Local Signals Research Articles

Protein kinase A and local signaling in cancer.

Protein kinase A (PKA) is a basophilic kinase implicated in the modulation of many cell-signaling and physiological processes. PKA also contributes to cancer-relevant events such as growth factor action, cell cycle control, cell migration and tumor metabolism. Germline and somatic mutations in PKA, gene amplifications, and chromosome rearrangements that encode kinase fusions, are linked to a growing number of malignant neoplasms. Mislocalization of PKA by exclusion from A-Kinase Anchoring Protein (AKAP) signaling islands further underlies cancer progression. This article highlights the influence of AKAP signaling and local kinase action in selected hallmarks of cancer. We also feature the utility of kinase inhibitor drugs as frontline and future anti-cancer therapies.

Abstract C021: Tumor-associated microbiota suppresses anti-tumor immunity by driving cDC1 dysfunction in lung cancer

Abstract Type 1 conventional dendritic cells (cDC1s) are critical for initiating and sustaining tumor-reactive CD8 T cells; lack of functional cDC1s is a key driver for failed tumor immunosurveillance and immunotherapy. However, what factors cause the cDC1 insufficiency in the tumor microenvironment (TME) remain poorly understood. Commensal microbiota has emerged as a key regulator of TME and the efficacy of cancer immunotherapies. Nonetheless, most studies have focused on the intestinal microbiome; it remains underexplored whether and how the local microbiota within tumors influences the anti-cancer immunity. Using the autochthonous Kras LSL-G12D/+ ; p53 flox/flox (KP) mouse model of lung cancer, we found an increased local bacterial burden and altered bacterial composition associated with lung tumors. Importantly, this local microbiota suppresses the anti-tumor CD8 T cell response both at baseline and in response to ICB therapies. Specifically, single-cell RNA-seq analysis revealed that the microbiota shapes the functional subsets of tumor-reactive CD8 T cells. Bacterial depletion promotes the accumulation of stem-like Tpex cells (precursor of exhausted T cells) in the TME, which serve as a reservoir of effector CD8 T cells and mediate an effective response upon ICB treatment. To distinguish the function of the local microbiota within TME from the distal gut microbiota, we developed a new method of aerosolized antibiotic treatment, which selectively ablates the intra-tumoral lung microbiota while preserving the intact gut microbiota. Using this approach, we demonstrated that removal of the intra-tumoral lung microbiota markedly improves the tumor-reactive T cell response and sensitizing “cold” lung tumors to ICB therapies. Mechanistically, we identified cDC1s as a central player in microbiota-mediated suppression of anti-tumor immunity. Local microbiota diminishes cDC1 quality and quantity in the lung TME, resulting in impaired T cell priming and Tpex maintenance. At the molecular level, our data revealed that bacterial products derived from the local microbiota induce type I interferon expression in tumor-associated myeloid cells and enhance GM-CSF production from cancer cells: chronic type I interferon and GM-CSF signaling acts cooperatively to reduce the functional cDC1 population. Combining in vitro cDC1 assays, competitive bone marrow chimera experiments and cDC1-specific knockout models, we establish the causal relationships between the local microbiota, IFN-I and GM-CSF signaling in cDC1s, and the tumor response to ICB. Altogether, our study uncovered a dominant role of tumor-associated microbiota in inhibiting cDC1s and suppressing anti-tumor immunity through type I IFN and GM-CSF dependent pathways in lung cancer. Our findings not only identify the intra-tumoral microbiota as a critical therapeutic target for lung cancer treatment, but also provide new insights into the tissue-specific, context-dependent regulatory mechanisms of cDC1s in the TME. Citation Format: Qiang Dong, Chengcheng Jin. Tumor-associated microbiota suppresses anti-tumor immunity by driving cDC1 dysfunction in lung cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr C021.

Key roles of two-component systems in intestinal signal sensing and virulence regulation in enterohemorrhagic Escherichia coli.

