Innovative treatments of refractory epilepsy are widely desired, for which chemogenetic technology can provide region- and cell-type-specific modulation with relative noninvasiveness. We aimed to explore the specific applications of chemogenetics for locally and remotely networks controlling hippocampal seizures. A virus coding for a modified human Gi-coupled M4 muscarinic receptor (hM4Di) on pyramidal cells was injected into either the right hippocampal CA3 or the bilateral anterior nucleus of the thalamus (ANT) in rats. After one month, seizures were induced by 4-aminopyridine (4-AP) injection into the right CA3. Simultaneously, clozapine-N-oxide (CNO) (2.5 mg/kg) or clozapine (0.1 mg/kg), the specific ligands acting on hM4Di, were injected intraperitoneally. We also set up hM4Di control and clozapine control groups to eliminate the influence of viral transfection and the ligand alone on the experimental results. For both local and remote controls, the mean seizure duration was significantly reduced upon ligand application in the experimental groups. Seizure frequency, on the other hand, only showed a significant decrease in local control, with a lower frequency in the clozapine group than in the CNO group. Both the effects of CNO and clozapine were time-dependent, and clozapine was faster than CNO in local seizure control. This study shows the potency of chemogenetics to attenuate hippocampal seizures locally or remotely by activating the transfected hM4Di receptor with CNO or clozapine. ANT is suggested as a potentially safe chemogenetic application target in the epileptic network for focal hippocampal seizures.

Our previous research has shown that prenatal methcathinone exposure affects the neurodevelopment and neurobehavior of adolescent offspring, but the study on whether these findings continue into adulthood is limited. This study aims to explore the effects of prenatal methcathinone exposure on anxiety-like behavior, learning and memory abilities, as well as serum 5-hydroxytryptamine and dopamine concentrations in adult offspring. Pregnant rats were injected daily with methcathinone between the 7th and 20th days of gestation. The neurobehavioral performance of both male and female adult offspring rats was evaluated by neurobehavioral tests, including open-field tests, Morris water maze (MWM) tests, and novel object recognition (NOR) tests. The levels of 5-hydroxytryptamine and dopamine concentration in rat serum were detected by ELISA. Significant differences were found in the length of center distance and time of center duration in the open-field test, as well as the times of crossing the platform in the MWM test, between the prenatal methcathinone exposure group and the control group. Results of the NOR test showed that adult offspring rats exposed to methcathinone need more time to discriminate the novel object. No gender differences were detected in the neurobehavioral tests. The serum concentrations of 5-hydroxytryptamine and dopamine in rats exposed to methcathinone prenatally were lower than that in the control group, and the serum dopamine concentration was independent of gender in each group. Prenatal methcathinone exposure affects the neurological behavior in adult offspring, and 5-hydroxytryptamine and dopamine might be involved in the process.

Recombinant antibody fragments are promising alternatives to full-length immunoglobulins, creating big opportunities for the pharmaceutical industry. Nowadays, antibody fragments such as antigen-binding fragments (Fab), single-chain fragment variable (scFv), single-domain antibodies (sdAbs), and bispecific antibodies (bsAbs) are being evaluated as diagnostics or therapeutics in preclinical models and in clinical trials. Immunotherapy approaches, including passive transfer of protective antibodies, have shown therapeutic efficacy in several animal models of Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal dementia (FTD), Huntington's disease (HD), transmissible spongiform encephalopathies (TSEs) and multiple sclerosis (MS). There are various antibodies approved by the Food and Drug Administration (FDA) for treating multiple sclerosis and two amyloid beta-specific humanized antibodies, Aducanumab and Lecanemab, for AD. Our previous review summarized data on recombinant antibodies evaluated in pre-clinical models for immunotherapy of neurodegenerative diseases. Here, we explore recent studies in this fascinating research field, give an update on new preventive and therapeutic applications of recombinant antibody fragments for neurological disorders and discuss the potential of antibody fragments for developing novel approaches for crossing the blood-brain barrier (BBB) and targeting cells and molecules of interest in the brain.

