Neuronal Counts Research Articles

Amelioration of propionic acid-induced autism-like behaviors in rats by fenofibrate: A focus on reduction of brain galectin-3 levels.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired social interactions and repetitive behaviors. This study examines the effects of fenofibrate on a propionic acid (PPA)-induced rat model of ASD, focusing on behavioral changes, inflammatory markers, and histological findings. Thirty male Wistar rats were divided into three groups: a control group, a group receiving PPA and saline, and a group treated with PPA and fenofibrate for 15 days. Behavioral assessments, including the three-chamber sociability test, open-field test, and passive avoidance learning, were conducted. Biochemical analyses measured TNF-α, NGF, IL-17, IL-2, and galectin-3 levels in brain tissues. Histological evaluations focused on Purkinje neuron counts in the cerebellum and neuronal changes in the CA1 and CA3 regions of the hippocampus, along with glial fibrillary acidic protein (GFAP) levels. Fenofibrate treatment significantly improved behavioral outcomes, reducing autism-like behaviors compared to the PPA/saline group. Biochemically, the PPA/saline group showed elevated levels of malondialdehyde, TNF-α, IL-2, IL-17, and galectin-3, which were reduced following fenofibrate treatment. Histologically, the PPA/saline group exhibited fewer, dysmorphic Purkinje neurons and increased glial activity in the CA1 region, both of which were ameliorated by fenofibrate treatment. Fenofibrate shows promise in mitigating autism-like behaviors in a rat model of ASD, likely due to its antioxidative and neuroprotective properties, which contribute to preserving neuronal integrity and reducing inflammation.

Prolonged STAT1 signaling in neurons causes hyperactive behavior

The interferon (IFN)-induced STAT1 signaling pathway is a canonical immune pathway that has also been implicated in regulating neuronal activity. The pathway is enriched in brains of individuals with autism spectrum disorder (ASD) and schizophrenia (SZ). Over-activation of the STAT1 pathway causes pathological transcriptional responses, however it is unclear how these responses might translate into behavioral phenotypes. We hypothesized that prolonged STAT1 signaling in neurons would be sufficient to cause behavioral deficits associated with neurodevelopmental disorders. In this study, we developed a novel mouse model with the clinical STAT1 gain-of-function mutation, T385M, in neurons. These mice were hyperactive and displayed neural hypoactivity with less neuron counts in the caudate putamen. Driving the STAT1 gain-of-function mutation exclusively in dopaminergic neurons, which project to the caudate putamen of the dorsal striatum, mimicked some hyperactive behaviors without a reduction of neurons. Moreover, we demonstrated that this phenotype is neuron specific, as mice with prolonged STAT1 signaling in all excitatory or inhibitory neurons or in microglia were not hyperactive. Overall, these findings suggest that STAT1 signaling in neurons is a crucial player in regulating striatal neuron activity and aspects of motor behavior.

Oseltamivir phosphate (Tamiflu) alters neurobehavior of zebrafish larvae by inducing mitochondrial dysfunction

Antiviral drugs are widely used, yet their potential risks during early development, particularly within the central nervous system, remain contentious. Oseltamivir phosphate (OSE), a commonly prescribed antiviral, is increasingly detected in various environments. However, its toxicity to organisms and the underlying mechanisms are not well understood. In this study, we employed the zebrafish model to evaluate the developmental neurotoxic effects of OSE at environmentally and therapeutically relevant doses, through high-throughput behavioral analysis, in vivo two-photon imaging, transcriptomic sequencing, pharmacological intervention, and biochemical and molecular assays. Our results indicated that OSE exposure increased heart rate and induced pericardial edema in zebrafish larvae. Additionally, OSE-exposed larvae exhibited hyperactive behavior, impaired social interactions, and reduced habitual learning capacity. Although OSE at our selected levels did not significantly affect neuron count in the brain, it activated neuroinflammatory responses, altered blood vessel morphology, modulated neurotransmitter levels and the expression of neurodevelopment-related genes. Transcriptomic analysis revealed upregulation of mitochondria-related genes associated with oxidative phosphorylation. Further assessments of mitochondrial function demonstrated altered activities of respiratory chain complexes, reduced mitochondrial membrane potential (MMP), and decreased ATP content. Notably, co-treatment with mitochondrial protectants acetyl-l-carnitine-hydrochloride (ALC) or nicotinamide riboside (NR) effectively mitigated OSE-induced neurobehavioral disorders. These findings suggest that overuse of OSE can pose neurodevelopmental risks for both humans and animals, potentially attributable to mitochondrial dysfunction.

