Number Of Neurons Research Articles

Efficient calibration of cost-efficient particulate matter sensors using machine learning and time-series alignment

Atmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure, highlighting the crucial need for monitoring PM levels to develop and implement effective risk mitigation measures. Notwithstanding, accurate measurement of PM concentration relies on expensive and cumbersome equipment. Despite the rising popularity of low-cost alternatives, their reliability remains questionable, given their sensitivity to environmental conditions, inherent instability, and manufacturing imperfections. This article proposes a novel approach to efficient correction of low-cost PM sensors. The primary calibration model is a feedforward artificial neural network (ANN), which directly renders predicted output of the corrected sensor based on environmental variables such as temperature, humidity, and atmospheric pressure. The ANN hyper-parameters are identified by aligning time series of prior reference and low-cost sensor readings, which enables the network to learn typical temporal changes of the sensor outcome as a function of the aforementioned parameters as well as operational relationships between the sensor and the reference device. The architecture of the ANN is optimized in terms of the number of neurons in each layer to enhance its generalization capability. Our methodology has been demonstrated using a custom-designed portable monitoring platform and reference data acquired from public stations in Gdansk. The results are indicative of excellent calibration reliability. The achieved correlation coefficients w.r.t. the reference readings are 0.86, 0.88, and 0.72 for PM1, PM10, and PM2.5, respectively, whereas RMSE values are only 3.0, 3.9, and 5.4 µg/m³.

Caspase-1 deletion reveals pyroptosis participates in neural damage induced by cerebral ischemia/reperfusion in tMCAO model mice.

Pyroptosis, a form of programmed cell death, drives inflammation in the context of cerebral ischemia/reperfusion. The molecular mechanism of pyroptosis underlying ischemia/reperfusion, however, is not fully understood. The transient middle cerebral artery occlusion was applied to wild-type and caspase-1 knockout mice. 2,3,5-Triphenyltetrazolium chloride-staining and immunohistochemistry were used to identify the ischemic region, and western blot and immunofluorescence for the examination of neuronal pyroptosis. The expression of inflammatory factors and the behavioral function assessments were further conducted to examine the effects of caspase-1 knockout on protection against ischemia/reperfusion injury. Ischemia/reperfusion injury increased pyroptosis-related signals represented by the overexpression of pyroptosis-related proteins including caspase-1 and gasdermin D (GSDMD). Meanwhile, the number of GSDMD positive neurons increased in penumbra by immunofluorescence staining. Compared with wild-type mice, those with caspase-1 knockout exhibited decreased levels of pyroptosis-related proteins following ischemia/reperfusion. Furthermore, ischemia/reperfusion attack-induced brain infarction, cerebral edema, inflammatory factors, and neurological outcomes were partially improved in caspase-1 knockout mice. The data indicate that pyroptosis participates in ischemia/reperfusion induced-damage, and the caspase-1 might be involved, it provides some new insights into the molecular mechanism of ischemia.

Changes in the cellular makeup of motor patterning circuits drive courtship song evolution in Drosophila

How evolutionary changes in genes and neurons encode species variation in complex motor behaviors is largely unknown. Here, we develop genetic tools that permit a neural circuit comparison between the model species Drosophila melanogaster and the closely related species D.yakuba, which has undergone a lineage-specific loss of sine song, one of the two major types of male courtship song in Drosophila. Neuroanatomical comparison of song-patterning neurons called TN1 across the phylogeny demonstrates a link between the loss of sine song and a reduction both in the number of TN1 neurons and the neurites supporting the sine circuit connectivity. Optogenetic activation confirms that TN1 neurons in D.yakuba have lost the ability to drive sine song, although they have maintained the ability to drive the singing wing posture. Single-cell transcriptomic comparison shows that D.yakuba specifically lacks a cell type corresponding to TN1A neurons, the TN1 subtype that is essential for sine song. Genetic and developmental manipulation reveals a functional divergence of the sex determination gene doublesex in D.yakuba to reduce TN1 number by promoting apoptosis. Our work illustrates the contribution of motor patterning circuits and cell type changes in behavioral evolution and uncovers the evolutionary lability of sex determination genes to reconfigure the cellular makeup of neural circuits.

