibroblasts, and the matrix components analyzed were trabecular bone, osteoid seams, bone marrow spaces, and fibrous matrices. A scoring system was utilized for quantifying the amount of staining recorded for the different osteogenic markers: a score of (+++[=5]), (++[=4]), and (+[=2]) indicated generalized strong, moderate, or mild staining, and a score of (+++[=4]), (++[=3]), and (+[=1]) indicated localized strong, moderate, or mild staining.
Mayer's hematoxylin was utilized for counterstaining. Non-immunized mouse and rabbit IgG (PP54 and PP64) (Millipore, Billerica, MA, USA) served as negative controls. Histomorphometric analysis was carried out on a pair of sections 150 µm apart. A light microscope (BX-63), a digital camera, and CellSenseTM software version V3. 2 (Olympus, Germany) were employed, and a square ROI 4 mm 2 in size was defined in two regions of each section: apically underneath the Schneiderian membrane and secondly in the central region of the cylindrical biopsy at a distance of 3 mm from the native bone of the alveolar crest (Figure  2 ). The bone area fraction, the graft material area fraction, and the bone-bioceramic contact were determined in both ROIs in order to characterize bone formation, the biodegradability of the bone grafting materials, and their bone bonding behavior, as described previously  [6, 23].
As a result, a much larger number of thin sections, in which capillary formation can be visualized at significantly higher resolutions, can be prepared from biopsies only 2. 5 mm in diameter compared to using a sawing microtome, which renders seven 50 µm thick sections per biopsy. Using this novel technique, we were able to visualize capillary formation with von Willebrand factor expression in the pores of degrading Si-CAP granules six months after sinus floor grafting (Figure  5i ). As a result, a prospective clinical study with a larger patient population has been designed which involves a split-mouth design, investigating angiogenesis and analyzing CBCT data for evaluating the volume stability of the grafted region in addition to detailed histologic analysis of osteogenesis, so as to generate an even more comprehensive dataset to further establish the evidence-based use of Si-CAP in patients.
Acknowledgments: The authors would like to thank  A. Kopp ,  M. Kratz , and  D. Scheid  for their excellent technical assistance. The authors are grateful to  Larry Fisher  ( NIDCR ) for providing the Col I and BSP antibodies, and to  Wolf-Dietrich Hübner ,  Fabian Peters , and  Gregor Thomas  for providing the Osseolive ® grafting material. The  ESRF  is acknowledged for providing access to beamline ID19.
, 2000)  using the same primers used for standard PCR. The raw sequences were trimmed and assembled using ChromasPro software version 1. 7 (Technelysium Pty Ltd. , Tewantin, Australia). The obtained sequences were matched with the GenBank database using the BLASTN program (https://blast. ncbi. nlm. nih. gov/Blast. cgi, last accessed January 2023). The resulting sequences were then used to construct a phylogenetic tree using the software MEGA7  (Kumar et al. , 2016)  with the maximum likelihood method (Tamura 3 parameter model/method) and 500 bootstrap replicates. Alignment was conducted using Muscle v3. 8. 31 with default parameters.
Bioinformatic analysis Reads were adjusted using Trimmomatic version 0. 36. 6  (Bolger et al. , 2014)  and assembled using the SPAdes software version 3. 13. 0 with default parameters  (Bankevich et al. , 2012). All contigs with a minimum length of 400 bp were conserved. BLASTn of these contigs versus nr was performed prior to the reconstruction of the genome into one single scaffold using the CONTIGuator tool  (Galardini et al. , 2011). Additionally, mapping of the obtained reads was performed using CLC Genomics Workbench  (Liu and Di, 2020)  against a reference genome of Ca. Saccharibacteria, Ca. Nanosynbacter lyticus strain TM7x (GenBank accession number CP007496. 1), using default settings with the length set at 0. 9 and the similarity fraction set at 0. 8. Moreover, all the reads obtained from 16S amplicon sequencing at the genomics platform of the University Hospital Mediterraneé Infection Institute were analyzed using the MetaGX pipeline with the Silva 9.
