Neuronal Counts Research Articles

Drop-off in axonal regeneration along the length of a cross-face nerve graft: An experimental study in rats.

The average nerve graft length utilized in cross-face nerve grafting for reconstruction of facial nerve palsy is 20-22 cm. While the graft length is thought to be one of the greatest determinants of muscle strength, the mechanism through which this happens remains unknown. We studied changes in axonal regeneration along the length of a 2 cm cross-face nerve graft in a rat model. The hypothesis was that axon count would decrease along the length of the graft. A 2 cm nerve graft (sciatic nerve) was used as a cross-face nerve graft in 16 adult female, 210-250 g, Sprague Dawley rats. Thirteen weeks later, 5 mm nerve biopsies were taken at four sites: the facial nerve trunk (control), proximal graft, midpoint of graft (1 cm distal to coaptation) and distal graft (2 cm distal to coaptation). Retrograde nerve labeling with FluoroGold was performed at the biopsied nerve site and the facial motor nucleus was taken 1 week later. Microscopic imaging and manual counting of axons and labeled motor nuclei was performed. Retrograde-labeled motor neuron counts were decreased at the midway point of the graft compared to the facial trunk (1517 ± 335 axons, Δ% = 92.5, p = .01) and even further decreased at the distal end of the graft (269 ± 293 axons, Δ% = 175.5, p = .006). Analysis of the nerve biopsies demonstrated no significant differences in myelinated axon count between the nerve trunk and over the length of the nerve graft (range 6207-7179 axons, Δ% = 14.5, p = .07). In a rat model, the number of regenerating motor neurons drops off along the length of the graft and axon count is preserved due to axon sprouting. How this pattern correlates to ultimate muscle strength remains unknown, but this study provides insight into why shorter grafts may afford better outcomes.

Locus coeruleus ablation in mice: protocol optimization, stereology and behavioral impact.

The Locus Coeruleus (LC) is in the brainstem and supplies key brain structures with noradrenaline, including the forebrain and hippocampus. The LC impacts specific behaviors such as anxiety, fear, and motivation, as well as physiological phenomena that impact brain functions in general, including sleep, blood flow regulation, and capillary permeability. Nevertheless, the short- and long-term consequences of LC dysfunction remain unclear. The LC is among the brain structures first affected in patients suffering from neurodegenerative diseases such as Parkinson's disease and Alzheimer's Disease, hinting that LC dysfunction may play a central role in disease development and progression. Animal models with modified or disrupted LC function are essential to further our understanding of LC function in the normal brain, the consequences of LC dysfunction, and its putative roles in disease development. For this, well-characterized animal models of LC dysfunction are needed. Here, we establish the optimal dose of selective neurotoxin N-(2-chloroethyl)-N-ethyl-bromo-benzylamine (DSP-4) for LC ablation. Using histology and stereology, we compare LC volume and neuron number in LC ablated (LCA) mice and controls to assess the efficacy of LC ablation with different numbers of DSP-4 injections. All LCA groups show a consistent decrease in LC cell count and LC volume. We then proceed to characterize the behavior of LCA mice using a light-dark box test, Barnes maze test, and non-invasive sleep-wakefulness monitoring. Behaviorally, LCA mice differ subtly from control mice, with LCA mice generally being more curious and less anxious compared to controls consistent with known LC function and projections. We note an interesting contrast in that control mice have varying LC size and neuron count but consistent behavior whereas LCA mice (as expected) have consistently sized LC but erratic behavior. Our study provides a thorough characterization of an LC ablation model, firmly consolidating it as a valid model system for the study of LC dysfunction.

Immature neurons in the primate amygdala: Changes with early development and disrupted early environment

In human and nonhuman primates, the amygdala paralaminar nucleus (PL) contains immature neurons. To explore the PL’s potential for cellular growth during development, we compared PL neurons in (1) infant and adolescent macaques (control, maternally-reared), and in (2) infant macaques that experienced separation from their mother in the first month of life compared to control maternally-reared infants. In maternally-reared animals, the adolescent PL had fewer immature neurons, more mature neurons, and larger immature soma volumes compared to infant PL. There were also fewer total neurons (immature plus mature) in adolescent versus infant PL, suggesting that some neurons move out of the PL by adolescence. Maternal separation did not change mean immature or mature neuron counts in infant PL. However, across all infant animals, immature neuron soma volume was strongly correlated with mature neuron counts. TBR1 mRNA, a transcript required for glutamatergic neuron maturation, is significantly reduced in the maternally-separated infant PL (DeCampo et al., 2017), and was also positively correlated with mature neuron counts in infant PL. We conclude that immature neurons gradually mature by adolescence, and that the stress of maternal separation may shift this trajectory, as revealed by correlations between TBR1 mRNA and mature neuron numbers across animals.