Morphofunctional changes in ventral and dorsal hippocampus in adult rats after chronic mild stress: a preclinical experimental study

Background. Stressful influences, depending on their severity and duration, can cause the development of pathological conditions. Repeated episodes of stress cause functional and structural changes in the central nervous system and can cause the development of depressive conditions. Depression is one of the leading mental illnesses. One of the most stress-sensitive brain structures is the hippocampus. Objective. To study is to evaluate structural changes in the hippocampus, which is considered as a heterogeneous structure with separate dorsal and ventral regions, to evaluate the expression of inducible nitric oxide synthase, endothelial nitric oxide synthase, serine racemase, synaptophysin in a mild stress model.Methods. A study of the effects of mild stress was carried out on 16 adult male Wistar rats (age 12 months, body weight 350–400 g). After acclimatization, the rats were divided into two equal groups (n = 8): intact (control) and stressed. When keeping animals, modeling and removing them from the experiment, we were guided by the Regulations for Carrying Out Work Using Laboratory Animals and the Declaration of Helsinki. Experimental modeling of depression in animals was induced by mild stress exposure for 7 days (30 minutes daily). Euthanasia was performed in a CO2 incubator. The brain was fixed in neutral buffered 10% formalin. Paraffin sections were made in the frontal plane, stained with hematoxylin and eosin, thionin using the Nissl method and examined at a level from –2.40 to –3.96 mm relative to bregma using an Axio Lab A1 microscope (Carl Zeiss Microscopy GmbH, Germany). Photo documentation was carried out with an AxioCam 105 color camera (Carl Zeiss Microscopy GmbH, Germany). Using the Image Analysis module of the ZEN 1.1.2.0 program (Carl Zeiss Microscopy GmbH, Germany) in the pyramidal layer of the hippocampus. Statistical analysis was performed with Microsoft Office Excel 2016 (Microsoft, USA) and Prism 6 (GraphPad Software Inc., USA). Comparisons of two conditions were made by nonparametric Mann-Whitney-U test to avoid a statistical bias of unequal data distribution. The level of significance was set at p < 0.05. The summarized data were presented as a as mean ± standard error of mean.Results. Functional research methods and assessment of pathological changes in hippocampal neurons are presented. An increase in the relative number of wrinkled hyperchromatic pyramidal neurons in the dorsal cornu ammonis field 3 in stressed rats was noted by 23.6% (p < 0.05) compared to the control. There was an increase in the relative number of inducible nitric oxide synthase-immunopositive neurons in the dorsal cornu ammonis field 3 by 40% ( p < 0.05) and the relative area of inducible nitric oxide synthase-immunoreactive material by 35% (p < 0.05) in the pyramidal layer of cornu ammonis field 3 in stressed rats. A decrease in the relative area of synaptophysin-immunopositive material in stressed rats was found in the ventral cornu ammonis field 3 compared to the control group by 16.8% (p < 0.05); decrease in the relative area of serine racemase-immunopositive material in dorsal cornu ammonis field 3 by 4.3% (p < 0.05) and ventral cornu ammonis field 3 by 7.8% (p < 0.05).Conclusion. The results of the study demonstrate that mild stress is an adequate model of depression in rats. In animals exposed to mild stress, pronounced morphological signs of damage to hippocampal neurons were revealed; motor and indicative exploratory activity decreases. Differences were found in morphofunctional changes in the dorsal and ventral parts of the hippocampus under the influence of mild stress. In cornu ammonis field 3 of the dorsal hippocampus, in contrast to the ventral section, more pronounced signs of damage to pyramidal layer neurons were observed. The increase in the relative number of inducible nitric oxide synthase-immunopositive neurons and the relative area of inducible nitric oxide synthase-immunoreactive material in the cornu ammonis field 3 pyramidal layer in stressed rats indicates an increase in nitric oxide production and the participation of nitrooxide-dependent free radical mechanisms of damage to hippocampal neurons. The decrease in the relative area of synaptophysin-immunoreactive material in stressed rats may contribute to changes in synaptic plasticity. A decrease in the relative area of serine racemase-immunoreactive material in the dorsal and ventral parts of cornu ammonis field 3 is considered to be a sign of a possible decrease in N-methyl-D-aspartate-dependent neurotransmission in the hippocampus under stress.

