Structural Brain Network Reorganization and Social Cognition Related to Adverse Perinatal Condition from Infancy to Early Adolescence.

Adverse conditions during fetal life have been associated to both structural and functional changes in neurodevelopment from the neonatal period to adolescence. In this study, connectomics was used to assess the evolution of brain networks from infancy to early adolescence. Brain network reorganization over time in subjects who had suffered adverse perinatal conditions is characterized and related to neurodevelopment and cognition. Three cohorts of prematurely born infants and children (between 28 and 35 weeks of gestational age), including individuals with a birth weight appropriated for gestational age and with intrauterine growth restriction (IUGR), were evaluated at 1, 6, and 10 years of age, respectively. A common developmental trajectory of brain networks was identified in both control and IUGR groups: network efficiencies of the fractional anisotropy (FA)-weighted and normalized connectomes increase with age, which can be related to maturation and myelination of fiber connections while the number of connections decreases, which can be associated to an axonal pruning process and reorganization. Comparing subjects with or without IUGR, a similar pattern of network differences between groups was observed in the three developmental stages, mainly characterized by IUGR group having reduced brain network efficiencies in binary and FA-weighted connectomes and increased efficiencies in the connectome normalized by its total connection strength (FA). Associations between brain networks and neurobehavioral impairments were also evaluated showing a relationship between different network metrics and specific social cognition-related scores, as well as a higher risk of inattention/hyperactivity and/or executive functional disorders in IUGR children

Multicenter prospective clinical study to evaluate children short-term neurodevelopmental outcome in congenital heart disease (children NEURO-HEART): study protocol

Congenital heart disease; Neurodevelopment; Predictive markersCardiopatía congénita; Desarrollo neurológico; Marcadores predictivosCardiopaties congènites; Neurodesenvolupament; Marcadors predictiusBackground: Congenital heart disease (CHD) is the most prevalent congenital malformation affecting 1 in 100 newborns. While advances in early diagnosis and postnatal management have increased survival in CHD children, worrying long-term outcomes, particularly neurodevelopmental disability, have emerged as a key prognostic factor in the counseling of these pregnancies. Methods: Eligible participants are women presenting at 20 to < 37 weeks of gestation carrying a fetus with CHD. Maternal/neonatal recordings are performed at regular intervals, from the fetal period to 24 months of age, and include: placental and fetal hemodynamics, fetal brain magnetic resonance imaging (MRI), functional echocardiography, cerebral oxymetry, electroencephalography and serum neurological and cardiac biomarkers. Neurodevelopmental assessment is planned at 12 months of age using the ages and stages questionnaire (ASQ) and at 24months of age with the Bayley-III test. Target recruitment is at least 150 cases classified in three groups according to three main severe CHD groups: transposition of great arteries (TGA), Tetralogy of Fallot (TOF) and Left Ventricular Outflow Tract Obstruction (LVOTO). Discussion: The results of NEURO-HEART study will provide themost comprehensive knowledge until date of children’s neurologic prognosis in CHD and will have the potential for developing future clinical decisive tools and improving preventive strategies in CHD.RETICS funded by the PN 2018-2021 (Spain), ISCIII- Sub-Directorate General for Research Assessment and Promotion and the European Regional Development Fund (FEDER), reference RD16/002

Generalisability of deep learning models in low-resource imaging settings: A fetal ultrasound study in 5 African countries

Most artificial intelligence (AI) research have concentrated in high-income countries, where imaging data, IT infrastructures and clinical expertise are plentiful. However, slower progress has been made in limited-resource environments where medical imaging is needed. For example, in Sub-Saharan Africa the rate of perinatal mortality is very high due to limited access to antenatal screening. In these countries, AI models could be implemented to help clinicians acquire fetal ultrasound planes for diagnosis of fetal abnormalities. So far, deep learning models have been proposed to identify standard fetal planes, but there is no evidence of their ability to generalise in centres with limited access to high-end ultrasound equipment and data. This work investigates different strategies to reduce the domain-shift effect for a fetal plane classification model trained on a high-resource clinical centre and transferred to a new low-resource centre. To that end, a classifier trained with 1,792 patients from Spain is first evaluated on a new centre in Denmark in optimal conditions with 1,008 patients and is later optimised to reach the same performance in five African centres (Egypt, Algeria, Uganda, Ghana and Malawi) with 25 patients each. The results show that a transfer learning approach can be a solution to integrate small-size African samples with existing large-scale databases in developed countries. In particular, the model can be re-aligned and optimised to boost the performance on African populations by increasing the recall to $0.92 \pm 0.04$ and at the same time maintaining a high precision across centres. This framework shows promise for building new AI models generalisable across clinical centres with limited data acquired in challenging and heterogeneous conditions and calls for further research to develop new solutions for usability of AI in countries with less resources

Multicenter prospective clinical study to evaluate children short-term neurodevelopmental outcome in congenital heart disease (children NEURO-HEART): study protocol.

BACKGROUND: Congenital heart disease (CHD) is the most prevalent congenital malformation affecting 1 in 100 newborns. While advances in early diagnosis and postnatal management have increased survival in CHD children, worrying long-term outcomes, particularly neurodevelopmental disability, have emerged as a key prognostic factor in the counseling of these pregnancies. METHODS: Eligible participants are women presenting at 20 to < 37 weeks of gestation carrying a fetus with CHD. Maternal/neonatal recordings are performed at regular intervals, from the fetal period to 24 months of age, and include: placental and fetal hemodynamics, fetal brain magnetic resonance imaging (MRI), functional echocardiography, cerebral oxymetry, electroencephalography and serum neurological and cardiac biomarkers. Neurodevelopmental assessment is planned at 12 months of age using the ages and stages questionnaire (ASQ) and at 24 months of age with the Bayley-III test. Target recruitment is at least 150 cases classified in three groups according to three main severe CHD groups: transposition of great arteries (TGA), Tetralogy of Fallot (TOF) and Left Ventricular Outflow Tract Obstruction (LVOTO). DISCUSSION: The results of NEURO-HEART study will provide the most comprehensive knowledge until date of children's neurologic prognosis in CHD and will have the potential for developing future clinical decisive tools and improving preventive strategies in CHD

Multicenter prospective clinical study to evaluate children short-term neurodevelopmental outcome in congenital heart disease (children NEURO-HEART) : study protocol

Altres ajuts: RETICS funded by the PN 2018-2021 (Spain).Congenital heart disease (CHD) is the most prevalent congenital malformation affecting 1 in 100 newborns. While advances in early diagnosis and postnatal management have increased survival in CHD children, worrying long-term outcomes, particularly neurodevelopmental disability, have emerged as a key prognostic factor in the counseling of these pregnancies. Eligible participants are women presenting at 20 to < 37 weeks of gestation carrying a fetus with CHD. Maternal/neonatal recordings are performed at regular intervals, from the fetal period to 24 months of age, and include: placental and fetal hemodynamics, fetal brain magnetic resonance imaging (MRI), functional echocardiography, cerebral oxymetry, electroencephalography and serum neurological and cardiac biomarkers. Neurodevelopmental assessment is planned at 12 months of age using the ages and stages questionnaire (ASQ) and at 24 months of age with the Bayley-III test. Target recruitment is at least 150 cases classified in three groups according to three main severe CHD groups: transposition of great arteries (TGA), Tetralogy of Fallot (TOF) and Left Ventricular Outflow Tract Obstruction (LVOTO). The results of NEURO-HEART study will provide the most comprehensive knowledge until date of children's neurologic prognosis in CHD and will have the potential for developing future clinical decisive tools and improving preventive strategies in CHD. , on 4th December 2016 (retrospectively registered)

Neurodevelopmental milestones and associated behaviours are similar among healthy children across diverse geographical locations.

It is unclear whether early child development is, like skeletal growth, similar across diverse regions with adequate health and nutrition. We prospectively assessed 1307 healthy, well-nourished 2-year-old children of educated mothers, enrolled in early pregnancy from urban areas without major socioeconomic or environmental constraints, in Brazil, India, Italy, Kenya and UK. We used a specially developed psychometric tool, WHO motor milestones and visual tests. Similarities across sites were measured using variance components analysis and standardised site differences (SSD). In 14 of the 16 domains, the percentage of total variance explained by between-site differences ranged from 1.3% (cognitive score) to 9.2% (behaviour score). Of the 80 SSD comparisons, only six were >±0.50 units of the pooled SD for the corresponding item. The sequence and timing of attainment of neurodevelopmental milestones and associated behaviours in early childhood are, therefore, likely innate and universal, as long as nutritional and health needs are met

Interrelación de laboratorios de control y laboratorios de investigación en España para la armonización de metodologías de determinación de toxinas paralizantes

XII Congreso Nacional de Agricultura, Madrid 24-26 de noviembre de 2009Marketing of cultured and harvested shellfish is linked to monitoring programs for granting food safety. Its complexity requires constant cooperation between research and monitoring laboratories in order to improve sampling and analysing performances, achieve legal requirements, etc. for increasing consumer’s health protection but not reducing producer’s benefits. The JACUMAR project «Comparison of methodologies for the evaluation of Paralytic Shellfish Poisoning (PSP) toxins in bivalves. Application for aquaculture in Spain» groups research and monitoring laboratories from Galicia, Andalucía and Cataluña. Efforts are focused on detection and quantification of PSP toxins, searching an analytical method able to fulfil technical and management requirementsEste proyecto está financiado por la Junta Asesora de Cultivos Marinos (JACUMAR), y los programas de control por los gobiernos autónomos de Galicia, Andalucía y CataluñaN

Relationship between the Clinical Frailty Scale and short-term mortality in patients ≥ 80 years old acutely admitted to the ICU: a prospective cohort study.

BACKGROUND: The Clinical Frailty Scale (CFS) is frequently used to measure frailty in critically ill adults. There is wide variation in the approach to analysing the relationship between the CFS score and mortality after admission to the ICU. This study aimed to evaluate the influence of modelling approach on the association between the CFS score and short-term mortality and quantify the prognostic value of frailty in this context. METHODS: We analysed data from two multicentre prospective cohort studies which enrolled intensive care unit patients ≥ 80 years old in 26 countries. The primary outcome was mortality within 30-days from admission to the ICU. Logistic regression models for both ICU and 30-day mortality included the CFS score as either a categorical, continuous or dichotomous variable and were adjusted for patient's age, sex, reason for admission to the ICU, and admission Sequential Organ Failure Assessment score. RESULTS: The median age in the sample of 7487 consecutive patients was 84 years (IQR 81-87). The highest fraction of new prognostic information from frailty in the context of 30-day mortality was observed when the CFS score was treated as either a categorical variable using all original levels of frailty or a nonlinear continuous variable and was equal to 9% using these modelling approaches (p < 0.001). The relationship between the CFS score and mortality was nonlinear (p < 0.01). CONCLUSION: Knowledge about a patient's frailty status adds a substantial amount of new prognostic information at the moment of admission to the ICU. Arbitrary simplification of the CFS score into fewer groups than originally intended leads to a loss of information and should be avoided. Trial registration NCT03134807 (VIP1), NCT03370692 (VIP2)

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe