Dead Neurons Research Articles

A kinetic scheme to examine the role of glial cells in the pathogenesis of Alzheimer's disease.

Alzheimer's disease (AD) is a complex neurodegenerative disorder that leads to severe impairments in cognitive functions including memory and learning. An improved kinetic model is proposed here to understand the pathogenesis of AD in particular the role of glial cells in the presence of amyloid plaques and neurofibrillary tangles (NFTs). The kinetic model describes the production of activated microglia and astroglia. It involves two rate equations and incorporates the dual role of these glial cells which can function as neuroprotective and as neurotoxic cells. Examination of the steady state solutions of the model predicts an increase in population of these glial cells as (AD) progresses, and that this continues to increase linearly even after the amyloid population has reached a plateau.This is in agreement with experimental data. Limiting AD to the effect of amyloid peptides alone is incorrect and the role of neurofibrillary tangles, clearance rate of dead neurons and neuroinflammation from glial cells are vital and must be included in understanding the pathogenesis of AD. The study shows that increasing the clearance of dead neurons and use of any method to deactivate the glial cells will diminish the progression of AD.

Exposure to Sub-Lethal Doses of Permethrin Is Associated with Neurotoxicity: Changes in Bioenergetics, Redox Markers, Neuroinflammation and Morphology.

Permethrin (PERM) is a member of the class I family of synthetic pyrethroids. Human use has shown that it affects different systems, with wide health dysfunctions. Our aim was to determine bioenergetics, neuroinflammation and morphology changes, as redox markers after subacute exposure to PERM in rats. We used MDA determination, protein carbonyl assay, mitochondrial O2 consumption, expression of pro-inflammatory cytokines and a deep histopathological analysis of the hippocampus. PERM (150 mg/kg and 300 mg/kg body weight/day, o.v.) increased lipoperoxidation and carbonylated proteins in a dose-dependent manner in the brain regions. The activities of antioxidant enzymes glutathione peroxidase, reductase, S-transferase, catalase, and superoxide dismutase showed an increase in all the different brain areas, with dose-dependent effects in the cerebellum. Cytokine profiles (IL-1β, IL-6 and TNF-α) increased in a dose-dependent manner in different brain tissues. Exposure to 150 mg/kg of permethrin induced degenerated and/or dead neurons in the rat hippocampus and induced mitochondrial uncoupling and reduction of oxidative phosphorylation and significantly decreased the respiratory parameters state 3-associated respiration in complex I and II. PERM exposure at low doses induces reactive oxygen species production and imbalance in the enzymatic antioxidant system, increases gene expression of pro-inflammatory interleukins, and could lead to cell damage mediated by mitochondrial functional impairment.

Methylene Blue Protects Against Acute Ethanol-Induced Oxidative Stress and Organ Damage

Ethanol (EtOH) intake is an important global health problem which affects many organs such as the brain, liver and stomach. The aim of the study was to examine the effect of the redox dye methylene blue (MethyB) on oxidative stress and histologic damage to the liver, gastric mucosa, and brain induced high dose ethanol (EtOH). Male rats were treated with EtOH (2 ml/rat, 96%) via intragastric route (for two consecutive days). MethyB (20 or 40 mg/kg, intraperitoneally) was given immediately after EtOH administration. The control group received saline. Rats were euthanized three hours after the last treatment. Brain and liver levels of malondialdehyde (MDA), reduced glutathione (GSH), and paraoxonase-1 (PON-1) as well as brain 5-lipoxygenase (5-LOX) and butyrylcholinesterase (BChE) were determined. Histopathological assessment of brain, liver and gastric damage was done. Results indicated that compared to saline treated animals, EtOH caused significant increase in MDA, along with decreased GSH and PON-1 activity in brain and liver. Additionally, it significantly increased 5-LOX and decreased brain BChE activity. The EtOH group showed the presence of dead and red neurons, and damage of glial cells. The liver exhibited vacuolar degeneration, apoptotic hepatocytes and foci of necrosis. The gastric mucosa showed areas of tissue damage, mucosal atrophy, and loss of normal architecture of glandular cells. The EtOH induced biochemical and histopathological alterations were alleviated after treatment with MethyB at a dose-dependent manner. These results demonstrate that MethyB is able to protect against from acute effects of EtOH on brain, liver and gastric tissue via an antioxidant action. MethyB might be of value in reducing tissue injury in acute EtOH intoxication.