Neural Network Modeling of a Stereolithography Printed Mesostructure

Abstract This paper addresses the scarcity of comprehensive studies on the collective impact of various parametric lattice designs on mesostructure functionality. Focusing on optimizing the energy absorption of a serpentine mesostructure made using stereolithography, this research leverages a feedforward neural network to explore the interplay between line width, number of turns, and material properties on the energy absorbed by the structure. Compression simulations using a finite element model, covering a range of configurations, provided the dataset for neural network training. The resulting network was used to probe correlations between geometric variables, material, and energy absorption. Additionally, a neural network sensitivity analysis explored the impact of hidden layers and number of neurons on the network's performance, demonstrating the network's robustness. The optimized mesostructure configuration, identified by the neural network, maximized energy absorption. Using foundational mechanics of materials concepts, the discussion explains how the geometry and material of the cellular mesostructure affect structural stiffness.

How smart was T. rex? Testing claims of exceptional cognition in dinosaurs and the application of neuron count estimates in palaeontological research.

Recent years have seen increasing scientific interest in whether neuron counts can act as correlates of diverse biological phenomena. Lately, Herculano-Houzel (2023) argued that fossil endocasts and comparative neurological data from extant sauropsids allow to reconstruct telencephalic neuron counts in Mesozoic dinosaurs and pterosaurs, which might act as proxies for behaviors and life history traits in these animals. According to this analysis, large theropods such as Tyrannosaurus rex were long-lived, exceptionally intelligent animals equipped with "macaque- or baboon-like cognition", whereas sauropods and most ornithischian dinosaurs would have displayed significantly smaller brains and an ectothermic physiology. Besides challenging established views on Mesozoic dinosaur biology, these claims raise questions on whether neuron count estimates could benefit research on fossil animals in general. Here, we address these findings by revisiting Herculano-Houzel's (2023) work, identifying several crucial shortcomings regarding analysis and interpretation. We present revised estimates of encephalization and telencephalic neuron counts in dinosaurs, which we derive from phylogenetically informed modeling and an amended dataset of endocranial measurements. For large-bodied theropods in particular, we recover significantly lower neuron counts than previously proposed. Furthermore, we review the suitability of neurological variables such as neuron numbers and relative brain size to predict cognitive complexity, metabolic rate and life history traits in dinosaurs, coming to the conclusion that they are flawed proxies for these biological phenomena. Instead of relying on such neurological estimates when reconstructing Mesozoic dinosaur biology, we argue that integrative studies are needed to approach this complex subject.

Transcriptional control of visual neural circuit development by GS homeobox 1.

As essential components of gene expression networks, transcription factors regulate neural circuit assembly. The homeobox transcription factor encoding gene, gs homeobox 1 (gsx1), is expressed in the developing visual system; however, no studies have examined its role in visual system formation. In zebrafish, retinal ganglion cell (RGC) axons that transmit visual information to the brain terminate in ten arborization fields (AFs) in the optic tectum (TeO), pretectum (Pr), and thalamus. Pretectal AFs (AF1-AF9) mediate distinct visual behaviors, yet we understand less about their development compared to AF10 in the TeO. Using gsx1 zebrafish mutants, immunohistochemistry, and transgenic lines, we observed that gsx1 is required for vesicular glutamate transporter, Tg(slc17a6b:DsRed), expression in the Pr, but not overall neuron number. gsx1 mutants have normal eye morphology, yet they exhibit impaired visual ability during prey capture. RGC axon volume in the gsx1 mutant Pr and TeO is reduced, and AF7 that is active during feeding is missing which is consistent with reduced hunting performance. Timed laser ablation of Tg(slc17a6b:DsRed)-positive cells reveals that they are necessary for AF7 formation. This work is the first to implicate gsx1 in establishing cell identity and functional neural circuits in the visual system.

