Cytotoxic Effects Of Zoledronic Acid On Human Epithelial Cells And Gingival Fibroblasts

Bisphosphonate-induced osteonecrosis has been related to the cytotoxicity of these drugs on oral mucosa cells. A previous study showed that 5 μM of zoledronic acid (ZA), a nitrogen-containing bisphosphonate, is the highest concentration of this drug found in the oral cavity of patients under treatment. Therefore, in order to simulate an osteonecrosis clinical condition, the aim of this study was to evaluate the highest concentration of ZA applied on human epithelial cells (HaCaT) and gingival fibroblasts. For this purpose, cells (3x104 cells/cm2) were seeded in wells for 48 h using complete culture medium (cDMEM). After 48 h incubation, the cDMEM was replaced by fresh serum-free culture medium (DMEM-FBS) in which the cells were maintained for additional 24 h. Then, 5 μM ZA were added to the DMEM-FBS and the cells incubated in contact with the drug for 48 h. After this period, the number of viable cells (trypan blue), cell viability (MTT assay), total protein (TP) production and cell morphology (SEM analysis) were assessed. Data were analyzed statistically by Mann-Whitney, ANOVA and Tukey's test (α=0.05). ZA caused a significant reduction in the number of viable cells and decreased the metabolic activity of both cell lines. However, decrease of TP production occurred only in the epithelial cell cultures. Morphological alterations were observed in both cell types treated with ZA. In conclusion, ZA (5 μM) was cytotoxic to human epithelial cells and gingival fibroblast cultures, which could be associated, clinically, with the development of bisphosphonateinduced osteonecrosis.246551558Civitelli, R., Napoli, N., Armamento-Villareal, R., Use of intravenous bisphosphonates in osteoporosis (2007) Curr Osteoporos Rep, 5, pp. 8-13Cohen, S.B., An update on bisphosphonates (2004) Curr Rheumatol Rep, 6, pp. 59-65Rogers, M.J., Watts, D.J., Russel, R.G., Overview of bisphosphonates (1997) Cancer, 80, pp. 1652-1660Rogers, M.J., Gordon, S., Benford, H.L., Coxon, F.P., Luckman, S.P., Monkkonen, J., Cellular and molecular mechanisms of action of bisphosphonates (2000) Cancer Supl, 88, pp. 2961-2978Lawson, M.A., Xia, Z., Barnett, B.L., Triffitt, J.T., Phipps, R.J., Dunford, J.E., Differences between bisphosphonates in binding affinities for hydroxyapatite (2010) J Biomed Mater Res Part B: Appl Biomater, 92, pp. 149-155Allen, M.R., Burr, D.B., The pathogenesis of bisphosphonate-related osteonecrosis of the jaw: So many hypotheses, so few data (2009) J Oral Maxillofac Surg, 67, pp. 61-70Otto, S., Pautke, C., Opelz, C., Wesphal, I., Drosse, I., Swager, J., Osteonecrosis of the jaw: Effects of bisphosphonate type, local concentration, and acidic milieu on the pathomechanism (2010) J Oral Maxillofac Surg, 68, pp. 2837-2845Reid, I.R., Booland, M.J., Is bisphosphonate-associated osteonecrosis of the jaw caused by soft tissue toxicity? (2007) Bone, 41, pp. 318-320Scheper, M.A., Badros, A., Chausparat, R., Cullen, K.J., Meiller, T.F., Effect of zoledronic acid on oral fibroblasts and epithelial cells: A potential mechanism of bisphosphonate-associated osteonecrosis (2009) Br J Haematol, 