Deep Learning Model for the Inspection of Coffee Bean Defects

The detection of coffee bean defects is the most crucial step prior to bean roasting. Existing defect detection methods used in the specialty coffee bean industry entail manual screening and sorting, require substantial human resources, and are not standardized. To solve these problems, this study developed a deep learning algorithm to detect defects in coffee beans. The results reveal that when the pooling layer was used to enhance features and reduce neural dimensionality, some of the coffee been features were lost or misclassified. Therefore, a novel dimensionality reduction method was adopted to increase the ability of feature extraction. The developed model also overcame the drawbacks of padding causing blurred image boundaries and the dead neurons causing impeding feature propagation. Images of eight types of coffee beans were used to train and test the proposed detection model. The proposed method was verified to reduce the bias when classifying defects in coffee beans. The detection accuracy rate of the proposed model was 95.2%. When the model was only used to detect the presence of defects, the accuracy rate increased to 100%. Thus, the proposed model is highly accurate in coffee bean defect detection in the classification of eight types of coffee beans.

A Highly Stable Two-Photon Ratiometric Fluorescence Probe for Real-Time Biosensing and Imaging of Nitric Oxide in Brain Tissues and Larval Zebrafish

A Highly Stable Two-Photon Ratiometric Fluorescence Probe for Real-Time Biosensing and Imaging of Nitric Oxide in Brain Tissues and Larval Zebrafish

Alzheimer-like cell death after vanadium pentoxide inhalation

Vanadium (V) toxicity depends on its oxidation state; it seems that vanadium pentoxide (V2O5) is the most toxic to the living cells. It has been reported that oral administration induces changes in motor activity and learning; in rats, I.P. administration increases lipid peroxidation levels in the cerebellum and the concentration of free radicals in the hippocampus and cerebellum. Mice that inhaled V2O5 presented a reduced number of tubulin+ in Leydig and Sertoli cells; it has also been reported that inhaled V2O5 induces loss of dendritic spines, necrosis, and hippocampus neuropil alterations; considering the direct consequence of the interaction of V with cytoskeletal components, makes us believe that V2O5 exposure could cause neuronal death in the hippocampus similar to that seen in Alzheimer disease. This work aimed to determine pyramidal hippocampal CA1 cytoskeletal alterations with Bielschowsky stain in rats exposed to V2O5. Male Wistar rats inhaled 0.02 M of V2O5 one h two times a week for two and six months. We found that rats, which inhaled V2O5 reached 56,57% of dead neurons after six months of inhalation; we recognize strong argyrophilic and collapsed somas and typical flame-shaped in all V-exposed rats hippocampus CA1 compared to controls. We also observe somatodendritic distortions. Axons and dendrites displayed thick dark bands replaced by noticeable thickening and nodosities and the cytoskeleton fibrillary proteins' linear traces. Our findings suggest that V2O5 inhalation induces Alzheimer-like cell death with evident cytoskeletal alterations.

Increased exosome secretion in neurons aging in vitro by NPC1-mediated endosomal cholesterol buildup.

As neurons age, they show a decrease in their ability to degrade proteins and membranes. Because undegraded material is a source of toxic products, defects in degradation are associated with reduced cell function and survival. However, there are very few dead neurons in the aging brain, suggesting the action of compensatory mechanisms. We show in this work that ageing neurons in culture show large multivesicular bodies (MVBs) filled with intralumenal vesicles (ILVs) and secrete more small extracellular vesicles than younger neurons. We also show that the high number of ILVs is the consequence of the accumulation of cholesterol in MVBs, which in turn is due to decreased levels of the cholesterol extruding protein NPC1. NPC1 down-regulation is the consequence of a combination of upregulation of the NPC1 repressor microRNA 33, and increased degradation, due to Akt-mTOR targeting of NPC1 to the phagosome. Although releasing more exosomes can be beneficial to old neurons, other cells, neighbouring and distant, can be negatively affected by the waste material they contain.