Development and Implementation of a Multilayer Deep Learning-Based Bank Credit Risk Forecasting System

The complexity of the financial environment and the international community makes the capital flow face various challenges, and it is difficult to obtain accurate credit prediction results in the actual application environment. Considering the complex non-linear characteristics of customer information, the Analytic Hierarchy Process is studied to meet the needs of bank credit risk assessment. On this basis, a depth neural network with different complexities was selected for the three indicators built to classify the features. The composition of the neural network module and the number of neurons were determined by experiment, and Dropout was used to prevent overfitting of the test dataset. Stability and ablation experiments showed that the model can control the error between datasets to 0.021. The ablation experiment showed that the numbers of hidden layers and neurons were the best. Simulation tests showed that the sensitivity and accuracy of this method were 85.25% and 92.55%, respectively, which were superior to other classification methods. The real data of banks in the past four years were tested. The results could accurately classify the risks of enterprises and individual customers, and the results of stress test showed that the model is stable. It is found that traditional credit risk assessment models rely on statistical means and rule decisions, and these methods may not fully reveal the complex non-linear relationship and the internal relationship of financial indicators in high-dimensional data. The combination of deep learning technology and hierarchical analysis can better deal with and explain the complex non-linear problems in bank risk assessment.

Multiple cholinergic receptor subtypes coordinate dual modulation of acetylcholine on anterior and posterior paraventricular thalamic neurons.

Paraventricular thalamus (PVT) plays important roles in the regulation of emotion and motivation through connecting many brain structures including the midbrain and the limbic system. Although acetylcholine (ACh) neurons of the midbrain were reported to send projections to PVT, little is known about how cholinergic signaling regulates PVT neurons. Here, we used both RNAscope and slice patch-clamp recordings to characterize cholinergic receptor expression and ACh modulation of PVT neurons in mice. We found ACh excited a majority of anterior PVT (aPVT) neurons but predominantly inhibited posterior PVT (pPVT) neurons. Compared to pPVT with more inhibitory M2 receptors, aPVT expressed higher levels of all excitatory receptor subtypes including nicotinic α4, α7, and muscarinic M1 and M3. The ACh-induced excitation was mimicked by nicotine and antagonized by selective blockers for α4β2 and α7 nicotinic ACh receptor (nAChR) subtypes as well as selective antagonists for M1 and M3 muscarinic ACh receptors (mAChR). The ACh-induced inhibition was attenuated by selective M2 and M4 mAChR receptor antagonists. Furthermore, we found ACh increased the frequency of excitatory postsynaptic currents (EPSCs) on a majority of aPVT neurons but decreased EPSC frequency on a larger number of pPVT neurons. In addition, ACh caused an acute increase followed by a lasting reduction in inhibitory postsynaptic currents (IPSCs) on PVT neurons of both subregions. Together, these data suggest that multiple AChR subtypes coordinate a differential modulation of ACh on aPVT and pPVT neurons.

The Effect of Varying Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Parameters on Wind Energy Prediction: A Comparative Study

Owing to the development of technology, the majority of nations throughout the world now rely on fossil fuels and nuclear power plants to meet their energy needs. However, as academic research on this subject has shown, it has become clear that alternative energy uses are necessary due to the gradual depletion of these fuels and their significant negative effects on the environment. In order to ensure energy diversity and end the energy shortage, the development of renewable energy sources is crucial. The prediction of wind power is crucial for effectively utilizing the potential of wind energy. In this study, an adaptive neuro-fuzzy inference system (ANFIS) and an artificial neural network (ANN) have been developed for the prediction of wind power. In this study, data sets were created by taking the daily average wind speeds of the selected wind turbine, the daily average power values it produces, and the daily average wind speed values in the Velimese region. By creating single-hidden layer and multi-hidden layer ANN models, the network was trained multiple times with different activation functions and different numbers of neurons, and wind power prediction was performed. In the ANFIS model, the number of membership functions is kept constant, and wind power prediction is performed using different membership functions. With these ANFIS and ANN models developed with different parameter combinations, it is aimed to determine the most efficient model by performing daily average wind power prediction. Parameter combinations were tested to determine the appropriate models, and as a result, the ANN and ANFIS models were compared with each other.