Performance Comparison of Bio-Inspired Algorithms for Optimizing an ANN-Based MPPT Forecast for PV Systems.

This study compares bio-inspired optimization algorithms for enhancing an ANN-based Maximum Power Point Tracking (MPPT) forecast system under partial shading conditions in photovoltaic systems. Four algorithms-grey wolf optimizer (GWO), particle swarm optimization (PSO), squirrel search algorithm (SSA), and cuckoo search (CS)-were evaluated, with the dataset augmented by perturbations to simulate shading. The standard ANN performed poorly, with 64 neurons in Layer 1 and 32 in Layer 2 (MSE of 159.9437, MAE of 8.0781). Among the optimized approaches, GWO, with 66 neurons in Layer 1 and 100 in Layer 2, achieved the best prediction accuracy (MSE of 11.9487, MAE of 2.4552) and was computationally efficient (execution time of 1198.99 s). PSO, using 98 neurons in Layer 1 and 100 in Layer 2, minimized MAE (2.1679) but had a slightly longer execution time (1417.80 s). SSA, with the same neuron count as GWO, also performed well (MSE 12.1500, MAE 2.7003) and was the fastest (987.45 s). CS, with 84 neurons in Layer 1 and 74 in Layer 2, was less reliable (MSE 33.7767, MAE 3.8547) and slower (1904.01 s). GWO proved to be the best overall, balancing accuracy and speed. Future real-world applications of this methodology include improving energy efficiency in solar farms under variable weather conditions and optimizing the performance of residential solar panels to reduce energy costs. Further optimization developments could address more complex and larger-scale datasets in real-time, such as integrating renewable energy sources into smart grid systems for better energy distribution.

Evaluating deep learning techniques for optimal neurons counting and characterization in complex neuronal cultures.

The counting and characterization of neurons in primary cultures have long been areas of significant scientific interest due to their multifaceted applications, ranging from neuronal viability assessment to the study of neuronal development. Traditional methods, often relying on fluorescence or colorimetric staining and manual segmentation, are time consuming, labor intensive, and prone to error, raising the need for the development of automated and reliable methods. This paper delves into the evaluation of three pivotal deep learning techniques: semantic segmentation, which allows for pixel-level classification and is solely suited for characterization; object detection, which focuses on counting and locating neurons; and instance segmentation, which amalgamates the features of the other two but employing more intricate structures. The goal of this research is to discern what technique or combination of those techniques yields the optimal results for automatic counting and characterization of neurons in images of neuronal cultures. Following rigorous experimentation, we conclude that instance segmentation stands out, providing superior outcomes for both challenges.

Predictive modeling of membrane reactor efficiency using advanced artificial neural networks for green hydrogen production

