Tree Compression with Top Trees Revisited

We revisit tree compression with top trees (Bille et al, ICALP'13) and present several improvements to the compressor and its analysis. By significantly reducing the amount of information stored and guiding the compression step using a RePair-inspired heuristic, we obtain a fast compressor achieving good compression ratios, addressing an open problem posed by Bille et al. We show how, with relatively small overhead, the compressed file can be converted into an in-memory representation that supports basic navigation operations in worst-case logarithmic time without decompression. We also show a much improved worst-case bound on the size of the output of top-tree compression (answering an open question posed in a talk on this algorithm by Weimann in 2012).Comment: SEA 201

Neuroimaging in cannabis use: a systematic review of the literature

Background We conducted a systematic review to assess the evidence for specific effects of cannabis on brain structure and function. The review focuses on the cognitive changes associated with acute and chronic use of the drug. Method We reviewed literature reporting neuroimaging studies of chronic or acute cannabis use published up until January 2009. The search was conducted using Medline, EMBASE, LILACS and PsycLIT indexing services using the following key words: cannabis, marijuana, delta-9-tetrahydrocannabinol, THC, cannabidiol, CBD, neuroimaging, brain imaging, computerized tomography, CT, magnetic resonance, MRI, single photon emission tomography, SPECT, functional magnetic resonance, fMRI, positron emission tomography, PET, diffusion tensor MRI, DTI-MRI, MRS and spectroscopy. Results Sixty-six studies were identified, of which 41 met the inclusion criteria. Thirty-three were functional (SPECT/PET/fMRI) and eight structural (volumetric/DTI) imaging studies. The high degree of heterogeneity across studies precluded a meta-analysis. The functional studies suggest that resting global and prefrontal blood flow are lower in cannabis users than in controls. The results from the activation studies using a cognitive task are inconsistent because of the heterogeneity of the methods used. Studies of acute administration of THC or marijuana report increased resting activity and activation of the frontal and anterior cingulate cortex during cognitive tasks. Only three of the structural imaging studies found differences between users and controls. Conclusions Functional neuroimaging studies suggest a modulation of global and prefrontal metabolism both during the resting state and after the administration of THC/marijuana cigarettes. Minimal evidence of major effects of cannabis on brain structure has been reporte

The validity and reliability of the CAMDEX-DS for assessing dementia in adults with Down syndrome in Brazil.

OBJECTIVE: Alzheimer's disease occurs at a higher prevalence and an earlier age in individuals with Down syndrome (DS) than typically developing individuals. However, diagnosing dementia in individuals with intellectual disability remains a challenge due to pre-existing cognitive deficits. The aim of this study was to investigate the validity and reliability of the Brazilian version of the Cambridge Examination for Mental Disorders of Older People with Down's syndrome and Others with Intellectual Disabilities (CAMDEX-DS) for individuals with DS. METHODS: Two psychiatrists, working independently, evaluated 92 adults with DS ≥ 30 years of age. The concurrent validity of the CAMDEX-DS was analyzed in relation to the gold standard of established international criteria. In a subgroup of 20 subjects, the concurrent validity of the CAMDEX-DS was analyzed in relation to an independent objective assessment of cognitive decline over three years. We analyzed the inter-rater reliability of cognitive assessment. RESULTS: The diagnostic accuracy of the CAMDEX-DS compared to the gold standard was 96.7%. CAMDEX-DS-based diagnosis was considered consistent with cognitive decline. The probability of a participant with dementia having cognitive decline was 83%. Inter-rater reliability for the participant assessment was good, with a kappa of > 0.8 for 93% of the CAMDEX-DS items. CONCLUSION: The CAMDEX-DS can be considered the first valid and reliable instrument for evaluating dementia in adults with DS in Brazil. Its use in such individuals could improve clinical practice and research

The validity and reliability of the CAMDEX-DS for assessing dementia in adults with Down syndrome in Brazil.

