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The present study was planned to study the relationships between age, personality (according to Zuckerman’s and Gray’s psychobiological models) and decision-making styles in relation to risky driving behaviors. The participants were habitual drivers, 538 (54.3%) men and 453 (45.7%) women, with a mean age around 45 years and mainly of middle socioeconomic status. The results indicate that the youngest men and women reported more Lapses, Ordinary violations, and Aggressive violations than the oldest men and women. Women reported more Lapses (d = −0.40), and men more Ordinary (d = 0.33) and Aggressive violations (d = 0.28) when driving. Linear and non-linear analysis clearly support the role of both personality traits and decision-making styles in risky driving behaviors. Aggressiveness, Sensitivity to Reward, Sensation Seeking played the main role from personality traits, and Spontaneous and Rational decision-making style also accounted for some variance regarding risky driving behaviors. This pattern was broadly replicated in both genders. The discussion section analyses congruencies with previous literature and makes recommendations on the grounds of observed results.

In propositional logic, it is stated that “for if A is predicated for every B, and B for every C, A must necessarily be predicated of every C”. Following a similar logical process, it can be said that If A > B and B > C, then A > C, this is called transitive inference (TI). Piaget developed a verbal task to evaluate TI in children. Subsequent studies adapted this task for animals using a conditioned discrimination between five-terms sequence of stimuli A + B-, B + C-, C + D-, and D + E-. If subjects prefer B over D during test, it is assumed that TI has occurred. In this experiment, we analyzed the effects of task complexity on TI by using a five-terms sequence of stimuli associated with probabilistic outcomes during training, in pigeons. Thus, both stimuli are reinforced in each pair but with different probability, 0.8 for + stimulus and 0.2 for the—stimulus. We found that performance during C + D- pair is impaired and preference in the test pair BD is affected. However, this impairment is dependent on individual differences in performance in C + D- pair. We compare our findings with previous research and conclude that Pavlovian mechanisms, as well as ordering of stimuli, can account for our findings.

Introduction: Long QT syndrome is the main arrhythmogenic disease responsible for sudden death in infants, especially in the first days of life. Performing an electrocardiogram in newborns could enable early diagnosis and adoption of therapeutic measures focused on preventing lethal arrhythmogenic events. However, the inclusion of an electrocardiogram in neonatal screening protocols still remains a matter of discussion. To comprehensively analyse the potential clinical value of performing an electrocardiogram and subsequent follow-up in a cohort of newborns.Methods: Electrocardiograms were performed in 685 neonates within the first week of life. One year follow-up was performed if QTc > 450 ms identified. Comprehensive genetic analysis using massive sequencing was performed in all cases with QTc > 470 ms.Results: We identified 54 neonates with QTc > 450 ms/ 480 ms at birth and, if persistent, pharmacological treatment was administrated during follow-up. A rare variant was identified as the potential cause of long QT syndrome in five cases. Three cases showed a family history of sudden arrhythmogenic death.Conclusions: Our prospective study identifies 0.14% of cases with a definite long QT, supporting implementation of electrocardiograms in routine pediatric protocols. It is an effective, simple and non-invasive approach that can help prevent sudden death in neonates and their relatives. Genetic analyses help to unravel the cause of arrhythmogenic disease in diagnosing neonates. Further, clinical assessment and genetic analysis of relatives allowed early identification of family members at risk of arrhythmias helping to adopt preventive personalized measures.

