Number Of Neurons Research Articles

The effect of chronic administration of oxycodone on the behavioral functions and histopathology in the cerebellum and striatum of adult male rats.

Oxycodone is widely used for pain management and acts via binding to mu- and kappa opioid receptors. It was shown that extended oxycodone usage can result fromthe demyelination and degeneration of neurons through the stress response, which triggers apoptotic signaling pathways. The striatum and cerebellum are recognized as significant contributors to addiction; however, there is no report on the effect of oxycodone on the cerebellum and striatum and motor coordination. We treated rats daily with oxycodone at 15mg/kg doses for thirty days.Motor performance and electromyography activity were then evaluated. Stereological methods were performed to assess the number of neurons in the cerebellum and striatum as well as immunohistochemistry for microgliosis and astrogliosis. Furthermore, the Sholl analysis method was utilized to evaluate the cellular structure of both microglia and astrocytes. Results of the rotarod test for motor coordination show no significant (P < 0.05) difference between the oxycodone subjects and those in the control group. In addition, open-field assessments indicated that the application of oxycodone did not alter the amount of distance covered (as an indicator of locomotion) or time spent in the central area (as an indicator of anxiety) (P < 0.001). The electromyography (EMG) test result showed that oxycodone caused a delay in the reaction of the muscular nerves (P < 0.001). Data and results from our experiment revealed that administering oxycodone did not affect astrogliosis and the number of neurons in the cerebellum and striatum (P < 0.05). In contrast, it altered neuromuscular function. In addition, oxycodone administration activated microglia in the cerebellum and striatum. In conclusion, we encourage more research on the adverse effects of oxycodone on the brain.

Evolution of lateralized gustation in nematodes.

Animals with small nervous systems have a limited number of sensory neurons that must encode information from a changing environment. This problem is particularly exacerbated in nematodes that populate a wide variety of distinct ecological niches but only have a few sensory neurons available to encode multiple modalities. How does sensory diversity prevail within this neuronal constraint? To identify the genetic basis for patterning different nervous systems, we demonstrate that sensory neurons in the Pristionchus pacificus respond to various salt sensory cues in a manner that is partially distinct from that of the distantly related nematode C. elegans . By visualizing neuronal activity patterns, we show that contrary to previous expectations based on its genome sequence, the salt responses of P. pacificus are encoded in a left/right asymmetric manner in the bilateral ASE neuron pair. Our study illustrates patterns of evolutionary stability and change in the gustatory system of nematodes.

Proposal and detailed theoretical analysis on a photonic neural network with optically pumped Spin-VCSEL spiking neurons

A dual-layer photonic spiking neural network (PSNN) was constructed, where multiple optically pumped spin vertical-cavity surface-emitting lasers (Spin-VCSELs) were proposed as spiking neurons. Based on a detailed theoretical analysis of leaky integrate-and-fire (LIF) and refractory period characteristics of Spin-VCSEL neurons, the training and testing performance for the studied PSNN was evaluated using two standard pattern classification tasks (Iris dataset, simple digit recognition). The results showed that, by selecting appropriate parameters such as frequency detuning and number of pre-synaptic neurons, etc., higher training/testing accuracies beyond 90% can be obtained. When compared with traditional electrically pumped VCSEL, a threshold reduction of up to 50% can be achieved under nanosecond scale spin relaxation time and circular polarization optical pumping, the feasibility of realizing high accuracy (88%) pattern classification near the reduced threshold was also verified. Therefore, optically pumped Spin-VCSEL neurons can become a valuable new choice for high-performance PSNN with reduced power consumption.

