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Dental plaque is one type of biofouling on the tooth surface that consists of a diverse population of microorganisms and extracellular matrix and causes oral diseases and even systematic diseases. Numerous studies have focused on preventing bacteria and proteins on tooth surfaces, especially with anti-biofouling coatings. Anti-biofouling coatings can be stable and sustainable over the long term on the tooth surface in the complex oral environment. In this review, numerous anti-biofouling coatings on the tooth surface and hydroxyapatite (as the main component of dental hard tissue) were summarized based on their mechanisms, which include three major strategies: antiprotein and antibacterial adhesion through chemical modification, contact killing through the modification of antimicrobial agents, and antibacterial agent release. The first strategy of coatings can resist the adsorption of proteins and bacteria. However, these coatings use passive strategies and cannot kill bacteria. The second strategy can interact with the cell membrane of bacteria to cause bacterial death. Due to the possibility of delivering a high antibacterial agent concentration locally, the third strategy is recommended and will be the trend of local drug use in dentistry in the future.

Additional file 1: Fig. S1. The percentage change in age-standardized incidence (A), death (B) and DALY (C) rates of AYA cancers for 204 countries and territories in both sexes from 1990 to 2019. Fig. S2. Global age-specific counts and rates of YLLs and YLDs per 100 000 population due to AYA cancers, 2019. Fig. S3. Global trends in absolute and proportional burden of incident cases, deaths, and DALYs by AYA cancer type and sex among 15- to 19-year-olds, 1990–2019. (A) Trends in the number of incident cases of AYA cancers by type. (B) Trends in composition of total incident cases of AYA cancers. (C) Trends in the number of deaths of AYA cancers by type. (D) Trends in composition of total deaths of AYA cancers. (E) Trends in the number of DALYs of AYA cancers by type. (F) Trends in composition of total DALYs of AYA cancers. AYA cancer types were sorted in decreasing magnitude f the total number of incident cases, deaths, or DALYs among 15- to 19-year-olds for both sexes combined from 1990 to 2019. Fig. S4. Global trends in absolute and proportional burden of incident cases, deaths, and DALYs by AYA cancer type and sex among 20- to 29-year-olds, 1990–2019. (A) Trends in the number of incident cases of AYA cancers by type. (B) Trends in composition of total incident cases of AYA cancers. (C) Trends in the number of deaths of AYA cancers by type. (D) Trends in composition of total deaths of AYA cancers. (E) Trends in the number of DALYs of AYA cancers by type. (F) Trends in composition of total DALYs of AYA cancers. AYA cancer types were sorted in decreasing magnitude of the total number of incident cases, deaths, or DALYs among 20- to 29-year-olds for both sexes combined from 1990 to 2019. Fig. S5. Global trends in absolute and proportional burden of incident cases, deaths, and DALYs by AYA cancer type and sex among 30- to 39-year-olds, 1990–2019. (A) Trends in the number of incident cases of AYA cancers by type. (B) Trends in composition of total incident cases of AYA cancers. (C) Trends in the number of deaths of AYA cancers by type. (D) Trends in composition of total deaths of AYA cancers. (E) Trends in the number of DALYs of AYA cancers by type. (F) Trends in composition of total DALYs of AYA cancers. AYA cancer types were sorted in decreasing magnitude of total number of incident cases, deaths, or DALYs among 30- to 39-year-olds for both sexes combined from 1990 to 2019. Fig. S6. The trend in age-standardized incidence rates of AYA cancers across 21 GBD regions by SDI for both sexes combined, 1990–2019. Coloured lines and symbols represent global and regional estimates of incidence rates. Each point on a line represents 1 year, starting from 1990 and ending in 2019. In all regions, the SDI has increased constantly over time. Therefore, points further to the right denote later years for a given region and higher SDI. The black line indicates locally weighted smoothing estimates of incidence rates based on SDI in all regions. The grey shading around the black line represents the 95% confidence interval of the estimated incidence rates. Fig. S7. The trend in age-standardized death rates of AYA cancers across 21 GBD regions by SDI for both sexes combined, 1990–2019. Coloured lines and symbols represent global and regional estimates of death rates. Each point on a line represents 1 year, starting from 1990 and ending in 2019. In all regions, the SDI has increased constantly over time. Therefore, points further to the right denote later years for a given region and higher SDI. The black line indicates locally weighted smoothing estimates of death rates based on SDI in all regions. The grey shading around the black line represents the 95% confidence interval of the estimated death rates. Fig. S8. The trend in age-standardized DALY rates of AYA cancers across 21 GBD regions by SDI for both sexes combined, 1990–2019. Coloured lines and symbols represent global and regional estimates of DALY rates. Each point on a line represents 1 year, starting from 1990 and ending in 2019. In all regions, the SDI has increased