To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure email@example.com
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Ecosystem modeling, a pillar of the systems ecology paradigm (SEP), addresses questions such as, how much carbon and nitrogen are cycled within ecological sites, landscapes, or indeed the earth system? Or how are human activities modifying these flows? Modeling, when coupled with field and laboratory studies, represents the essence of the SEP in that they embody accumulated knowledge and generate hypotheses to test understanding of ecosystem processes and behavior. Initially, ecosystem models were primarily used to improve our understanding about how biophysical aspects of ecosystems operate. However, current ecosystem models are widely used to make accurate predictions about how large-scale phenomena such as climate change and management practices impact ecosystem dynamics and assess potential effects of these changes on economic activity and policy making. In sum, ecosystem models embedded in the SEP remain our best mechanism to integrate diverse types of knowledge regarding how the earth system functions and to make quantitative predictions that can be confronted with observations of reality. Modeling efforts discussed are the Century ecosystem model, DayCent ecosystem model, Grassland Ecosystem Model ELM, food web models, Savanna model, agent-based and coupled systems modeling, and Bayesian modeling.
Clarifying the relationship between depression symptoms and cardiometabolic and related health could clarify risk factors and treatment targets. The objective of this study was to assess whether depression symptoms in midlife are associated with the subsequent onset of cardiometabolic health problems.
The study sample comprised 787 male twin veterans with polygenic risk score data who participated in the Harvard Twin Study of Substance Abuse (‘baseline’) and the longitudinal Vietnam Era Twin Study of Aging (‘follow-up’). Depression symptoms were assessed at baseline [mean age 41.42 years (s.d. = 2.34)] using the Diagnostic Interview Schedule, Version III, Revised. The onset of eight cardiometabolic conditions (atrial fibrillation, diabetes, erectile dysfunction, hypercholesterolemia, hypertension, myocardial infarction, sleep apnea, and stroke) was assessed via self-reported doctor diagnosis at follow-up [mean age 67.59 years (s.d. = 2.41)].
Total depression symptoms were longitudinally associated with incident diabetes (OR 1.29, 95% CI 1.07–1.57), erectile dysfunction (OR 1.32, 95% CI 1.10–1.59), hypercholesterolemia (OR 1.26, 95% CI 1.04–1.53), and sleep apnea (OR 1.40, 95% CI 1.13–1.74) over 27 years after controlling for age, alcohol consumption, smoking, body mass index, C-reactive protein, and polygenic risk for specific health conditions. In sensitivity analyses that excluded somatic depression symptoms, only the association with sleep apnea remained significant (OR 1.32, 95% CI 1.09–1.60).
A history of depression symptoms by early midlife is associated with an elevated risk for subsequent development of several self-reported health conditions. When isolated, non-somatic depression symptoms are associated with incident self-reported sleep apnea. Depression symptom history may be a predictor or marker of cardiometabolic risk over decades.
Novel endometrial cancer (EC) early-detection approaches may reduce racial disparities in mortality. We conducted six community-based focus groups with White and Black women (N = 57 participants) in February-March 2020 to explore acceptability of a home-based tampon sampling approach for EC. Participants also completed a survey. Data were analyzed using qualitative content analysis. Awareness of EC and risk factors was low. Acceptability regarding home sampling was high, but participants expressed concerns about instruction complexity and potential risks. Black women reported lower comfort with tampons. Increasing EC awareness, self-efficacy, and familiarization with tampons would advance prospects for at-home sample collection for EC testing.
This is the first report on the association between trauma exposure and depression from the Advancing Understanding of RecOvery afteR traumA(AURORA) multisite longitudinal study of adverse post-traumatic neuropsychiatric sequelae (APNS) among participants seeking emergency department (ED) treatment in the aftermath of a traumatic life experience.
We focus on participants presenting at EDs after a motor vehicle collision (MVC), which characterizes most AURORA participants, and examine associations of participant socio-demographics and MVC characteristics with 8-week depression as mediated through peritraumatic symptoms and 2-week depression.
Eight-week depression prevalence was relatively high (27.8%) and associated with several MVC characteristics (being passenger v. driver; injuries to other people). Peritraumatic distress was associated with 2-week but not 8-week depression. Most of these associations held when controlling for peritraumatic symptoms and, to a lesser degree, depressive symptoms at 2-weeks post-trauma.
