773 research outputs found
Hampaiden menetys, alaleuan morfologia ja proteettinen hoito: kliininen, radiologinen ja <em>in vitro</em> tutkimus
No full textAbstractTooth loss adversely affects patients’ quality of life and causes inevitable changes in the mandibular morphology. Polymethyl methacrylate (PMMA) is the most frequently used material of removable dentures. Denture stomatitis (DS) is a common clinical finding among denture wearers, particularly patients with debilitating diseases. Several fillers and nanofillers have been used to improve the physical, mechanical, antifungal, and antimicrobial properties of PMMA.The aim of the present retrospective cross-sectional study was to determine the prevalence of tooth loss and the commonly used prosthetic constructions in 479 adult patients at the Department of Substitutive Dental Sciences (SDS), College of Dentistry, University of Dammam, currently Imam Abdulrahman Bin Faisal University, Dammam. The influence of tooth loss on mandibular morphology was studied by using cone-beam computed tomographic (CBCT) scans of 101 patients. The effect of addition of thymoquinone (TQ) and nanodiamonds (NDs) to PMMA on the flexural and surface properties of PPMA and their antifungal influence was tested through in vitro studies.Edentulousness was recorded in 6%, a single edentulous arch in 8%, and partial edentulousness in 74% of the patients. Age and diabetes were significantly associated with edentulousness. Males had a significantly higher number of missing teeth compared to females. Kennedy class III was most common in the upper and lower jaw and was treated more often with fixed partial denture (FPD) than with removable partial denture (RPD). Larger gonial angle (GA) of the mandible was found in edentulous patients, in females and in older compared to dentate patients, males and younger patients. The addition of TQ to PMMA at low concentration did not significantly change the flexural strength, elastic modulus or surface properties of PMMA. The addition of NDs to PMMA significantly reduced surface roughness and the Candida albicans (C. albicans) count.Edentulousness increased in old age and caused changes in mandibular morphology. TQ addition at low concentration did not change the flexural and surface properties of PMMA. NDs decreased the surface roughness of PMMA and Candida albicans adhesion, which could help in the prevention of denture stomatitis.Original papersOriginal papers are not included in the electronic version of the dissertation.Fouda, S. M., Al-Harbi, F. A., Khan, S. Q., Virtanen, J. I., & Raustia, A. (2017). Missing Teeth and Prosthetic Treatment in Patients Treated at College of Dentistry, University of Dammam. International Journal of Dentistry, 2017, 1–6. https://doi.org/10.1155/2017/7593540Self-archived versionFouda, S., Gad, M., El Tantawi, M., Virtanen, J., Sipila, K., & Raustia, A. (2019). Influence of tooth loss on mandibular morphology: A cone-beam computed tomography study. Journal of Clinical and Experimental Dentistry, 0–0. https://doi.org/10.4317/jced.55879Gad, M. M., Al‐Thobity, A. M., Fouda, S. M., Näpänkangas, R., & Raustia, A. (2018). Flexural and Surface Properties of PMMA Denture Base Material Modified with Thymoquinone as an Antifungal Agent. Journal of Prosthodontics, 29(3), 243–250. https://doi.org/10.1111/jopr.12967Fouda, S. M., Gad, M. M., Ellakany, P., Al-Thobity, A. M., Al-Harbi, F. A., Virtanen, J. I., & Raustia, A. (2019). The effect of nanodiamonds on candida albicans adhesion and surface characteristics of PMMA denture base material - an in vitro study. Journal of Applied Oral Science, 27. https://doi.org/10.1590/1678-7757-2018-0779Self-archived versionTiivistelmäHampaattomuus vaikuttaa potilaiden elämänlaatuun ja aiheuttaa alaleuan muodon muutoksia. Hampaattomuutta ja hammaspuutoksia voidaan hoitaa purennan kuntoutuksella irtoproteeseilla ja kiinteällä protetiikalla. Polymetyylimetakrylaatti (PMMA) on yleisimmin käytetty irtoproteesien