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Abstract Misinformation surrounding crises poses a significant challenge for public institutions. Understanding the relative effectiveness of different types of interventions to counter misinformation, and which segments of the population are most and least receptive to them, is crucial. We conducted a preregistered online experiment involving 5228 participants from Germany, Greece, Ireland, and Poland. Participants were exposed to misinformation on climate change or COVID-19. In addition, they were pre-emptively exposed to a prebunk, warning them of commonly used misleading strategies, before encountering the misinformation, or were exposed to a debunking intervention afterwards. The source of the intervention (i.e. the European Commission) was either revealed or not. The findings show that both interventions change four variables reflecting vulnerability to misinformation in the expected direction in almost all cases, with debunks being slightly more effective than prebunks. Revealing the source of the interventions did not significantly impact their overall effectiveness. One case of undesirable effect heterogeneity was observed: debunks with revealed sources were less effective in decreasing the credibility of misinformation for people with low levels of trust in the European Union (as elicited in a post-experimental questionnaire). While our results mostly suggest that the European Commission, and possibly other public institutions, can confidently debunk and prebunk misinformation regardless of the trust level of the recipients, further evidence on this is needed.

Abstract Communication by rare, binary spikes is a key factor for the energy efficiency of biological brains. However, it is harder to train biologically-inspired spiking neural networks than artificial neural networks. This is puzzling given that theoretical results provide exact mapping algorithms from artificial to spiking neural networks with time-to-first-spike coding. In this paper we analyze in theory and simulation the learning dynamics of time-to-first-spike-networks and identify a specific instance of the vanishing-or-exploding gradient problem. While two choices of spiking neural network mappings solve this problem at initialization, only the one with a constant slope of the neuron membrane potential at threshold guarantees the equivalence of the training trajectory between spiking and artificial neural networks with rectified linear units. For specific image classification architectures comprising feed-forward dense or convolutional layers, we demonstrate that deep spiking neural network models can be effectively trained from scratch on MNIST and Fashion-MNIST datasets, or fine-tuned on large-scale datasets, such as CIFAR10, CIFAR100 and PLACES365, to achieve the exact same performance as that of artificial neural networks, surpassing previous spiking neural networks. Our approach accomplishes high-performance classification with less than 0.3 spikes per neuron, lending itself for an energy-efficient implementation. We also show that fine-tuning spiking neural networks with our robust gradient descent algorithm enables their optimization for hardware implementations with low latency and resilience to noise and quantization.

Abstract Breast cancer is a prevalent and significant cause of mortality in women, and manifests as six molecular subtypes. Its further histologic classification into non-invasive ductal or lobular carcinoma (DCIS) and invasive carcinoma (ILC or IDC) underscores its heterogeneity. The ubiquitin–proteasome system plays a crucial role in breast cancer, with inhibitors targeting the 26S proteasome showing promise in clinical treatment. The Cullin-RING ubiquitin ligases, including CUL3, have direct links to breast cancer. This study focuses on CUL3 as a potential biomarker, leveraging high-throughput sequencing, gene expression profiling, experimental and data analysis tools. Through comprehensive analysis using databases like GEPIA2 and UALCAN, as well as TCGA datasets, CUL3's expression and its association with prognostic values were assessed. Additionally, the impact of CUL3 overexpression was explored in MCF-7 and MDA-MB-231 breast cancer cell lines, revealing distinct differences in molecular and phenotypic characteristics. We further profiled its expression and localization in breast cancer tissues identifying prominent differences between luminal A and TNBC tumors. Conclusively, CUL3 was found to be associated with cell cycle progression, and DNA damage response, exhibiting diverse roles depending on the tumor's molecular type. It exhibits a tendency to act as an oncogene in triple-negative tumors and as a tumor suppressor in luminal A types, suggesting a potential significance in breast cancer progression and therapeutic directions.

Little is known about the cognitive effort associated with algebraic activity in the elementary and middle school grades. However, this investigation is significant for sensitizing teachers and researchers to the mental demands of algebra learning. In this paper, we focus on the relationship between algebraic thinking and domain-general cognitive abilities. The sample of the study comprised 591 students from grades 4 to 7. The students' abilities in algebraic thinking were assessed through a test that involved three task categories: generalized arithmetic, functional thinking, and modelling languages. Test batteries were used to assess students' domain-general cognitive abilities in terms of analogical, serial, spatial, and deductive reasoning. The results of structural equation modelling analysis indicated that: (1) analogical reasoning predicts students' abilities only in generalized arithmetic; (2) serial reasoning predicts students' abilities only in generalized arithmetic; (3) spatial reasoning predicts students' abilities in functional thinking and modelling languages; and (4) deductive reasoning predicts students' abilities in all three categories. Differences between students across grades are also discussed.