These observations, coupled with substantial variation in the relative strength of the mediating pathways across predictors, raises the possibility of diverse and potentially complex underlying biological and psychological processes that remain to be elucidated in more in-depth analyses of the rich and evolving AURORA database to find new targets for intervention and new tools for risk-based stratification following trauma exposure.
Associations of socioenvironmental features like urbanicity and neighborhood deprivation with psychosis are well-established. An enduring question, however, is whether these associations are causal. Genetic confounding could occur due to downward mobility of individuals at high genetic risk for psychiatric problems into disadvantaged environments.
We examined correlations of five indices of genetic risk [polygenic risk scores (PRS) for schizophrenia and depression, maternal psychotic symptoms, family psychiatric history, and zygosity-based latent genetic risk] with multiple area-, neighborhood-, and family-level risks during upbringing. Data were from the Environmental Risk (E-Risk) Longitudinal Twin Study, a nationally-representative cohort of 2232 British twins born in 1994–1995 and followed to age 18 (93% retention). Socioenvironmental risks included urbanicity, air pollution, neighborhood deprivation, neighborhood crime, neighborhood disorder, social cohesion, residential mobility, family poverty, and a cumulative environmental risk scale. At age 18, participants were privately interviewed about psychotic experiences.
Higher genetic risk on all indices was associated with riskier environments during upbringing. For example, participants with higher schizophrenia PRS (OR = 1.19, 95% CI = 1.06–1.33), depression PRS (OR = 1.20, 95% CI = 1.08–1.34), family history (OR = 1.25, 95% CI = 1.11–1.40), and latent genetic risk (OR = 1.21, 95% CI = 1.07–1.38) had accumulated more socioenvironmental risks for schizophrenia by age 18. However, associations between socioenvironmental risks and psychotic experiences mostly remained significant after covariate adjustment for genetic risk.
Genetic risk is correlated with socioenvironmental risk for schizophrenia during upbringing, but the associations between socioenvironmental risk and adolescent psychotic experiences appear, at present, to exist above and beyond this gene-environment correlation.
In 2019, a 42-year-old African man who works as an Ebola virus disease (EVD) researcher traveled from the Democratic Republic of Congo (DRC), near an ongoing EVD epidemic, to Philadelphia and presented to the Hospital of the University of Pennsylvania Emergency Department with altered mental status, vomiting, diarrhea, and fever. He was classified as a “wet” person under investigation for EVD, and his arrival activated our hospital emergency management command center and bioresponse teams. He was found to be in septic shock with multisystem organ dysfunction, including circulatory dysfunction, encephalopathy, metabolic lactic acidosis, acute kidney injury, acute liver injury, and diffuse intravascular coagulation. Critical care was delivered within high-risk pathogen isolation in the ED and in our Special Treatment Unit until a diagnosis of severe cerebral malaria was confirmed and EVD was definitively excluded.
This report discusses our experience activating a longitudinal preparedness program designed for rare, resource-intensive events at hospitals physically remote from any active epidemic but serving a high-volume international air travel port-of-entry.
This work focuses on understanding the formation of the first massive, passive galaxies in clusters, as a first step to the development of environmental trends seen at low redshift. Cl J1449 + 0856 is an excellent case to study this - a galaxy cluster at redshift z = 1.99 that already shows evidence of a virialised atmosphere. Here we highlight two recent results: the discovery of merger-driven star formation and highly-excited molecular gas in galaxies at the core of Cl J1449, along with the lowest-mass Sunyaev-Zel’dovich detection to date.
The DIVING3D Survey (Deep Integral Field Spectrograph View of Nuclei of Galaxies) aims to observe, with high signal/noise and high spatial resolution, a statistically complete sample of southern galaxies brighter than B = 12.0 The main objectives of this survey are to study: 1) the nuclear emission line properties; 2) the circumnuclear emission line properties; 3) the central stellar kinematics and 4) the central stellar archaeology. Preliminary results of individual or small groups of galaxies have been published in 18 papers.
We present spatially resolved kinematics of ionized gas in the narrow-line region (NLR) and extended narrow-line region (ENLR) in a sample of nearby active galaxies. Utilizing long-slit spectroscopy from Apache Point Observatory (APO)13s ARC 3.5 m Telescope and Hubble Space Telescope (HST) we analyzed the strong λ5007 Å [O III] emission line profiles and mapped the radial velocity distribution of gas at increasing radii from the center. We identified the extents of Active Galactic Nuclei (AGN) driven outflows in our sample and determined the distances at which the observed gas kinematics is being dominated by the rotation of the host galaxy. We also measured the effectiveness of radiative driving of the ionized gas using mass distribution profiles calculated with two-dimensional modeling of surface brightness profiles in our targets. Finally, we compared our kinematic results of the outflow sizes with the maximum distances at which the gas is being radiatively driven to investigate whether these outflows are capable of disrupting or evacuating the star-forming gas at these distances.
