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Whether global change will drive changing forests from net carbon (C) sinks to sources relates to how quickly deadwood decomposes. Because complete wood mineralization takes years, most experiments focus on how traits, environments and decomposer communities interact as wood decay begins. Few experiments last long enough to test whether drivers change with decay rates through time, with unknown consequences for scaling short-term results up to long-term forest ecosystem projections. Using a 7 year experiment that captured complete mineralization among 21 temperate tree species, we demonstrate that trait effects fade with advancing decay. However, wood density and vessel diameter, which may influence permeability, control how decay rates change through time. Denser wood loses mass more slowly at first but more quickly with advancing decay, which resolves ambiguity about the after-life consequences of this key plant functional trait by demonstrating that its effect on decay depends on experiment duration and sampling frequency. Only long-term data and a time-varying model yielded accurate predictions of both mass loss in a concurrent experiment and naturally recruited deadwood structure in a 32-year-old forest plot. Given the importance of forests in the carbon cycle, and the pivotal role for wood decay, accurate ecosystem projections are critical and they require experiments that go beyond enumerating potential mechanisms by identifying the temporal scale for their effects.

Rationale: Meta-analyses have suggested the risk of cardiovascular disease (CVD) events is significantly higher after a chronic obstructive pulmonary disease (COPD) exacerbation. However, many of these studies have included a broad array of CVD events or have been limited to highly selected patient populations potentially not generalizable to the broader population of COPD. Objectives and Methods: We assessed the risk of atherosclerotic cardiovascular disease (ASCVD) hospitalizations after COPD hospitalization compared with before COPD hospitalization and identified patient factors associated with ASCVD hospitalizations after COPD hospitalization. This retrospective cohort study used claims data from 920,550 Medicare beneficiaries hospitalized for COPD from 2016 to 2019 in the United States. The primary outcome was risk of an ASCVD hospitalization composite outcome (myocardial infarction, percutaneous coronary intervention, coronary artery bypass graft surgery, stroke, or transient ischemic attack) in the 30 days and 1 year after COPD hospitalization relative to the same time period before COPD hospitalization. Time in the before and after COPD hospitalization time periods to a composite ASCVD hospitalization outcome were modeled using an extension of the Cox proportional hazards model, the Anderson-Gill model, with adjustment for patient characteristics. Additional analyses evaluated for interactions in subgroups associated with the composite ASCVD hospitalization outcome. Results: Among 920,550 patients in the 30-day and 1-year cohorts (mean age, 73–74 yr) the hazard ratio estimate (95% confidence interval) for the composite ASCVD hospitalization outcome after COPD hospitalization versus before COPD hospitalization for the 30-day cohort was 0.99 (0.93, 1.05; P = 0.67), and for the 1-year cohort, it was 0.99 (0.97, 1.02; P = 0.53) after adjustment. We observed three subgroups that were significantly associated with higher risk for ASCVD hospitalizations 1 year after COPD hospitalization: 76+ years old, women, and COPD hospitalization severity. Conclusions: Among Medicare beneficiaries hospitalized for COPD, the risk of ASCVD hospitalization was not significantly increased 30 days or 1 year after COPD hospitalization relative to before COPD hospitalization. In subgroup analyses, we identified age 76+ years old, female sex, and COPD hospitalization severity as high-risk subgroups with increased risk of ASCVD events 1 year after COPD hospitalization. Further research is needed to characterize the COPD exacerbation populations at highest ASCVD hospitalization risk. [ABSTRACT FROM AUTHOR]

Outcomes: 1. Upon completion, participants will be able to list cancer populations (ie, by cancer type) that have a higher relative prevalence of substance use disorders (SUD), as well as commonly used substances 2. Upon completion, participants will demonstrate an appreciation of the need for targeted intervention development efforts to address concurrent cancer/SUD in high-SUD prevalence cancer populations Despite the close connection between cancer and substance use (with some individuals predisposed to cancer due to their substance use history and/or using substances to cope with cancer-related distress) the prevalence of substance use disorders (SUD) among people with cancer is unknown. We characterized overall and cancer type-specific prevalence of SUD to identify populations that may benefit from interventions aimed at mitigating the negative effects of SUD on cancer and pain outcomes. We used data from the cross-sectional National Survey on Drug Use and Health (2015–2020), which includes information on current SUD (assessed using DSM criteria) and cancer history. We calculated the weighted population prevalence of SUD and corresponding standard errors (both expressed as %) among adults with any history of solid tumor cancer. Among 6,101 respondents with a history of cancer, overall SUD prevalence was 3.83% (0.32%). Alcohol was most common (2.78% (0.26%)), followed by stimulants (0.50% (0.10%)), cannabis (0.46% (0.10%)), opioids (0.43% (0.10%)), and sedatives (0.12% (0.04%)). SUD were most prevalent in head/neck cancers (9.74% (2.33%)), esophageal/gastric cancers (9.17% (3.36%)), cervical cancer (6.32% (1.24%)), and melanoma (5.46% (1.12%)). The distribution of specific substances differed by cancer type. For example, in head/neck cancers, as in the overall sample, alcohol accounted for most SUD (7.47% (1.89%)); however, sedatives were more common in this group (1.38% (1.36%)) than in the overall sample. In gastric/esophageal cancers, cannabis was most common (6.94% (4.32%)), followed by opioids (2.23% (2.24%)). In certain cancers, SUD are as prevalent as other common comorbidities (eg, diabetes, depression). Despite the prevalence and known consequences of untreated SUD (eg, for cancer pain management), and existence of effective treatments for SUD, the field lacks strategies to manage SUD and cancer concurrently. Future studies should target high-SUD prevalence cancer types and identify strategies to improve care integration. [ABSTRACT FROM AUTHOR]

