Neurons In Brain Research Articles

Gated parametric neuron for spike-based audio recognition

Spiking neural networks (SNNs) aim to simulate real neural networks in the human brain with biologically plausible neurons. The leaky integrate-and-fire (LIF) neuron is one of the most widely studied SNN architectures. However, it has the vanishing gradient problem when trained with backpropagation. Additionally, its neuronal parameters are often manually specified and fixed, in contrast to the heterogeneity of real neurons in the human brain. This paper proposes a gated parametric neuron (GPN) to process spatio-temporal information effectively with the gating mechanism. Compared with the LIF neuron, the GPN has two distinguishing advantages: (1) it copes well with the vanishing gradients by improving the flow of gradient propagation; and, (2) it learns spatio-temporal heterogeneous neuronal parameters automatically. Additionally, we use the same gate structure to eliminate initial neuronal parameter selection and design a hybrid recurrent neural network-SNN structure. Experiments on two spike-based audio datasets demonstrated that the GPN network outperformed several state-of-the-art SNNs, could mitigate vanishing gradients, and had spatio-temporal heterogeneous parameters. Our work shows the ability of SNNs to handle long-term dependencies and achieve high performance simultaneously.

Widespread Neuroanatomical Integration and Distinct Electrophysiological Properties of Glioma-Innervating Neurons.

We have developed a novel system utilizing rabies virus-based monosynaptic tracing to directly visualize neurons that synapse onto human glioma cells implanted in mouse brain. This approach enables the mapping and quantitative analysis of these glioma-innervating neurons (GINs) in the entire mouse brain and overcomes previous barriers of molecular and electrophysiological analysis of these neurons due to the inability to identify them. Our findings indicate that GINs integrate into existing neural networks in a location-specific manner. Long-range GINs are mostly glutamatergic, with a subset expressing both glutamatergic and GABAergic markers and local striatal GINs are GABAergic, highlighting a complex neuromodulatory profile. Additionally, GINs exhibit unique action potential characteristics, distinct from similarly selected neurons in non-tumor-bearing brains. This study provides new insights into neuronal adaptations in response to forming putative synapses onto glioma, elucidating the intricate synaptic relationship between GINs and gliomas.

Single-cell dissection of the human blood-brain barrier and glioma blood-tumor barrier

The blood-brain barrier (BBB) serves as a crucial vascular specialization, shielding and nourishing brain neurons and glia while impeding drug delivery. Here, we conducted single-cell mRNA sequencing of human cerebrovascular cells from 13 surgically resected glioma samples and adjacent normal brain tissue. The transcriptomes of 103,230 cells were mapped, including 57,324 endothelial cells (ECs) and 27,703 mural cells (MCs). Both EC and MC transcriptomes originating from lower-grade glioma were indistinguishable from those of normal brain tissue, whereas transcriptomes from glioblastoma (GBM) displayed a range of abnormalities. Among these, we identified LOXL2-dependent collagen modification as a common GBM-dependent trait and demonstrated that inhibiting LOXL2 enhanced chemotherapy efficacy in both murine and human patient-derived xenograft (PDX) GBM models. Our comprehensive single-cell RNA sequencing-based molecular atlas of the human BBB, coupled with insights into its perturbations in GBM, holds promise for guiding future investigations into brain health, pathology, and therapeutic strategies.

The mechanism of hypoxia-inducible factor-1α enhancing the transcriptional activity of transferrin ferroportin 1 and regulating the Nrf2/HO-1 pathway in ferroptosis after cerebral ischemic injury

