dataesr/scientific-paragraphs-categorization huggingface dataset:
Nirmatrelvir (coadministered with ritonavir as PAXLOVID TM ) reduces the risk of COVID-19-related hospitalizations and all-cause death in individuals with mild-to-moderate COVID-19 at high risk of progression to severe disease. Ritonavir is coadministered as a pharmacokinetic enhancer. However, ritonavir may cause drug-drug interactions (DDIs) due to its interactions with various drug-metabolizing enzymes and transporters, including cytochrome P450 (CYP) 3A, CYP2D6, and P-glycoprotein transporters. To better understand the extent of DDIs (or lack thereof) of nirmatrelvir; ritonavir in a clinical setting, this study used real-world evidence (RWE) from the Optum Clinformatics Data Mart database to identify the top 100 drugs most commonly prescribed to US patients at high risk of progression to severe COVID-19 disease.
The top 100 drugs were identified based on total counts associated with drugs prescribed to high-risk patients (i. e. , ≥ 1 medical condition associated with an increased risk of severe COVID-19) who were continuously enrolled in the database throughout 2019 and had ≥ 1 prescription claim. Each of the 100 drugs was then assessed for DDI risk based on their metabolism, excretion, and transport pathways identified from available US prescribing and medical literature sources. Seventy drugs identified were not expected to have DDIs with nirmatrelvir; ritonavir, including many cardiovascular agents, anti-infectives, antidiabetic agents, and antidepressants. Conversely, 30 drugs, including corticosteroids, narcotic analgesics, anticoagulants, statins, and sedatives/hypnotics, were expected to cause DDIs with nirmatrelvir; ritonavir.
When coadministered with nirmatrelvir, ritonavir's interactions with such enzymes can cause drug-drug interactions (DDIs) with substrates of these enzymes. DDI studies conducted with ritonavir, with and without nirmatrelvir, suggest that inhibition effects on CYP3A and P-gp were primarily due to ritonavir, with nirmatrelvir having minimal or no additional incremental effect  (11). The relative potency of ritonavir to inhibit CYP3A4, CYP2D6, and P-gp, as well as to induce CYP3A4, is described in Supplementary Table  I. CYP3A4 inhibition occurs rapidly after initiating ritonavir, with maximum inhibition occurring within 48 h  (12, 13). After ritonavir dosing is discontinued, approximately 80-90% of CYP3A4 inhibition resolves within 3 days  (13, 14). In a clinical DDI study of nirmatrelvir; ritonavir as a victim drug of CYP3A4 inhibition (NCT04962022), nirmatrelvir mean area under the concentration versus time curve (AUC) and maximum observed concentration (C max ) increased by an additional 39% and 19%, respectively, when nirmatrelvir; ritonavir was coadministered with itraconazole, a potent CYP3A4 inhibitor, compared with nirmatrelvir; ritonavir administered alone  (15).
This suggests that additional CYP3A4 inhibitors do not substantially increase the degree of nirmatrelvir CYP3A4 inhibition beyond the effect of ritonavir when coadministered with nirmatrelvir; ritonavir. Conversely, in another clinical DDI study (NCT04962230), nirmatrelvir mean AUC and C max decreased by 55% and 43%, respectively, following coadministration with carbamazepine, a potent CYP3A4 inducer, compared with nirmatrelvir; ritonavir alone  (15). Therefore, DDIs that cause induction of nirmatrelvir as a victim drug should also be considered when prescribing nirmatrelvir; ritonavir. Ritonavir is commonly used as a pharmacokinetic (PK) enhancer in human immunodeficiency (HIV) and hepatitis C virus therapies  (16). While infectious disease prescribers may have more experience managing DDIs with ritonavir, general practitioners who see patients with COVID-19 at risk of severe outcomes may not be as familiar with ritonavir DDIs, and they may need additional resources to manage them.
