Genetically Encoded Photocatalysis Enables Spatially Restricted Optochemical Modulation of Neurons in Live Mice.

Light provides high temporal precision for neuronal modulations. Small molecules are advantageous for neuronal modulation due to their structural diversity, allowing them to suit versatile targets. However, current optochemical methods release uncaged small molecules with uniform concentrations in the irradiation area, which lack spatial specificity as counterpart optogenetic methods from genetic encoding for photosensitive proteins. Photocatalysis provides spatial specificity by generating reactive species in the proximity of photocatalysts. However, current photocatalytic methods use antibody-tagged heavy-metal photocatalysts for spatial specificity, which are unsuitable for neuronal applications. Here, we report a genetically encoded metal-free photocatalysis method for the optochemical modulation of neurons via deboronative hydroxylation. The genetically encoded photocatalysts generate doxorubicin, a mitochondrial uncoupler, and baclofen by uncaging stable organoboronate precursors. The mitochondria, nucleus, membrane, cytosol, and ER-targeted drug delivery are achieved by this method. The distinct signaling pathway dissection in a single projection is enabled by the dual optogenetic and optochemical control of synaptic transmission. The itching signaling pathway is investigated by photocatalytic uncaging under live-mice skin for the first time by visible light irradiation. The cell-type-specific release of baclofen reveals the GABABR activation on NaV1.8-expressing nociceptor terminals instead of pan peripheral sensory neurons for itch alleviation in live mice.

Gut microbiota-derived cholic acid mediates neonatal brain immaturity and white matter injury under chronic hypoxia.

Chronic hypoxia, common in neonates, disrupts gut microbiota balance, which is crucial for brain development. This study utilized cyanotic congenital heart disease (CCHD) patients and a neonatal hypoxic rat model to explore the association. Both hypoxic rats and CCHD infants exhibited brain immaturity, white matter injury (WMI), brain inflammation, and motor/learning deficits. Through 16s rRNA sequencing and metabolomic analysis, a reduction in B. thetaiotaomicron and P. distasonis was identified, leading to cholic acid accumulation. This accumulation triggered M1 microglial activation and inflammation-induced WMI. Administration of these bacteria rescued cholic acid-induced WMI in hypoxic rats. These findings suggest that gut microbiota-derived cholic acid mediates neonatal WMI and brain inflammation, contributing to brain immaturity under chronic hypoxia. Therapeutic targeting of these bacteria provides a non-invasive intervention for chronic hypoxia patients.

Sensory ASIC3 channel exacerbates psoriatic inflammation via a neurogenic pathway in female mice.

Psoriasis is an immune-mediated skin disease associated with neurogenic inflammation, but the underlying molecular mechanism remains unclear. We demonstrate here that acid-sensing ion channel 3 (ASIC3) exacerbates psoriatic inflammation through a sensory neurogenic pathway. Global or nociceptor-specific Asic3 knockout (KO) in female mice alleviates imiquimod-induced psoriatic acanthosis and type 17 inflammation to the same extent as nociceptor ablation. However, ASIC3 is dispensable for IL-23-induced psoriatic inflammation that bypasses the need for nociceptors. Mechanistically, ASIC3 activation induces the activity-dependent release of calcitonin gene-related peptide (CGRP) from sensory neurons to promote neurogenic inflammation. Botulinum neurotoxin A and CGRP antagonists prevent sensory neuron-mediated exacerbation of psoriatic inflammation to similar extents as Asic3 KO. In contrast, replenishing CGRP in the skin of Asic3 KO mice restores the inflammatory response. These findings establish sensory ASIC3 as a critical constituent in psoriatic inflammation, and a promising target for neurogenic inflammation management.

An ultra-short-acting benzodiazepine in thalamic nucleus reuniens undermines fear extinction via intermediation of hippocamposeptal circuits.

Benzodiazepines, commonly used for anxiolytics, hinder conditioned fear extinction, and the underlying circuit mechanisms are unclear. Utilizing remimazolam, an ultra-short-acting benzodiazepine, here we reveal its impact on the thalamic nucleus reuniens (RE) and interconnected hippocamposeptal circuits during fear extinction. Systemic or RE-specific administration of remimazolam impedes fear extinction by reducing RE activation through A type GABA receptors. Remimazolam enhances long-range GABAergic inhibition from lateral septum (LS) to RE, underlying the compromised fear extinction. RE projects to ventral hippocampus (vHPC), which in turn sends projections characterized by feed-forward inhibition to the GABAergic neurons of the LS. This is coupled with long-range GABAergic projections from the LS to RE, collectively constituting an overall positive feedback circuit construct that promotes fear extinction. RE-specific remimazolam negates the facilitation of fear extinction by disrupting this circuit. Thus, remimazolam in RE disrupts fear extinction caused by hippocamposeptal intermediation, offering mechanistic insights for the dilemma of combining anxiolytics with extinction-based exposure therapy.

SH2B1 Tunes Hippocampal ERK Signaling to Influence Fluid Intelligence in Humans and Mice.

Fluid intelligence is a cognitive domain that encompasses general reasoning, pattern recognition, and problem-solving abilities independent of task-specific experience. Understanding its genetic and neural underpinnings is critical yet challenging for predicting human development, lifelong health, and well-being. One approach to address this challenge is to map the network of correlations between intelligence and other constructs. In the current study, we performed a genome-wide association study using fluid intelligence quotient scores from the UK Biobank to explore the genetic architecture of the associations between obesity risk and fluid intelligence. Our results revealed novel common genetic loci (SH2B1, TUFM, ATP2A1, and FOXO3) underlying the association between fluid intelligence and body metabolism. Surprisingly, we demonstrated that SH2B1 variation influenced fluid intelligence independently of its effects on metabolism but partially mediated its association with bilateral hippocampal volume. Consistently, selective genetic ablation of Sh2b1 in the mouse hippocampus, particularly in inhibitory neurons, but not in excitatory neurons, significantly impaired working memory, short-term novel object recognition memory, and behavioral flexibility, but not spatial learning and memory, mirroring the human intellectual performance. Single-cell genetic profiling of Sh2B1-regulated molecular pathways revealed that Sh2b1 deletion resulted in aberrantly enhanced extracellular signal-regulated kinase (ERK) signaling, whereas pharmacological inhibition of ERK signaling reversed the associated behavioral impairment. Our cross-species study thus provides unprecedented insight into the role of SH2B1 in fluid intelligence and has implications for understanding the genetic and neural underpinnings of lifelong mental health and well-being.

The applied principles of EEG analysis methods in neuroscience and clinical neurology.

Electroencephalography (EEG) is a non-invasive measurement method for brain activity. Due to its safety, high resolution, and hypersensitivity to dynamic changes in brain neural signals, EEG has aroused much interest in scientific research and medical fields. This article reviews the types of EEG signals, multiple EEG signal analysis methods, and the application of relevant methods in the neuroscience field and for diagnosing neurological diseases. First, three types of EEG signals, including time-invariant EEG, accurate event-related EEG, and random event-related EEG, are introduced. Second, five main directions for the methods of EEG analysis, including power spectrum analysis, time-frequency analysis, connectivity analysis, source localization methods, and machine learning methods, are described in the main section, along with different sub-methods and effect evaluations for solving the same problem. Finally, the application scenarios of different EEG analysis methods are emphasized, and the advantages and disadvantages of similar methods are distinguished. This article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives, provide references for subsequent research, and summarize current issues and prospects for the future.