materiaali. Suun sieni-infektio, proteesistomatiitti, on yleinen kliininen löydös proteesipotilailla ja erityisesti potilailla, joilla on yleiskuntoa heikentäviä sairauksia. Erilaisia lisämateriaaleja on käytetty parantamaan PMMA:n fysikaalisia, mekaanisia ja antimikrobisia ominaisuuksia.Tämän retrospektiivisen poikittaistutkimuksen tarkoituksena oli kartoittaa hampaattomuuden ja hammaspuutosten esiintyvyys ja toteutetut proteettiset hoidot 479 saudiarabialaisella aikuispotilaalla, jotka oli hoidettu Dammanin yliopiston hammaslääketieteen laitoksella. Hammaspuutosten vaikutusta alaleuan muotoon tutkittiin 101 potilaan kartiokeilatietokonetomografia (KKTT) kuvista. Tymokinonin (thymoquinone, TQ) ja nanotimanttien (ND) lisäyksen vaikutusta PPMA:n taivutuslujuuteen ja pintaominaisuuksiin sekä niiden antimikrobisia ominaisuuksia tutkittiin in vitro kokein.Täydellistä hampaattomuutta oli 6 %:lla, ylä- tai alaleuan hampaattomuutta 8 %:lla ja osittaista hampaattomuutta 74 %:lla potilaista. Hampaattomuutta lisäsivät merkittävästi potilaan ikä sekä yleissairauksista diabetes. Miehillä oli merkittävästi enemmän omia hampaita jäljellä kuin naisilla. Hammaspuutosten sijainnin luokittelussa Kennedyn luokka III oli yleisin sekä ylä- että alaleuassa ja puutos oli useammin hoidettu kiinteällä siltaratkaisulla kuin irrotettavalla osaproteesilla. Alaleuan leukakulma oli hampaattomilla, naisilla ja vanhemmilla potilailla suurempi kuin hampaallisilla, miehillä ja nuoremmilla potilailla.Alhainen TQ-pitoisuus ei merkittävästi muuttanut PMMA:n taivutuslujuutta, kimmomoduulia eikä sen pintaominaisuuksia. Nanotimanttien lisäys vähensi merkittävästi PMMA:n pinnankarheutta ja Candida albicans-kasvustoa.Tutkimus osoitti, että hampaattomuus lisääntyi iän myötä ja aiheutti alaleuan muodon muutoksia. Alhainen TQ-pitoisuus ei muuttanut PMMA:n taivutuslujuutta tai pintaominaisuuksia. Nanotimantit alensivat PMMA:n pinnankarheutta ja Candida albicansin kiinnittymistä siihen, mistä voisi olla apuna proteesistomatiitin ehkäisyssä.OsajulkaisutOsajulkaisut eivät sisälly väitöskirjan elektroniseen versioon.Fouda, S. M., Al-Harbi, F. A., Khan, S. Q., Virtanen, J. I., & Raustia, A. (2017). Missing Teeth and Prosthetic Treatment in Patients Treated at College of Dentistry, University of Dammam. International Journal of Dentistry, 2017, 1–6. https://doi.org/10.1155/2017/7593540Rinnakkaistallennettu versioFouda, S., Gad, M., El Tantawi, M., Virtanen, J., Sipila, K., & Raustia, A. (2019). Influence of tooth loss on mandibular morphology: A cone-beam computed tomography study. Journal of Clinical and Experimental Dentistry, 0–0. https://doi.org/10.4317/jced.55879Gad, M. M., Al‐Thobity, A. M., Fouda, S. M., Näpänkangas, R., & Raustia, A. (2018). Flexural and Surface Properties of PMMA Denture Base Material Modified with Thymoquinone as an Antifungal Agent. Journal of Prosthodontics, 29(3), 243–250. https://doi.org/10.1111/jopr.12967Fouda, S. M., Gad, M. M., Ellakany, P., Al-Thobity, A. M., Al-Harbi, F. A., Virtanen, J. I., & Raustia, A. (2019). The effect of nanodiamonds on candida albicans adhesion and surface characteristics of PMMA denture base material - an in vitro study. Journal of Applied Oral Science, 27. https://doi.org/10.1590/1678-7757-2018-0779Rinnakkaistallennettu versioAcademic dissertation to be presented with the assent of the Doctoral Training Committee of Health and Biosciences of the University of Oulu for public defence in the Markku Larmas auditorium (H1091) in Dentopolis, on 12 March 2021, at 12 noonAbstract
Tooth loss adversely affects patients’ quality of life and causes inevitable changes in the mandibular morphology. Polymethyl methacrylate (PMMA) is the most frequently used material of removable dentures. Denture stomatitis (DS) is a common clinical finding among denture wearers, particularly patients with debilitating diseases. Several fillers and nanofillers have been used to improve the physical, mechanical, antifungal, and antimicrobial properties of PMMA.
The aim of the present retrospective cross-sectional study was to determine the prevalence of tooth loss and the commonly used prosthetic constructions in 479 adult patients at the Department of Substitutive Dental Sciences (SDS), College of Dentistry, University of Dammam, currently Imam Abdulrahman Bin Faisal University, Dammam. The influence of tooth loss on mandibular morphology was studied by using cone-beam computed tomographic (CBCT) scans of 101 patients. The effect of addition of thymoquinone (TQ) and nanodiamonds (NDs) to PMMA on the flexural and surface properties of PPMA and their antifungal influence was tested through in vitro studies.
Edentulousness was recorded in 6%, a single edentulous arch in 8%, and partial edentulousness in 74% of the patients. Age and diabetes were significantly associated with edentulousness. Males had a significantly higher number of missing teeth compared to females. Kennedy class III was most common in the upper and lower jaw and was treated more often with fixed partial denture (FPD) than with removable partial denture (RPD). Larger gonial angle (GA) of the mandible was found in edentulous patients, in females and in older compared to dentate patients, males and younger patients. The addition of TQ to PMMA at low concentration did not significantly change the flexural strength, elastic modulus or surface properties of PMMA. The addition of NDs to PMMA significantly reduced surface roughness and the Candida albicans (C. albicans) count.
Edentulousness increased in old age and caused changes in mandibular morphology. TQ addition at low concentration did not change the flexural and surface properties of PMMA. NDs decreased the surface roughness of PMMA and Candida albicans adhesion, which could help in the prevention of denture stomatitis.Tiivistelmä
Hampaattomuus vaikuttaa potilaiden elämänlaatuun ja aiheuttaa alaleuan muodon muutoksia. Hampaattomuutta ja hammaspuutoksia voidaan hoitaa purennan kuntoutuksella irtoproteeseilla ja kiinteällä protetiikalla. Polymetyylimetakrylaatti (PMMA) on yleisimmin käytetty irtoproteesien materiaali. Suun sieni-infektio, proteesistomatiitti, on yleinen kliininen löydös proteesipotilailla ja erityisesti potilailla, joilla on yleiskuntoa heikentäviä sairauksia. Erilaisia lisämateriaaleja on käytetty parantamaan PMMA:n fysikaalisia, mekaanisia ja antimikrobisia ominaisuuksia.
Tämän retrospektiivisen poikittaistutkimuksen tarkoituksena oli kartoittaa hampaattomuuden ja hammaspuutosten esiintyvyys ja toteutetut proteettiset hoidot 479 saudiarabialaisella aikuispotilaalla, jotka oli hoidettu Dammanin yliopiston hammaslääketieteen laitoksella. Hammaspuutosten vaikutusta alaleuan muotoon tutkittiin 101 potilaan kartiokeilatietokonetomografia (KKTT) kuvista. Tymokinonin (thymoquinone, TQ) ja nanotimanttien (ND) lisäyksen vaikutusta PPMA:n taivutuslujuuteen ja pintaominaisuuksiin sekä niiden antimikrobisia ominaisuuksia tutkittiin in vitro kokein.
Täydellistä hampaattomuutta oli 6 %:lla, ylä- tai alaleuan hampaattomuutta 8 %:lla ja osittaista hampaattomuutta 74 %:lla potilaista. Hampaattomuutta lisäsivät merkittävästi potilaan ikä sekä yleissairauksista diabetes. Miehillä oli merkittävästi enemmän omia hampaita jäljellä kuin naisilla. Hammaspuutosten sijainnin luokittelussa Kennedyn luokka III oli yleisin sekä ylä- että alaleuassa ja puutos oli useammin hoidettu kiinteällä siltaratkaisulla kuin irrotettavalla osaproteesilla. Alaleuan leukakulma oli hampaattomilla, naisilla ja vanhemmilla potilailla suurempi kuin hampaallisilla, miehillä ja nuoremmilla potilailla.
