Insectivorous birds and bats outperform ants in the top-down regulation of arthropods across strata of a Japanese temperate forest.

Birds, bats and ants are recognised as significant arthropod predators. However, empirical studies reveal inconsistent trends in their relative roles in top-down control across strata. Here, we describe the differences between forest strata in the separate effects of birds, bats and ants on arthropod densities and their cascading effects on plant damage. We implemented a factorial design to exclude vertebrates and ants in both the canopy and understorey. Additionally, we separately excluded birds and bats from the understorey using diurnal and nocturnal exclosures. At the end of the experiments, we collected all arthropods and assessed herbivory damage. Arthropods responded similarly to predator exclusion across forest strata, with a density increase of 81% on trees without vertebrates and 53% without both vertebrates and ants. Additionally, bird exclusion alone led to an 89% increase in arthropod density, while bat exclusion resulted in a 63% increase. Herbivory increased by 42% when vertebrates were excluded and by 35% when both vertebrates and ants were excluded. Bird exclusion alone increased herbivory damage by 28%, while the exclusion of bats showed a detectable but non-significant increase (by 22%). In contrast, ant exclusion had no significant effect on arthropod density or herbivory damage across strata. Our results reveal that the effects of birds and bats on arthropod density and herbivory damage are similar between the forest canopy and understorey in this temperate forest. In addition, ants were not found to be significant predators in our system. Furthermore, birds, bats and ants appeared to exhibit antagonistic relationships in influencing arthropod density. These findings highlight, unprecedentedly, the equal importance of birds and bats in maintaining ecological balance across different strata of a temperate forest.

Meta-analysis of the Microbial Diversity Cultured in Bioreactors Simulating the Gut Microbiome.

Understanding the intricate ecological interactions within the gut microbiome and unravelling its impact on human health is a challenging task. Bioreactors are valuable tools that have contributed to our understanding of gut microbial ecology. However, there is a lack of studies describing and comparing the microbial diversity cultivated in these models. This knowledge is crucial for refining current models to reflect the gastrointestinal microbiome accurately. In this study, we analysed the microbial diversity of 1512 samples from 18 studies available in public repositories that employed cultures performed in batches and various bioreactor models to cultivate faecal microbiota. Community structure comparison between samples using t-distributed stochastic neighbour embedding and the Hellinger distance revealed a high variation between projects. The main driver of these differences was the inter-individual variation between the donor faecal inocula. Moreover, there was no overlap in the structure of the microbial communities between studies using the same bioreactor platform. In addition, α-diversity analysis using Hill numbers showed that highly complex bioreactors did not exhibit higher diversities than simpler designs. However, analyses of five projects in which the samples from the faecal inoculum were also provided revealed an amplicon sequence variants enrichment in bioreactors compared to the inoculum. Finally, a comparative analysis of the taxonomy of the families detected in the projects and the GMRepo database revealed bacterial families exclusively found in the bioreactor models. These findings highlight the potential of bioreactors to enrich low-abundance microorganisms from faecal samples, contributing to uncovering the gut microbial "dark matter".

A complex relation between levels of adult hippocampal neurogenesis and expression of the immature neuron marker doublecortin.

We investigated the mechanisms underlying the effects of the antidepressant fluoxetine on behavior and adult hippocampal neurogenesis (AHN). After confirming our earlier report that the signaling molecule ß-arrestin-2 (ß-Arr2) is required for the antidepressant-like effects of fluoxetine, we found that the effects of fluoxetine on proliferation of neural progenitors and survival of adult-born granule cells are absent in the ß-Arr2 knockout (KO) mice. To our surprise, fluoxetine induced a dramatic upregulation of the number of doublecortin (DCX)-expressing cells in the ß-Arr2 KO mice, indicating that this marker can be increased even though AHN is not. We discovered two other conditions where a complex relationship occurs between the number of DCX-expressing cells compared to levels of AHN: a chronic antidepressant model where DCX is upregulated and an inflammation model where DCX is downregulated. We concluded that assessing the number of DCX-expressing cells alone to quantify levels of AHN can be complex and that caution should be applied when label retention techniques are unavailable.

Indirect maternal effects via nest microbiome composition drive gut colonization in altricial chicks.

