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Periodontal Diseases

Periodontal Diseases are a group of inflammatory conditions affecting the tissues surrounding and supporting the teeth.
These diseases can lead to tooth loss if left untreated.
Symtpoms may include gum inflammation, bleeding, and receding gums.
Factors like poor oral hygiene, tobacco use, and certain medical conditions can increase the risk.
Early detection and proper management are crucial for maintaining oral health and preventing complications.
PubCompare.ai's AI-driven platform can help researchers optimize their work on Periodontal Diseases, locating the best protocols from literature, preprints, and patents to enable reproducibility and accuracy.

Most cited protocols related to «Periodontal Diseases»

Isolation and Culture of Human Gingival Cells

Human tissue samples were collected from clinically healthy gingiva of subjects who had no history of periodontal disease and relatively healthy periodontium. The gingival tissues were obtained as remnant or discarded tissues following routine dental procedures at the School of Dentistry, USC and the Outpatient Dental Clinic at Los Angeles County-USC Medical Center under the approved Institutional Review Board protocol at USC.
Gingival tissues were treated aseptically and incubated overnight at 4°C with dispase (2 mg/ml; Sigma-Aldrich) to separate the epithelial and lower spinous layer. The tissues were minced into 1- to 3-mm² fragments and digested at 37°C for 2 h in sterile PBS containing 4 mg/ml collagenase IV (Worthington Biochemical). The dissociated cell suspension was filtered through a 70-μm cell strainer (Falcon), plated on nontreated 10-cm petri dishes (VWR Scientific Products) with complete α-MEM (Invitrogen) containing 10% FBS (BD Clontech), 100 U/ml penicillin/100 μg/ml streptomycin (Invitrogen), 2 mM l-glutamine, 100 mM nonessential amino acid, and 550 μM 2-ME (Sigma-Aldrich), and cultured at 37°C in a humidified tissue culture incubator with 5% CO₂ and 95% O₂. After 72 h, the nonadherent cells were removed. The plastic-adherent confluent cells were passaged with 0.05% trypsin containing 1 mM EDTA and continuously subcultured and maintained in the complete growth medium. Cells from second to sixth passages were used in the experiments.

Zhang Q., Shi S., Liu Y., Uyanne J., Shi Y., Shi S, & Le A.D. (2009). Mesenchymal Stem Cells Derived from Human Gingiva Are Capable of Immunomodulatory Functions and Ameliorate Inflammation-Related Tissue Destruction in Experimental Colitis. Journal of immunology (Baltimore, Md. : 1950), 183(12), 7787-7798.

Publication 2009

Amino Acids Cells Collagenase Culture Media Dental Care dispase Edetic Acid Ethics Committees, Research Gingiva Glutamine Healthy Volunteers Homo sapiens Hyperostosis, Diffuse Idiopathic Skeletal Mucolipidosis Type IV Penicillins Periodontal Diseases Periodontium Sterility, Reproductive Streptomycin Tissues Trypsin Vertebral Column

European Periodontal Care Guideline

This guideline was developed following methodological guidance published by the Standing Guideline Commission of the Association of Scientific Medical Societies in Germany (AWMF) (https://www.awmf.org/leitlinien/awmf‐regelwerk/awmf‐guidance.html) and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Working Group (https://www.gradeworkinggroup.org/).
The guideline was developed under the auspices of the European Federation of Periodontology (EFP) and overseen by the EFP Workshop Committee. This guideline development process was steered by an Organizing Committee and a group of methodology consultants designated by the EFP. All members of the Organizing Committee were part of the EFP Workshop Committee.
To ensure adequate stakeholder involvement, the EFP established a guideline panel involving dental professionals representing 36 national periodontal societies within the EFP (Table 1a).
These delegates were nominated, participated in the guideline development process and had voting rights in the consensus conference. For the guideline development process, delegates were assigned to four Working Groups that were chaired by the members of the Organizing Committee and advised by the methodology consultants. This panel was supported by key stakeholders from European scientific societies with a strong professional interest in periodontal care and from European organizations representing key groups within the dental profession, and key experts from non‐EFP member countries, such as North America (Table 1b).
In addition, EFP engaged an independent guideline methodologist to advise the panel and facilitate the consensus process (Prof. Dr. med. Ina Kopp). The guideline methodologist had no voting rights.
EFP and the guideline panel tried to involve patient organizations but were not able to identify any regarding periodontal diseases at European level. In a future update, efforts will be undertaken to include the perspective of citizens/patients (Brocklehurst et al., 2018).

