Ectomycorrhizal communities of ponderosa pine and lodgepole pine in the south-central Oregon pumice zone

Forest ecosystems of the Pacific Northwest of the USA are changing as a result of climate change. Specifically, rise of global temperatures, decline of winter precipitation, earlier loss of snowpack, and increased summer drought are altering the range of Pinus contorta. Simultaneously, flux in environmental conditions within the historic P. contorta range may facilitate the encroachment of P. ponderosa into P. contorta territory. Furthermore, successful pine species migration may be constrained by the distribution or co-migration of ectomycorrhizal fungi (EMF). Knowledge of the linkages among soil fungal diversity, community structure, and environmental factors is critical to understanding the organization and stability of pine ecosystems. The objectives of this study were to establish a foundational knowledge of the EMF communities of P. ponderosa and P. contorta in the Deschutes National Forest, OR, USA, and to examine soil characteristics associated with community composition. We examined EMF root tips of P. ponderosa and P. contorta in soil cores and conducted soil chemistry analysis for P. ponderosa cores. Results indicate that Cenococcum geophilum, Rhizopogon salebrosus, and Inocybe flocculosa were dominant in both P. contorta and P. ponderosa soil cores. Rhizopogon spp. were ubiquitous in P. ponderosa cores. There was no significant difference in the species composition of EMF communities of P. ponderosa and P. contorta. Ordination analysis of P. ponderosa soils suggested that soil pH, plant-available phosphorus (Bray), total phosphorus (P), carbon (C), mineralizable nitrogen (N), ammonium (NH₄), and nitrate (NO₃) are driving EMF community composition in P. ponderosa stands. We found a significant linear relationship between EMF species richness and mineralizable N. In conclusion, P. ponderosa and P. contorta, within the Deschutes National Forest, share the same dominant EMF species, which implies that P. ponderosa may be able to successfully establish within the historic P. contorta range and dominant EMF assemblages may be conserved.Keywords: Pinus ponderosa, Pine species migration, Climate change, Ectomycorrhizal communities, Pinus contort

Insights into the O : C-dependent mechanisms controlling the evaporation of α-pinene secondary organic aerosol particles

The volatility of oxidation products of volatile organic compounds (VOCs) in the atmosphere is a key factor to determine if they partition into the particle phase contributing to secondary organic aerosol (SOA) mass. Thus, linking volatility and measured particle composition will provide insights into SOA formation and its fate in the atmosphere. We produced α-pinene SOA with three different oxidation levels (characterized by average oxygen-to-carbon ratio; O:C‾=0.53, 0.69, and 0.96) in an oxidation flow reactor. We investigated the particle volatility by isothermal evaporation in clean air as a function of relative humidity (RH &lt;2&thinsp;%, 40&thinsp;%, and 80&thinsp;%) and used a filter-based thermal desorption method to gain volatility and chemical composition information. We observed reduced particle evaporation for particles with increasing O:C‾ ratio, indicating that particles become more resilient to evaporation with oxidative aging. Particle evaporation was increased in the presence of water vapour and presumably particulate water; at the same time the resistance of the residual particles to thermal desorption was increased as well. For SOA with O:C‾=0.96, the unexpectedly large increase in mean thermal desorption temperature and changes in the thermogram shapes under wet conditions (80&thinsp;% RH) were an indication of aqueous phase chemistry. For the lower O:C‾ cases, some water-induced composition changes were observed. However, the enhanced evaporation under wet conditions could be explained by the reduction in particle viscosity from the semi-solid to liquid-like range, and the observed higher desorption temperature of the residual particles is a direct consequence of the increased removal of high-volatility and the continued presence of low-volatility compounds.</p

Eight years of sub-micrometre organic aerosol composition data from the boreal forest characterized using a machine-learning approach

The Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) II, located within the boreal forest of Finland, is a unique station in the world due to the wide range of long-term measurements tracking the Earth-atmosphere interface. In this study, we characterize the composition of organic aerosol (OA) at SMEAR II by quantifying its driving constituents. We utilize a multi-year data set of OA mass spectra measured in situ with an Aerosol Chemical Speciation Monitor (ACSM) at the station. To our knowledge, this mass spectral time series is the longest of its kind published to date. Similarly to other previously reported efforts in OA source apportionment from multi-seasonal or multi-annual data sets, we approached the OA characterization challenge through positive matrix factorization (PMF) using a rolling window approach. However, the existing methods for extracting minor OA components were found to be insufficient for our rather remote site. To overcome this issue, we tested a new statistical analysis framework. This included unsupervised feature extraction and classification stages to explore a large number of unconstrained PMF runs conducted on the measured OA mass spectra. Anchored by these results, we finally constructed a relaxed chemical mass balance (CMB) run that resolved different OA components from our observations. The presented combination of statistical tools provided a data-driven analysis methodology, which in our case achieved robust solutions with minimal subjectivity. Following the extensive statistical analyses, we were able to divide the 2012-2019 SMEAR II OA data (mass concentration interquartile range (IQR): 0.7, 1.3, and 2.6 mu gm(-3)) into three sub-categories - low-volatility oxygenated OA (LV-OOA), semi-volatile oxygenated OA (SV-OOA), and primary OA (POA) - proving that the tested methodology was able to provide results consistent with literature. LV-OOA was the most dominant OA type (organic mass fraction IQR: 49 %, 62 %, and 73 %). The seasonal cycle of LV-OOA was bimodal, with peaks both in summer and in February. We associated the wintertime LV-OOA with anthropogenic sources and assumed biogenic influence in LV-OOA formation in summer. Through a brief trajectory analysis, we estimated summertime natural LV-OOA formation of tens of ngm 3 h 1 over the boreal forest. SV-OOA was the second highest contributor to OA mass (organic mass fraction IQR: 19 %, 31 %, and 43 %). Due to SV-OOA's clear peak in summer, we estimate biogenic processes as the main drivers in its formation. Unlike for LV-OOA, the highest SV-OOA concentrations were detected in stable summertime nocturnal surface layers. Two nearby sawmills also played a significant role in SV-OOA production as also exemplified by previous studies at SMEAR II. POA, taken as a mix of two different OA types reported previously, hydrocarbon-like OA (HOA) and biomass burning OA (BBOA), made up a minimal OA mass fraction (IQR: 2 %, 6 %, and 13 %). Notably, the quantification of POA at SMEAR II using ACSM data was not possible following existing rolling PMF methodologies. Both POA organic mass fraction and mass concentration peaked in winter. Its appearance at SMEAR II was linked to strong southerly winds. Similar wind direction and speed dependence was not observed among other OA types. The high wind speeds probably enabled the POA transport to SMEAR II from faraway sources in a relatively fresh state. In the event of slower wind speeds, POA likely evaporated and/or aged into oxidized organic aerosol before detection. The POA organic mass fraction was significantly lower than reported by aerosol mass spectrometer (AMS) measurements 2 to 4 years prior to the ACSM measurements. While the co-located long-term measurements of black carbon supported the hypothesis of higher POA loadings prior to year 2012, it is also possible that short-term (POA) pollution plumes were averaged out due to the slow time resolution of the ACSM combined with the further 3 h data averaging needed to ensure good signal-to-noise ratios (SNRs). Despite the length of the ACSM data set, we did not focus on quantifying long-term trends of POA (nor other components) due to the high sensitivity of OA composition to meteorological anomalies, the occurrence of which is likely not normally distributed over the 8-year measurement period. Due to the unique and realistic seasonal cycles and meteorology dependences of the independent OA subtypes complemented by the reasonably low degree of unexplained OA variability, we believe that the presented data analysis approach performs well. Therefore, we hope that these results encourage also other researchers possessing several-yearlong time series of similar data to tackle the data analysis via similar semi- or unsupervised machine-learning approaches. This way the presented method could be further optimized and its usability explored and evaluated also in other environments.Peer reviewe

SARS-CoV-2 infection and antibody seroprevalence in routine surveillance patients, healthcare workers and general population in Kita region, Mali: an observational study 2020–2021

Objective: To estimate the degree of SARS-CoV-2 transmission among healthcare workers (HCWs) and general population in Kita region of Mali. Design: Routine surveillance in 12 health facilities, HCWs serosurvey in five health facilities and community serosurvey in 16 villages in or near Kita town, Mali. Setting: Kita region, western Mali; local health centres around the central (regional) referral health centre. Participants: Patients in routine surveillance, HCWs in local health centres and community members of all ages in populations associated with study health centres. Main outcome measures: Seropositivity of ELISA test detecting SARS-CoV-2-specific total antibodies and real-time RT-PCR confirmed SARS-CoV-2 infection. Results: From 2392 routine surveillance samples, 68 (2.8%, 95% CI: 2.2% to 3.6%) tested positive for SARS-CoV-2 by RT-PCR. The monthly positivity rate was 0% in June–August 2020 and gradually increased to 6% by December 2020 and 6.2% by January 2021, then declined to 5.5%, 3.3%, 3.6% and 0.8% in February, March, April and May 2021, respectively. From 397 serum samples collected from 113 HCWs, 175 (44.1%, 95% CI: 39.1% to 49.1%) were positive for SARS-CoV-2 antibodies. The monthly seroprevalence was around 10% from September to November 2020 and increased to over 40% from December 2020 to May 2021. For community serosurvey in December 2020, overall seroprevalence of SARS-CoV-2 antibodies was 27.7%. The highest age-stratified seroprevalence was observed in participants aged 60–69 years (45.5%, 95% CI: 32.3% to 58.6%). The lowest was in children aged 0–9 years (14.0%, 95% CI: 7.4% to 20.6%). Conclusions: SARS-CoV-2 in rural Mali is much more widespread than assumed by national testing data and particularly in the older population and frontline HCWs. The observation is contrary to the widely expressed view, based on limited data, that COVID-19 infection rates were lower in 2020–2021 in West Africa than in other settings