Introduction: Any viral pandemic is a global health and mental health issue. The World Health Organization and mental health associations have warned that the current COVID-19 pandemic will lead to a drastic increase of stress-related conditions and mental health issues globally.Materials and Methods: An online web-based survey has been launched from 10 to 15 April 2020 in Paraguay in order to collect information regarding the stress related to the quarantine during the COVID-19 pandemic. It has been spread through social media (“WhatsApp,” “Twitter,” and “Facebook”). Two thousand two hundred and six Paraguayan citizens, over 18 years of age, completed the survey voluntarily. Socio-demographics as well as ratings at Self-perceived Stress Scale have been collected and analyzed.Results: Two thousand two hundred and six subjects (74.12% men) aged between 18 and 75 with an average of 34 ± 11 years old completed the survey. 12.42% (276 subjects) of sample reported a preexisting diagnosis of mental disorder, and 175 participants (7.93%) reported an increase of preexisting symptoms with the onset of COVID-19 quarantine. 41.97% of them had anxiety and 54.38% did not receive any specific treatment. The general population rated 18.10 ± 5.99 at Self-perceived Stress Scale, which indicates a moderate level of self-perceived stress. Significant association was found between higher levels of stress and female sex, being single, or reporting preexisting mental disorder, above all anxiety and depression (p < 0.01). In fact, in 63.87% of mentally ill subjects (n = 175), the quarantine has worsened symptoms of preexisting mental disorders.Conclusion: This study suggests a stressful impact of COVID-19 pandemic, with the majority of participants reporting a moderate level of self-perceived stress. We suggest mental health services to provide a phone-based or web-based support to the general population in order to contrast the psychological impact of the pandemic. This approach may improve the accessibility to mental healthcare services in Paraguay, especially in times of social distancing.

Introduction: Eating disorders (EDs) have increased globally in women of childbearing age, related to the concern for body shape promoted in industrialized countries. Pregnancy may exacerbate a previous ED or conversely may be a chance for improving eating patterns due to the mother's concern for the unborn baby. EDs may impact pregnancy evolution and increase the risk of adverse outcomes such as miscarriage, preterm delivery, poor fetal growth, or malformations, but the knowledge on this topic is limited.Methods: We performed a systematic review of studies on humans in order to clarify the mechanisms underpinning the adverse pregnancy outcomes in patients with EDs.Results: Although unfavorable fetal development could be multifactorial, maternal malnutrition, altered hormonal pathways, low pre-pregnancy body mass index, and poor gestational weight gain, combined with maternal psychopathology and stress, may impair the evolution of pregnancy. Environmental factors such as malnutrition or substance of abuse may also induce epigenetic changes in the fetal epigenome, which mark lifelong health concerns in offspring.Conclusions: The precocious detection of dysfunctional eating behaviors in the pre-pregnancy period and an early multidisciplinary approach comprised of nutritional support, psychotherapeutic techniques, and the use of psychotropics if necessary, would prevent lifelong morbidity for both mother and fetus. Further prospective studies with large sample sizes are needed in order to design a structured intervention during every stage of pregnancy and in the postpartum period.

Prenatal alcohol exposure is associated to different physical, behavioral, cognitive, and neurological impairments collectively known as fetal alcohol spectrum disorder. The underlying mechanisms of ethanol toxicity are not completely understood. Experimental studies during human pregnancy to identify new diagnostic biomarkers are difficult to carry out beyond genetic or epigenetic analyses in biological matrices. Therefore, animal models are a useful tool to study the teratogenic effects of alcohol on the central nervous system and analyze the benefits of promising therapies. Animal models of alcohol spectrum disorder allow the analysis of key variables such as amount, timing and frequency of ethanol consumption to describe the harmful effects of prenatal alcohol exposure. In this review, we aim to synthetize neurodevelopmental disabilities in rodent fetal alcohol spectrum disorder phenotypes, considering facial dysmorphology and fetal growth restriction. We examine the different neurodevelopmental stages based on the most consistently implicated epigenetic mechanisms, cell types and molecular pathways, and assess the advantages and disadvantages of murine models in the study of fetal alcohol spectrum disorder, the different routes of alcohol administration, and alcohol consumption patterns applied to rodents. Finally, we analyze a wide range of phenotypic features to identify fetal alcohol spectrum disorder phenotypes in murine models, exploring facial dysmorphology, neurodevelopmental deficits, and growth restriction, as well as the methodologies used to evaluate behavioral and anatomical alterations produced by prenatal alcohol exposure in rodents.