Impact of Maternal Ketogenic Diet on NLRP3 Inflammasome Response in the Offspring Brain.

The effects of maternal diet on the neuroimmune responses of the offspring remain to be elucidated. We investigated the impact of maternal ketogenic diet (KD) on the NLRP3 inflammasome response in the offspring's brain. C57BL/6 female mice were randomly allocated into standard diet (SD) and ketogenic diet (KD) groups for 30 days. After mating, the presence of sperm in the vaginal smear was considered day 0 of pregnancy, and female mice continued their respective diets during pregnancy and the lactation period. Following birth, pups were further allocated into two groups and given either LPS or intraperitoneal saline on postnatal (PN) days 4, 5 and 6; they were sacrificed on PN11 or PN21. Neuronal densities were significantly lower globally in the KD group when compared to the SD group at PN11. Neuronal density in the prefrontal cortex (PFC) and dentate gyrus (DG) regions were also significantly lower in the KD group when compared to the SD group at PN21. Following administration of LPS, the decrease in the neuronal count was more prominent in the SD group when compared to the KD group in the PFC and DG regions at PN11 and PN21. NLRP3 and IL-1β were higher in the KD group than in the SD group at PN21 in the PFC, CA1 and DG regions, and were significantly lower in the DG region of the KD group especially when compared to the SD group following LPS. Results of our study reveal that maternal KD negatively affects the offspring's brain in the mouse model. The effects of KD exhibited regional variations. On the other hand, in the presence of KD exposure, NLRP3 expression after LPS injection was lower in the DG and CA1 areas but not in the PFC when compared to SD group. Further experimental and clinical studies are warranted to elucidate the molecular mechanisms underlying the impact of antenatal KD exposure and regional discrepancies on the developing brain.

Stereology neuron counts correlate with deep learning estimates in the human hippocampal subregions

Hippocampal subregions differ in specialization and vulnerability to cell death. Neuron death and hippocampal atrophy have been a marker for the progression of Alzheimer’s disease. Relatively few studies have examined neuronal loss in the human brain using stereology. We characterize an automated high-throughput deep learning pipeline to segment hippocampal pyramidal neurons, generate pyramidal neuron estimates within the human hippocampal subfields, and relate our results to stereology neuron counts. Based on seven cases and 168 partitions, we vet deep learning parameters to segment hippocampal pyramidal neurons from the background using the open-source CellPose algorithm, and show the automated removal of false-positive segmentations. There was no difference in Dice scores between neurons segmented by the deep learning pipeline and manual segmentations (Independent Samples t-Test: t(28) = 0.33, p = 0.742). Deep-learning neuron estimates strongly correlate with manual stereological counts per subregion (Spearman’s correlation (n = 9): r(7) = 0.97, p < 0.001), and for each partition individually (Spearman’s correlation (n = 168): r(166) = 0.90, p <0 .001). The high-throughput deep-learning pipeline provides validation to existing standards. This deep learning approach may benefit future studies in tracking baseline and resilient healthy aging to the earliest disease progression.

Faults detection, location, and classification of the elements in the power system using intelligent algorithm

This study proposes an intelligent protection relay design that uses artificial neural networks to secure electrical parts in power infrastructure from different faults. Electrical transformer and transmission lines are protected using intelligent differential and distance relay, respectively. Faults are categorized, and their locations are pinpointed using three-phase current values and zero-current characteristics to differentiate between non-earth and ground faults. The optimal aspects of the artificial neural network were chosen for optimal results with the least possible error. Levenberg-Marquardt was established as the ideal training technique for the suggested system comprising the differential relay. Levenberg-Marquardt was the optimal training technique for the proposed framework consisting of the differential relay. Fault detection and categorization were performed using 20 and 50 hidden layers, and the corresponding error rates were 9.9873e-3 and 1.1953e-29. In the context of fault detection by the distance relay, the hidden layer neuron counts were 400, 250, and 300 for fault detection, categorization, and location; training error rates were 7.8761e-2, 1.2063e-6, and 1.1616e-26, respectively.