Top 100 Drug Selection The initial data selection was performed using the full year of the 2019 CDM database. The 2019 analysis period was chosen to avoid capture of anomalous drug utilization patterns resulting from altered healthcare-seeking behaviors during the early COVID-19 pandemic period. The criteria for high-risk patients included ≥ 1 characteristic or underlying medical condition associated with an increased risk of developing severe illness from COVID-19 as defined by the US Centers for Disease Control and Prevention (CDC)  (27). The condition must have appeared in the claim records during the 12 months prior for inclusion in the dataset. Medical conditions attributed to high-risk patients based on CDC guidelines as of October 2021 included the following factors: ≥ 65 years of age (where age was assessed on the index date) and/or a history of cancer, chronic kidney disease, chronic lung diseases, chronic liver disease, dementia or other neurologic condition, diabetes (type 1 or type 2), Down syndrome, cardiovascular disease, HIV infection, hypertension, immune deficiencies/immunocompromised state, mental health conditions (i.
If details on these pathways were not available in the US prescribing information, then the prescribing information was supplemented with information from DailyMed or scientific literature. Information on elimination and disposition pathways is typically provided in the Pharmacokinetics (Metabolism and Excretion) section within the drug's prescribing information. Data from in vitro metabolism studies and human absorption, distribution, metabolism, and excretion (ADME) studies is generally provided to assess the contribution of each elimination pathway to overall elimination. These sections were reviewed to assess if the drug was a substrate for CYP3A4, CYP2D6, or P-gp and thus potentially likely to interact with nirmatrelvir; ritonavir. It is possible that drugs can have multiple elimination pathways affected by ritonavir.
DDI potential was further assessed by reviewing information in the Contraindications, Warning and Precautions, and/or Drug Interactions sections of the prescribing information, which also were used to identify if the drug was a strong CYP3A4 inducer. This mimics the process in which an HCP would access publicly available information for each drug. Second, if there was no evidence that the elimination or disposition pathways were affected by ritonavir, then the drug was not expected to interact with nirmatrelvir; ritonavir and no further assessment was needed. Conversely, if an interaction with an elimination or disposition pathway was possible, the prescribing information was reviewed for available clinical DDI study data describing the magnitude of change in PK parameters with ritonavir or similarly acting inhibitors.
Additionally, in such cases, contemporary literature was searched to confirm the magnitude of change in PK (i. e. , > 30% change) when possible. Third, for drugs identified as likely to interact with nirmatrelvir; ritonavir, the Contraindications, Warning and Precautions, and Drug Interactions sections of each drug's prescribing information were reviewed to identify recommendations for management of the interaction. DDI management approaches generally involved a contraindication, discontinuation, dose adjustment, or increased monitoring of adverse events. The clinical relevance of the DDI was noted based on what is reported in the prescribing information, as review of this information would be the general practice followed by HCPs. Information from this analysis for all the 100 drugs was compiled into a single table for ease of data presentation.
Therefore, the interpretation of these data and implications for dosing with nirmatrelvir; ritonavir may slightly differ. The current analysis has some limitations. More than 1,900 drugs are substrates of CYP3A4, and hundreds are substrates of P-gp  (45, 46). This analysis focused on the top 100 drugs most likely to be coadministered with nirmatrelvir; ritonavir to patients at high risk of severe COVID-19. This analysis leveraged the Optum CDM database, which includes prescription drug utilization. Thus, supplements and over-the-counter drugs, such as Saint John's Wort (Hypericum perforatum), were not captured. The top 100 drugs were queried from a US-based RWE database, and the results may not be fully translatable to other countries. There are likely to be many other drugs that are prescribed in the high-risk COVID-19 patient population beyond these top 100 drugs, some of which may interact with nirmatrelvir; ritonavir.
Furthermore, Weber and Bookstein  [31]  defined three types of SL: SL on curves, SL on surfaces, and constructed SL (i. e. at the beginning and end of a curve). We defined a set of LMs (based on cephalometric analysis) and SLs on curves that were placed on the lateral cephalometric radiographs of each patient from our sample (Fig  1 ). To ensure geometric comparability between the corresponding SLs, these were slid using a thinplate spline (TPS) algorithm that minimized bending energy  [32, 33]. The placement of the LMs, as well as the semi-automatic measurements of the SL on the lower and mandibular labial curves using the TPS algorithm, were carried out using the Viewbox Cephalometric Software (version 4. 1, Dhal, Athens, Greece). We used four anatomical LMs (Fig 1 ): the Ar point (posterior articular, intersection of the posterior edge of the Ramus with the exocranial surface of the clivus), B (Supramental, the most sloping point of the anterior mandibular alveolar concavity), the Stomion point (Stm) (junction between the upper and lower lips), and the soft tissue chin point (Me') (soft tissue projection of the bony chin point, perpendicular to the Frankfort plane).