Alhainen TQ-pitoisuus ei merkittävästi muuttanut PMMA:n taivutuslujuutta, kimmomoduulia eikä sen pintaominaisuuksia. Nanotimanttien lisäys vähensi merkittävästi PMMA:n pinnankarheutta ja Candida albicans-kasvustoa.
Tutkimus osoitti, että hampaattomuus lisääntyi iän myötä ja aiheutti alaleuan muodon muutoksia. Alhainen TQ-pitoisuus ei muuttanut PMMA:n taivutuslujuutta tai pintaominaisuuksia. Nanotimantit alensivat PMMA:n pinnankarheutta ja Candida albicansin kiinnittymistä siihen, mistä voisi olla apuna proteesistomatiitin ehkäisyssä
The role of Plasmodium falciparum var genes in malaria in pregnancy
No full textSequestration of Plasmodium falciparum-infected erythrocytes in the placenta is responsible for many of the harmful effects of malaria during pregnancy. Sequestration occurs as a result of parasite adhesion molecules expressed on the surface of infected erythrocytes binding to host receptors in the placenta such as chondroitin sulphate A (CSA). Identification of the parasite ligand(s) responsible for placental adhesion could lead to the development of a vaccine to induce antibodies to prevent placental sequestration. Such a vaccine would reduce the maternal anaemia and infant deaths that are associated with malaria in pregnancy. Current research indicates that the parasite ligands mediating placental adhesion may be members of the P. falciparum variant surface antigen family PfEMP1, encoded by var genes. Two relatively well-conserved subfamilies of var genes have been implicated in placental adhesion, however, their role remains controversial. This review examines the evidence for and against the involvement of var genes in placental adhesion, and considers whether the most appropriate vaccine candidates have yet been identified
The COVID-19 pandemic in Greece, Iceland, New Zealand, and Singapore: Health policies and lessons learned
No full textObjective(s)
This paper aims at providing an overview of the COVID-19 situation, health policies, and economic impact in Greece, Iceland, New Zealand, and Singapore. The four countries were chosen due to their ability to contain the spread and mitigate the effects of COVID-19 on their societies.
Method(s)
We use document analysis based on the available national reports, media announcements, official coronavirus websites and governmental decrees in each of the four countries starting from the 1st of January o the 9th of August announcements. We apply a policy gradient to compare and examine the policies implemented in the four countries.
Finding(s)
The four countries have different demographic, epidemiological, socioeconomic profiles but managed to control the pandemic at an early stage in terms of total number of positive cases. The four countries managed to absorb the health system shock and decrease the case fatality ratio of COVID-19. Early interventions were crucial to avoid expected life lost in case of no early lockdown. The pandemic triggered several economic stimulus and relief measures in the four countries; the impact or the economic rebound is yet to be fully observed.