Cerebral ischemic/reperfusion (I/R) injury has high disability and morbidity. Hypoxia-inducible factor-1α (HIF-1α) may enhance the transcriptional activity of transferrin ferroportin 1 (FPN1) in regulating ferroptosis after cerebral ischemia injury (CII). In this study, cerebral I/R injury rat models were established and treated with pcDNA3.1-HIF-1α, pcDNA3.1-NC lentiviral plasmid, or ML385 (a specific Nrf2 inhibitor). Additionally, oxygen-glucose deprivation/reoxygenation (OGD/R) exposed PC12 cells were used as an in vitro model of cerebral ischemia and treated with pcDNA3.1-HIF-1α, si-FPN1, or ML385. The results elicited that cerebral I/R injury rats exhibited increased Longa scores, TUNEL and NeuN co-positive cells, Fe2+ concentration, ROS and HIF-1α levels, and MDA content, while reduced cell density and number, GSH content, and GPX4 protein level. Morphologically abnormal and disordered hippocampal neurons were also observed in CII rats. HIF-1α inhibited brain neuron ferroptosis and ameliorated I/R injury. HIF-1α alleviated OGD-induced PC12 cell ferroptosis. OGD/R decreased FPN1 protein level in PC12 cells, and HIF-1α enhanced FPN1 transcriptional activity. FPN1 knockdown reversed HIF-1α-mediated alleviation of OGD/R-induced ferroptosis. HIF-1α activated the Nrf2/HO-1 pathway by enhancing FPN1 expression and alleviating OGD/R-induced ferroptosis. Conjointly, HIF-1α enhanced the transcriptional activity of FPN1, activated the Nrf2/HO-1 pathway, and inhibited ferroptosis of brain neurons, thereby improving I/R injury in CII rats.

Robust iterative value conversion: Deep reinforcement learning for neurochip-driven edge robots

A neurochip is a device that reproduces the signal processing mechanisms of brain neurons and calculates Spiking Neural Networks (SNNs) with low power consumption and at high speed. Thus, neurochips are attracting attention from edge robot applications, which suffer from limited battery capacity. This paper aims to achieve deep reinforcement learning (DRL) that acquires SNN policies suitable for neurochip implementation. Since DRL requires a complex function approximation, we focus on conversion techniques from Floating Point NN (FPNN) because it is one of the most feasible SNN techniques. However, DRL requires conversions to SNNs for every policy update to collect the learning samples for a DRL-learning cycle, which updates the FPNN policy and collects the SNN policy samples. Accumulative conversion errors can significantly degrade the performance of the SNN policies. We propose Robust Iterative Value Conversion (RIVC) as a DRL that incorporates conversion error reduction and robustness to conversion errors. To reduce them, FPNN is optimized with the same number of quantization bits as an SNN. The FPNN output is not significantly changed by quantization. To robustify the conversion error, an FPNN policy that is applied with quantization is updated to increase the gap between the probability of selecting the optimal action and other actions. This step prevents unexpected replacements of the policy’s optimal actions. We verified RIVC’s effectiveness on a neurochip-driven robot. The results showed that RIVC consumed 1/15 times less power and increased the calculation speed by five times more than an edge CPU (quad-core ARM Cortex-A72). The previous framework with no countermeasures against conversion errors failed to train the policies. Videos from our experiments are available: https://youtu.be/Q5Z0-BvK1Tc.

Light and dopamine impact two circadian neurons to promote morning wakefulness

In both mammals and flies, circadian brain neurons orchestrate physiological oscillations and behaviors like wake and sleep-these neurons can be subdivided by morphology and by gene expression patterns. Recent single-cell sequencing studies identified 17 Drosophila circadian neuron groups. One of these includes only two lateral neurons (LNs), which are marked by the expression of the neuropeptide ion transport peptide (ITP). Although these two ITP+ LNs have long been grouped with five other circadian evening activity cells, inhibiting the two neurons alone strongly reduces morning activity, indicating that they also have a prominent morning function. As dopamine signaling promotes activity in Drosophila, like in mammals, we considered that dopamine might influence this morning activity function. Moreover, the ITP+ LNs express higher mRNA levels than other LNs of the type 1-like dopamine receptor Dop1R1. Consistent with the importance of Dop1R1, cell-specific CRISPR-Cas9 mutagenesis of this receptor in the two ITP+ LNs renders flies significantly less active in the morning, and exvivo live imaging shows Dop1R1-dependent cyclic AMP (cAMP) responses to dopamine in these two neurons. Notably, the response is more robust in the morning, reflecting higher morning Dop1R1 mRNA levels in the two neurons. As mRNA levels are not elevated in constant darkness, this suggests light-dependent upregulation of morning Dop1R1 transcript levels. Taken together with the enhanced morning cAMP response to dopamine, the data indicate how light and dopamine promote morning wakefulness in flies, mimicking the important effect of light on morning wakefulness in humans.

