Background Problems in learning that sights, sounds, or situations that were once associated with danger have become safe (extinction learning) may explain why some individuals suffer prolonged psychological distress following traumatic experiences. Although simple learning models have been unable to provide a convincing account of why this learning fails, it has recently been proposed that this may be explained by individual differences in beliefs about the causal structure of the environment. Methods Here, we tested two competing hypotheses as to how differences in causal inference might be related to trauma-related psychopathology, using extinction learning data collected from clinically well-characterised individuals with varying degrees of post-traumatic stress (N = 56). Model parameters describing individual differences in causal inference were related to multiple post-traumatic stress disorder (PTSD) and depression symptom dimensions via network analysis. Results Individuals with more severe PTSD were more likely to assign observations from conditioning and extinction stages to a single underlying cause. Specifically, greater re-experiencing symptom severity was associated with a lower likelihood of inferring that multiple causes were active in the environment. Conclusions We interpret these results as providing evidence of a primary deficit in discriminative learning in participants with more severe PTSD. Specifically, a tendency to attribute a greater diversity of stimulus configurations to the same underlying cause resulted in greater uncertainty about stimulus-outcome associations, impeding learning both that certain stimuli were safe, and that certain stimuli were no longer dangerous. In the future, better understanding of the role of causal inference in trauma-related psychopathology may help refine cognitive therapies for these disorders.
Research shows that negative experiences in childhood have a long-lasting impact on one's psychological outcomes and one's physiology. The voice is a crucial means of expression, and its complex physiology is believed to be reflective of emotional and mental states. Parenting practices (particularly those contributing to insecure attachment) and traumatic experiences in childhood may thus also influence vocal characteristics. Except for literature on psychogenic voice disorders, the relationship between such experiences and the 'normal' voice is generally unexplored; we propose that a potential relationship is most likely to emerge in singers, for whom the voice is a more central part of their sense of self. In this paper, we test the hypothesis that vocal characteristics relate to attachment and trauma history. Study 1: 25 singers (age 18-35) completed an attachment history questionnaire (ECR-R) and the Singing Voice Handicap Index. Voice range profile and perturbation measures were recorded and analyzed for voice quality assessment. Study 2: 26 singers (age 19-33) completed the attachment history questionnaire, the Childhood Trauma Questionnaire, and the State and Trait Anxiety Inventory. They were also administered the Test of Self-Conscious Affect to assess shame and guilt proneness. Voice range profile, perturbation, and spectrogram measures were recorded and analyzed. The results indicated that anxious attachment, shame, and emotional neglect can predict vocal acoustic measures of intensity and, to some extent, perturbation. This suggests the need to address attachment, shame, and trauma history patterns in the aspiring performer.
Problems in learning that sights, sounds, or situations that were once associated with danger have become safe (extinction learning) may explain why some individuals suffer prolonged psychological distress following traumatic experiences. Although simple associative learning models have been unable to provide a convincing account of how and why this learning fails, it has recently been proposed that this may be explained by individual differences in beliefs about the causal structure of the environment. Here, we tested two competing hypotheses as to how differences in causal inference might be related to trauma-related psychopathology, using extinction learning data collected from clinically well-characterized individuals with varying degrees of post-traumatic stress (N=56). Latent cause modelling revealed that individuals with more severe PTSD were more likely to assign observations from conditioning and extinction stages to a single underlying cause. Specifically, multivariate analysis incorporating multiple PTSD and depression symptom dimensions revealed a negative relationship between tendency to infer multiple causes were active in the environment and re-experiencing symptom severity. We interpret these results as providing evidence of a primary deficit in discriminative learning in participants with more severe PTSD re-experiencing symptoms. Specifically, in these individuals, a greater tendency to attribute all stimulus configurations to the same underlying cause resulted in greater uncertainty about stimulus-outcome associations, and impeded learning both that certain stimuli were safe, and that certain stimuli were no longer dangerous. Better understanding of the role of causal inference in trauma-related psychopathology may have relevance for the refinement of cognitive therapies for these disorders.
Background Metabolic reprogramming is a well-known marker of cancer, and it represents an early event during hepatocellular carcinoma (HCC) development. The recent approval of several molecular targeted agents has revolutionized the management of advanced HCC patients. Nevertheless, the lack of circulating biomarkers still affects patient stratification to tailored treatments. In this context, there is an urgent need for biomarkers to aid treatment choice and for novel and more effective therapeutic combinations to avoid the development of drug-resistant phenotypes. This study aims to prove the involvement of miR-494 in metabolic reprogramming of HCC, to identify novel miRNA-based therapeutic combinations and to evaluate miR-494 potential as a circulating biomarker. Methods Bioinformatics analysis identified miR-494 metabolic targets. QPCR analysis of glucose 6-phosphatase catalytic subunit (G6pc) was performed in HCC patients and preclinical models. Functional analysis and metabolic assays assessed G6pc targeting and miR-494 involvement in metabolic changes, mitochondrial dysfunction, and ROS production in HCC cells. Live-imaging analysis evaluated the effects of miR-494/G6pc axis in cell growth of HCC cells under stressful conditions. Circulating miR-494 levels were assayed in sorafenib-treated HCC patients and DEN-HCC rats. Results MiR-494 induced the metabolic shift of HCC cells toward a glycolytic phenotype through G6pc targeting and HIF-1A pathway activation. MiR-494/G6pc axis played an active role in metabolic plasticity of cancer cells, leading to glycogen and lipid droplets accumulation that favored cell survival under harsh environmental conditions. High miR-494 serum levels associated with sorafenib resistance in preclinical models and in a preliminary cohort of HCC patients. An enhanced anticancer effect was observed for treatment combinations between antagomiR-494 and sorafenib or 2-deoxy-glucose in HCC cells. Conclusions MiR-494/G6pc axis is critical for the metabolic rewiring of cancer cells and associates with poor prognosis. MiR-494 deserves attention as a candidate biomarker of likelihood of response to sorafenib to be tested in future validation studies. MiR-494 represents a promising therapeutic target for combination strategies with sorafenib or metabolic interference molecules for the treatment of HCC patients who are ineligible for immunotherapy.
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