Application of stimuli-responsive hydrogel in brain disease treatment.

Treating brain diseases presents significant challenges due to neuronal degeneration, inflammation, and the intricate nature of the brain. Stimuli-responsive hydrogels, designed to closely resemble the brain's extracellular matrix, have emerged as promising candidates for controlled drug delivery and tissue engineering. These hydrogels have the unique ability to encapsulate therapeutic agents and release them in a controlled manner when triggered by environmental stimuli. This property makes them particularly suitable for delivering drugs precisely to targeted areas of the brain, while minimizing collateral damage to healthy tissue. Their preclinical success in treating various brain diseases in animal studies underscores their translational potential for human brain disease treatment. However, a deeper understanding of their long-term behavior, biodistribution, and biocompatibility within the brain remains crucial. Furthermore, exploring novel hydrogel systems and therapeutic combinations is paramount for advancing towards more effective treatments. This review summarizes the latest advancements in this field over the past 5 years, specifically highlighting preclinical progress with novel stimuli-responsive hydrogels for treating brain diseases.

Exploring perceptions of genetic risk and the transmission of substance use disorders.

BACKGROUND: Substance use disorders (SUDs) have been consistently shown to exhibit moderate intergenerational continuity (1-3). While much research has examined genetic and social influences on addiction, less attention has been paid to clients' and lay persons' perceptions of genetic influences on the heritability of SUD (4) and implications for treatment. METHODS: For this qualitative study, twenty-six structured Working Model of the Child Interviews (WMCI) were conducted with mothers receiving inpatient SUD treatment. These interviews were thematically analyzed for themes related to maternal perceptions around intergenerational transmission of substance use behaviours. RESULTS: Findings show that over half of the mothers in this sample were preoccupied with their children's risk factors for addictions. Among this group, 29% spontaneously expressed concerns about their children's genetic risk for addiction, 54% shared worries about their children's propensity for addiction without mentioning the word gene or genetic. Additionally, 37% had challenges in even discussing their children's future when prompted. These concerns mapped onto internal working models of attachment in unexpected ways, with parents who were coded with balanced working models being more likely to discuss intergenerational risk factors and parents with disengaged working models displaying difficulties in discussing their child's future. CONCLUSION: This research suggests that the dominant discourse around the brain-disease model of addictions, in its effort to reduce stigma and self-blame, may have unintended downstream consequences for parents' mental models about their children's risks for future addiction. Parents receiving SUD treatment, and the staff who deliver it, may benefit from psychoeducation about the intergenerational transmission of SUD as part of treatment.

Evaluating the associations between intelligence quotient and multi-tissue proteome from the brain, CSF and plasma.

Intelligence quotient is a vital index to evaluate the ability of an individual to think rationally, learn from experience and deal with the environment effectively. However, limited efforts have been paid to explore the potential associations of intelligence quotient traits with the tissue proteins from the brain, CSF and plasma. The information of protein quantitative trait loci was collected from a recently released genome-wide association study conducted on quantification data of proteins from the tissues including the brain, CSF and plasma. Using the individual-level genotypic data from the UK Biobank cohort, we calculated the polygenic risk scores for each protein based on the protein quantitative trait locus data sets above. Then, Pearson correlation analysis was applied to evaluate the relationships between intelligence quotient traits (including 120 330 subjects for 'fluid intelligence score' and 38 949 subjects for 'maximum digits remembered correctly') and polygenic risk scores of each protein in the brain (17 protein polygenic risk scores), CSF (116 protein polygenic risk scores) and plasma (59 protein polygenic risk scores). The Bonferroni corrected P-value threshold was P < 1.30 × 10-4 (0.05/384). Finally, Mendelian randomization analysis was conducted to test the causal relationships between 'fluid intelligence score' and pre-specific proteins from correlation analysis results. Pearson correlation analysis identified significant association signals between the protein of macrophage-stimulating protein and fluid intelligence in brain and CSF tissues (P brain = 1.21 × 10-8, P CSF = 1.10 × 10-7), as well as between B-cell lymphoma 6 protein and fluid intelligence in CSF (P CSF = 1.23 × 10-4). Other proteins showed close-to-significant associations with the trait of 'fluid intelligence score', such as plasma protease C1 inhibitor (P CSF = 4.19 × 10-4, P plasma = 6.97 × 10-4), and with the trait of 'maximum digits remembered correctly', such as tenascin (P plasma = 3.42 × 10-4). Additionally, Mendelian randomization analysis results suggested that macrophage-stimulating protein (Mendelian randomization-Egger: ß = 0.54, P = 1.64 × 10-61 in the brain; ß = 0.09, P = 1.60 × 10-12 in CSF) had causal effects on fluid intelligence score. We observed functional relevance of specific tissue proteins to intelligence quotient and identified several candidate proteins, such as macrophage-stimulating protein. This study provided a novel insight to the relationship between tissue proteins and intelligence quotient traits.