Statistical analysis plan for the LAKANA trial: a cluster-randomized, placebo-controlled, double-blinded, parallel group, three-arm clinical trial testing the effects of mass drug administration of azithromycin on mortality and other outcomes among 1–11-month-old infants in Mali

BACKGROUND:The Large-scale Assessment of the Key health-promoting Activities of two New mass drug administration regimens with Azithromycin (LAKANA) trial in Mali aims to evaluate the efficacy and safety of azithromycin (AZI) mass drug administration (MDA) to 1–11-month-old infants as well as the impact of the intervention on antimicrobial resistance (AMR) and mechanisms of action of azithromycin. To improve the transparency and quality of this clinical trial, we prepared this statistical analysis plan (SAP). METHODS/DESIGN: LAKANA is a cluster randomized trial that aims to address the mortality and health impacts of biannual and quarterly AZI MDA. AZI is given to 1–11-month-old infants in a high-mortality setting where a seasonal malaria chemoprevention (SMC) program is in place. The participating villages are randomly assigned to placebo (control), two-dose AZI (biannual azithromycin-MDA), and four-dose AZI (quarterly azithromycin-MDA) in a 3:4:2 ratio. The primary outcome of the study is mortality among the intention-to-treat population of 1–11-month-old infants. We will evaluate relative risk reduction between the study arms using a mixed-effects Poisson model with random intercepts for villages, using log link function with person-years as an offset variable. We will model outcomes related to secondary objectives of the study using generalized linear models with considerations on clustering. CONCLUSION: The SAP written prior to data collection completion will help avoid reporting bias and data-driven analysis for the primary and secondary aims of the trial. If there are deviations from the analysis methods described here, they will be described and justified in the publications of the trial results. TRIAL REGISTRATION: ClinicalTrials.gov ID NCT04424511. Registered on 11 June 2020

Developing a digital intervention for cancer survivors: an evidence-, theory- and person-based approach

This paper illustrates a rigorous approach to developing digital interventions using an evidence-, theory- and person-based approach. Intervention planning included a rapid scoping review which identified cancer survivors’ needs, including barriers and facilitators to intervention success. Review evidence (N=49 papers) informed the intervention’s Guiding Principles, theory-based behavioural analysis and logic model. The intervention was optimised based on feedback on a prototype intervention through interviews (N=96) with cancer survivors and focus groups with NHS staff and cancer charity workers (N=31). Interviews with cancer survivors highlighted barriers to engagement, such as concerns about physical activity worsening fatigue. Focus groups highlighted concerns about support appointment length and how to support distressed participants. Feedback informed intervention modifications, to maximise acceptability, feasibility and likelihood of behaviour change. Our systematic method for understanding user views enabled us to anticipate and address important barriers to engagement. This methodology may be useful to others developing digital interventions

Can We Really Prevent Suicide?

Every year, suicide is among the top 20 leading causes of death globally for all ages. Unfortunately, suicide is difficult to prevent, in large part because the prevalence of risk factors is high among the general population. In this review, clinical and psychological risk factors are examined and methods for suicide prevention are discussed. Prevention strategies found to be effective in suicide prevention include means restriction, responsible media coverage, and general public education, as well identification methods such as screening, gatekeeper training, and primary care physician education. Although the treatment for preventing suicide is difficult, follow-up that includes pharmacotherapy, psychotherapy, or both may be useful. However, prevention methods cannot be restricted to the individual. Community, social, and policy interventions will also be essentia

Constraints on Nucleon Decay via "Invisible" Modes from the Sudbury Neutrino Observatory

Data from the Sudbury Neutrino Observatory have been used to constrain the lifetime for nucleon decay to ``invisible'' modes, such as n -> 3 nu. The analysis was based on a search for gamma-rays from the de-excitation of the residual nucleus that would result from the disappearance of either a proton or neutron from O16. A limit of tau_inv > 2 x 10^{29} years is obtained at 90% confidence for either neutron or proton decay modes. This is about an order of magnitude more stringent than previous constraints on invisible proton decay modes and 400 times more stringent than similar neutron modes.Comment: Update includes missing efficiency factor (limits change by factor of 2) Submitted to Physical Review Letter

A Search for Neutrinos from the Solar hep Reaction and the Diffuse Supernova Neutrino Background with the Sudbury Neutrino Observatory

A search has been made for neutrinos from the hep reaction in the Sun and from the diffus

Stigma and Self-Stigma in Addiction

Addictions are commonly accompanied by a sense of shame or self-stigmatization. Self-stigmatization results from public stigmatization in a process leading to the internalization of the social opprobrium attaching to the negative stereotypes associated with addiction. We offer an account of how this process works in terms of a range of looping effects, and this leads to our main claim that for a significant range of cases public stigma figures in the social construction of addiction. This rests on a social constructivist account in which those affected by public stigmatization internalize its norms. Stigma figures as part-constituent of the dynamic process in which addiction is formed. Our thesis is partly theoretical, partly empirical, as we source our claims about the process of internalization from interviews with people in treatment for substance use problems