bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2023.08.23.554260

Machine learning identifies phenotypic profile alterations of human dopaminergic neurons exposed to bisphenols and perfluoroalkyls

Di Credico, A.·Weiss, A.·Corsini, M.·Gaggi, G.·Ghinassi, B.·Wilbertz, J. H.·Di Baldassarre, A.
View original source ↗Export metadata ↓

Abstract

Parkinsons disease (PD) is the second most common neurodegenerative disease and is characterized by the loss of midbrain dopaminergic neurons. Endocrine disruptors (EDs) are active substances that interfere with hormonal signaling. Among EDs, bisphenols (BPs) and perfluoroalkyls (PFs) are chemicals leached from plastics and other household products, and humans are unavoidably exposed to these xenobiotics. Data from animal studies suggest that ED exposure may play a role in PD, but data about the effect of BPs and PFs on human models of the nervous system are lacking. Previous studies demonstrated that machine learning (ML) applied to microscopy data can classify different cell phenotypes based on image features. In this study, the effect of BPs and PFs at different concentrations within the real-life exposure range (0.01, 0.1, 1, and 2 M) on the phenotypic profile of human stem cell-derived midbrain dopaminergic neurons (mDANs) was analyzed. Cells exposed for 72 hours to the xenobiotics were stained with neuronal markers and evaluated using high content microscopy yielding 126 different phenotypic features. Two different ML models (XGBoost and LightGBM) were trained to classify ED-treated versus control mDANs. ED-treated mDANs were identified with high accuracy (0.92). Assessment of the phenotypic feature contribution to the classification showed that EDs induced a significant increase of alpha-synuclein (Syn) and tyrosine hydroxylase (TH) staining intensity within the neurons. Moreover, microtubule-associated protein 2 (MAP2) neurite length and branching were significantly diminished in treated neurons. Our study shows that human mDANs are adversely impacted by exposure to EDs, causing their phenotype to shift and exhibit more characteristics of PD. Importantly, ML-supported high-content imaging can identify concrete but subtle subcellular phenotypic changes that can be easily overlooked by visual inspection alone and that define EDs effects in mDANs, thus enabling further pathological characterization in the future.

Source connections

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Di Credico, A., Weiss, A., Corsini, M., Gaggi, G., Ghinassi, B., Wilbertz, J. H., Di Baldassarre, A.. 2023-08-24. Machine learning identifies phenotypic profile alterations of human dopaminergic neurons exposed to bisphenols and perfluoroalkyls. https://doi.org/10.1101/2023.08.23.554260

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Distinguishing evidence accumulation from choice confidence in neural signatures of perceptual decision making

Human electrophysiology research has identified the centro-parietal positivity (CPP) as an apparent neural correlate of sensory evidence accumulation during perceptual decision-making. The CPP has also been shown to closely scale with subjective confidence. Coupled with the fact of its domain-generality and lack of choice selectivity, this observation raises the possibility that the CPP might in fact trace subjective confidence rather than cumulative evidence, two quantities that are closely correlated in most experiments. To disentangle confidence from cumulative evidence, we used predictive cues with 80% validity to manipulate prior expectations of participants during a contrast discrimination task while recording electroencephalography (EEG). At the time of decision termination, confidence is expected to reach a higher level for validly cued versus invalidly cued choices, whereas the opposite would be expected of a cumulative evidence signal due to biased decision starting points. As expected, valid cues led to faster, more accurate and more confident responses compared to invalid and neutral cues. At the neural level, cues produced systematic increases in preparation of the expected action prior to evidence onset as indexed by premotor mu/beta activity, consistent with cue-biased criterion adjustments. The pre-response CPP amplitude was significantly reduced for validly cued choices and the effect remained even when matching for confidence. Together these findings suggest that the CPP is not a direct read-out of subjective confidence, but an evidence accumulation signal that contributes to both decision formation and confidence estimation.

neuroscience↗
bioRxiv2026

A Neurocompliant Ionic Conductive Hydrogel Orchestrates Glial and Vascular Remodeling to Mitigate Traumatic Brain Injury

Developing conductive scaffolds for neural regeneration is often hindered by the cytotoxicity and mechanical mismatch inherent to conventional electronic fillers. Here, we report an ultrasoft ionically conductive hydrogel engineered by grafting choline-based bioionic liquids (BIL) onto fish gelatin (FiBGel). Systematic optimization yields brain-mimetic conductivity (0.25-0.68 S/m), elastic moduli (0.6-0.9 kPa), and physiological water content (72-81%). In 3D culture, the matrix drives spontaneous neurogenesis, achieving ~90% MAP2+ neurons with robust calcium signaling, while concurrently supporting endothelial network formation. We report the first intracerebral administration of a BIL hydrogel, demonstrating remarkable biocompatibility and immunomodulation. In a traumatic brain injury model, a single FiBGel dose halves reactive astrogliosis, enhances cortical revascularization, and limits lesion cavity expansion. Leveraging an FDA-recognized micronutrient, FiBGel offers a translatable strategy that integrates neuromechanics, conductivity, immune modulation, and vascular support within one injectable scaffold for minimally invasive treatment of brain injuries.

neuroscience↗
bioRxiv2026

Changes in anterior cingulate connectivity associated with response to antidepressant treatment for major depressive disorder

Background: Resting-state functional connectivity (rsFC) involving the anterior cingulate cortex (ACC) and the hippocampal formation has been implicated in major depressive disorder (MDD) and antidepressant response. However, it remains unclear whether connectivity changes in distinct ACC subdivisions and hippocampal formation reflect general antidepressant effects or are specifically associated with clinical improvement. Methods: Forty-one, unmedicated adults with MDD underwent functional MRI before and after 8 weeks of sertraline or bupropion treatment. Seed-based rsFC analyses examined subgenual ACC (sgACC), pregenual ACC (pgACC), dorsal ACC (dACC), and hippocampal formation connectivity. Linear mixed-effects models tested whether connectivity change was associated with treatment response, remission, and dimensional improvement in depressive symptoms. Results: Thirty individuals (73.2%) responded to treatment and 26 (63.4%) achieved remission. Overall, rsFC decreased pre- to post-treatment between (1) dACC and pgACC (but not sgACC and hippocampal formation) and (2) cortical regions primarily involving default mode and frontoparietal networks. When considering treatment response, differences in sgACC and pgACC connectivity with temporal and inferior frontal regions emerged (increased in responders vs. decreased in non-responders). Remission was similarly associated with increased sgACC connectivity with temporal and prefrontal regions, and increased sgACC connectivity with temporal cortical regions related to greater reductions in depressive symptoms. Conclusions: Antidepressant treatment was associated with distinct patterns of ACC connectivity change, with general reductions in dorsal and pregenual connectivity but increases in subgenual and pregenual connectivity associated with favorable clinical outcomes. Findings suggest that changes in sgACC/pgACC connectivity are particularly relevant to antidepressant treatment response. Keywords: Major depressive disorder; Resting-state functional connectivity; Anterior cingulate cortex; Antidepressant treatment; Treatment response; Subgenual anterior cingulate cortex.

neuroscience↗