Map activation of various brain regions using different frequencies of electroacupuncture ST36, utilizing the FosCreER strategy

Objective: Electroacupuncture (EA) is an alternative treatment option for pain. Different frequencies of EA have different pain-relieving effects; however, the central mechanism is still not well understood. Methods: The Fos2A-iCreER (TRAP):Ai9 mice were divided into three groups (sham, 2 Hz, and 100 Hz). The mice were intraperitoneally injected with 4-hydroxytamoxifen (4-OHT) immediately after EA at Zusanli (ST36) for 30 min to record the activated neurons. One week later, the mice were sacrificed, and the number of TRAP-treated neurons activated by EA in the thalamus, amygdala, cortex, and hypothalamus was determined. Results: In the cortex, 2 Hz EA activated more TRAP-treated neurons than 100 Hz EA did in the cingulate cortex area 1 (Cg1) and primary somatosensory cortex (S1), and 2 and 100 Hz EAs did not differ from sham EA. TRAP-treated neurons activated by 2 Hz EA were upregulated in the insular cortex (IC) and secondary somatosensory cortex (S2) compared with those activated by 100 Hz and sham EA. In the thalamus, the number of TRAP-treated neurons activated by 2 Hz EA was elevated in the paraventricular thalamic nucleus (PV) compared with those activated by sham EA. In the ventrolateral thalamic nucleus (VL), the number of TRAP-treated neurons activated by 2 Hz EA was significantly upregulated compared with those activated by 100 Hz EA, and sham EA showed no difference compared with 2 or 100 Hz EA. TRAP-treated neurons were more frequently activated in the ventral posterolateral thalamic nucleus (VPL) by 2 Hz EA than by 100 Hz or sham EA. Conclusions: Low-frequency EA ST36 effectively activates neurons in the Cg1, S1, S2, IC, VPL, PV, and VL. The enhanced excitability of the aforementioned nuclei induced by low-frequency EA may be related to its superior efficacy in the treatment of neuropathological pain.

Tyrosine hydroxylase expression and neuronal loss in the male and female adolescent ventral tegmental area

Adolescence is a critical period of development characterized by numerous behavioral and neuroanatomical changes. While studies of adolescent neurodevelopment typically compare adolescent age groups with young adults, there are fewer studies that assess developmental trajectories within the adolescent period. In the adolescent prefrontal cortex, some maturational changes take place linearly/chronologically, while others are associated specifically with pubertal onset. The adolescent ventral tegmental area (VTA), a primary source of forebrain dopamine, is relatively understudied during this period. In the present study, dopamine neuron number, total neuron number and tyrosine hydroxylase expression are assessed in the male and female rat VTA at three timepoints: postnatal day(P) 30 (pre-pubertal), P40 (post-pubertal for females, pre-pubertal for males) and P60 (post-pubertal). There was a non-significant trend for a reduction in total VTA neuron number between P30 and P60, but there was a significant reduction in dopamine neuron number across age. The expression of tyrosine hydroxylase did not change with age. However, in a second cohort of subjects, brain tissue was collected pre-pubertal, from recently post-pubertal males and females, and young adults. In this cohort, there was a sex-specific and transient decrease in tyrosine hydroxylase expression in recently post-pubertal males. These results suggest a selective pruning of VTA dopamine cells between early adolescence and young adulthood, while pubertal onset may coincide with a rapid maturation of these neurons. These findings may have implications for psychiatric disorders associated with dopamine dysfunction that tend to manifest during adolescence.

Investigating green hydrogen production operated by redundant energy on a solar PV mini-grid through matlab simulation and artificial neural network

Green hydrogen is an important part of the transition to a net zero economy, due to its potential to deliver high amounts of energy without pollution. One important opportunity to produce green hydrogen is the use of redundant energy on solar PV mini-grids. Redundant energy is the potential generation of a mini-grid that is never utilized due to low demand and the mismatch of peak solar PV generation and peak demand. In this study, a typical rural community solar PV mini-grid is simulated using Matlab Simulink and incorporated with a water electrolyser for hydrogen production. Having run the simulation for 365 days of the year, it was revealed that the mini-grid can produce a daily average of 1.18–2.16 kg, a monthly average of 36.59–64.84 kg and a yearly total of 609.26 kg of hydrogen. Subsequently, an artificial neuron network was trained with data acquired from the simulation. With varying configurations of the number of neurons and hidden layers, it was found that the model successfully predicts hydrogen production on the mini-grid with the highest performance (RMSE = 39.85 g and R2 = 0.9979) seen when the number of hidden layers is 40 and the number of neurons per hidden layer is 3.