Transitive inference (TI) has been studied in humans and several animals such as rats, pigeons and fishes. Using different methods for training premises it has been shown that a non-trained relation between stimuli can be stablished, so that if A > B > C > D > E, then B > D. Despite the widely reported cases of TI, the specific mechanisms underlying this phenomenon remain under discussion. In the present experiment pigeons were trained in a TI procedure with four premises. After being exposed to all premises, the pigeons showed a consistent preference for B over D during the test. After overtraining C+D- alone, B was still preferred over D. However, the expected pattern of training performance (referred to as serial position effect) was distorted, whereas TI remained unaltered. The results are discussed regarding value transfer and reinforcement contingencies as possible mechanisms. We conclude that reinforcement contingencies can affect training performance without altering TI.

BackgroundHuman milk is the best option for feeding newborns, especially premature infants. In the absence of breast milk, milk from a human milk bank can be a suitable alternative. However, the nutritional content of human milk may be insufficient to meet these high requirements and milk fortification is needed. To facilitate the implementation of simpler and faster analyzers in neonatal healthcare facilities, this study focuses on the concordance analysis of two different analyzers, one based on mid-infrared and the other on ultrasound, in comparison to the Bradford method for determining protein concentration in human milk.MethodsMature milk samples from donor mothers were collected and pasteurized at the Human Milk Bank of Barcelona and protein quantification was performed using mid-infrared (MIRIS-HMA), ultrasound (MilkoScope Julie27), and the classical Bradford reference methods. The intraclass correlation coefficient (ICC) with 95% confidence interval and Bland–Altman plots were used to assess the agreement between methods.ResultsThe mean protein concentration of 142 milk samples calculated using MIRIS-HMA, MilkoScope, and the Bradford assay were 1.38, 1.15, and 1.19 g/100 ml, respectively. The ICC was 0.70 for MIRIS-HMA vs. Bradford and 0.37 for MilkoScope vs. Bradford.ConclusionMIRIS-HMA obtained a better agreement with the Bradford technique and is a promising method for developing new devices based on MIR transmission spectroscopy principles. This study confirms how MIRIS-HMA can be used to accurately calculate the protein concentration of human milk.

IntroductionFetal alcohol spectrum disorders include a variety of physical and neurocognitive disorders caused by prenatal alcohol exposure. Although their overall prevalence is around 0.77%, FASD remains underdiagnosed and little known, partly due to the complexity of their diagnosis, which shares some symptoms with other pathologies such as autism spectrum, depression or hyperactivity disorders.MethodsThis study included 73 control and 158 patients diagnosed with FASD. Variables selected were based on IOM classification from 2016, including sociodemographic, clinical, and psychological characteristics. Statistical analysis included Kruskal-Wallis test for quantitative factors, Chi-square test for qualitative variables, and Machine Learning (ML) algorithms for predictions.ResultsThis study explores the application ML in diagnosing FASD and its subtypes: Fetal Alcohol Syndrome (FAS), partial FAS (pFAS), and Alcohol-Related Neurodevelopmental Disorder (ARND). ML constructed a profile for FASD based on socio-demographic, clinical, and psychological data from children with FASD compared to a control group. Random Forest (RF) model was the most efficient for predicting FASD, achieving the highest metrics in accuracy (0.92), precision (0.96), sensitivity (0.92), F1 Score (0.94), specificity (0.92), and AUC (0.92). For FAS, XGBoost model obtained the highest accuracy (0.94), precision (0.91), sensitivity (0.91), F1 Score (0.91), specificity (0.96), and AUC (0.93). In the case of pFAS, RF model showed its effectiveness, with high levels of accuracy (0.90), precision (0.86), sensitivity (0.96), F1 Score (0.91), specificity (0.83), and AUC (0.90). For ARND, RF model obtained the best levels of accuracy (0.87), precision (0.76), sensitivity (0.93), F1 Score (0.84), specificity (0.83), and AUC (0.88). Our study identified key variables for efficient FASD screening, including traditional clinical characteristics like maternal alcohol consumption, lip-philtrum, microcephaly, height and weight impairment, as well as neuropsychological variables such as the Working Memory Index (WMI), aggressive behavior, IQ, somatic complaints, and depressive problems.DiscussionOur findings emphasize the importance of ML analyses for early diagnoses of FASD, allowing a better understanding of FASD subtypes to potentially improve clinical practice and avoid misdiagnosis.

