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Antidepressant medication and interpersonal psychotherapy (IPT) are both recommended interventions in depression treatment guidelines based on literature reviews and meta-analyses. However, ‘conventional’ meta-analyses comparing their efficacy are limited by their reliance on reported study-level information and a narrow focus on depression outcome measures assessed at treatment completion. Individual participant data (IPD) meta-analysis, considered the gold standard in evidence synthesis, can improve the quality of the analyses when compared with conventional meta-analysis.
We describe the protocol for a systematic review and IPD meta-analysis comparing the efficacy of antidepressants and IPT for adult acute-phase depression across a range of outcome measures, including depressive symptom severity as well as functioning and well-being, at both post-treatment and follow-up (PROSPERO: CRD42020219891).
We will conduct a systematic literature search in PubMed, PsycINFO, Embase and the Cochrane Library to identify randomised clinical trials comparing antidepressants and IPT in the acute-phase treatment of adults with depression. We will invite the authors of these studies to share the participant-level data of their trials. One-stage IPD meta-analyses will be conducted using mixed-effects models to assess treatment effects at post-treatment and follow-up for all outcome measures that are assessed in at least two studies.
This will be the first IPD meta-analysis examining antidepressants versus IPT efficacy. This study has the potential to enhance our knowledge of depression treatment by comparing the short- and long-term effects of two widely used interventions across a range of outcome measures using state-of-the-art statistical techniques.
Despite their legal protection status, protected areas (PAs) can benefit from priority ranks when ongoing threats to their biodiversity and habitats outpace the financial resources available for their conservation. It is essential to develop methods to prioritize PAs that are not computationally demanding in order to suit stakeholders in developing countries where technical and financial resources are limited. We used expert knowledge-derived biodiversity measures to generate individual and aggregate priority ranks of 98 mostly terrestrial PAs on Madagascar. The five variables used were state of knowledge (SoK), forest loss, forest loss acceleration, PA size and relative species diversity, estimated by using standardized residuals from negative binomial models of SoK regressed onto species diversity. We compared our aggregate ranks generated using unweighted averages and principal component analysis (PCA) applied to each individual variable with those generated via Markov chain (MC) and PageRank algorithms. SoK significantly affected the measure of species diversity and highlighted areas where more research effort was needed. The unweighted- and PCA-derived ranks were strongly correlated, as were the MC and PageRank ranks. However, the former two were weakly correlated with the latter two. We recommend using these methods simultaneously in order to provide decision-makers with the flexibility to prioritize those PAs in need of additional research and conservation efforts.
We present a detailed overview of the cosmological surveys that we aim to carry out with Phase 1 of the Square Kilometre Array (SKA1) and the science that they will enable. We highlight three main surveys: a medium-deep continuum weak lensing and low-redshift spectroscopic HI galaxy survey over 5 000 deg2; a wide and deep continuum galaxy and HI intensity mapping (IM) survey over 20 000 deg2 from
$z = 0.35$
to 3; and a deep, high-redshift HI IM survey over 100 deg2 from
$z = 3$
to 6. Taken together, these surveys will achieve an array of important scientific goals: measuring the equation of state of dark energy out to
$z \sim 3$
with percent-level precision measurements of the cosmic expansion rate; constraining possible deviations from General Relativity on cosmological scales by measuring the growth rate of structure through multiple independent methods; mapping the structure of the Universe on the largest accessible scales, thus constraining fundamental properties such as isotropy, homogeneity, and non-Gaussianity; and measuring the HI density and bias out to
$z = 6$
. These surveys will also provide highly complementary clustering and weak lensing measurements that have independent systematic uncertainties to those of optical and near-infrared (NIR) surveys like Euclid, LSST, and WFIRST leading to a multitude of synergies that can improve constraints significantly beyond what optical or radio surveys can achieve on their own. This document, the 2018 Red Book, provides reference technical specifications, cosmological parameter forecasts, and an overview of relevant systematic effects for the three key surveys and will be regularly updated by the Cosmology Science Working Group in the run up to start of operations and the Key Science Programme of SKA1.
As bottom water warms, destabilisation of gas hydrates may increase the extent of methane-rich sediments. The authors present an assessment of organic carbon processing by the benthic community in methane-rich sediments, including one of the first investigations of inorganic C fixation in a non-hydrothermal vent setting. This topic was previously poorly studied, and there is much need to fill the gaps in knowledge of such ecosystems. The authors hypothesized that benthic C fixation would occur, and that a high biomass macrofaunal community would play a substantial role in organic C cycling. Experiments were conducted at a 257 m deep site off South Georgia. Sediment cores were amended with 13C and 15N labelled algal detritus, or 13C labelled bicarbonate solution. In the bicarbonate experiment, labelling of bacteria-specific phospholipid fatty acids provided direct evidence of benthic C fixation, with transfer of fixed C to macrofauna and dissolved organic carbon (DOC). In the algae experiment, macrofauna played an active role in organic carbon cycling. Compared to similar experiments, low temperature supressed the rates of community respiration and macrofaunal C uptake. While benthic C fixation occurred, the biological processing of organic carbon was dominantly controlled by low temperature and high photic zone productivity.
Patient expectancy is an important source of placebo effects in antidepressant clinical trials, but all prior studies measured expectancy prior to the initiation of medication treatment. Little is known about how expectancy changes during the course of treatment and how such changes influence clinical outcome. Consequently, we undertook the first analysis to date of in-treatment expectancy during antidepressant treatment to identify its clinical and demographic correlates, typical trajectories, and associations with treatment outcome.
