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A behavioral comparison of male and female adults with high functioning autism spectrum conditions
Autism spectrum conditions (ASC) affect more males than females in the general population. However, within ASC it is unclear if there are phenotypic sex differences. Testing for similarities and differences between the sexes is important not only for clinical assessment but also has implications for theories of typical sex differences and of autism. Using cognitive and behavioral measures, we investigated similarities and differences between the sexes in age- and IQ-matched adults with ASC (high-functioning autism or Asperger syndrome). Of the 83 (45 males and 38 females) participants, 62 (33 males and 29 females) met Autism Diagnostic Interview-Revised (ADI-R) cut-off criteria for autism in childhood and were included in all subsequent analyses. The severity of childhood core autism symptoms did not differ between the sexes. Males and females also did not differ in self-reported empathy, systemizing, anxiety, depression, and obsessive-compulsive traits/symptoms or mentalizing performance. However, adult females with ASC showed more lifetime sensory symptoms (pβ=β0.036), fewer current socio-communication difficulties (pβ=β0.001), and more self-reported autistic traits (pβ=β0.012) than males. In addition, females with ASC who also had developmental language delay had lower current performance IQ than those without developmental language delay (p<0.001), a pattern not seen in males. The absence of typical sex differences in empathizing-systemizing profiles within the autism spectrum confirms a prediction from the extreme male brain theory. Behavioral sex differences within ASC may also reflect different developmental mechanisms between males and females with ASC. We discuss the importance of the superficially better socio-communication ability in adult females with ASC in terms of why females with ASC may more often go under-recognized, and receive their diagnosis later, than males
Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms
Importance: Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. Objective: To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms. Design, Setting, and Participants: In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016. Main Outcomes and Measurements: Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists' specificity with radiologists' sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists' recall assessment was developed and evaluated. Results: Overall, 144β―231 screening mammograms from 85β―580 US women (952 cancer positive β€12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166β―578 examinations from 68β―008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists' sensitivity, lower than community-practice radiologists' specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms and US radiologist assessments resulted in a higher area under the curve of 0.942 and achieved a significantly improved specificity (92.0%) at the same sensitivity. Conclusions and Relevance: While no single AI algorithm outperformed radiologists, an ensemble of AI algorithms combined with radiologist assessment in a single-reader screening environment improved overall accuracy. This study underscores the potential of using machine learning methods for enhancing mammography screening interpretation
A European proficiency test on thin film tandem photovoltaic devices
A round robin proficiency test RR PT on thin film multi junction MJ photovoltaic PV cells was run between 13 laboratories within the European project CHEETAH. Five encapsulated PV cells were circulated to participants for being tested at Standard Test Conditions STC . Three cells were a Si amp; 956;c Si tandem PV devices, each of which had a different short circuit current ratio between the top junction and the bottom one; the remaining two cells were single junction PV devices made with material representative of the individual junctions in the MJ cells. The RR PT s main purpose was to assess the capability of the participating laboratories, in terms of employed facilities and procedures, to test MJ PV devices. Therefore, participant
Volcanic impacts on the Holocene vegetation history of Britain and Ireland? A review and meta-analysis of the pollen evidence
Volcanic ash layers show that the products of Icelandic volcanism reached Britain and Ireland many times during the Holocene. Historical records suggest that at least one eruption, that of Laki in a.d. 1783, was associated with impacts on vegetation. These results raise the question: did Icelandic volcanism affect the Holocene vegetation history of Britain and Ireland? Several studies have used pollen data to address this issue but no clear consensus has been reached. We re-analyse the palynological data using constrained ordination with various representations of potential volcanic impacts. We find that the palynological evidence for volcanic impacts on vegetation is weak but suggest that this is a case of absence of evidence and is not necessarily evidence of absence of impact. To increase the chances of identifying volcanic impacts, future studies need to maximise temporal resolution, replicate results, and investigate a greater number of tephras in a broader range of locations, including more studies from lake sediments
Climate change and freshwater zooplankton: what does it boil down to?
