dataesr/scientific-paragraphs-categorization huggingface dataset:
6, K04. 7)  [35]. After exclusion of patients with a history of previous AF, patients were followed up for new-onset AF with hospitalisation using ICD-10 codes. Identifying AF using an electronic database is considered reliable, and PMSI data have been evaluated in previous studies  [32, 36]. Baseline characteristics from patients hospitalised during 2013 with or without dental periapical abscesses were recorded, in addition to age, gender, and medical history. Events and predictors for AF were monitored with at least 5 years follow up. We also calculated the CHA 2 DS 2 VASc score (congestive heart failure, high blood pressure, diabetes, stroke, heart disease, age, gender) which is used for stroke risk stratification, but used this to stratify risk for new-onset AF where acute periapical abscess was present  [34] [35] [36] [37].
Ethical Approval The research database involved a collection of non-identifiable information used for data analysis with external researchers. The study was conducted retrospectively and, as patients were not involved in its conduct, there was no impact on their care. Studies such as this study have been labelled as clinical audits, therefore sponsorship was not required from the University of Liverpool or the University of Tours  [32, 37, 38]. Comparable to previous articles, informed consent was not obtained as the data were retrospective  [22, 23]. All patient information remained confidential and anonymised. The French law allows approval of certain public institutions, such as large university hospitals, to self-declare authorisation and access to confidential information when using electronic data for research purposes.
The specificity and sensitivity for CHA 2 DS 2 VASc scores as a predictor for new-onset AF and dental periapical abscess were examined further by plotting the Area Under the Curve-Receiver Operating Characteristic (AUC-ROC). All comparisons with p < 0. 05 were considered statistically significant. All analyses were performed using Enterprise Guide 7. 1, (SAS Institute Inc. , SAS Campus Drive, Cary, NC, USA), USA and STATA version 12. 0 (Stata Corp, College Station, TX, USA).
Limitations We investigated dental infection using a hospital database, and although this enables us to monitor large amounts of data, a major limitation is its retrospective design, and it does not imply cause or effect. As in previous studies, our study defined diagnosis of newonset AF during hospitalisation, rather than using detailed investigations or outpatient appointments, meaning it could underestimate the true incidence of AF. Unadjusted incidence rate of AF was lower in patients with dental periapical abscess, but these patients were markedly younger. We thus used multivariable analysis to account for differences in age and prevalent comorbidities associated with AF for the study population. Although we found dental abscess to be an independent risk factor using multivariable analysis, there may have been some confounders missing from the dataset.
Nonetheless, our data accounted for more potential confounders (such as smoking, obesity and alcohol related diagnosis) which have been a limitation for other prior studies investigating oral diseases and AF  [22] [23] [24]. Another possible limitation is that even though we accounted for selection-bias using a nationwide database with the French population, different codes may be more common in different countries and that the data presented may not be generalisable. A cross sectional study in England found dental problems accounted for 0. 7% of all attendees in emergency departments and "dental unspecified", "dental abscess" and "toothache" and were the most common codes used  [30]. Currie et al. [30]  went on to explain that the true number of patients attending with acute dental periapical abscess may have been underrepresented due to non-dental healthcare staff using codes "dental unspecified" and general abscess (rather than dental).
Search Strategy Understanding the interactions of microorganisms with the host and with each other, as well as their impact on health, was improved by the development of high-throughput sequencing techniques for genetic material since 2000  [25]. The research was carried out from January 2000 to July 2021 to clarify the relationship between AD and the oral microbiome. So as not to restrict the search only to oral pathologies, terms identifying the main oral ecological niches "Dental plaque," "Saliva," and Mouth" were associated with the search term "Mouth diseases" and used in combination with the Boolean operator "AND"/"OR" as per the following equation: (((("Mouth"[Mesh]) OR "Mouth Diseases"[Mesh]) OR "Dental Plaque"[Mesh]) OR "Saliva"[Mesh]) AND "Alzheimer Disease"  [Mesh]  The search was performed in the MEDLINE literature database through PubMed interface.
Data Extraction Two independent operators (F. D. and Y. M. ) manually checked the references of eligible studies on the subject, according to inclusion/exclusion criteria. An analysis of titles and abstracts by F. D. and Y. M. was performed to identify potentially relevant articles based on inclusion criteria. When the information in the abstracts was deemed insufficient, a review of the complete study decided on its relevance. A discussion between the two reviewers took place to reach a consensus with discrepancies in the selection decision process.
