Paralelización a algoritmos de compresión fractal de imágenes

Se analiza la paralelización de un algoritmo clásico de compresión fractal de imagenes, utilizando procesadores heterogéneos conectados en red con un soporte de procesamiento distribuido basado en PVM y XPVM. En particular se discuten dos métricas de interés: el speed-up obtenible (separando los tiempos propios del overhead de comunicaciones) al incrementar el número de procesadores y la pérdida resultante del índice de compresión alcanzado. Si bien se trata de una clase de algoritmo muy particular, resulta de interés tecnológico sobre todo en aplicaciones donde la información es comprimida una vez y almacenada para su recuperación en consulta muchas veces (por ejemplo en servidores de información InterNet) ya que los índices de compresión alcanzables con una pérdida aceptable son muy altos y al mismo tiempo el algortimo de descompresión es muy rápido. Por último se discute el efecto de variar el particionamiento de la imagen sobre los tiempos de procesamiento y la posibilidad de realizar un particionamiento adaptivo con el fin de optimizar la relación índice de compresión/pérdida aceptable sin deterioro del speed-up.Eje: Procesamiento distribuido y paralelo. Tratamiento de señalesRed de Universidades con Carreras en Informática (RedUNCI

Parental perspectives on psychiatric comorbidity in preschoolers with autism spectrum disorders receiving publicly funded mental health services

An increased prevalence of psychiatric comorbidity (PC) in individuals with Autism Spectrum Disorders (ASD) is consistently reported. While several studies have examined PC in school-aged children, adolescents and adults with ASD, investigations on PC in preschoolers are less common. In this study, we explore the prevalence and the type of PC in a sample of 989 preschoolers with ASD through the DSM-Oriented Scales (DOS) of the Child Behavior Checklist (CBCL 1½-5) and their possible links with the core features of ASD and cognitive functioning. Results indicated that 37.8% of the sample had at least one PC in addition to ASD; these subjects displayed significantly higher Total score (p = 0.02) and Social Affect score (p = 0.003) on the ADOS-based calibrated severity scores (CSS), as well as lower (p ≤ 0.0001) performance IQ (pIQ) compared to ASD individuals without PC. As far as the specific DOS, Affective Problems (AP) were detected in 23.4% of the whole sample, ADHD Problems (ADHD) in 17.3%, Anxiety Problems (AXP) in 16.7%, and Oppositional Problems (OP) in 7.9%. These different comorbidities were isolated in 195 subjects (Mono-comorbid group: 19.7% of the whole sample), while 179 subjects (18.1% of the whole sample) had two or more types of PC (Multi-comorbid group). One-way ANOVA revealed that subjects with multi-comorbidity have statistically significant lower pIQ and higher Total score and Social Affect score on CSS-ADOS. Specific differences for each type of comorbidity and gender differences were also discussed. Taken together, results indicate a considerable presence of PC in preschoolers with ASD that should be accurately considered during the assessment and diagnosis process in order to plan a tailored intervention based not only on core symptoms of ASD, but also on comorbid psychiatric condition since preschool age

Early and stable difficulties of everyday executive functions predict autism symptoms and emotional/behavioral problems in preschool age children with autism: a 2-year longitudinal study

IntroductionLongitudinal studies of autistic children show that autism symptoms and emotional/behavioral problems vary and change over time. However, the factors that affect this variability remain far from certain and very little is known about what take place in the preschool period and the role of executive functions (EF).MethodsHere, we test the influence of stable difficulties in everyday executive functioning (EEF) during early childhood across 2 years on autistic symptoms and emotional and behavioral problems. Twenty-nine autistic children (24 males and 5 females) were assessed twice within the space of 2 years. At baseline (M = 29 months, SD =5.6 months), participants were assessed for EEF, cognitive development, autistic symptoms, and emotional/behavioral problems. At follow-up, we repeated the same assessment except for cognitive development.ResultsThe group with stable difficulties (across 2 years) in EEF during early childhood showed a worsening in the severity of autistic symptoms and emotional and behavioral problems compared with children without EEF difficulties (p < 0.05), and these effects cannot be attributable to cognitive development.DiscussionOur results suggest that early and stable EEF plays the role of a modifier by interacting with the core domains of autism, in particular with the social affect domain (SA CSS), influencing social cognition and exacerbating or lessening symptom expression and emotional behavioral problems. These short-term longitudinal and preliminary findings underscore the importance of EEF as necessary target for early intervention in children with autism

Functional evaluation of awareness in vegetative and minimally conscious state

Objective: The aim of this study was to assess differences in brain activation in a large sample of Vegetative State (VS) and Minimally Conscious State (MCS) patients, using functional magnetic resonance imaging (fMRI). Methods: We studied 50 patients four to seven months after brain injury. By using international clinical criteria and validated behavioural scales such as the Glasgow Coma Scale and the Clinical Unawareness Assessment Scale, the patients were grouped into VS (n=23) and MCS (n=27). All patients underwent to fMRI examination. After 6 months, the patients were reassessed using Glasgow Outcome Scale and Revised Coma Recovery Scale. Results: fMRI showed significant (p<0.01, cluster-corrected) brain activation in the primary auditory cortex bilaterally during the acoustic stimuli in patients with both VS and MCS. However, ten patients clinically classified as VS, showed a pattern of brain activation very similar to that of MCS patients. Six months later, these ten VS patients had significant clinical improvement, evolving into MCS, whereas the other VS patients and patients with MCS remained clinically stable. Conclusion: Brain activity could help in discerning whether the status of wakefulness in VS is also accompanied by partial awareness, as occurs in MCS. This may have very important prognostic implications

Sex Differences in Autism Spectrum Disorder: An Investigation on Core Symptoms and Psychiatric Comorbidity in Preschoolers

Findings regarding sex differences in autism spectrum disorder (ASD), as far as core symptoms and psychiatric comorbidities (PC) are concerned, are inconsistent, inconclusive, or conflicting among studies. The lower prevalence of ASD in females than in males and the age and intelligence quotient (IQ) heterogeneity among samples made it difficult to investigate these differences. This case–control study tries to deepen the impact of sex differences on core symptoms of autism and PC in 214 preschoolers with ASD (mean age, 45.26) without impairment in non-verbal IQ (nvIQ ≥70). A total of 107 ASD females (mean age, 44.51 ± 13.79 months) were matched one by one with 107 males (mean age, 46.01 ± 13.42 months) for chronological age (±6 months) and nvIQ (±6 points). We used the Autism Diagnostic Observation Schedule 2 (ADOS-2) and the Child Behavior Checklist (CBCL) 1.5–5 to explore autism severity and PC. The results highlight that ASD females did not significantly differ from ASD males regarding the severity of autism. Statistically significant lower levels of emotionally reactive (p = 0.005, η2 = 0.04), anxious-depressed (p = 0.001, η2 = 0.05), internalizing problems (p = 0.04, η2 = 0.02), and DSM-Oriented Scales anxiety problems (p = 0.02, η2 = 0.04) in ASD females than in ASD males were also detected. Our findings of no difference in the autism severity and lower internalizing problems in females than males with ASD extend the knowledge of autism in females during preschool years. Compared to other similar studies on this topic, we can state that these results are not supported by differences in nvIQ between sexes nor by the presence of cognitive impairment. It confirms the need for clinicians to consider sex differences when describing autism psychopathology

Gut microbiota functional profiling in autism spectrum disorders: bacterial VOCs and related metabolic pathways acting as disease biomarkers and predictors

BackgroundAutism spectrum disorder (ASD) is a multifactorial neurodevelopmental disorder. Major interplays between the gastrointestinal (GI) tract and the central nervous system (CNS) seem to be driven by gut microbiota (GM). Herein, we provide a GM functional characterization, based on GM metabolomics, mapping of bacterial biochemical pathways, and anamnestic, clinical, and nutritional patient metadata.MethodsFecal samples collected from children with ASD and neurotypical children were analyzed by gas-chromatography mass spectrometry coupled with solid phase microextraction (GC–MS/SPME) to determine volatile organic compounds (VOCs) associated with the metataxonomic approach by 16S rRNA gene sequencing. Multivariate and univariate statistical analyses assessed differential VOC profiles and relationships with ASD anamnestic and clinical features for biomarker discovery. Multiple web-based and machine learning (ML) models identified metabolic predictors of disease and network analyses correlated GM ecological and metabolic patterns.ResultsThe GM core volatilome for all ASD patients was characterized by a high concentration of 1-pentanol, 1-butanol, phenyl ethyl alcohol; benzeneacetaldehyde, octadecanal, tetradecanal; methyl isobutyl ketone, 2-hexanone, acetone; acetic, propanoic, 3-methyl-butanoic and 2-methyl-propanoic acids; indole and skatole; and o-cymene. Patients were stratified based on age, GI symptoms, and ASD severity symptoms. Disease risk prediction allowed us to associate butanoic acid with subjects older than 5 years, indole with the absence of GI symptoms and low disease severity, propanoic acid with the ASD risk group, and p-cymene with ASD symptoms, all based on the predictive CBCL-EXT scale. The HistGradientBoostingClassifier model classified ASD patients vs. CTRLs by an accuracy of 89%, based on methyl isobutyl ketone, benzeneacetaldehyde, phenyl ethyl alcohol, ethanol, butanoic acid, octadecane, acetic acid, skatole, and tetradecanal features. LogisticRegression models corroborated methyl isobutyl ketone, benzeneacetaldehyde, phenyl ethyl alcohol, skatole, and acetic acid as ASD predictors.ConclusionOur results will aid the development of advanced clinical decision support systems (CDSSs), assisted by ML models, for advanced ASD-personalized medicine, based on omics data integrated into electronic health/medical records. Furthermore, new ASD screening strategies based on GM-related predictors could be used to improve ASD risk assessment by uncovering novel ASD onset and risk predictors