IntroductionEven though infant crying is a common phenomenon in humans’ early life, it is still a challenge for researchers to properly understand it as a reflection of complex neurophysiological functions. Our study aims to determine the association between neonatal cry acoustics with neurophysiological signals and behavioral features according to different cry distress levels of newborns.MethodsMultimodal data from 25 healthy term newborns were collected simultaneously recording infant cry vocalizations, electroencephalography (EEG), near-infrared spectroscopy (NIRS) and videos of facial expressions and body movements. Statistical analysis was conducted on this dataset to identify correlations among variables during three different infant conditions (i.e., resting, cry, and distress). A Deep Learning (DL) algorithm was used to objectively and automatically evaluate the level of cry distress in infants.ResultsWe found correlations between most of the features extracted from the signals depending on the infant’s arousal state, among them: fundamental frequency (F0), brain activity (delta, theta, and alpha frequency bands), cerebral and body oxygenation, heart rate, facial tension, and body rigidity. Additionally, these associations reinforce that what is occurring at an acoustic level can be characterized by behavioral and neurophysiological patterns. Finally, the DL audio model developed was able to classify the different levels of distress achieving 93% accuracy.ConclusionOur findings strengthen the potential of crying as a biomarker evidencing the physical, emotional and health status of the infant becoming a crucial tool for caregivers and clinicians.

Background: Data analysis techniques such as machine learning have been used for assisting in triage and the diagnosis of health problems. Nevertheless, it has not been used yet to assist community pharmacists with services such as the Minor Ailment Services These services have been implemented to reduce the burden of primary care consultations in general medical practitioners (GPs) and to allow a better utilization of community pharmacists’ skills. However, there is a need to refer high-risk patients to GPs.Aim: To develop a predictive model for high-risk patients that need referral assisting community pharmacists’ triage through a minor ailment service.Method: An ongoing pragmatic type 3 effectiveness-implementation hybrid study was undertaken at a national level in Spanish community pharmacies since October 2020. Pharmacists recruited patients presenting with minor ailments and followed them 10 days after the consultation. The main outcome measured was appropriate medical referral (in accordance with previously co-designed protocols). Nine machine learning models were tested (three statistical, three black box and three tree models) to assist pharmacists in the detection of high-risk individuals in need of referral.Results: Over 14′000 patients were included in the study. Most patients were female (68.1%). With no previous treatment for the specific minor ailment (68.0%) presented. A percentage of patients had referral criteria (13.8%) however, not all of these patients were referred by the pharmacist to the GP (8.5%). The pharmacists were using their clinical expertise not to refer these patients. The primary prediction model was the radial support vector machine (RSVM) with an accuracy of 0.934 (CI95 = [0.926,0.942]), Cohen’s kappa of 0.630, recall equal to 0.975 and an area under the curve of 0.897. Twenty variables (out of 61 evaluated) were included in the model. radial support vector machine could predict 95.2% of the true negatives and 74.8% of the true positives. When evaluating the performance for the 25 patient’s profiles most frequent in the study, the model was considered appropriate for 56% of them.Conclusion: A RSVM model was obtained to assist in the differentiation of patients that can be managed in community pharmacy from those who are at risk and should be evaluated by GPs. This tool potentially increases patients’ safety by increasing pharmacists’ ability to differentiate minor ailments from other medical conditions.