Therapeutic potential of Canna edulis RS3-resistant starch in alleviating neuroinflammation and apoptosis in a Parkinson's disease rat model

This study aimed to investigate the effects of Miao medicinal Canna edulis RS3-resistant starch on behavioral performance and substantia nigra neuron apoptosis-related indicators in a rat model of Parkinson's disease (PD). Among the experimental groups, except for the control group, we induced PD rat models by subcutaneous injection of rotenone in the neck and back. After model induction, a 28-day drug intervention was conducted. Various techniques have been employed, including behavioral analysis, Real-time Polymerase Chain Reaction (RT-PCR), western blotting, enzyme-linked immunosorbent assay (ELISA), immunofluorescence, and terminal deoxynucleotidyltransferase-mediated UTP nick-ends. labeling (TUNEL) and Nissl staining to investigate the effect of Canna edulis RS3-resistant starch on the substantia nigra and neuronal apoptosis-related markers in the brains of PD model rats. Our study revealed that Canna edulis RS3, a resistant starch, significantly reduced the climbing time of PD model rats, prolonged their hanging time, lowered the expression levels of the inflammatory factors IL-1β, IL-6, and TNF-α, increased the number of TH-positive neurons in the substantia nigra, and decreased the levels of IL-1β, IL-6, and TNF-α. Furthermore, Canna edulis RS3 elevated the protein expression levels of tyrosine hydroxylase (TH) and Bcl-2 while reducing those of Bax, TLR4, NLRP3,and p-P65, and mitigated apoptosis and morphological changes in dopaminergic neurons in the substantia nigra region. Our results suggest that Canna edulis RS3-resistant starch may offer therapeutic benefits for PD patients with PD by potentially influencing inflammation and apoptosis in the dopaminergic system.

Efficient grid management: smart forecasting of short-term power load using PSO-LSTM

Recent load forecasting techniques combining machine learning models and hyperparameter optimization algorithms have shown success for short-term load forecasting (STLF) task, but they often require complex programming, higher computational costs, and greater parameter tuning. In this paper, we introduce an improved STLF model that combines Long Short-Term Memory (LSTM) neural network with Particle Swarm Optimization (PSO) for enhanced performance. In the proposed approach, the number of hidden neurons in different LSTM layers, learning rate and the number of iterations for training are optimized using the PSO algorithm. To validate the effectiveness of this method, meteorological data and historical load data from a real-world power grid are used as input. The experimental results reveal PSO significantly enhances hyperparameter tuning for LSTM neural networks, leading to improved predictive modelling. The PSO-LSTM model performed better than the LSTM model by more than 20% (in terms of Mean Absolute Error), and showed low sensitivity to hyperparameters. Comparative analysis with alternative approaches from the literature further validates the PSO-LSTM’s effectiveness in STLF. Additionally, the model achieved stable multi-step prediction capabilities, with average errors of 3.6445 for MAE, 4.6509 for RMSE, and 4.6519 for MAPE over a 1–4 day ahead lead times. This study highlights PSO-LSTM’s enhanced robustness and accuracy in power load prediction while addressing hyperparameter tuning challenges through self-optimization.

A comprehensive analysis of the artificial neural networks model for predicting monkeypox outbreaks

Monkeypox is a viral disease that causes outbreaks in various countries, significantly impacting public health and healthcare systems. Effective preparedness and response efforts require accurately predicting the severity of these outbreaks. Currently, there are no publicly released studies for nations like Chile and Mexico on monkeypox, leading to this study's creation. We use a neural network model with a time series dataset of monkeypox cases from multiple countries, including Argentina, Brazil, France, Germany, Chile, and Mexico. The Levenberg-Marquardt learning technique is employed to develop and validate single and two hidden layers artificial neural network models. We train various model architectures with different numbers of hidden layer neurons using the K-fold cross-validation early stopping method. Additionally, we use long short-term memory and gated recurrent unit models, commonly employed for time series data processing, to compare the performance of our artificial neural network model.