Conclusion(s)
We conclude that early, proactive and strict interventions along with leveraging previous experience on communicable diseases and the evolution of testing strategies are key lessons that can be synthesized from the interventions of the four countries and that could be useful for a potential second wave or similar pandemics
COVID-19 and dermatology: a comprehensive guide for dermatologists
No full textAs of the 11th of March, the world health organization (WHO) declared Coronavirus disease‐2019 (COVID‐19) as a pandemic disease caused by SARS‐CoV‐2 (previously known as 2019‐nCOV) (1,2). By the 19th of April, 2,241,778 confirmed patients were reported worldwide with 152,552 COVID‐19 related deaths (3). The COVID‐19 pandemic represents the most serious health crisis facing the modern world resulting in unprecedented efforts to contain this pandemic and its consequence
Brain Tumor Characterization Using Radiogenomics in Artificial Intelligence Framework
No full textBrain tumor characterization (BTC) is the process of knowing the underlying cause of brain tumors and their characteristics through various approaches such as tumor segmentation, classification, detection, and risk analysis. The substantial brain tumor characterization includes the identification of the molecular signature of various useful genomes whose alteration causes the brain tumor. The radiomics approach uses the radiological image for disease characterization by extracting quantitative radiomics features in the artificial intelligence (AI) environment. However, when considering a higher level of disease characteristics such as genetic information and mutation status, the combined study of “radiomics and genomics” has been considered under the umbrella of “radiogenomics”. Furthermore, AI in a radiogenomics’ environment offers benefits/advantages such as the finalized outcome of personalized treatment and individualized medicine. The proposed study summarizes the brain tumor’s characterization in the prospect of an emerging field of research, i.e., radiomics and radiogenomics in an AI environment, with the help of statistical observation and risk-of-bias (RoB) analysis. The PRISMA search approach was used to find 121 relevant studies for the proposed review using IEEE, Google Scholar, PubMed, MDPI, and Scopus. Our findings indicate that both radiomics and radiogenomics have been successfully applied aggressively to several oncology applications with numerous advantages. Furthermore, under the AI paradigm, both the conventional and deep radiomics features have made an impact on the favorable outcomes of the radiogenomics approach of BTC. Furthermore, risk-of-bias (RoB) analysis offers a better understanding of the architectures with stronger benefits of AI by providing the bias involved in them
Role of Artificial Intelligence in Radiogenomics for Cancers in the Era of Precision Medicine
No full textRadiogenomics, a combination of “Radiomics” and “Genomics,” using Artificial Intelligence (AI) has recently emerged as the state-of-the-art science in precision medicine, especially in oncology care. Radiogenomics syndicates large-scale quantifiable data extracted from radiological medical images enveloped with personalized genomic phenotypes. It fabricates a prediction model through various AI methods to stratify the risk of patients, monitor therapeutic approaches, and assess clinical outcomes. It has recently shown tremendous achievements in prognosis, treatment planning, survival prediction, heterogeneity analysis, reoccurrence, and progression-free survival for human cancer study. Although AI has shown immense performance in oncology care in various clinical aspects, it has several challenges and limitations. The proposed review provides an overview of radiogenomics with the viewpoints on the role of AI in terms of its promises for computa-tional as well as oncological aspects and offers achievements and opportunities in the era of precision medicine. The review also presents various recommendations to diminish these obstacles
Crossing the Rubicon: making a case for refining the classification of Jihadist Terrorism
No full textThis paper posits that our current understanding of Jihadist Terrorism as a monolithic sub-type of Political Terrorism is flawed and that as a result our governments counter this threat with inappropriately-adapted methods. The author argues: (A) There is a sub-type of Jihadist Terrorism that is more consistent with Walter’s ‘Military Terrorism’ or Feldman and Hinojosa’s ‘Guerrilla Warfare’ than within the typology of Political Terrorism; (B) The author-proposed sub-type of ‘War Terrorism’ should be accepted, examined, defined, and established; and (C) Establishing the author’s sub-type will allow western democracies to devise better counter-terrorism strategies while protecting the civil liberties of their citizens.Publisher PD
Cardiovascular/Stroke Risk Assessment in Patients with Erectile Dysfunction—A Role of Carotid Wall Arterial Imaging and Plaque Tissue Characterization Using Artificial Intelligence Paradigm: A Narrative Review