In the basic verbal task from Piaget, when a relation of the form if A > B and B > C is given, a logical inference A > C is expected. This process is called transitive inference (TI). The adapted version for animals involves the presentation of a simultaneous discrimination between stimuli pairs. In this way, when A+B−, B+C−, C+D−, D+E− is trained, a B>D preference is expected, assuming that if A>B>C>D>E, then B>D. This effect has been widely reported using several procedures and different species. In the current experiment TI was evaluated employing probabilistic reinforcement. Thus, for the positive stimuli a .7 probability was administered and for the negative stimuli a .3 probability was administered. Under this arrangement the relation A>B>C>D>E is still allowed, but TI becomes more difficult. Five pigeons (Columba Livia) were exposed to the mentioned arrangement. Only one pigeon reached the criterion in C+D− discrimination, whereas the remaining did not. Only the one who successfully solved C+D− was capable of learning TI, whereas the others were not. Additionally, it was found that correct response ratios did not predict BD performance. Consequently, probabilistic reinforcement disrupted TI, but some positional ordering was retained in the test. The results suggest that TI might be affected by associative strength but also by the positional ordering of the stimuli. The discussion addresses the two main accounts of TI: the associative account and the ordinal representation account.

BackgroundDuring early skin-to-skin contact (ESSC), alterations in peripheral oxygen saturation (SpO2) and heart rate (HR) have been frequently observed.ObjectivesThis study aimed to determine the incidence of cardiorespiratory events (CREs) during ESSC in healthy term newborns (HTNs) and estimate the association of maternal and neonatal prognostic factors with the risk of CREs.MethodsA pooled analysis of the cohort from a clinical trial involving healthy mother–child dyads during ESSC was performed. Pulse oximetry was employed to continuously monitor SpO2 and HR within 2 h after birth. The individual and combined prognostic relevance of the demographic and clinical characteristics of dyads for the occurrence of a CRE (SpO2 180 bpm) was analyzed through logistic regression models.ResultsOf the 254 children assessed, 169 [66.5%; 95% confidence interval (95% CI), 60.5–72.5%] had at least one CRE. The characteristics that increased the risk of CRE were maternal age ≥35 years (odds ratio, 2.21; 95% CI, 1.19–4.09), primiparity (1.96; 1.03–3.72), gestational body mass index (BMI) >25 kg/m2 (1.92; 1.05–3.53), and birth time between 09:00 p.m. and 08:59 a.m. (2.47; 1.02–5.97).ConclusionCREs were more frequent in HTNs born during nighttime and in HTNs born to first-time mothers, mothers ≥35 years, and mothers with a gestational BMI >25 kg/m2. These predictor variables can be determined during childbirth. Identification of neonates at higher risk of developing CREs would allow for closer surveillance during ESSC.

The oceans are a fundamental source for climate balance, sustainability of resources and life on Earth, therefore society has a strong and pressing interest in maintaining and, where possible, restoring the health of the marine ecosystems. Effective, integrated ocean observation is key to suggesting actions to reduce anthropogenic impact from coastal to deep-sea environments and address the main challenges of the 21st century, which are summarized in the UN Sustainable Development Goals and Blue Growth strategies. The European Multidisciplinary Seafloor and water column Observatory (EMSO), is a European Research Infrastructure Consortium (ERIC), with the aim of providing long-term observations via fixed-point ocean observatories in key environmental locations across European seas from the Arctic to the Black Sea. These may be supported by ship-based observations and autonomous systems such as gliders. In this paper, we present the EMSO Generic Instrument Module (EGIM), a deployment ready multi-sensor instrumentation module, designed to measure physical, biogeochemical, biological and ecosystem variables consistently, in a range of marine environments, over long periods of time. Here, we describe the system, features, configuration, operation and data management. We demonstrate, through a series of coastal and oceanic pilot experiments that the EGIM is a valuable standard ocean observation module, which can significantly improve the capacity of existing ocean observatories and provides the basis for new observatories. The diverse examples of use included the monitoring of fish activity response upon oceanographic variability, hydrothermal vent fluids and particle dispersion, passive acoustic monitoring of marine mammals and time series of environmental variation in the water column. With the EGIM available to all the EMSO Regional Facilities, EMSO will be reaching a milestone in standardization and interoperability, marking a key capability advancement in addressing issues of sustainability in resource and habitat management of the oceans.