constantly over time. Therefore, points further to the right denote later years for a given region and higher SDI. The black line indicates locally weighted smoothing estimates of DALY rates based on SDI in all regions. The grey shading around the black line represents the 95% confidence interval of the estimated DALY rates. Table S1. Incident cases, deaths, and DALYs of AYA cancers among 15 to 19 years in 2019, and percentage change in age-specific rates from 1990 to 2019, by sex, SDI quintile, and cancer types. Absolute incidence, deaths, and DALYs represent AYA cancers among 15- to 19-year-olds (both sexes combined). Rates are reported per 100 000 person-years. Data in parentheses are 95% uncertainty intervals. DALY=disability-adjusted life-year. SDI=Socio-demographic Index. UI=uncertainty interval. Table S2. Incident cases, deaths, and DALYs of AYA cancers among 20- to 24-year-olds in 2019, and percentage change in age-specific rates from 1990 to 2019, by sex, SDI quintile, and cancer types. Absolute incidence, deaths, and DALYs represent AYA cancers among 20- to 24-year-olds (both sexes combined). Rates are reported per 100 000 person-years. Data in parentheses are 95% uncertainty intervals. DALY=disability-adjusted life-year. SDI=Socio-demographic Index. UI=uncertainty interval. Table S3. Incident cases, deaths, and DALYs of AYA cancers among 25- to 29-year-olds in 2019, and percentage change in age-specific rates from 1990 to 2019, by sex, SDI quintile, and cancer types. Absolute incidence, deaths, and DALYs represent AYA cancers among 25- to 29-year-olds (both sexes combined). Rates are reported per 100 000 person-years. Data in parentheses are 95% uncertainty intervals. DALY=disability-adjusted life-year. SDI=Socio-demographic Index. UI=uncertainty interval. Table S4. Incident cases, deaths, and DALYs of AYA cancers among 30- to 34-year-olds in 2019, and percentage change in age-specific rates from 1990 to 2019, by sex, SDI quintile, and cancer types. Absolute incidence, deaths, and DALYs represent AYA cancers among 30- to 34-year-olds (both sexes combined). Rates are reported per 100 000 person-years. Data in parentheses are 95% uncertainty intervals. DALY=disability-adjusted life-year. SDI=Socio-demographic Index. UI=uncertainty interval. Table S5. Incident cases, deaths, and DALYs of AYA cancers among 35- to 39-year-olds in 2019, and percentage change in age-specific rates from 1990 to 2019, by sex, SDI quintile, and cancer types. Absolute incidence, deaths, and DALYs represent AYA cancers among 35- to 39-year-olds (both sexes combined). Rates are reported per 100 000 person-years. Data in parentheses are 95% uncertainty intervals. DALY=disability-adjusted life-year. SDI=Socio-demographic Index. UI=uncertainty interval. Table S6. Global cause of disease-related death among AYAs in 2019, by GBD SDI quintile. Numbers of deaths are presented outside the parentheses. Numbers inside the parentheses represent percentage of the total deaths due to non-communicable diseases. Table S7. Absolute magnitude of changes in age-standardized rates of AYA cancers among GBD regions, from 1990 to 2019, by sex. GBD regions demonstrating temporal trends at odds with global trends are selected for reporting. The majority of GBD regions demonstrated increased AYA cancer incidence rate and decreased death and DALY rates. Therefore, GBD regions with decreased incidence rate and increased death and DALY rates are selected for reporting. Within selected GBD regions, top 10 cancer types leading to increased incidence rate, decreased death rate, and decreased DALY rate from 1990 to 2019 are reported. Negative value indicates lower age-standardized rates in 2019 compared to 1990. Table S8. AYA cancer ranking by the number of incident cases at the global level and according to SDI quintile, super-regions, regions, and countries, both sexes, 2019. Colour intensity and number ranking are assigned according to the rank of absolute number of incident cases of each cancer type among all cancer types. Dark red and number ranking of 1 indicate the highest rank and greatest absolute number of incident cases. Dark green and number ranking of 32 indicate the lowest rank and the smallest absolute number of incident cases. Table S9. AYA cancer ranking by the number of deaths at the global level and according to SDI quintile, super-regions, regions, and countries, both sexes, 2019. Colour intensity and number ranking are assigned according to the rank of absolute number of deaths of each cancer type among all cancer types. Dark red and number ranking of 1 indicate the highest rank and greatest absolute number of deaths. Dark green and number ranking of 32 indicate the lowest rank and the smallest absolute number of deaths. Table S10. AYA cancer ranking by the number of DALYs at the global level and according to SDI quintile, super-regions, regions, and countries, both sexes, 2019. Colour intensity and number ranking are assigned according to the rank of absolute number of DALYs of each cancer type among all cancer types. Dark red and number ranking of 1 indicate the highest rank and greatest absolute DALY burden. Dark green and number ranking of 32 indicate the lowest rank and the smallest absolute DALY burden. Table S11. Ranking of the number of incident cases of childhood cancer, AYA cancer, and cancers among the population aged

