Background. The extent to which prenatal low-level mercury (Hg) exposure through maternal fish intake and heavy metals exposure affect children neurodevelopment is controversial and may appear in long term. In 2007 a prospective cohort, the Northern Adriatic Cohort II (NAC-II), was established to investigate the association between prenatal Hg exposure from maternal fish consumption and child neurodevelopment. 900 pregnant women were enrolled. 632 and 470 children underwent neurodevelopmental evaluation, respectively, at 18 and 40 months of age. The NAC-II cohort is a part of the Mediterranean cohort in “Public health impact of long-term, low-level, mixed element exposure in susceptible population strata” project.Methods. This protocol describes the follow-up assessment of the effects of prenatal low level Hg and other heavy metals exposure on the developing nervous system of the children born within the NAC-II and reached the age of 7 years. Child diet components are estimated through a Diet Diary. Child hair and urine are collected for determination of Hg level. In addition, levels of other potentially neurotoxic metals, namely Manganese, Cadmium, Lead, Arsenic and Selenium are also measured in the same matrices.DiscussionThis protocol extends to the first years of schooling age the evaluation of the neurotoxicant effect of Mercury and of the other heavy metals on children’s neurodevelopment, adjusting for the potential confounders such as the lifestyles and the social economic status of children’s families. Longitudinal analysis of neurodevelopment, assessed in different ages (18, 40 months and 7 years), are performed.

Human biomonitoring (HBM) is a rapidly developing field that is emphasized as an important approach for the assessment of health risks. However, its value for health risk assessment (HRA) remains to be clarified. We performed a review of publications concerned with applications of HBM in the assessment of health risks. The selection of publications for this review was limited by the search engines used (only PubMed and Scopus) and a timeframe of the last five years. The review focused on the clarity of 10 HRA elements, which influence the quality of HRA. We show that the usage of HBM data in HRA is limited and unclear. Primarily, the key HRA elements are not consistently applied or followed when using HBM in such assessments, and secondly, there are inconsistencies regarding the understanding of fundamental risk analysis principles and good practices in risk analysis. Our recommendations are as follows: (i) potential usage of HBM data in HRA should not be non-critically overestimated but rather limited and aligned to a specific value for exposure assessment or for the interpretation of health damage; (ii) improvements to HRA approaches, using HBM information or not, are needed and should strictly follow theoretical foundations of risk analysis.

Substance use disorder (SUD) is a chronic neuropsychiatric condition characterized by persistent drug seeking and impaired behavioral control. Dopaminergic signaling has long been recognized as a central regulator of reinforcement learning, motivation, and habit formation. Addictive substances profoundly alter dopamine transmission through multiple mechanisms. These drug-induced changes contribute to the initiation, escalation, and persistence of addictive behaviors. In addition to dopamine, the cholinergic system has emerged as an important modulator of striatal circuit function. Acetylcholine and its receptors interact extensively with dopaminergic pathways, shaping striatal signaling dynamics and influencing learning and action selection, with particularly strong relevance for nicotine dependence. In this review, we discuss how striatal dopamine and acetylcholine contribute to learning, habit formation, and addiction-related behaviors, as well as how these systems interact at the circuit level. By integrating these findings, we propose a framework for understanding how dopamine–acetylcholine interactions may influence behavioral regulation relevant to substance use disorders.

Background The Newcomb-Benford Law (NBL) describes the distribution frequency of the first significant digit in large data sets and suggests that the probability for the significant digits is not uniform. To date, it is used as an evaluation tool to identify fraudulent or manipulated data across many fields, although this practice may be flawed. Uninformed applications may lead to inappropriate labelling of data as falsified when, in actuality, underlying mechanisms may drive accordance to the distribution. Objectives To investigate the properties of the NBL in the natural sciences, we applied the concept to five toxicological datasets to investigate how it can be applied in biological systems and if intrinsic characteristics of the data may drive accordance or violation. We hypothesize that physiologically advantageous (essential and beneficial) elements will result in a violation of the NBL due to active and preferential uptake. Methods Observational and experimental studies, different age groups, and biosample types (blood, urine, hair, bone) were assessed, with each measuring a range of essential, beneficial, and non-essential elements. Eight statistical tests were trialled, including the often-used Pearson’s Chi-squared. The Judge-Schecter Mean Deviation test was determined to be the most appropriate statistical test and was applied to each elemental grouping (Essential, Beneficial, Non-Essential) and a combination of all. Results Results indicate that physiological mechanisms, like preferential elemental uptake, lead to violations with distinctive patterns that also depend on the anatomic function of the biosample. Discussion Visual analysis based on the NB distribution could be useful in distinguishing the difference between violations resulting from data tampering versus those resulting from innate physiological mechanisms. Overall, the use of the NBL for detecting data manipulation in exposure studies necessitates reevaluation, urging a deeper understanding of the intrinsic nature of the data.

Background/Objectives: Dopamine is well known for its role in reward learning, where phasic activity encodes prediction errors and supports the formation of cue–outcome associations. More recently, dopamine has been implicated in encoding salience, novelty, and aversive events, suggesting a broader function in shaping learning and memory across motivational contexts. However, how accumbal dopamine contributes to the recovery of extinguished fear, a process central to relapse in anxiety and trauma-related disorders, remains unclear. Methods: Here, we examined NAc core dopamine dynamics during shock-induced reinstatement of an extinguished fear memory. Using dLight fiber photometry, we found that a sustained decrease in baseline dopamine marked extinction recall. In contrast, an unexpected reminder footshock prevented this reduction, maintaining dopamine levels near baseline as freezing behavior re-emerged. Results: The reminder shock also evoked a transient dopamine peak, and optogenetic manipulations demonstrated that dopamine signaling during this period bidirectionally modulated reinstatement, with enhancement of dopamine release increasing reinstatement and inhibition of dopamine terminals markedly attenuating it. Together, these results demonstrate that unexpected aversive events reset NAc core dopamine levels and gate the return of extinguished fear. Conclusions: By revealing that accumbal dopamine contributes to fear recovery, this work broadens current models of dopamine function and identifies a neural mechanism through which surprising events may promote relapse of aversive memories in anxiety- and stress-related disorders.