The purpose of this study was to evaluate the efficacy and feasibility of a 4-week planned osteopathic manipulative treatment intervention on the improvement of neurocognitive and behavioral symptoms usually associated with fetal alcohol spectrum disorder. Thirty-two symptomatic children without fetal alcohol spectrum disorder aged 3–6 years with low level of attention from two schools and an osteopathic center were recruited in a prospective randomized pilot study in an osteopathic manipulative treatment group [osteopathic manipulative treatment (OMT)] or a control group (standard support measures). Neurocognitive maturity test results for attention (A), iconic memory (IM), spatial structuration (SS), and visual perception (VP) were recorded at baseline and post-intervention. No adverse effects were communicated and there were no dropouts. A significant increase in neurocognitive assessments was observed in children in the OMT group at post-treatment. Intergroup post-intervention statistical differences were found for A, SS, and IM were p = 0.005, p < 0.001, and p < 0.001, respectively; no differences were seen for VP (p = 0.097). This study shows that a 4-week osteopathic manipulative treatment intervention may be a feasible and effective therapeutic approach for neurocognitive and behavioral symptoms usually present in fetal alcohol spectrum disorder, justifying more studies on children affected by this condition.

Solenogastres are vermiform marine molluscs characterised by an aculiferous mantle, a longitudinal ventral pedal groove and a terminal or subterminal pallial cavity. Their classification is based in part on the type of mantle sclerites, but identification to even the family level generally requires the study of internal anatomical characters. Taxonomically important internal characters include those related to radular structure, the type of ventrolateral glandular organs of the pharynx and the reproductive system, among others. In order to study their internal anatomical organisation, according to the classical reconstruction method, serial histological sections of specimens are made, from which the 2D internal anatomy of the specimen can be reconstructed manually. However, this is a time-consuming technique that results in destruction of the specimen. Computed microtomography or micro-CT is a non-destructive technique based on the measurement of the attenuation of X-rays as they pass through a specimen. Micro-CT is faster than histology for studying internal anatomy and it is non-destructive, meaning that specimens may be used for e.g., DNA extraction or retained as intact vouchers. In this paper, the utility of micro-CT for studying taxonomically important internal anatomical structures was assessed. Results of the 3D anatomical study of the soft parts of four specimens of three species using micro-CT are presented: Proneomenia sluiteriHubrecht, 1880, Dorymenia menchuescribanaeGarcía-Álvarez et al., 2000 and Anamenia gorgonophilaKowalevsky, 1880. Micro-CT enabled detailed study of most taxonomically important anatomical characters, precise measurements of structures, and observation of the relative position of organs from a variety of angles. However, it was not possible to observe the radula and some details of the ventral foregut organs could not be discerned. Despite these limitations, results of this study highlight micro-CT as a valuable tool to compliment histology in the study of solenogaster anatomy and in non-destructively identifying animals to the family and even genus-level.

The ambiguous-cue task is composed of two-choice simultaneous discriminations involving three stimuli: positive (P), ambiguous (A), and negative (N). Two different trial types are presented: PA and NA. The ambiguous cue (A) served as an S- in PA trials, but as an S+ in NA trials. When using this procedure, it is typical to observe a less accurate performance in PA trials than in NA trials. This is called the ambiguous-cue effect. Recently, it was reported in starlings that the ambiguous-cue effect decreases when the stimuli are presented on an angled (120°) panel. The hypothesis is that the angled panel facilitates that the two cues from each discrimination are perceived as a compound, precluding value transfer via a second-order conditioning mechanism. In this experiment, we used pigeons and a flat panel. Nevertheless, our data were quite similar to the previous data in starlings. We conclude that the form of the panel cannot explain the ambiguous-cue effect. Several alternatives to be explored in future experiments are suggested. The riddle of the ambiguous-cue problem still remains unsolved.