05; 95% CI = 1. 00-1. 11, p = 0. 042) than Insurance Service (NHIS) database, drugs as part of a diagnosis of AD non-chronic periodontitis participants. using a several covariates (smoking, (ICD-10 codes F00, G30) or VD * Study design, Information on CP-related clinical alcohol consumption and physical (ICD-10 code F01) index limited, definition of dementia based on activity). Age, sex, household income, drug reimbursement, no evaluation of level of smoking status, alcohol education or apolipoprotein E (APOE) e4 consumption, physical activity, genotype. body mass index, systolic blood pressure, fasting serum glucose, total cholesterol and Charlson Comorbidity Index Dominy et al. , 2019 Experimental study Assessment of the prevalence of P. P. gingivalis and Gingipaïn load in P. gingivalis and gingipains load in the brain play [39] (mice) gingivalis (Pg) in the brains of people brain tissue a significative role in the pathogenesis of AD.
In the present study, we used the rapid, cost-effective routine identification by matrixassisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) for the identification of an unknown strain, which was isolated from a dental plaque sample from a 51-year-old man with clinical gingival health following successful treatment of periodontitis. Strain Marseille-Q4569 T was then described using data from next-generation sequencing data, morphological examinations and biochemical characteristics. We propose to establish for this strain the species name Kingella bonacorsii sp. nov.
Strain Isolation and Phenotypic Characteristics Strain Marseille-Q4569 T was isolated from a dental plaque sample from a 51-year-old man with clinical gingival health following successful treatment of periodontitis and living in Marseille, France. Strain Marseille-Q4569 T could not be identified by MALDI-TOF MS, as the score was lower than 1. 8 against the MEPHI (Microbes, Evolution, Phylogénie, Infection) database. The reference spectrum of strain Marseille-Q4569 T (Figure  1 ) did not belong to any known Kingella species (Figure  2 ). Growth was observed on 5% sheep blood-enriched Columbia agar (BioMérieux, Marcy l'Etoile, France) at 37 • C after 24 h of incubation under aerobic atmosphere. Growth was also achieved in anaerobic (AnaeroGen Compact; Oxoid, Thermo Scientific, Dardilly, France) and microaerophilic atmospheres (campyGEN; Oxoid, Thermo Scientific, Dardilly, France).
Grevich et al. [6]  reported that juvenile idiopathic arthritis patients had significantly more gingival inflammation, and plaque microbiota analysis revealed bacteria belonging to genera Kingella elevated. By contrast, other authors showed that periodontal inflammation, in case of gingivitis or periodontitis, was characterized by a reduction of Kingella species  [7, 8]. In the present study, we used the rapid, cost-effective routine identification by matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) for the identification of an unknown strain, which was isolated from a dental plaque sample from a 51-year-old man with clinical gingival health following successful treatment of periodontitis. Strain Marseille-Q4569 T was then described using data from nextgeneration sequencing data, morphological examinations and biochemical characteristics.
Strain Isolation and Phenotypic Characteristics Strain Marseille-Q4569 T was isolated from a dental plaque sample from a 51-year-old man with clinical gingival health following successful treatment of periodontitis and living in Marseille, France. Strain Marseille-Q4569 T could not be identified by MALDI-TOF MS, as the score was lower than 1. 8 against the MEPHI (Microbes, Evolution, Phylogénie, Infection) database. The reference spectrum of strain Marseille-Q4569 T (Figure  1 ) did not belong to any known Kingella species (Figure  2 ). Growth was observed on 5% sheep bloodenriched Columbia agar (BioMérieux, Marcy l'Etoile, France) at 37 °C after 24 h of incubation under aerobic atmosphere. Growth was also achieved in anaerobic (AnaeroGen Compact; Oxoid, Thermo Scientific, Dardilly, France) and microaerophilic atmospheres (campyGEN; Oxoid, Thermo Scientific, Dardilly, France).
Genome Sequencing Information and Genome Properties The genome size of strain Marseille-Q4569 T was 2,502,986 bp long with a 54. 0% G+C content. The genome assembly was achieved on 9 contigs with a mean coverage of 36. 0. It was deposited into GenBank under the accession number JAEHNZ000000000. Of the 2698 predicted genes, 2556 were protein-coding genes, 71 were RNAs (4 5S rRNA, 4 16S rRNA, 4 23S rRNA, 55 tRNAs and 4 ncRNA), and 71 were pseudo genes. Genes with putative function (by clusters of orthologous groups, COGs) were 1353 for Kingella bonacorsii strain Marseille-Q4569 T (Table  3 ). Finally, 1177 genes (43. 6%) were annotated as hypothetical proteins for strain Marseille-Q4569 T. A circular map showing a complete view of the genome of strain Marseille-Q4569 T is shown in Figure  4.
Comparison with Closely Related Bacterial Strains The 16S rDNA-based similarity analysis of strain Marseille-Q4569 T against GenBank yielded highest nucleotide sequence similarities of 98. 72 % sequence identity with K. oralis strain UB-38 T (GenBank accession no. NR_025891. 1). The 16S rRNA gene sequence was deposited into GenBank under the accession number MW367549. The phylogenetic tree highlighting the position of the strain relative to other closely related species is shown in Figure  5. A circular map generated using the CGView Server BETA  [14]  showing a complete view of the genome of strain Marseille-Q4569 T.
Comparison with Closely Related Bacterial Strains The 16S rDNA-based similarity analysis of strain Marseille-Q4569 T against GenBank yielded highest nucleotide sequence similarities of 98. 72 % sequence identity with K. oralis strain UB-38 T (GenBank accession no. NR_025891. 1). The 16S rRNA gene sequence was deposited into GenBank under the accession number MW367549. The phylogenetic tree highlighting the position of the strain relative to other closely related species is shown in Figure  5. The genome of strain Marseille-Q4569 T was compared to the available genomes of nine closely related bacterial strains. The genome size of our strain (2. 50 Mb) was larger than that of N. cinerea, K. kingae, B. denitrificans, N. shayeganii, K. oralis, N. zalophi and N. chenwenguii (1. 83 Mb, 2. 00 Mb, 2.
32 Mb, 2. 35 Mb, 2. 40 Mb, 2. 42 Mb, 2. 49 Mb, respectively), but smaller than that of S. alvi (2. 52 Mb) and N. canis (2. 56 Mb). The G+C content of our strain (54. 0%) was equal to or higher than that of all strains compared, with the exception of K. oralis (54. 3%), B. denitrificans (55. 8%) and N. shayeganii (56. 4%). When performing digital DNA-DNA hybridization (dDDH) analysis, strain Marseille-Q4569 T exhibited values ranging from 63. 6 (60. 7-66. 4)% with K. oralis to 22. 2 (19. 9-24. 6)% with N. canis (Table  4 ). ) with default parameters, phylogenetic inference were obtained using the maximum likelihood method and the MEGA X software  [15]. The bootstrap values obtained by repeating the analysis 1000 times to generate a majority consensus tree are shown at the nodes. There was a total of 1360 positions in the final dataset.
The matrix sample was then crystallized by air-drying at room temperature, as previously described  [20]. Two spots were systematically created for each colony, and each isolate was characterized by at least 12 spots. The obtained spectra were imported into the BioTyper-RTC TM version 3. 0 software (Bruker Daltonics GmbH, Bremen, Germany) and analyzed by standard pattern matching (with default parameter settings) against the constantly updated MEPHI database (https://www. mediterranee-infection. com/acces-ressources/base-de-donnees/ urms-data-base/, (accessed on 4 January 2021). Interpretation of the scores was carried out as previously reported  [19]. A log score ≥ 2. 0 was considered an identification with high confidence, according to the manufacturer (Bruker Daltonics GmbH). One purified strain, designated Marseille-Q4569 T , and deposited in the Collection de Souches de l'Unité des Rickettsies under accession number Q4569, could not be identified by MALDI-TOF MS.
Then, fatty acid methyl esters were separated using an Elite 5-MS column and monitored by mass spectrometry (Clarus 500-SQ 8 S, Perkin Elmer, Courtaboeuf, Villebon sur Yvette, France). Spectral database search was performed using MS Search 2. 0 operated with the Standard Reference Database 1A (NIST, Gaithersburg, MD, USA) and the FAMEs mass spectral database (Wiley, Chichester, UK).
Assembly and Annotation of Genome Sequence A pipeline incorporating different software (Velvet  [24] , Spades  [25] , Soap Denovo  [26] ) and trimmed data (MiSeq and Trimmomatic  [27]  software) or untrimmed data (only MiSeq software) was used to perform the assembly. The reduction of assembly gaps was obtained with GapCloser. Scaffolds <800 bp and scaffolds with a depth value <25% of the mean depth were removed. The best assembly was selected using different criteria (number of scaffolds, N50, number of N). The prediction in the open reading frame (ORF) was performed using Prokka (Galaxy v 1. 14. 5) with default settings  [28]. Deviations in the sequencing regions predicted by ORFs were excluded. BlastP was used to predict the bacterial proteome (E value of 1e03, coverage of 70% and percent identity of 30) according to the orthological group (COG) database.
In the absence of a match, the search for BlastP in the database  [29]  was extended with an E value of 1e03, coverage of 70% and percent identity of 30. On the other hand, if the length of the sequence was less than 80 amino acids (aa), an E value of 1e05 was used. The rRNA and tRNA genes were retrieved using Prokka (Galaxy v 1. 14. 5) [30, 31]. In addition, CGView Server BETA  [14]  was used to generate a circular map displaying a complete view of the genome of strain Marseille-Q4569 T.
Phylogenetic Analysis and Genome Comparison The 16S rRNA gene sequence of strain Marseille-Q4569 T was obtained and compared to the closest related species retrieved using the National Center for Biotechnology Information, Basic Local Alignment Search Tool (NCBI BLAST; https://blast. ncbi. nlm. nih. gov/ Blast. cgi, (accessed on 30 December 2020)) and then submitted to the GenBank database. Phylogenetic analyses were performed using MEGA X software  [23] , with genetic distances determined according to the Kimura two-parameter model  [24]  and phylogenies reconstructed with the maximum-likelihood method. The topology of the phylogenetic tree was conducted using the bootstrap method with 1000 repetitions. All positions containing gaps and missing data were eliminated from the dataset (complete deletion option).
To estimate the mean level of nucleotide sequence similarity at the genome level between strain Marseille-Q4569 T and closely related species, the digital DNA-DNA hybridization (dDDH) as well as the orthologous average nucleotide identity (OrthoANI v 0. 93. 1) parameters were calculated using the OAT  [18]  and GGDC (Genome-to-Genome Distance Calculator v 2. 1)  [16]  software programs, respectively. The Pangenome distribution of strain Marseille-Q4569 T and other closely related species was assessed using the Roary software (Galaxy v 3. 13. 0) [32].
Electrochemically anodized (EA) surfaces promise enhanced biological properties and may be a solution to ensure a seal between peri-implant soft tissues and dental transmucosal components. However, the interaction between the modified nano-structured surface and the gingival cells needs further investigation. The aim of this systematic review is to analyze the biological response of gingival cells to EA titanium surfaces in in vitro studies with a score-based reliability assessment. A protocol aimed at answering the following focused question was developed: "How does the surface integrity (e. g. , topography and chemistry) of EA titanium influence gingival cell response in in vitro studies?". A search in three computer databases was performed using keywords. A quality assessment of the studies selected was performed using the SciRAP method.
Search Strategy An electronic restricted search of studies published only between 1 January 2011 and 31 December 2020 in three databases (MEDLINE/Pubmed, EMBASE, and Web of Sciences) was performed using keywords related to anodization on titanium surfaces combined with keywords related to soft tissues with AND/OR as Boolean operators. This equation was structured as shown in Table  1. No limits were applied regarding the sample size, but only articles written in English were selected. (1) "anodic oxidation" OR "surface modification*" OR "modified surface*" OR "anodization" OR "nano topography" OR "anodized" OR "nanotube*" (2) "abutment*" OR "dental abutment*" OR "dental implant*" (3) "fibroblast*" OR "human gingival fibroblast*" OR "gingival cell*" OR "peri-implant soft tissue*" OR "gingival epithelial cell*" (4) "titanium" OR "titanium alloy*" OR "Ti6Al4V" (5) "Zirconia" OR "Zirconium" 1 AND 2 AND 3 AND 4 NOT 5 The results of the electronic research were imported into software (Excel, Microsoft) to exclude duplicates.