The imperative to decarbonize the energy sector has prompted substantial advancements in clean electricity generation, with hydrogen emerging as a promising low-carbon energy carrier. While hydrogen synthesis from renewable sources is crucial, challenges persist, necessitating innovative approaches for efficient and sustainable production. This study leverages diverse artificial neural network (ANN) models to assess and predict system efficiency based on key operational variables in membrane reactor systems. The multilayered perceptron (MLP) and radial basis function (RBF) methodologies are employed, with the MLP models optimized across twelve training algorithms and eight activation functions, exploring up to three hidden layers with variable neuron counts. The MLP model, utilizing the Levenberg-Marquard training algorithm and Tangent-Sigmoid activation function, achieved a high correlation coefficient (R2) of 0.9975 for training and 0.9962 for testing, and a mean squared error (MSE) of 0.00425 for training and 0.23951 for testing, indicating precise and accurate efficiency predictions. The Log-Sigmoid activation function also performed well, with R² values of 0.9971 (training) and 0.9961 (testing), and MSE values of 0.004086 (training) and 0.17694 (testing). Optimization of the RBF network identified the best performance with a spread parameter of 1 and 35 neurons, although the MLP model demonstrated superior accuracy and reduced computational time. Statistical analysis, encompassing correlation coefficient, mean squared error, Root Mean Squared error, absolute average deviation, absolute average relative deviation, and runtime, confirms the network’s consistent and accurate estimation of system efficiency across various input variables. The study highlights that applying tansig and logsig activation functions, configured with neuron counts of 20, 17, 6 and 23, 20, 2 at the first, second and third hidden layers, respectively, offers enhanced accuracy and reliability. The MLP model’s high performance underscores its potential to identify optimal conditions for H2 generation based on system efficiency, thereby advancing membrane reactor technology for hydrogen production.

WuYou decoction effectively reduces neuronal damage, synaptic dysfunction, and Aβ production in rats exposed to chronic sleep deprivation by modulating the Aβ-related enzymes and SIRT1/Nrf2/NF-κB pathway

Ethnopharmacological relevanceChronic sleep deprivation (CSD) can result in neuronal damage, synaptic dysfunction, Aβ production, neuroinflammation, and ultimately cognitive deterioration. WuYou Decoction (WYD), a contemporary prescription, has shown promise in enhancing sleep quality and cognitive performance in individuals with insomnia. However, the specific molecular mechanisms responsible for the neuroprotective effects of WYD on CSD remain incompletely understood. Aim of the studyThis study aimed to investigate the neuroprotective effects of WYD on the CSD model and its molecular mechanism. Materials and methodsUHPLC-MS/MS analysis was utilized to analyze the active ingredients of WYD extract. The study employed the multi-platform water environment method to establish the CSD model in rats. Subsequent to treatment with varying doses of WYD in CSD rats, cognitive function and pathological alterations in hippocampus and cortex, including neuronal damage, synaptic dysfunction, Aβ production, and neuroinflammation, were evaluated through a combination of Morris Water Maze test, HE staining, Nissl staining, Golgi-Cox staining, Transmission electron microscope, ELISA, Immunohistochemistry staining, Immunofluorescence staining and Western blot. ResultsUHPLC-MS/MS analysis revealed a total of 99 active ingredients were identified from the WYD extract. The administration of WYD exhibited a mitigation of cognitive decline in the model of CSD, as evidenced by increased neuron count in the hippocampus and cortex, and improved density and length of dendritic spines in these brain regions. Furthermore, WYD was found to suppress the Aβ production, and inhibit the expression of BACE1, PS1, GFAP, IBA1, IL-1β, IL-6, TNF-α, phosphorylated IκBα (Ser32) and phosphorylated NF-κB p65 (Ser536) in the hippocampus and cortex, while also increasing the levels of PSD95, SYN1, ADAM10, IDE, SIRT1 and Nrf2. ConclusionsWYD exhibits neuroprotective properties in CSD, potentially through modulation of the Aβ-related enzymes and SIRT1/Nrf2/NF-κB pathway.

Berberine alleviates cerebellar damage in global cerebral ischemia: A comprehensive study with stereological analysis, evaluation of the antioxidant response, and locomotor function in rat models

AbstractBackgroundGlobal cerebral ischemia (GCI) leads to significant oxidative damage in the cerebellum, mainly affecting Purkinje cells. This study aimed to investigate the neuroprotective effects of berberine chloride (BBR), a compound known for its antioxidant properties against GCI.Materials and methodsFourty‐two adult male Wistar rats were divided into three groups: Sham, GCI, and GCI + BBR. Rats received BBR (50 mg/kg) seven days before and six hours after inducing GCI via bilateral common carotid artery occlusion for 20 min. They were assessed for locomotor activity by the open‐field test, the cerebellar biochemical factors malondialdehyde (MDA), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), cerebellum volume and Purkinje neuron count by stereological analysis.ResultsThe BBR treatment reduced the concentration of MDA and increased the activity of antioxidant enzymes SOD, CAT and GPx in the GCI + BBR group compared to the GCI group. Stereological analysis revealed higher Purkinje cell count, cerebellum, white matter, and gray matter volume in the GCI + BBR group compared to the GCI group. Furthermore, GCI + BBR showed enhanced locomotor function compared to the GCI group.ConclusionBBR showed therapeutic benefits and improved locomotor function. It demonstrated antioxidative effects by lowering MDA levels, boosting enzymatic activities, and significantly mitigating Purkinje cell death and cerebellar volume loss.

