Redefining operant conditioning of escape behaviour in lymnaea stagnalis

The escape behaviour is one of the many behavioural responses that can be operantly conditioned in a stimulus-dependent manner in both vertebrates and invertebrates. By exposing the pond snail Lymnaea stagnalis repeatedly to a negative reinforcement its natural tendency to explore its surroundings can be operantly conditioned in both adult and aged snails. When adult snails were trained with 100 mM of KCl their number of escapes was significantly decreased and the latency to first escape was significantly increased. Our behavioural protocol allowed us to investigate memory acquisition, consolidation, and retrieval in pre-and post-training sessions over different days. From the 3rd day of training the learned response was strengthened: the number of the escapes in the post-test session remained significantly reduced even when animals were presented with distilled water. Moreover, adult snails exposed to the negative reinforcement for at least 4 days started to escape significantly less than the control group also in the pre-test session. This effect became more pronounced in the following days and was accompanied by a significant increase in the latency to first escape at the beginning of the pre-test on day 6 and 7. Aged snails, instead, showed selective deficiencies when operantly conditioned: memory retention appeared only after 7 days, while memory retrieval could not be induced. This redefined paradigm can help unravelling a variety of sophisticated cognitive phenomena in L. stagnalis and could be employed also to study the basis of memory impairment occurring during neuro-aging

Lymnaea stagnalis as model for translational neuroscience research: from pond to bench

The purpose of this review is to illustrate how a reductionistic, but sophisticated, approach based on the use of a simple model system such as the pond snail Lymnaea stagnalis (L. stagnalis), might be useful to address fundamental questions in learning and memory. L. stagnalis, as a model, provides an interesting platform to investigate the dialog between the synapse and the nucleus and vice versa during memory and learning. More importantly, the "molecular actors" of the memory dialogue are well-conserved both across phylogenetic groups and learning paradigms, involving single- or multi-trials, aversion or reward, operant or classical conditioning. At the same time, this model could help to study how, where and when the memory dialog is impaired in stressful conditions and during aging and neurodegeneration in humans and thus offers new insights and targets in order to develop innovative therapies and technology for the treatment of a range of neurological and neurodegenerative disorders

Emotional, Behavioral, and Physical Health Consequences in Caregivers of Children with Cancer: A Network Analysis Differentiation in Mothers’ and Fathers’ Reactivity

Background: Pediatric cancer presents mental and physical challenges for patients and their caregivers. However, parental distress has been understudied despite its negative impact on quality of life, disability, and somatic disorders. Parents of oncopediatric patients experience high levels of suffering with their resilience tested throughout their children’s illness. Identifying at-risk parents and offering specific treatments is crucial and urgent to prevent or alleviate negative outcomes. Methods: This study used statistical and network analyses to examine symptom patterns assessed by the Kellner Symptom Questionnaire in 16 fathers and 23 mothers at different time points: diagnosis, treatment, and discharge. Results: The results indicated significantly higher distress levels in parents of oncopediatric children compared to the control reference population. Gender-specific differences in symptom profiles were observed at each time point, and symptoms showed a gradual but non-significant decrease over time. Conclusions: The network analysis yielded valuable insights that, when applied in clinical practice, can guide the implementation of timely treatments to prevent and manage parental distress, thus addressing long-term, stress-related issues in primary caregivers of children diagnosed and treated for cancer

Psychosocial assessment of families caring for a child with acute lymphoblastic leukemia, epilepsy or asthma: Psychosocial risk as network of interacting symptoms

The purpose of this study is to assess psychosocial risk across several pediatric medical conditions and test the hypothesis that different severe or chronic pediatric illnesses are characterized by disease specific enhanced psychosocial risk and that risk is driven by disease specific connectivity and interdependencies among various domains of psychosocial function using the Psychosocial Assessment Tool (PAT). In a multicenter prospective cohort study of 195 patients, aged 5-12, 90 diagnosed with acute lymphoblastic leukemia (ALL), 42 with epilepsy and 63 with asthma, parents completed the PAT2.0 or the PAT2.0 generic version. Multivariate analysis was performed with disease as factor and age as covariate. Graph theory and network analysis was employed to study the connectivity and interdependencies among subscales of the PAT while data-driven cluster analysis was used to test whether common patterns of risk exist among the various diseases. Using a network modelling approach analysis, we observed unique patterns of interconnected domains of psychosocial factors. Each pathology was characterized by different interdependencies among the most central and most connected domains. Furthermore, data-driven cluster analysis resulted in two clusters: patients with ALL (89%) mostly belonged to cluster 1, while patients with epilepsy and asthma belonged primarily to cluster 2 (83% and 82% respectively). In sum, implementing a network approach improves our comprehension concerning the character of the problems central to the development of psychosocial difficulties. Therapy directed at problems related to the most central domain(s) constitutes the more rational one because such an approach will inevitably carry over to other domains that depend on the more central function

A network study to differentiate suicide attempt risk profiles in male and female patients with major depressive disorder