The IC87201 (a PSD95/nNOS Inhibitor) Attenuates Post- Stroke Injuries.

N-methyl-D-aspartate receptor-dependent excitotoxicity is one of the most important mechanisms underlying stroke injury and the resulting neuronal death. In the present study, in order to reduce post-stroke brain injury and improve behavioral performance, a new molecule named IC87201, which acts as an inhibitor of PSD95/nNOS interaction in the intracellular signaling pathway of NMDA receptors, was administered. Using the middle cerebral artery occlusion (MCAO) technique, 24 adult male rats were subjected to one hour of cerebral ischemia. Animals were randomly divided into sham, MCAO, MCAO + DXM, and MCAO + IC87201 groups, and in the last two groups, intraperitoneal injection of dextromethorphan hydrobromide monohydrate (DXM), as an NMDA antagonist, and IC87201 was performed after ischemia. Neurobehavioral scores were evaluated for seven days, and on the last two days, the rats' memory performance was appraised using the passive avoidance test. On seventh day, the brain tissue was properly prepared for stereological analysis. Stereological studies of the hippocampus CA1 and CA3 regions revealed that changes in the total and infarcted volumes, total number of neurons, non-neurons, and dead neurons are the consequences of cerebral ischemia. Also, following cerebral ischemia, neurobehavioral and memory function impairments which were assessed by modified neurological severity scores (mNSS) and passive avoidance test, were observed. The aforementioned impairments were recovered after administration of IC87201 significantly and more potently than DXM. Based on our findings, IC87201 successfully attenuated post-ischemia damages. Therefore, this molecule can be considered as a new therapeutic approach in future research.

Single cell tracing of Pomc neurons reveals recruitment of ‘Ghost’ subtypes with atypical identity in a mouse model of obesity

The hypothalamus contains a remarkable diversity of neurons that orchestrate behavioural and metabolic outputs in a highly plastic manner. Neuronal diversity is key to enabling hypothalamic functions and, according to the neuroscience dogma, it is predetermined during embryonic life. Here, by combining lineage tracing of hypothalamic pro-opiomelanocortin (Pomc) neurons with single-cell profiling approaches in adult male mice, we uncovered subpopulations of ‘Ghost’ neurons endowed with atypical molecular and functional identity. Compared to ‘classical’ Pomc neurons, Ghost neurons exhibit negligible Pomc expression and are ‘invisible’ to available neuroanatomical approaches and promoter-based reporter mice for studying Pomc biology. Ghost neuron numbers augment in diet-induced obese mice, independent of neurogenesis or cell death, but weight loss can reverse this shift. Our work challenges the notion of fixed, developmentally programmed neuronal identities in the mature hypothalamus and highlight the ability of specialised neurons to reversibly adapt their functional identity to adult-onset obesogenic stimuli.

Neuronal cell cycle reentry events in the aging brain are more prevalent in neurodegeneration and lead to cellular senescence.

Increasing evidence indicates that terminally differentiated neurons in the brain may recommit to a cell cycle-like process during neuronal aging and under disease conditions. Because of the rare existence and random localization of these cells in the brain, their molecular profiles and disease-specific heterogeneities remain unclear. Through a bioinformatics approach that allows integrated analyses of multiple single-nucleus transcriptome datasets from human brain samples, these rare cell populations were identified and selected for further characterization. Our analyses indicated that these cell cycle-related events occur predominantly in excitatory neurons and that cellular senescence is likely their immediate terminal fate. Quantitatively, the number of cell cycle re-engaging and senescent neurons decreased during the normal brain aging process, but in the context of late-onset Alzheimer's disease (AD), these cells accumulate instead. Transcriptomic profiling of these cells suggested that disease-specific differences were predominantly tied to the early stage of the senescence process, revealing that these cells presented more proinflammatory, metabolically deregulated, and pathology-associated signatures in disease-affected brains. Similarly, these general features of cell cycle re-engaging neurons were also observed in a subpopulation of dopaminergic neurons identified in the Parkinson's disease (PD)-Lewy body dementia (LBD) model. An extended analysis conducted in a mouse model of brain aging further validated the ability of this bioinformatics approach to determine the robust relationship between the cell cycle and senescence processes in neurons in this cross-species setting.