Enterohemorrhagic Escherichia coli (EHEC) is a foodborne pathogen that infects humans by colonizing the large intestine. Upon reaching the large intestine, EHEC mediates local signal recognition and the transcriptional regulation of virulence genes to promote adherence and colonization in a highly site-specific manner. Two-component systems (TCSs) represent an important strategy used by EHEC to couple external stimuli with the regulation of gene expression, thereby allowing EHEC to rapidly adapt to changing environmental conditions. An increasing number of studies published in recent years have shown that EHEC senses a variety of host- and microbiota-derived signals present in the human intestinal tract and coordinates the expression of virulence genes via multiple TCS-mediated signal transduction pathways to initiate the disease-causing process. Here, we summarize how EHEC detects a wide range of intestinal signals and precisely regulates virulence gene expression through multiple signal transduction pathways during the initial stages of infection, with a particular emphasis on the key roles of TCSs. This review provides valuable insights into the importance of TCSs in EHEC pathogenesis, which have relevant implications for the development of antibacterial therapies against EHEC infection.

AKAP1/PKA-mediated GRP75 phosphorylation at mitochondria-associated endoplasmic reticulum membranes protects cancer cells against ferroptosis.

Emerging evidence suggests that signaling pathways can be spatially regulated to ensure rapid and efficient responses to dynamically changing local cues. Ferroptosis is a recently defined form of lipid peroxidation-driven cell death. Although the molecular mechanisms underlying ferroptosis are emerging, spatial aspects of its signaling remain largely unexplored. By analyzing a public database, we found that a mitochondrial chaperone protein, glucose-regulated protein 75 (GRP75), may have a previously undefined role in regulating ferroptosis. This was subsequently validated. Interestingly, under ferroptotic conditions, GRP75 translocated from mitochondria to mitochondria-associated endoplasmic reticulum (ER) membranes (MAMs) and the cytosol. Further mechanistic studies revealed a highly spatial regulation of GRP75-mediated antiferroptotic signaling. Under ferroptotic conditions, lipid peroxidation predominantly accumulated at the ER, which activated protein kinase A (PKA) in a cAMP-dependent manner. In particular, a signaling microdomain, the outer mitochondrial membrane protein A-kinase anchor protein 1 (AKAP1)-anchored PKA, phosphorylated GRP75 at S148 in MAMs. This caused GRP75 to be sequestered outside the mitochondria, where it competed with Nrf2 for Keap1 binding through a conserved high-affinity RGD-binding motif, ETGE. Nrf2 was then stabilized and activated, leading to the transcriptional activation of a panel of antiferroptotic genes. Blockade of the PKA/GRP75 axis dramatically increased the responses of cancer cells to ferroptosis both in vivo and in vitro. Our identification a localized signaling cascade involved in protecting cancer cells from ferroptosis broadens our understanding of cellular defense mechanisms against ferroptosis and also provides a new target axis (AKAP1/PKA/GRP75) to improve the responses of cancer cells to ferroptosis.

Causal inference predicts the transition from integration to segmentation in motion perception.

Motion provides a powerful sensory cue for segmenting a visual scene into objects and inferring the causal relationships between objects. Fundamental mechanisms involved in this process are the integration and segmentation of local motion signals. However, the computations that govern whether local motion signals are perceptually integrated or segmented remain unclear. Hierarchical Bayesian causal inference has recently been proposed as a model for these computations, yet a hallmark prediction of the model - its dependency on sensory uncertainty - has remained untested. We used a recently developed hierarchical stimulus configuration to measure how human subjects integrate or segment local motion signals while manipulating motion coherence to control sensory uncertainty. We found that (a) the perceptual transition from motion integration to segmentation shifts with sensory uncertainty, and (b) that perceptual variability is maximal around this transition point. Both findings were predicted by the model and challenge conventional interpretations of motion repulsion effects.