144, pp. 667-676Scheper, M.A., Badros, A., Salama, A.R., Wartburton, G., Cullen, K.J., Weikel, D.S., A novel bioassay model to determine clinically significant bisphosphonate levels (2009) Support Care Cancer, 17, pp. 1553-1557Ruggiero, S.L., Mehrotra, B., Rosenberg, T.J., Engroff, S.L., Osteonecrosis of the jaws associated with the use of bisphosphonates: A review of 63 cases (2004) J Oral Maxillofac Surg, 62, pp. 527-534Walter, C., Klein, M.O., Pabst, A., Al-Nawas, B., Duscher, H., Ziebart, T., Influence of bisphosphonates on endothelial cells, fibroblasts, and osteogenic cells (2010) Clin Oral Investig, 14, pp. 35-41Kumar, S.K.S., Gorur, A., Schaauddin, C., Shuler, C.F., Costerton, J.W., Sedghizadeh, P.P., The role of microbial biofilms in osteonecrosis of the jaw associated with bisphosphonate therapy (2010) Curr Osteoporos Rep, 8, pp. 40-48Aas, J.A., Paster, B.J., Stokes, L.N., Olsen, I., Dewhirst, F.E., Defining the normal bacterial flora of the oral cavity (2005) J Clin Microbiol, 43, pp. 5721-5732Basso, F.G., Pansani, T.N., Turrioni, A.P.S., Bagnato, V.S., Hebling, J., de Souza Costa, C.A., In vitro wound healing improvement by low-level laser therapy application in cultured gingival fibroblasts (2012) Int J Dent, , [Epub ahead of print. DOI: 10.1155/2012/719452]Wiegand, C., Hipler, U., Methods for the measurement of cell and tissue compatibility including tissue regeneration process (2008) GMS Krankenhhyg Interdiszip, 3, pp. 1863-5245Basso, F.G., Oliveira, C.F., Kurachi, C., Hebling, J., de Souza Costa, C.A., Biostimulatory effect of low-level laser therapy on keratinocytes in vitro (2013) Lasers Med Sci, 28, pp. 367-374De Souza Costa, C.A., Duarte, P.T., de Souza, P.P., Giro, E.M., Hebling, J., Cytotoxic effects and pulpal response caused by a mineral trioxide aggregate formulation and calcium hydroxide (2008) Am J Dent, 21, pp. 255-261Oliveira, C.F., Basso, F.G., Lins, E.C.C., Kurachi, C., Hebling, J., Bagnato, V.S., Increased viability of odontoblast-like cells subjected to low-level laser irradiation (2010) Laser Phys, 20, pp. 1659-1666Read, S.M., Northcote, D.H., Minimization of variation in the response to different proteins of the Coomassie blue G dye-binding assay for protein (1981) Anal Biochem, 116, pp. 53-64Oliveira, C.F., Basso, F.G., Lins, E.C., Kurachi, C., Hebling, J., Bagnato, V.S., In vitro effect of low-level laser on odontoblast-like cells (2011) Laser Phys Lett, 8, pp. 155-163Simon, M.J.K., Niehoff, P., Kimming, B., Wiltfang, J., Açil, Y., Expression profile and synthesis of different collagen types I, II III and V of human gingival fibroblasts, osteoblasts, ans SaOs-2 cells after bisphosphonate treatment (2010) Clin Oral Investig, 14, pp. 51-58Migliorati, C.A., Siegel, M.A., Elting, L.S., Bisphosphonate-associated osteonecrosis: A long-term complication of bisphosphonate treatment (2006) Lancet Oncol, 7, pp. 508-514Werner, S., Krieg, T., Smola, H., Keratinocyte-fibroblast interactions in wound healing (2007) J Investigative Dermatol, 127, pp. 998-1008Ravosa, M.J., Ning, J., Liu, Y., Stack, M.S., Bisphosphonate effects on the behavior of oral epithelial cells and oral fibroblasts (2011) Arch Oral Biol, 56, pp. 491-49