Recent Progressions on Peripheral Hypotheses of Hypothalamic Aging

Background: It is well known that the changes of hypothalamus in control of hormones determine the chronological manifestations of aging in mammals.Aim: It is aimed to review the progressions on recently hypothesized peripheral mechanisms responsible for the senescent changes of the hypothalamic nuclei and secretion.Methods: It was searched the papers from Pubmed and Baidu, and then analyzed and summarized.Results and Discussions: (a) It was proposed by Cai that the decrease in slow-wave sleep (SWS) resulting from continual skin aging cause both decrease in secretion of growth hormone (GH) and degeneration of suprachiasmatic nucleus(SCN) for hypothalamus. (b) It was soon hypothesized by the Europeans that the increase in body fat be responsible for the degeneration of male hypothalamic preoptic sexually dimorphic nucleus (SDN-POA), which was supported by the increment of aromatase converting testosterone to estradiol as proposed by Cohen, with testosterone required to maintain SDN-POA. In parallel, it was speculated the aging of female ovary toward menopause as acceleration and precocity similarly in association with the corresponding senescent changes in lipid, aromatase and estradiol. (c) It was the hypothalamic paraventricular nucleus (PVN) that retained neuron number unchanged during aging for psychological stress..Conclusion: It is summarized that the hypothalamic senescence resulting from these peripheral mechanisms shifts the functional balance among these three hypothalamic systems toward aging.

Nutritional Imbalance between Omega-6 and Omega-3 Polyunsaturated Fatty Acids during Pregnancy Increases the Number of Pyramidal Neurons in the Basolateral Amygdala and Anxiety-Related Behavior in Offspring.

Modern agriculture allows for the production of foods that are high in n-6 linoleic acid and low in n-3 α-linolenic acid (LAhigh/ALAlow), which are suggested to be associated with an increased risk for the onset of anxiety disorders. However, there is not sufficient evidence to understand its underlying brain mechanism. Given that mouse offspring derived from mothers fed a LAhigh/ALAlow diet during gestation and early lactation showed increased anxiety-related behaviors and that rodents exposed to a LAhigh/ALAlow diet are more vulnerable to stress, in this study, we investigated the effects of maternal LAhigh/ALAlow diet consumption on stress-induced anxiety-related behavior and the brain structures involved in the expression of negative emotional states in mouse offspring. In a standard environment, offspring exposed to either the control diet or the LAhigh/ALAlow diet in utero showed similar stay times in the center zone in the open field test. On the other hand, under stressful environments, offspring exposed to the LAhigh/ALAlow diet in utero showed decreased stay times in the center zone compared to those exposed to the control diet. We further found that the number of a subpopulation of pyramidal neurons in the basolateral amygdala, which can regulate negative emotional behaviors, was greater in the offspring exposed to the LAhigh/ALAlow diet compared to those exposed to the control diet. These data suggest that maternal dietary imbalance between n-6 and n-3 polyunsaturated fatty acids confers stress vulnerability to offspring during the process of brain development.

Statistical and machine learning models for location-specific crop yield prediction using weather indices.

Crop yield prediction gains growing importance for all stakeholders in agriculture. Since the growth and development of crops are fully connected with many weather factors, it is inevitable to incorporate meteorological information into yield prediction mechanism. The changes in climate-yield relationship are more pronounced at a local level than across relatively large regions. Hence, district or sub-region-level modeling may be an appropriate approach. To obtain a location- and crop-specific model, different models with different functional forms have to be explored. This systematic review aims to discuss research papers related to statistical and machine-learning models commonly used to predict crop yield using weather factors. It was found that Artificial Neural Network (ANN) and Multiple Linear Regression were the most applied models. Support Vector Regression (SVR) model has a high success ratio as it performed well in most of the cases. The optimization options in ANN and SVR models allow us to tune models to specific patterns of association between weather conditions of a location and crop yield. ANN model can be trained using different activation functions with optimized learning rate and number of hidden layer neurons. Similarly, the SVR model can be trained with different kernel functions and various combinations of hyperparameters. Penalized regression models namely, LASSO and Elastic Net are better alternatives to simple linear regression. The nonlinear machine learning models namely, SVR and ANN were found to perform better in most of the cases which indicates there exists a nonlinear complex association between crop yield and weather factors.

