Effect of hydroalcoholic extract of Myracrodruon urundeuva All. and Qualea grandiflora Mart. leaves on the viability and activity of microcosm biofilm and on enamel demineralization

Objectives: The aim of this study was to assess the effect of Myracrodruon urundeuva All. and Qualea grandiflora Mart. leaves hydroalcoholic extracts on viability and metabolism of a microcosm biofilm and on enamel demineralization prevention. Methodology: Microcosm biofilm was produced on bovine enamel using inoculum from pooled human saliva mixed with McBain saliva, under 0.2% sucrose exposure, for 14 days. The biofilm was daily-treated with the extracts for 1 min. At the end, it was analyzed with respect to viability by fluorescence, CFU counting and extracellular polysaccharides (phenol-sulphuric acid colorimetric assay) and lactic acid (enzymatic assay) production. The demineralization was measured by TMR. The data were compared using ANOVA or Kruskal-Wallis (p<0.05). Results: M. urundeuva All. at 100, 10 and 0.1 μg/mL and Q. grandiflora Mart. at 100 and 0.1 μg/mL reduced biofilm viability similarly to positive control (chlorhexidine) and significantly more than the negative-vehicle control (35% ethanol). M. urundeuva at 1000, 100 and 0.1 μg/mL were able to reduce both lactobacilli and mutans streptococci CFU counting, while Q. grandiflora (1000 and 1.0 μg/mL) significantly reduced mutans streptococci CFU counting. On the other hand, the natural extracts were unable to significantly reduce extracellular polysaccharides and lactic acid productions neither the development of enamel carious lesions.  Conclusions: The extracts showed antimicrobial properties on microcosm biofilm, however, they had no effect on biofilm metabolism and caries protection

The Effect of Toothpastes Containing Natural Extracts on Bacterial Species of a Microcosm Biofilm and on Enamel Caries Development.

This study investigated the effects of herbal toothpaste on bacterial counts and enamel demineralization. Thirty-six bovine enamel samples were exposed to a microcosm biofilm using human saliva and McBain saliva (0.2% sucrose) for 5 days at 37 °C and first incubated anaerobically, then aerobically-capnophilically. The following experimental toothpaste slurries (2 × 2 min/day) were applied: (1) Vochysia tucanorum (10 mg/g); (2) Myrcia bella (5 mg/g); (3) Matricaria chamomilla (80 mg/g); (4) Myrrha and propolis toothpaste (commercial); (5) fluoride (F) and triclosan (1450 ppm F), 0.3% triclosan and sorbitol (Colgate®, positive control); (6) placebo (negative control). The pH of the medium was measured, bacteria were analyzed using quantitative polymerase chain reaction, and enamel demineralization was quantified using transverse microradiography. The total bacterial count was reduced by toothpaste containing Myrcia bella, Matricaria chamomilla, fluoride, and triclosan (commercial) compared to the placebo. As far as assessable, Myrcia bella, Matricaria chamomilla, and Myrrha and propolis (commercial) inhibited the outgrowth of S. mutans, while Lactobacillus spp. were reduced/eliminated by all toothpastes except Vochysia tucanorum. Mineral loss and lesion depth were significantly reduced by all toothpastes (total: 1423.6 ± 115.2 vol% × μm; 57.3 ± 9.8 μm) compared to the placebo (2420.0 ± 626.0 vol% × μm; 108.9 ± 21.17 μm). Herbal toothpastes were able to reduce enamel demineralization

MICRObiota on BILIOpancreatic malignant diseases [MICROBILIO]: A systematic review

Introduction: The increase in the incidence of pancreatic and biliary cancers has attracted the search for methods of early detection of diseases and biomarkers. The authors propose to analyze new findings on the association between microbiota and Pancreatic Ductal Adenocarcinoma (PDAC) or Cholangiocarcinoma (CCA). Methods: This systematic review was carried out according to the items of Preferred Reports for Systematic Reviews and Protocol Meta-Analysis (PRISMA-P). This study was registered by the Prospective Register of Systematic Reviews (PROSPERO), identification code CRD42020192748 before the review was carried out. Articles were selected from the PUBMED, EMBASE, and Cochrane databases. Results: Most studies (86.67%) used 16s rRNA as a sequencing method. The main comorbidities found were diabetes mellitus, systemic arterial hypertension, and dyslipidemia. Many studies were limited by the small number of participants, but the biases were mostly low. There was very little concordance about the composition of the microbiome of different sites, for both case and control groups when compared to other studies' results. Bile sample analysis was the one with a greater agreement between studies, as three out of four studies found Escherichia in cases of CCA. Conclusion: There was great disagreement in the characterization of both the microbiota of cases and control groups. Studies are still scarce, making it difficult to adequately assess the data in this regard. It was not possible to specify any marker or to associate any genus of microbiota bacteria with PDAC or CCA