Explanatory variables Data on three explanatory variables were collected for each patient and tested as potential predictors for post-operative changes in mandibular and labio-mental morphology: maxillary advancement, maxillary impaction, and divergence. Maxillary advancement (in mm) was characterized by the difference between the pre-and post-operative coordinates (x;y) of the ANS (anterior nasal spine) point on the lateral radiographs. For maxillary impaction, we distinguished "clockwise maxillary impaction" (when posterior impaction was more significant), "anti-clockwise maxillary impaction" (when anterior impaction was more significant), and "homogenous maxillary impaction" (when both impactions were similar). The anterior and posterior impactions were characterized by the difference between the pre-and post-operative coordinates (x;y) of the ANS and PNS (posterior nasal spine) points on the lateral radiographs.
Finally, divergence was defined by the Frankfurt-mandibular plane angle (FMA, angle formed by the intersection of the Frankfort horizontal plane with the mandibular plane). A patient was considered hypo-divergent if FMA was <22˚, normo-divergent if FMA was 22-28˚, and hyper-divergent if FMA was >28˚. Since diagnostic cephalometry enables the study of skeletal malocclusion, divergence and characterization of maxillary movements were carried out using the Viewbox Cephalometric Software.
Research Study Design This is a cluster randomised, controlled, multicentre, open-label intervention trial with a 6-month patient follow-up period. This intervention trial assessed the effectiveness of TEPOH in PWS followed in 26 outpatient psychiatry centres in France Clinicaltrials. gov: NCT02512367). A cluster design was chosen as the intervention was implemented in a team setting, and to minimize contamination between the intervention and control groups (TEPOH vs. standard care); clusters were defined as outpatient psychiatry centres. The trial was completed with a qualitative approach based on semi-directive interviews of caregivers to complement the results of the main study. These interviews aimed to explore the view that caregivers had a posteriori on the implementation of the EBENE program within their structure.
We calculated the rate of CPI ≥ 3 at Month 6 (primary outcome). As the trial was stopped early, only descriptive analyses were realized at baseline, 3 and 6 months. All analyses were performed using SAS version 9. 4 (SAS Institute INC. ). To complete the quantitative analysis, a health sociologist conducted exploratory interviews with health managers and nurses. The objective of these interviews was to highlight the grey areas of this study concerning the strengths and weaknesses of the programme from the point of view of these professionals. Only a health professional coordinator and nurses were questioned. The doctors, after agreeing to the participation of the patients in this study, were not involved in the implementation of the programme. These interviews were conducted using qualitative research methodologies  [27].
Ethics EBENE was funded by the "Programme Hospitalier Recherche Clinique" research program, and Dijon University Hospital was the sponsor. The study was approved by the institutional review board (French Ethics Committee for the Protection of Persons (CPP) III of Eastern France (Approval reference: 2015-A00407-42) and the French data protection agency (CNIL), complied with the ethical standards defined by the Declaration of Helsinki and Good Clinical Practice, and was registered on Clinicaltrials. gov: NCT02512367.
Teeth Selection The ethics committee of the Saint Joseph University of Beirut, Lebanon (USJ-2019-237) approved this study. One hundred primary anterior teeth with minimal root resorption, belonging to children aged 3 to 6 and extracted for reasons unrelated to this study as part of treatment plans at the University of X's Department of Pediatric Dentistry, were collected and kept in formocresol 0. 1%. Teeth with previous pulpotomy or pulpectomy, internal resorption, and advanced root resorption were excluded after inspection under an operating microscope. Therefore, 30 primary anterior teeth were included in this study. Using the IBM SPSS statistics software (version 27. 0), the sample size was calculated. To ensure more than 80% power and an alpha error probability of 0. 05, two groups of 15 canals each were formed.
Micro CT Scanning For tooth imaging, a micro-CT Platform (EA2496, Montrouge, France) was used to investigate the 30 teeth. Each tooth was individually scanned with a micro-CT scanner (Quantum FX; PerkinElmer Health Sciences; Hopkinton) to measure the void volume (µm 3 ) in each third in order to assess the filling percentage and voids in the coronal, middle, and apical thirds. The field of view was set at 10 mm to acquire 3D images with an isotropic resolution of 20 µm. Acquisition settings were 160 kV, 90 mA, and 360 • scanning rotation. DICOM data were imported into 3D Slicer 5. 1 software. The following semi-automated threshold-based segmentations were realized:.
