Machine learning driven methodology for enhanced nylon microplastic detection and characterization.

In recent years, the field of microplastic (MP) research has evolved significantly; however, the lack of a standardized detection methodology has led to incomparability across studies. Addressing this gap, our current study innovates a reliable MP detection system that synergizes sample processing, machine learning, and optical photothermal infrared (O-PTIR) spectroscopy. This approach includes examining high-temperature filtration and alcohol treatment for reducing non-MP particles and utilizing a support vector machine (SVM) classifier focused on key wavenumbers that could discriminate between nylon MPs and non-nylon MPs (1077, 1541, 1635, 1711 cm-1 were selected based on the feature importance of SVM-Full wavenumber model) for enhanced MP identification. The SVM model built from key wavenumbers demonstrates a high accuracy rate of 91.33%. Results show that alcohol treatment is effective in minimizing non-MP particles, while filtration at 70 °C has limited impact. Additionally, this method was applied to assess MPs released from commercial nylon teabags, revealing an average release of 106 particles per teabag. This research integrates machine learning with O-PTIR spectroscopy, paving the way for potential standardization in MP detection methodologies and providing vital insights into their environmental and health implications.

DV21 decreases excitability of cortical pyramidal neurons and acts in epilepsy.

Epilepsy is one of the most common neurological disorders and the administration of antiepileptic drugs (AEDs) is the most common treatment. Although there are more than 15 AEDs available, a third of epilepsy patients remain refractory to available drugs, so novel effective drugs are needed. Here, we found that DV21, which is a natural triterpenoid compound extracted from plants of the Asclepiadaceae family, significantly decreased the incidence and stages of seizures in three classical drug-induced acute seizure models in C57BL/6 mice. Furthermore, we also found that the antiepileptic effect of DV21 might be partly mediated through reducing the excitability of cortical pyramidal neurons by increasing M current, which are low-threshold non-inactivating voltage-gated potassium currents. Moreover, the application of XE991, an inhibitor of M current, could block most the antiepileptic effect of DV21. Taken together, our results indicated that DV21 might be a novel leading compound for the treatment of epilepsy.

Loss of MeCP2 in cholinergic neurons causes part of RTT-like phenotypes via α7 receptor in hippocampus.

Mutations in the X-linked MECP2 gene cause Rett syndrome (RTT), an autism spectrum disorder characterized by impaired social interactions, motor abnormalities, cognitive defects and a high risk of epilepsy. Here, we showed that conditional deletion of Mecp2 in cholinergic neurons caused part of RTT-like phenotypes, which could be rescued by re-expressing Mecp2 in the basal forebrain (BF) cholinergic neurons rather than in the caudate putamen of conditional knockout (Chat-Mecp2(-/y)) mice. We found that choline acetyltransferase expression was decreased in the BF and that α7 nicotine acetylcholine receptor signaling was strongly impaired in the hippocampus of Chat-Mecp2(-/y) mice, which is sufficient to produce neuronal hyperexcitation and increase seizure susceptibility. Application of PNU282987 or nicotine in the hippocampus rescued these phenotypes in Chat-Mecp2(-/y) mice. Taken together, our findings suggest that MeCP2 is critical for normal function of cholinergic neurons and dysfunction of cholinergic neurons can contribute to numerous neuropsychiatric phenotypes.

Selectively driving cholinergic fibers optically in the thalamic reticular nucleus promotes sleep.

Cholinergic projections from the basal forebrain and brainstem are thought to play important roles in rapid eye movement (REM) sleep and arousal. Using transgenic mice in which channelrhdopsin-2 is selectively expressed in cholinergic neurons, we show that optical stimulation of cholinergic inputs to the thalamic reticular nucleus (TRN) activates local GABAergic neurons to promote sleep and protect non-rapid eye movement (NREM) sleep. It does not affect REM sleep. Instead, direct activation of cholinergic input to the TRN shortens the time to sleep onset and generates spindle oscillations that correlate with NREM sleep. It does so by evoking excitatory postsynaptic currents via α7-containing nicotinic acetylcholine receptors and inducing bursts of action potentials in local GABAergic neurons. These findings stand in sharp contrast to previous reports of cholinergic activity driving arousal. Our results provide new insight into the mechanisms controlling sleep.