The numerous and varied forms of neurodegenerative illnesses provide a considerable challenge to contemporary healthcare. The emergence of artificial intelligence has fundamentally changed the diagnostic picture by providing effective and early means of identifying these crippling illnesses. As a subset of computational intelligence, machine-learning algorithms have become very effective tools for the analysis of large datasets that include genetic, imaging, and clinical data. Moreover, multi-modal data integration, which includes information from brain imaging (MRI, PET scans), genetic profiles, and clinical evaluations, is made easier by computational intelligence. A thorough knowledge of the course of the illness is made possible by this consolidative method, which also facilitates the creation of predictive models for early medical evaluation and outcome prediction. Furthermore, there has been a great deal of promise shown by the use of artificial intelligence to neuroimaging analysis. Sophisticated image processing methods combined with machine learning algorithms make it possible to identify functional and structural anomalies in the brain, which often act as early indicators of neurodegenerative diseases. This chapter examines how computational intelligence plays a critical role in improving the diagnosis of neurodegenerative diseases such as Parkinson\'s, Alzheimer\'s, etc. To sum up, computational intelligence provides a revolutionary approach for improving the identification of neurodegenerative illnesses. In the battle against these difficult disorders, embracing and improving these computational techniques will surely pave the path for more individualized therapy and more therapies that are successful.

Mitochondria are singular cell organelles essential for many cellular functions, which includes responding to stress, regulating calcium levels, maintaining protein homeostasis, and coordinating apoptosis response. The vitality of cells, therefore, hinges on the optimal functioning of these dynamic organelles. Mitochondrial Quality Control Mechanisms (MQCM) play a pivotal role in ensuring the integrity and functionality of mitochondria. Perturbations in these mechanisms have been closely associated with the pathogenesis of neurodegenerative disorders such as Parkinson\'s disease, Alzheimer\'s disease, Huntington\'s disease, and amyotrophic lateral sclerosis. Compelling evidence suggests that targeting specific pathways within the MQCM could potentially offer a therapeutic avenue for rescuing mitochondrial integrity and mitigating the progression of neurodegenerative diseases. The intricate interplay of cellular stress, protein misfolding, and impaired quality control mechanisms provides a nuanced understanding of the underlying pathology. Consequently, unravelling the specific MQCM dysregulation in neurodegenerative disorders becomes paramount for developing targeted therapeutic strategies. This review delves into the impaired MQCM pathways implicated in neurodegenerative disorders and explores emerging therapeutic interventions. By shedding light on pharmaceutical and genetic manipulations aimed at restoring MQCM efficiency, the discussion aims to provide insights into novel strategies for ameliorating the progression of neurodegenerative diseases. Understanding and addressing mitochondrial quality control mechanisms not only underscore their significance in cellular health but also offer a promising frontier for advancing therapeutic approaches in the realm of neurodegenerative disorders.

BACKGROUND: Rheum tanguticum root, cataloged as \"Daehwang\" in the Korean Pharmacopeia, is rich in various anthraquinones known for their anti-inflammatory and antioxidant properties. Formulations containing Daehwang are traditionally employed for treating neurological conditions. This study aimed to substantiate the antiepileptic and neuroprotective efficacy of R. tanguticum root extract (RTE) against trimethyltin (TMT)-induced epileptic seizures and hippocampal neurodegeneration.
METHODS: The constituents of RTE were identified by ultra-performance liquid chromatography (UPLC). Experimental animals were grouped into the following five categories: control, TMT, and three TMT+RTE groups with dosages of 10, 30, and 100 mg/kg. Seizure severity was assessed daily for comparison between the groups. Brain tissue samples were examined to determine the extent of neurodegeneration and neuroinflammation using histological and molecular biology techniques. Network pharmacology analysis involved extracting herbal targets for Daehwang and disease targets for epilepsy from multiple databases. A protein-protein interaction network was built using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and pivotal targets were determined by topological analysis. Enrichment analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) tool to elucidate the underlying mechanisms.
RESULTS: The RTE formulation was found to contain sennoside A, sennoside B, chrysophanol, emodin, physcion, (+)-catechin, and quercetin-3-O-glucuronoid. RTE effectively inhibited TMT-induced seizures at 10, 30, and 100 mg/kg dosages and attenuated hippocampal neuronal decay and neuroinflammation at 30 and 100 mg/kg dosages. Furthermore, RTE significantly reduced mRNA levels of tumor necrosis factor (TNF-α), glial fibrillary acidic protein (GFAP), and c-fos in hippocampal tissues. Network analysis revealed TNF, Interleukin-1 beta (IL-1β), Interleukin-6 (IL-6), Protein c-fos (FOS), RAC-alpha serine/threonine-protein kinase (AKT1), and Mammalian target of rapamycin (mTOR) as the core targets. Enrichment analysis demonstrated significant involvement of R. tanguticum components in neurodegeneration (p = 4.35 × 10-5) and TNF signaling pathway (p = 9.94 × 10-5).
CONCLUSIONS: The in vivo and in silico analyses performed in this study suggests that RTE can potentially modulate TMT-induced epileptic seizures and neurodegeneration. Therefore, R. tanguticum root is a promising herbal treatment option for antiepileptic and neuroprotective applications.