The Effect of Biotic Stress in Plant Species Induced by ‘Candidatus Phytoplasma solani’—An Artificial Neural Network Approach

Infections with phytoplasma present one of the most significant biotic stresses influencing plant health, growth, and production. The phytoplasma ‘Candidatus Phytoplasma solani’ infects a variety of plant species. This pathogen impacts the physiological and morphological characteristics of plants causing stunting, yellowing, leaf curling, and other symptoms that can lead to significant economic losses. The aim of this study was to determine biochemical changes in peony (Paeonia tenuifolia L.), mint (Mentha × piperita L.), and dill (Anethum graveolens L.) induced by ‘Ca. Phytoplasma solani’ in Serbia as well as to predict the impact of the biotic stress using artificial neural network (ANN) modeling. The phylogenetic position of the Serbian ‘Ca. Phytoplasma solani’ strains originated from the tested hosts using 16S rRNA (peony and carrot strains) and plsC (mint and dill strains) sequences indicated by their genetic homogeneity despite the host of origin. Biochemical parameters significantly differed in asymptomatic and symptomatic plants, except for total anthocyanidins contents in dill and the capacity of peony and mint extracts to neutralize superoxide anions and hydroxyl radicals, respectively. Principal Component Analysis (PCA) showed a correlation between different chemical parameters and revealed a clear separation among the samples. Based on the ANN performance, the optimal number of hidden neurons for the calculation of TS, RG, PAL, LP, NBT, •OH, TP, TT, Tflav, Tpro, Tant, DPPH, and Car was nine (using MLP 8-9-13), as it produced high r2 values (1.000 during the training period) and low SOS values. Developing an effective early warning system for the detection of plant diseases in different plant species is critical for improving crop yield and quality.

Fractionated brain X-irradiation profoundly reduces hippocampal immature neuron numbers without affecting spontaneous behavior in mice

Whole brain radiotherapy (WBRT) is used to improve tumor control in patients with primary brain tumors, or brain metastasis from various primary tumors to improve tumor control. However, WBRT can lead to cognitive decline in patients. We assessed whether fractionated WBRT (fWBRT) affects spontaneous behavior of mice in automated home cages and cognition (spatial memory) using the Barnes maze.Male C57Bl/6j mice received bi-lateral fWBRT at a dosage of 4 Gy/day on 5 consecutive days. In line with previous reports, immunohistochemical analysis of doublecortin positive cells in the dentate gyrus showed a profound reduction in immature neurons 4 weeks after fWBRT. Surprisingly, spontaneous behavior as measured in automated home cages was not affected. Moreover, learning and memory measured with Barnes maze, was also not affected 4–6 weeks after fWBRT. At 10–11 weeks after fWBRT a significant difference in escape latency during the learning phase, but not in the probe test of the Barnes maze was observed.In conclusion, although we confirmed the serious adverse effect of fWBRT on neurogenesis 4 weeks after fWBRT, we did not find similar profound effects on spontaneous behavior in the automated home cage nor on learning abilities as measured by the Barnes maze. The relationship between the neurobiological effects of fWBRT and cognition seems more complex than often assumed and the choice of animal model, cognitive tasks, neurobiological parameters, and experimental set-up might be important factors in these types of experiments.

Improved therapeutic approach for spinal muscular atrophy via ubiquitination-resistant survival motor neuron variant.