No full textPurpose: The role of erectile dysfunction (ED) has recently shown an association with the risk of stroke and coronary heart disease (CHD) via the atherosclerotic pathway. Cardiovascular disease (CVD)/stroke risk has been widely understood with the help of carotid artery disease (CTAD), a surrogate biomarker for CHD. The proposed study emphasizes artificial intelligence-based frameworks such as machine learning (ML) and deep learning (DL) that can accurately predict the severity of CVD/stroke risk using carotid wall arterial imaging in ED patients. Methods: Using the PRISMA model, 231 of the best studies were selected. The proposed study mainly consists of two components: (i) the pathophysiology of ED and its link with coronary artery disease (COAD) and CHD in the ED framework and (ii) the ultrasonic-image morphological changes in the carotid arterial walls by quantifying the wall parameters and the characterization of the wall tissue by adapting the ML/DL-based methods, both for the prediction of the severity of CVD risk. The proposed study analyzes the hypothesis that ML/DL can lead to an accurate and early diagnosis of the CVD/stroke risk in ED patients. Our finding suggests that the routine ED patient practice can be amended for ML/DL-based CVD/stroke risk assessment using carotid wall arterial imaging leading to fast, reliable, and accurate CVD/stroke risk stratification. Summary: We conclude that ML and DL methods are very powerful tools for the characterization of CVD/stroke in patients with varying ED conditions. We anticipate a rapid growth of these tools for early and better CVD/stroke risk management in ED patients
Segmentation-Based Classification Deep Learning Model Embedded with Explainable AI for COVID-19 Detection in Chest X-ray Scans
No full textBackground and Motivation: COVID-19 has resulted in a massive loss of life during the last two years. The current imaging-based diagnostic methods for COVID-19 detection in multiclass pneumonia-type chest X-rays are not so successful in clinical practice due to high error rates. Our hypothesis states that if we can have a segmentation-based classification error rate <5%, typically adopted for 510 (K) regulatory purposes, the diagnostic system can be adapted in clinical settings. Method: This study proposes 16 types of segmentation-based classification deep learning-based systems for automatic, rapid, and precise detection of COVID-19. The two deep learning-based segmentation networks, namely UNet and UNet+, along with eight classification models, namely VGG16, VGG19, Xception, InceptionV3, Densenet201, NASNetMobile, Resnet50, and MobileNet, were applied to select the best-suited combination of networks. Using the cross-entropy loss function, the system performance was evaluated by Dice, Jaccard, area-under-the-curve (AUC), and receiver operating characteristics (ROC) and validated using Grad-CAM in explainable AI framework. Results: The best performing segmentation model was UNet, which exhibited the accuracy, loss, Dice, Jaccard, and AUC of 96.35%, 0.15%, 94.88%, 90.38%, and 0.99 (p-value <0.0001), respectively. The best performing segmentation-based classification model was UNet+Xception, which exhibited the accuracy, precision, recall, F1-score, and AUC of 97.45%, 97.46%, 97.45%, 97.43%, and 0.998 (p-value <0.0001), respectively. Our system outperformed existing methods for segmentation-based classification models. The mean improvement of the UNet+Xception system over all the remaining studies was 8.27%. Conclusion: The segmentation-based classification is a viable option as the hypothesis (error rate <5%) holds true and is thus adaptable in clinical practice
Attention-Based UNet Deep Learning Model for Plaque Segmentation in Carotid Ultrasound for Stroke Risk Stratification: An Artificial Intelligence Paradigm
No full textStroke and cardiovascular diseases (CVD) significantly affect the world population. The early detection of such events may prevent the burden of death and costly surgery. Conventional methods are neither automated nor clinically accurate. Artificial Intelligence-based methods of automatically detecting and predicting the severity of CVD and stroke in their early stages are of prime importance. This study proposes an attention-channel-based UNet deep learning (DL) model that identifies the carotid plaques in the internal carotid artery (ICA) and common carotid artery (CCA) images. Our experiments consist of 970 ICA images from the UK, 379 CCA images from diabetic Japanese patients, and 300 CCA images from post-menopausal women from Hong Kong. We combined both CCA images to form an integrated database of 679 images. A rotation transformation technique was applied to 679 CCA images, doubling the database for the experiments. The cross-validation K5 (80% training: 20% testing) protocol was applied for accuracy determination. The results of the Attention-UNet model are benchmarked against UNet, UNet++, and UNet3P models. Visual plaque segmentation showed improvement in the Attention-UNet results compared to the other three models. The correlation coefficient (CC) value for Attention-UNet is 0.96, compared to 0.93, 0.96, and 0.92 for UNet, UNet++, and UNet3P models. Similarly, the AUC value for Attention-UNet is 0.97, compared to 0.964, 0.966, and 0.965 for other models. Conclusively, the Attention-UNet model is beneficial in segmenting very bright and fuzzy plaque images that are hard to diagnose using other methods. Further, we present a multi-ethnic, multi-center, racial bias-free study of stroke risk assessment
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