A comprehensive review on modeling aspects of infusion-based drug delivery in the brain.

Brain disorders represent an ever-increasing health challenge worldwide. While conventional drug therapies are less effective due to the presence of the blood-brain barrier, infusion-based methods of drug delivery to the brain represent a promising option. Since these methods are mechanically controlled and involve multiple physical phases ranging from the neural and molecular scales to the brain scale, highly efficient and precise delivery procedures can significantly benefit from a comprehensive understanding of drug-brain and device-brain interactions. Behind these interactions are principles of biophysics and biomechanics that can be described and captured using mathematical models. Although biomechanics and biophysics have received considerable attention, a comprehensive mechanistic model for modeling infusion-based drug delivery in the brain has yet to be developed. Therefore, this article reviews the state-of-the-art mechanistic studies that can support the development of next-generation models for infusion-based brain drug delivery from the perspective of fluid mechanics, solid mechanics, and mathematical modeling. The supporting techniques and database are also summarized to provide further insights. Finally, the challenges are highlighted and perspectives on future research directions are provided. STATEMENT OF SIGNIFICANCE: Despite the immense potential of infusion-based drug delivery methods for bypassing the blood-brain barrier and efficiently delivering drugs to the brain, achieving optimal drug distribution remains a significant challenge. This is primarily due to our limited understanding of the complex interactions between drugs and the brain that are governed by principles of biophysics and biomechanics, and can be described using mathematical models. This article provides a comprehensive review of state-of-the-art mechanistic studies that can help to unravel the mechanism of drug transport in the brain across the scales, which underpins the development of next-generation models for infusion-based brain drug delivery. More broadly, this review will serve as a starting point for developing more effective treatments for brain diseases and mechanistic models that can be used to study other soft tissue and biomaterials.

Intracellular calcium dysregulation in heart and brain diseases: Insights from induced pluripotent stem cell studies.

The central nervous system (CNS) plays a role in regulating heart rate and myocardial contractility through sympathetic and parasympathetic nerves, and the heart can impact the functional equilibrium of the CNS through feedback signals. Although heart and brain diseases often coexist and mutually influence each other, the potential links between heart and brain diseases remain unclear due to a lack of reliable models of these relationships. Induced pluripotent stem cells (iPSCs), which can differentiate into multiple functional cell types, stem cell biology and regenerative medicine may offer tools to clarify the mechanisms of these relationships and facilitate screening of effective therapeutic agents. Because calcium ions play essential roles in regulating both the cardiovascular and nervous systems, this review addresses how recent iPSC disease models reveal how dysregulation of intracellular calcium might be a common pathological factor underlying the relationships between heart and brain diseases.

Neuronal Ceroid Lipofuscinoses Type 7 (CLN7)- A Case Series Reporting Cross Sectional and Retrospective Clinical Data to Evaluate Validity of Standardized Tools to Assess Disease Progression, Quality of Life, and Adaptive Skills.

Background: This study evaluated the clinical characteristics of neuronal ceroid lipofuscinosis type 7 or CLN7 disease spectrum to characterize the clinical, electrophysiologic and neuroimaging phenotypes. Methods: We performed a single-center cross sectional data collection along with retrospective medical chart review in patients with a genetic diagnosis of CLN7. This study received ethical approval by the University of Texas Southwestern Medical Center Institutional Review Board. A total of 8 patients were included between the ages of 4 to 6 years. All patients had a genetic diagnosis of CLN7 with homozygous or compound heterozygous mutations in the MFSD8 gene. The information collected includes patient demographics, developmental history, neurological events including seizures and neurodevelopmental regression along with further evaluation of brain magnetic resonance imaging and electrophysiological findings. The clinical phenotype is described through cross sectional and retrospective data collection and standardized tools assessing quality of life and functional skills. Conclusions: Our findings in this cohort of CLN7 patients indicated that development is initially normal with onset of clinical symptoms as early as two years of age. Language problems were noted prior to or at the onset of seizures in all cases. Gait problems were noted prior to seizure onset in 3 of 8 patients, and at or within 6 months after the onset of seizures in 5 of 8 patients. All patients followed a progressive course of language, motor, and neurocognitive deterioration. Congruent with the medical history, our patients had significantly low scores on adaptive abilities. Natural history data such as this can be used to support future clinical trial designs.