Sanz M., Herrera D., Kebschull M., Chapple I., Jepsen S., Berglundh T., Sculean A, & Tonetti M.S. (2020). Treatment of stage I–III periodontitis—The EFP S3 level clinical practice guideline. Journal of Clinical Periodontology, 47(Suppl 22), 4-60.

Publication 2020

Committee Members Conferences Dental Health Services Europeans Patients Periodontal Diseases Periodontium

CE-TOF-MS Data Analysis Workflow

Raw data were analyzed with our proprietary software called MasterHands, which has already been used in several CE-TOF-MS-based profiling studies (Hirayama et al. 2009 (link); Minami et al. 2009 (link); Saito et al. 2009 (link)). The data analysis workflow starting with the raw data included noise-filtering, baseline correction, peak detection and integration of the peak area from sliced electropherograms (the width of each electropherogram was 0.02 m/z). Such functions are commonly used by data processing software such as MassHunter from Agilent Technologies, or XCMS (Smith et al. 2006 (link)) for liquid chromatography-MS or gas chromatography-MS data. The accurate m/z value for each peak detected within the time domain was calculated with Gaussian curve-fitting to the mass spectrum on the m/z domain peak. The alignment of peaks in multiple measurements was done by dynamic programming (DP)-based techniques (Baran et al. 2006 (link); Soga et al. 2006 (link)) with slight modifications. The method picked up a few representative peaks using the Douglas-Peucker algorithm (Wallace et al. 2004 (link)) from unit m/z electropherograms, found corresponding peaks across multiple samples by DP, and optimized the numerical parameters of the normalization function for CE-migration (Reijenga et al. 2002 (link)). Instead of representative peaks, we used the detected peaks with accurate m/z values and regarded the peaks whose m/z difference was less than 20 ppm as ones that were derived from the same electropherograms.
All peak areas were divided by the area of the internal standard (relative area) to normalize the signal intensities, and to avoid injection-volume bias and mass-spectrometry detector sensitivity bias among multiple measurements. Undetected peaks with a threshold signal-to-noise ratio of 2 were given a peak area of 0. The relative areas of the 17 healthy control samples and of the pancreatic and breast cancer, and the periodontal disease samples were multiplied by 1.25/1.1 to standardize the sample concentration.
The peaks derived from salt and neutral molecules were found in the first and the last few minutes, respectively. Then, isotopic compounds, ringing, spikes and fragment and adduct ions were eliminated and the peak data sets were compared across the sample profiles and aligned according to m/z and migration time. Although all of the metabolites were quantified separately, the sum of the quantified values of leucine and isoleucine were counted as a single marker owing to the low separation of these peaks. Peaks showing P < 0.05 in the non-parametric, multiple comparison Steel–Dwass test, between the controls and at least one disease cohort were selected as candidate markers.

Sugimoto M., Wong D.T., Hirayama A., Soga T, & Tomita M. (2009). Capillary electrophoresis mass spectrometry-based saliva metabolomics identified oral, breast and pancreatic cancer-specific profiles. Metabolomics, 6(1), 78-95.