Atorvastatin Improves the Propionic Acid-Induced Autism in Rats: The Roles of Sphingosine-1-Phosphate and Anti-inflammatory Action.

Purpose The aim of this study is to investigate the benefits of atorvastatin on the propionic acid-induced autism model via increasingsphingosine-1-phosphate and anti-inflammatory actions with imaging andbrain tissue investigations. Materials and methods Twenty-five mg/kg/day/rat of propionic acid (PPA) was administered intraperitoneally to 20 male Wistar rats, and 10 male Wistar rats were fed orally. Study groups were designed as follows: Group 1: Control Group (orally fed control, n=10); Group 2 (PPA+saline, n=10); Group 3 (PPA+Atorvastatin, n=10). The brain biochemical and histopathology assessments andmagnetic resonance (MR) imaging were conducted across groups in order to compare them. Results The PPA+Atorvastatingroup was found to have significantly lowerlevels ofbrain malondialdehyde,IL-2level, IL-17, tumor necrosis factor-alpha (TNF-α),and lactate compared to the PPA+saline group.The PPA+Atorvastatingroup had higher levels of nerve growth factor and nuclear factor erythroid 2-related factor 2 (NRF-2)and sphingosine-1-phosphate. In histopathology assessments, the PPA+Atorvastatingroup was found to have significantly higher neuronal counts of CA1 andCA2 in the hippocampus, and Purkinje cells in the cerebellum. Conclusions Current findings suggest that atorvastatin increases sphingosine-1-phosphate levels and decreases inflammatory actions which characterize the autism rodent model implemented in this study.These preliminary results have to be confirmed byfurther experimental and clinical studies.

Estimation and analysis of missing temperature data in high altitude and snow-dominated regions using various machine learning methods.

Considering the importance of limited natural resources, accurately recording and evaluating temperature data is critical. The daily average temperature values obtained for the years 2019-2021 of eight highly correlated meteorological stations, characterized by mountainous and cold climate features in the northeast of Turkey, were analyzed by an artificial neural network (ANN), support vector regression (SVR), and regression tree (RT) methods. Output values produced by different machine learning methods compared with different statistical evaluation criteria and the Taylor diagram. ANN6, ANN12, medium gaussian SVR, and linear SVR were chosen as the most suitable methods, especially due to their success in estimating data at high (> 15 ℃) and low (< 0 ℃) temperatures. All the methodologies and network architectures used produced successful results (NSE-R2 > 0.90). Some deviations have been observed in the estimation results due to the decrease in the amount of heat emitted from the ground due to fresh snow, especially in the -1 ~ 5℃ range, where snowfall begins, in the mountainous areas characterized by heavy snowfall. In models with low neuron numbers (ANN1,2,3) in ANN architecture, the increase in the number of layers does not affect the results. However, the increase in the number of layers in models with high neuron counts positively affects the accuracy of the estimation.

A hybrid model for metro passengers flow prediction

In this paper, a novel ensemble learning model named EWT-EnsemLSTM-SSA, which assembles long short-term memory (LSTM), support vector regression (SVR), and sparrow search algorithm (SSA), is a proposed to deal with long term metro passenger flow volume prediction, which is an essential content of traffic flow prediction problems. Firstly, the empirical wavelet transform (EWT) method is introduced to decompose the original dataset into five wavelet time-sequence data for further prediction. Then, a cluster of LSTMs with diverse hidden layers and neuron counts are employed to explore and exploit the implicit information of the EWT-decomposed signals. Next, the output of LSTMs is aggregated into a nonlinear regression method SVR. Lastly, SSA is utilized to optimize the SVR automatically. The proposed EWT-EnsemLSTM-SSA model is applied in three case studies, using the data collected from the passengers’ amount in the Minneapolis, America metro, divided into one hour in one day. Experiment results, which compare the proposed EnsemLSTM-SSA model with five conventional time series forecasting models, show that the proposed model can achieve a better performance than the traditional prediction algorithms.

Increased Brain-Derived Neurotrophic Factor and Hippocampal Dendritic Spine Density Are Associated with the Rapid Antidepressant-like Effect of Iron-citalopram and Iron-Imipramine Combinations in Mice

Iron supplementation previously demonstrated antidepressant-like effects in post-partum rats. The present study evaluates the possible synergistic antidepressant effect of sub-therapeutic dose of iron co-administered with citalopram or imipramine in female Institute of Cancer Research mice. Depression-like symptoms were induced in the forced swim (FST), tail suspension (TST), and open space swim (OSST) tests while open field test (OFT) was used to assess locomotor activity. Mice (n = 8) received iron (0.8–7.2 mg/kg), citalopram (3–30 mg/kg), imipramine (3–30 mg/kg), desferrioxamine (50 mg/kg) or saline in the single treatment phase of each model and subsequently a sub-therapeutic dose of iron co-administered with citalopram or imipramine. Assessment of serum brain derived neurotrophic factor (BDNF) and dendritic spine density was done using ELISA and Golgi staining techniques respectively. Iron, citalopram and imipramine, unlike desferrioxamine, reduced immobility score in the TST, FST and OSST without affecting locomotor activity, suggesting antidepressant-like effect. Sub-therapeutic dose of iron in combination with citalopram or imipramine further enhanced the antidepressant-like effect, producing a more rapid effect when compared to the iron, citalopram or imipramine alone. Iron, citalopram and imipramine or their combinations increased serum BDNF concentration, hippocampal neuronal count and dendritic spine densities. Our study provides experimental evidence that iron has antidepressant-like effect and sub-therapeutic dose of iron combined with citalopram or imipramine produces more rapid antidepressant-like effect. We further show that iron alone or its combination with citalopram or imipramine attenuates the neuronal loss associated with depressive conditions, increases dendritic spines density and BDNF levels. These finding suggest iron-induced neuronal plasticity in the mice brain.

Tissue stretching is a confounding factor for the evaluation of neurodegeneration in the fast-ageing killifish.

The fast-ageing killifish has gained increasing attention as a promising gerontology model to study age-related processes and neurodegeneration. Interestingly, it is the first vertebrate model organism that shows physiological neuron loss at old age in its central nervous system (CNS), including its brain and retina. However, the fact that the killifish brain and retina are ever-growing tissues complicates studying neurodegenerative events in aged fish. Indeed, recent studies showed that the method of tissue sampling, either using sections or whole-organs, has a large effect on the observed cell densities in the fast-expanding CNS. Here, we elaborated on how these two sampling methods affect neuronal counts in the senescent retina and how this tissue grows upon ageing. Analysis of the different retinal layers in cryosections revealed age-dependent reduction in cellular density but evaluation of whole-mount retinas did not detect any neuron loss, as a result of an extremely fast retinal expansion with age. Using BrdU pulse-chase experiments, we showed that the young adult killifish retina mainly grows by cell addition. However, with increasing age, the neurogenic potency of the retina declines while the tissue keeps on growing. Further histological analyses revealed tissue stretching, including cell size increase, as the main driver of retinal growth at old age. Indeed, both cell size and inter-neuronal distance augment with ageing, thereby decreasing neuronal density. All in all, our findings urge the 'ageing science' community to consider cell quantification bias and employ tissue-wide counting methods to reliably quantify neuronal numbers in this unique gerontology model.

Blood pressure-related white matter microstructural disintegrity and associated cognitive function impairment in asymptomatic adults

Background and objectivesWe aimed to investigate the white matter (WM) microstructural/cytostructural disintegrity patterns related to higher systolic blood pressure (SBP), and whether they mediate SBP effects on cognitive performance in...

Successful retrograde regeneration using a sensory branch for motor nerve transfer.