Morpho-Anatomical Degeneration of Dopaminergic Neurons in Adult Zebrafish Brain after Exposure to Nickel

Chronic exposure to heavy metals has been widely demonstrated to induce pathological features in different tissues and, in particular, in the central nervous system. Specific neurons, including dopaminergic neurons, were observed to be more susceptible to toxic agents. Several previous studies performed on zebrafish (Danio rerio) models observed that exposure to nickel (one of the most abundant heavy metals) induces impairment of memory and anxious-like behaviors. Nevertheless, this phenotypical evidence has not been associated with dopaminergic system damage, and no reports showing the effects of nickel on dopaminergic neurons are available. In this study, we aim to analyze the precise distribution and variation in dopaminergic neurons in adult zebrafish after chronic (96 h) exposure to nickel ions dissolved in water at different sub-lethal doses (0.4 mg L−1; 2 mg L−1 and 4 mg L−1). The effects of treatment on dopaminergic neurons were evaluated by measuring transcript and protein levels of tyrosine hydroxylase (TH), described as a dopaminergic neuron marker. As shown, the expression of the th1 and th2 genes was reduced in the entire brain of zebrafish treated with nickel. Immunostaining analysis allowed us to localize TH-expressing neurons mainly in the posterior tuberculum, where they were observed to be reduced after nickel treatment in a dose-dependent fashion. Consistently, the TUNEL assay revealed a significant increase in apoptosis of TH-expressing cells after treatment with 2 mg L−1 and 4 mg L−1 of nickel. Our findings represent the first evidence of the effect of nickel on the dopaminergic system.

Triggering Tau Fibrillization by Electroreduction: A New Tool for Studying Amyloid Diseases

The pathological aggregation of the microtubule-associated protein tau is a hallmark of various neurodegenerative disorders, including Alzheimer’s disease (AD), Pick’s disease and frontotemporal dementia. Tau protein’s reversible assembly and binding to microtubules in brain neurons are regulated by charge-neutralizing phosphorylation. Hyperphosphorylation, on the other hand, leads to irreversible formation of cytotoxic filaments. Under physiological conditions, tau remains remarkably stable, exhibiting intrinsically disordered behavior and reversible assembly. Irreversible aggregation requires specific mutations, preformed seeds or nucleating polyanionic cofactors. However, heparin-induced fibrils differ structurally from brain-derived filaments, and the presence of such cofactors can impede therapeutic agent development. We have developed a quick and easy method to generate cofactor-free filaments using heterogeneous electroreduction as a surrogate for charge-neutralization by hyperphosphorylation. We combine electrochemistry with in situ UV absorbance, circular dichroism and dynamic light scattering spectroscopies to dynamically follow tau’s conformational changes and assembly. Electroreduction of positively charged residues of the protein leads to rapid formation of b-rich structures, even at times as short as 15 minutes. The extent of assembly can be controlled by fine-tuning electroreductive potentials and electrolyte conditions. Relevance of this new method was confirmed by examining the impact of an early-onset AD-causing tau mutant and known inhibitors on aggregation kinetics. Our results demonstrate comparable effects to heparin-induced fibrils, as assessed by thioflavin-T fluorescence, dynamic light scattering, circular dichroism and electron microscopy. Low-voltage electroreduction provides a platform to study the effects of tau mutations and effectors, as well as to develop rapid assays to test how additional effectors may inhibit, disassemble or direct the trajectory of tau assembly. The versatility of our approach also suggests its potential applicability to a broader spectrum of neurodegenerative amyloid diseases.

From Blur to Brilliance: The Ascendance of Advanced Microscopy in Neuronal Cell Biology.