Publication 2009

Gas Chromatography Hypersensitivity Ions Isoleucine Isotopes Leucine Liquid Chromatography Malignant Neoplasm of Breast Mass Spectrometry Pancreas Periodontal Diseases Sodium Chloride Steel

CE-TOF-MS Data Analysis Workflow

Raw data were analyzed with our proprietary software called MasterHands, which has already been used in several CE-TOF-MS-based profiling studies (Hirayama et al. 2009 (link); Minami et al. 2009 (link); Saito et al. 2009 (link)). The data analysis workflow starting with the raw data included noise-filtering, baseline correction, peak detection and integration of the peak area from sliced electropherograms (the width of each electropherogram was 0.02 m/z). Such functions are commonly used by data processing software such as MassHunter from Agilent Technologies, or XCMS (Smith et al. 2006 (link)) for liquid chromatography-MS or gas chromatography-MS data. The accurate m/z value for each peak detected within the time domain was calculated with Gaussian curve-fitting to the mass spectrum on the m/z domain peak. The alignment of peaks in multiple measurements was done by dynamic programming (DP)-based techniques (Baran et al. 2006 (link); Soga et al. 2006 (link)) with slight modifications. The method picked up a few representative peaks using the Douglas-Peucker algorithm (Wallace et al. 2004 (link)) from unit m/z electropherograms, found corresponding peaks across multiple samples by DP, and optimized the numerical parameters of the normalization function for CE-migration (Reijenga et al. 2002 ). Instead of representative peaks, we used the detected peaks with accurate m/z values and regarded the peaks whose m/z difference was less than 20 ppm as ones that were derived from the same electropherograms.
All peak areas were divided by the area of the internal standard (relative area) to normalize the signal intensities, and to avoid injection-volume bias and mass-spectrometry detector sensitivity bias among multiple measurements. Undetected peaks with a threshold signal-to-noise ratio of 2 were given a peak area of 0. The relative areas of the 17 healthy control samples and of the pancreatic and breast cancer, and the periodontal disease samples were multiplied by 1.25/1.1 to standardize the sample concentration.
The peaks derived from salt and neutral molecules were found in the first and the last few minutes, respectively. Then, isotopic compounds, ringing, spikes and fragment and adduct ions were eliminated and the peak data sets were compared across the sample profiles and aligned according to m/z and migration time. Although all of the metabolites were quantified separately, the sum of the quantified values of leucine and isoleucine were counted as a single marker owing to the low separation of these peaks. Peaks showing P < 0.05 in the non-parametric, multiple comparison Steel–Dwass test, between the controls and at least one disease cohort were selected as candidate markers.

Publication 2009

Gas Chromatography Hypersensitivity Ions Isoleucine Isotopes Leucine Liquid Chromatography Malignant Neoplasm of Breast Mass Spectrometry Pancreas Periodontal Diseases Sodium Chloride Steel

Time-Course Gingival Changes in Ligature-Induced Periodontitis

Following a protocol approved by the Institutional Animal Care and Use Committee (IACUC) of the University of Puerto Rico, anesthetized animals were examined by a single investigator using a Maryland probe on the facial aspect of the teeth, 2 proximal sites per tooth (mesio- and disto-buccal), excluding the canines and 3^rd molars. The clinical examination included probing pocket depth (PD), and bleeding on probing (BOP; 0–5 scale) (Ebersole et al., 2008 (link)). At the initiation of the study, all animals were evaluated clinically for periodontal disease, and only animals with mean bleeding on probing (BOP) of ≤1 and mean pocket depths (PD) <3 mm were entered into the study. After taking the baseline gingival samples, ligatures were placed on the second premolar and first and second molars of both maxillary quadrants. Further, clinical evaluation for ligated sites was obtained and a buccal gingival papilla from each animal was taken using a standard gingivectomy technique at 2 weeks and 1 month (initiation of disease), and 3 months (progression of disease), time in which soft and alveolar bone destruction has been shown to occur in this model (Smith et al., 1993 (link), Branch-Mays et al., 2008 (link), Moritz et al., 1998 (link)). Then, ligatures were removed after sampling at 3 months and samples taken 2 months later (resolution). Samples were maintained frozen at −80°C in RNAlater solution until RNA preparation for microarray and real time RT-PCR analysis.

Ebersole J.L., Kirakodu S., Novak M.J., Stromberg A.J., Shen S., Orraca L., Gonzalez-Martinez J., Burgos A, & Gonzalez O.A. (2014). Cytokine Gene Expression Profiles during Initiation, Progression and Resolution of Periodontitis. Journal of clinical periodontology, 41(9), 853-861.