The mammalian brain\'s complete dependence on oxygen for ATP production makes it highly susceptible to hypoxia, at high altitudes or in clinical scenarios including anemia or pulmonary disease. Hypoxia plays a crucial role in the development of various brain disorders, such as Alzheimer\'s, Parkinson\'s, and other age-related neurodegenerative diseases. On the other hand, a decrease in environmental oxygen levels, such as prolonged stays at high elevations, may have beneficial impacts on the process of ageing and the likelihood of death. Additionally, the utilization of controlled hypoxia exposure could potentially serve as a therapeutic approach for age-related brain diseases. Recent findings indicate that the involvement of HIF-1α and the NLRP3 inflammasome is of significant importance in the development of Alzheimer\'s disease. HIF-1α serves as a pivotal controller of various cellular reactions to oxygen deprivation, exerting influence on a multitude of physiological mechanisms such as energy metabolism and inflammatory responses. The NLRP3 plays a crucial role in the innate immune system by coordinating the initiation of inflammatory reactions through the assembly of the inflammasome complex. This review examines the information pertaining to the contrasting effects of hypoxia on the brain, highlighting both its positive and deleterious effects and molecular pathways that are involved in mediating these different effects. This study explores potential strategies for therapeutic intervention that focus on restoring cellular balance and reducing neuroinflammation, which are critical aspects in addressing this severe neurodegenerative condition and addresses crucial inquiries that warrant further future investigations.

This manuscript explores the use of nanostructured chitosan for intranasal drug delivery, targeting improved therapeutic outcomes in neurodegenerative diseases, psychiatric care, pain management, vaccination, and diabetes treatment. Chitosan nanoparticles are shown to enhance brain delivery, improve bioavailability, and minimize systemic side effects by facilitating drug transport across the blood-brain barrier. Despite substantial advancements in targeted delivery and vaccine efficacy, challenges remain in scalability, regulatory approval, and transitioning from preclinical studies to clinical applications. The future of chitosan-based nanomedicines hinges on advancing clinical trials, fostering interdisciplinary collaboration, and innovating in nanoparticle design to overcome these hurdles and realize their therapeutic potential.

Antibodies that can selectively remove rogue proteins in the brain are an obvious choice to treat neurodegenerative disorders (NDs), but after decades of efforts, only two antibodies to treat Alzheimer\'s disease are approved, dozens are in the testing phase, and one was withdrawn, and the other halted, likely due to efficacy issues. However, these outcomes should have been evident since these antibodies cannot enter the brain sufficiently due to the blood-brain barrier (BBB) protectant. However, all products can be rejuvenated by binding them with transferrin, preferably as smaller fragments. This model can be tested quickly and at a low cost and should be applied to bapineuzumab, solanezumab, crenezumab, gantenerumab, aducanumab, lecanemab, donanemab, cinpanemab, and gantenerumab, and their fragments. This paper demonstrates that conjugating with transferrin does not alter the binding to brain proteins such as amyloid-β (Aβ) and α-synuclein. We also present a selection of conjugate designs that will allow cleavage upon entering the brain to prevent their exocytosis while keeping the fragments connected to enable optimal binding to proteins. The identified products can be readily tested and returned to patients with the lowest regulatory cost and delays. These engineered antibodies can be manufactured by recombinant engineering, preferably by mRNA technology, as a more affordable solution to meet the dire need to treat neurodegenerative disorders effectively.

One of the most challenging and controversial issues in microbiome research is related to gut microbial metabolism and neuropsychological disorders. Psychobiotics affect human behavior and central nervous system processes via the gut-brain axis, involving neuronal, immune, and metabolic pathways. They have therapeutic potential in the treatment of several neurodegenerative and neurodevelopmental disorders such as depression, anxiety, autism, attention deficit hyperactivity disorder, Alzheimer\'s disease, Parkinson\'s disease, schizophrenia, Huntington\'s disease, anorexia nervosa, and multiple sclerosis. However, the mechanisms underlying the interaction between psychobiotics and the abovementioned diseases need further exploration. This review focuses on the relationship between gut microbiota and its impact on neurological and neurodegenerative disorders, examining the potential of psychobiotics as a preventive and therapeutic approach, summarising recent research on the gut-brain axis and the potential beneficial effects of psychobiotics, highlighting the need for further research and investigation in this area.