Li Zhou,1 Hai Ming Wong,1 Quan Li Li2 1Department of Paediatric Dentistry, Faculty of Dentistry, The University of Hong Kong, Hong Kong, SAR 999077, People’s Republic of China; 2Key Laboratory of Oral Diseases Research of Anhui Province, College and Hospital of Stomatology, Anhui Medical University, Hefei 230000, People’s Republic of ChinaCorrespondence: Hai Ming WongFaculty of Dentistry, The University of Hong Kong, 34 Hospital Road, Hong Kong, SAR 999077, People’s Republic of ChinaTel +852 28590261Fax +852 25593803Email wonghmg@hku.hkQuan Li LiCollege and Hospital of Stomatology, Anhui Medical University, No. 69, Meishan Road, Hefei 230000, People’s Republic of ChinaEmail ql-li@126.comAbstract: Dental plaque is one type of biofouling on the tooth surface that consists of a diverse population of microorganisms and extracellular matrix and causes oral diseases and even systematic diseases. Numerous studies have focused on preventing bacteria and proteins on tooth surfaces, especially with anti-biofouling coatings. Anti-biofouling coatings can be stable and sustainable over the long term on the tooth surface in the complex oral environment. In this review, numerous anti-biofouling coatings on the tooth surface and hydroxyapatite (as the main component of dental hard tissue) were summarized based on their mechanisms, which include three major strategies: antiprotein and antibacterial adhesion through chemical modification, contact killing through the modification of antimicrobial agents, and antibacterial agent release. The first strategy of coatings can resist the adsorption of proteins and bacteria. However, these coatings use passive strategies and cannot kill bacteria. The second strategy can interact with the cell membrane of bacteria to cause bacterial death. Due to the possibility of delivering a high antibacterial agent concentration locally, the third strategy is recommended and will be the trend of local drug use in dentistry in the future.Keywords: anti-biofouling coating, antibacterial agent, hydroxyapatite, tooth surface, binding

Additional file 1. STROBE Statement—checklist of items that should be included in reports of observational studies.

Additional file 1. Questionnaire.

Additional file 1: Table S1. The characteristics of participants.

With cancer survival rate climbing up over the past three decades, quality of life for cancer patients has become an issue of major concern. Oral health plays an important part in one’s overall quality of life. However, oral health status can be severely hampered by side effects of cancer therapies including surgery, chemotherapy, radiotherapy, and hematopoietic stem cell transplantation. Moreover, prevention and treatment of these complications are often overlooked in clinical practice. The present paper aims at drawing health care professionals’ attention to oral complications associated with cancer therapy by giving a comprehensive review. Brief comments on contemporary cancer therapies will be given first, followed by detailed description of oral complications associated with cancer therapy. Finally, a summary of preventive strategies and treatment options for common oral complications including oral mucositis, oral infections, xerostomia, and dysgeusia will be given.