The objective of this study was to test whether regenerating motor axons from a donor nerve can travel in a retrograde fashion using sensory branches to successfully reinnervate a motor nerve end organ. This study has two parts. In part I, rats (n = 30) were assigned to one of five groups for obturator nerve (ON)-to-femoral nerve transfer: group 1, ON-to-saphenous nerve (SN) distal stump; group 2, ON-to-SN proximal stump without femoral nerve proper (FNP) injury; group 3, ON-to-SN proximal stump with FNP crush injury; group 4, ON-to-SN proximal stump with FNP transection injury; and group 5, gold standard transfer, ON-to-motor femoral nerve (MFN) branch. At 8 weeks, retrograde labeling was done from the distal MFN, and the spinal cords were examined to assess the degree of obturator motor axon regeneration across the five groups. In part II, only group 4 was examined (n = 8). Through use of immunostaining and optical tissue clearing methods, the nerve transfer networks were cleared and imaged using light-sheet fluorescence microscopy to visualize the regeneration pathways in 2D and 3D models at 2- and 8-week time points. Proximal FNP transection (group 4) enabled a significantly higher number of retrogradely regenerated motor axons compared with control groups 1-3. Moreover, group 4 had modest, but nonsignificant, superiority of motor neuron counts compared with the positive control group, group 5. Optical tissue clearing demonstrated that the axons traveled in a retrograde fashion from the recipient sensory branch to the FNP mixed stump, then through complex turns, down to distal branches. Immunostaining confirmed the tissue clearing findings and suggested perineurium disruption as a means by which axons could traverse across fascicular boundaries. Sensory branches can transmit regenerating axons from donor nerves back to main mixed recipient nerves, then distally toward target organs. The extent of retrograde regeneration is markedly influenced by the type and severity of injury sustained by the recipient nerve. Using a sensory branch as a bridge for retrogradely regenerating axons can open new potential horizons in nerve repair surgery for severely injured mixed nerves.

Predicting main engine power and emissions for container, cargo, and tanker ships with artificial neural network analysis

The most significant aspect of international shipping is sea transportation, and the developments to be made in maritime transport will inspire and predict all other fields. Therefore, determining a ship’s main engine power has great importance in terms of both energy efficiency and environmental factors. The maritime transport and shipping industry has currently begun to understand the importance of artificial intelligence technology. This study uses an artificial neural network (ANN) model to predict the main engine power and pollutant emissions of container, cargo, and tanker ships over 14 parameters: maximum speed, average speed, breadth, year built, ship type, status, length overall (LOA), light displacement, summer displacement, fuel type, deadweight tonnage (DWT), gross tonnage, engine cylinder size, and engine stroke length. In order to provide accurate results, the ANN analysis was trained with data from 3,020 ships, which is quite high compared to the studies in the literature. Many ANN models have been developed and compared to achieve minimal errors and highest accuracy in the results. The regression values, which involve the training, validation, and test values for the different ship types, were obtained as 0.99773 for container ships, 0.98964 for cargo ships, and 0.97755 for tanker ships, with a value of 0.97189 for all ships. The ANN structure was tested using many variations for hidden neuron counts, with the ANN analysis made with 30 neurons obtaining the best results. The ANN analysis results were compared with real values, which showed that very accurate results had been obtained according to the mean squared error (MSE), regression, and mean absolute percentage error (MAPE) results. The MSE value had exceeded 20,000 in the two-input ANN model, but decreased to 0.03, 0.081, and 0.13 with the 14-input model for container, cargo, and tanker ships, respectively. In order to make accurate predictions with maximum precision in the ANN analyses, the study attempted to use different values for the numbers of hidden neurons and inputs and then presented the performance results. The developed model can be used in future studies to be done on fuel consumption and energy efficiency for ships in maritime transport.

Neuroprotective effects of Apis dorsata forest honey on the neurons count in cerebrum and cerebellum of mice (Mus musculus) exposed to monosodium glutamate

Introduction: Monosodium glutamate or MSG can have an effect on increasing the production of reactive oxygen species (ROS) in the brain. Apis dorsata forest honey is known to have higher antioxidant activity than Apis mellifera and Apis cerana honey. This study aims to determine the preventive effect of Apis dorsata honey on the number of pyramidal cerebrum neurons and purkinje cerebellum neurons of mice (Mus musculus) exposed to monosodium glutamate (MSG). Material and Methods: This study used 25 mice which were divided into 5 groups. In the K- group only aquadest was given. The K+ group was given 4mg/gBB of MSG. Groups P1, P2, and P3 given Apis dorsata honey at a dose of 53.82mg/20gBW, 107.64mg/20gBW, and 161.46mg/20gBW. All treatments were carried out orally for 52 days. Results: The results showed that the average number of cerebral pyramidal neurons in the K-, K+, P1, P2, and P3 groups was 12.24±0.607; 7.24±2.875; 12.48±1.513; 15.72±0.944; and 19.28±2.827. The mean number of purkinje cerebellar neurons was 4.8±1.456; 2.08±0.807; 3.08±1.035; 3.56±0.434; and 4.68±1.390. Discussion: The average number of pyramidal neurons and purkinje neurons in the group given preventive dose of Apis dorsata honey and exposed to MSG was higher and there is a significant difference compared to the group that was only exposed to MSG. It can be concluded that the administration of Apis dorsata honey can maintain the number of pyramidal cerebrum neurons and purkinje cerebellar neurons in mice exposed to MSG.

Does lithium poisoning induce brain injuries?-A histopathological rat study.

Due to a narrow therapeutic index, prolonged lithium treatment and overdose may result in neurotoxicity. Neurotoxicity is deemed reversible with lithium clearance. However, echoing the report of syndrome of irreversible lithium-effectuated neurotoxicity (SILENT) in rare severe poisonings, lithium-induced histopathological brain injuries including extensive neuronal vacuolization, spongiosis and ageing-like neurodegenerative changes were described in the rat following acute toxic and pharmacological exposure. We aimed to investigate the histopathological consequences of lithium exposure in rat models mimicking prolonged treatment and all three patterns of acute, acute-on-chronic and chronic poisonings observed in humans. We performed histopathology and immunostaining-based analyses using optic microscopy of brains obtained from male Sprague-Dawley rats randomly assigned to lithium or saline (controls) and treated according to the therapeutic or to the three poisoning models. No lesion was observed in any brain structure in any of the models. Neuron and astrocyte counts did not differ significantly between lithium-treated rats and controls. Our findings support that lithium-induced neurotoxicity is reversible and brain injury not a common feature of toxicity.

PINK1 deficiency with Ca2+ changes in the hippocampus exacerbates septic encephalopathy in mice

PTEN-induced putative kinase 1 (PINK1) is a mitochondrial kinase that protects against oxidative stress-induced cellular death. PINK1 deletion, on the other hand, disrupts mitochondrial calcium (Ca2+) homeostasis in various brain disorders. This study looked at how PINK1 affects hippocampal intracellular Ca2+ changes in mice with septic encephalopathy. Mice were injected intraperitoneally with lipopolysaccharide (LPS, 5 mg/kg) to induce septic encephalopathy; then, fiber photometry was used to record hippocampal Ca2+ transients during behavioral tests in freely moving mice. Basal cytoplasmic Ca2+ levels were detected under a fluorescent microscope. LPS induced PINK1 expression and neuronal loss in the hippocampus of mice, whereas no difference in neuronal counts was shown between PINK1 knockout LPS mice and WT LPS mice. PINK1 deficiency led to inhibited Ca2+ transients and increased intracellular Ca2+ levels in the hippocampus of mice, thus, significantly aggravating the cognitive dysfunction in septic mice. An analysis of Parkin and PLC-γ1, downstream effectors of PINK1, showed that they are associated with the effects of PINK1. These results demonstrate that PINK1 deficiency disrupts intracellular Ca2+ homeostasis and exacerbates septic encephalopathy. This observation suggests a protective role of PINK1 in septic encephalopathy.

Extracellular Vesicles Derived from Bone Mesenchymal Stem Cells Carrying circ_0000075 Relieves Cerebral Ischemic Injury by Competitively Inhibiting miR-218-5p and Up-regulating E3 Ubiquitin Ligase SMURF2.