In situ mixer calibration for superconducting quantum circuits

Mixers play a crucial role in superconducting quantum computing, primarily by facilitating frequency conversion of signals to enable precise control and readout of quantum states. However, imperfections, particularly local oscillator leakage and unwanted sideband signal, can significantly compromise control fidelity. To mitigate these defects, regular and precise mixer calibrations are indispensable, yet they pose a formidable challenge in large-scale quantum control. Here, we introduce an in situ and scalable mixer calibration scheme using superconducting qubits. Our method leverages the qubit's response to imperfect signals, allowing for calibration without modifying the wiring configuration. We experimentally validate the efficacy of this technique by benchmarking single-qubit gate error and qubit coherence time.

Plants Under Stress: Exploring Physiological and Molecular Responses to Nitrogen and Phosphorus Deficiency

Nitrogen (N) and phosphorus (P) are essential mineral macronutrients critical for plant structure and function. Both contribute to processes ranging from cellular integrity to signal transduction. Since plants require these nutrients in high concentrations, replenishing them in soil often involves chemical fertilizers. However, the main source of P, rock phosphate, is non-renewable and in decline. N, second only to carbon, oxygen, and hydrogen in plant requirements, is vital for synthesizing proteins, nucleic acids, and plant pigments. Although N is available to plants through biological fixation or fertilizer application, the frequent application of N is not a sustainable solution due to environmental concerns like groundwater contamination and eutrophication. Plants have developed sophisticated mechanisms to adapt to nutrient deficiencies, such as changes in root architecture, local signaling, and long-distance signaling through the phloem. A dual deficiency of N and P is common in the field. In addition to individual N and P deficiency responses, this review also highlights some of the most recent discoveries in the responses of plants to the combined N and P deficiencies. Understanding the molecular and physiological responses in plants to mineral deficiency will help implement strategies to produce plants with high mineral use efficiency, leading to the reduced application of fertilizers, decreased mineral runoff, and improved environment.

Influence of LO cable movements on VNA measurements using Frequency Extensions

Abstract. In this study, the impact of local oscillator cable movements or drift during VNA measurements using frequency extenders is investigated. A non-reciprocal measurement error caused by alterations of the local oscillator signal in R 900 (WR 10) waveguide measurements from 75 to 110 GHz is observed and systematically analyzed. Furthermore, the theory behind this effect and its implications on measurement results are discussed, as well as possible corrections for both calibrated and raw measurement data.

Detecting biological motion signals in human and monkey superior colliculus: a subcortical-cortical pathway for biological motion perception.

Most vertebrates, including humans, are highly adept at detecting and encoding biological motion, even when it is portrayed by just a few point lights attached to the head and major joints. However, the function of subcortical regions in biological motion perception has been scarcely explored. Here, we investigate the role of the superior colliculus in local biological motion processing. Using high-field (3 T) and ultra-high-field (7 T) functional magnetic resonance imaging, we record the neural responses of the superior colliculus to scrambled point-light walkers (with local kinematics retained) in both humans and male macaque monkeys. Results show that the superior colliculus, especially the superficial layers, selectively responds to local biological motion. Furthermore, dynamic causal modeling analysis reveals a subcortical-cortical functional pathway that transmits local biological motion signals from the superior colliculus via the middle temporal visual complex to the posterior superior temporal sulcus in the human brain. These findings suggest the existence of a cross-species mechanism in the superior colliculus that facilitates the detection of local biological motion at the early stage of the visual processing stream.

