Under stressful conditions, the hypothalamic-pituitary-adrenal (HPA) axis acts to promote transitory physiological adaptations that are often resolved after the stressful stimulus is no longer present. In addition to corticosteroids (e.g., cortisol), the neurosteroid allopregnanolone (3α,5α-tetrahydroprogesterone, 3α-hydroxy-5α-pregnan-20-one) participates in negative feedback mechanisms that restore homeostasis. Chronic, repeated exposure to stress impairs the responsivity of the HPA axis and dampens allopregnanolone levels, participating in the etiopathology of psychiatric disorders, such as major depressive disorder (MDD) and post-traumatic stress disorder (PTSD). MDD and PTSD patients present abnormalities in the HPA axis regulation, such as altered cortisol levels or failure to suppress cortisol release in the dexamethasone suppression test. Herein, we review the neurophysiological role of allopregnanolone both as a potent and positive GABAergic neuromodulator but also in its capacity of inhibiting the HPA axis. The allopregnanolone function in the mechanisms that recapitulate stress-induced pathophysiology, including MDD and PTSD, and its potential as both a treatment target and as a biomarker for these disorders is discussed.

Even though major depressive disorder (MDD) and post-traumatic stress disorder (PTSD) are among the most prevalent and incapacitating mental illnesses in the world, their diagnosis still relies solely on the characterization of subjective symptoms (many of which are shared by multiple disorders) self-reported by patients. Thus, the need for objective measures that aid in the detection of and differentiation between psychiatric disorders becomes urgent. In this paper, we explore the potential of neurosteroids and neurotrophic proteins as biomarkers for MDD and PTSD. Circulating levels of the GABAergic neuroactive steroid, allopregnanolone, are diminished in MDD and PTSD patients, which corroborates the finding of depleted neurosteroid levels observed in animal models of these disorders. The neurotrophic protein, brain-derived neurotropic factor (BDNF), is also reduced in the periphery and in the brain of MDD patients and depressed-like animals that express lower neurosteroid levels. Although the role of BDNF in PTSD psychopathology seems less clear and merits more research, we propose a causal link between allopregnanolone levels and BDNF expression that could function as a biomarker axis for the diagnosis of both MDD and PTSD.

Allopregnanolone (3α,5α-tetrahydroprogesterone; pharmaceutical formulation: brexanolone) is a neurosteroid that has recently been approved for the treatment of postpartum depression, promising to fill part of a long-lasting gap in the effectiveness of pharmacotherapies for depressive disorders. In this review, we explore the experimental research that characterized the antidepressant-like effects of allopregnanolone, with a particular focus on the neurotrophic adaptations induced by this neurosteroid in preclinical studies. We demonstrate that there is a consistent decrease in allopregnanolone levels in limbic brain areas in rodents submitted to stress-induced models of depression, such as social isolation and chronic unpredictable stress. Further, both the drug-induced upregulation of allopregnanolone or its direct administration reduce depressive-like behaviors in models such as the forced swim test. The main drugs of interest that upregulate allopregnanolone levels are selective serotonin reuptake inhibitors (SSRIs), which present the neurosteroidogenic property even in lower, non-SSRI doses. Finally, we explore how these antidepressant-like behaviors are related to neurogenesis, particularly in the hippocampus. The protagonist in this mechanism is likely the brain-derived neurotrophic factor (BFNF), which is decreased in animal models of depression and may be restored by the normalization of allopregnanolone levels. The role of an interaction between GABA and the neurotrophic mechanisms needs to be further investigated.

Background: This study aims to identify the association between parenting styles and behavioral changes among adolescents regarding the consumption of alcohol, tobacco, cannabis, cocaine/crack. Methods: A group of ninety-nine adolescents (39 girls and 60 boys), aged 14 to 19 years (17.05 ± 1.51), who called in to a call center that provides counseling to substance users, was followed-up for 30 days. Data collection occurred between March 2009 and October 2015. The adolescents answered questions regarding parental responsiveness and demanding nature on a scale to assess parental styles and provided sociodemographic data, substance abuse consumption characteristics, and the Contemplation Ladder scale score. Results: The parental styles most reported by the adolescents were authoritative (30%) and indulgent (28%). Children who perceived their mothers as having an indulgent style and who had absent fathers presented more difficulties in making behavioral changes to avoid alcohol and cocaine/crack consumption. Conclusion: The study found that parent-child relationships were associated with a lack of change in the adolescent regarding substance use behavior, particularly the consumption of alcohol and cocaine/crack.

Toluene is the main substance contained in products used as inhalants. The frequent abuse of toluene-based inhalants requires the definition of a simple laboratory parameter that allows acute exposure assessment. This study aimed at defining urinary hippuric acid (UHA) levels related to intentional exposure to toluene, and to correlate them to blood toluene concentration (BT). Methods. BT and UHA levels were measured in 65 homeless adolescents of Porto Alegre, Brazil. Results. Toluene was detected in 91.9% of the investigated population, who presented BT levels from 0.5 to 83.7 μg/mL. There was good correlation between UHA and BT concentrations (r = 0.78), and in homeless adolescents, UHA levels higher than 3.0 g/g creatinine indicate intentional exposure to toluene. Conclusions. The determination of UHA concentrations can be used as a screening method for the detection of intentional exposure to toluene, but its diagnosis must include BT toluene dosage, as well as circumstantial and clinical evidence.

Undergraduate students are often impacted by depression, anxiety, and stress. In this context, machine learning may support mental health assessment. Based on the following research question: “How do machine learning models perform in the detection of depression, anxiety, and stress among undergraduate students?”, we aimed to evaluate the performance of these models. PubMed, Embase, PsycINFO, and Web of Science databases were searched, aiming at studies meeting the following criteria: publication in English; targeting undergraduate university students; empirical studies; having been published in a scientific journal; and predicting anxiety, depression, or stress outcomes via machine learning. The certainty of evidence was analyzed using the GRADE. As of January 2024, 2,304 articles were found, and 48 studies met the inclusion criteria. Different types of data were identified, including behavioral, physiological, internet usage, neurocerebral, blood markers, mixed data, as well as demographic and mobility data. Among the 33 studies that provided accuracy assessment, 30 reported values that exceeded 70%. Accuracy in detecting stress ranged from 63% to 100%, anxiety from 53.69% to 97.9%, and depression from 73.5% to 99.1%. Although most models present adequate performance, it should be noted that 47 of them only performed internal validation, which may overstate the performance data. Moreover, the GRADE checklist suggested that the quality of the evidence was very low. These findings indicate that machine learning algorithms hold promise in Public Health; however, it is crucial to scrutinize their practical applicability. Further studies should invest mainly in external validation of the machine learning models.