Heterogeneity in choice models of addiction: the role of context.

RATIONALE: Theories of addiction guide scientific progress, funding priorities, and policy development and ultimately shape how people experiencing or recovering from addiction are perceived and treated. Choice theories of addiction are heterogenous, and different models have divergent implications. This breeds confusion among laypeople, scientists, practitioners, and policymakers and reduces the utility of robust findings that have the potential to reduce the global burden of addiction-associated harms. OBJECTIVE: Here we differentiate classes of choice models and articulate a novel framing for a class of addiction models, called contextual models, which share as a first principle the influence of the environment and other contextual factors on behavior within discrete choice contexts. RESULTS: These models do not assume that all choice behaviors are voluntary, but instead that both proximal and distal characteristics of the choice environment-and particularly the benefits and costs of both drug use and non-drug alternatives-can influence behavior in ways that are outside of the awareness of the individual. From this perspective, addiction is neither the individual's moral failing nor an internal uncontrollable urge but rather is the result of environmental contingencies that reinforce the behavior. CONCLUSIONS: Contextual models have implications for guiding research, practice, and policy, including identification of novel target mechanisms while also improving existing interventions.

Microfluidic Interfaces for Chronic Bidirectional Access to the Brain.

Two-photon polymerization (TPP) is an additive manufacturing technique with micron-scale resolution that is rapidly gaining ground for a range of biomedical applications. TPP is particularly attractive for the creation of microscopic three-dimensional structures in biocompatible and noncytotoxic resins. Here, TPP is used to develop microfluidic interfaces which provide chronic fluidic access to the brain of preclinical research models. These microcatheters can be used for either convection-enhanced delivery (CED) or for the repeated collection of liquid biopsies. In a brain phantom, infusions with the micronozzle result in more localized distribution clouds and lower backflow compared to a control catheter. In mice, the delivery interface enables faster, more precise, and physiologically less disruptive fluid injections. A second microcatheter design enables repeated, longitudinal sampling of cerebrospinal fluid (CSF) over time periods as long as 250 days. Moreover, further in vivo studies demonstrate that the blood-CSF barrier is intact after chronic implantation of the sampling interface and that samples are suitable for downstream molecular analysis for the identification of nucleic acid- or peptide-based biomarkers. Ultimately, the versatility of this fabrication technique implies a great translational potential for simultaneous drug delivery and biomarker tracking in a range of human neurological diseases.

Natural sweetener glycyrrhizin protects against precocious puberty by modulating the gut microbiome.

AIMS: Precocious puberty (PP) may lead to many adverse outcomes. Recent evidence suggests that PP is a gut-brain disease. On the other hand, the use of glycyrrhizin, a natural sweetener, has become popular in the past decade. Glycyrrhizin possesses various health benefits, but its impact on PP has yet to be investigated. We aimed to explore the protective effects of glycyrrhizin against PP in both humans (observational) and animals (interventional). MATERIALS AND METHODS: In the human cohort, we investigated the association between glycyrrhizin consumption and risk of PP. In the animal experiment, we observed puberty onset after feeding danazol-induced PP rats with glycyrrizin. Blood, fecal, and hypothalamic samples were harvested to evaluate potential mechanistic pathways. We also performed a fecal microbiota transplantation to confirm to causal relationship between glycyrrhizin and PP risk. KEY FINDINGS: Glycyrrhizin exhibited a protective effect against PP in children (OR 0.60, 95%CI: 0.39-0.89, p = 0.013), primarily driven by its significance in girls, while no significant effect was observed in boys. This effect was consistent with findings in rodents. These benefits were achieved through the modulation of the gut microbiome, which functionally suppressed the hypothalamic-pituitary-gonadal axis and prevented PP progression. A fecal microbiota transplantation indicated that the causal correlation between glycyrrhizin intake and PP is mediated by the gut microbiome alterations. SIGNIFICANCE: Our findings suggest that glycyrrhizin can protect against PP by altering the gut microbiome. Long term use of glycyrrhizin is safe and tolerable. Therefore, glycyrrhizin can serve as a safe and affordable complementary therapy for PP.

The tryptophan metabolic pathway of the microbiome and host cells in health and disease.

The intricate and dynamic tryptophan (Trp) metabolic pathway in both the microbiome and host cells highlights its profound implications for health and disease. This pathway involves complex interactions between host cellular and bacteria processes, producing bioactive compounds such as 5-Hydroxytryptamine (5-HT) and kynurenine (Kyn) derivatives. Immune responses to Trp metabolites through specific receptors have been explored, highlighting the role of the aryl hydrocarbon receptor (AHR) in inflammation modulation. Dysregulation of this pathway is implicated in various diseases, such as Alzheimer's and Parkinson's diseases, mood disorders, neuronal diseases, autoimmune diseases such as multiple sclerosis (MS), and cancer. In this article, we describe the impact of the 5-HT, Trp, indole, and Trp metabolites on health and disease. Further, we review the impact of microbiome-derived Trp metabolites that affect immune responses and contribute to maintaining homeostasis, especially in an experimental autoimmune encephalitis (EAE) model of MS.

Connectional-style-guided contextual representation learning for brain disease diagnosis.

Structural magnetic resonance imaging (sMRI) has shown great clinical value and has been widely used in deep learning (DL) based computer-aided brain disease diagnosis. Previous DL-based approaches focused on local shapes and textures in brain sMRI that may be significant only within a particular domain. The learned representations are likely to contain spurious information and have poor generalization ability in other diseases and datasets. To facilitate capturing meaningful and robust features, it is necessary to first comprehensively understand the intrinsic pattern of the brain that is not restricted within a single data/task domain. Considering that the brain is a complex connectome of interlinked neurons, the connectional properties in the brain have strong biological significance, which is shared across multiple domains and covers most pathological information. In this work, we propose a connectional style contextual representation learning model (CS-CRL) to capture the intrinsic pattern of the brain, used for multiple brain disease diagnosis. Specifically, it has a vision transformer (ViT) encoder and leverages mask reconstruction as the proxy task and Gram matrices to guide the representation of connectional information. It facilitates the capture of global context and the aggregation of features with biological plausibility. The results indicate that CS-CRL achieves superior accuracy in multiple brain disease diagnosis tasks across six datasets and three diseases and outperforms state-of-the-art models. Furthermore, we demonstrate that CS-CRL captures more brain-network-like properties, and better aggregates features, is easier to optimize, and is more robust to noise, which explains its superiority in theory.

A no-fault risk compensation approach for radiation risks incurred in space travel.

In this paper we recommend an appropriate compensation approach should be established for fatality and disabilities that may occur due to space radiation exposures of government or industry workers. A brief review of compensation approaches for nuclear energy and nuclear weapons development workers in the United States and other countries is described. We then summarize issues in the application of probability of causation calculation and provide examples of probability of causation (PC) calculations for missions to the International Space Station and Earth's moon or for Mars exploration. The main focus of this paper follows with a recommendation of a no-fault approach to compensation with the creation of appropriate insurance policies funded by employers to cover all disabilities or fatality, without requiring proof of causation or restriction to conditions that imply causation. Importantly we propose that the compensation described should be managed by recourse to private insurers.

Ribosome Profiling and Mass Spectrometry Reveal Widespread Mitochondrial Translation Defects in a Striatal Cell Model of Huntington Disease.

Huntington disease (HD) is caused by an expanded polyglutamine mutation in huntingtin (mHTT) that promotes prominent atrophy in the striatum and subsequent psychiatric, cognitive deficits, and choreiform movements. Multiple lines of evidence point to an association between HD and aberrant striatal mitochondrial functions; however, the present knowledge about whether (or how) mitochondrial mRNA translation is differentially regulated in HD remains unclear. We found that protein synthesis is diminished in HD mitochondria compared to healthy control striatal cell models. We utilized ribosome profiling (Ribo-Seq) to analyze detailed snapshots of ribosome occupancy of the mitochondrial mRNA transcripts in control and HD striatal cell models. The Ribo-Seq data revealed almost unaltered ribosome occupancy on the nuclear-encoded mitochondrial transcripts involved in oxidative phosphorylation (SDHA, Ndufv1, Timm23, Tomm5, Mrps22) in HD cells. By contrast, ribosome occupancy was dramatically increased for mitochondrially encoded oxidative phosphorylation mRNAs (mt-Nd1, mt-Nd2, mt-Nd4, mt-Nd4l, mt-Nd5, mt-Nd6, mt-Co1, mt-Cytb, and mt-ATP8). We also applied tandem mass tag-based mass spectrometry identification of mitochondrial proteins to derive correlations between ribosome occupancy and actual mature mitochondrial protein products. We found many mitochondrial transcripts with comparable or higher ribosome occupancy, but diminished mitochondrial protein products, in HD. Thus, our study provides the first evidence of a widespread dichotomous effect on ribosome occupancy and protein abundance of mitochondria-related genes in HD.

Ketogenic therapy towards precision medicine for brain diseases.

Precision nutrition and nutrigenomics are emerging in the development of therapies for multiple diseases. The ketogenic diet (KD) is the most widely used clinical diet, providing high fat, low carbohydrate, and adequate protein. KD produces ketones and alters the metabolism of patients. Growing evidence suggests that KD has therapeutic effects in a wide range of neuronal diseases including epilepsy, neurodegeneration, cancer, and metabolic disorders. Although KD is considered to be a low-side-effect diet treatment, its therapeutic mechanism has not yet been fully elucidated. Also, its induced keto-response among different populations has not been elucidated. Understanding the ketone metabolism in health and disease is critical for the development of KD-associated therapeutics and synergistic therapy under any physiological background. Here, we review the current advances and known heterogeneity of the KD response and discuss the prospects for KD therapy from a precision nutrition perspective.

Constructing hierarchical attentive functional brain networks for early AD diagnosis.

Analyzing functional brain networks (FBN) with deep learning has demonstrated great potential for brain disorder diagnosis. The conventional construction of FBN is typically conducted at a single scale with a predefined brain region atlas. However, numerous studies have identified that the structure and function of the brain are hierarchically organized in nature. This urges the need of representing FBN in a hierarchical manner for more effective analysis of the complementary diagnostic insights at different scales. To this end, this paper proposes to build hierarchical FBNs adaptively within the Transformer framework. Specifically, a sparse attention-based node-merging module is designed to work alongside the conventional network feature extraction modules in each layer. The proposed module generates coarser nodes for further FBN construction and analysis by combining fine-grained nodes. By stacking multiple such layers, a hierarchical representation of FBN can be adaptively learned in an end-to-end manner. The hierarchical structure can not only integrate the complementary information from multiscale FBN for joint analysis, but also reduce the model complexity due to decreasing node sizes. Moreover, this paper argues that the nodes defined by the existing atlases are not necessarily the optimal starting level to build FBN hierarchy and exploring finer nodes may further enrich the FBN representation. In this regard, each predefined node in an atlas is split into multiple sub-nodes, overcoming the scale limitation of the existing atlases. Extensive experiments conducted on various data sets consistently demonstrate the superior performance of the proposed method over the competing methods.

Validating a minipig model of reversible cerebral demyelination using human diagnostic modalities and electron microscopy.

BACKGROUND: Inflammatory demyelinating diseases of the central nervous system, such as multiple sclerosis, are significant sources of morbidity in young adults despite therapeutic advances. Current murine models of remyelination have limited applicability due to the low white matter content of their brains, which restricts the spatial resolution of diagnostic imaging. Large animal models might be more suitable but pose significant technological, ethical and logistical challenges. METHODS: We induced targeted cerebral demyelinating lesions by serially repeated injections of lysophosphatidylcholine in the minipig brain. Lesions were amenable to follow-up using the same clinical imaging modalities (3T magnetic resonance imaging, 11C-PIB positron emission tomography) and standard histopathology protocols as for human diagnostics (myelin, glia and neuronal cell markers), as well as electron microscopy (EM), to compare against biopsy data from two patients. FINDINGS: We demonstrate controlled, clinically unapparent, reversible and multimodally trackable brain white matter demyelination in a large animal model. De-/remyelination dynamics were slower than reported for rodent models and paralleled by a degree of secondary axonal pathology. Regression modelling of ultrastructural parameters (g-ratio, axon thickness) predicted EM features of cerebral de- and remyelination in human data. INTERPRETATION: We validated our minipig model of demyelinating brain diseases by employing human diagnostic tools and comparing it with biopsy data from patients with cerebral demyelination. FUNDING: This work was supported by the DFG under Germany's Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy, ID 390857198) and TRR 274/1 2020, 408885537 (projects B03 and Z01).