Real time identification of anomalous events in coastal regions using deep learning techniques

SummaryThe present existing weather prediction systems deployed by weather forecasting agencies predict the anomalous events using numerical simulation models developed based on geophysics and oceanographic theories. The major disadvantage with existing models is that are explicit simulation models. So, we try to build a real time prediction system that will automatically predict the intensity of any marine natural disaster events and alert the authorities to take necessary actions using a satellite and observational real time data set including moored met ocean data. We propose a novel hybrid model which is a combination of Convolutional Neural Network (CNN) and Long Short‐Term Memory (LSTM). The paper analyzes various other models such as Gated Recurrent Unit (GRU), Bidirectional LSTM (Bi‐LSTM) Recurrent Neural Network (RNN), and Extreme Learning Machine. In addition the other standard CNN architectures are also analyzed. Since the residual CNN network is the most effective architecture, the paper proposes a modification of the residual CNN network by combining the residual CNN network with LSTM/GRU RNN network along with a proposed new activation function which was experimentally proved to be more effective than the deep learning community standard activation function ReLU. The proposed new activation function overcomes the dead neuron propagation problem in ReLU activation function and hence the model's accuracy is increased by more than 1%. The proposed CNN + LSTM/GRU model is benchmarked with UCR time series benchmark dataset and it is experimentally seen that the model performs better than all existing algorithms.

DDoS Detection Using a Cloud-Edge Collaboration Method Based on Entropy-Measuring SOM and KD-Tree in SDN

Software-defined networking (SDN) emerges as an innovative network paradigm, which separates the control plane from the data plane to improve the network programmability and flexibility. It is widely applied in the Internet of Things (IoT). However, SDN is vulnerable to DDoS attacks, which can cause network disasters. In order to protect SDN security, a DDoS detection method using cloud-edge collaboration based on Entropy-Measuring Self-organizing Maps and KD-tree (EMSOM-KD) is designed for SDN. Entropy measurement is utilized to select the ideal SOM map and classify SOM neurons considering the limitation of dead and suspicious neurons. EMSOM can detect most flows directly and filter out a few doubtable flows. Then these flows are fine-grained, identified by KD-tree. Due to the limited and precious resources of the controller, parameter computation is performed in the cloud. The edge controller implements DDoS detection by EMSOM-KD. The experiments are conducted to evaluate the performance of the proposed method. The results show that EMSOM-KD has better detection accuracy; moreover, it improves the KD-tree detection efficiency.

Cell Therapy for Stroke: A Mechanistic Analysis.

Cell therapy has been widely recognized as a promising strategy to enhance recovery in stroke survivors. However, despite an abundance of encouraging preclinical data, successful clinical translation remains elusive. As the field continues to advance, it is important to reexamine prior clinical trials in the context of their intended mechanisms, as this can inform future preclinical and translational efforts. In the present work, we review the major clinical trials of cell therapy for stroke and highlight a mechanistic shift between the earliest studies, which aimed to replace dead and damaged neurons, and later ones that focused on exploiting the various neuromodulatory effects afforded by stem cells. We discuss why both mechanisms are worth pursuing and emphasize the means through which cell replacement can still be achieved.

Flaxseed oil (Linum Usitatissimum) attenuates restraint stress-induced depressive-like behavior: Upregulation of neurotrophic factors in CA1 region of hippocampus

Objectives: In this study, we aimed to evaluate the anti-depressant effects of FS oil on the depressive-like behavior following immobility stress in mice.
 Methods: In this study, 32 male mice were divided into four groups: Control group; FS oil group; Model group: The immobility stress (using falcon for 20 day, 6 hours a day) + feeding with normal saline by oral gavage for another 20 days); Model+FS group: The immobility stress + feeding with 0.2 ml/kg of FS oil by oral gavage for another 20 days. At the end, all mice were evaluated with tail suspension test (TST) and sacrificed through cardiac puncture method. The brain was isolated and prepared for molecular and histopathological studies.
 Results: The gene expression and protein level of BGNF and GDNF were significantly increased in FS oil treated groups (P<0.05). In microscopic evaluations, the number of dead neurons significantly deceased in FS group (P<0.05). TST results showed a significant decrease in immobility time and depressive-like behaviors in FS oil treated group (P<0.05).
 Conclusion: FS oil feeding may be effective in treatment of depressive like disorders through its anti-oxidative and neurotrophic promoting features. Therefore, it can be used as an appropriate alternative choice in daily diet to prevent depression in clinical investigations.