Putting faults in the northern Chilean subduction margin into motion: evidence for remote dynamic earthquake triggering on the plate interface and within the forearc

Dynamic stresses on the order of ~1 kPa from passing waves of mainshock earthquakes can trigger aftershocks at remote distances. Here, we investigate the prevalence of remote earthquake triggering in northern Chile, where aseismic-slip triggering has been documented. Our twofold approach to quantify triggerability includes a statistical difference-of-means test to quantify seismicity-rate changes bracketing candidate mainshock times, and a waveform-based approach to look for triggered earthquakes missing from the local catalog. We find no persistent, statistically-significant seismicity-rate increases associated with any of the candidate mainshocks when considering the local catalog in aggregate. However, catalog statistics reveal evidence for localized triggering both on the subduction interface and within the shallower forearc faults. Waveforms reveal local, uncataloged earthquakes only visible using a high-pass filter that removes the mainshock signal that otherwise overprints the local signals. Based on Japan mainshocks, we cannot rule out antipodal triggering. Areas showing higher triggerability are consistent with regions of low locking inferred from GNSS models and regions of observed aseismic slip. The spatial coincidence of triggering and low-locking, combined with the absence of a stress-triggering threshold, requires non-linear triggering mechanisms, such as altered frictional strength or aseismic-slip triggering, to be consistent with the observations.

Insulin Resistance Is a Modifying Factor for Parkinson's Disease.

Parkinson's disease (PD) is the second most common, and the fastest-growing neurodegenerative disorder with unclear etiology in most cases. Therefore, the identification of non-genetic risk factors for PD pathology is crucial to develop effective preventative or therapeutic strategies. An increasing number of evidence suggests that central insulin resistance might have an essential role in PD pathology. Nevertheless, it is not clear whether insulin resistance arises from external factors/lifestyle, comorbidities such as type 2 diabetes or it can occur in a PD patient's brain independently from peripheral insulin resistance. We aimed to investigate insulin resistance and its role in GBA1mutation-associated PD pathogenesis and phenotype severity. Midbrain organoids, generated from induced pluripotent stem cells (iPSCs) of PD patients carrying the GBA1-N370S heterozygous mutation (GBA-PD) and healthy donors, were exposed to different insulin concentrations to modify insulin signaling function. Transcriptomics analysis was performed to explore insulin signaling gene expression patterns in GBA-PD and to find a potential target for GBA-PD-associated phenotype rescue. The insulin signaling pathway genes show dysregulation in GBA-PD. Particularly, we highlight that a knockdown of FOXO1 mitigates the loss of dopaminergic neurons and cellular death in GBA-PD. Additionally, our findings suggest a promising therapeutic potential of the anti-diabetic drug Pioglitazone in decreasing dopaminergic neuron loss associated with GBA-PD. Local insulin signaling dysfunction plays a substantial role in GBA-PD pathogenesis, exacerbating dopaminergic neuron death. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Local signal detection on irregular domains with generalized varying coefficient models

In spatial analysis, it is essential to understand and quantify spatial or temporal heterogeneity. This paper focuses on the generalized spatially varying coefficient model (GSVCM), a powerful framework to accommodate spatial heterogeneity by allowing regression coefficients to vary in a given spatial domain. We propose a penalized bivariate spline method for detecting local signals in GSVCM. The key idea is to use bivariate splines defined on triangulation to approximate nonparametric varying coefficient functions and impose a local penalty on L 2 norms of spline coefficients for each triangle to identify null regions of zero effects. Moreover, we develop model confidence regions as the inference tool to quantify the uncertainty of the estimated null regions. Our method partitions the region of interest using triangulation and efficiently approximates irregular domains. In addition, we propose an efficient algorithm to obtain the proposed estimator using the local quadratic approximation. We also establish the consistency of estimated nonparametric coefficient functions and the estimated null regions. The numerical performance of the proposed method is evaluated in both simulation cases and real data analysis.

Distance similarity entropy: a sensitive nonlinear feature extraction method for rolling bearing fault diagnosis

Entropy-based methods are widely used in machinery fault diagnosis for characterizing system disorder and complexity. However, conventional entropy techniques often fail to capture local signal variations when analyzing relationships between vectors, especially in complex settings. This leads to incomplete representations of subtle features and dynamic behaviors, resulting in inaccurate estimations of system complexity and affecting diagnostic accuracy and reliability. To address these limitations, a novel distance similarity entropy (DSEn) is proposed in this paper: (1) It leverages element-wise distances to precisely capture local shifts and subtle distortions between subsequences. (2) It employs a Gaussian kernel function for vector similarity, enhancing signal pattern analysis by preserving subtle differences and mitigating the impact of outliers. (3) It uses probability density estimation of distance similarities between adjacent vectors to track changes in internal signal patterns, enabling more accurate and sensitive estimations of signal complexity. Synthetic signal experiments demonstrate that DSEn excels in detecting dynamic time series changes and characterizing signal complexity. Tests on two bearing datasets reveal that DSEn's extracted features show significant differences, highlighted by Hedges’ g effect size. Compared to other commonly used entropies (SampEn, PermEn, FuzzEn, DistEn, etc.), DSEn shows superior fault identification accuracy, computational efficiency, and noise resistance.

Evidence of Browning and Inflammation Features in Visceral Adipose Tissue of Women with Endometriosis

Patients with endometriosis tend to have a low body mass index, suggesting an inverse relationship between body fat and risk of disease. This is supported by evidence that miRNAs differentially expressed in endometriosis induce browning of pre-adipocytes in vitro. Thus, we hypothesize that endometriosis may underlie adipose tissue (AT) dysfunction and browning. Identify inflammation and browning processes in AT collected from endometriosis patients. Visceral and subcutaneous AT samples were obtained during endometriosis (n = 32) or uterine myoma (n = 14; controls) surgery. Blood catecholamines were determined by high-performance liquid chromatography while IL-6 and TGF-β levels were quantified by ELISA. Adipocyte cross-sectional areas were analyzed in H&E-stained sections by computer-assisted morphometry. Macrophages (F4/80; Galectin-3) and browning activation (UCP-1; PGC-1α) in tissues were identified by dual label immunofluorescence. Expression of inflammatory (IL-6; MCP-1; Galectin-3; CD206; TIMP1; TGF-β) and browning-related (UCP-1; PGC-1α; DIO2; CITED1; CIDEA; TMEM26; TBX1; PRDM16; PPAR-γ) molecules in AT were assessed by RT-PCR and Western blotting. Compared to controls, patients presented smaller adipocytes, especially in VAT, and lower norepinephrine levels. Serum IL-6, but not TGF-β, was increased in patients. UCP-1, PGC-1α, IL-6, and MCP-1 were upregulated in VAT from endometriosis women, which also evidenced a reduction of CD206, relative to controls. However, no differences were found in mRNA expression of IL-6, TIMP1, and TGF-β nor Galectin-3 protein levels. In SAT, protein expression remained unchanged between patients and controls. Our findings support an endometriosis' role as a pro-catabolic state along with local signals of VAT browning and inflammation.

Postsynaptic BMP signaling regulates myonuclear properties in Drosophila larval muscles.

The syncytial mammalian muscle fiber contains a heterogeneous population of (myo)nuclei. At the neuromuscular junction (NMJ), myonuclei have specialized positioning and gene expression. However, it remains unclear how myonuclei are recruited and what regulates myonuclear output at the NMJ. Here, we identify specific properties of myonuclei located near the Drosophila larval NMJ. These synaptic myonuclei have increased size in relation to their surrounding cytoplasmic domain (size scaling), increased DNA content (ploidy), and increased levels of transcription factor pMad, a readout for BMP signaling activity. Our genetic manipulations show that local BMP signaling affects muscle size, nuclear size, ploidy, and NMJ size and function. In support, RNA sequencing analysis reveals that pMad regulates genes involved in muscle growth, ploidy (i.e., E2f1), and neurotransmission. Our data suggest that muscle BMP signaling instructs synaptic myonuclear output that positively shapes the NMJ synapse. This study deepens our understanding of how myonuclear heterogeneity supports local signaling demands to fine tune cellular function and NMJ activity.