In Vitro Effect Of Low-level Laser Therapy On Typical Oral Microbial Biofilms

The aim of this study was to evaluate the effect of specific parameters of low-level laser therapy (LLLT) on biofilms formed by Streptococcus mutans, Candida albicans or an association of both species. Single and dual-species biofilms - SSB and DSB - were exposed to laser doses of 5, 10 or 20 J/cm 2 from a near infrared InGaAsP diode laser prototype (LASERTable; 780 ± 3 nm, 0.04 W). After irradiation, the analysis of biobilm viability (MTT assay), biofilm growth (cfu/mL) and cell morphology (SEM) showed that LLLT reduced cell viability as well as the growth of biofilms. The response of S. mutans (SSB) to irradiation was similar for all laser doses and the biofilm growth was dose dependent. However, when associated with C. albicans (DSB), S. mutans was resistant to LLLT. For C. albicans, the association with S. mutans (DSB) caused a significant decrease in biofilm growth in a dose-dependent fashion. The morphology of the microorganisms in the SSB was not altered by LLLT, while the association of microbial species (DSB) promoted a reduction in the formation of C. albicans hyphae. LLLT had an inhibitory effect on the microorganisms, and this capacity can be altered according to the interactions between different microbial species.226502510Marques, M.M., Pereira, A.N., Fujihara, N.A., Nogueira, F.N., Eduardo, C.P., Effect of low-power laser irradiation on protein synthesis and ultrastructure of human gingival fibroblasts (2004) Lasers Surg Med, 34, pp. 260-265Damante, C.A., de Micheli, G., Miyagi, S.P.H., Feist, I.S., Marques, M.M., Effect of laser phototherapy on the release of fibroblast growth factors by human gingival fibroblasts (2009) Lasers Med Sci, 24, pp. 885-891Moritz, A., Schoop, U., Goharkhay, K., Schauer, P., Doertbudak, O., Wernisch, J., Treatment of periodontal pockets with a diode laser (1998) Lasers Surg Med, 22, pp. 302-311Nussbaum, E.L., Lilge, L., Mazzulli, T., Effects of 630-, 660-, 810-, and 905-nm laser irradiation delivering radiant exposure of 1-50 J/cm 2 on three species of bacteria in vitro (2002) J Clin Laser Med Surg, 20, pp. 325-333Nussbaum, E.L., Lilge, L., Mazzulli, T., Effects of low-level laser therapy (LLLT) of 810 nm upon in vitro growth of bacteria: Relevance of irradiance and radiant exposure (2003) J Clin Laser Med Surg, 21, pp. 283-290Lino, M.D.M.C., Carvalho, F.B., Oliveira, L.R., Magalhães, E.B., Pinheiro, A.L.B., Ramalho, L.M.P., Laser phototherapy as a treatment for radiotherapy-induced oral mucositis (2011) Braz Dent J, 22, pp. 162-165Maver-Biscanin, M., Mravak-Stipetic, M., Jerolimov, V., Biscanin, A., Fungicidal effect of diode laser irradiation in patients with denture stomatitis (2004) Lasers Surg Med, 35, pp. 259-262Dworkin, M., Endogenous photosensitization in a carotinoidless mutant of Rhodopseudomonas speroides (1958) J Gen Physiol, 43, pp. 1099-1112Rosenberg, B., Kemeny, G., Switzer, R.C., Hamilton, T.C., Quantitative evidence for protein denaturation as the cause of thermal death (1971) Nature, 232, pp. 471-473Krespi, Y.P., Kizhner, V., Nistico, L., Hall-Stoodley, L., Stoodley, P., Laser disruption and killing of methicillin-resistant Staphylococcus aureus biofilms (2011) Am J Otolaryngol, 32, pp. 198-202Shirtliff, M.E., Peters, B.M., Jabra-Rizk, M.A., Cross-kingdom interactions: Candida albicans and bacteria (2009) FEMS Microbiol Lett, 299, pp. 1-8Pereira-Cenci, T., Deng, D.M., Kraneveld, E.A., Manders, E.M.M., del Bel, C.A.A., ten Cate, J.M., The effect of Streptococcus mutans and Candida glabrata on Candida albicans biofilms formed on different surfaces (2008) Arch Oral Biol, 53, pp. 755-764Marsh, P.D., Microbial ecology of dental plaque and its significance in health and disease (1994) Adv Dent Res, 8, pp. 263-271Karkowska-Kuleta, J., Rapala-Kozik, M., Kozik, A., Fungi pathogenic to humans: Molecular bases of virulence of Candida albicans, Cryptococcus neoformans and Aspergillus fumigatus (2009) Acta Biochim Pol, 56, pp. 211-224Thein, Z.M., Samaranayake, Y.H., Samaranayake, L.P., Dietary sugars, serum and the biocide chlorhexidine digluconate modify the population and structural dynamics of mixed Candida albicans and Escherichia coli biofilms (2007) APMIS, 115, pp. 1241-1251Kwieciński, J., Eick, S., Wójcik, K., Effects of tea tre (Melaleuca alternifolia) oil on Staphylococcus aureus in biofilms and stationary phase (2009) Int J Antimicrob Agents, 33, pp. 343-347Wang, Z.C., Fan, L.Y., Jiang, J.Q., Cai, W., Ding, Y., Study on the counting of Streptococcus mutans, Streptococcus sanguis, Haemophilus actinomycetemcomitans by methyl thiazolyl tetrazolium colorimetric method (2010) Hua Xi Kou Qiang Yi Xue Za Zhi, 28, pp. 306-310Nguyen, P.T.M., Abranches, J., Phan, T., Marquis, R.E., Repressed respiration of oral Streptococci grow in biofilms (2002) Curr Microbiol, 44, pp. 262-266Singleton, S., Treloar, R., Warren, P., Watson, G.K., Hodgson, R., Allison, C., Methods for microscopic characterization of oral biofilms: Analysis of colonization, microstructure, and molecular transport phenomena (1997) Adv Dent Res, 11, pp. 133-149Jarosz, L.M., Deng, D.M., van der Mei, H.C., Crielaard, W., Krom, B.P., Streptococcus mutans competence-stimulating peptide inhibits Candida albicans hypha formation (2009) Eukaryot Cell, 8, pp. 1658-1664Dortbudak, O., Haas, R., Bernhart, T., Mailath-Pokorny, G., Lethal photosensitization for decontamination of implant surface in the treatment of peri-implantitis (2001) Clin Oral Implant Res, 12, pp. 104-10