0 and culturomics databases  (Diakite et al. , 2019). MetaGX is an in-lab pipeline developed with the start-up XeGen (http://xegen. eu/) based on QIIME  (Caporaso et al. , 2010)  using BLAST  (Altschul et al. , 1990)  for taxonomic assignment and SILVA  (Quast et al. , 2013; Yilmaz et al. , 2014)  as a reference dictionary. For taxonomic assignments, we only included OTUs consisting of at least 20 reads. The OTUs were then searched against each database using BLASTN. The best match (≥ 97% identity and 100% coverage) was retrieved for each OTU from the reference database, and taxonomy was assigned up to the species level. The database consisted of 3,788 samples at the time our analysis was conducted. Nonhuman samples (including animal, environmental, insect and unidentified samples) were excluded from this study.
Prevalence of CPR in human samples from the MetaGX database The 16S amplicon datasets from the MetaGX database were analyzed to assess the prevalence and abundance of CPR within the human microbiome  (Diakite et al. , 2019). Seven CPR phyla, namely, Ca. Saccharibacteria, Ca. Atribacteria, Ca. Parcubacteria, Ca. Microgenomates, Ca. Dojkabacteria, Ca. Gracilibacteria and Ca. Katanobacteria were detected in these datasets (Table  1 ). Ca. Saccharibacteria was the most represented phylum in all the analyzed sample types (oral cavity, sputum, gastrointestinal tract, respiratory tract, urinary tract, and human breast milk). A total of 28. 9% (1,026/3,550) of the samples presented reads assigned to the CPR and the phylum Ca. Saccharibacteria was the most represented. One hundred percent (9/9) of the sputum samples, 94.
Retrospective screening of Candidatus Saccharibacteria in clinical samples After analysis of our 16S amplicon database, we performed a retrospective study and screened for the presence of Ca. Saccharibacteria in different types of clinical samples. The screening was performed using standard PCR and real-time PCR for the initial assessment, which was then confirmed by observation of Ca. Saccharibacteria using scanning electron microscopy and Sanger sequencing (Figure  3 , Table  S3 ) of the PCR products of positive samples (Table  2 ). Finally, we were able to reconstruct two CPR bacterial genomes from the mapping of reads obtained from shotgun metagenomics of stool and oral cavity samples (Table  2 ).
The mapping-based assembly of reads obtained from the shotgun sequencing of a positive oral sample (Ct=19. 04) allowed the reconstruction of a genome with 81% coverage of the reference genome (GenBank accession number CP007496. 1). This genomic sequence consisted of one scaffold with a size of 0. 7 Mbp and a GC% of 43. 42. The 16S rRNA gene (GenBank accession number OX335640) shared a similarity of 100% with that of Ca. Nanosynbacter sp. HMT-352 strain TM7-037 (CP089288. 1), whereas the maximum digital DNA-DNA hybridization (dDDH)  (Auch et al. , 2010; Meier-Kolthoff et al. , 2013)  of 70. 7% was shared with Ca. Minimicrobia massiliensis (GenBank accession number CADDWL010000000).
Human fecal samples Fecal samples also presented a prevalence of Ca. Saccharibacteria and accounted for 52. 6% (40/76) of the positive samples based on the RT-PCR results, with a mean Ct of  28. 55 [24. 53-33. 33 ] (Figure  4B ). Additionally, 65. 8% (50/76) of fecal samples were positive for Ca. Saccharibacteria using standard PCR (Figure  4B ), and the corresponding sequences matched Ca. Saccharibacteria (Figure  3 , Table  S3 ). This was confirmed with the SEM micrographs showing structures consistent with these minimicrobes in positive fecal samples (Figure  4B ). Moreover, two genomes (GenBank accession numbers CADDWL010000000 and CAJGBL010000000) were reconstructed from the mapping of reads generated using shotgun sequencing of two fecal samples (Ct 24. 65 and Ct 27. 55) against Ca. Nanosynbacter lyticus TM7x (GenBank accession number CP007496.