Publication 2014

Animals Bicuspid Bones Canis familiaris Cheek Disease Progression Face Freezing Gingiva Gingivectomy Institutional Animal Care and Use Committees Ligature Maxilla Microarray Analysis Molar Nipples Periodontal Diseases Physical Examination Real-Time Polymerase Chain Reaction Tooth

Most recents protocols related to «Periodontal Diseases»

Comprehensive AS Management System Database

The EMRMS was established in November, 2016 to assist rheumatologists in conducting ASDAS assessments and comprehensively evaluating clinical outcomes in all patients with AS attending TCVGH. The EMRMS database contains information necessary to determite ASDAS, including CRP, level and erythrocyte sedimentation rate [ESR], patient comorbidities, patient history, and family history. The reliability and validity of the data have been verified^{14 (link)}.Patients with AS were consecutively enrolled in the TCVGH-AS cohort after they received a confirmed AS diagnosis from a TCVGH rheumatologist according to the 1984 modified New York criteria^{10 (link)}. The CRP and ESR data were automatically uploaded to the TCVGH healthcare information system (HIS) to reduce human error. The baseline information, which was collected by trained nurses during the initial visit, including clinical characteristics, onset age, comorbidities at presentation (hypertension, diabetes mellitus, hyperlipidemia, hepatitis B, hepatitis C, renal insufficiency, gout, coronary artery disease, stroke, periodontal disease, osteoporosis, and tuberculosis history), periarticular extraspinal features (synovitis, enthesitis, and dactylitis) and nonarticular manifestations (psoriasis, uveitis, and IBD), family history of autoimmune disease, and patient history of arthropathy, obtained through standardized questionnaires and worksheets to ensure reproducibility and adherence to good laboratory practice. The rheumatologist in charge then confirmed patients’ clinical characteristics, and nurses assisted the patients with AS to complete the self-assessment questionnaires for disease evaluation. The following measures were used: global assessment of disease activity on a numerical rating scale (NRS) of 0–10, back pain on an NRS of 0–10, duration of morning stiffness on an NRS of 0–10, and peripheral pain or swelling on an NRS of 0–10. Before every 3-month visiting clinic, the patient would first to have blood examination. Blood reports can be uploaded to EMRMS through the HIS system, trained nurses assist patient fills out the questionnaire on EMRMS, the assessment of disease activity completed before visiting the doctor. All laboratory data, including CRP and ESR, have been uploaded to the HIS. The IT at TCVGH help "feed-forward" the patient reported outcomes to HIS, and do the auto-calculation of ASDAS-ESR, ASDAS-CRP using the ESR, CRP data in HIS, then "feed-back" these data to both HIS and EMRMS, showing the data on the summary overview "dashboard" in the EMRMS, which was shown both in HIS and the devices (iPAD handled by a nurse in charge and smartphones of patients with AS).

Huang P.J., Chen Y.H., Huang W.N., Chen Y.M., Lai K.L., Hsieh T.Y., Hung W.T., Lin C.T., Tseng C.W., Tang K.T., Chou Y.Y., Wu Y.D., Huang C.Y., Hsieh C.W., Chen Y.J., Liao Y.W., Liu Y.T, & Chen H.H. (2023). The electronic medical record management systems may improve monitoring and control of disease activity in patients with ankylosing spondylitis. Scientific Reports, 13, 3957.

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Publication 2023

Arthropathy Autoimmune Diseases Back Pain BLOOD Cerebrovascular Accident Charge Nurses Coronary Artery Disease Diabetes Mellitus Diagnosis Gout Hepatitis B Hepatitis C virus High Blood Pressures Homo sapiens Hyperlipidemia Medical Devices Nurses Osteoporosis Pain Patients Periodontal Diseases Physicians Psoriasis Renal Insufficiency Rheumatologist Sedimentation Rates, Erythrocyte Self-Assessment Synovitis Tuberculosis Uveitis