Epilepsy is a neurological disease with no defined cause, characterized by recurrent epileptic seizures. These occur due to the dysregulation of excitatory and inhibitory neurotransmitters in the central nervous system (CNS). Psychopharmaceuticals have undesirable side effects; many patients require more than one pharmacotherapy to control crises. With this in mind, this work emphasizes the discovery of new substances from natural products that can combat epileptic seizures. Using in silico techniques, this review aims to evaluate the antiepileptic and multi-target activity of phenylpropanoid derivatives. Initially, ligand-based virtual screening models (LBVS) were performed with 468 phenylpropanoid compounds to predict biological activities. The LBVS were developed for the targets alpha- amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA), voltage-gated calcium channel Ttype (CaV), gamma-aminobutyric acid A (GABAA), gamma-aminobutyric acid transporter type 1 (GAT-1), voltage-gated potassium channel of the Q family (KCNQ), voltage-gated sodium channel (NaV), and N-methyl D-aspartate (NMDA). The compounds that had good results in the LBVS were analyzed for the absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters, and later, the best molecules were evaluated in the molecular docking consensus. The TR430 compound showed the best results in pharmacokinetic parameters; its oral absorption was 99.03%, it did not violate any Lipinski rule, it showed good bioavailability, and no cytotoxicity was observed either from the molecule or from the metabolites in the evaluated parameters. TR430 was able to bind with GABAA (activation) and AMPA (inhibition) targets and demonstrated good binding energy and significant interactions with both targets. The studied compound showed to be a promising molecule with a possible multi-target activity in both fundamental pharmacological targets for the treatment of epilepsy.

Psychiatric and mood disorders may play an important role in the development and persistence of irritable bowel syndrome (IBS). Previously, we hypothesized that stress-induced implicit memories may persist throughout life via epigenetic processes in the enteric nervous system (ENS), independent of the central nervous system (CNS). These epigenetic memories in the ENS may contribute to developing and perpetuating IBS. Here, we further elaborate on our earlier hypothesis. That is, during pregnancy, maternal prenatal stresses perturb the HPA axis and increase circulating cortisol levels, which can affect the maternal gut microbiota. Maternal cortisol can cross the placental barrier and increase cortisol-circulating levels in the fetus. This leads to dysregulation of the HPA axis, affecting the gut microbiota, microbial metabolites, and intestinal permeability in the fetus. Microbial metabolites, such as short-chain fatty acids (which also regulate the development of fetal ENS), can modulate a range of diseases by inducing epigenetic changes. These mentioned processes suggest that stress-related, implicit, long-term epigenetic memories may be programmed into the fetal ENS during pregnancy. Subsequently, this implicit epigenetic stress information from the fetal ENS could be conveyed to the CNS through the bidirectional microbiota-gut-brain axis (MGBA), leading to perturbed functional connectivity among various brain networks and the dysregulation of affective and pain processes.

Schizophrenia (SCZ) usually begins in early adult life. The underlying molecular mechanisms of SCZ remain unclear. There is evidence for the involvement of abnormalities in metabolic and endocrine systems in SCZ, even in drug-naïve first-episode schizophrenia patients (DNFES). However, the association between impaired regulation of glucose metabolism and sex hormones was not studied in SCZ. This study aimed to evaluate the interrelationship between sex hormones and high fasting glucose levels in male DNFES patients. A total of 99 patients with SCZ were recruited, and fasting glucose, fasting insulin, the insulin resistance index (HOMA-IR), and sex hormones were measured. We found that some male patients with SCZ had abnormal levels in glucose metabolism parameters and gonadal hormones that were not within the normal range. Linear regression analysis adjusted for age, waist circumference, and body mass index showed that testosterone levels were negatively associated with fasting insulin in male patients (β = -0.21, t = -2.2, p = 0.03). Our findings confirm the abnormalities in glucose metabolism parameters and gonadal hormones at the onset of the illness in male DNFES patients with SCZ. In addition, there was an interaction effect between abnormal glucose metabolism and sex hormones in male patients.