Gut microbial communities are complex and heterogeneous and play critical roles for animal hosts. Early-life disruptions to microbiome establishment can negatively impact host fitness and development. However, the consequences of such early-life disruptions remain unknown in wild birds. To help fill this gap, we investigated the effect of continuous early-life gut microbiome disruptions on the establishment and development of gut communities in wild Great tit (Parus major) and Blue tit (Cyanistes caeruleus) nestlings by applying antibiotics and probiotics. Treatment neither affected nestling growth nor their gut microbiome composition. Independent of treatment, nestling gut microbiomes of both species grouped by brood, which shared the highest numbers of bacterial taxa with both nest environment and their mother. Although fathers showed different gut communities than their nestlings and nests, they still contributed to structuring chick microbiomes. Lastly, we observed that the distance between nests increased inter-brood microbiome dissimilarity, but only in Great tits, indicating that species-specific foraging behaviour and/or microhabitat influence gut microbiomes. Overall, the strong maternal effect, driven by continuous recolonization from the nest environment and vertical transfer of microbes during feeding, appears to provide resilience towards early-life disruptions in nestling gut microbiomes.

Are the Relevant Risk Factors Being Adequately Captured in Empirical Studies of Smoking Initiation? A Machine Learning Analysis Based on the Population Assessment of Tobacco and Health Study.

INTRODUCTION: Cigarette smoking continues to pose a threat to public health. Identifying individual risk factors for smoking initiation is essential to further mitigate this epidemic. To the best of our knowledge, no study today has used machine learning (ML) techniques to automatically uncover informative predictors of smoking onset among adults using the Population Assessment of Tobacco and Health (PATH) study. AIMS AND METHODS: In this work, we employed random forest paired with Recursive Feature Elimination to identify relevant PATH variables that predict smoking initiation among adults who have never smoked at baseline between two consecutive PATH waves. We included all potentially informative baseline variables in wave 1 (wave 4) to predict past 30-day smoking status in wave 2 (wave 5). Using the first and most recent pairs of PATH waves was found sufficient to identify the key risk factors of smoking initiation and test their robustness over time. The eXtreme Gradient Boosting method was employed to test the quality of these selected variables. RESULTS: As a result, classification models suggested about 60 informative PATH variables among many candidate variables in each baseline wave. With these selected predictors, the resulting models have a high discriminatory power with the area under the specificity-sensitivity curves of around 80%. We examined the chosen variables and discovered important features. Across the considered waves, two factors, (1) BMI, and (2) dental and oral health status, robustly appeared as important predictors of smoking initiation, besides other well-established predictors. CONCLUSIONS: Our work demonstrates that ML methods are useful to predict smoking initiation with high accuracy, identifying novel smoking initiation predictors, and to enhance our understanding of tobacco use behaviors. IMPLICATIONS: Understanding individual risk factors for smoking initiation is essential to prevent smoking initiation. With this methodology, a set of the most informative predictors of smoking onset in the PATH data were identified. Besides reconfirming well-known risk factors, the findings suggested additional predictors of smoking initiation that have been overlooked in previous work. More studies that focus on the newly discovered factors (BMI and dental and oral health status,) are needed to confirm their predictive power against the onset of smoking as well as determine the underlying mechanisms.

The evolution of age-specific smoking cessation rates in the United States from 2009 to 2017: a Kalman filter based approach.

BACKGROUND: Tracking the US smoking cessation rate over time is of great interest to tobacco control researchers and policymakers since smoking cessation behaviors have a major effect on the public's health. Recent studies have employed dynamic models to estimate the US cessation rate through observed smoking prevalence. However, none of those studies has provided annual estimates of the cessation rate by age group. Hence, the primary objective of this study is to estimate annual smoking cessation rates specific to different age groups in the US from 2009 to 2017. METHODS: We employed a Kalman filter approach to investigate the annual evolution of age-group-specific cessation rates, unknown parameters of a mathematical model of smoking prevalence, during the 2009-2017 period using data from the 2009-2018 National Health Interview Surveys. We focused on cessation rates in the 25-44, 45-64 and 65 + age groups. RESULTS: The findings show that cessation rates followed a consistent u-shaped curve over time with respect to age (i.e., higher among the 25-44 and 65 + age groups, and lower among 45-64-year-olds). Over the course of the study, the cessation rates in the 25-44 and 65 + age groups remained nearly unchanged around 4.5% and 5.6%, respectively. However, the rate in the 45-64 age group exhibited a substantial increase of 70%, from 2.5% to 2009 to 4.2% in 2017. The estimated cessation rates in all three age groups tended to converge to the weighted average cessation rate over time. CONCLUSIONS: The Kalman filter approach offers a real-time estimation of cessation rates that can be helpful for monitoring smoking cessation behavior.