The intricate network of the brain's neurons and synapses poses unparalleled challenges for research, distinct from other biological studies. This is particularly true when dissecting how neurons and their functional units work at a cell biological level. While traditional microscopy has been foundational, it was unable to reveal the deeper complexities of neural interactions. However, an imaging renaissance has transformed our capabilities. Advancements in light and electron microscopy, combined with correlative imaging, now achieve unprecedented resolutions, uncovering the most nuanced neural structures. Maximizing these tools requires more than just technical proficiency. It is crucial to align research aims, allocate resources wisely, and analyze data effectively. At the heart of this evolution is interdisciplinary collaboration, where various experts come together to translate detailed imagery into significant biological insights. This review navigates the latest developments in microscopy, underscoring both the promise of and prerequisites for bending this powerful tool set to understanding neuronal cell biology.

Novel Therapeutic Horizons: SNCA Targeting in Parkinson's Disease.

Alpha-synuclein (αSyn) aggregates are the primary component of Lewy bodies, which are pathological hallmarks of Parkinson's disease (PD). The toxicity of αSyn seems to increase with its elevated expression during injury, suggesting that therapeutic approaches focused on reducing αSyn burden in neurons could be beneficial. Additionally, studies have shown higher levels of SNCA mRNA in the midbrain tissues and substantia nigra dopaminergic neurons of sporadic PD post-mortem brains compared to controls. Therefore, the regulation of SNCA expression and inhibition of αSyn synthesis could play an important role in the pathogenesis of injury, resulting in an effective treatment approach for PD. In this context, we summarized the most recent and innovative strategies proposed that exploit the targeting of SNCA to regulate translation and efficiently knock down cytoplasmatic levels of αSyn. Significant progress has been made in developing antisense technologies for treating PD in recent years, with a focus on antisense oligonucleotides and short-interfering RNAs, which achieve high specificity towards the desired target. To provide a more exhaustive picture of this research field, we also reported less common but highly innovative strategies, including small molecules, designed to specifically bind 5'-untranslated regions and, targeting secondary nucleic acid structures present in the SNCA gene, whose formation can be modulated, acting as a transcription and translation control. To fully describe the efficiency of the reported strategies, the effect of αSyn reduction on cellular viability and dopamine homeostasis was also considered.

IL-33 relieves nerve injury by mediating microglial polarization in neuromyelitis optica spectrum disorders via the IL-33/ST2 pathway

Interleukin-33 (IL-33) is a member of the interleukin-1 cytokine family. Its function in regulating microglial M1/M2 polarization in neuromyelitis optica spectrum disorder (NMOSD) is still unelucidated. To evaluate the role of IL-33 in NMOSD, we constructed NMOSD mice model by injecting purified serum IgG from AQP4-IgG seropositive NMOSD patients into experimental autoimmune encephalomyelitis (EAE) mice, and IL-33 was intraperitoneally injected into NMOSD mice 3 d before the model induction. We found that pretreatment of the NMOSD mice with IL-33 relieved brain neuron loss, and demyelination and improved the structure of axons, astrocytes, and mitochondria. In the neuronal and microglial coculture system, pretreatment with IL-33 in microglia alleviated NMOSD serum-induced inflammation and damaged morphology in cultured neurons. IL-33 transformed microglia to the M2 phenotype, and NMOSD serum promoted microglia to the M1 phenotype in cultured BV2 cells. Moreover, IL-33 influenced microglial polarity via the IL-33/ST2 pathway. IL-33 may be a novel insight useful for further developing NMOSD-targeted therapy and drug development.

Mechanism Analysis and Response of Digital Financial Inclusion to Labor Economy based on ANN and Contribution Analysis