Mandibular Incisor Extraction and Analysis

This research project was approved by the Committee in Ethics and the institutional review board (Issuing Number: KY2022-089-01). Extracted permanent mandibular incisors were collected from the Dental Department of the Ninth People’s Hospital of Suzhou, from 2016 to 2022. All subjects were native Chinese, and the teeth were extracted because of periodontal disease, nonrestorable caries, trauma, or prosthodontic reasons. The teeth type (the permanent mandibular central and lateral incisors) was accurately identified by the operator according to its external anatomy, position in the dental arch, tooth sockets in jaw bone, and dental history, and the age of the subject was also recorded. The exclusion criteria were as follows: (a) teeth with a fracture or other major defects in the roots, (b) teeth with root canal fillings, crown restorations, and open apices, and (c) the tooth type cannot be determined correctly. A total of 53 mandibular central and 53 mandibular lateral incisors were included in the current study. The age of the subjects ranged from 14 to 84 years old (mean age = 56.3 ± 16.7 years).
Before investigation, the specimens were immersed in 5% sodium hypochlorite solution for 2 h to remove attached soft tissue. Calculus and stains were removed by an ultrasonic dental scaler. Then the teeth were stored in 10% neutral formalin fix solution.

Tang Y., Wu Y., Pei F., Liu C., Qiu Y., Yang T, & Gu Y. (2023). A micro–computed tomographic analysis of the root canal systems in the permanent mandibular incisors in a Chinese population. BMC Oral Health, 23, 129.

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Publication 2023

Calculi Chinese Dental Arch Dental Caries Dental Health Services Ethics Committees, Research Formalin Incisor Jaw Mandible Periodontal Diseases Plant Roots Root Canal Obturation Sodium Hypochlorite Staining Tissues Tooth Tooth Fractures Tooth Socket Ultrasonics Wounds and Injuries

Periodontal Health Assessment Protocol

Upon confirmation of eligibility for enrollment in the study, clinical periodontal measurements including probing pocket depth (PPD) (mm), clinical attachment loss (CAL) (mm), plaque index (PI) [26 (link)], gingival index (GI) [27 (link)], and bleeding on probing (BOP) (presence/absence) (%) [28 (link)] were recorded from all participants (test and control) during their visit to the Periodontology Department at timepoint 2. Clinical periodontal measurements were performed at six sites on each tooth (mesio-buccal, mid-buccal, disto-buccal, mesio-lingual, mid-lingual, and disto-lingual locations), except for third molars, using a manual periodontal probe (Williams, Hu-Friedy, Chicago, IL, USA) by a single trained examiner (AS). Intra-examiner agreement was determined for CAL. The intra-examiner reproducibility was determined through repeated examinations of 10 subjects with a one-hour interval (k = 0.95).
Diagnosis of periodontal disease was based on clinical and radiographic criteria proposed by 2017 World Workshop on the Classifications of Periodontal and Peri-implant Disease and Conditions [29 (link)]. Individuals with a BOP < 10% without attachment loss and radiographic bone loss were considered to have periodontal health [30 (link)]. Individuals presenting with a BOP ≥ 10%, and PPD ≤ 3 mm without attachment loss and radiographic bone loss were considered gingivitis [31 (link)]. The criteria for patients with periodontitis were (1) interdental CAL detectable at ≥ 2 non-adjacent teeth or (2) buccal or oral CAL ≥ 3 mm with PPD > 3 mm detectable at ≥ 2 teeth [32 (link)]. The periodontal examiner was not blind to the test or control status.

Sari A., Dikmen N.K, & Nibali L. (2023). Association between periodontal diseases and COVID-19 infection: a case–control study with a longitudinal arm. Odontology, 111(4), 1009-1017.