The autoimmune process that induces type 1 diabetes can also affect other organs, leading to the development of additional autoimmune diseases in patients, thus hindering diabetes control. The most common comorbidities include autoimmune thyroid diseases and celiac disease. Globally, this subject is increasingly drawing the attention of researchers, given the magnitude and severity of the association between autoimmune diseases and type 1 diabetes. The aim of the present study is to assess the prevalence of autoimmune diseases, with the primary focus on celiac disease, associated with type 1 diabetes in children and adolescents, as well as their impact on the progression of type 1 diabetes. Material and methods: The present study was conducted within the Pediatric Section, Pediatric Diabetology Department of the Emergency Clinical Hospital “St. Apostle Andrew” in Constanța, including 15 cases diagnosed with type 1 diabetes in children during the period 2017-2022. Results: The patients included in the study are aged between 1 and 13 years highlighting the age group of 3-6 years as the most commonly encountered. The most commonly encountered HbA1c values are in the range of 10-12%, accounting for 53% of the total, we can thus observe a prevalence of high and very high HbA1c values. In order to confirm the diagnosis of type 1 diabetes, specific antibodies were sampled, 97% of patients being tested positive for at least one antibody. Conclusions: The association between diabetes mellitus and another autoimmune disease is encountered at a relatively high percentage. Higher levels of HbA1c at the onset of type 1 diabetes have been associated with an increased risk of long-term complications.

Background: In the pediatric intensive care unit (PICU), sepsis, sepsis syndromes, septic shock, and multiorgan system failure are frequently encountered and are considered important conditions; Methods: This is a retrospective, observational study over a period of 3 years, that is aimed to investigate the predictive role of lactate levels at admission in order to evaluate disease progression of pediatric patients with septic shock syndrome with the role to identify whether lactate levels at admission could serve as a significant predictor of adverse outcomes. The sample consisted of 21 patients between 1 and 36 months, diagnosed and treated for hemodynamic shock in a tertiary center; Results: The study found that lactate level at admission greater than or equal to 4.95 was associated with 32.5 times increased odds of serious evolution. The study also identified other potential predictors, such as lactate level 12 hours after admission, hemodynamic parameters, and demographic factors; Conclusions: These findings suggest that monitoring lactate levels at admission can provide important information to predict mortality and guiding treatment decisions in pediatric patients with shock syndrome.

This study investigated the role of online applets in early algebra lessons. The effect of two different types of intervention modules on developing students' early algebraic thinking abilities was compared. The first intervention module involved the use of open applets and real-life contexts (open-real). The second intervention module involved the use of closed applets and pure mathematics contexts (closed/pure). "Open" applets are considered to promote more explorative ways of working with mathematical ideas, whereas "closed" applets are considered to guide students' ways of working through more sequential, step-by-step approaches. Real-life contexts present everyday applications of mathematics, where pure mathematics contexts focus on the mathematical concepts and procedures, with no reference to the way they could be associated with real-life situations. Nevertheless, both intervention modules followed an inquiry-based approach. The total number of the participants were 96 young students of Grade 5 with an average age of 10,5 years old. These students were tested through a pre- and a post-test on early algebraic thinking. The test involved three categories of early algebra tasks: generalized arithmetic, functional thinking, and modeling languages. Data from the pre- and post-test comparison showed that students who participated in the "open/real" module had a statistically significant higher improvement in functional thinking compared to students who participated in the "closed/pure" module. There were no statistically significant differences between the improvement of the two groups of students in generalized arithmetic and modeling languages. These findings offer pedagogical implications in respect to the design of early algebra lessons that take advantage of the affordances of available educational technology.

Background: Iron deficiency (ID) is a global problem that affects women more prevalently, causing vast health consequences. Screening by hemoglobin and serum ferritin is currently applied for ID. Recently, interest in complete blood count parameters (CBC) has emerged for its close relationship with body iron stores. Objectives: to examine whether hematological indices of CBC [namely red cell distribution width-coefficient of variation (RDW-CV) and platelets distribution width-coefficient of variation (PDW-CV)] can serve as a predictor for ID in Iraqi women. Subjects and Methods: A cross-sectional study at the National Center of Hematology recruited 200 women into a study group: 100 anemic women and 100 healthy controls. Their demographics, hematological indices, and iron indicators (serum ferritin, iron, total iron binding capacity (TIBC), and transferrin saturation) were collected. Results: The RDW-CV and platelet counts were statistically higher in the IDA cases, while PDW was lower. RDW had significant correlation to serum ferritin (r=-0.2, P=0.04), while PDW was significantly linked to serum ferritin (0.22, P=0.03) TIBC (r=-0.24, P=0.02) and TSP (r-0.23, P=0.02). RDW had the highest positive and negative predictive values, with 84 and 97 %, respectively, followed by platelet counts, which scored 72 and 78 %, respectively. RDW-CV cutoff value scored the highest sensitivity, 97%, and specificity, 82%, in discriminating ID cases from healthy controls with an area under the curve of 0.98 and P