Extracellular vesicle (EV)-encapsulated circRNAs have the potential role in affecting brain disorders. However, the role of circ_0000075 in cerebral ischemic injury remains unclear. Here, we tried to investigate the mechanism of bone marrow mesenchymal stem cell (BMSC)-derived EVs carrying circ_0000075 in the control of cerebral ischemic injury. Initially, a mouse model with cerebral ischemic injury was induced by middle cerebral artery occlusion (MCAO), followed by the determination of circ_0000075 expression. Then, neurons were isolated and subjected to oxygen-glucose deprivation/reperfusion. BMSCs were isolated for extraction of EVs. The correlation among circ_0000075, microRNA (miR)-218-5p, and Smad ubiquitination regulatory factor 2 (SMURF2) was detected with their roles in cerebral ischemic injury analyzed in vivo and in vitro. circ_0000075 was down-regulated in MCAO mice and engineered RVG-EVs were internalized by neurons to up-regulate circ_0000075 expression. Treatment of RVG-circ_0000075-EVs reduced brain tissue damage, increased neuronal count, and significantly curtailed apoptosis rate, suppressing cerebral ischemic injury in vitro and in vivo. miR-218-5p was targeted by circ_0000075 in neurons, which promoted SMURF2 expression. A negative correlation between SMURF2 and transcriptional regulator Yin Yang 1 (YY1) was identified. In vitro experiments further proved that circ_ 00,000 75 could down-regulate the expression of YY1 through SMURF2, and finally relieving cerebral ischemic injury. Collectively, engineered EVs delivered circ_0000075 into brain tissues and increased circ_0000075 expression, which down-regulated miR-218-5p and up-regulated SMURF2, thus alleviating cerebral ischemic injury.

Transient dystonia correlates with parkinsonism after 1-methyl-4-phenyl-1,2,3,6- tetrahydropyridine in nonhuman primates.

Unilateral internal carotid artery 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) infusion in non-human primates produces transient contralateral hemi-dystonia followed by stable contralateral hemi-parkinsonism; the relationship between dystonia and parkinsonism remains unclear. We hypothesized that transient dystonia severity following MPTP correlates with parkinsonism severity. In male Macaca nemestrina (n = 3) and M. fascicularis (n = 17) we administered unilateral intra-carotid MPTP, then correlated validated blinded ratings of transient peak dystonia and delayed parkinsonism. We also correlated dystonia severity with post-mortem measures of residual striatal dopamine and nigral neuron counts obtained a mean 53 ± 15 days following MPTP, after resolution of dystonia but during stable parkinsonism. Median latency to dystonia onset was 1 day, and peak severity 2.5 days after MPTP; total dystonia duration was 13.5 days. Parkinsonism peaked a median of 19.5 days after MPTP, remaining nearly constant thereafter. Peak dystonia severity highly correlated with parkinsonism severity (r[18] = 0.82, p < 0.001). Residual cell counts in lesioned nigra correlated linearly with peak dystonia scores (r[18] = -0.68, p=<0.001). Dystonia was not observed in monkeys without striatal dopamine depletion (n = 2); dystonia severity correlated with striatal dopamine depletion when residual nigral cell loss was less than 50% ([11] r = -0.83, p < 0.001) but spanned a broad range with near complete striatal dopamine depletion, when nigral cell loss was greater than 50%. Our data indicate that residual striatal dopamine may not reflect dystonia severity. We speculate on mechanisms of transient dystonia followed by parkinsonism that may be studied using this particular NHP MPTP model to better understand relationships of transient dystonia to nigrostriatal injury and parkinsonism.

Reduced anterior insular cortex volume in male heroin addicts: a postmortem study

We and others have observed reduced volumes of brain regions, including the nucleus accumbens, globus pallidus, hypothalamus, and habenula in opioid addiction. Notably, the insular cortex has been under increasing study in addiction, and a smaller anterior insula has been found in alcohol-addicted cases. Here, we have investigated whether similar effects occur in heroin addicts compared to healthy controls. Volumes of the anterior and posterior insula in heroin addicts (n = 14) and controls (n = 13) were assessed by morphometry of Nissl-myelin-stained serial whole-brain coronal sections. The mean relative volume of the anterior insular cortex was smaller than in non-addicted controls (3010 ± 614 *10–6 versus 3970 ± 1306 *10–6; p = 0.021). However, no significant differences in neuronal cell counts were observed. Therefore, the observed volume reduction appears to be a consequence of damaged connecting structures such as neuropil and glial cells. The findings were not confounded by age or duration of autolysis. Our results provide further evidence of structural deficits in key hubs of the addiction circuitry in heroin-dependent individuals and warrant further research in this area.