Micro CT Scanning For tooth imaging, a micro-CT Platform (EA2496, Montrouge, France) was used to investigate the 30 teeth. Each tooth was individually scanned with a micro-CT scanner (Quantum FX; PerkinElmer Health Sciences; Hopkinton) to measure the void volume (µm 3 ) in each third in order to assess the filling percentage and voids in the coronal, middle, and apical thirds. The field of view was set at 10 mm to acquire 3D images with an isotropic resolution of 20 µm. Acquisition settings were 160 kV, 90 mA, and 360° scanning rotation. DICOM data were imported into 3D Slicer 5. 1 software. The following semiautomated threshold-based segmentations were realized:.
Digital Microscopy Observations Specimen polished surfaces (n = 90, three surfaces for each tooth) were first examined under a digital microscope VHX-5000 (KEYENCE, Osaka, Japan), and one image was captured for each specimen at 100× magnification. The micrographs were coded by an expert examiner who was not involved in the experiment, displaying the canal wall surface of both groups at the coronal, middle, and apical thirds, for blinded analysis using the VHX-5000 software (KEYENCE, Osaka, Japan) to measure the total area of the filling materials and of the internal and external voids in µm 3 following a previous study  [28]  (Figure  2 ). After that, the percentages of voids were calculated and statistically analyzed. Bioengineering 2023, 10, x FOR PEER REVIEW 5 of 13.
Digital Microscopy Observations Specimen polished surfaces (n = 90, three surfaces for each tooth) were first examined under a digital microscope VHX-5000 (KEYENCE, Osaka, Japan), and one image was captured for each specimen at 100× magnification. The micrographs were coded by an expert examiner who was not involved in the experiment, displaying the canal wall surface of both groups at the coronal, middle, and apical thirds, for blinded analysis using the VHX-5000 software (KEYENCE, Osaka, Japan) to measure the total area of the filling materials and of the internal and external voids in µm 3 following a previous study  [28]  (Figure  2 ). After that, the percentages of voids were calculated and statistically analyzed.
Confocal Laser Scanning Microscopy Analysis Confocal laser scanning microscope (Zeiss, LSM 710, Göttingen, Germany) with an objective 10× Plan NeoFluor and a 514 nm excitation wavelength compatible with rhodamine dye was used to examine all the canals (n = 90, three surfaces for each tooth). The entire dentinal tubule penetration area was determined using ImageJ software (NIH). The deepest penetration from the canal wall to the point of maximum sealer penetration was calculated using ImageJ software. Each measurement was performed twice to assure accuracy and reproducibility. The penetration depths at 8 circumferential sites were averaged to obtain the mean sealer penetration depths in µm with the highest degree of accuracy at the coronal, middle, and apical sections for Bio-C Pulpecto and ZOE.
05). The goal of this study was to assess and categorize the data obtained from micro-CT, digital microscopy, CLSM, and SEM so that clinicians could comprehend every aspect of root canal filling on primary teeth. The novelty of this study consists of its combination of numerous in vitro methodologies to evaluate the filling capabilities of root canal pastes used on primary teeth and its choice of the filling material, namely a bioceramic created exclusively for primary teeth. Therefore, each technique would enable comprehension of a certain component of the obturation and provide never-before-published data. The first methodology adopted in this study to compare the filling ability of ZOE and Bio-C Pulpecto was micro-CT imaging. Micro-CT is used to analyze tooth structure objectively, allowing for quantitative and qualitative image analysis  [33, 34].
Introduction: Primary Sjögren's syndrome (pSS) is a systemic autoimmune disease characterized by exocrine gland dysfunction. No therapeutic strategy is sufficient on its own for the management of dry mouth and therapeutic innovations are required. Methods: This Predelfi study was a single-center, prospective, comparative, randomized, double-blind, cross-over controlled study with the primary objective of assessing the tolerance to and effectiveness of two adhesive biofilms (containing prebiotics and, sodium alginate, respectively) in patients with pSS and hyposialia (#NCT04206826 in ClinicalTrials. gov). Secondary objectives were to obtain initial data regarding the clinical effectiveness of such biofilms in the improvement of signs and symptoms related to dry mouth and potential changes in the oral microbiota.