The omega-3 polyunsaturated fatty acids (PUFAs) Docosahexaenoic acid (DHA) and Eicosapentaenoic acid (EPA) exert multiple cardioprotective effects, influencing inflammation, platelet activation, endothelial function and lipid metabolism, besides their well-established triglyceride lowering properties. It is not uncommon for omega-3 PUFAs to be prescribed for hypertriglyceridemia, alongside antiplatelet therapy in cardiovascular disease (CVD) patients. In this regard, we studied the effect of EPA and DHA, in combination with antiplatelet drugs, in platelet aggregation and P-selectin and αIIbβ3 membrane expression. The antiplatelet drugs aspirin and triflusal, inhibitors of cyclooxygenase-1 (COX-1); ticagrelor, an inhibitor of the receptor P2Y12; vorapaxar, an inhibitor of the PAR-1 receptor, were combined with DHA or EPA and evaluated against in vitro platelet aggregation induced by agonists arachidonic acid (AA), adenosine diphosphate (ADP) and TRAP-6. We further investigated procaspase-activating compound 1 (PAC-1) binding and P-selectin membrane expression in platelets stimulated with ADP and TRAP-6. Both DHA and EPA displayed a dose-dependent inhibitory effect on platelet aggregation induced by AA, ADP and TRAP-6. In platelet aggregation induced by AA, DHA significantly improved acetylsalicylic acid (ASA) and triflusal’s inhibitory activity, while EPA enhanced the inhibitory effect of ASA. In combination with EPA, ASA and ticagrelor expressed an increased inhibitory effect towards ADP-induced platelet activation. Both fatty acids could not improve the inhibitory effect of vorapaxar on AA- and ADP-induced platelet aggregation. In the presence of EPA, all antiplatelet drugs displayed a stronger inhibitory effect towards TRAP-6-induced platelet activation. Both omega-3 PUFAs inhibited the membrane expression of αIIbβ3, though they had no effect on P-selectin expression induced by ADP or TRAP-6. The antiplatelet drugs exhibited heterogeneity regarding their effect on P-selectin and αIIbβ3 membrane expression, while both omega-3 PUFAs inhibited the membrane expression of αIIbβ3, though had no effect on P-selectin expression induced by ADP or TRAP-6. The combinatory effect of DHA and EPA with the antiplatelet drugs did not result in enhanced inhibitory activity compared to the sum of the individual effects of each component.

The most frequent hyperglycemic emergency is diabetic ketoacidosis (DKA), which puts individuals with diabetes mellitus at the highest risk of mortality that may be avoided. DKA affects people with type 1 diabetes more frequently than type 2, with 30% of occurrences in patients who have already been diagnosed with type 2 diabetes. High blood sugar level, ketosis and metabolic acidosis are symptoms of DKA. The aim of the study is to emphasize the main manifestation of type 1 diabetes which is diabetic ketoacidosis, as well as, to analyze the factors predisposing to recurrent episodes of diabetic ketoacidosis. Material and Methods. The retrospective study was conducted on a period between 2017-2022, including hospitalized children aged between 0-16 years with recurrent diabetic ketoacidosis within the Pediatric Clinic of Clinical Emergency Hospital “St. Andrew the Apostle” Constanta, aiming to analyze the factors predisposing to recurrent episodes of diabetic ketoacidosis according to age, sex, environment, socio-economic status, heredo-collateral antecedents, symptoms, personal pathological history, clinical and laboratory data. Results. It was observed that the incidence of episodes of diabetic ketoacidosis increased considerably since 2019, the maximum being recorded in 2020, while the lowest percentage is in 2017. During 2020–2021, the age group of 10–14 years presented. Genetic sex remains a nonmodifiable risk factor that is thought to play a role in terms of glycemic control, but also the occurrence of complications in patients with type 1 diabetes. It was shown that 37% of the causes of the recurrence of DKA episodes were found to be diet variation, 28% to be viral diseases, 26% to be insulin administration errors, 6% to be trauma, and only 3% to be Mauriac syndrome. Conclusions. Numerous research from the medical literature have supported the hypothesis that SARS-CoV-2 may be a catalyst for autoimmunity in the pathogenesis of type 1 diabetes, indicating a causal connection between the two illnesses. It has been established that diet non-compliance is the primary cause of recurrent episodes of ketoacidosis.