A comprehensive study on diesel oil bioremediation under microcosm conditions using a combined microbiological, enzymatic, mass spectrometry, and metabarcoding approach

This study aims at the application of a marine fungal consortium (Aspergillus sclerotiorum CRM 348 and Cryptococcus laurentii CRM 707) for the bioremediation of diesel oil-contaminated soil under microcosm conditions. The impact of biostimulation (BS) and/or bioaugmentation (BA) treatments on diesel-oil biodegradation, soil quality, and the structure of the microbial community were studied. The use of the fungal consortium together with nutrients (BA/BS) resulted in a TPH (Total Petroleum Hydrocarbon) degradation 42% higher than that obtained by natural attenuation (NA) within 120 days. For the same period, a 72 to 92% removal of short-chain alkanes (C12 to C19) was obtained by BA/BS, while only 3 to 65% removal was achieved by NA. BA/BS also showed high degradation efficiency of long-chain alkanes (C20 to C24) at 120 days, reaching 90 and 92% of degradation of icosane and heneicosane, respectively. In contrast, an increase in the levels of cyclosiloxanes (characterized as bacterial bioemulsifiers and biosurfactants) was observed in the soil treated by the consortium. Conversely, the NA presented a maximum of 37% of degradation of these alkane fractions. The 5-ringed PAH benzo(a)pyrene, was removed significantly better with the BA/BS treatment than with the NA (48 vs. 38 % of biodegradation, respectively). Metabarcoding analysis revealed that BA/BS caused a decrease in the soil microbial diversity with a concomitant increase in the abundance of specific microbial groups, including hydrocarbon-degrading (bacteria and fungi) and also an enhancement in soil microbial activity. Our results highlight the great potential of this consortium for soil treatment after diesel spills, as well as the relevance of the massive sequencing, enzymatic, microbiological and GC-HRMS analyses for a better understanding of diesel bioremediation.This research was financially supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (grant #2016/07957-7) and by Conselho Nacional de Desenvolvimento Tecnológico (CNPq) (grant #407986/2018-6).Peer reviewe

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2\ub75th percentile and 100 as the 97\ub75th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59\ub74 (IQR 35\ub74–67\ub73), ranging from a low of 11\ub76 (95% uncertainty interval 9\ub76–14\ub70) to a high of 84\ub79 (83\ub71–86\ub77). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of 'leaving no one behind', it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. METHODS: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator

Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data. Methods: We estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting. Findings: Globally, for females, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and haemoglobinopathies and haemolytic anaemias in both 1990 and 2017. For males, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and tuberculosis including latent tuberculosis infection in both 1990 and 2017. In terms of YLDs, low back pain, headache disorders, and dietary iron deficiency were the leading Level 3 causes of YLD counts in 1990, whereas low back pain, headache disorders, and depressive disorders were the leading causes in 2017 for both sexes combined. All-cause age-standardised YLD rates decreased by 3·9% (95% uncertainty interval [UI] 3·1-4·6) from 1990 to 2017; however, the all-age YLD rate increased by 7·2% (6·0-8·4) while the total sum of global YLDs increased from 562 million (421-723) to 853 million (642-1100). The increases for males and females were similar, with increases in all-age YLD rates of 7·9% (6·6-9·2) for males and 6·5% (5·4-7·7) for females. We found significant differences between males and females in terms of age-standardised prevalence estimates for multiple causes. The causes with the greatest relative differences between sexes in 2017 included substance use disorders (3018 cases [95% UI 2782-3252] per 100 000 in males vs 1400 [1279-1524] per 100 000 in females), transport injuries (3322 [3082-3583] vs 2336 [2154-2535]), and self-harm and interpersonal violence (3265 [2943-3630] vs 5643 [5057-6302]). Interpretation: Global all-cause age-standardised YLD rates have improved only slightly over a period spanning nearly three decades. However, the magnitude of the non-fatal disease burden has expanded globally, with increasing numbers of people who have a wide spectrum of conditions. A subset of conditions has remained globally pervasive since 1990, whereas other conditions have displayed more dynamic trends, with different ages, sexes, and geographies across the globe experiencing varying burdens and trends of health loss. This study emphasises how global improvements in premature mortality for select conditions have led to older populations with complex and potentially expensive diseases, yet also highlights global achievements in certain domains of disease and injury

Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. METHODS: The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries-Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODEm), to generate cause fractions and cause-specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised