Long-term fire and vegetation change in northwestern Amazonia.

Amazonian forest plots are used to quantify biodiversity and carbon sequestration, and provide the foundation for much of what is known about tropical ecology. Many plots are assumed to be undisturbed, but recent work suggests that past fire, forest openings, and cultivation created vegetation changes that have persisted for decades to centuries (ecological legacies). The Yasuní Forest Dynamics plot is one of the most biodiverse places on earth, yet its human history remains unknown. Here, we use charcoal and phytolith analysis to investigate the fire and vegetation history of the Yasuní forest plot, and compare results with nearby forest plots in Colombia (Amacayacu) and Peru (Medio Putumayo-Algodón [MPA]) to explore the spatial variability of past disturbances and ecological legacies in northwestern Amazonia. Three 14C dated charcoal fragments provided evidence for a modern (1956 CE) and a past fire event ca. 750 years ago at Yasuní, compared with fire ages of 1000-1600 years ago documented at Amacayacu and MPA. Small-scale disturbances and localized canopy openings also occurred in the Yasuní plot. Phytolith assemblages from Yasuní and Amacayacu showed more variability in past vegetation change than MPA. Low-intensity, non-continuous disturbances occurred at all three plots in the past, and our results highlight the variability of past human activities both in space and time in northwestern Amazonia. Our data also suggest that post-Columbian human disturbances from the Rubber Boom (AD 1850-1920) and subsequent oil exploration have likely left stronger ecological legacies than those left by pre-Columbian peoples in our studied regions.

Time trends in smoking in Russia in the light of recent tobacco control measures: synthesis of evidence from multiple sources.

BACKGROUND: The study aims at identifying long-term trends and patterns of current smoking by age, gender, and education in Russia, including the most recent period from 2008 during which tobacco control policies were implemented, and to estimate the impact on mortality of any reductions in prevalence. We present an in-depth analysis based on an unprecedentedly large array of survey data. METHODS: We examined pooled micro-data on smoking from 17 rounds of the Russian Longitudinal Monitoring Study of 1996-2016, 11 other surveys conducted in Russia in 1975-2017, and two comparator surveys from England and the USA. Standardization by age and education, regression and meta-analysis were used to estimate trends in the prevalence of current smoking by gender, age, and educational patterns. RESULTS: From the mid-1970s to the mid-2000s smoking prevalence among men was relatively stable at around 60%, after which time prevalence declined in every age and educational group. Among women, trends in smoking were more heterogeneous. Prevalence more than doubled above the age of 55 years from very low levels (< 5%). At younger ages, there were steep increases until the mid-2000s after which prevalence has declined. Trends differed by educational level, with women in the lowest educational category accounting for most of the long-term increase. We estimate that the decline in male smoking may have contributed 6.2% of the observed reduction in cardiovascular deaths among men in the period 2008-16. CONCLUSIONS: The implementation of an effective tobacco control strategy in Russia starting in 2008 coincided with a decline in smoking prevalence among men from what had been stable, high levels over many decades regardless of age and education. Among women, the declines have been more uneven, with young women showing recent downturns, while the smoking prevalence in middle age has increased, particularly among those with minimal education. Among men, these positive changes will have made a small contribution to the reduction in mortality seen in Russia since 2005.

Dynamics in child undernutrition in Bangladesh: Evidence from nationally representative surveys between 1997 and 2014.

BACKGROUND: Bangladesh has been struggling to reduce the prevalence of childhood undernutrition, which impedes physical and mental capability and accelerates morbidity and mortality. OBJECTIVES: The objective of the paper is to examine the changes over time in the association between potential covariates and nutritional status of Bangladeshi children. METHODS: The study combined and analyzed data from six waves of Demographic and Health Surveys between 1997 and 2014. Multivariable binary logistic regression models have been fitted to data from individual waves. Overall association has been investigated using forest plots, and meta-regression has been utilized to assess the pace of change in the association over time. RESULTS: Parental education and place of residence showed a consistent association with nutritional status of children. Children from parents with no little education were more likely to be undernourished than those from parents with secondary or higher level of education (odds ratio [OR] in 1997 = 3.34, 95% confidence interval [CI] = 2.65-4.22, OR in 2004 = 1.93, 95% CI = 1.58-2.37). On the other hand, gaps in the association of wealth and childhood nutrition have been widening consistently so that in 2014 children from households from the lowest 40% wealth category were 2.66 times (OR = 2.66, 95% CI = 2.13-3.33) as likely as to be undernourished than those from upper 20%. CONCLUSIONS: The findings have policy implications in terms of developing programs directed to mothers with a relatively poor socioeconomic background. A specific example would be providing nutritional education in relation to importance of childhood nutrition or cheaper nutritious food.

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models.

Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs.

An integrated pan-tropical biomass map using multiple reference datasets.

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha(-1) vs. 21 and 28 Mg ha(-1) for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets.

The effects of anaesthetics on postoperative physiological reactions: a meta-analysis.

This study aimed to systematically investigate the effects of different anaesthetics on postoperative physiological reactions compared with placebo. The literature search was conducted using three databases: PubMed, EMBASE, and the Cochrane Library. Studies published from January 1990 to January 2015 were screened. The language was restricted to English. Heterogeneity was analyzed by the Q test and I(2) statistic. A fixed-effect model was used for homogenous data and a random-effects model for heterogeneous data. The odds ratio (OR) and 95% confidence interval (CI) were calculated to monitor the incidences of overall adverse events, arterial blood pressure, and cardiac abnormalities. Sensitivity analysis was performed to estimate the strength of the meta-analysis, and publication bias was analyzed using Egger's test. A total of 24 articles were included in this meta-analysis. There were 1,810 and 1,806 cases in the anaesthetic group and the placebo group, respectively. The incidence of overall adverse events was significantly lower in the anaesthetic group compared with the placebo group (OR = 0.57; 95% CI, 0.38-0.84). No publication bias was observed, and no inverse estimates were calculated using sensitivity analysis. There was no significant difference for the incidence of arterial blood pressure (OR = 4.62; 95% CI, 0.90-23.70) and cardiac abnormalities (OR = 1.18; 95% CI, 0.53-2.63) between the two groups. Although the incidence of overall adverse events was decreased in the anaesthetic group, it is impossible to determine whether the use of anaesthetics during surgical operation has a protective effect on postoperative physiological reactions.

Missing the trees for the forest: most subgroup analyses using forest plots at the ASCO annual meeting are inconclusive.

Background: Oncologists often refer to forest plots to determine which patient subgroups may be more likely to benefit from a therapy tested in a randomized clinical trial (RCT). We sought to empirically determine the information content of subgroup comparisons from forest plots of RCTs. Methods: We assessed all forest plots from RCTs of therapeutic interventions presented orally at the American Society of Clinical Oncology Annual Meetings in 2020 and 2021. Subgroups were considered as showing evidence of treatment effect heterogeneity in forest plots when their confidence intervals (CIs) did not overlap with the vertical line corresponding to the main effect observed in the overall RCT cohort. Subgroups were considered as showing evidence of treatment effect homogeneity in forest plots when their CIs did not meaningfully differ, within 80-125% equivalence range, with the values compatible with the main effect. All other subgroups were considered as inconclusive. Results: A total of 99 forest plots were presented, and only 24.2% contained one or more subgroups suggestive of treatment effect heterogeneity. A total of 81 forest plots provided enough information to evaluate treatment effect heterogeneity and homogeneity. These 81 forest plots represented a total of 1344 individual subgroups, of which 57.2% were inconclusive, 41.1% showed evidence of treatment effect homogeneity, and 1.6% yielded evidence suggestive of treatment effect heterogeneity. Conclusion: The majority of subgroup comparisons were inconclusive in this empirical analysis of forest plots used in oncology RCTs. Different strategies should be considered to improve the estimation and representation of subgroup-specific effects.

Meta-analysis of in-vitro cytotoxicity evaluation studies of zinc oxide nanoparticles: Paving way for safer innovations.

Nano-based products have shown their daunting presence in several sectors. Among them, Zinc Oxide (ZnO) nanoparticles wangled the reputation of providing "next-generation solutions" and are being utilized in plethora of products. Their widespread application has led to increased exposure of these particles, raising concerns regarding toxicological repercussions to the human health and environment. The diversity, complexity, and heterogeneity in the available literature, along with correlation of befitting attributes, makes it challenging to develop one systematic framework to predict this toxicity. The present study aims at developing predictive modelling framework to tap the prospective features responsible for causing cytotoxicity in-vitro on exposure to ZnO nanoparticles. Rigorous approach was used to mine the information from complete body of evidence published to date. The attributes, features and experimental conditions were systematically extracted to unmask the effect of varied features. 1240 data points from 76 publications were obtained, containing 14 qualitative and quantitative attributes, including physiochemical properties of nanoparticles, cell culture and experimental parameters to perform meta-analysis. For the first time, the efforts were made to investigate the degree of significance of attributes accountable for causing cytotoxicity on exposure to ZnO nanoparticles. We show that in-vitro cytotoxicity is closely related with dose concentration of nanoparticles, followed by exposure time, disease state of the cell line and size of these nanoparticles among other attributes.

Lobectomy versus segmentectomy in patients with stage T (> 2 cm and ≤ 3 cm) N0M0 non-small cell lung cancer: a propensity score matching study.

