Effect of Different Luting Cements on Fracture Resistance in Endodontically Treated Teeth

INTRODUCTION: The aim of the present study was to evaluate the effect of three types of luting cements used for post cementation on the fracture resistance of endodontically treated maxillary premolars, restored with resin composite. MATERIALS AND METHODS: One hundred intact single-rooted human maxillary premolars were randomly divided into 5 groups of 20 each. In groups 2-5, post spaces were prepared after root canal treatment and clinical crown reduction up to 1.5 mm above the CEJ. Teeth were divided in groups as follows: Group 1: intact teeth, Group 2: active prefabricated metallic posts (PMP), Group 3: PMP cemented with zinc phosphate luting cement, Group 4: PMP cemented with glass ionomer luting cement and Group 5: PMP cemented with resin luting cement. In groups 2-5 the teeth were restored with resin composite. Following thermocycling, the palatal cusp of each specimen was loaded to compression at an angle of 150˚ to its longitudinal axis at a strain rate of 2 mm/min until fracture occurred. Data were analyzed using one-way ANOVA and a post hoc Tukey test. Chi-square test was used for comparison of failure mode. RESULTS: There were significant differences in fracture resistance between the test groups (P<0.001). The differences between group 2 with groups 1, 4 and 5 were statistically significant (P<0.05); whereas there were no significant differences in fracture resistance between the two other groups (P>0.05). Furthermore, there were no significant differences in the mode of failure between the 5 groups (P>0.05).  CONCLUSION: Zinc phosphate, glass ionomer and resin luting cements showed similar behaviors and achieved fracture resistance comparable to intact teeth. However, the use of active post (without cement) adversely affected the fracture resistance of root canal treated teeth

Effects of fennel, asafetida and ginseng ethanolic extracts on growth and proliferation of mouse breast cancer 4T1 cell lines

Background: The 4T1 cells tumor growth and metastatic pattern in BALB/c mice very closely mimic human breast cancer. These herbal remedies used in traditional folk medicine have been the source of many medically beneficial drugs. The aim of the current study was to evaluate the anti-proliferative activity of the asafoetida, ginseng and fennel ethanolic extracts on mouse breast cancer 4T1 cell-line invitro.Method: in this experimental study, Asafoetida, gensing and fennel were extracted; 4T1 mouse mammary tumor cell line were cultured in 48-well flat bottom plate in density of 50x103 per well in 100 µl RPMI1640 medium then different dilutions of each extract (25 , 50, 100, 200, 500, and 2000 μg/ml) were added to cell culture. Cells then were incubated at 37 oC for 24 hours. After 24 h, cell Proliferation was determined by the BRDU assay . dataset of experiments were collected and analysed with SPSS19 software. Significant level of Data was Examined with one-way ANOVA method and

Effect of three prophylaxis methods on surface roughness of giomer

Objectives: Plaque and stains are removed by prophylaxis methods from tooth surfaces. Since prophylaxis methods can have a detrimental effect on the surface finish of restorations, the aim of this in vitro study was to investigate the effect of three prophylaxis methods, including pumice with rubber cup, pumice with brush, and air-powder polishing device (APD) on the surface roughness of giomer. Study design: Sixty four cylindrical giomer (Beautifil II, Shofu) samples with a diameter of 6 mm and a height of 2 mm were used. Subsequent to a 3-month period of storage in distilled water at 37ºC, the samples were randomly divided into four groups of 16. In group 1 (control), no prophylaxis procedure was carried out. In groups 2 to 4 the samples were exposed to pumice with rubber cup, pumice with brush, and APD prophylaxis methods, respectively. The surface roughness of the samples was measured using a profilometer and the effect of different prophylaxis methods on surface topography was characterized by atomic force microscopy (AFM). All data were analyzed by one-way ANOVA and Duncan?s post hoc test at a significance level of P < 0.05. Results: There were statistically significant differences in surface roughness among the groups (P < 0.0005). Furthermore, in pairwise comparisons there were statistically significant differences between all the groups (P < 0.05). The roughest surfaces, in descending order, were observed with the use of APD, pumice with brush, and pumice with rubber cup. Conclusions: The use of different prophylaxis methods resulted in an increased surface roughness of giomer compared with the control group. APD prophylaxis exerted the most detrimental effects on the surface of giomer

Effect of pre-heating on the mechanical properties of silorane-based and methacrylate-based composites

