44 research outputs found

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

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    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

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    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

    Brain glucose sensors play a significant role in the regulation of pancreatic glucose-stimulated insulin secretion.

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    As patients decline from health to type 2 diabetes, glucose-stimulated insulin secretion (GSIS) typically becomes impaired. Although GSIS is driven predominantly by direct sensing of a rise in blood glucose by pancreatic β-cells, there is growing evidence that hypothalamic neurons control other aspects of peripheral glucose metabolism. Here we investigated the role of the brain in the modulation of GSIS. To examine the effects of increasing or decreasing hypothalamic glucose sensing on glucose tolerance and insulin secretion, glucose or inhibitors of glucokinase, respectively, were infused into the third ventricle during intravenous glucose tolerance tests (IVGTTs). Glucose-infused rats displayed improved glucose handling, particularly within the first few minutes of the IVGTT, with a significantly lower area under the excursion curve within the first 10 min (AUC0-10). This was explained by increased insulin secretion. In contrast, infusion of the glucokinase inhibitors glucosamine or mannoheptulose worsened glucose tolerance and decreased GSIS in the first few minutes of IVGTT. Our data suggest a role for brain glucose sensors in the regulation of GSIS, particularly during the early phase. We propose that pharmacological agents targeting hypothalamic glucose-sensing pathways may represent novel therapeutic strategies for enhancing early phase insulin secretion in type 2 diabetes

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

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    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

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

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    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

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    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

    Wet-dry-wet drug screen leads to the synthesis of TS1, a novel compound reversing lung fibrosis through inhibition of myofibroblast differentiation

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    Therapies halting the progression of fibrosis are ineffective and limited. Activated myofibroblasts are emerging as important targets in the progression of fibrotic diseases. Previously, we performed a high-throughput screen on lung fibroblasts and subsequently demonstrated that the inhibition of myofibroblast activation is able to prevent lung fibrosis in bleomycin-treated mice. High-throughput screens are an ideal method of repurposing drugs, yet they contain an intrinsic limitation, which is the size of the library itself. Here, we exploited the data from our “wet” screen and used “dry” machine learning analysis to virtually screen millions of compounds, identifying novel anti-fibrotic hits which target myofibroblast differentiation, many of which were structurally related to dopamine. We synthesized and validated several compounds ex vivo (“wet”) and confirmed that both dopamine and its derivative TS1 are powerful inhibitors of myofibroblast activation. We further used RNAi-mediated knock-down and demonstrated that both molecules act through the dopamine receptor 3 and exert their anti-fibrotic effect by inhibiting the canonical transforming growth factor β pathway. Furthermore, molecular modelling confirmed the capability of TS1 to bind both human and mouse dopamine receptor 3. The anti-fibrotic effect on human cells was confirmed using primary fibroblasts from idiopathic pulmonary fibrosis patients. Finally, TS1 prevented and reversed disease progression in a murine model of lung fibrosis. Both our interdisciplinary approach and our novel compound TS1 are promising tools for understanding and combating lung fibrosis

    SARS-CoV-2 infection induces DNA damage, through CHK1 degradation and impaired 53BP1 recruitment, and cellular senescence

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    Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the RNA virus responsible for the coronavirus disease 2019 (COVID-19) pandemic. Although SARS-CoV-2 was reported to alter several cellular pathways, its impact on DNA integrity and the mechanisms involved remain unknown. Here we show that SARS-CoV-2 causes DNA damage and elicits an altered DNA damage response. Mechanistically, SARS-CoV-2 proteins ORF6 and NSP13 cause degradation of the DNA damage response kinase CHK1 through proteasome and autophagy, respectively. CHK1 loss leads to deoxynucleoside triphosphate (dNTP) shortage, causing impaired S-phase progression, DNA damage, pro-inflammatory pathways activation and cellular senescence. Supplementation of deoxynucleosides reduces that. Furthermore, SARS-CoV-2 N-protein impairs 53BP1 focal recruitment by interfering with damage-induced long non-coding RNAs, thus reducing DNA repair. Key observations are recapitulated in SARS-CoV-2-infected mice and patients with COVID-19. We propose that SARS-CoV-2, by boosting ribonucleoside triphosphate levels to promote its replication at the expense of dNTPs and by hijacking damage-induced long non-coding RNAs’ biology, threatens genome integrity and causes altered DNA damage response activation, induction of inflammation and cellular senescence

    Ablation of liver Fxr results in an increased colonic mucus barrier in mice

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    Background & Aims: The interorgan crosstalk between the liver and the intestine has been the focus of intense research. Key in this crosstalk are bile acids, which are secreted from the liver into the intestine, interact with the microbiome, and upon absorption reach back to the liver. The bile acid-activated farnesoid X receptor (Fxr) is involved in the gut-to-liver axis. However, liver-to-gut communication and the roles of bile acids and Fxr remain elusive. Herein, we aim to get a better understanding of Fxr-mediated liver-to-gut communication, particularly in colon functioning. Methods: Fxr floxed/floxed mice were crossed with cre-expressing mice to yield Fxr ablation in the intestine (Fxr-intKO), liver (Fxr-livKO), or total body (Fxr-totKO). The effects on colonic gene expression (RNA sequencing), the microbiome (16S sequencing), and mucus barrier function by ex vivo imaging were analysed. Results: Despite relatively small changes in biliary bile acid concentration and composition, more genes were differentially expressed in the colons of Fxr-livKO mice than in those of Fxr-intKO and Fxr-totKO mice (3272, 731, and 1824, respectively). The colons of Fxr-livKO showed increased expression of antimicrobial genes, Toll-like receptors, inflammasome-related genes and genes belonging to the ‘Mucin-type O-glycan biosynthesis’ pathway. Fxr-livKO mice have a microbiome profile favourable for the protective capacity of the mucus barrier. The thickness of the inner sterile mucus layer was increased and colitis symptoms reduced in Fxr-livKO mice. Conclusions: Targeting of FXR is at the forefront in the battle against metabolic diseases. We show that ablation of Fxr in the liver greatly impacts colonic gene expression and increased the colonic mucus barrier. Increasing the mucus barrier is of utmost importance to battle intestinal diseases such as inflammatory bowel disease, and we show that this might be done by antagonising FXR in the liver. Lay summary: This study shows that the communication of the liver to the intestine is crucial for intestinal health. Bile acids are key players in this liver-to-gut communication, and when Fxr, the master regulator of bile acid homoeostasis, is ablated in the liver, colonic gene expression is largely affected, and the protective capacity of the mucus barrier is increased
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