Study population Ten patients with pSS were included. The Ethical Review Boards at Brest Hospital approved the study protocol (registration number NCT04206826, ClinicalTrials. gov). Diagnosis of pSS was made according to the ACR/EULAR classification criteria. Hyposialia was determined by measuring the stimulated salivary flow rate (SSF < 0. 8 ml/ min) and unstimulated salivary flow rate (USF < 0. 3 ml/min).
Study design The study was designed as a single-center, prospective, comparative, randomized, double-blind, cross-over controlled study. Each patient received a biofilm containing prebiotics (biofilm A) or sodium alginate (biofilm B) in a double-blind manner (operator and patient) for two treatment periods of 1 month interspersed with a 1-month washout period (Figure  1 ). The order of treatment (A then B or B then A) was assigned by randomization performed using the CSRandomization module of the Clinsight software. Half of the patients were randomly assigned to the group "A then B" and the other half to the group "B then A. ".
Clinical assessment At each of the four visits (D0, D30, D60, and D90), data regarding the items listed in Table  1  were collected. Examination of the oral mucosa consisted of an objective clinical evaluation of the general state of the mucous membranes (e. g. , redness, dryness, and degree of inflammation) with the establishment of a dry mouth clinical score (DMCS) based on the Challacombe scale  (Osailan et al. , 2011). In addition, at D30 and D90, the degree of redness and inflammation of the gingival mucosa near the site of application of the biofilm was assessed. The patients also completed a validated dry mouth self-report questionnaire comprising 18 items, and a self-report on specific signs and symptoms of dry mouth (such as slurred speech, chewing, swallowing, taste alterations, and burning sensations) using the VAS from 0 to 100 mm  (Salom et al.
Oral microbiota analysis The FASTQ files were processed with the QIIME2 software (v. 2021-8, https://qiime2. org/; Bolyen et al. , 2019)  and were imported in the "PairedEndFastqManifestPhred33"-format. The pipeline DADA2 was used to control the sequence quality and construct the feature table  (Callahan et al. , 2016). The forward and reverse sequences were truncated at 300 and 280 bases, respectively, with all other parameters set to default. Sequence count per sample ranged between 2,298 and 15,225. Prior to taxonomic assignment, reference reads were extracted using the 16S rRNA reference sequences (HOMD_16S_rRNA_RefSeq_V15. 22. p9. fasta) obtained from the expanded Human Oral Microbiome Database V3 website (https:// www. homd. org; eHOMD), on the basis of matches to the primer pair (8F/534R).
The resulting reference reads were then trained as a Naïve Bayes classifier with the corresponding eHOMD 16S rRNA reference sequence taxonomy file for QIIME (HOMD_16S_rRNA_RefSeq_V15. 22. qiime. taxonomy) that was also obtained from the eHOMD website. Core diversity analyses included alpha  (Faith's Phylogenetic Diversity; Faith, 1992)  and beta diversity metrics (weighted UniFrac, and PCoA Bray-Curtis;  Bray and Curtis, 1957; Lozupone et al. , 2007). Each of the feature tables with taxonomic assignment at the species level was exported for further analyses. Sequence data will be made available upon request.
The microbiome at baseline was first compared between the two groups and no differentially abundant features was observed (data not shown). The microbial population of each treatment arm at D60 (after the washout) was then assessed to examine whether it differed compared with the microbial population at D0. No differentially abundant features were reported in sodium alginate biofilm (B) then prebiotic biofilm (A) treatment group, whereas Prevotella salivae was found to have higher abundance at D60 than D0 in prebiotic biofilm (A) then sodium alginate biofilm (B) treatment group (Figure  5A ). Moreover, the effect of the prebiotic biofilm (A) and sodium alginate biofilm (B) in the first treatment period (D0 versus D30) and second treatment period (D60 versus D90) was assessed. When prebiotic biofilm (A) was administered in the first treatment period, an increase in relative abundance was observed for the genera Prevotella (family Prevotellaceae and order Bacteroidales) and Veillonella (class Negativicutes; Figure  5B ).