Zolgensma is a gene-replacement therapy that has led to a promising treatment for spinal muscular atrophy (SMA). However, clinical trials of Zolgensma have raised two major concerns: insufficient therapeutic effects and adverse events. In a recent clinical trial, 30% of patients failed to achieve motor milestones despite pre-symptomatic treatment. In addition, more than 20% of patients showed hepatotoxicity due to excessive virus dosage, even after the administration of an immunosuppressant. Here, we aimed to test whether a ubiquitination-resistant variant of survival motor neuron (SMN), SMNK186R, has improved therapeutic effects for SMA compared with wild-type SMN (SMNWT). A severe SMA mouse model, SMA type 1.5 (Smn-/-; SMN2+/+; SMN∆7+/-) mice, was used to compare the differences in therapeutic efficacy between AAV9-SMNWT and AAV9-SMNK186R. All animals were injected within Postnatal Day (P) 1 through a facial vein or cerebral ventricle. AAV9-SMNK186R-treated mice showed increased lifespan, body weight, motor neuron number, muscle weight and functional improvement in motor functions as compared with AAV9-SMNWT-treated mice. Lifespan increased by more than 10-fold in AAV9-SMNK186R-treated mice (144.8±26.11days) as compared with AAV9-SMNWT-treated mice (26.8±1.41days). AAV9-SMNK186R-treated mice showed an ascending weight pattern, unlike AAV9-SMNWT-treated mice, which only gained weight until P20 up to 5g on average. Several motor function tests showed the improved therapeutic efficacy of SMNK186R. In the negative geotaxis test, AAV9-SMNK186R-treated mice turned their bodies in an upward direction successfully, unlike AAV9-SMNWT-treated mice, which failed to turn upwards from around P23. Hind limb clasping phenotype was rarely observed in AAV9-SMNK186R-treated mice, unlike AAV9-SMNWT-treated mice that showed clasping phenotype for more than 20 out of 30s. At this point, the number of motor neurons (1.5-fold) and the size of myofibers (2.1-fold) were significantly increased in AAV9-SMNK186R-treated mice compared with AAV9-SMNWT-treated mice without prominent neurotoxicity. AAV9-SMNK186R had fewer liver defects compared with AAV9-SMNWT, as judged by increased proliferation of hepatocytes (P<0.0001) and insulin-like growth factor-1 production (P<0.0001). Especially, low-dose AAV9-SMNK186R (nine-fold) also reduced clasping time compared with SMNWT. SMNK186R will provide improved therapeutic efficacy in patients with severe SMA with insufficient therapeutic efficacy. Low-dose treatment of SMA patients with AAV9-SMNK186R can reduce the adverse events of Zolgensma. Collectively, SMNK186R has value as a new treatment for SMA that improves treatment effectiveness and reduces adverse events simultaneously.

The effectiveness of hesperidin on bisphenol A-induced spinal cord toxicity in a diabetic rat model

The potential health risks of bisphenol A (BS) and diabetes (DI) has sparked public concern due to be ubiquitous worldwide. The purpose of this study was to investigate the detrimental impact of BS (200 mg/kg) on the spinal cord tissue in a rat diabetic model. We also evaluated the antioxidant capacity of hesperidin (HS) (100 mg/kg) on spinal cord in BS-treated diabetic rat. Seventy male Wistar albino rats, weighing 180–230 g and 8 weeks old, were randomly chosen, and assigned into seven groups of 10 rats: Control (KON), BS, DI, BS + DI, HS + BS, HS + DI, HS + BS + DI. At the end of the 14-day experimental period, all samples were examined using stereological, biochemical, and histopathological techniques. Our biochemical findings revealed that the SOD level was significantly lower in the BS, DI, and BS + DI groups compared to the KON group (p < 0.05). Compared to the KON group, there was a significant decrease in the number of motor neurons and an increase in the mean volume of central canals in the BS, DI, and BS + DI groups (p < 0.05). In the HS + BC group than the BS group and in the HS + DI group than the DI group, SOD activity and the number of motor neurons were significantly higher; also, the mean volume of spinal central canal was significantly lower (p < 0.05). The novel findings gathered from the histopathological assessment supported our quantitative results. Our speculation was that the exposure to BS and DI was the main cause of neurological alteration in the spinal cord tissues. The administration of HS had the therapeutic potential to mitigate spinal cord abnormalities resulting from BS and DI. However, HS supplementation did not alleviate spinal cord complications in BS-treated diabetic rats.

Octopaminergic descending neurons in Drosophila: Connectivity, tonic activity and relation to locomotion

Projection neurons that communicate between different brain regions and local neurons that shape computation within a brain region form the majority of all neurons in the brain. Another important class of neurons is neuromodulatory neurons; these neurons are in much smaller numbers than projection/local neurons but have a large influence on computations in the brain. Neuromodulatory neurons are classified by the neurotransmitters they carry, such as dopamine and serotonin. Much of our knowledge of the effect of neuromodulators comes from experiments in which either a large population of neuromodulatory neurons or the entire population is perturbed. Alternatively, a given neuromodulator is exogenously applied. While these experiments are informative of the general role of the neurotransmitter, one limitation of these experiments is that the role of individual neuromodulatory neurons remains unknown. In this study, we investigate the role of a class of octopaminergic (octopamine is the invertebrate equivalent of norepinephrine) neurons in Drosophila or fruit fly. Neuromodulation in Drosophila work along similar principles as humans; and the smaller number of neuromodulatory neurons allow us to assess the role of individual neurons. This study focuses on a subpopulation of octopaminergic descending neurons (OA-DNs) whose cell bodies are in the brain and project to the thoracic ganglia. Using in-vivo whole-cell patch-clamp recordings and anatomical analyses that allow us to compare light microscopy data to the electron microscopic volumes available in the fly, we find that neurons within each cluster have similar physiological properties, including their relation to locomotion. However, neurons in the same cluster with similar anatomy have very different connectivity. Our data is consistent with the hypothesis that each OA-DN is recruited individually and has a unique function within the fly's brain.

Role of RB1 in neurodegenerative diseases: inhibition of post-mitotic neuronal apoptosis via Kmt5b.

During the development of the vertebrate nervous system, 50% of the nerve cells undergo apoptosis shortly after formation. This process is important for sculpting tissue during morphogenesis and removing transiently functional cells that are no longer needed, ensuring the appropriate number of neurons in each region. Dysregulation of neuronal apoptosis can lead to neurodegenerative diseases. However, the molecular events involved in activating and regulating the neuronal apoptosis program are not fully understood. In this study, we identified several RB1 mutations in patients with neurodegenerative diseases. Then, we used a zebrafish model to investigate the role of Rb1 in neuronal apoptosis. We showed that Rb1-deficient mutants exhibit a significant hindbrain neuronal apoptosis, resulting in increased microglia infiltration. We further revealed that the apoptotic neurons in Rb1-deficient zebrafish were post-mitotic neurons, and Rb1 inhibits the apoptosis of these neurons by regulating bcl2/caspase through binding to Kmt5b. Moreover, using this zebrafish mutant, we verified the pathogenicity of the R621S and L819V mutations of human RB1 in neuronal apoptosis. Collectively, our data indicate that the Rb1-Kmt5b-caspase/bcl2 axis is crucial for protecting post-mitotic neurons from apoptosis and provides an explanation for the pathogenesis of clinically relevant mutations.

Diagnosis of brain disease based on the deep learning algorithms of neural imaging techniques

Neuroimaging technology is considered a non-invasive method research the structure and function of the brain which have been widely used in neuroscience, psychiatry, psychology, and other fields. The development of Deep Learning Neural Network (DLNN), based on the deep learning algorithms of neural imaging techniques in brain disease diagnosis plays a more and more important role. In this paper, a deep neural network imaging technology based on Stack Auto-Encoder (SAE) feature extraction is constructed, and then Support Vector Machine (SVM) was used to solve binary classification problems (Alzheimer’s disease [AD] and Mild Cognitive Impairment [MCI]). Four sets of experimental data were employed to perform the training and testing stages of DLNN. The number of neurons in each of the DLNNs was determined using the grid search technique. Overall, the results of DLNNs performance indicated that the SAE feature extraction was superior over (Accuracy Rate [AR] = 74.9% with structure of 93-171-49-22-93) shallow layer features extraction (AR = 70.8% with structure of 93-22-93) and primary features extraction (AR = 69.2%).