OBJECTIVE: Alzheimer's disease occurs at a higher prevalence and an earlier age in individuals with Down syndrome (DS) than typically developing individuals. However, diagnosing dementia in individuals with intellectual disability remains a challenge due to pre-existing cognitive deficits. The aim of this study was to investigate the validity and reliability of the Brazilian version of the Cambridge Examination for Mental Disorders of Older People with Down's syndrome and Others with Intellectual Disabilities (CAMDEX-DS) for individuals with DS. METHODS: Two psychiatrists, working independently, evaluated 92 adults with DS ≥ 30 years of age. The concurrent validity of the CAMDEX-DS was analyzed in relation to the gold standard of established international criteria. In a subgroup of 20 subjects, the concurrent validity of the CAMDEX-DS was analyzed in relation to an independent objective assessment of cognitive decline over three years. We analyzed the inter-rater reliability of cognitive assessment. RESULTS: The diagnostic accuracy of the CAMDEX-DS compared to the gold standard was 96.7%. CAMDEX-DS-based diagnosis was considered consistent with cognitive decline. The probability of a participant with dementia having cognitive decline was 83%. Inter-rater reliability for the participant assessment was good, with a kappa of > 0.8 for 93% of the CAMDEX-DS items. CONCLUSION: The CAMDEX-DS can be considered the first valid and reliable instrument for evaluating dementia in adults with DS in Brazil. Its use in such individuals could improve clinical practice and research

Analysis of a nanoparticle‑enriched fraction of plasma reveals miRNA candidates for down syndrome pathogenesis

Down syndrome (DS) is caused by the presence of part or all of a third copy of chromosome 21. DS is associated with several phenotypes, including intellectual disability, congenital heart disease, childhood leukemia and immune defects. Specific microRNAs (miRNAs/miR) have been described to be associated with DS, although none of them so far have been unequivocally linked to the pathology. The present study focuses to the best of our knowledge for the first time on the miRNAs contained in nanosized RNA carriers circulating in the blood. Fractions enriched in nanosized RNA-carriers were separated from the plasma of young participants with DS and their non-trisomic siblings and miRNAs were extracted. A microarray-based analysis on a small cohort of samples led to the identification of the three most abundant miRNAs, namely miR-16-5p, miR-99b-5p and miR-144-3p. These miRNAs were then profiled for 15 pairs of DS and non‑trisomic sibling couples by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Results identified a clear differential expression trend of these miRNAs in DS with respect to their non-trisomic siblings and gene ontology analysis pointed to their potential role in a number of typical DS features, including ‘nervous system development’, ‘neuronal cell body’ and certain forms of ‘leukemia’. Finally, these expression levels were associated with certain typical quantitative and qualitative clinical features of DS. These results contribute to the efforts in defining the DS‑associated pathogenic mechanisms and emphasize the importance of properly stratifying the miRNA fluid vehicles in order to probe biomolecules that are otherwise hidden and/or not accessible to (standard) analysis

Nanoanalytical analysis of bisphosphonate-driven alterations of microcalcifications using a 3D hydrogel system and in vivo mouse model

Vascular calcification predicts atherosclerotic plaque rupture and cardiovascular events. Retrospective studies of women taking bisphosphonates (BiPs), a proposed therapy for vascular calcification, showed that BiPs paradoxically increased morbidity in patients with prior acute cardiovascular events but decreased mortality in event-free patients. Calcifying extracellular vesicles (EVs), released by cells within atherosclerotic plaques, aggregate and nucleate calcification. We hypothesized that BiPs block EV aggregation and modify existing mineral growth, potentially altering microcalcification morphology and the risk of plaque rupture. Three-dimensional (3D) collagen hydrogels incubated with calcifying EVs were used to mimic fibrous cap calcification in vitro, while an ApoE-/- mouse was used as a model of atherosclerosis in vivo. EV aggregation and formation of stress-inducing microcalcifications was imaged via scanning electron microscopy (SEM) and atomic force microscopy (AFM). In both models, BiP (ibandronate) treatment resulted in time-dependent changes in microcalcification size and mineral morphology, dependent on whether BiP treatment was initiated before or after the expected onset of microcalcification formation. Following BiP treatment at any time, microcalcifications formed in vitro were predicted to have an associated threefold decrease in fibrous cap tensile stress compared to untreated controls, estimated using finite element analysis (FEA). These findings support our hypothesis that BiPs alter EV-driven calcification. The study also confirmed that our 3D hydrogel is a viable platform to study EV-mediated mineral nucleation and evaluate potential therapies for cardiovascular calcification