AIMP2 accumulation in brain leads to cognitive deficits and blood secretion in Parkinson’s disease

BackgroundPropagation of neuronal α-synuclein aggregate pathology to the cortex and hippocampus correlates with cognitive impairment in Parkinson’s disease (PD) dementia and dementia with Lewy body disease. Previously, we showed accumulation of the parkin substrate aminoacyl-tRNA synthetase interacting multifunctional protein-2 (AIMP2) in the temporal lobe of postmortem brains of patients with advanced PD. However, the potential pathological role of AIMP2 accumulation in the cognitive dysfunction of patients with PD remains unknown.MethodsWe performed immunofluorescence imaging to examine cellular distribution and accumulation of AIMP2 in brains of conditional AIMP2 transgenic mice and postmortem PD patients. The pathological role of AIMP2 was investigated in the AIMP2 transgenic mice by assessing Nissl-stained neuron counting in the hippocampal area and Barnes maze to determine cognitive functions. Potential secretion and cellular uptake of AIMP2 was monitored by dot blot analysis and immunofluorescence. The utility of AIMP2 as a new PD biomarker was evaluated by dot blot and ELISA measurement of plasma AIMP2 collected from PD patients and healthy control followed by ROC curve analysis.ResultsWe demonstrated that AIMP2 is toxic to the dentate gyrus neurons of the hippocampus and that conditional AIMP2 transgenic mice develop progressive cognitive impairment. Moreover, we found that neuronal AIMP2 expression levels correlated with the brain endothelial expression of AIMP2 in both AIMP2 transgenic mice and in the postmortem brains of patients with PD. AIMP2, when accumulated, was released from the neuronal cell line SH-SY5Y cells. Secreted AIMP2 was taken up by human umbilical vein endothelial cells. Consistent with the fact that AIMP2 can be released into the extracellular space, we showed that AIMP2 transgenic mice have higher levels of plasma AIMP2. Finally, ELISA-based assessment of AIMP2 in plasma samples from patients with PD and controls, and subsequent ROC curve analysis proved that high plasma AIMP2 expression could serve as a reliable molecular biomarker for PD diagnosis.ConclusionsThe pathological role in the hippocampus and the cell-to-cell transmissibility of AIMP2 provide new therapeutic avenues for PD treatment, and plasma AIMP2 combined with α-synuclein may improve the accuracy of PD diagnosis in the early stages.

Whole-brain annotation and multi-connectome cell typing of Drosophila

The fruit fly Drosophila melanogaster has emerged as a key model organism in neuroscience, in large part due to the concentration of collaboratively generated molecular, genetic and digital resources available for it. Here we complement the approximately 140,000 neuron FlyWire whole-brain connectome1 with a systematic and hierarchical annotation of neuronal classes, cell types and developmental units (hemilineages). Of 8,453 annotated cell types, 3,643 were previously proposed in the partial hemibrain connectome2, and 4,581 are new types, mostly from brain regions outside the hemibrain subvolume. Although nearly all hemibrain neurons could be matched morphologically in FlyWire, about one-third of cell types proposed for the hemibrain could not be reliably reidentified. We therefore propose a new definition of cell type as groups of cells that are each quantitatively more similar to cells in a different brain than to any other cell in the same brain, and we validate this definition through joint analysis of FlyWire and hemibrain connectomes. Further analysis defined simple heuristics for the reliability of connections between brains, revealed broad stereotypy and occasional variability in neuron count and connectivity, and provided evidence for functional homeostasis in the mushroom body through adjustments of the absolute amount of excitatory input while maintaining the excitation/inhibition ratio. Our work defines a consensus cell type atlas for the fly brain and provides both an intellectual framework and open-source toolchain for brain-scale comparative connectomics.

Long Short-Term Memory and Gated Recurrent Unit Modeling for Stock Price Forecasting

The rapid advancement of deep learning technology offers significant benefits, particularly for time series data forecasting. LSTM and GRU are two deep learning methods used for forecasting. This study aims to compare the LSTM and GRU methods in predicting the stock prices of PT Mayora Indah Tbk, listed on the Indonesia Stock Exchange (IDX), accessed through Yahoo Finance. The model architecture was developed using combinations of data splitting, learning rate, epoch count, and neuron count. The combinations used in this study include data splits of 70:30 and 80:20, with varying parameter combinations of learning rates at 0.01, 0.001, and 0.0001, epoch counts of 50, 100, and 150, and neuron counts of 50 and 100. The results indicate that the GRU method outperforms the LSTM method in prediction accuracy. The RMSE and MAPE tests show that the GRU method yields RMSE and MAPE of 34.4233 and 1.27%, respectively, compared to the LSTM method with RMSE and MAPE of 35.3775 and 1.28%. The best GRU architecture was achieved with a learning rate of 0.001, 50 neurons, and 150 epochs, while the best LSTM architecture was achieved with a learning rate of 0.001, 100 neurons, and 150 epochs. The optimal architecture for both methods was found with a data split of 70:30

Cognitive resilience to Alzheimer's disease characterized by cell-type abundance.

The molecular basis of cognitive resilience (CR) among pathologically confirmed Alzheimer's disease (AD) cases is not well understood. Abundance of 13 cell types and neuronal subtypes in brain bulk RNA-seq data from the anterior caudate, dorsolateral prefrontal cortex (DLPFC), and posterior cingulate cortex (PCC) obtained from 434 AD cases, 318 cognitively resilient AD cases, and 188 controls in the Religious Orders Study and Rush Memory and Aging Project was estimated by deconvolution. PVALB+ neuron abundance was negatively associated with cognitive status and tau pathology in the DLPFC and PCC (Padj<0.001) and the most reduced neuronal subtype in AD cases compared to controls in DLPFC (Padj=8.4×10-7) and PCC (Padj=0.0015). We identified genome-wide significant association of neuron abundance with TMEM106B single nucleotide polymorphism rs13237518 in PCC (p=6.08×10-12). rs13237518 was also associated with amyloid beta (p=0.0085) and tangles (p=0.0073). High abundance of PVALB+ neurons may be a marker of CR. TMEM106B variants may influence CR independent of AD pathology. Neuron retention and a lack of astrocytosis are highly predictive of Alzheimer's disease (AD) resilience. PVALB+ GABAergic and RORB+ glutamatergic neurons are associated with cognitive status. A TMEM106B single nucleotide polymorphism is related to lower AD risk, higher neuron count, and increased AD pathology.

Neuroprotective effects of Paederia foetida Linn. on scopolamine-induced cognitive impairment in rats.

Alzheimer's disease (AD) poses a significant health-care challenge, often linked to cognitive decline caused by oxidative stress. This study investigated the potential neuroprotective effects of the Paederia foetida leaf extract (PFE) in rats that exhibited scopolamine-induced dementia mimicking AD. Forty-two male rats were treated with either donepezil (0.5 mg/kg) or PFE at doses of 250, 500, and 1000 mg/kg for 14 days before and 14 days after the beginning of Alzheimer's-like symptoms after 14 consecutive days of scopolamine administration. Behavioral tests, including the open-field test for locomotor activity and the Morris water maze task for learning and memory assessment, were conducted. Neuronal cell counts and biochemical assays were performed to further analyze outcomes. All groups exhibited normal locomotor activity. The scopolamine group displayed longer escape latency times, reduced time in the target quadrant, decreased number of surviving neurons, and increased malondialdehyde and decreased glutathione levels compared with the control group. However, pre-treatment with 1000 mg/kg PFE notably mitigated the neurotoxic effects of scopolamine. The neuroprotective properties of PFE are highlighted, suggesting its potential as a promising treatment strategy for AD.

UAMC-3203 inhibits ferroptosis and promotes functional recovery in rats with spinal cord injury

Spinal cord injury (SCI) results in irreversible neurological impairment. After SCI, Ferritinophagy-induced free iron released from ferritin can lead to extensive lipid peroxidation and aggravate neurological damage. NRF2/HO-1 pathway is to endow cells with a protective effect against oxidative stress, and it plays an important role in the transcriptional activation of a series of antioxidant and detoxification genes. UAMC-3203 is a ferrostatin-1(Fer-1) analogue with better solubility and stability, which can more effectively inhibit ferroptosis after SCI. A rat SCI model was constructed, and the recovery of motor function was observed after treatment with UAMC-3203. ELISA was employed to assess the impact of UAMC-3203 on inflammation-related factors, while immunofluorescence was utilized to investigate the influence of UAMC-3203 on neuronal count as well as the activation of astrocytes and microglia/macrophages. Malondialdehyde (MDA) were detected to reflect the level of oxidation products. Western blot analysis was used to measure the level of ferroptosis markers and the expression of NRF2/HO-1. Our findings demonstrate that UAMC-3203 inhibits the production of reactive oxygen species (ROS) and lipid peroxides, preventing ferroptosis and reducing neuronal degeneration. Additionally, UAMC-3203 suppresses astrocyte proliferation and microglia/macrophage activation, as well as the release of ferroptosis-related inflammatory factors. These combined effects contribute to the preservation of spinal cord tissue and the facilitation of motor function recovery. UAMC-3203 maybe inhibit ferroptosis after SCI to promote functional recovery.

Neuroprotective effects of mesenchymal stromal cells in mouse models of Alzheimer’s Disease: The Mediating role of gut microbes and their metabolites via the Microbiome-Gut-Brain axis

The intricacy and multifaceted nature of Alzheimer’s disease (AD) necessitate therapies that target multiple aspects of the disease. Mesenchymal stromal cells (MSCs) emerge as potential agents to mitigate AD symptoms; however, whether their therapeutic efficacy involves modulation of gut microbiota and the microbiome-gut-brain axis (MGBA) remains unexplored. In this study, we evaluated the effects of three distinct MSCs types—derived from the umbilical cord (UCMSC), dental pulp (SHED), and adipose tissue (ADSC)—in an APP/PS1 mouse model of AD. In comparison to saline control, MSCs administration resulted in a significant reduction of behavioral disturbances, amyloid plaques, and phosphorylated tau in the hippocampus and frontal cortex, accompanied by an increase in neuronal count and Nissl body density across AD-afflicted brain regions. Through 16S rRNA gene sequencing, we identified partial restoration of gut microbial balance in AD mice post-MSCs treatment, evidenced by the elevation of neuroprotective Akkermansia and reduction of the AD-associated Sphingomonas. To examine whether gut microbiota involved in MSCs efficacy in treating AD, SHED with better anti-inflammatory and gut microbiota recovery effects among three MSCs, and another AD model 5 × FAD mice with earlier and more pathological proteins in brain than APP/PS1, were selected for further studies. Antibiotic-mediated gut microbial inactivation attenuated MSCs efficacy in 5 × FAD mice, implicating the involvement of gut microbiota in the therapeutic mechanism. Functional analysis of altered gut microbiota and targeted bile acid metabolism profiling revealed a significant enhancement in bile acid variety following MSCs therapy. A chief bile acid constituent, taurocholic acid (TCA), was orally administered to AD mice and similarly abated AD symptoms. Nonetheless, the disruption of intestinal neuronal integrity with enterotoxin abrogated the ameliorative impact of both MSCs and TCA treatments. Collectively, our findings substantiate that MSCs confer therapeutic benefits in AD within a paradigm that primarily involves regulation of gut microbiota and their metabolites through the MGBA.

Assessment of nebivolol efficacy in experimental models of toxoplasmosis: insights into parasite burden reduction and neuronal protection.

This study investigates the efficacy of nebivolol (NBV) in experimental models of toxoplasmosis, focusing on parasite burden reduction and neuronal protection. In the acute model of experimental toxoplasmosis, Swiss mice infected with RH strain tachyzoites received oral NBV chlorhydrate doses of 2mg/kg/day and 4mg/kg/day for 8days. Treatment with NBV significantly reduced parasite burden compared to vehicle and standard drug (PYR) groups. In the chronic model of experimental toxoplasmosis, C57/BL6 mice infected with the ME49 strain received NBV chlorhydrate 41days post-infection and were evaluated after 10days of treatment. NBV chlorhydrate effectively reduced cyst number and area, as well as bradyzoite burden compared to controls. Histological analysis demonstrated that NBV chlorhydrate preserved neuronal count, with the 4mg/kg/day dose yielding counts similar to non-infected mice. Statistical analysis confirmed significant differences compared to control groups. Furthermore, immunohistochemical analysis revealed a significant reduction in iNOS labeling in the brains of mice treated with NBV chlorhydrate, indicating a decrease in nitric oxide production compared to control groups. These findings suggest NBV's potential as a promising candidate for toxoplasmosis treatment, highlighting its ability to reduce parasite burden and protect neuronal integrity. Further research is warranted to elucidate NBV's mechanisms of action and its clinical application in managing toxoplasmosis.

Stack performance classification and fault diagnosis optimization of solid oxide fuel cell system based on bayesian artificial neural network and feature selection

Solid oxide fuel cell (SOFC) has attracted much attention because of its high efficiency and silent power generation, and can be applied to the field of fuel cell-powered unmanned boats. However, a fuel deficit failure in the system can lead to reduced stack performance, reducing the reliability of SOFC applications in the field of unmanned boats. Therefore, this paper proposes an efficient breakdown diagnosis model for SOFC system fault diagnosis. Firstly, Bayesian artificial neural network is constructed by using the best feature data subset after Relief-F combined with minimum Redundancy Maximum Relevance algorithm feature selecting. Secondly, the correct diagnosis rate under different number of optimal features is calculated, and the best feature combinations are combined to verify. Finally, the particle swarm algorithm selects the optimal hidden neuron count to optimization model. Experimental findings suggest that for correct diagnosis rate, the breakdown diagnosis model based on the optimal number of 3 features can reduce the training time and maintain high accuracy compared with the use of all 34 features. This research result provides a feasible way for the fault diagnosis application of SOFC system power generation in the field of unmanned boats.

Repetitive magnetic stimulation prevents dorsal root ganglion neuron death and enhances nerve regeneration in a sciatic nerve injury rat model

Peripheral nerve injury (PNI) often leads to retrograde cell death in the spinal cord and dorsal root ganglia (DRG), hindering nerve regeneration and functional recovery. Repetitive magnetic stimulation (rMS) promotes nerve regeneration following PNI. Therefore, this study aimed to investigate the effects of rMS on post-injury neuronal death and nerve regeneration. Seventy-two rats underwent autologous sciatic nerve grafting and were divided into two groups: the rMS group, which received rMS and the control (CON) group, which received no treatment. Motor neuron, DRG neuron, and caspase-3 positive DRG neuron counts, as well as DRG mRNA expression analyses, were conducted at 1-, 4-, and 8-weeks post-injury. Functional and axon regeneration analyses were performed at 8-weeks post-injury. The CON group demonstrated a decreased DRG neuron count starting from 1 week post-injury, whereas the rMS group exhibited significantly higher DRG neuron counts at 1- and 4-weeks post-injury. At 8-weeks post-injury, the rMS group demonstrated a significantly greater myelinated nerve fiber density in autografted nerves. Furthermore, functional analysis showed significant improvements in latency and toe angle in the rMS group. Overall, these results suggest that rMS can prevent DRG neuron death and enhance nerve regeneration and motor function recovery after PNI.

Timing of SMN replacement therapies in mouse models of spinal muscular atrophy: a systematic review and meta-analysis.