Enhancing drug-target interaction predictions in context of neurodegenerative diseases using bidirectional long short-term memory in male Swiss albino mice pharmaco-EEG analysis

Background and ObjectiveEmerging diseases like Parkinson or Alzheimer's, which are not curable, endanger human mental health and are challenging to research. Drug target interactions (DTI) are pivotal in the screening of candidate drugs and focus on a small pool of drug targets. Electroencephalogram shows the responses to psychotropic medicines in the brain bioelectric activity. Synaptic activity can be analyzed by using Local Field Potential recordings obtained from micro-electrodes implanted in the brain. The aim is to evaluate the effects of drug on brain bioelectric activity and increase the drug classification accuracy. The ultimate goal is to advance our understanding of how drugs affect synaptic activity and open the door to more focused treatment for neurodegenerative diseases. MethodsIn this study, Pharmaco-EEG recordings are processed using Advanced neural network models, particularly Convolutional Neural Networks, to assess the effects of medications. The five different medicines used in this study are Ephedrine, Fluoxetine, Kratom, Morphine, and Saline. The signals observed are local field potential signals. To overcome some limits of DTI prediction, we propose Bidirectional Long Short-Term Memory (LSTM) for the categorization of intracranial EEG (i-EEG) data, departing from standard approaches. Similar EEG patterns are presumably caused by drugs that work by homologous pharmacological pathways, producing similar psychotropic effects. To improve accuracy and reduce training loss, our study introduces a bidirectional LSTM model for classification along with Bayesian optimization ResultsHigh recall, precision, and F1-Scores, particularly a 95% F1-Score for morphine, ephedrine, fluoxetine, and saline, suggest good performance in predicting these drug classes. Kratom produces a somewhat lower recall of 94%, but a high F1-Score of 97% and perfect precision of 1.00. The weighted average F1-Score, macro average, and overall accuracy are all consistently high (around 97%), indicating that the model works well throughout the spectrum of drugs. ConclusionsImproved model performance was demonstrated by using a diversified dataset with five drug categories and bidirectional LSTM boosted with Bayesian optimization for hyperparameter tuning. From earlier limited-category models, it represents a substantial advancement.

Bitter taste receptors as sensors of gut luminal contents.

Taste is important in the selection of food and is orchestrated by a group of distinct receptors, the taste G protein-coupled receptors (GPCRs). Taste 1 receptors (Tas1rs in mice and TAS1Rs in humans; also known as T1Rs) detect sweet and umami tastes, and taste 2 receptors (Tas2rs in mice and TAS2Rs in humans; also known as T2Rs) detect bitterness. These receptors are also expressed in extraoral sites, including the gastrointestinal mucosa. Tas2rs/TAS2Rs have gained interest as potential targets to prevent or treat metabolic disorders. These bitter taste receptors are expressed in functionally distinct types of gastrointestinal mucosal cells, including enteroendocrine cells, which, upon stimulation, increase intracellular Ca2+ and release signalling molecules that regulate gut chemosensory processes critical for digestion and absorption of nutrients, for neutralization and expulsion of harmful substances, and for metabolic regulation. Expression of Tas2rs/TAS2Rs in gut mucosa is upregulated by high-fat diets, and intraluminal bitter 'tastants' affect gastrointestinal functions and ingestive behaviour through local and gut-brain axis signalling. Tas2rs/TAS2Rs are also found in Paneth and goblet cells, which release antimicrobial peptides and glycoproteins, and in tuft cells, which trigger type 2 immune response against parasites, thus providing a direct line of defence against pathogens. This Review will focus on gut Tas2r/TAS2R distribution, signalling and regulation in enteroendocrine cells, supporting their role as chemosensors of luminal content that serve distinct functions as regulators of body homeostasis and immune response.

Voltage-Guided and Non-Voltage-Guided Superior Vena Cava Isolation in Patients With Atrial Fibrillation.

In addition to the pulmonary vein, the superior vena cava (SVC) is an important focus of atrial fibrillation (AF). However, SVC isolation may cause serious complications, and appropriate settings and techniques for SVC isolation are lacking. This study enrolled 86 consecutive patients with AF who underwent SVC isolation. Voltage mapping using a multi-electrode catheter and ablation were performed under the guidance of an electro-anatomical mapping system. The lines encircling the SVC were divided into eight anatomic segments on the SVC geometry, and each segment was subjected to voltage-guided (VG) ablation in decreasing order of voltage (starting from the segment with the highest voltage). Non-VG (NVG) ablation was performed anatomically from the anterior wall toward the septum with one-round cautery. A total of 86 cases (66 males, mean age 69 [60, 74], mean CHA2DS2 VASc score 2 [1, 3], 58 paroxysmal AF) with AF were included for ablation. Electrical SVC isolation was successfully achieved in all patients. The length of the myocardial sleeves, as measured from the SVC-RA junction to the end of the local signal, was 37 [28, 45]mm. Major axis of the RA-SVC junction was 15 [13, 17] and minor axis of the RA-SVC junction was 11 [9, 13]. The number of ablation points with VG SVC isolation was fewer than that for NVG SVC isolation (8 [5, 11.5] vs. 11.5 [8.8, 13.3]; p=0.001). The procedure time of VG SVC isolation was greater than that of NVG SVC isolation (259s [154, 379] vs. 167s [115, 222]; p=0.012). There were no significant differences in the complication rates. VG SVC isolation reduced the number of ablation points compared with NVG SVC isolation.

Activity-dependent synapse clustering underlies eye-specific competition in the developing retinogeniculate system.

Co-active synaptic connections are often spatially clustered to facilitate local dendritic computations underlying learning, memory, and basic sensory processing. In the mammalian visual system, retinal ganglion cell (RGC) axons converge to form clustered synaptic inputs that enable local signal integration in the dorsal lateral geniculate nucleus (dLGN) of the thalamus. While visual experience promotes retinogeniculate synapse clustering after eye-opening, the earliest events in cluster formation prior to visual experience are unknown. Here, using volumetric super-resolution single-molecule localization microscopy and eye-specific labeling of developing retinogeniculate synapses in mice, we show that synaptic clustering is eye-specific and activity-dependent during retinogeniculate refinement in the first postnatal week. We identified a subset of retinogeniculate synapses with multiple active zones that are surrounded by like-eye synapses and depleted of synapse clustering from the opposite eye. In mutant mice with disrupted spontaneous retinal wave activity, synapses with multiple active zones still form, but do not exhibit the synaptic clustering seen in controls. These results highlight a role for spontaneous retinal activity in regulating eye-specific synaptic clustering in circuits essential for visual perception and behavior.

Near-infrared light stimulation regulates neural oscillation and memory behavior of mice with Alzheimer's disease.

Photobiomodulation (PBM) is a non-invasive neuromodulation technique for the brain. Low-intensity near-infrared light (1-500 mw) has demonstrated the ability to improve memory in Alzheimer's disease (AD) model mice, suggesting its potential for AD treatment. However, the impact of PBM on neural oscillations in the hippocampal region affected by AD remains unknown. In this study, AD model mice were subjected to PBM for 60 days and then tested using novel object recognition behavior (NOR) experiments. During behavioral experiments, local field potential signals (LFP) of the mice was recorded using a single electrode in the CA1 region to analyze memory ability and neural oscillation characteristics. The results revealed that mice stimulated with PBM exhibited significantly higher new object differentiation indices compared to the Sham group (p < 0.01). Furthermore, PBM stimulation led to a significant increase in relative power and sample entropy of theta and gamma bands (p < 0.01). The coupling intensities of θ-low-γ and θ-high-γ were also significantly higher in the PBM group compared to the Sham group (p < 0.01). In conclusion, these findings suggest that PBM may improve memory ability in AD mice through regulation of neural oscillation characteristics, providing a theoretical basis for utilizing PBM as a treatment modality for Alzheimer's disease.