Improved Cerebral Perfusion Pressure and Microcirculation byDrag Reducing Polymer-Enforced Resuscitation Fluid After Traumatic Brain Injury and Hemorrhagic Shock.

Hemorrhagic shock (HS) after traumatic brain injury (TBI) reduces cerebral perfusion pressure (CPP) and cerebral blood flow (CBF), increasing hypoxia and doubling mortality. Volume expansion with resuscitation fluids (RFs) for HS does not improve CBF and tissue oxygen, while hypervolemia exacerbates brain edema and elevates intracranial pressure (ICP). We tested whether drag-reducing polymers (DRPs), added to isotonic Hetastarch (HES), would improve CBF but prevent ICP increase. TBI was induced in rats by fluid percussion, followed by controlled hemorrhage to mean arterial pressure (MAP)=40mmHg. HES-DRP or HES was infused to MAP=60mmHg for 1h, followed by blood reinfusion to MAP=70mmHg. Temperature, MAP, ICP, cortical Doppler flux, blood gases, and electrolytes were monitored. Microvascular CBF, tissue hypoxia, and neuronal necrosis were monitored by two-photon laser scanning microscopy 5h after TBI/HS. TBI/HS reduced CPP and CBF, causing tissue hypoxia. HES-DRP (1.9±0.8mL) more than HES (4.5±1.8mL) improved CBF and tissue oxygenation (p<0.05). In the HES group, ICP increased to 23±4mmHg (p<0.05) but in HES-DRP to 12±2mmHg. The number of dead neurons, microthrombosis, and the contusion volume in HES-DRP were significantly less than in the HES group (p<0.05). HES-DRP required a smaller volume, which reduced ICP and brain edema.

Addition of Drag-Reducing Polymers to Colloid Resuscitation Fluid Enhances Cerebral Microcirculation and Tissue Oxygenation After Traumatic Brain Injury Complicated byHemorrhagic Shock.

Hemorrhagic shock (HS) is a severe complication of traumatic brain injury (TBI) that doubles mortality due to severely compromised microvascular cerebral blood flow (mvCBF) and oxygen delivery reduction, as a result of hypotension. Volume expansion with resuscitation fluids (RF) for HS does not improve microvascular CBF (mvCBF); moreover, it aggravates brain edema. We showed that the addition of drag-reducing polymers (DRP) to crystalloid RF (lactated Ringer's) significantly improves mvCBF, oxygen supply, and neuronal survival in rats suffering TBI+HS. Here, we compared the effects of colloid RF (Hetastarch) with DRP (HES-DRP) and without (HES). Fluid percussion TBI (1.5 ATA, 50ms) was induced in rats and followed by controlled HS to a mean arterial pressure (MAP) of 40mmHg. HES or HES-DRP was infused to restore MAP to 60mmHg for 1h (prehospital period), followed by blood reinfusion to a MAP of 70mmHg (hospital period). In vivo two-photon microscopy was used to monitor cerebral microvascular blood flow, tissue hypoxia (NADH), and neuronal necrosis (i.v. propidium iodide) for 5h after TBI+HS, followed by postmortem DiI vascular painting. Temperature, MAP, blood gases, and electrolytes were monitored. Statistical analyses were done using GraphPad Prism by Student's t-test or Kolmogorov-Smirnov test, where appropriate. TBI+HS compromised mvCBF and tissue oxygen supply due to capillary microthrombosis. HES-DRP improved mvCBF and tissue oxygenation (p<0.05) better than HES. The number of dead neurons in the HES-DRP was significantly less than in the HES group: 76.1±8.9 vs. 178.5±10.3 per 0.075 mm3 (P<0.05). Postmortem visualization of painted vessels revealed vast microthrombosis in both hemispheres that were 33±2% less in HES-DRP vs. HES (p<0.05). Thus, resuscitation after TBI+HS using HES-DRP effectively restores mvCBF and reduces hypoxia, microthrombosis, and neuronal necrosis compared to HES. HES-DRP is more neuroprotective than lactated Ringer's with DRP and requires an infusion of a smaller volume, which reduces the development of hypervolemia-induced brain edema.

The Drosophila amyloid precursor protein homologue mediates neuronal survival and neuroglial interactions.

The amyloid precursor protein (APP) is a structurally and functionally conserved transmembrane protein whose physiological role in adult brain function and health is still unclear. Because mutations in APP cause familial Alzheimer's disease (fAD), most research focuses on this aspect of APP biology. We investigated the physiological function of APP in the adult brain using the fruit fly Drosophila melanogaster, which harbors a single APP homologue called APP Like (APPL). Previous studies have provided evidence for the implication of APPL in neuronal wiring and axonal growth through the Wnt signaling pathway during development. However, like APP, APPL continues to be expressed in all neurons of the adult brain where its functions and their molecular and cellular underpinnings are unknown. We report that APPL loss of function (LOF) results in the dysregulation of endolysosomal function in neurons, with a notable enlargement of early endosomal compartments followed by neuronal cell death and the accumulation of dead neurons in the brain during a critical period at a young age. These defects can be rescued by reduction in the levels of the early endosomal regulator Rab5, indicating a causal role of endosomal function for cell death. Finally, we show that the secreted extracellular domain of APPL interacts with glia and regulates the size of their endosomes, the expression of the Draper engulfment receptor, and the clearance of neuronal debris in an axotomy model. We propose that APP proteins represent a novel family of neuroglial signaling factors required for adult brain homeostasis.

TREM2 Alzheimer\u2019s variant R47H causes similar transcriptional dysregulation to knockout, yet only subtle functional phenotypes in human iPSC-derived macrophages

BackgroundTREM2 is a microglial cell surface receptor, with risk mutations linked to Alzheimer’s disease (AD), including R47H. TREM2 signalling via SYK aids phagocytosis, chemotaxis, survival, and changes to microglial activation state. In AD mouse models, knockout (KO) of TREM2 impairs microglial clustering around amyloid and prevents microglial activation. The R47H mutation is proposed to reduce TREM2 ligand binding. We investigated cell phenotypes of the R47H mutant and TREM2 KO in a model of human microglia, and compared their transcriptional signatures, to determine the mechanism by which R47H TREM2 disrupts function.MethodsWe generated human microglia-like iPSC-macrophages (pMac) from isogenic induced pluripotent stem cell (iPSC) lines, with homozygous R47H mutation or TREM2 knockout (KO). We firstly validated the effect of the R47H mutant on TREM2 surface and subcellular localization in pMac. To assess microglial phenotypic function, we measured phagocytosis of dead neurons, cell morphology, directed migration, survival, and LPS-induced inflammation. We performed bulk RNA-seq, comparing significant differentially expressed genes (DEGs; p < 0.05) between the R47H and KO versus WT, and bioinformatically predicted potential upstream regulators of TREM2-mediated gene expression.ResultsR47H modified surface expression and shedding of TREM2, but did not impair TREM2-mediated signalling, or gross phenotypes that were dysregulated in the TREM2 KO (phagocytosis, motility, survival). However, altered gene expression in the R47H TREM2 pMac overlapped by 90% with the TREM2 KO and was characterised by dysregulation of genes involved with immunity, proliferation, activation, chemotaxis, and adhesion. Downregulated mediators of ECM adhesion included the vitronectin receptor αVβ3, and consequently, R47H TREM2 pMac adhered weakly to vitronectin compared with WT pMac. To counteract these transcriptional defects, we investigated TGFβ1, as a candidate upstream regulator. TGFβ1 failed to rescue vitronectin adhesion of pMac, although it improved αVβ3 expression.ConclusionsThe R47H mutation is not sufficient to cause gross phenotypic defects of human pMac under standard culture conditions. However, overlapping transcriptional defects with TREM2 KO supports the hypothesised partial loss-of-function effects of the R47H mutation. Furthermore, transcriptomics can guide us to more subtle phenotypic defects in the R47H cells, such as reduced cell adhesion, and can be used to predict targets for therapeutic intervention.