The Neuroscience of Sadness: A Multidisciplinary Synthesis and Collaborative Review for the Human Affectome Project

Sadness is typically characterized by raised inner eyebrows, lowered corners of the mouth, reduced walking speed, and slumped posture. Ancient subcortical circuitry provides a neuroanatomical foundation, extending from dorsal periaqueductal grey to subgenual anterior cingulate, the latter of which is now a treatment target in disorders of sadness. Electrophysiological studies further emphasize a role for reduced left relative to right frontal asymmetry in sadness, underpinning interest in the transcranial stimulation of left dorsolateral prefrontal cortex as an antidepressant target. Neuroimaging studies – including meta-analyses – indicate that sadness is associated with reduced cortical activation, which may contribute to reduced parasympathetic inhibitory control over medullary cardioacceleratory circuits. Reduced cardiac control may – in part – contribute to epidemiological reports of reduced life expectancy in affective disorders, effects equivalent to heavy smoking. We suggest that the field may be moving toward a theoretical consensus, in which different models relating to basic emotion theory and psychological constructionism may be considered as complementary, working at different levels of the phylogenetic hierarchy

Multi-center MRI prediction models: Predicting sex and illness course in first episode psychosis patients.

Structural Magnetic Resonance Imaging (MRI) studies have attempted to use brain measures obtained at the first-episode of psychosis to predict subsequent outcome, with inconsistent results. Thus, there is a real need to validate the utility of brain measures in the prediction of outcome using large datasets, from independent samples, obtained with different protocols and from different MRI scanners. This study had three main aims: 1) to investigate whether structural MRI data from multiple centers can be combined to create a machine-learning model able to predict a strong biological variable like sex; 2) to replicate our previous finding that an MRI scan obtained at first episode significantly predicts subsequent illness course in other independent datasets; and finally, 3) to test whether these datasets can be combined to generate multicenter models with better accuracy in the prediction of illness course. The multi-center sample included brain structural MRI scans from 256 males and 133 females patients with first episode psychosis, acquired in five centers: University Medical Center Utrecht (The Netherlands) (n=67); Institute of Psychiatry, Psychology and Neuroscience, London (United Kingdom) (n=97); University of São Paulo (Brazil) (n=64); University of Cantabria, Santander (Spain) (n=107); and University of Melbourne (Australia) (n=54). All images were acquired on 1.5-Tesla scanners and all centers provided information on illness course during a follow-up period ranging 3 to 7years. We only included in the analyses of outcome prediction patients for whom illness course was categorized as either "continuous" (n=94) or "remitting" (n=118). Using structural brain scans from all centers, sex was predicted with significant accuracy (89%; p<0.001). In the single- or multi-center models, illness course could not be predicted with significant accuracy. However, when reducing heterogeneity by restricting the analyses to male patients only, classification accuracy improved in some samples. This study provides proof of concept that combining multi-center MRI data to create a well performing classification model is possible. However, to create complex multi-center models that perform accurately, each center should contribute a sample either large or homogeneous enough to first allow accurate classification within the single-center

10Kin1day: a bottom-up neuroimaging initiative

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.The 10Kin1day workshop was generously sponsored by the Neuroscience and Cognition program Utrecht (NCU) of the Utrecht University (https://www.uu.nl/en/research/neuroscience-and-cognition-utrecht), the ENIGMA consortium (http://enigma.ini.usc.edu), and personal grants: MvdH: NWOVIDI (452-16-015), MQ Fellowship; SB-C: the Wellcome Trust; Medical Research Council UK; NIHR CLAHRC for Cambridgeshire and Peterborough Foundation National Health Services Trust; Autism Research Trust; LB: New Investigator Award, Canadian Institutes of Health Research; Dara Cannon: Health Research Board (HRB), Ireland (grant code HRA-POR2013-324); SC: Research Grant Council (Hong Kong)-GRF 14101714; Eveline Crone: ERC-2010-StG-263234; UD: DFG, grant FOR2107 DA1151/5-1, DA1151/5-2, SFB-TRR58, Project C09, IZKF, grant Dan3/012/17; SD: MRC-RFA-UFSP-01-2013 (Shared Roots MRC Flagship grant); TF: Marie Curie Programme, International Training Programme, r’Birth; DG: National Science Centre (UMO-2011/02/A/NZ5/00329); BG: National Science Centre (UMO-2011/02/A/NZ5/00329); JH: Western Sydney University Postgraduate Research Award; LH: Science Foundation Ireland, ERC; HH: Research Grant Council (Hong Kong)-GRF 14101714; LJ: Velux Stiftung, grant 369 & UZH University Research Priority Program Dynamics of Healthy Aging; AJ: DFG, grant FOR2107 JA 1890/7-1; KJ: National Science Centre (UMO-2013/09/N/HS6/02634); VK: The Russian Foundation for Basic Research (grant code 15-06-05758 A); TK: DFG, grant FOR2107 KI 588/14-1, DFG, grant FOR2107 KI 588/15-1; AK: DFG, grant FOR2107 KO 4291/4-1, DFG, grant FOR2107 KO 4291/3-1; IL: The Russian Foundation for Basic Research (grant code 15-06-05758 A); EL: Health and Medical Research Fund - 11121271; SiL: NHMRC-ARC Dementia Fellowship 1110414, NHMRC Dementia Research Team Grant 1095127, NHMRC Project Grant 1062319; CL-J: 537-2011, 2014-849; AM: Wellcome Trust Strategic Award (104036/Z/14/Z), MRC Grant MC_PC_17209; CM: Heisenberg-Grant, German Research Foundation, DFG MO 2363/3-2; PM: Foundation for Science and Technology, Portugal - PDE/BDE/113601/2015; KN: National Science Centre (UMO-2011/02/A/NZ5/00329); PN: National Science Centre (UMO-2013/09/N/HS6/02634); JiP: NWO-Veni 451-10-007; PaR: PER and US would like to thank the Schizophrenia Research Institute and the Chief-Investigators of the Australian Schizophrenia Research Bank V. Carr, U. Schall, R. Scott, A. Jablensky, B. Mowry, P. Michie, S. Catts, F. Henskens, and C. Pantelis; AS: National Science Centre (UMO-2011/02/A/NZ5/00329); SS: European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 707730; CS-M: Carlos III Health Institute (PI13/01958), Carlos III Health Institute (PI16/00889), Carlos III Health Institute (CPII16/00048); ES: National Science Centre (UMO-2011/02/A/NZ5/00329); AT: The Russian Foundation for Basic Research (grant code 15-06-05758 A); DT-G: PI14/00918, PI14/00639; Leonardo Tozzi: Marie Curie Programme, International Training Programme, r’Birth; SV: IMPRS Neurocom stipend; TvE: National Center for Research Resources at the National Institutes of Health (grant numbers: NIH 1 U24 RR021992 (Function Biomedical Informatics Research Network), NIH 1 U24 RR025736-01 (Biomedical Informatics Research Network Coordinating Center; http://www.birncommunity.org) and the NIH Big Data to Knowledge (BD2K) award (U54 EB020403 to Paul Thompson). NvH: NWO-VIDI (452-11-014); MW: National Science Centre (UMO-2011/02/A/NZ5/00329); Veronica O’Keane: Meath Foundation; AV and AW: CRC Obesity Mechanism (SFB 1052) Project A1 funded by DFG. The funding sources had no role in the study design, data collection, analysis, and interpretation of the data. We further like to thank Joanna Goc, Veronica O’Keane, Devon Shook, and Leonardo Tozzi for their participation and/or support of the 10K project. HCP data was provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University