BACKGROUND: The safety and effectiveness of lung segmentectomy in patients with early non-small cell lung cancer (NSCLC) remains controversial. We have therefore reviewed the clinicopathologic characteristics and survival outcomes of patients treated with lobectomy or segmentectomy for early T (> 2 and ≤ 3 cm) N0M0 NSCLC. METHODS: We obtained data from the Surveillance, Epidemiology, and End Results database for patients who underwent lobectomy or segmentectomy between 2004 and 2015. To reduce bias and imbalances between the treatment groups, propensity score matching analysis was performed. We used Kaplan-Meier curves to estimate overall survival (OS) and lung cancer-specific survival (LCSS). We conducted univariate and multivariate Cox proportional hazards regression analyses to identify independent prognostic factors for OS and cancer-specific survival, and applied the Cox proportional hazards model to create forest plots. RESULTS: Before matching, both univariate and multivariate Cox regression analyses revealed that patients who underwent lobectomy exhibited better OS (P < 0.001) and LCSS (P = 0.001) than patients who underwent segmentectomy. However, after matching, survival differences between the groups were not significant; OS (P = 0.434) and LCSS (P = 0.593). Regression analyses revealed that age and tumor grade were independent predictors of OS and LCSS (P < 0.05). CONCLUSIONS: Patients with stage T (> 2 and ≤ 3 cm) N0M0 NSCLC undergoing segmentectomy can obtain OS and LCSS similar to those obtained with lobectomy. Further studies are required considering the solid component effects and pathologic tumor types regarding segmentectomies. Additional long-term survival and outcome analyses should be conducted with larger cohorts.

Above-ground biomass recovery following logging and thinning over 46 years in an Australian tropical forest.

Managed tropical forests are a globally important carbon pool, but the effects of logging and thinning intensities on long-term biomass dynamics are poorly known. We investigated the demographic mechanisms of above-ground biomass recovery over 48 years in an Australian tropical forest following four silvicultural treatments: selective logging only as a control and selective logging followed by low-, medium- and high-intensity thinning. Initial biomass recovery rates following thinning were poor predictors of the long-term changes. Initial biomass recovery from 1969 to 1973 was slow and was largely concentrated on an increase in the biomass of residual stems. From 1973 to 1997, above ground biomass (AGB) increased almost linearly, with a similar slope for all sites. From 1997 to 2015, the rate of biomass accumulation slowed, especially for the L treatment. All thinning treatments stimulated more recruitment and regrowth of non-harvested remaining trees compared to the untreated control. Biomass at both the low and medium intensity treatments has almost fully recovered to 98% and 97% of pre-logging biomass levels respectively. The predicted times of complete above-ground biomass recovery for the logging only and high intensity treatments are 55 and 77 years respectively. The slower biomass recovery at the logging only site was largely due to increased mortality in the last measurement period. The slower recovery of the high intensity site was due to a combination of a higher initial reduction in biomass from thinning and the increased mortality in the last measurement period. The high mortality rates in the most recent measurement period are likely due to the impacts of two cyclones that impacted the study site. Our results suggest that it will take at least around 50 years for this site to recover to its pre-harvest biomass, much longer than many of the cutting cycles currently used in tropical forest management.

Presentation of meta-analysis plots.

Meta-analysis (forest) plots are widely used to show the results from multiple individual randomized trials or observational studies that address the same question, including the assessment of screening markers. They show the between study spread of results and provide a summary estimate of the results from all the studies combined. We here illustrate the advantage of ordering study results by the magnitude of the effect and including a vertical shaded band encompassing the summary 95% confidence interval of the summary estimate to emphasize the uncertainty of the estimate in a way that is more prominent than only displaying a "diamond" around its value.

[Clinical research XXIII. From clinical judgment to meta-analyses]. / Investigación clínica XXIII. Del juicio clínico a los metaanálisis.

Systematic reviews (SR) are studies made in order to ask clinical questions based on original articles. Meta-analysis (MTA) is the mathematical analysis of SR. These analyses are divided in two groups, those which evaluate the measured results of quantitative variables (for example, the body mass index -BMI-) and those which evaluate qualitative variables (for example, if a patient is alive or dead, or if he is healing or not). Quantitative variables generally use the mean difference analysis and qualitative variables can be performed using several calculations: odds ratio (OR), relative risk (RR), absolute risk reduction (ARR) and hazard ratio (HR). These analyses are represented through forest plots which allow the evaluation of each individual study, as well as the heterogeneity between studies and the overall effect of the intervention. These analyses are mainly based on Student's t test and chi-squared. To take appropriate decisions based on the MTA, it is important to understand the characteristics of statistical methods in order to avoid misinterpretations.

Las revisiones sistemáticas (RS) son estudios que intentan contestar una pregunta clínica por medio del uso de artículos originales. Los metaanálisis (MTA) son el análisis matemático de las revisiones sistemáticas. Estos análisis se dividen en dos grandes grupos: aquellos que evalúan los resultados medidos como variables cuantitativas (por ejemplo, el índice de masa corporal ­IMC­) y aquellos que evalúan variables cualitativas (por ejemplo, si un paciente está vivo o muerto, o si ha mejorado o no de su enfermedad). Los primeros utilizan en general la diferencia de medias. Para los segundos se puede utilizar el cálculo de razón de momios (RM) u odds ratio (OR), riesgo relativo (RR), reducción absoluta del riesgo (RAR), hazard ratio (HR), etcétera. Estos análisis se grafican por medio de forest plots que permiten tanto la evaluación individual de los estudios como la del resultado final, así como la heterogenidad de estas comparaciones. Asimismo, estos análisis se basan en análisis estadísticos básicos como la t de Student y la chi cuadrada. Para la toma de decisiones basadas en las RS y en los MTA, es importante evaluar cuidadosamente los posibles sesgos y los apartados estadísticos con el fin evitar malas interpretaciones.