Search for flavour-changing neutral currents in processes with one top quark and a photon using 81 fb⁻¹ of pp collisions at \sqrts = 13 TeV with the ATLAS experiment

A search for flavour-changing neutral current (FCNC) events via the coupling of a top quark, a photon, and an up or charm quark is presented using 81 fb−1 of proton–proton collision data taken at a centre-of-mass energy of 13 TeV with the ATLAS detector at the LHC. Events with a photon, an electron or muon, a b-tagged jet, and missing transverse momentum are selected. A neural network based on kinematic variables differentiates between events from signal and background processes. The data are consistent with the background-only hypothesis, and limits are set on the strength of the tqγ coupling in an effective field theory. These are also interpreted as 95% CL upper limits on the cross section for FCNC tγ production via a left-handed (right-handed) tuγ coupling of 36 fb (78 fb) and on the branching ratio for t→γu of 2.8×10−5 (6.1×10−5). In addition, they are interpreted as 95% CL upper limits on the cross section for FCNC tγ production via a left-handed (right-handed) tcγ coupling of 40 fb (33 fb) and on the branching ratio for t→γc of 22×10−5 (18×10−5). © 2019 The Author(s

Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Accurate assessments of current and future fertility—including overall trends and changing population age structures across countries and regions—are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios. Methods: To estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10–54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values—a metric assessing gain in forecasting accuracy—by comparing predicted versus observed ASFRs from the past 15 years (2007–21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline. Findings: During the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63–5·06) to 2·23 (2·09–2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137–147), declining to 129 million (121–138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1—canonically considered replacement-level fertility—in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7–29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59–2·08) in 2050 and 1·59 (1·25–1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6–43·1) in 2050 and 54·3% (47·1–59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions—decreasing, for example, in south Asia from 24·8% (23·7–25·8) in 2021 to 16·7% (14·3–19·1) in 2050 and 7·1% (4·4–10·1) in 2100—but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40–1·92) in 2050 and 1·62 (1·35–1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction. Interpretation: Fertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world. Funding: Bill & Melinda Gates Foundation

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. Funding: Bill & Melinda Gates Foundation

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. Methods: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. Findings: The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. Interpretation: Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. Funding: Bill & Melinda Gates Foundation

Measurement of the top-quark mass using a leptonic invariant mass in pp collisions at s√ = 13 TeV with the ATLAS detector

A measurement of the top-quark mass (mt) in the tt¯ → lepton + jets channel is presented, with an experimental technique which exploits semileptonic decays of b-hadrons produced in the top-quark decay chain. The distribution of the invariant mass mℓμ of the lepton, ℓ (with ℓ = e, μ), from the W-boson decay and the muon, μ, originating from the b-hadron decay is reconstructed, and a binned-template profile likelihood fit is performed to extract mt. The measurement is based on data corresponding to an integrated luminosity of 36.1 fb−1 of s√ = 13 TeV pp collisions provided by the Large Hadron Collider and recorded by the ATLAS detector. The measured value of the top-quark mass is mt = 174.41 ± 0.39 (stat.) ± 0.66 (syst.) ± 0.25 (recoil) GeV, where the third uncertainty arises from changing the PYTHIA8 parton shower gluon-recoil scheme, used in top-quark decays, to a recently developed setup

Effect Of Sulfur Oxidation On The Transmission Mechanism Of4jhh Nmr Coupling Constants In 1,3-dithiane

Long-range 4JHH couplings in 1,3-dithiane derivatives are rationalized in terms of the effects of hyperconjugative interactions involving the S=0 group. Theoretical and experimental studies of 4JHH couplings were carried out in 1,3-dithiane-l-oxide (2), cw-l,3-dithiane-l,3-dioxide (3), l,3-dithiane-l,l,3-trioxide (4), and 1,3-dithiane-1,1,3,3-tetraoxide (5) compounds. Hyperconjugative interactions were studied with the natural bond orbital, NBO, method. Hyperconjugative interactions involving the LP O, oxygen lone pair and σ*C2-S1 and σ*S1-C6 antibonding orbitals yield an increase of 4JHeq-Heq couplings. Long-range 4JHax-Hax couplings were also observed between hydrogen atoms in axial orientation, which are rationalized as originating in hyperconjugative interactions involving the bonding σC6-h axand antibonding σ*S=O orbitals. 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