BACKGROUND: Recent work suggests that amyloid beta (Aβ) positron emission tomography (PET) tracer uptake shortly after injection (\"early phase\") reflects brain metabolism and perfusion. We assessed this modality in a predominantly amyloid-negative neurodegenerative condition, Parkinson\'s disease (PD), and hypothesized that early-phase 18F-florbetaben (eFBB) uptake would reproduce characteristic hypometabolism and hypoperfusion patterns associated with cognitive decline in PD.
METHODS: One hundred fifteen PD patients across the spectrum of cognitive impairment underwent dual-phase Aβ PET, structural and arterial spin labeling (ASL) magnetic resonance imaging (MRI), and neuropsychological assessments. Multiple linear regression models compared eFBB uptake to cognitive performance and ASL MRI perfusion.
RESULTS: Reduced eFBB uptake was associated with cognitive performance in brain regions previously linked to hypometabolism-associated cognitive decline in PD, independent of amyloid status. Furthermore, eFBB uptake correlated with cerebral perfusion across widespread regions.
CONCLUSIONS: EFBB uptake is a potential surrogate measure for cerebral perfusion/metabolism. A dual-phase PET imaging approach may serve as a clinical tool for assessing cognitive impairment.
UNASSIGNED: Images taken at amyloid beta (Aβ) positron emission tomography tracer injection may reflect brain perfusion and metabolism.Parkinson\'s disease (PD) is a predominantly amyloid-negative condition.Early-phase florbetaben (eFBB) in PD was associated with cognitive performance.eFBB uptake reflects hypometabolism-related cognitive decline in PD.eFBB correlated with arterial spin labeling magnetic resonance imaging measured cerebral perfusion.eFBB distinguished dementia from normal cognition and mild cognitive impairment.Findings were independent of late-phase Aβ burden.Thus, eFBB may serve as a surrogate measure for brain metabolism/perfusion.

Mutations in the DDHD2 (DDHD domain containing 2) gene cause autosomal recessive spastic paraplegia type 54 (SPG54), a rare neurodegenerative disorder characterized by the early childhood onset of progressive spastic paraplegia. DDHD2 is reported as the principal brain triacylglycerol (TAG) lipase whose dysfunction causes massive lipid droplet (LD) accumulation in the brains of SPG54 patients. However, the precise functions of DDHD2 in regulating LD catabolism are not yet fully understood. In a recent study, we demonstrate that DDHD2 interacts with multiple members of the Atg8-family proteins (MAP1LC3/LC3s, GABARAPs), which play crucial roles in lipophagy. DDHD2 possesses two LC3-interacting region (LIR) motifs that contribute to its LD-eliminating activity. Moreover, DDHD2 enhances the colocalization between LC3B and LDs to promote lipophagy. LD·ATTEC, a compound that tethers LC3 to LDs to enhance their macroautophagic/autophagic clearance, effectively counteracts DDHD2 deficiency-induced LD accumulation. These findings provide insights into the dual functions of DDHD2 as a TAG lipase and cargo receptor for lipophagy in neuronal LD catabolism, and also suggest a potential therapeutic approach for treating SPG54 patients.

Traumatic brain injuries (TBIs) can lead to long-lasting cognitive impairments, and some survivors experience cognitive decline post-recovery. Early detection of decline is important for care planning, and understanding risk factors for decline can elucidate targets for prevention. While neuropsychological testing is the gold standard approach to characterizing cognitive function, there is a need for brief, scalable tools that are capable of detecting clinically significant changes in post-TBI cognition. This study examines whether clinically significant change can be detected using the Brief Test of Adult Cognition by Telephone (BTACT) in a sample of individuals with chronic TBI and investigates whether potentially modifiable factors are associated with cognitive decline. Ninety participants aged 40 or older with complicated mild to severe TBI participated in two telephone-based study visits approximately one year apart. Demographic, head trauma exposure, comorbid medical conditions, physical and psychosocial functioning data were collected via self-report. The BTACT, a brief measure of global cognitive function, was used to assess cognitive performance across six domains. A Reliable Change Index (RCI) for quantifying clinically significant changes in BTACT performance was calculated. Results revealed cognitive decline in 10% to 27% of participants across various cognitive domains. More specifically, only depressive symptoms, including depressed affect and anhedonia, were significantly associated with cognitive decline after correcting for multiple comparisons using FDR. Other factors such as the number of blows to the head, male gender, dyspnea, increased anxiety symptoms, seizures, illicit drug use, and fewer cardiovascular comorbidities should be considered hypothesis-generating. Importantly, age was not a significant predictor of cognitive decline, which challenges the assumption that cognitive decline is solely related to the natural aging process. It suggests that there are unique factors associated with TBI that impact cognitive function, and these factors can affect individuals across the lifespan. The BTACT is a brief and sensitive tool for identifying clinically meaningful changes in cognitive function over a relatively brief period (i.e., one year) in a sample of individuals in the chronic stages of TBI (i.e., x̅=6.7 years post-TBI). Thus, the BTACT may be useful in surveillance efforts aimed at understanding and detecting decline, particularly in situations where in-person cognitive screening is impractical or unfeasible. We also identified potentially modifiable targets for the prevention of post-TBI cognitive decline. These findings can offer insights into treatment goals and preventive strategies for individuals at risk for cognitive decline, as well as help to facilitate early identification efforts.