Distress Tolerance in Relation to Treatment Persistence, Engagement, and Improvement in an Exposure-Based Treatment for Sexually Abused Incarcerated Women

Incarcerated populations are disproportionately affected by traumatic experiences and symptoms of posttraumatic stress disorder (PTSD). Many effective treatments for PTSD utilize exposure-based techniques which require engaging with emotionally distressing content. However, individuals with PTSD and low distress tolerance (DT) are more likely than those with PTSD and higher DT to engage in avoidant coping behaviors and have relatively high treatment attrition rates in general. This study explored relations between DT and treatment persistence, engagement, and improvement in incarcerated women (N = 85) enrolled in an 8-week exposure-based sexual assault recovery group at a minimum-security prison. I hypothesized lower baseline levels of DT would be related to lower treatment persistence and engagement with distressing content during treatment. I also hypothesized lower baseline DT would be related to lower treatment gains and higher levels of post-treatment symptoms of PTSD and depression. Finally, I hypothesized completing exposure-based group therapy would be associated with increases in DT post-treatment. Contrary to hypotheses, no significant relation was found between baseline DT and treatment persistence. Furthermore, lower levels of baseline DT were associated with higher levels of emotional engagement during exposure, which was the opposite of what was predicted. Also contrary to expectations, non-linear effects were found for relations between baseline DT and improvements in internalizing symptoms: lower levels of baseline DT were associated with greater symptom improvement than moderate to high levels of baseline DT. Consistent with hypotheses, DT significantly improved from pre- to post-treatment. Qualitative analyses of respondents at post-treatment revealed concerns of dropping out related to fear of sharing (e.g., trust violations, increased symptoms) and motivations for staying related to healing and commitment. Themes did not vary by baseline DT. Overall, findings suggest participants with lower baseline DT can not only benefit from exposure-based therapy, but were more emotionally engaged in exposure and demonstrated greater internalizing symptoms improvement than those with moderate to high baseline DT

Dopamine neurons modulate neural encoding and expression of depression-related behaviour

Major depression is characterized by diverse debilitating symptoms that include hopelessness and anhedonia1. Dopamine neurons involved in reward and motivation are among many neural populations that have been hypothesized to be relevant, and certain antidepressant treatments, including medications and brain stimulation therapies, can influence the complex dopamine system. Until now it has not been possible to test this hypothesis directly, even in animal models, as existing therapeutic interventions are unable to specifically target dopamine neurons. Here we investigated directly the causal contributions of defined dopamine neurons to multidimensional depression-like phenotypes induced by chronic mild stress, by integrating behavioural, pharmacological, optogenetic and electrophysiological methods in freely moving rodents. We found that bidirectional control (inhibition or excitation) of specified midbrain dopamine neurons immediately and bidirectionally modulates (induces or relieves) multiple independent depression symptoms caused by chronic stress. By probing the circuit implementation of these effects, we observed that optogenetic recruitment of these dopamine neurons potently alters the neural encoding of depression-related behaviours in the downstream nucleus accumbens of freely moving rodents, suggesting that processes affecting depression symptoms may involve alterations in the neural encoding of action in limbic circuitry

The Influence of pCO2 and Temperature on Gene Expression of Carbon and Nitrogen Pathways in Trichodesmium IMS101

Growth, protein amount, and activity levels of metabolic pathways in Trichodesmium are influenced by environmental changes such as elevated pCO2 and temperature. This study examines changes in the expression of essential metabolic genes in Trichodesmium grown under a matrix of pCO2 (400 and 900 µatm) and temperature (25 and 31°C). Using RT-qPCR, we studied 21 genes related to four metabolic functional groups: CO2 concentrating mechanism (bicA1, bicA2, ccmM, ccmK2, ccmK3, ndhF4, ndhD4, ndhL, chpX), energy metabolism (atpB, sod, prx, glcD), nitrogen metabolism (glnA, hetR, nifH), and inorganic carbon fixation and photosynthesis (rbcL, rca, psaB, psaC, psbA). nifH and most photosynthetic genes exhibited relatively high abundance and their expression was influenced by both environmental parameters. A two to three orders of magnitude increase was observed for glnA and hetR only when both pCO2 and temperature were elevated. CO2 concentrating mechanism genes were not affected by pCO2 and temperature and their expression levels were markedly lower than that of the nitrogen metabolism and photosynthetic genes. Many of the CO2 concentrating mechanism genes were co-expressed throughout the day. Our results demonstrate that in Trichodesmium, CO2 concentrating mechanism genes are constitutively expressed. Co-expression of genes from different functional groups were frequently observed during the first half of the photoperiod when oxygenic photosynthesis and N2 fixation take place, pointing at the tight and complex regulation of gene expression in Trichodesmium. Here we provide new data linking environmental changes of pCO2 and temperature to gene expression in Trichodesmium. Although gene expression indicates an active metabolic pathway, there is often an uncoupling between transcription and enzyme activity, such that transcript level cannot usually be directly extrapolated to metabolic activity