Brain disorders are one of the major global mortality issues, and their early detection is crucial for healing. Machine learning, specifically deep learning, is a technology that is increasingly being used to detect and diagnose brain disorders. Our objective is to provide a quantitative bibliometric analysis of the field to inform researchers about trends that can inform their Research directions in the future. We carried out a bibliometric analysis to create an overview of brain disorder detection and diagnosis using machine learning and deep learning. Our bibliometric analysis includes 1550 articles gathered from the Scopus database on automated brain disorder detection and diagnosis using machine learning and deep learning published from 2015 to May 2023. A thorough bibliometric análisis is carried out with the help of Biblioshiny and the VOSviewer platform. Citation analysis and various measures of collaboration are analyzed in the study. According to a study, maximum research is reported in 2022, with a consistent rise from preceding years. The majority of the authors referenced have concentrated on multiclass classification and innovative convolutional neural network models that are effective in this field. A keyword analysis revealed that among the several brain disorder types, Alzheimer's, autism, and Parkinson's disease had received the greatest attention. In terms of both authors and institutes, the USA, China, and India are among the most collaborating countries. We built a future research agenda based on our findings to help progress research on machine learning and deep learning for brain disorder detection and diagnosis. In summary, our quantitative bibliometric analysis provides useful insights about trends in the field and points them to potential directions in applying machine learning and deep learning for brain disorder detection and diagnosis.</P>.

The pervasiveness and mortality associated with methamphetamine abuse have doubled during the past decade, suggesting a possible worldwide substance use crisis. Epitomizing the pathophysiology and toxicology of methamphetamine abuse proclaims severe signs and symptoms of neurotoxic and neurobehavioral manifestations in both humans and animals. Most importantly, chronic use of this drug enhances the probability of developing neurodegenerative diseases manifolds. Parkinson's disease is one such neurological disorder, which significantly and evidently not only shares a number of toxic pathogenic mechanisms induced by methamphetamine exposure but is also interlinked both structurally and genetically. Methamphetamine-induced neurodegeneration involves altered dopamine homeostasis that promotes the aggregation of α-synuclein protofibrils in the dopaminergic neurons and drives these neurons to make them more vulnerable to degeneration, as recognized in Parkinson's disease. Moreover, the pathologic mechanisms such as mitochondrial dysfunction, oxidative stress, neuroinflammation and decreased neurogenesis detected in methamphetamine abusers dramatically resemble to what is observed in Parkinson's disease cases. Therefore, the present review comprehensively cumulates a holistic illustration of various genetic and molecular mechanisms putting across the notion of how methamphetamine administration and intoxication might lead to Parkinson's disease-like pathology and Parkinsonism.

Memory refers to the imprint accumulated in the brain by life experiences and represents the basis for humans to engage in advanced psychological activities such as thinking and imagination. Previously, research activities focused on memory have always targeted neurons. However, in addition to neurons, astrocytes are also involved in the encoding, consolidation, and extinction of memory. In particular, astrocytes are known to affect the recruitment and function of neurons at the level of local synapses and brain networks. Moreover, the involvement of astrocytes in memory and memory-related disorders, especially in Alzheimer's disease (AD) and post-traumatic stress disorder (PTSD), has been investigated extensively. In this review, we describe the unique contributions of astrocytes to synaptic plasticity and neuronal networks and discuss the role of astrocytes in different types of memory processing. In addition, we also explore the roles of astrocytes in the pathogenesis of memory-related disorders, such as AD, brain aging, PTSD and addiction, thus suggesting that targeting astrocytes may represent a potential strategy to treat memory-related neurological diseases. In conclusion, this review emphasizes that thinking from the perspective of astrocytes will provide new ideas for the diagnosis and therapy of memory-related neurological disorders.