Periodically activated physics-informed neural networks for assimilation tasks for three-dimensional Rayleigh–Bénard convection

We apply physics-informed neural networks to three-dimensional Rayleigh–Bénard convection in a cubic cell with a Rayleigh number of Ra=106 and a Prandtl number of Pr=0.7 to assimilate the velocity vector field from given temperature fields and vice versa. With the respective ground truth data provided by a direct numerical simulation, we are able to evaluate the performance of the different activation functions applied (sine, hyperbolic tangent and exponential linear unit) and different numbers of neurons (32, 64, 128, 256) for each of the five hidden layers of the multi-layer perceptron. The main result is that the use of a periodic activation function (sine) typically benefits the assimilation performance in terms of the analyzed metrics, correlation with the ground truth and mean average error. The higher quality of results from sine-activated physics-informed neural networks is also manifested in the probability density function and power spectra of the inferred velocity or temperature fields. Regarding the two assimilation directions, the assimilation of temperature fields based on velocities appears to be more challenging in the sense that it exhibits a sharper limit on the number of neurons below which viable assimilation results cannot be achieved.

Excitotoxic spinal damage induced by kainic acid impairs locomotion, alters nociception, and reduces CREB nuclear translocation

Our previous in vitro studies showed that excitotoxicity evoked by glutamate analogue kainate (KA) significantly decreased the number of rat spinal neurons and triggered high release of glutamate leading to locomotor network block. Our current objective was to assess the role of CREB as a predictive marker of damage following chemically-induced spinal cord injury by using in vivo and in vitro models. Thus, in vivo excitotoxicity in Balb/c adult mice was induced by KA intraspinal injection, while in vitro spinal cord excitotoxicity was produced by bath-applied KA. KA application evoked significant neuronal loss, deterioration in hindlimb motor coordination and thermal allodynia. In addition, immunohistochemical analysis showed that KA application resulted in decreased number of CREB positive nuclei in the ventral horn and in dorsal layers III-IV. Our data suggests that excitotoxic-induced neuronal loss may be potentially predicted by altered CREB nuclear translocation.

Hypothalamic representation of the imminence of predator threat detected by the vomeronasal organ in mice.

Animals have the innate ability to select optimal defensive behaviors with appropriate intensity in response to predator threats within specific contexts. Such innate behavioral decisions are thought to be computed in the medial hypothalamic nuclei, which contain neural populations that directly control defensive behavioral outputs. The vomeronasal organ (VNO) serves as a primary sensory channel for detecting predator cues by relaying signals to the medial hypothalamic nuclei, particularly the ventromedial hypothalamus (VMH), via the medial amygdala (MeA) and bed nucleus of the stria terminalis (BNST). Here, we demonstrate that cat saliva contains predator cues that signal the imminence of predator threat and modulate the intensity of freezing behavior through the VNO in mice. Cat saliva activates neurons expressing the V2R-A4 subfamily of sensory receptors, suggesting that specific receptor groups are responsible for inducing the freezing behavior. The number of VNO neurons activated in response to saliva correlates with both the freshness of saliva and the intensity of freezing behavior. In contrast, the downstream neurons in the accessory olfactory bulb (AOB) and the defensive behavioral circuit are activated to a similar extent by fresh and old saliva. Strikingly, however, the number of VMH neurons activated by fresh, but not old, saliva positively correlates with the intensity of freezing behavior. Detailed analysis of the spatial distribution of neurons responding to fresh and old saliva, as well as the overlap of those activated within the same individual mice, revealed that fresh and old saliva predominantly activate distinct neuronal populations within the VMH. Collectively, this study suggests that there is an accessory olfactory circuit in mice that is specifically tuned to time-sensitive components of cat saliva, which optimizes their defensive behavior to maximize their chance of survival according to the imminence of threat.