Suicide attempts are a possible consequence of Major Depressive Disorder (MDD), although their prevalence varies across different epidemiological studies. Suicide attempt is a significant predictor of death by suicide, highlighting its importance in understanding and preventing tragic outcomes. Researchers are increasingly recognizing the need to study the differences between males and females, as several distinctions emerge in terms of the characteristics, types and motivations of suicide attempts. These differences emphasize the importance of considering gender-specific factors in the study of suicide attempts and developing tailored prevention strategies. We conducted a network analysis to represent and investigate which among multiple neurocognitive, psychosocial, demographic and affective variables may prove to be a reliable predictor for identifying the 'suicide attempt risk' (SAR) in a sample of 81 adults who met DSM-5 criteria for MDD. Network analysis resulted in differences between males and females regarding the variables that were going to interact and predict the SAR; in particular, for males, there is a stronger link toward psychosocial aspects, while for females, the neurocognitive domain is more relevant in its mnestic subcomponents. Network analysis allowed us to describe otherwise less obvious differences in the risk profiles of males and females that attempted to take their own lives. Different neurocognitive and psychosocial variables and different interactions between them predict the probability of suicide attempt unique to male and female patients

The dynamic interaction between symptoms and pharmacological treatment in patients with major depressive disorder: the role of network intervention analysis

Introduction: The Major Depressive Disorder (MDD) is a mental health disorder that affects millions of people worldwide. It is characterized by persistent feelings of sadness, hopelessness, and a loss of interest in activities that were once enjoyable. MDD is a major public health concern and is the leading cause of disability, morbidity, institutionalization, and excess mortality, conferring high suicide risk. Pharmacological treatment with Selective Serotonin Reuptake Inhibitors (SSRIs) and Serotonin Noradrenaline Reuptake Inhibitors (SNRIs) is often the first choice for their efficacy and tolerability profile. However, a significant percentage of depressive individuals do not achieve remission even after an adequate trial of pharmacotherapy, a condition known as treatment-resistant depression (TRD). Methods: To better understand the complexity of clinical phenotypes in MDD we propose Network Intervention Analysis (NIA) that can help health psychology in the detection of risky behaviors, in the primary and/or secondary prevention, as well as to monitor the treatment and verify its effectiveness. The paper aims to identify the interaction and changes in network nodes and connections of 14 continuous variables with nodes identified as "Treatment" in a cohort of MDD patients recruited for their recent history of partial response to antidepressant drugs. The study analyzed the network of MDD patients at baseline and after 12 weeks of drug treatment. Results: At baseline, the network showed separate dimensions for cognitive and psychosocial-affective symptoms, with cognitive symptoms strongly affecting psychosocial functioning. The MoCA tool was identified as a potential psychometric tool for evaluating cognitive deficits and monitoring treatment response. After drug treatment, the network showed less interconnection between nodes, indicating greater stability, with antidepressants taking a central role in driving the network. Affective symptoms improved at follow-up, with the highest predictability for HDRS and BDI-II nodes being connected to the Antidepressants node. Conclusion: NIA allows us to understand not only what symptoms enhance after pharmacological treatment, but especially the role it plays within the network and with which nodes it has stronger connections

Paracrine effect of regulatory T cells promotes cardiomyocyte proliferation during pregnancy and after myocardial infarction

Cardiomyocyte proliferation stops at birth when the heart is no longer exposed to maternal blood and, likewise, to regulatory T cells (Tregs) that are expanded to promote maternal tolerance towards the fetus. Here, we report a role of Tregs in promoting cardiomyocyte proliferation. Treg-conditioned medium promotes cardiomyocyte proliferation, similar to the serum from pregnant animals. Proliferative cardiomyocytes are detected in the heart of pregnant mothers, and Treg depletion during pregnancy decreases both maternal and fetal cardiomyocyte proliferation. Treg depletion after myocardial infarction results in depressed cardiac function, massive inflammation, and scarce collagen deposition. In contrast, Treg injection reduces infarct size, preserves contractility, and increases the number of proliferating cardiomyocytes. The overexpression of six factors secreted by Tregs (Cst7, Tnfsf11, Il33, Fgl2, Matn2, and Igf2) reproduces the therapeutic effect. In conclusion, Tregs promote fetal and maternal cardiomyocyte proliferation in a paracrine manner and improve the outcome of myocardial infarction

Psychosocial assessment of families caring for a child with acute lymphoblastic leukemia, epilepsy or asthma: Psychosocial risk as network of interacting symptoms

The purpose of this study is to assess psychosocial risk across several pediatric medical conditions and test the hypothesis that different severe or chronic pediatric illnesses are characterized by disease specific enhanced psychosocial risk and that risk is driven by disease specific connectivity and interdependencies among various domains of psychosocial function using the Psychosocial Assessment Tool (PAT). In a multicenter prospective cohort study of 195 patients, aged 5-12, 90 diagnosed with acute lymphoblastic leukemia (ALL), 42 with epilepsy and 63 with asthma, parents completed the PAT2.0 or the PAT2.0 generic version. Multivariate analysis was performed with disease as factor and age as covariate. Graph theory and network analysis was employed to study the connectivity and interdependencies among subscales of the PAT while data-driven cluster analysis was used to test whether common patterns of risk exist among the various diseases. Using a network modelling approach analysis, we observed unique patterns of interconnected domains of psychosocial factors. Each pathology was characterized by different interdependencies among the most central and most connected domains. Furthermore, data-driven cluster analysis resulted in two clusters: Patients with ALL (89%) mostly belonged to cluster 1, while patients with epilepsy and asthma belonged primarily to cluster 2 (83% and 82% respectively). In sum, implementing a network approach improves our comprehension concerning the character of the problems central to the development of psychosocial difficulties. Therapy directed at problems related to the most central domain(s) constitutes the more rational one because such an approach will inevitably carry over to other domains that depend on the more central function