Introduction. Gut microbiota is a microecosystem with a dynamic complexity, influenced by multiple factors, with impact on the composition and long-term health. An imbalance in gut microbiota, often termed as ‘dysbiosis’, is associated with a wide variety of pediatric diseases, including allergies, diabetes mellitus, autoimmune diseases, autism spectrum disorders and celiac disease. The aim of the study is to emphasize the main clinical manifestations and to analyze the risk factors of gut dysbiosis in the first three years of life. Material and Methods. The retrospective study was conducted on a period between 2020-2022, including children aged between 0-3 years with intestinal dysbiosis, aiming to analyses the factors predisposing to imbalance in gut composition according to age, gender, environmental factors, personal medical history, clinical manifestations, and laboratory data. Results and Discussions. Main clinical manifestations of dysbiosis in the first three years of life are represented by abdominal pain, vomiting, irritability, diarrheal stools and stools with mucus. C-section represents a major risk factor for the occurrence of gut dysbiosis in infants. Low birth weight is a risk factor due to imbalance of intestine function and high susceptibility to dysbiosis. Infant formulas determine a low concentration of beneficial bacteria. Urban area represents an environmental factor with increased susceptibility of subjects for gut dysbiosis. Antibiotherapy in the first year of life is a factor which determines a low microbial diversity in infants. Conclusions. The interplay between intestinal microbiota, environment and host is a multidirectional relationship. Factors such as mode of delivery, type of feeding, weight, living conditions and antibiotherapy have an influence on the modulation of the microbiological milieu in the first three years of life, with impact on long-term health.

Aim of the study. This study aimed to evaluate malondialdehyde status and dyslipidemia in diabetic children. In children, type 1 diabetes mellitus (T1DM) is considered one of the most common chronic autoimmune diseases. The first step is detecting insulin deficiency expressed by hyperglycemia. The short- and long-term effects are significant and affect all body parts: blood vessels, eyes, kidneys, brain, heart, and nerves. Persistent hyperglycemia generates reactive oxygen species (ROS) / free radicals through metabolic abnormalities such as glucose autooxidation and non-enzymatic glycation. Materials and methods. This study included 50 children with T1DM with a mean age of 7.6 years. Important elements were evaluated to establish clear indicators of atherosclerotic activity (lipoperoxidation, protein oxidation, changes in the status of antioxidant defense systems, plasma oxygen radical absorbance capacity (ORAC), glycated hemoglobin (HbA1c), total cholesterol, and triglycerides). Results. Malondialdehyde (MDA) and lipid levels were correlated and significantly higher (0,87 ± 0.2 versus 1,8 ± 0,87 µmol/L, 66,33 +/-14,21 versus 43,33 +/- 7,2 respectively; P < 0.001), and a significant reduction in plasma total antioxidant capacity. Conclusions. MDA levels presented elevated values, indicating the negative connection between atherosclerotic risk factors and MDA. This important conclusion can be drawn every time a patient with type 1 diabetes presents LDL excess levels, therefore representing an increased lipid peroxidation resulting in higher MDA levels. From this point, the correlation between hyperglycemia (the main source of increased oxidative stress) in patients with poor metabolic control and MDA is not the only path to anticipate the risk of atherosclerotic complications.

Abstract Visual oddity task was conceived to study universal ethnic-independent analytic intelligence of humans from a perspective of comprehension of spatial concepts. Advancements in artificial intelligence led to important breakthroughs, yet excelling at such abstract tasks remains challenging. Current approaches typically resort to non-biologically-plausible architectures with ever-growing models consuming substantially more energy than the brain. Motivated by the brain’s efficiency and reasoning capabilities, we present a biologically inspired system that receives inputs from synthetic eye movements – reminiscent of saccades, and processes them with neuronal units incorporating dynamics of neocortical neurons. We introduce a procedurally generated visual oddity dataset to train an architecture extending conventional relational networks and our proposed system. We demonstrate that both approaches are capable of abstract problem-solving at high accuracy, and we uncover that both share the same essential underlying mechanism of reasoning in seemingly unrelated aspects of their architectures. Finally, we show that the biologically inspired network achieves superior accuracy, learns faster and requires fewer parameters than the conventional network.