Abstract Given the inclusiveness of digital inclusive finance (DFI) and its complex impact mechanism on the labor economy, this study uses the characteristics of adaptive and self-learning ability of artificial neural network (ANN) to simulate the process of delivering stimuli to nerve cells in the human brain through linear weighted summarization and functional mapping, and implement the optimization learning algorithm to adjust the weights in the network structure, thus completing the hierarchical analysis of index weight. At the same time, the neural network structure is used to approach the greatest extent and Garson algorithm is used for sensitivity analysis. We use data on the labor economy and digital financial inclusion in Heilongjiang, Jilin, and Liaoning provinces in China from 2011 to 2021 as a training dataset. The study found that (1) the indexes of DFI have different importance to the indexes of labor economy, among which the most important are the number and amount of insurance per capita and the proportion of the number and amount paid by digital technology, which have a normalized importance of 100 and 99.3%, further, R-square coverage is above 0.95, respectively, for labor economy indicators; (2) For different subdivided indicators, the indexes of DFI determine different significance. This study employs tools and policies related to DFI to address labor economy challenges, so as to promote the overall economic construction. This study studies the response and transmission mechanism of the concept of DFI to the labor economy, and explores the labor economy problems such as improving labor productivity and labor mismatch in the economy under its “inclusive” principle. Compared with the traditional weight analysis, it is closer to the real situation and has a stronger ability to fit the reality. In the future, the model could be rebased and measured against absolute indicators and a wider dataset could be adopted for extension to more areas.

In silico investigation of lipid-based compounds implicated in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal, currently incurable neurodegenerative disease that progressively affects the upper motor neurons in the brain and lower motor neurons in the spinal cord. A significant portion of patients exhibit abnormalities in lipid metabolism, which appear to contribute to denervation and subsequent motor neuron degeneration. This study aimed to computationally identify lipid-based compounds associated with ALS and elucidate their pathological and therapeutic roles to facilitate effective ALS diagnosis and treatment. The methodologies employed encompassed rational database searches, pharmacokinetic and target predictions, as well as docking and molecular dynamics simulations (MDS). The findings from the disease-to-lipids analysis identified 20 lipid compounds correlated with ALS, primarily categorized as potential inhibitors within the functional classes of vitamins, antibiotics, organic acids, and phytochemicals. Pharmacokinetic predictions revealed that only four compounds exhibited permeability across the blood–brain barrier, namely 4-hydroxynonenal, resveratrol, rotenone, and valproic acid. Docking simulations indicated the highest binding affinity for 4-hydroxynonenal with alkaline ceramidase 2 (−4.516 kcal/mol), resveratrol with carbonic anhydrase 6 (−7.070 kcal/mol), rotenone with cytochrome P450 2C19 (−7.378 kcal/mol), and valproic acid with glutamate carboxypeptidase 2 (−5.629 kcal/mol). Furthermore, MDS and molecular mechanics/generalized born surface area calculations demonstrated the stability and binding energies of the complexes under simulated physiological conditions. In summary, further investigation is warranted to explore the synergistic effects of resveratrol and valproic acid in ALS, the mechanisms underlying 4-hydroxynonenal adduct-assisted aggregate formation of certain enzymes in ALS, and the impact of prolonged human exposure to rotenone from marine food sources (such as fish) on the development of ALS.

Novel energy optimizer, meldonium, rapidly restores acute hypobaric hypoxia-induced brain injury by targeting phosphoglycerate kinase 1

BackgroundAcute hypobaric hypoxia-induced brain injury has been a challenge in the health management of mountaineers; therefore, new neuroprotective agents are urgently required. Meldonium, a well-known cardioprotective drug, has been reported to have neuroprotective effects. However, the relevant mechanisms have not been elucidated. We hypothesized that meldonium may play a potentially novel role in hypobaric hypoxia cerebral injury.MethodsWe initially evaluated the neuroprotection efficacy of meldonium against acute hypoxia in mice and primary hippocampal neurons. The potential molecular targets of meldonium were screened using drug-target binding Huprot™ microarray chip and mass spectrometry analyses after which they were validated with surface plasmon resonance (SPR), molecular docking, and pull-down assay. The functional effects of such binding were explored through gene knockdown and overexpression.ResultsThe study clearly shows that pretreatment with meldonium rapidly attenuates neuronal pathological damage, cerebral blood flow changes, and mitochondrial damage and its cascade response to oxidative stress injury, thereby improving survival rates in mice brain and primary hippocampal neurons, revealing the remarkable pharmacological efficacy of meldonium in acute high-altitude brain injury. On the one hand, we confirmed that meldonium directly interacts with phosphoglycerate kinase 1 (PGK1) to promote its activity, which improved glycolysis and pyruvate metabolism to promote ATP production. On the other hand, meldonium also ameliorates mitochondrial damage by PGK1 translocating to mitochondria under acute hypoxia to regulate the activity of TNF receptor-associated protein 1 (TRAP1) molecular chaperones.ConclusionThese results further explain the mechanism of meldonium as an energy optimizer and provide a strategy for preventing acute hypobaric hypoxia brain injury at high altitudes.

An ankyrin G–binding motif mediates TRAAK periodic localization at axon initial segments of hippocampal pyramidal neurons

The axon initial segment (AIS) is a critical compartment in neurons. It converts postsynaptic input into action potentials that subsequently trigger information transfer to target neurons. This process relies on the presence of several voltage-gated sodium (NaV) and potassium (KV) channels that accumulate in high densities at the AIS. TRAAK is a mechanosensitive leak potassium channel that was recently localized to the nodes of Ranvier. Here, we uncover that TRAAK is also present in AISs of hippocampal and cortical neurons in the adult rat brain as well as in AISs of cultured rat hippocampal neurons. We show that the AIS localization is driven by a C-terminal ankyrin G-binding sequence that organizes TRAAK in a 190 nm spaced periodic pattern that codistributes with periodically organized ankyrin G. We furthermore uncover that while the identified ankyrin G-binding motif is analogous to known ankyrin G-binding motifs in NaV1 and KV7.2/KV7.3 channels, it was acquired by convergent evolution. Our findings identify TRAAK as an AIS ion channel that convergently acquired an ankyrin G-binding motif and expand the role of ankyrin G to include the nanoscale organization of ion channels at the AIS.

Neurons for infant social behaviors in the mouse zona incerta.

Understanding the neural basis of infant social behaviors is crucial for elucidating the mechanisms of early social and emotional development. In this work, we report a specific population of somatostatin-expressing neurons in the zona incerta (ZISST) of preweaning mice that responds dynamically to social interactions, particularly those with their mother. Bidirectional neural activity manipulations in pups revealed that widespread connectivity of preweaning ZISST neurons to sensory, emotional, and cognitive brain centers mediates two key adaptive functions associated with maternal presence: the reduction of behavior distress and the facilitation of learning. These findings reveal a population of neurons in the infant mouse brain that coordinate the positive effects of the relationship with the mother on an infant's behavior and physiology.

Microglia rescue neurons from aggregate-induced neuronal dysfunction and death through tunneling nanotubes

Microglia are crucial for maintaining brain health and neuron function. Here, we report that microglia establish connections with neurons using tunneling nanotubes (TNTs) in both physiological and pathological conditions. These TNTs facilitate the rapid exchange of organelles, vesicles, and proteins. In neurodegenerative diseases like Parkinson's and Alzheimer's disease, toxic aggregates of alpha-synuclein (α-syn) and tau accumulate within neurons. Our research demonstrates that microglia useTNTsto extract neurons from these aggregates, restoring neuronal health. Additionally, microglia sharetheir healthy mitochondria with burdened neurons, reducing oxidative stress and normalizing gene expression. Disrupting mitochondrial function with antimycin A before TNT formation eliminates this neuroprotection. Moreover, co-culturing neurons with microglia and promoting TNT formation rescuessuppressed neuronal activity caused by α-syn or tau aggregates. Notably, TNT-mediated aggregate transfer is compromised in microglia carrying Lrrk22(Gly2019Ser) or Trem2(T66M) and (R47H)mutations, suggesting a role in the pathology of these gene variants in neurodegenerative diseases.

Differential Impact of Serotonin Signaling Methylphenidate on Young versus Adult: Insights from Behavioral and Dorsal Raphe Nucleus Neuronal Recordings from Freely Behaving Rats.

Methylphenidate (MPD) remains a cornerstone pharmacological intervention for managing ADHD, yet its increasing usage among ordinary youth and adults outside clinical contexts necessitates a thorough investigation into its developmental effects. This study seeks to simultaneously investigate the behavioral and neuronal changes within the dorsal raphe (DR) nucleus, a center of serotonergic neurons in the mammalian brain, before and after the administration of varying doses of acute and chronic MPD in freely behaving young and adult rats implanted with DR recording electrodes. Wireless neuronal and behavioral recording systems were used over 10 consecutive experimental days. Eight groups were examined: saline, 0.6, 2.5, and 10.0 mg/kg MPD for both young and adult rats. Six daily MPD injections were administered on experimental days 1 to 6, followed by a three-day washout period and MPD re-administration on experimental day 10 (ED10). The analysis of neuronal activity recorded from 504 DR neurons (DRNs) in young rats and 356 DRNs in adult rats reveals significant age-dependent differences in acute and chronic MPD responses. This study emphasizes the importance of aligning electrophysiological evaluations with behavioral outcomes following extended MPD exposure, elucidating the critical role of DRNs and serotonin signaling in modulating MPD responses and delineating age-specific variations in young versus adult rat models.

Changes in Cerebrospinal Fluid Concentrations of Selenium Species Induced by Tofersen Administration in Subjects with Amyotrophic Lateral Sclerosis Carrying SOD1 Gene Mutations.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease affecting the brain and spinal cord motor neurons. On 25 April 2023, the drug tofersen, an antisense oligonucleotide, received the US Food and Drug Administration approval for treating ALS in adults carrying mutations of the SOD1 gene. We aimed at assessing whether cerebrospinal fluid concentrations of selenium, an element of both toxicological and nutritional interest possibly involved in disease etiology and progression, are modified by tofersen administration. We determined concentrations of selenium species by anion exchange chromatography hyphenated to inductively coupled plasma-dynamic reaction cell-mass spectrometry and overall selenium by using inductively coupled plasma sector-field mass spectrometry, at baseline and 6months after active tofersen treatment in ten Italian ALS patients carrying the SOD1 gene mutation. Concentrations of total selenium and many selenium species substantially increased after the intervention, particularly of inorganic (tetravalent and hexavalent) selenium and of the organic species selenomethionine and a compound co-eluting with the selenocystine standard. Overall, these findings suggest that tofersen treatment markedly alters selenium status and probably the redox status within the central nervous system, possibly due to a direct effect on neurons and/or the blood-brain barrier. Further studies are required to investigate the biological and clinical relevance of these findings and how they might relate to the pharmacological effects of the drug and to disease progression.

Classification of Alzheimer’s Disease Based on Deep Learning Using Medical Images

Neurodegenerative disorders, notably Alzheimer’s, pose an escalating global health challenge. Marked by the degeneration of brain neurons, these conditions lead to a gradual decline in nerve cells. Worldwide, over 55 million people grapple with dementia, with Alzheimer’s prominently impacting the aging demographic. The primary hurdle to early Alzheimer’s detection is the widespread lack of awareness. The main goal is to design and implement an artificial intelligence system using deep learning (DL) to detect Alzheimer’s disease (AD) through medical images and classify them into various stages, such as non-demented, moderate dementia, mild dementia, and very mild dementia. The dataset contains 6400 magnetic resonance images in .jpg format, with standardized dimensions of 176 × 208 pixels. To demonstrate the advantages of data augmentation and transformation techniques, four scenarios were created: two without these techniques, utilizing the Adam and SGD optimizers, and two with these techniques, also employing the Adam and SGD optimizers, respectively. The main results revealed that scenarios utilizing these techniques exhibited more stable performance when validated with a new dataset. Scenario 3, using the Adam optimizer, achieved a weighted average accuracy of 91.83%, whereas scenario 4, employing the SGD optimizer, reached 87.58% accuracy. In contrast, scenarios 1 and 2, which omitted these techniques, obtained low accuracies below 55%. It is concluded that classifying AD with a DL model exceeding 90% accuracy is feasible. This is the importance of utilizing data augmentation and transformation techniques to improve generalizability to input image variations, which is a consistent factor in the healthcare sector.