Single-Turnover Variable Chlorophyll Fluorescence as a Tool for Assessing Phytoplankton Photosynthesis and Primary Productivity: Opportunities, Caveats and Recommendations

Phytoplankton photosynthetic physiology can be investigated through single-turnover variable chlorophyll fluorescence (ST-ChlF) approaches, which carry unique potential to autonomously collect data at high spatial and temporal resolution. Over the past decades, significant progress has been made in the development and application of ST-ChlF methods in aquatic ecosystems, and in the interpretation of the resulting observations. At the same time, however, an increasing number of sensor types, sampling protocols, and data processing algorithms have created confusion and uncertainty among potential users, with a growing divergence of practice among different research groups. In this review, we assist the existing and upcoming user community by providing an overview of current approaches and consensus recommendations for the use of ST-ChlF measurements to examine in-situ phytoplankton productivity and photo-physiology. We argue that a consistency of practice and adherence to basic operational and quality control standards is critical to ensuring data inter-comparability. Large datasets of inter-comparable and globally coherent ST-ChlF observations hold the potential to reveal large-scale patterns and trends in phytoplankton photo-physiology, photosynthetic rates and bottom-up controls on primary productivity. As such, they hold great potential to provide invaluable physiological observations on the scales relevant for the development and validation of ecosystem models and remote sensing algorithms

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019 : a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2·72 (95% uncertainty interval [UI] 2·66–2·79) in 2000 to 2·31 (2·17–2·46) in 2019. Global annual livebirths increased from 134·5 million (131·5–137·8) in 2000 to a peak of 139·6 million (133·0–146·9) in 2016. Global livebirths then declined to 135·3 million (127·2–144·1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2·1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27·1% (95% UI 26·4–27·8) of global livebirths. Global life expectancy at birth increased from 67·2 years (95% UI 66·8–67·6) in 2000 to 73·5 years (72·8–74·3) in 2019. The total number of deaths increased from 50·7 million (49·5–51·9) in 2000 to 56·5 million (53·7–59·2) in 2019. Under-5 deaths declined from 9·6 million (9·1–10·3) in 2000 to 5·0 million (4·3–6·0) in 2019. Global population increased by 25·7%, from 6·2 billion (6·0–6·3) in 2000 to 7·7 billion (7·5–8·0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58·6 years (56·1–60·8) in 2000 to 63·5 years (60·8–66·1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

The Somatic Genomic Landscape of Glioblastoma

We describe the landscape of somatic genomic alterations based on multi-dimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer

Measuring early life adversity: a dimensional approach

Exposure to adversity in childhood is associated with elevations in numerous physical and mental health outcomes across the life course. The biological embedding of early experience during periods of developmental plasticity is one pathway that contributes to these associations. Dimensional models specify mechanistic pathways linking different dimensions of adversity to health and well-being outcomes later in life. While findings from existing studies testing these dimensions have provided promising preliminary support for these models, less agreement exists about how to measure the experiences that comprise each dimension. Here, we review existing approaches to measuring two dimensions of adversity: threat and deprivation. We recommend specific measures for measuring these constructs and, when possible, document when the same measure can be used by different reporters and across the lifespan to maximize the utility with which these recommendations can be applied. Through this approach, we hope to stimulate progress in understanding how particular dimensions of early environmental experience contribute to lifelong health