SuperDeConFuse: A supervised deep convolutional transform based fusion framework for financial trading systems

This work proposes a supervised multi-channel time-series learning framework for financial stock trading. Although many deep learning models have recently been proposed in this domain, most of them treat the stock trading time-series data as 2-D image data, whereas its true nature is 1-D time-series data. Since the stock trading systems are multi-channel data, many existing techniques treating them as 1-D time-series data are not suggestive of any technique to effectively fusion the information carried by the multiple channels. To contribute towards both of these shortcomings, we propose an end-to-end supervised learning framework inspired by the previously established (unsupervised) convolution transform learning framework. Our approach consists of processing the data channels through separate 1-D convolution layers, then fusing the outputs with a series of fully-connected layers, and finally applying a softmax classification layer. The peculiarity of our framework, that we call SuperDeConFuse (SDCF), is that we remove the nonlinear activation located between the multi-channel convolution layers and the fully-connected layers, as well as the one located between the latter and the output layer. We compensate for this removal by introducing a suitable regularization on the aforementioned layer outputs and filters during the training phase. Specifically, we apply a logarithm determinant regularization on the layer filters to break symmetry and force diversity in the learnt transforms, whereas we enforce the non-negativity constraint on the layer outputs to mitigate the issue of dead neurons. This results in the effective learning of a richer set of features and filters with respect to a standard convolutional neural network. Numerical experiments confirm that the proposed model yields considerably better results than state-of-the-art deep learning techniques for the real-world problem of stock trading.

Quantitative neurotoxicology: Potential role of artificial intelligence/deep learning approach.

Neurotoxicity studies are important in the preclinical stages of drug development process, because exposure to certain compounds that may enter the brain across a permeable blood brain barrier damages neurons and other supporting cells such as astrocytes. This could, in turn, lead to various neurological disorders such as Parkinson's or Huntington's disease as well as various dementias. Toxicity assessment is often done by pathologists after these exposures by qualitatively or semiquantitatively grading the severity of neurotoxicity in histopathology slides. Quantification of the extent of neurotoxicity supports qualitative histopathological analysis and provides a better understanding of the global extent of brain damage. Stereological techniques such as the utilization of an optical fractionator provide an unbiased quantification of the neuronal damage; however, the process is time-consuming. Advent of whole slide imaging (WSI) introduced digital image analysis which made quantification of neurotoxicity automated, faster and with reduced bias, making statistical comparisons possible. Although automated to a certain level, simple digital image analysis requires manual efforts of experts which is time-consuming and limits analysis of large datasets. Digital image analysis coupled with a deep learning artificial intelligence model provides a good alternative solution to time-consuming stereological and simple digital analysis. Deep learning models could be trained to identify damaged or dead neurons in an automated fashion. This review has focused on and discusses studies demonstrating the role of deep learning in segmentation of brain regions, toxicity detection and quantification of degenerated neurons as well as the estimation of area/volume of degeneration.

In Vitro Oxygen-Glucose Deprivation-Induced Stroke Models with Human Neuroblastoma Cell- and Induced Pluripotent Stem Cell-Derived Neurons.

Stroke is a devastating neurological disorder and one of the leading causes of mortality and disability. To understand the cellular and molecular mechanisms of stroke and to develop novel therapeutic approaches, two different in vitro human cell-based stroke models were established using oxygen-glucose deprivation (OGD) conditions. In addition, the effect of adipose stem cells (ASCs) on OGD-induced injury was studied. In the present study, SH-SY5Y human neuroblastoma cells and human induced pluripotent stem cells (hiPSCs) were differentiated into neurons, cultured under OGD conditions (1% O2) for 24 h, and subjected to a reperfusion period for 24 or 72 h. After OGD, ASCs were cocultured with neurons on inserts for 24 or 72 h to study the neuroprotective potential of ASCs. The effect of OGD and ASC coculture on the viability, apoptosis, and proliferation of and axonal damage to neuronal cells was studied. The results showed that OGD conditions induced cytotoxicity and apoptosis of SH-SY5Y- and hiPSC-derived neurons, although more severe damage was detected in SH-SY5Y-derived neurons than in hiPSC-derived neurons. Coculture with ASCs was protective for neurons, as the number of dead ASC-cocultured neurons was lower than that of control cells, and coculture increased the proliferation of both cell types. To conclude, we developed in vitro human cell-based stroke models in SH-SY5Y- and hiPSC-derived neurons. This was the first time hiPSCs were used to model stroke in vitro. Since OGD had different effects on the studied cell types, this study highlights the importance of using several cell types in in vitro studies to confirm the outcomes of the study. Here, ASCs exerted a neuroprotective effect by increasing the proliferation and decreasing the death of SH-SY5Y- and hiPSC-derived neurons after OGD.

Therapeutic Advancement in Neuronal Transdifferentiation of Mesenchymal Stromal Cells for Neurological Disorders.

Neurodegenerative disorders have become the leading cause of chronic pain and death. Treatments available are not sufficient to help the patients as they only alleviate the symptoms and not the cause. In this regard, stem cells therapy has emerged as an upcoming option for the replacement of dead and damaged neurons. Stem cells, in general, are characterized as cells exhibiting potency properties, i.e., on being subjected to specific conditions they transform into cells of another lineage. Of all the types, mesenchymal stem cells (MSCs) are known for their pluripotent nature without the obstacle of ethical concern surrounding the procurement of other cell types. Although fibroblasts are quite similar to MSCs morphologically, certain markers like CD73, CD 90 are specific to MSCs, making both the cell types distinguishable from each other. This is implemented while procuring MSCs from a plethora of sources like umbilical cord blood, adipose tissue, bone marrow, etc. Among these, bone marrow MSCs are the most widely used type for neural regeneration. Neural regeneration is achieved via transdifferentiation. Several studies have either transplanted the stem cells into rodent models or have carried out transdifferentiation in vitro. The process involves a combination of growth factors, pre-treatment factors, and neuronal differentiation inducing mediums. The results obtained are characterized by neuron-like morphology, expression of markers, along with electrophysical activity in some. Recent attempts involve exploring biomaterials that may mimic the native ECM and therefore can be directly introduced at the site of interest. The review gives a brief description of MSCs, their sources and markers, and the different attempts that have been made towards achieving the goal of differentiating MSCs into neurons.

The effect of glutathione and buserelin on the stereological parameters of the hypothalamus in the cyclophosphamide-treated mice

IntroductionNew anticancer drugs have increased the survival and fertility rates in young patients. These drugs (i.e., cyclophosphamide; Cyc) have some side effects on the hypothalamus and fertility. One possible chemical for reducing these side effects is thiol or GnRH agonist. This study aimed to evaluate the capability of these agents for reducing the cyclophosphamide effects on the hypothalamus. MethodsSixty-three female mice were randomly assigned into seven groups. All groups including the control group had free access to water and mouse chow ad libitum. The sham group received normal saline. The Glu and Bus groups received glutathione (Glu) and buserelin (Bus) daily for 16 days, while the Cyc group received only cyclophosphamide as a single dose; the Cyc + Glu and Cyc + Bus groups, in addition to cyclophosphamide, received glutathione and buserelin, respectively. The volume of the hypothalamus, its neuron number, and dead neurons were evaluated using stereological methods. ResultsThere was no significant difference in the evaluated stereological parameters between the control and sham groups. However, the animals which received Cyc showed a decrease in the volume of the hypothalamus and its neuron number and density and an increase in cell death as compared with the control group. The treatment of the mice that received Cyc with Glu or Bus prevented these changes. ConclusionThis study showed that both GnRH agonist and thiol preserved or improved structural changes in the hypothalamus caused by cyclophosphamide in mice, suggesting that using thiol and especially GnRH agonist along with chemotherapy drugs may have protective effects on fertility.