Machine Learning Approaches for Short-Term Photovoltaic Power Forecasting

A photovoltaic (PV) power forecasting prediction is a crucial stage to utilize the stability, quality, and management of a hybrid power grid due to its dependency on weather conditions. In this paper, a short-term PV forecasting prediction model based on actual operational data collected from the PV experimental prototype installed at the engineering college of Misan University in Iraq is designed using various machine learning techniques. The collected data are initially classified into three diverse groups of atmosphere conditions—sunny, cloudy, and rainy meteorological cases—for various seasons. The data are taken for 3 min intervals to monitor the swift variations in PV power generation caused by atmospheric changes such as cloud movement or sudden changes in sunlight intensity. Then, an artificial neural network (ANN) technique is used based on the gray wolf optimization (GWO) and genetic algorithm (GA) as learning methods to enhance the prediction of PV energy by optimizing the number of hidden layers and neurons of the ANN model. The Python approach is used to design the forecasting prediction models based on four fitness functions: R2, MAE, RMSE, and MSE. The results suggest that the ANN model based on the GA algorithm accommodates the most accurate PV generation pattern in three different climatic condition tests, outperforming the conventional ANN and GWO-ANN forecasting models, as evidenced by the highest Pearson correlation coefficient values of 0.9574, 0.9347, and 0.8965 under sunny, cloudy, and rainy conditions, respectively.

PET imaging of synaptic vesicle glycoprotein 2 subtype A for neurological recovery in ischemic stroke.

[18F]SynVesT-1 is a novel radiopharmaceutical for assessing synaptic density in vivo. This study aims to investigate the potential of [18F]SynVesT-1 positron emission tomography (PET) in evaluating neurological recovery in the rat model of ischemic stroke, and to compare its performance with [18F]FDG PET. Sprague-Dawley rats were subjected to photothrombotic cerebral infarction, and safinamide was administered intraperitoneally from day 3 to day 14 post-stroke to alleviate neurological deficits. Cylinder test and forelimb placing test were performed to assess the neurological function. MRI, [18F]SynVesT-1 PET/CT and [18F]FDG PET/CT imaging were used to evaluate infarct volume, synaptic density, and cerebral glucose metabolism pre- and post-treatment. [18F]SynVesT-1 and [18F]FDG PET images were compared using Statistical Parametric Mapping (SPM) and region of interest (ROI)-based analysis. Post-mortem histological analysis was performed to validate PET images. Safinamide treatment improved behavioral outcomes in stroke-damaged rats. Both [18F]SynVesT-1 and [18F]FDG PET detected stroke-induced injury, with the injured region being significantly larger in [18F]FDG PET than in [18F]SynVesT-1 PET. Compared with the saline group, radiotracer uptake in the injured area significantly increased in [18F]SynVesT-1 PET after safinamide treatment, whereas no notable change was observed in [18F]FDG PET. Additionally, [18F]SynVesT-1 PET imaging showed a better correlation with neurological function recovery than [18F]FDG PET. Post-mortem analysis revealed increased neuronal numbers, synaptic density, and synaptic neuroplasticity, as well as decreased glia activation in the stroke-injured area after treatment. [18F]SynVesT-1 PET effectively quantified spatiotemporal dynamics of synaptic density in the rat model of stroke, and showed different capabilities in detecting stroke injury and neurological recovery compared with [18F]FDG PET. The utilization of [18F]SynVesT-1 PET holds promise as a potential non-invasive biomarker for evaluating ischemic stroke in conjunction with [18F]FDG PET.

Changes in AmotL2 Expression in Cells of the Human Enteral Nervous System in Oxaliplatin-Induced Enteric Neuropathy.