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Publication 2023

Cheek Diagnosis Eligibility Determination Gingival Index Gingivitis Osteopenia Patients Periodontal Diseases Periodontitis Periodontium Physical Examination Third Molars Tongue Tooth Tooth Loss Visually Impaired Persons X-Rays, Diagnostic

Autogenous vs. Allogenic Bone Grafts for Implant Placement

The present pilot study was conducted from January 2020 to June 2021 at the outpatient Department of Periodontology, of our institute in accordance with the Helsinki Declaration of 1975, as revised in 2013 and was registered at Clinical Trial Registry of India. A written informed consent was obtained from all the participating patients. The study was also approved by Institutional Ethics Committee.
A total of 20 patients in the age range of 20–50 years were enrolled for the study and were fully informed about the surgical procedure and treatment alternatives. Patients were randomly divided into two groups using simple randomization method by computer-generated numbers to reduce potential bias involved.

Group I – Patients treated using autogenous bone block graft (n = 10)

Group II –Patients treated using allogenic DFDBA bone block graft (n = 10).

The inclusion criterion mandated systemically healthy patients requiring dental implant placement, presence of a clinically relevant bone atrophy of the alveolar ridge in the predominantly horizontal and/or vertical plane as identified by cone beam computed tomography (CBCT). The minimum defect size of ≤3 mm at crestal and middle sites of bucco-palatal dimension of residual alveolar ridge, edentulous space of a single tooth missing in the maxillary anterior region were included. The exclusion criteria consisted of a history of radiotherapy in the head and neck region, existing severe periodontal disease, bruxism, smoking habit or alcoholism, pregnancy, psychiatric problems, and/or use of medications known to alter bone healing.
After screening, radiographic examination including CBCT analysis was carried out before undergoing the surgical procedure. The patients underwent a thorough initial periodontal examination including the plaque index, gingival index, and probing depth. The preoperative CBCT measurements are as follows:
The alveolar bone levels were measured in their height, width, and depth at the cervical, middle, and apical level taking adjacent teeth as reference [Figure 1].

Bawankar P.V., Kolte A.P, & Kolte R.A. (2023). Patient-centered outcome measures comparing the autogenous and allogenic bone blocks in the augmentation of deficient alveolar ridges: A pilot study. Journal of Indian Society of Periodontology, 27(1), 87-94.

Publication 2023

Alcoholic Intoxication, Chronic Alveolar Bone Loss Bones Bone Transplantation Bruxism Cardiac Arrest Cone-Beam Computed Tomography Gingival Index Head Implant, Dental Institutional Ethics Committees Maxilla Neck Operative Surgical Procedures Outpatients Patients Periodontal Diseases Periodontium Pharmaceutical Preparations Pregnancy Radiotherapy Ridge, Alveolar Tooth Tooth Loss X-Rays, Diagnostic

Timing of Periodontal Treatment and Birth Outcomes

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Publication 2023

Adverse Birth Outcomes Childbirth Dental Health Services Diagnosis Ethnicity Hypersensitivity Obstetric Delivery Periodontal Diseases Pregnancy Woman

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More about "Periodontal Diseases"

Periodontal diseases, also known as gum diseases or periodontitis, are a group of inflammatory conditions that affect the tissues surrounding and supporting the teeth.
These conditions can lead to tooth loss if left untreated.
Symptoms may include gum inflammation, bleeding, and receding gums.
Factors like poor oral hygiene, tobacco use, and certain medical conditions, such as diabetes, can increase the risk of developing periodontal diseases.
Early detection and proper management are crucial for maintaining oral health and preventing complications.
Researchers can utilize AI-driven platforms like PubCompare.ai to optimize their work on periodontal diseases.
These platforms can help locate the best protocols from literature, preprints, and patents, enabling reproducibility and accuracy in their research.
When studying periodontal diseases, researchers may also encounter terms like FBS (Fetal Bovine Serum), SAS version 9.4 (Statistical Analysis System), Penicillin, Streptomycin, Trypsin, SPSS Statistics (Statistical Package for the Social Sciences), α-MEM (Alpha Minimal Essential Medium), DMEM (Dulbecco's Modified Eagle Medium), UNC-15 (a gene in Caenorhabditis elegans), and Stata 12.0 (a statistical software package).
These tools and resources can be valuable in understanding and advancing research on periodontal diseases.
By leveraging the power of AI-driven comparisons, researchers can find the optimal solutions for their research needs, ultimately contributing to the prevention and management of periodontal diseases and improving overall oral health.