Diphenyl Diselenide Attenuates Mitochondrial Damage During Initial Hypoxia and Enhances Resistance to Recurrent Hypoxia.

Hypoxia plays a significant role in the development of various cerebral diseases, many of which are associated with the potential risk of recurrence due to mitochondrial damage. Conventional drug treatments are not always effective for hypoxia-related brain diseases, necessitating the exploration of alternative compounds. In this study, we investigated the potential of diphenyl diselenide [(PhSe)2] to ameliorate locomotor impairments and mitigate brain mitochondrial dysfunction in zebrafish subjected to hypoxia. Additionally, we explored whether these improvements could confer resistance to recurrent hypoxia. Through a screening process, an appropriate dose of (PhSe)2 was determined, and animals exposed to hypoxia received a single intraperitoneal injection of 100 mg/kg of the compound or vehicle. After 1 h from the injection, evaluations were conducted on locomotor deficits, (PhSe)2 content, mitochondrial electron transport system, and mitochondrial viability in the brain. The animals were subsequently exposed to recurrent hypoxia to assess the latency time to hypoxia symptoms. The findings revealed that (PhSe)2 effectively crossed the blood-brain barrier, attenuated locomotor deficits induced by hypoxia, and improved brain mitochondrial respiration by modulating complex III. Furthermore, it enhanced mitochondrial viability in the telencephalon, contributing to greater resistance to recurrent hypoxia. These results demonstrate the beneficial effects of (PhSe)2 on both hypoxia and recurrent hypoxia, with cerebral mitochondria being a critical target of its action. Considering the involvement of brain hypoxia in numerous pathologies, (PhSe)2 should be further tested to determine its effectiveness as a potential treatment for hypoxia-related brain diseases.

Understanding immune microenvironment alterations in the brain to improve the diagnosis and treatment of diverse brain diseases.

Abnormal inflammatory states in the brain are associated with a variety of brain diseases. The dynamic changes in the number and function of immune cells in cerebrospinal fluid (CSF) are advantageous for the early prediction and diagnosis of immune diseases affecting the brain. The aggregated factors and cells in inflamed CSF may represent candidate targets for therapy. The physiological barriers in the brain, such as the blood‒brain barrier (BBB), establish a stable environment for the distribution of resident immune cells. However, the underlying mechanism by which peripheral immune cells migrate into the brain and their role in maintaining immune homeostasis in CSF are still unclear. To advance our understanding of the causal link between brain diseases and immune cell status, we investigated the characteristics of immune cell changes in CSF and the molecular mechanisms involved in common brain diseases. Furthermore, we summarized the diagnostic and treatment methods for brain diseases in which immune cells and related cytokines in CSF are used as targets. Further investigations of the new immune cell subtypes and their contributions to the development of brain diseases are needed to improve diagnostic specificity and therapy.

Transcranial photobiomodulation for brain diseases: review of animal and human studies including mechanisms and emerging trends.

The brain diseases account for 30% of all known diseases. Pharmacological treatment is hampered by the blood-brain barrier, limiting drug delivery to the central nervous system (CNS). Transcranial photobiomodulation (tPBM) is a promising technology for treating brain diseases, due to its effectiveness, non-invasiveness, and affordability. tPBM has been widely used in pre-clinical experiments and clinical trials for treating brain diseases, such as stroke and Alzheimer's disease. This review provides a comprehensive overview of tPBM. We summarize emerging trends and new discoveries in tPBM based on over one hundred references published in the past 20 years. We discuss the advantages and disadvantages of tPBM and highlight successful experimental and clinical protocols for treating various brain diseases. A better understanding of tPBM mechanisms, the development of guidelines for clinical practice, and the study of dose-dependent and personal effects hold great promise for progress in treating brain diseases.