Tumor cell-derived Timp-1 is necessary for maintaining metastasis-promoting Met-signaling via inhibition of Adam-10.

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The long-lasting protective effect of HGF in cardiomyoblasts exposed to doxorubicin requires a positive feed-forward loop mediated by ERK1,2-TIMP1-STAT3

Previous studies showed that the hepatocyte growth factor (HGF)–Met receptor axis plays long-lasting cardioprotection against doxorubicin anti-cancer therapy. Here, we explored the mechanism(s) underlying the HGF protective effect. DNA damage was monitored by histone H2AX phosphorylation and apoptosis by proteolytic cleavage of caspase 3. In doxorubicin-treated H9c2 cardiomyoblasts, the long-lasting cardioprotection is mediated by activation of the Ras/Raf/Mek/Erk (extracellular signal-regulated kinase 1,2) signaling pathway and requires Stat3 (signal transducer and activator of transcription 3) activation. The HGF protection was abrogated by the Erk1,2 inhibitor, PD98059. This translated into reduced Y705 phosphorylation and impaired nuclear translocation of Stat3, showing crosstalk between Erk1,2 and Stat3 signaling. An array of 29 cytokines, known to activate Stat3, was interrogated to identify the molecule(s) linking the two pathways. The analysis showed a selective increase in expression of the tissue inhibitor of metalloproteinases-1 (Timp1). Consistently, inhibition in cardiomyoblasts of Timp1 translation by siRNAs blunted both Stat3 activation and the cardioprotective effect of HGF. Thus, Timp1 is responsible for the generation of a feed-forward loop of Stat3 activation and helps cardiomyocytes to survive during the genotoxic stress induced by anthracyclines

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