Background: The use of composites in dental restoration has been commonly criticized, due to their underwhelming mechanical properties. This problem may be solved partially by preheating. The present research aims to determine the effect of preheating on the mechanical properties of two different classes of composites. Material and Methods: A Silorane-based (Silorane) and a Methacrylate-based (Z250) composite were preheated to different temperatures (25, 37, and 68 °C) and afterwards were tested with the appropriate devices for each testing protocol. The materialâ s flexural strength, elastic modulus, and Vickers microhardness were evaluated. Two-way ANOVA, and Tukeyâ s post hoc were used to analyze the data. Results: Microhardness and elastic modulus increased with preheating, while flexural strength values did not increase significantly with preheating. Furthermore the methacrylate-based composite (Z250) showed higher values compared to the Silorane-based composite (Silorane) in all the tested properties. Conclusions: Preheating Silorane enhances the compositeâ s microhardness and elastic modulus but does not affect its flexural strength. On the other hand, preheating Z250 increases its microhardness but does not change its flexural strength or elastic modulus. In addition, the Z250 composite shows higher microhardness and flexural strength than Silorane, but the elastic modulus values with preheating are similar. Therefore Z250 seems to have better mechanical properties making it the better choice in a clinical situation

Shear bond strengths of composite resin and giomer to mineral trioxide aggregate at different time intervals

The efficacy of the bond between the restorative materials and the pulp capping materials has an important role in the success of vital pulp therapy. Therefore, the aim of this study was to evaluate the shear bond strength of composite resin and giomer to MTA at different time intervals after mixing of MTA. Ninety cylindrical MTA samples were prepared and assigned to two groups (n=45) based on the restorative materials used (composite resin or giomer). Each group was subdivided into 3 subgroups (n=15) based on the evaluation intervals (immediately, 2.45 hours and 3 days after mixing MTA). After the bonding procedures, the shear bond strengths of the samples were measured in MPa at a strain rate of 0.5 mm/min. Data were analyzed with repeated-measures ANOVA, post hoc tests and t-test (P<0.05). Bond strength of composite resin was minimum at baseline but it increased significantly 2.45 hours after mixing MTA (P=0.002), with no significant changes in bond strength up to three days (P=0.08). Bond strength of giomer did not exhibit any significant changes from baseline to 2.45 hours after mixing MTA (P=078); however, at 3 days it reached a minimum (P=0.000). In addition, the means of bond strength of composite resin 2.45 hours and 3 days after mixing were significantly higher than those of giomer (P=0.001 and P=0.000, respectively). Bond strengths of composite resin 2.45 hours and also 3 days after mixing were significantly higher than those of giomer. In addition, the shear bond strength of giomer decreased over time; however, the shear bond strength of composite resin increased

Effect of 10% sodium ascorbate on Streptococcus mutans adherence to bleached bovine enamel surface

Sodium ascorbate has been suggested to modify bleaching agents’ side effects especially on composite resin bonding to dental hard tissues. The aim of the present study was to evaluate the effect of 10% sodium ascorbate on Streptococcus mutans adherence to bleached enamel surfaces. Sixty enamel slabs from bovine incisors were used. After sterilization of the intact enamel surfaces with UV light, the specimens were randomly divided into the following treatment groups: (1) immersion in normal saline containing 2%NaN3; (2) bleaching of enamel surfaces with 10% carbamide peroxide; (3) bleaching of enamel surfaces with 10% carbamide peroxide followed by 10% sodium ascorbate treatment. Adherence of S. mutans to enamel surfaces was determined bacteriologically. Data was analyzed using one-way ANOVA and post hoc Tukey tests (P &lt; 0.05).10% sodium ascorbate after bleaching (Group 3) caused a significant increase in surface adherence of S. mutans compared to groups 1 and 2 (P &lt; 0.001). Because of bacterial adherence subsequent to use of sodium ascorbate to bleached enamel caries risk may be increased.Keywords: Sodium ascorbate, Streptococcus mutans, carbamide peroxideAfrican Journal of Biotechnology Vol. 9(33), pp. 5419-5422, 16 August, 201

The effect of pre-heating on monomer elution from bulk-fill resin composites

The present study was aimed to evaluate the effect of pre-heating of bulk -fill resin composites on monomer elution from them. Three different types of resin composites were used including Tetric N-Ceram Bulk Fill, X-tra Fill and X-tra Base. 10 cylindrical samples were prepared from each resin composites. Before light curing, 5 samples were pre-heated until reaching 68?C, then 5 other samples were polymerized at room temperature. After 24 hours, release of UDMA, TEGDMA and BIS-GMA monomers were measured by High-Performance Liquid Chromatography analysis. Data analysis was performed by two-way ANOVA test, Games-Howell and Sidak post hoc tests. Pre-heating did not have any statistically significant effect on the mean values of UDMA, TEGDMA and Bis-GMA elution (p>0.05). The greatest amount of released Bis-GMA and UDMA was obtained from Tetric N-Ceram Bulk-fill composite. The greatest amount of released TEGDMA was obtained from X-tra Fill composite. X-tra Base composite showed the lowest amount of monomer release (P<0.001). Pre-heating did not have any effect on monomer release from bulk-fill resin composites. Moreover, the amount and the type of monomers released from various bulk-fill resin composites were not similar

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic