82 research outputs found
Going 'Above and Beyond': Are Those High in Autistic Traits Less Pro-social?
Few studies have explored how the cognitive differences associated with autistic spectrum disorder translate into everyday social behaviour. This study investigated pro-social behaviour in students scoring high and low on the autism-spectrum quotient (AQ), using a novel scenario task: 'Above and Beyond'. Each scenario involved an opportunity to behave pro-socially, and thus required balancing the needs of a character against participants' own interests. High AQ participants both generated responses and selected courses of action that were less pro-social than those of the low AQ group. For actions of low pro-social value they gave higher self-satisfaction ratings; conversely, they gave lower self-satisfaction ratings for high pro-social actions. The implications for everyday functioning are considered for those with high autistic traits
Prognosis of follicular lymphoma: a predictive model based on a retrospective analysis of 987 cases
Patients (n-987) with a histologically confirmed diagnosis of follicular lymphoma were studied with the aim of developing a prognostic model specifically devised for this type of lymphoma. We collected information on age, sex, Ann Arbor stage, number of extranodal disease sites, bone marrow (BM) involvement, bulky disease, B symptom criteria (fever, night sweats, and weight loss), performance status (PS), serum lactate dehydrogenase (LDH) level, serum albumin level, hemoglobin level, and erythrocyte sedimentation rate (ESR). In the training sample of 429 patients with complete data, multivariate analysis showed that age, sex, number of extranodal sites, B symptoms, serum LDH level, and ESR were factors predictive for overall survival. Using these 6 variables, a prognostic model was devised to identify 3 groups at different risk. The 5- and 10-year survival rate was 90% and 65% for patients at low risk, respectively; 75% and 54% for patients at intermediate risk; and 38% and 11% for those at high risk (log-rank test, 86.62; P < .0001). The model was also predictive (P = .0001) in the validation sample of 265 patients with complete data only for the 6 variables used in the development of the model and even in the group of 210 patients from the validation sample uniformly treated with doxorubicin-containing regimens (P = .0001). The prognostic model appears to be very useful in identifying patients with follicular lymphoma at low, intermediate, or high risk
Effects of Chronic Sleep Restriction during Early Adolescence on the Adult Pattern of Connectivity of Mouse Secondary Motor Cortex
Cortical circuits mature in stages, from early synaptogenesis and synaptic pruning to late synaptic refinement, resulting in the adult anatomical connection matrix. Because the mature matrix is largely fixed, genetic or environmental factors interfering with its establishment can have irreversible effects. Sleep disruption is rarely considered among those factors, and previous studies have focused on very young animals and the acute effects of sleep deprivation on neuronal morphology and cortical plasticity. Adolescence is a sensitive time for brain remodeling, yet whether chronic sleep restriction (CSR) during adolescence has long-term effects on brain connectivity remains unclear. We used viral-mediated axonal labeling and serial two-photon tomography to measure brain-wide projections from secondary motor cortex (MOs), a high-order area with diffuse projections. For each MOs target, we calculated the projection fraction, a combined measure of passing fibers and axonal terminals normalized for the size of each target. We found no homogeneous differences in MOs projection fraction between mice subjected to 5 days of CSR during early adolescence (P25–P30, ≥50% decrease in daily sleep, n=14) and siblings that slept undisturbed (n=14). Machine learning algorithms, however, classified animals at significantly above chance levels, indicating that differences between the two groups exist, but are subtle and heterogeneous. Thus, sleep disruption in early adolescence may affect adult brain connectivity. However, because our method relies on a global measure of projection density and was not previously used to measure connectivity changes due to behavioral manipulations, definitive conclusions on the long-term structural effects of early CSR require additional experiments
Reduction of EEG Theta Power and Changes in Motor Activity in Rats Treated with Ceftriaxone
The glutamate transporter GLT-1 is responsible for the largest proportion of total glutamate transport. Recently, it has been demonstrated that ceftriaxone (CEF) robustly increases GLT-1 expression. In addition, physiological studies have shown that GLT-1 up-regulation strongly affects synaptic plasticity, and leads to an impairment of the prepulse inhibition, a simple form of information processing, thus suggesting that GLT-1 over-expression may lead to dysfunctions of large populations of neurons. To test this possibility, we assessed whether CEF affects cortical electrical activity by using chronic electroencephalographic (EEG) recordings in male WKY rats. Spectral analysis showed that 8 days of CEF treatment resulted in a delayed reduction in EEG theta power (7–9 Hz) in both frontal and parietal derivations. This decrease peaked at day 10, i.e., 2 days after the end of treatment, and disappeared by day 16. In addition, we found that the same CEF treatment increased motor activity, especially when EEG changes are more prominent. Taken together, these data indicate that GLT-1 up-regulation, by modulating glutamatergic transmission, impairs the activity of widespread neural circuits. In addition, the increased motor activity and prepulse inhibition alterations previously described suggest that neural circuits involved in sensorimotor control are particularly sensitive to GLT-1 up-regulation
Effects of Chronic Sleep Restriction during Early Adolescence on the Adult Pattern of Connectivity of Mouse Secondary Motor Cortex
Cortical circuits mature in stages, from early synaptogenesis and synaptic pruning to late synaptic refinement, resulting in the adult anatomical connection matrix. Because the mature matrix is largely fixed, genetic or environmental factors interfering with its establishment can have irreversible effects. Sleep disruption is rarely considered among those factors, and previous studies have focused on very young animals and the acute effects of sleep deprivation on neuronal morphology and cortical plasticity. Adolescence is a sensitive time for brain remodeling, yet whether chronic sleep restriction (CSR) during adolescence has long-term effects on brain connectivity remains unclear. We used viral-mediated axonal labeling and serial two-photon tomography to measure brain-wide projections from secondary motor cortex (MOs), a high-order area with diffuse projections. For each MOs target, we calculated the projection fraction, a combined measure of passing fibers and axonal terminals normalized for the size of each target. We found no homogeneous differences in MOs projection fraction between mice subjected to 5 days of CSR during early adolescence (P25–P30, ≥50% decrease in daily sleep, n=14) and siblings that slept undisturbed (n=14). Machine learning algorithms, however, classified animals at significantly above chance levels, indicating that differences between the two groups exist, but are subtle and heterogeneous. Thus, sleep disruption in early adolescence may affect adult brain connectivity. However, because our method relies on a global measure of projection density and was not previously used to measure connectivity changes due to behavioral manipulations, definitive conclusions on the long-term structural effects of early CSR require additional experiments
Should I give kids money? The role of pocket money on at-risk behaviors in Italian adolescents
Background. Discussion on the impact of pocket money on positive behaviors is still debated. Objective. To investigate the effect of diverse money allowance schemes on risky behaviors (smoking, alcohol, binge drinking, drug use, gambling) during adolescence. Method. 989 students aged 15 from Lombardy (Italy) reported information on money availability in the 2018 wave of the Health Behaviour in School-aged Children study. To analyze the relationship between money availability and risky behaviors we computed odds ratios and 95% confidence intervals through unconditional multiple logistic regression models. Results. Spending more than 10€ weekly was associated with higher likelihood to smoke, binge drink or gamble. Receiving pocket money (rather than receiving money upon request) was related to higher likelihood to engage in risky behaviors. Conclusions. Pocket money may have a negative impact on adolescents, particularly with a substantial amount of money. More research is needed to understand why providing money only if needed may serve as a protective factor against risky behaviors
SNPs in DNA repair or oxidative stress genes and late subcutaneous fibrosis in patients following single shot partial breast irradiation
<p>Abstract</p> <p>Background</p> <p>The aim of this study was to evaluate the potential association between single nucleotide polymorphisms related response to radiotherapy injury, such as genes related to DNA repair or enzymes involved in anti-oxidative activities. The paper aims to identify marker genes able to predict an increased risk of late toxicity studying our group of patients who underwent a Single Shot 3D-CRT PBI (SSPBI) after BCS (breast conserving surgery).</p> <p>Methods</p> <p>A total of 57 breast cancer patients who underwent SSPBI were genotyped for SNPs (single nucleotide polymorphisms) in XRCC1, XRCC3, GST and RAD51 by Pyrosequencing technology. Univariate analysis (ORs and 95% CI) was performed to correlate SNPs with the risk of developing ≥ G2 fibrosis or fat necrosis.</p> <p>Results</p> <p>A higher significant risk of developing ≥ G2 fibrosis or fat necrosis in patients with: polymorphic variant <it>GSTP1 </it>(Ile105Val) (OR = 2.9; 95%CI, 0.88-10.14, <it>p </it>= 0.047).</p> <p>Conclusions</p> <p>The presence of some SNPs involved in DNA repair or response to oxidative stress seem to be able to predict late toxicity.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT01316328">NCT01316328</a></p
TRIAGEM NEONATAL DE IMUNODEFICIÊNCIAS GRAVES COMBINADAS POR MEIO DE TRECS E KRECS: SEGUNDO ESTUDO PILOTO NO BRASIL
RESUMO Objetivo: Validar a quantificação de T-cell receptor excision circles (TRECs) e kappa-deleting recombination circles (KRECs) por reação em cadeia de polimerase (polymerase chain reaction, PCR) em tempo real (qRT-PCR), para triagem neonatal de imunodeficiências primárias que cursam com defeitos nas células T e/ou B no Brasil. Métodos: Amostras de sangue de recém-nascidos (RN) e controles foram coletadas em papel-filtro. O DNA foi extraÃdo e os TRECs e KRECs foram quantificados por reação duplex de qRT-PCR. O valor de corte foi determinado pela análise de Receiver Operating Characteristics Curve, utilizando-se o programa Statistical Package for the Social Sciences (SSPS) (IBM®, Armonk, NY, EUA). Resultados: 6.881 amostras de RN foram analisadas quanto à concentração de TRECs e KRECs. Os valores de TRECs variaram entre 1 e 1.006 TRECs/µL, com média e mediana de 160 e 139 TRECs/µL, respectivamente. Três amostras de pacientes diagnosticados com imunodeficiência grave combinada (severe combined immunodeficiency, SCID) apresentaram valores de TRECs abaixo de 4/µL e um paciente com SÃndrome de DiGeorge apresentou TRECs indetectáveis. Os valores de KRECs encontraram-se entre 10 e 1.097 KRECs/µL, com média e mediana de 130 e 108 KRECs/µL, e quatro pacientes com diagnóstico de agamaglobulinemia tiveram resultados abaixo de 4 KRECs/µL. Os valores de corte encontrados foram 15 TRECs/µL e 14 KRECs/µL, e foram estabelecidos de acordo com a análise da Receiver Operating Characteristics Curve, com sensibilidade de 100% para detecção de SCID e agamaglobulinemia, respectivamente. Conclusões: A quantificação de TRECs e KRECs foi capaz de diagnosticar crianças com linfopenias T e/ou B em nosso estudo, validando a técnica e dando o primeiro passo para a implementação da triagem neonatal em grande escala no Brasil
A machine-learning parsimonious multivariable predictive model of mortality risk in patients with Covid-19
The COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models have been validated but few of them are implemented in daily practice. The objective of the study was to validate a machine-learning risk prediction model using easy-to-obtain parameters to help to identify patients with COVID-19 who are at higher risk of death. The training cohort included all patients admitted to Fondazione Policlinico Gemelli with COVID-19 from March 5, 2020, to November 5, 2020. Afterward, the model was tested on all patients admitted to the same hospital with COVID-19 from November 6, 2020, to February 5, 2021. The primary outcome was in-hospital case-fatality risk. The out-of-sample performance of the model was estimated from the training set in terms of Area under the Receiving Operator Curve (AUROC) and classification matrix statistics by averaging the results of fivefold cross validation repeated 3-times and comparing the results with those obtained on the test set. An explanation analysis of the model, based on the SHapley Additive exPlanations (SHAP), is also presented. To assess the subsequent time evolution, the change in paO2/FiO2 (P/F) at 48 h after the baseline measurement was plotted against its baseline value. Among the 921 patients included in the training cohort, 120 died (13%). Variables selected for the model were age, platelet count, SpO2, blood urea nitrogen (BUN), hemoglobin, C-reactive protein, neutrophil count, and sodium. The results of the fivefold cross-validation repeated 3-times gave AUROC of 0.87, and statistics of the classification matrix to the Youden index as follows: sensitivity 0.840, specificity 0.774, negative predictive value 0.971. Then, the model was tested on a new population (n = 1463) in which the case-fatality rate was 22.6%. The test model showed AUROC 0.818, sensitivity 0.813, specificity 0.650, negative predictive value 0.922. Considering the first quartile of the predicted risk score (low-risk score group), the case-fatality rate was 1.6%, 17.8% in the second and third quartile (high-risk score group) and 53.5% in the fourth quartile (very high-risk score group). The three risk score groups showed good discrimination for the P/F value at admission, and a positive correlation was found for the low-risk class to P/F at 48 h after admission (adjusted R-squared = 0.48). We developed a predictive model of death for people with SARS-CoV-2 infection by including only easy-to-obtain variables (abnormal blood count, BUN, C-reactive protein, sodium and lower SpO2). It demonstrated good accuracy and high power of discrimination. The simplicity of the model makes the risk prediction applicable for patients in the Emergency Department, or during hospitalization. Although it is reasonable to assume that the model is also applicable in not-hospitalized persons, only appropriate studies can assess the accuracy of the model also for persons at home
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