We present the first results of the Deep Integral Field Spectroscopy View of Nuclei of Galaxies (DIVING3D) survey, obtained from the analysis of the nuclear emission-line spectra of a sub-sample we call mini-DIVING3D, including all southern galaxies with B < 11.2 and |b| >15°. In comparison with previous studies, very few galaxies were classified as Transition objects. A possible explanation is that at least part of the Transition objects are composite systems, with a central low-ionization nuclear emission-line region (LINER) contaminated by the emission from circumnuclear H II regions. The high spatial resolution of the DIVING3D survey allowed us to isolate the nuclear emission from circumnuclear contaminations, reducing the number of Transition objects.
We investigate the processes of active galactic nuclei (AGN) feeding and feedback in the narrow line regions (NLRs) and host galaxies of nearby AGN through spatially resolved spectroscopy with the Gemini Near-Infrared Integral Field Spectrograph (NIFS) and the Hubble Space Telescope’s Space Telescope Imaging Spectrograph (STIS). We examine the connection between nuclear and galactic inflows and outflows by adding long-slit spectra of the host galaxies from Apache Point Observatory. We demonstrate that nearby AGN can be fueled by a variety of mechanisms. We find that the NLR kinematics can often be explained by in situ ionization and radiative acceleration of ambient gas, often in the form of dusty molecular spirals that may be the fueling flow to the AGN.
In this work, we present preliminary results regarding the nuclear emission lines of a statistically complete sample of 56 early-type galaxies that are part of the Deep Integral Field Spectroscopy View of Nuclei of Galaxies (DIVING3D) Project. All early type galaxies (ETGs) were observed with the Gemini Multi-Object Spectrograph Integral Field Unit (GMOS-IFU) installed on the Gemini South Telescope. We detected emission lines in 93% of the sample, mostly low-ionization nuclear emission-line region galaxies (LINERs). We did not find Transition Objects nor H II regions in the sample. Type 1 objects are seen in ∼23% of the galaxies.
In the past decade, network analysis (NA) has been applied to psychopathology to quantify complex symptom relationships. This statistical technique has demonstrated much promise, as it provides researchers the ability to identify relationships across many symptoms in one model and can identify central symptoms that may predict important clinical outcomes. However, network models are highly influenced by node selection, which could limit the generalizability of findings. The current study (N = 6850) tests a comprehensive, cognitive–behavioral model of eating-disorder symptoms using items from two, widely used measures (Eating Disorder Examination Questionnaire and Eating Pathology Symptoms Inventory).
We used NA to identify central symptoms and compared networks across the duration of illness (DOI), as chronicity is one of the only known predictors of poor outcome in eating disorders (EDs).
Our results suggest that eating when not hungry and feeling fat were the most central symptoms across groups. There were no significant differences in network structure across DOI, meaning the connections between symptoms remained relatively consistent. However, differences emerged in central symptoms, such that cognitive symptoms related to overvaluation of weight/shape were central in individuals with shorter DOI, and behavioral central symptoms emerged more in medium and long DOI.
Our results have important implications for the treatment of individuals with enduring EDs, as they may have a different core, maintaining symptoms. Additionally, our findings highlight the importance of using comprehensive, theoretically- or empirically-derived models for NA.
The Murchison Widefield Array (MWA) is an open access telescope dedicated to studying the low-frequency (80–300 MHz) southern sky. Since beginning operations in mid-2013, the MWA has opened a new observational window in the southern hemisphere enabling many science areas. The driving science objectives of the original design were to observe 21 cm radiation from the Epoch of Reionisation (EoR), explore the radio time domain, perform Galactic and extragalactic surveys, and monitor solar, heliospheric, and ionospheric phenomena. All together
programs recorded 20 000 h producing 146 papers to date. In 2016, the telescope underwent a major upgrade resulting in alternating compact and extended configurations. Other upgrades, including digital back-ends and a rapid-response triggering system, have been developed since the original array was commissioned. In this paper, we review the major results from the prior operation of the MWA and then discuss the new science paths enabled by the improved capabilities. We group these science opportunities by the four original science themes but also include ideas for directions outside these categories.
The Murchison Widefield Array (MWA) is an electronically steered low-frequency (<300 MHz) radio interferometer, with a ‘slew’ time less than 8 s. Low-frequency (∼100 MHz) radio telescopes are ideally suited for rapid response follow-up of transients due to their large field of view, the inverted spectrum of coherent emission, and the fact that the dispersion delay between a 1 GHz and 100 MHz pulse is on the order of 1–10 min for dispersion measures of 100–2000 pc/cm3. The MWA has previously been used to provide fast follow-up for transient events including gamma-ray bursts (GRBs), fast radio bursts (FRBs), and gravitational waves, using systems that respond to gamma-ray coordinates network packet-based notifications. We describe a system for automatically triggering MWA observations of such events, based on Virtual Observatory Event standard triggers, which is more flexible, capable, and accurate than previous systems. The system can respond to external multi-messenger triggers, which makes it well-suited to searching for prompt coherent radio emission from GRBs, the study of FRBs and gravitational waves, single pulse studies of pulsars, and rapid follow-up of high-energy superflares from flare stars. The new triggering system has the capability to trigger observations in both the regular correlator mode (limited to ≥0.5 s integrations) and using the Voltage Capture System (VCS, 0.1 ms integration) of the MWA and represents a new mode of operation for the MWA. The upgraded standard correlator triggering capability has been in use since MWA observing semester 2018B (July–Dec 2018), and the VCS and buffered mode triggers will become available for observing in a future semester.
A new fossil site in a previously unexplored part of western Madagascar (the Beanka Protected Area) has yielded remains of many recently extinct vertebrates, including giant lemurs (Babakotia radofilai, Palaeopropithecus kelyus, Pachylemur sp., and Archaeolemur edwardsi), carnivores (Cryptoprocta spelea), the aardvark-like Plesiorycteropus sp., and giant ground cuckoos (Coua). Many of these represent considerable range extensions. Extant species that were extirpated from the region (e.g., Prolemur simus) are also present. Calibrated radiocarbon ages for 10 bones from extinct primates span the last three millennia. The largely undisturbed taphonomy of bone deposits supports the interpretation that many specimens fell in from a rock ledge above the entrance. Some primates and other mammals may have been prey items of avian predators, but human predation is also evident. Strontium isotope ratios (87Sr/86Sr) suggest that fossils were local to the area. Pottery sherds and bones of extinct and extant vertebrates with cut and chop marks indicate human activity in previous centuries. Scarcity of charcoal and human artifacts suggests only occasional visitation to the site by humans. The fossil assemblage from this site is unusual in that, while it contains many sloth lemurs, it lacks ratites, hippopotami, and crocodiles typical of nearly all other Holocene subfossil sites on Madagascar.
TwinsUK is the largest cohort of community-dwelling adult twins in the UK. The registry comprises over 14,000 volunteer twins (14,838 including mixed, single and triplets); it is predominantly female (82%) and middle-aged (mean age 59). In addition, over 1800 parents and siblings of twins are registered volunteers. During the last 27 years, TwinsUK has collected numerous questionnaire responses, physical/cognitive measures and biological measures on over 8500 subjects. Data were collected alongside four comprehensive phenotyping clinical visits to the Department of Twin Research and Genetic Epidemiology, King’s College London. Such collection methods have resulted in very detailed longitudinal clinical, biochemical, behavioral, dietary and socioeconomic cohort characterization; it provides a multidisciplinary platform for the study of complex disease during the adult life course, including the process of healthy aging. The major strength of TwinsUK is the availability of several ‘omic’ technologies for a range of sample types from participants, which includes genomewide scans of single-nucleotide variants, next-generation sequencing, metabolomic profiles, microbiomics, exome sequencing, epigenetic markers, gene expression arrays, RNA sequencing and telomere length measures. TwinsUK facilitates and actively encourages sharing the ‘TwinsUK’ resource with the scientific community — interested researchers may request data via the TwinsUK website (http://twinsuk.ac.uk/resources-for-researchers/access-our-data/) for their own use or future collaboration with the study team. In addition, further cohort data collection is planned via the Wellcome Open Research gateway (https://wellcomeopenresearch.org/gateways). The current article presents an up-to-date report on the application of technological advances, new study procedures in the cohort and future direction of TwinsUK.