Recently, major advances in the climateβzooplankton interface have been made some of which appeared to receive much attention in a broader audience of ecologists as well. In contrast to the marine realm, however, we still lack a more holistic summary of recent knowledge in freshwater. We
discuss climate change-related variation in physical and biological attributes of lakes and running waters, high-order ecological functions, and subsequent alteration
in zooplankton abundance, phenology, distribution, body size, community structure, life history parameters, and behavior by focusing on community level responses. The adequacy of large-scale climatic indices in ecology has received considerable support and provided a framework for the interpretation of community and species level responses in freshwater zooplankton. Modeling perspectives deserve particular consideration, since this promising stream of
ecology is of particular applicability in climate change
research owing to the inherently predictive nature of
this field. In the future, ecologists should expand their
research on species beyond daphnids, should address
questions as to how different intrinsic and extrinsic
drivers interact, should move beyond correlative
approaches toward more mechanistic explanations,
and last but not least, should facilitate transfer of
biological data both across space and time
The RESET project: constructing a European tephra lattice for refined synchronisation of environmental and archaeological events during the last c. 100 ka
This paper introduces the aims and scope of the RESET project (. RESponse of humans to abrupt Environmental Transitions), a programme of research funded by the Natural Environment Research Council (UK) between 2008 and 2013; it also provides the context and rationale for papers included in a special volume of Quaternary Science Reviews that report some of the project's findings. RESET examined the chronological and correlation methods employed to establish causal links between the timing of abrupt environmental transitions (AETs) on the one hand, and of human dispersal and development on the other, with a focus on the Middle and Upper Palaeolithic periods. The period of interest is the Last Glacial cycle and the early Holocene (c. 100-8 ka), during which time a number of pronounced AETs occurred. A long-running topic of debate is the degree to which human history in Europe and the Mediterranean region during the Palaeolithic was shaped by these AETs, but this has proved difficult to assess because of poor dating control. In an attempt to move the science forward, RESET examined the potential that tephra isochrons, and in particular non-visible ash layers (cryptotephras), might offer for synchronising palaeo-records with a greater degree of finesse. New tephrostratigraphical data generated by the project augment previously-established tephra frameworks for the region, and underpin a more evolved tephra 'lattice' that links palaeo-records between Greenland, the European mainland, sub-marine sequences in the Mediterranean and North Africa. The paper also outlines the significance of other contributions to this special volume: collectively, these illustrate how the lattice was constructed, how it links with cognate tephra research in Europe and elsewhere, and how the evidence of tephra isochrons is beginning to challenge long-held views about the impacts of environmental change on humans during the Palaeolithic. Β© 2015 Elsevier Ltd.RESET was funded through Consortium Grants awarded by the Natural Environment Research Council, UK, to a collaborating team drawn from four institutions: Royal Holloway University of London (grant reference NE/E015905/1), the Natural History Museum, London (NE/E015913/1), Oxford University (NE/E015670/1) and the University of Southampton, including the National Oceanography Centre (NE/01531X/1). The authors also wish to record their deep gratitude to four members of the scientific community who formed a consultative advisory panel during the lifetime of the RESET project: Professor Barbara Wohlfarth (Stockholm University), Professor JΓΈrgen Peder Steffensen (Niels Bohr Institute, Copenhagen), Dr. Martin Street (Romisch-Germanisches Zentralmuseum, Neuwied) and Professor Clive Oppenheimer (Cambridge University). They provided excellent advice at key stages of the work, which we greatly valued. We also thank Jenny Kynaston (Geography Department, Royal Holloway) for construction of several of the figures in this paper, and Debbie Barrett (Elsevier) and Colin Murray Wallace (Editor-in-Chief, QSR) for their considerable assistance in the production of this special volume.Peer Reviewe
DIA1R Is an X-Linked Gene Related to Deleted In Autism-1
Background: Autism spectrum disorders (ASDs) are frequently occurring disorders diagnosed by deficits in three core functional areas: social skills, communication, and behaviours and/or interests. Mental retardation frequently accompanies the most severe forms of ASDs, while overall ASDs are more commonly diagnosed in males. Most ASDs have a genetic origin and one gene recently implicated in the etiology of autism is the Deleted-In-Autism-1 (DIA1) gene. Methodology/Principal Findings: Using a bioinformatics-based approach, we have identified a human gene closely related to DIA1, we term DIA1R (DIA1-Related). While DIA1 is autosomal (chromosome 3, position 3q24), DIA1R localizes to the X chromosome at position Xp11.3 and is known to escape X-inactivation. The gene products are of similar size, with DIA1 encoding 430, and DIA1R 433, residues. At the amino acid level, DIA1 and DIA1R are 62 % similar overall (28 % identical), and both encode signal peptides for targeting to the secretory pathway. Both genes are ubiquitously expressed, including in fetal and adult brain tissue. Conclusions/Significance: Examination of published literature revealed point mutations in DIA1R are associated with X-linked mental retardation (XLMR) and DIA1R deletion is associated with syndromes with ASD-like traits and/or XLMR. Together, these results support a model where the DIA1 and DIA1R gene products regulate molecular traffic through the cellular secretory pathway or affect the function of secreted factors, and functional deficits cause disorders with ASD-lik
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