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eHealth is a new approach for managing several health conditions, but up to now not so many interventions have shown their efficacy/effectiveness. The AUTAPP Project tries to add knowledge in eHealth interventions targeted to Mental Health disorders, specifically Autism Spectrum Disorder (ASD) management that requires complex interventions that integrate different psychosocial interventions. AUTAPP aims to develop an evidence based Clinical Decision Support System (CDSS) using mobile technology for improving the decision process on psychosocial therapies in ASD. This study aimed to identify recommendations on which the algorithm of the CDSS will be developed.
A systematic review (November 2009-November 2018) was carried out to identify the existing scientific evidence published in relation to the effectiveness of: (i) early detection protocols; (ii) assessment tools; (iii) existing non-pharmacological therapies. Main databases were consulted (PubMed, Cochrane Library, PsychoInfo). Articles were reviewed by two independent reviewers. The quality of included publications and recommendations were assessed according to SIGN criteria.
A total number of 147 publications were included (477 identified): 96 for non-pharmacological therapies, 33 for assessment tools and eighteen for early detection. Regarding early detection and assessment, 12 recommendations were identified and six obtained the highest level (A), such as the convenience of multidisciplinary diagnosis teams and the usefulness of the Modified Checklist for Autism in Toddlers (M-CHAT) for ASD confirmation. For non-pharmacological therapies, 16 recommendations were collected. Those with higher levels of recommendations were family, environmental and educational (three As and one B). Interventions with lower levels of recommendation (C) were interventions which exercise, computers and neurological approaches.
This systematic review allows both to identify gaps and opportunities in psychosocial interventions research and be the base for the CDSS algorithm. In the future professionals, careers and people diagnosed with ASD will validate the mobile CDSS.
Recent open-label trials show that psychedelics, such as ayahuasca, hold promise as fast-onset antidepressants in treatment-resistant depression.
To test the antidepressant effects of ayahuasca, we conducted a parallel-arm, double-blind randomized placebo-controlled trial in 29 patients with treatment-resistant depression. Patients received a single dose of either ayahuasca or placebo. We assessed changes in depression severity with the Montgomery-Åsberg Depression Rating Scale (MADRS) and the Hamilton Depression Rating scale at baseline, and at 1 (D1), 2 (D2), and 7 (D7) days after dosing.
We observed significant antidepressant effects of ayahuasca when compared with placebo at all-time points. MADRS scores were significantly lower in the ayahuasca group compared with placebo at D1 and D2 (p = 0.04), and at D7 (p < 0.0001). Between-group effect sizes increased from D1 to D7 (D1: Cohen's d = 0.84; D2: Cohen's d = 0.84; D7: Cohen's d = 1.49). Response rates were high for both groups at D1 and D2, and significantly higher in the ayahuasca group at D7 (64% v. 27%; p = 0.04). Remission rate showed a trend toward significance at D7 (36% v. 7%, p = 0.054).
To our knowledge, this is the first controlled trial to test a psychedelic substance in treatment-resistant depression. Overall, this study brings new evidence supporting the safety and therapeutic value of ayahuasca, dosed within an appropriate setting, to help treat depression. This study is registered at http://clinicaltrials.gov (NCT02914769).
Eclipsing binary systems offer a unique opportunity to accurately measure the fundamental properties of stars. In the past years, masses and radii of low-mass stars in these systems have been obtained with uncertainties well below the 3% level, imposing stringent constrains on theoretical models. Several results revealed that there is a discrepancy between the radius predicted by models and that from the observations of about 5–10% depending on the mass range. On the other hand, effective temperatures are overestimated by models by about a 10%. These discrepancies have been usually attributed to stellar magnetic activity, however, the correct scenario is not yet clear. The progress in the understanding of stellar activity on low-mass stars and its relation with the radius discrepancies with models is summarized here both from the empirical and the theoretical points of view.
To analyse the relationship between maternal intakes of fish and other seafood during pregnancy and child neurodevelopment at age 4 years. Although pregnant women are advised to limit seafood intakes because of possible neurotoxin contamination, several studies suggest that overall maternal seafood intakes are associated with improved child neurodevelopment, perhaps because of higher DHA intakes.
The study uses data from a prospective birth cohort study. Maternal seafood intakes were assessed using a semi-quantitative FFQ administered shortly after delivery. Multivariate linear regression was used to estimate associations between seafood consumption and scores on the McCarthy Scales of Children’s Abilities (MCSA). Analyses were stratified by breast-feeding duration as breast milk is a source of DHA during the postnatal phase of the brain growth spurt.
Menorca, Spain, 1997–2001.
Full-term children (n 392) with data on maternal diet in pregnancy, breast-feeding duration and neurodevelopment at age 4 years.
Among children breast-fed for <6 months, maternal fish intakes of >2–3 times/week were associated with significantly higher scores on several MCSA subscales compared with intakes ≤1 time/week. There was no association among children breast-fed for longer periods. Maternal intakes of other seafood (shellfish/squid) were, however, inversely associated with scores on several subscales, regardless of breast-feeding duration.
The study suggests that moderately high intakes of fish, but not other seafood, during pregnancy may be beneficial for neurodevelopment among children breast-fed for <6 months. Further research in other populations with high seafood intakes and data on additional potential confounders are needed to confirm this finding.
In this work we have studied CM Draconis, one of the least massive eclipsing binaries known. Its components are very similar, with masses and radii of about 0.23 M⊙ and 0.25 R⊙. We have analysed light curves in the R and I bands to calculate the fundamental properties of this system with accuracies better than 1%. With these results we plan to carry out a thorough test of the models, which have been found to predict smaller radii and larger effective temperatures than observed for these low-mass stars. This will also be especially interesting in the case of CM Dra since the mechanism driving magnetic activity is thought to be different from that of more massive stars. In addition, the extended time-span of the observations has led to the detection of apsidal motion. This provides a further check on models through the determination of the internal structure of the stars.
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