Background: Dichotomization using the lower quartile as cutoff is commonly used for harmonizing heterogeneous physical activity (PA) measures across studies. However, this may create misclassification and hinder discovery of new loci. Objectives: This study aimed to evaluate the performance of selecting individuals from the extremes of the exposure (SIEE) as an alternative approach to reduce such misclassification. Method: For systolic and diastolic blood pressure in the Framingham Heart Study, we performed a genome-wide association study with gene-PA interaction analysis using three PA variables derived by SIEE and two other dichotomization approaches. We compared number of loci detected and overlap with loci found using a quantitative PA variable. In addition, we performed simulation studies to assess bias, false discovery rates (FDR), and power under synergistic/antagonistic genetic effects in exposure groups and in the presence/absence of measurement error. Results: In the empirical analysis, SIEE's performance was neither the best nor the worst. In most simulation scenarios, SIEE was consistently outperformed in terms of FDR and power. Particularly, in a scenario characterized by antagonistic effects and measurement error, SIEE had the least bias and highest power. Conclusion: SIEE's promise appears limited to detecting loci with antagonistic effects. Further studies are needed to evaluate SIEE's full advantage. [ABSTRACT FROM AUTHOR]

Selective logging, the targeted harvesting of timber trees in a single cutting cycle, is globally rising in extent and intensity. Short-term impacts of selective logging on tropical forests have been widely investigated, but long-term effects on temporal dynamics of forest structure and composition are largely unknown. Understanding these long-term dynamics will help determine whether tropical forests are resilient to selective logging and inform choices between competing demands of anthropogenic use versus conservation of tropical forests. Forest dynamics can be studied within the framework of succession theory, which predicts that temporal turnover rates should decline with time since disturbance. Here, we investigated the temporal dynamics of a tropical forest in Kibale National Park, Uganda over 45 years following selective logging. We estimated turnover rates in stems, species composition, and functional traits (wood density and diameter at breast height), using observations from four censuses in 1989, 1999, 2006, and 2013, of stems ⩾10 cm diameter within 17 unlogged and 9 logged 200 × 10 m vegetation plots. We used null models to account for interdependencies among turnover rates in stems, species composition, and functional traits. We tested predictions that turnover rates should be higher and decrease with increasing time since the selective logging event in logged forest, but should be less temporally variable in unlogged forest. Overall, we found higher turnover rates in logged forest for all three attributes, but turnover rates did not decline through time in logged forest and was not less temporally variable in unlogged forest. These results indicate that successional models that assume recovery to pre-disturbance conditions are inadequate for predicting the effects of selective logging on the dynamics of the tropical forest in Kibale. Selective logging resulted in persistently higher turnover rates, which may compromise the carbon storage capacity of Kibale’s forest. Selective logging effects may also interact with effects from other global trends, potentially causing major long-term shifts in the dynamics of tropical forests. Similar studies in tropical forests elsewhere will help determine the generality of these conclusions. Ultimately, the view that selective logging is a benign approach to the management of tropical forests should be reconsidered in the light of studies of the effects of this practice on long-term forest dynamics. [ABSTRACT FROM AUTHOR]

1. Participants will be able to identify subpopulations of cancer survivors (based on cancer type) that have a high prevalence of substance misuse. 2. Participants will be able to identify substances that are commonly misused among cancer survivors. We present actionable data on high substance misuse-prevalence cancer populations that highlight the need for targeted interventions in these groups. Based on our results, implementing evidence-based interventions for alcohol misuse (e.g., screening, brief intervention, treatment) in cervical and head/neck cancer care settings may be particularly impactful. Substance misuse (i.e., high-risk use that does not meet criteria for use disorder but may result in harm) is at least as prevalent among cancer survivors (people diagnosed with cancer) as it is in the general population. Among cancer survivors, substance misuse is associated with poor cancer outcomes. To generate cancer type-specific estimates of substance misuse, with the goal of guiding attention and resources towards populations where interventions are most needed. We used data from the National Survey on Drug Use and Health (2015-2020) to calculate the weighted population prevalence of substance misuse and corresponding standard errors (both expressed as %) among adults with any solid tumor cancer history, overall and by cancer type. Misuse was defined as: binge drinking (alcohol), use other than prescribed (prescription drugs), or any nonmedical use. Substance categories included: alcohol, opioids (illicit and prescription), sedatives (prescription sedatives and tranquilizers), and stimulants (prescription, methamphetamine, and cocaine). We excluded cannabis in the absence of established definitions of misuse. Among 6,101 cancer survivors, the prevalence of alcohol misuse was 14% (0.6%). Opioid misuse was less common (3% [0.3%]), as were sedative and stimulant misuse (< 2% each). With respect to cancer type-specific prevalence, substance misuse was highly prevalent among cervical and head/neck cancer survivors, including for alcohol (cervical: 24% [3%], head/neck: 27% [7%]) and opioids (cervical: 5% [1%]), head/neck: (5% [3%]). Results were consistent in a sub-cohort of 1,437 cancer survivors diagnosed with cancer in the past year, with the highest rates of substance misuse observed in cervical and head/neck cancers. Efforts to address substance misuse should target patients with cervical and head/neck cancers. Evidence-based interventions for alcohol (e.g., screening, brief intervention, treatment) may be particularly impactful. Our results are actionable, elucidating clear opportunities to address substance misuse in cancer survivors. Palliative care in oncology/Psychosocial support [ABSTRACT FROM AUTHOR]