Data Extraction and Analysis Data were extracted independently by the two reviewers using two tables specifically developed for this purpose. The first table included the article title and year of publication, sample preparation (materials, fabricant, and anodization parameters), and biological evaluation (measuring variables, methodology, cell density, duration, and number of replicates). The second table presented the characteristics of the different surfaces (surface roughness, NT/NP morphology, and wettability) and the biological results compared to the control surface.
7 ± 7. 7/100 while the mean methodologic quality score was 77. 8 ± 7. 8/100. Details of quality evaluations are shown in Table 2. Identification Pubmed/MELINE database (n=111) Web of Science database (n=186) EMBASE database (n=100) Records before duplicates removed (n=397) Screening Records after duplicates removed (n=216) Title and and abstract screened Records excluded (n=216) (n= 169) Eligibility Full text articles assessed for eligibility (n= 47) Full-text articles excluded with reasons (n= 33) cluded Studies included in qualitative synthesis (n=14).
In such cases, the particles remain close to the initial size and small differences are difficult to be detected. 59, 133 An optimal initial particle edge size should be determined in advance, based on the sieve aperture and the way of data processing of cumulative weight data from sieving. 54 e mastication process may belong to one of the three following conditions: totally healthy, moderately impaired and totally impaired, corresponding to masticatory capacity, compensatory adaptation and masticatory incapacity. 134, 135 Capacity means that mastication is perfectly achieved. Compensatory adaptation occurs when mastication is slightly disturbed, but the individual concerned can implement a physiological adaptation, mainly an increase in the number of cycles, that makes a normal bolus. Incapacity/deficiency means the function is largely deficient, because the individual fails to make a proper food bolus.
Purpose Cholecystectomy is one of the most common laparoscopic procedures. A critical phase of laparoscopic cholecystectomy consists in clipping the cystic duct and artery before cutting them. Surgeons can improve the clipping safety by ensuring full visibility of the clipper, while enclosing the artery or the duct with the clip applier jaws. This can prevent unintentional interaction with neighboring tissues or clip misplacement. In this article, we present a novel real-time feedback to ensure safe visibility of the instrument during this critical phase. This feedback incites surgeons to keep the tip of their clip applier visible while operating. Methods We present a new dataset of 300 laparoscopic cholecystectomy videos with frame-wise annotation of clipper tip visibility. We further present ClipAssistNet, a neural network-based image classifier which detects the clipper tip visibility in single frames.
ClipAssistNet ensembles predictions from 5 neural networks trained on different subsets of the dataset. Results Our model learns to classify the clipper tip visibility by detecting its presence in the image. Measured on a separate test set, ClipAssistNet classifies the clipper tip visibility with an AUROC of 0. 9107, and 66. 15% specificity at 95% sensitivity. Additionally, it can perform real-time inference (16 FPS) on an embedded computing board; this enables its deployment in operating room settings. Conclusion This work presents a new application of computer-assisted surgery for laparoscopic cholecystectomy, namely real-time feedback on adequate visibility of the clip applier. We believe this feedback can increase surgeons' attentiveness when departing from safe visibility during the critical clipping of the cystic duct and artery.
We approach this problem by building a binary image classifier which detects the clipper tip visibility. To this end, we utilize a new dataset tailormade for our application. This dataset is composed of laparoscopy cholecystectomy videos with frame-wise binary labels for the clipper tip visibility. We further present ClipAssistNet. This image classifier ensembles predictions of 5 residual neural network classifiers  [15]  trained on different subsets of our dataset. Given the inherent availability of endoscopic recordings, laparoscopy has been an ideal candidate for computer vision research. At the video level, particular efforts were put on video segmentation for surgical phase  [4, 9, 18, 35]  and surgical action recognition  [13, 21] , as well as in remaining surgery duration prediction  [27, 36].
Data Our model relies on frame-wise binary labels of the clipper tip visibility. A frame is labeled as tip visible if the tip of the clip applier is present in the frame and if it is not occluded by another tool or tissue. Clippers are composed of a shaft and two jaws; we define the clipper tip as the tips of both jaws. In an open position, the instrument tip is labeled as visible if and only if the tips of both jaws are not occluded. Our data include appliers for metal clips (mostly from the brand Aesculap Challenger ) and for polymer clips (from the brand Grena ) (respectively, top left and right in Fig. 1 ). In case of the polymer clip applier, we consider the visibility of the polymer clip tip as sufficient (see Fig. 1 , right center image). The frames are annotated in their appearance order, that is, consecutive frames are annotated successively.