Characterization of trajectories of physical activity and cigarette smoking from early adolescence to adulthood.

BACKGROUND: Cigarette smoking and physical inactivity are two critical risk factors for noncommunicable diseases and all-cause mortality. However, few studies have compared the long-term trajectories of both behaviors, as well as multilevel factors associated with trajectory patterns. Using the National Longitudinal Study of Adolescent to Adult Health (Add Health) Wave I through V survey data, this study characterized distinct subgroups of the population sharing similar behavioral patterns from adolescence to adulthood, as well as predictors of subgroup membership for physical activity (PA) and cigarette smoking behavior respectively. METHODS: Using the Add Health Wave I through V survey data, we identified the optimal number of latent classes and class-specific trajectories of PA and cigarette smoking from early adolescence to adulthood, fitting latent growth mixture models with standardized PA score and past 30-day cigarette smoking intensity as outcome measures and age as a continuous time variable. Associations of baseline sociodemographic factors, neighborhood characteristics, and sociopsychological factors with trajectory class membership were assessed using multinomial logistic regression. RESULTS: We identified three distinct subgroups of non-linear PA trajectories in the study population: moderately active group (N = 1067, 5%), persistently inactive group (N = 14,257, 69%) and worsening activity group (N = 5410, 26%). Foror cigarette smoking, we identified three distinct non-linear trajectory subgroups: persistent non-smoker (N = 14,939, 72%), gradual quitter (N = 2357, 11%), and progressing smoker (N = 3393, 16%). Sex, race/ethnicity, neighborhood environment and perceived peer support during adolescence were significant predictors of both physical activity and cigarette smoking trajectory subgroup membership from early adolescence to adulthood. CONCLUSIONS: There are three distinct subgroups of individuals sharing similar PA and cigarette smoking behavioral profile respectively from adolescence to adulthood in the Add Health study population. Behavioral interventions that focus on neighborhood environment (e.g. establish community-based activity center) and relationship to peers during adolescence (e.g. peer counseling) could be key to long-term PA promotion and cigarette smoking cessation.

Is Adolescent E-Cigarette Use Associated With Subsequent Smoking? A New Look.

INTRODUCTION: Prospective studies have consistently reported a strong association between e-cigarette use and subsequent cigarette smoking, but many failed to adjust for important risk factors. METHODS: Using longitudinal data from the Population Assessment of Tobacco and Health (PATH) Study, we employed multivariable logistic regressions to assess the adolescent vaping-to-smoking relationship, with four regressions (Models 1-4) sequentially adding more risk factors.Our sample included all waves (waves 1-5) of the PATH Study. RESULTS: The association between ever e-cigarette use and subsequent cigarette smoking decreased substantially in magnitude when adding more control variables, including respondents' sociodemographic characteristics, exposure to tobacco users, cigarette susceptibility, and behavioral risk factors. Using the most recent data (waves 4-4.5 and waves 4.5-5), this association was not significant in the most complete model (Model 4). Using wave 4.5-5 data, the adjusted odds ratio (aOR) for ever e-cigarette use at initial wave and subsequent past 12-month smoking declined from 4.07 (95% confidence interval [CI, 2.86-5.81) in Model 1, adjusting only for sociodemographic characteristics, to 1.35 (95% CI, 0.84-2.16) in Model 4, adjusting for all potential risk factors. Similarly, the aOR of ever e-cigarette use and past 30-day smoking at wave 5 decreased from 3.26 (95% CI, 1.81-5.86) in Model 1 to 1.21 (95% CI, 0.59-2.48) with all covariates (Model 4). CONCLUSIONS: Among adolescent never cigarette smokers, those who had ever used e-cigarettes at baseline, compared with never e-cigarette users, exhibited modest or non-significant increases in subsequent past 12-month or past 30-day smoking when adjusting for behavioral risk factors.

Monitoring the Increase in the U.S. Smoking Cessation Rate and Its Implication for Future Smoking Prevalence.

INTRODUCTION: We calculate the U.S. adult smoking cessation rate for 2014-2019, compare it to the historical trend, and estimate the implication for future smoking prevalence. METHODS: We repeated an earlier analysis, which examined the cessation rate from 1990 to 2014, extending the period to 2019. Employing National Health Interview Survey (NHIS) and National Survey on Drug Use and Health (NSDUH) data, we estimated the adult cessation rate in 6-year intervals, using weighted nonlinear least squares. We then employed a meta-regression model to test whether the cessation rate has increased beyond expectation. We used cessation rate estimates and smoking initiation rate estimates to project smoking prevalence in 2030 and eventual steady-state prevalence. RESULTS: The annual cessation rate increased 29% using NHIS data (from 4.2% in 2008-2013 to 5.4% in 2014-2019) and 33% with NSDUH data (4.2%-5.6%). The cessation rate increase accounts for 60% of a smoking prevalence decline in the most recent period exceeding the 1990-2013 predicted trend. The remaining 40% owes to declining smoking initiation. With current initiation and cessation rates, smoking prevalence should fall to 8.3% in 2030 and eventually reach a steady state of 3.53%. CONCLUSIONS: The smoking cessation rate continued to increase during 2014-2019. NHIS and NSDUH results are practically identical. The larger share (60%) of the smoking prevalence decrease, beyond expectation, attributable to the increased cessation rate is encouraging since the positive health effects of cessation occur much sooner than those derived from declining initiation. IMPLICATIONS: The smoking cessation rate in the United States continues to increase, accelerating the decline in smoking prevalence. This increase suggests that the Healthy People 2030 goal of 5% adult smoking prevalence, while ambitious, is attainable. Our findings can be used in simulation and statistical models that aim to predict future prevalence and population health effects due to smoking under various scenarios.

The importance of peer imitation on smoking initiation over time: a dynamical systems approach.

A recent Institute of Medicine Report calls for explicit modeling of smoking initiation, cessation and addiction processes. We introduce a model of smoking initiation that explicitly teases out the percentage of initiation due to social pressures, which we call "peer-imitation," and the percentage due to other factors, such as media ads, family smoking, and psychological factors, which we call "self-initiation." We propose a dynamic non-linear behavioral contagion model of smoking initiation and employ data from the National Survey on Drug Use and Health to estimate the relative contributions of imitation and self-initiation to the overall smoking initiation process. Although the percent of total smoking due to peer imitation has been trending downward over time, it remains higher than the percent due to self-initiation. We note unexpected changes for the 2007 cohort, and we discuss possible implications for intervention and for the spread of e-cigarettes.

Optimization of 5-CQA Extraction Conditions from Green Coffee By-Product (Coffea arabica) Using a Response-Surface Design and the Study of Its Extraction Kinetics.

To take advantage of the residues generated in the production of products from green coffee and due to the special interest in the compounds contained in the bean, a by-product obtained after the extraction of the oil was studied. The physical characterization of the green-coffee-bean by-product was carried out. Subsequently, the extraction of compound 5-CQA was carried out via leaching using central composition design 24 and evaluating factors such as temperature, time, solid/solvent ratio, and ethanol percentage, and its yield was quantified using HPLC. In addition, the response-surface methodology was used to maximize the efficiency of 5-CQA extraction and to perform the kinetic study. Yields of 59 ± 2 mg of 5-CQA/g from the by-product were obtained, and by selecting the best leaching conditions, the kinetic study was performed at 45, 60, and 75 °C, increasing the yield to a total of 61.8 ± 3 mg of 5-CQA/g. By applying the kinetic model of mass transfer, a fit of R2 > 0.97 was obtained, with KLa values between 0.266 and 0.320 min−1. This study showed an approach to optimize the 5-CQA extraction conditions, resulting in a simple, fast, reproducible, accurate, and low-cost method.

Reviving through human hippocampal newborn neurons.

Recent contradictory data has renewed discussion regarding the existence of adult hippocampal neurogenesis (AHN) in humans, i.e., the continued production of new neurons in the brain after birth. The present review revisits the debate of AHN in humans from a historical point of view in the face of contradictory evidence, analyzing the methods employed to investigate this phenomenon. Thus, to date, of the 57 studies performed in humans that we reviewed, 84% (48) concluded in favor of the presence of newborn neurons in the human adult hippocampus. Besides quality of the tissue (such as postmortem intervals below 26hours as well as tissue conservation and fixation), considerations for assessing and quantify AHN in the human brain require the use of stereology and toxicological analyses of clinical data of the patient.

A Magic Bullet? The Potential Impact of E-Cigarettes on the Toll of Cigarette Smoking.

INTRODUCTION: We examine the proportion of US smoking-produced mortality that e-cigarettes might eliminate under assumptions regarding vaping's ability to increase smoking cessation, vaping's health risks, and the possibility that vaping will increase smoking among young people. METHODS: We employ a dynamic population simulation model that tracks individuals from ages 0 to 110, differentiated by gender and smoking status. Using data from the US Census, the National Vital Statistics Reports, Cancer Prevention Study II, and the National Health Interview Survey, we estimate the number of smoking-related life-years lost (LYL) from 2018 to 2100 in a no-vaping scenario. We then compare results for model runs that assess the impact of vaping under a variety of assumptions. RESULTS: The combination of assumptions produces 360 possible scenarios. 357 (99%) yield positive estimates of life-years saved (LYS) due to vaping by 2100, from 143 000 to 65 million. Most scenarios result in millions of individuals quitting smoking due to vaping. On average, vaping-induced quitters gain an extra 1.2-2.0 years of life compared to smokers who quit without vaping. The impact of vaping is greatest when it most helps smokers who otherwise have the greatest difficulty quitting smoking. While the numbers of LYS are generally large across all scenarios, they often represent a small fraction of the toll of smoking. CONCLUSIONS: Vaping is highly likely to reduce smoking-produced mortality. Still, vaping is not "the" answer to the public health crisis created by smoking. Rather, it may well be a tool to add to the armamentarium of effective tobacco control measures. IMPLICATIONS: E-cigarettes hold the potential to reduce cigarette smoking's enormous toll. By itself, however, tobacco harm reduction, as embodied in vaping, is no magic bullet. Going forward, tobacco control will require vigilant application of the evidence-based measures that have brought us so much success in combatting smoking. It will require, as well, the search for and adoption of novel means of attacking the remaining problem. Harm reduction can, and many would say should, be a part of the complex formula that will eventually bring about the demise of smoking.

Estimating the Population Health Impact of Recently Introduced Modified Risk Tobacco Products: A Comparison of Different Approaches.

INTRODUCTION: Various approaches have been used to estimate the population health impact of introducing a Modified Risk Tobacco Product (MRTP). AIMS AND METHODS: We aimed to compare and contrast aspects of models considering effects on mortality that were known to experts attending a meeting on models in 2018. RESULTS: Thirteen models are described, some focussing on e-cigarettes, others more general. Most models are cohort-based, comparing results with or without MRTP introduction. They typically start with a population with known smoking habits and then use transition probabilities either to update smoking habits in the "null scenario" or joint smoking and MRTP habits in an "alternative scenario". The models vary in the tobacco groups and transition probabilities considered. Based on aspects of the tobacco history developed, the models compare mortality risks, and sometimes life-years lost and health costs, between scenarios. Estimating effects on population health depends on frequency of use of the MRTP and smoking, and the extent to which the products expose users to harmful constituents. Strengths and weaknesses of the approaches are summarized. CONCLUSIONS: Despite methodological differences, most modellers have assumed the increase in risk of mortality from MRTP use, relative to that from cigarette smoking, to be very low and have concluded that MRTP introduction is likely to have a beneficial impact. Further model development, supplemented by preliminary results from well-designed epidemiological studies, should enable more precise prediction of the anticipated effects of MRTP introduction. IMPLICATIONS: There is a need to estimate the population health impact of introducing modified risk nicotine-containing products for smokers unwilling or unable to quit. This paper reviews a variety of modeling methodologies proposed to do this, and discusses the implications of the different approaches. It should assist modelers in refining and improving their models, and help toward providing authorities with more reliable estimates.

An estimation of the harm of menthol cigarettes in the United States from 1980 to 2018.

BACKGROUND: Menthol cigarettes are thought to encourage smoking initiation among youths and young adults and make it more difficult for smokers to quit, thus increasing cigarette harm. However, no study to date has quantified the damage that menthol cigarettes have caused the US population. OBJECTIVE: To estimate the excess smoking prevalence, smoking initiation, and mortality in the US from 1980 through 2018 that can be attributed to menthol cigarettes. METHODS: Using a well-established simulation model of smoking prevalence and health effects and data from the National Health Interview Survey (NHIS), we first reproduced the overall US adult smoking prevalence between 1980 and 2018 (pseudo-R2=0.98) and associated mortality. Then we re-ran the model, assuming that menthol cigarettes were not present in the market over the same period. Finally, we compared both scenarios to quantify the public health harm attributable to menthol over the 1980-2018 period. RESULTS: From 1980 to 2018, we found that menthol cigarettes were responsible for slowing down the decline in smoking prevalence by 2.6 percentage points (13.7% vs 11.1% in 2018). Our results also show that menthol cigarettes were responsible for 10.1 million extra smokers, 3 million life years lost and 378 000 premature deaths during that period. CONCLUSIONS: With millions of excess smoking initiators and thousands of smoking-related deaths due to mentholated cigarettes from 1980 through 2018, our results indicate that these products have had a significant detrimental impact on the public's health and could continue to pose a substantial health risk. Our findings can assist the Food and Drug Administration in evaluating potential regulatory actions for mentholated tobacco products.

Consequences of a match made in hell: the harm caused by menthol smoking to the African American population over 1980-2018.

BACKGROUND: For many years, national surveys have shown a consistently disproportionately high prevalence of menthol smokers among African Americans compared with the general population. However, to our knowledge, no prior study has quantified the harm that menthol smoking has caused on that population. In this work, we estimate the public health harm that menthol cigarettes have caused to the African American community over the last four decades. METHODS: Using National Health Interview Survey data, we employed a well-established simulation model to reproduce the observed smoking trajectory over 1980-2018 in the African American population. Then, we repeat the experiment, removing the effects of menthol on the smoking initiation and cessation rates over that period, obtaining a new hypothetical smoking trajectory. Finally, we compared both scenarios to calculate the public health harm attributable to menthol cigarettes over 1980-2018. RESULTS: Our results show that menthol cigarettes were responsible for 1.5 million new smokers, 157 000 smoking-related premature deaths and 1.5 million life-years lost among African Americans over 1980-2018. While African Americans constitute 12% of the total US population, these figures represent, respectively, a staggering 15%, 41% and 50% of the total menthol-related harm. DISCUSSION: Our results show that menthol cigarettes disproportionally harmed African Americans significantly over the last 38 years and are responsible for exacerbating health disparities among that population. Removing menthol cigarettes from the market would benefit the overall US population but, particularly, the African American community.

ChEMBL: towards direct deposition of bioassay data.

ChEMBL is a large, open-access bioactivity database (https://www.ebi.ac.uk/chembl), previously described in the 2012, 2014 and 2017 Nucleic Acids Research Database Issues. In the last two years, several important improvements have been made to the database and are described here. These include more robust capture and representation of assay details; a new data deposition system, allowing updating of data sets and deposition of supplementary data; and a completely redesigned web interface, with enhanced search and filtering capabilities.

[Creutzfeldt-Jakob disease, experience in 17 patients]. / Enfermedad de Creutzfeldt-Jakob: experiencia de 5 años en un hospital terciario de Chile.

BACKGROUND: Creutzfeldt-Jakob disease (CJD) is a prion affection that typically produces a rapidly progressive dementia with different neurologic and extra-neurologic manifestations. AIM: To characterize clinical, imaging and electroencephalography findings in patients with a probable CJD. PATIENTS AND METHODS: A case series study of patients admitted in the Neurology department at a public hospital, between 2014 and 2019. Demographic, clinical, imaging, and electroencephalographic data of patients with probable CJD were analyzed. RESULTS: Seventeen patients aged 63 ± 11 years (53% women) with a probable CJD were gathered. The incidence was 4.7 cases/year per million inhabitants. Twenty four percent of patients had a family history of CJD. The median time between the onset of symptoms and the hospital admission was three months with a survival of four months. The most common clinical manifestations were an amnesic syndrome in 88%, myoclonus in 76%, frontal syndrome and ataxia in 71%. Brain MRI was abnormal in all patients. The preponderant finding was the involvement of the caudate nucleus in 82% of cases. In the EEG, 94% of patients had abnormalities. All had a theta-delta slowing as a base rhythm. The pseudo-periodic pattern was observed in the 29% and status epilepticus in 18%. CONCLUSIONS: In this group of patients we observed the heterogeneity of the clinical manifestations of the disease, the frequent imaging and electroencephalographic alterations and the short evolution time leading to death.

How much of the future mortality toll of smoking can be avoided?

OBJECTIVE: To determine how much future smoking-related mortality in the USA can be prevented, recognising that some of that future mortality results from past smoking. METHODS: Employing a dynamic population simulation model, we estimate smoking's expected mortality burden in the USA, measured as life-years lost (LYL), in a status-quo scenario run from 2018 through 2100. We then estimate LYL attributable to past smoking assuming that all smoking ceases at the end of 2017. We calculate the potential avoidable LYL, which we call the maximum potential reduction in premature mortality (MPRPM), as the difference between the two. We use data from the US Census Bureau, National Vital Statistics Reports, the National Health Interview Survey and Cancer Prevention Study II. RESULTS: Under status-quo assumptions, smoking will claim 305 million LYL in the US from 2018 to 2100. If all smoking ceased at the end of 2017, past smoking would be responsible for 191.8 million LYL. Thus, avoidable LYL by 2100-the MPRPM-would be 113.2 million, 37% of the expected toll of smoking. A sensitivity analysis finds that were the annual smoking initiation rate 3% instead of 7.8%, the MPRPM would be 13-14% lower. Were the annual permanent smoking cessation rate twice our status-quo estimate of 4.35%, the MPRPM would be 38-39% lower. CONCLUSIONS: Public health can address only the future toll of future smoking. Smoking's MPRPM is the reduction in the mortality burden of smoking that tobacco control can strive to achieve.

E-cigarettes: Comparing the Possible Risks of Increasing Smoking Initiation with the Potential Benefits of Increasing Smoking Cessation.

Introduction: The public health community is divided regarding electronic cigarettes. Skeptics emphasize potential vaping-induced increases in smoking among children and possible health hazards for adults. Enthusiasts consider e-cigarettes much less dangerous than smoking and believe they increase adult smoking cessation. We compare potential health benefits and costs to put these two perspectives in context. Methods: Using a dynamic model that tracks the US adult population's smoking status and smoking-related deaths over time, we simulate the effects of vaping-induced smoking initiation and cessation on life-years saved or lost to the year 2070. The base case assumes that vaping annually increases smoking initiation by 2% and smoking cessation by 10%. Sensitivity analyses raise the initiation rate increase to 6% while decreasing the cessation rate increase to 5%. Sensitivity analyses also test vaping's reducing the health benefits of quitting smoking by 10%. Results: With base-case assumptions, the population gains almost 3.3 million life-years by 2070. If all people who quit smoking by vaping lose 10% of the benefit of quitting smoking, the net life-year gain falls to 2.4 million. Under worst-case assumptions, in which vaping increases smoking initiation by 6% and cessation by 5%, and vaping-induced quitters lose 10% of the health benefits, the population gains over 580000 life-years. Conclusion: Potential life-years gained as a result of vaping-induced smoking cessation are projected to exceed potential life-years lost due to vaping-induced smoking initiation. These results hold over a wide range of plausible parameters. Implications: Our analysis strongly suggests that the upside health benefit associated with e-cigarettes, in terms of their potential to increase adult smoking cessation, exceeds their downside risk to health as a result of their possibly increasing the number of youthful smoking initiators. Public messaging and policy should continue to strive to reduce young people's exposure to all nicotine and tobacco products. But, they should not do so at the expense of limiting such products' potential to help adult smokers to quit.