Mutations in the Survival of Motor Neuron 1 gene lead to a loss of survival motor neuron protein in patients with spinal muscular atrophy. Revolutionary advances in gene therapy have led to survival motor neuron-replacement therapies that significantly prolong life expectancy and improve neuromuscular function. However, accumulating evidence suggests that the timing of survival motor neuron-replacement therapies is a critical determinant of success. We performed a systematic review and meta-analysis of all pre-clinical studies testing survival motor neuron replacement therapies in mouse models of spinal muscular atrophy to assess the impact of timing of delivery on therapeutic effectiveness. We incorporated four databases in this pre-registered study (PROSPERO 2020 CRD42020200180): EMBASE, PubMed, Scopus and Web of Science. Inclusion criteria were; primary research article, a measure of survival analysis, use of survival motor neuron mouse model and evaluation of survival motor neuron-targeting therapy. Exclusion criteria included; use of therapies not known to directly target survival motor neuron, genetic manipulations and/or lack of appropriate controls. We screened papers using the SyRF platform. The main outcome we assessed was survival in treated groups compared to untreated groups. We performed meta-analysis of survival using median survival ratio and the random effects model and measured heterogeneity using the I 2 statistic. Subgroup analyses were performed to assess treatment efficacy based on timing of intervention (embryonic delivery, day of birth, postnatal day 2 and postnatal day 3 or later) and treatment type. If detailed in the studies, body weight compared to untreated spinal muscular atrophy models and motor neuron number were included as secondary outcomes for meta-analysis. 3469 studies were initially identified, with 78 ultimately included. Survival motor neuron-replacement therapies significantly affected survival in favour of treatment by a factor of 1.20 (95% CI 1.10-1.30, P < 0.001) with high heterogeneity (I 2 = 95%). Timing of treatment was a significant source of heterogeneity (P < 0.01), with earlier treatment having a greater impact on survival. When stratified by type of treatment, earlier treatment continued to have the strongest effect with viral vector replacement therapy and antisense oligonucleotide therapy. Secondary outcome measures of body weight and spinal motor neuron counts were also positively associated with early treatment. Earlier delivery of survival motor neuron replacement therapies is therefore a key determinant of treatment efficacy in spinal muscular atrophy.

Utility of melatonin on brain injury, synaptic transmission, and energy metabolism in rats with sepsis.

Melatonin is a powerful endogenous antioxidant hormone. Its healing effects on energy balance and neuronal damage associated with oxidative metabolism disorders have been reported in pathologic conditions. We aimed to determinate the utility of melatonin on neuronal damage, synaptic transmission, and energy balance in the brain tissue of rats with sepsis induced with LPS. Rats was divided into four groups such as control, LPS (20mg/kg i.p.), melatonin (10mg/kg i.p. × 3), and LPS + Melatonin (LPS + Mel). After 6h from the first injection, rats were decapitated, and also tissue and serum samples were taken. Lipid peroxidation and neuron-specific enolase (NSE) levels were determined from the serum in all group. High energy compounds, creatine, and creatine phosphate are measured by HPLC methods from the homogenized tissue. Counts of living neurons are marked with NeuN (neuronal nuclei), degenerated neurons are marked with S100-ß and synaptic vesicles transmission is analyzed with synaptophysin antibodies immunoreactivities. One-way ANOVA and post hoc Tukey tests were used to statistical analysis. In LPS group, AMP, ATP, creatine, and creatine phosphate levels were significantly decreased (p < 0.05), and also ADP levels were significantly increased compared with the other groups (p < 0.01). Living neurons counts were significantly decreased in LPS (p < 0.01), melatonin, and LPS + Melatonin (p < 0.05) groups compared with control. Degenerated neurons counts were increased in LPS group compared with control (p < 0.01) and also decreased in both of melatonin and LPS + Melatonin groups (p < 0.01). Synaptophysin immunoreactivity was decreased in LPS group compared with the other groups (p < 0.05). We observed that melatonin administration prevents neuronal damage, regulates energy metabolism, and protects synaptic vesicle proteins from sepsis-induced reduction.