Data were combined from two randomized controlled trials of antidepressant medication for major depressive disorder in which baseline and in-treatment expectancy assessments were available. Machine learning methods were used to identify pre-treatment clinical and demographic predictors of expectancy. Multilevel models were implemented to test the effects of expectancy on subsequent treatment outcome, disentangling within- and between-patient effects.
Random forest analyses demonstrated that whereas more severe depressive symptoms predicted lower pre-treatment expectancy, in-treatment expectancy was unrelated to symptom severity. At each measurement point, increased in-treatment patient expectancy significantly predicted decreased depressive symptoms at the following measurement (B = −0.45, t = −3.04, p = 0.003). The greater the gap between expected treatment outcomes and actual depressive severity, the greater the subsequent symptom reductions were (B = 0.49, t = 2.33, p = 0.02).
Greater in-treatment patient expectancy is associated with greater subsequent depressive symptom reduction. These findings suggest that clinicians may benefit from monitoring and optimizing patient expectancy during antidepressant treatment. Expectancy may represent another treatment parameter, similar to medication compliance and side effects, to be regularly monitored during antidepressant clinical management.
The effects of marriage between biological relatives on the incidence of childhood genetic illness and mortality are of major policy significance, as rates of consanguinity exceed 50% in various countries. Empirical research on this question is complicated by the fact that consanguinity is often correlated with poverty and other unobserved characteristics of households, which may have independent effects on mortality. This study has developed an instrumental variables empirical strategy to re-examine this question, based on the concept that the availability of unmarried cousins of the opposite gender at the time of marriage creates quasi-random variation in the propensity to marry consanguineously. Using primary data collected in Bangladesh in 2006–07 and Pakistan in 2009–10, the study found that previous estimates of the impact of consanguinity on child health were biased and falsely precise. The study also empirically investigated the social and economic causes of consanguinity (including marital quality) and concludes that marrying a cousin can have positive economic effects for one’s natal family, by allowing deferral of dowry payments until after marriage.
British Anglo-Catholic and high church Anglicans promoted a new set of foreign missionary initiatives in the Pacific and South and East Africa in the 1860s. Theorizing new indigenizing models for mission inspired by Tractarian medievalism, the initiatives envisioned a different and better engagement with ‘native’ cultures. Despite setbacks, the continued use of Anglican sisters in Hawai‘i and brothers in Melanesia, Africa and India created a potent new imaginative space for missionary endeavour, but one problematized by the uneven reach of empire: from contested, as in the Pacific, to normal and pervasive, as in India. Of particular relevance was the Sandwich Islands mission, invited by the Hawaiian crown, where Bishop T. N. Staley arrived in 1862, followed by Anglican missionary sisters in 1864. Immensely controversial in Britain and America, where among evangelicals in particular suspicion of ‘popish’ religious practice ran high, Anglo-Catholic methods and religious communities mobilized discussion, denunciation and reaction. Particularly in the contested imperial space of an independent indigenous monarchy, Anglo-Catholics criticized what they styled the cruel austerities of evangelical American ‘puritanism’ and the ambitions of American imperialists; in the process they catalyzed a reconceptualized imperial reformism with important implications for the shape of the late Victorian British empire.
Tumor profiling tests can help to identify whether women with breast cancer need chemotherapy due to their risk of relapse, and some may be able to predict benefit from chemotherapy. We focused on four genetic tests: Oncotype DX (O-DX), MammaPrint (MMP), EndoPredict and Prosigna, and one immunohistochemistry test, IHC4, for the National Institute of Health and Care Excellence as part of their Diagnostic Appraisal Programme.
A systematic review was undertaken, including searching of nine databases in February 2017 plus other sources including a previous review published in 2013. The review included studies assessing clinical effectiveness of the five tumor profiling tests, with or without clinicopathological factors, to guide decisions about adjuvant chemotherapy in people with ER-positive, HER-2 negative, Stage I-II cancer with 0 to 3 positive lymph nodes (LN). The PROBAST tool and Cochrane risk of bias tools were used to assess risk of bias.
A total of 153 studies were included; the strength of evidence base for individual tests was varied. Results suggest all tests are prognostic for risk of relapse, though results were more varied in LN positive (+) patients than in LN negative (0) patients. Evidence was limited about whether tests can predict benefit from chemotherapy (available for MMP and O-DX only). Studies that assessed the impact of the tests on clinical decisions indicate that the net change in chemotherapy recommendations or decisions pre-/post-test ranged from an increase of one percent to a decrease of 23 percent among UK studies, and a decrease of zero percent to 64 percent across European studies.
The studies included in the review suggest that all of the tests can provide prognostic information on the risk of relapse; however results were more varied in LN+ patients than in LN0 patients. There is limited and varying evidence for prediction of chemotherapy benefit.
Radiocarbon dating using charcoal and bone collagen, two standards of archaeological chronology, can be difficult to impossible in environments where natural burning is common and bone does not preserve well. In such settings, charcoal ages cannot always be trusted and collagen is unavailable. Calcined bone can be a viable alternative medium in these situations but it has rarely been exploited in the Americas. One area that could benefit from its use is the forested Pacific Northwest. We compare calcined bone ages with charcoal and/or collagen dates from individual features or discrete cultural strata in 10 Washington, Oregon, Idaho, and British Columbia sites dating between 9000 and 100 B.P. Resulting radiocarbon age estimates based on calcined bone closely match those based on charcoal and/or collagen in nearly all cases. We obtained calcined bone dates from three additional Holocene-aged sites that had not previously produced accurate results, obtaining findings consistent with estimates based on cross dating. Preserving well where all other organic media of cultural origin are lost or unreliable, calcined bone holds promise for dating sites in conifer forests and other acidic soil settings, and can allow researchers to refine archaeological sequences that have long defied accurate chronometric analysis.