Socioeconomic consequences of the COVID‐19 pandemic for people who use drugs

The COVID-19 pandemic triggered widespread socioeconomic hardship, disproportionately impacting disadvantaged populations. People who use illicit drugs are more likely to experience unemployment, homelessness, criminal justice involvement and poorer health outcomes than the general community, yet little is known about the socioeconomic impacts of the pandemic on their lives. To address this gap in the literature, we conducted in-depth interviews with 76 participants from two cohort studies of people who use illicit drugs (people who inject drugs and/or use methamphetamine) in Victoria, Australia. Findings support claims that pandemic-related Social Security supplementary payments and initiatives to reduce homelessness, although not systemically transforming people's lives, produced temporary relief from chronic socioeconomic hardship. Results also indicate how temporary interruptions to drug supply chains inflated illicit drug prices and produced adverse consequences such as financial and emotional stress, which was exacerbated by drug withdrawal symptoms for many participants. Furthermore, increased community demand for emergency food and housing support during the pandemic appeared to reduce participants' access to these services. Our findings about the unintended consequences of pandemic responses on the socioeconomic lives of a group of people who use illicit drugs provide insights into and opportunities for policy reform to redress their entrenched disadvantage

"It's a revolving door": Ego-depletion among prisoners with injecting drug use histories as a barrier to post-release success

Background: People who inject drugs (PWID) are overrepresented among prisoner populations worldwide. This qualitative study used the psychological concept of “ego-depletion” as an exploratory framework to better understand the disproportionate rates of reincarceration among people with injecting drug use histories. The aim was to illuminate mechanisms by which prospects for positive post-release outcomes for PWID are enhanced or constricted. Methods: Participants were recruited from a longitudinal cohort study, SuperMIX, in Victoria, Australia. Eligible participants were invited to participate in an in-depth interview. Inclusion criteria were: aged 18+; lifetime history of injecting drug use; incarcerated for >three months and released from custody <12 months previously. Analysis of 48 interviews examined how concepts relevant to the ego-depletion framework (self-regulation; standards; consequences and mitigators of ego-depletion) manifested in participants’ narratives. Results: Predominantly, participants aimed to avoid a return to problematic drug use and recidivism, and engaged in effortful self-regulation to pursue their post-release goals. Post-release environments were found to diminish self-regulation resources, leading to states of ego-depletion and compromising the capacity to self-regulate according to their ideals. Fatalism, stress, and fatigue associated with the transition period exacerbated ego-depletion. Strategies that mitigated ego-depletion included avoidance of triggering environments; reducing stress through opioid agonist therapy; and fostering positive affect through supportive relationships. Conclusions: Post-release environments are ego-depleting and inconducive to sustaining behavioural changes for PWID leaving prison. Corrections’ behaviourist paradigms take insufficient account of the socio-structural factors impacting on an individual's self-regulation capacities in the context of drug dependence and desistance processes. Breaking the cycles of reincarceration among PWID requires new approaches that moderate ego-depletion and facilitate long-term goal-pursuit

Environmental Exposures during Puberty: Window of Breast Cancer Risk and Epigenetic Damage.

During puberty, a woman's breasts are vulnerable to environmental damage ("window of vulnerability"). Early exposure to environmental carcinogens, endocrine disruptors, and unhealthy foods (refined sugar, processed fats, food additives) are hypothesized to promote molecular damage that increases breast cancer risk. However, prospective human studies are difficult to perform and effective interventions to prevent these early exposures are lacking. It is difficult to prevent environmental exposures during puberty. Specifically, young women are repeatedly exposed to media messaging that promotes unhealthy foods. Young women living in disadvantaged neighborhoods experience additional challenges including a lack of access to healthy food and exposure to contaminated air, water, and soil. The purpose of this review is to gather information on potential exposures during puberty. In future directions, this information will be used to help elementary/middle-school girls to identify and quantitate environmental exposures and develop cost-effective strategies to reduce exposures

Suppression of p53 function in normal human mammary epithelial cells increases sensitivity to extracellular matrix–induced apoptosis

Little is known about the fate of normal human mammary epithelial cells (HMECs) that lose p53 function in the context of extracellular matrix (ECM)–derived growth and polarity signals. Retrovirally mediated expression of human papillomavirus type 16 (HPV-16) E6 and antisense oligodeoxynucleotides (ODNs) were used to suppress p53 function in HMECs as a model of early breast cancer. p53+ HMEC vector controls grew exponentially in reconstituted ECM (rECM) until day 6 and then underwent growth arrest on day 7. Ultrastructural examination of day 7 vector controls revealed acinus-like structures characteristic of normal mammary epithelium. In contrast, early passage p53− HMEC cells proliferated in rECM until day 6 but then underwent apoptosis on day 7. p53− HMEC-E6 passaged in non-rECM culture rapidly (8–10 passages), lost sensitivity to both rECM-induced growth arrest and polarity, and also developed resistance to rECM-induced apoptosis. Resistance was associated with altered expression of α3-integrin. Treatment of early passage p53− HMEC-E6 cells with either α3- or β1-integrin function-blocking antibodies inhibited rECM-mediated growth arrest and induction of apoptosis. Our results indicate that suppression of p53 expression in HMECs by HPV-16 E6 and ODNs may sensitize cells to rECM-induced apoptosis and suggest a role for the α3/β1-heterodimer in mediating apoptosis in HMECs grown in contact with rECM

Global Imprint of Mycorrhizal Fungi on Whole-Plant Nutrient Economics

Mycorrhizal fungi are critical members of the plant microbiome, forming a symbiosis with the roots of most plants on Earth. Most plant species partner with either arbuscular or ectomycorrhizal fungi, and these symbioses are thought to represent plant adaptations to fast and slow soil nutrient cycling rates. This generates a second hypothesis, that arbuscular and ectomycorrhizal plant species traits complement and reinforce these fungal strategies, resulting in nutrient acquisitive vs. conservative plant trait profiles. Here we analyzed 17,764 species level trait observations from 2,940 woody plant species to show that mycorrhizal plants differ systematically in nitrogen and phosphorus economic traits. Differences were clearest in temperate latitudes, where ectomycorrhizal plant species are more nitrogen use- and phosphorus use-conservative than arbuscular mycorrhizal species. This difference is reflected in both aboveground and belowground plant traits and is robust to controlling for evolutionary history, nitrogen fixation ability, deciduousness, latitude, and species climate niche. Furthermore, mycorrhizal effects are large and frequently similar to or greater in magnitude than the influence of plant nitrogen fixation ability or deciduous vs. evergreen leaf habit. Ectomycorrhizal plants are also more nitrogen conservative than arbuscular plants in boreal and tropical ecosystems, although differences in phosphorus use are less apparent outside temperate latitudes. Our findings bolster current theories of ecosystems rooted in mycorrhizal ecology and support the hypothesis that plant mycorrhizal association is linked to the evolution of plant nutrient economic strategies

Characterizing the diurnal patterns of errors in the prediction of evapotranspiration by several land‐surface models: An NACP analysis

Land‐surface models use different formulations of stomatal conductance and plant hydraulics, and it is unclear which type of model best matches the observed surface‐atmosphere water flux. We use the North American Carbon Program data set of latent heat flux (LE) measurements from 25 sites and predictions from 9 models to evaluate models' ability to resolve subdaily dynamics of transpiration. Despite overall good forecast at the seasonal scale, the models have difficulty resolving the dynamics of intradaily hysteresis. The majority of models tend to underestimate LE in the prenoon hours and overestimate in the evening. We hypothesize that this is a result of unresolved afternoon stomatal closure due to hydrodynamic stresses. Although no model or stomata parameterization was consistently best or worst in terms of ability to predict LE, errors in model‐simulated LE were consistently largest and most variable when soil moisture was moderate and vapor pressure deficit was moderate to limiting. Nearly all models demonstrate a tendency to underestimate the degree of maximum hysteresis which, across all sites studied, is most pronounced during moisture‐limited conditions. These diurnal error patterns are consistent with models' diminished ability to accurately simulate the natural hysteresis of transpiration. We propose that the lack of representation of plant hydrodynamics is, in part, responsible for these error patterns. Key Points Land‐surface models produce subdaily patterns of latent heat flux error Error patterns are characterized by the stomatal conductance formulation used Current models lack a mechanism to simulate hysteretic transpirationPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108341/1/jgrg20246.pd

Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation

Data-model integration plays a critical role in assessing and improving our capacity to predict ecosystem dynamics. Similarly, the ability to attach quantitative statements of uncertainty around model forecasts is crucial for model assessment and interpretation and for setting field research priorities. Bayesian methods provide a rigorous data assimilation framework for these applications, especially for problems with multiple data constraints. However, the Markov chain Monte Carlo (MCMC) techniques underlying most Bayesian calibration can be prohibitive for computationally demanding models and large datasets. We employ an alternative method, Bayesian model emulation of sufficient statistics, that can approximate the full joint posterior density, is more amenable to parallelization, and provides an estimate of parameter sensitivity. Analysis involved informative priors constructed from a meta-analysis of the primary literature and specification of both model and data uncertainties, and it introduced novel approaches to autocorrelation corrections on multiple data streams and emulating the sufficient statistics surface. We report the integration of this method within an ecological workflow management software, Predictive Ecosystem Analyzer (PEcAn), and its application and validation with two process-based terrestrial ecosystem models: SIPNET and ED2. In a test against a synthetic dataset, the emulator was able to retrieve the true parameter values. A comparison of the emulator approach to standard brute-force MCMC involving multiple data constraints showed that the emulator method was able to constrain the faster and simpler SIPNET model's parameters with comparable performance to the brute-force approach but reduced computation time by more than 2 orders of magnitude. The emulator was then applied to calibration of the ED2 model, whose complexity precludes standard (brute-force) Bayesian data assimilation techniques. Both models are constrained after assimilation of the observational data with the emulator method, reducing the uncertainty around their predictions. Performance metrics showed increased agreement between model predictions and data. Our study furthers efforts toward reducing model uncertainties, showing that the emulator method makes it possible to efficiently calibrate complex models.</p