Gastrointestinal (GI) toxicity is a common side effect in patients undergoing oxaliplatin (OxPt)-based chemotherapy for colorectal cancer (CRC). Frequently, this complication persists in the long term and could affect the efficacy of the treatment and the patient's life quality. This long-term GI toxicity is thought to be related to OxPt-induced enteral neuropathy. AmotL2 is a member of the Angiomotin family of proteins, which play a role in cell survival, neurite outgrowth, synaptic maturation, oxidative stress protection, and inflammation. In order to assess the role of AmotL2 in OxPt-induced enteral neuropathy, we studied the expression of AmotL2 in cells of the enteric nervous system (ENS) of untreated and OxPt-treated CRC patients and its relationship with inflammation, using immunofluorescence confocal microscopy. Our results in human samples show that the total number of neurons and glial cells decreased in OxPt-treated patients, and TNF-α and AmotL2 expression was increased and colocalized in both neurons and glia. AmotL2 differential expression between OxPt-treated and untreated CRC patients shows the involvement of this scaffold protein in the inflammatory component and toxicity by OxPt in the ENS.

Mastocytosis and intraepithelial lymphocytosis in the ileum and colon characterize chronic Toxoplasma gondii infection in mice

Toxoplasma gondii is the causative agent of toxoplasmosis, a common zoonotic disease affecting vertebrates with high global incidence. For the parasite to disseminate throughout the body, it crosses the intestinal barrier, triggering inflammatory reactions. This study aimed to assess the tissue response in the ileum and colon of mice following chronic infection with T. gondii. Fourteen mice were divided into two groups: the infected group received 1000 T. gondii oocysts via gavage, and after 60 days, the mice were euthanized. The ileum and colon were collected and processed for histological analysis, inflammatory marker measurement and myenteric neuron analysis. Chronic infection resulted in a significant increase in intraepithelial lymphocytes and mast cells, as well as morphometric changes such as increased total intestinal wall thickness of the ileum, crypt depth, collagen fiber area, and a decrease in myeloperoxidase activity, without altering nitric oxide levels. While the number of myenteric neurons remained unchanged, there was an increase in vasoactive intestinal peptide expression. These results suggest persistence intestinal inflammatory stimuli in chronic T. gondii infection.

Testosterone in Puberty Regulates Emotional Contagion and Consolation via the Vasopressin System in the Anterior Cingulate Cortex of C57BL/6J Mice

Introduction: Empathy is the ability of an individual to present and respond to the emotions of others and is thought to originate from parental behavior. Testosterone could promote aggression and inhibit biparental behavior and vasopressin (AVP) could promote aggression. Given levels of aggression and parental care are closely associated with levels of empathy, we hypothesized that testosterone may influence empathetic behavior via the AVP system. Methods: We examined testosterone levels and tested social, empathic, and anxiety-like behaviors after castration surgery to pubertal mice, and subsequently examined the molecular levels of AVP, V1aR in different brain regions. Finally, pharmacological experiments were used to test the effects on empathic behavior by injecting testosterone in combination with V1aR antagonist. Results: Here, we show that pubertal castration reduced serum testosterone levels, increased empathetic behavior and sociality, and reduced anxiety-like behaviors in male C57 mice. The pubertal castration also reduced AVP and vasopressin receptor (V1aR) protein levels, and AVP mRNA levels in the PVN. It also reduced the number of AVP-positive neurons in the PVN. In addition, pubertal subcutaneous injection of testosterone reduced emotional contagion and consolation of castrated mice, while concomitant injection of V1aR antagonists into the anterior cingulate cortex (ACC) reversed the downregulation of emotional contagion and consolation induced by testosterone. Conclusion: It is suggested that testosterone in puberty regulates empathetic behavior in C57 mice possibly via the AVP system in the ACC. These findings help us to understand the neuroendocrine mechanisms underlying empathetic behavior and provide potential targets for the treatment of psychiatric disorders associated with low empathy.