Degenerative Brain Disease Research Articles

Glaucoma - A Window into Future Neurodegeneration

Glaucoma is the leading cause of irreversible blindness in the world. Recent studies propose glaucoma to be a neurodegenerative disease due to overlap with diagnoses such as Alzheimer’s, Parkinson’s, and amyotrophic lateral sclerosis. Emerging reports have linked glaucoma as a risk factor for future certain neurodegenerative diseases, however, results have been conflicting. The development of degenerative brain disease consists of both a genetic and environmental component. If diagnosed with glaucoma, patients should take additional measurements to reduce the likelihood of developing additional nerve cell loss.

Sphingomyelin Inhibits Hydrolytic Activity of Heterodimeric PLA2 in Model Myelin Membranes: Pharmacological Relevance.

In this work, the heterodimeric phospholipase A2, HDP-2, from viper venom was investigated for its hydrolytic activity in model myelin membranes as well as for its effects on intermembrane exchange of phospholipids (studied by phosphorescence quenching) and on phospholipid polymorphism (studied by 1H-NMR spectroscopy) to understand the role of sphingomyelin (SM) in the demyelination of nerve fibers. By using well-validated in vitro approaches, we show that the presence of SM in model myelin membranes leads to a significant inhibition of the hydrolytic activity of HDP-2, decreased intermembrane phospholipid exchange, and reduced phospholipid polymorphism. Using AutoDock software, we show that the NHδ+ group of the sphingosine backbone of SM binds to Tyr22(C=Opbδ-) of HDP-2 via a hydrogen bond which keeps only the polar head of SM inside the HDP-2's active center and positions the sn-2 acyl ester bond away from the active center, thus making it unlikely to hydrolyze the alkyl chains at the sn-2 position. This observation strongly suggests that SM inhibits the catalytic activity of HDP-2 by blocking access to other phospholipids to the active center of the enzyme. Should this observation be verified in further studies, it would offer a tantalizing opportunity for developing effective pharmaceuticals to stop the demyelination of nerve fibers by aberrant PLA2s with overt activity - as observed in brain degenerative diseases - by inhibiting SM hydrolysis and/or facilitating SM synthesis in the myelin sheath membrane.

Nasal lymphatic obstruction of CSF drainage as a possible cause of Alzheimer's disease and dementia.

Alzheimer's disease, the most common form of dementia among older adults, slowly destroys memory and thinking skills. In recent years, scientists have made tremendous progress in understanding Alzheimer's disease, still, they do not yet fully understand what causes the disease. This article proposes a novel etiology for Alzheimer's disease. Our hypothesis developed from a review of nuclear medicine scans, in which the authors observed a significant increase in nasal turbinate vasodilation and blood pooling in patients with hypertension, sleep apnea, diabetes and/or obesity, all risk factors for Alzheimer's disease. The authors propose that nasal turbinate vasodilation and resultant blood pooling lead to the obstruction of normal nasal lymphatic clearance of cerebrospinal fluid and its waste products from the brain. The nasal turbinate vasodilation, due to increased parasympathetic activity, occurs alongside the well-established increased sympathetic activity of the cardiovascular system as seen in patients with hypertension. The increased parasympathetic activity is likely due to an autonomic imbalance secondary to the increase in worldwide consumption of highly processed food associated with dysregulation of the glucose regulatory system. The authors' hypothesis offers a novel mechanism and a new paradigm for the etiology of Alzheimer's disease and helps explain the rapid worldwide rise in the disease and other dementias which are expected to double in the next 20 years. This new paradigm provides compelling evidence for the modulation of the parasympathetic nervous system as a novel treatment strategy for Alzheimer's disease and other degenerative brain diseases, specifically targeting nasal turbinate lymphatic flow.

Natural Products and Their Neuroprotective Effects in Degenerative Brain Diseases: A Comprehensive Review.

As the global population ages, the incidence of neurodegenerative diseases such as Alzheimer's and Parkinson's is rapidly rising. These diseases present a significant public health challenge, as they severely impair cognitive and motor functions, ultimately leading to a substantial reduction in quality of life and placing a heavy burden on healthcare systems worldwide. Although several therapeutic agents have been developed to manage the symptoms of these diseases, their effectiveness is often limited, and there remains an urgent need for preventive strategies. Growing evidence indicates that bioactive compounds from natural products possess neuroprotective properties through antioxidant and anti-inflammatory effects, modulating key pathways such as phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) and brain-derived neurotrophic factor-tropomyosin receptor kinase B-cAMP response element-binding protein (BDNF-TrkB-CREB), which are crucial for neuronal survival. These compounds may also reduce amyloid-beta and tau pathology, as well as enhance cholinergic neurotransmission by inhibiting acetylcholinesterase activity. By targeting oxidative stress, neuroinflammation, and neurodegeneration, natural products offer a promising approach for both prevention and treatment. These findings suggest that natural products may be promising for preventing and treating neurodegenerative diseases. This review aims to explore the pathogenesis of neurodegenerative diseases, the limitations of current therapies, and the potential role of natural products as therapeutic agents.

Biomarkers of Parkinson's disease in perspective of early diagnosis and translation of neurotrophic therapies.

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by progressive loss of dopamine neurons and aberrant deposits of alpha-synuclein (α-syn) in the brain. The symptomatic treatment is started after the onset of motor manifestations in a late stage of the disease. Preclinical studies with neurotrophic factors (NTFs) show promising results of disease-modifying neuroprotective or even neurorestorative effects. Four NTFs have entered phase I-II clinical trials with inconclusive outcomes. This is not surprising because the preclinical evidence is from acute early-stage disease models, but the clinical trials included advanced PD patients. To conclude the value of NTF therapies, clinical studies should be performed in early-stage patients with prodromal symptoms, that is, before motor manifestations. In this review, we summarize currently available diagnostic and prognostic biomarkers that could help identify at-risk patients benefiting from NTF therapies. Focus is on biochemical and imaging biomarkers, but also other modalities are discussed. Neuroimaging is the most important diagnostic tool today, but α-syn imaging is not yet viable. Modern techniques allow measuring various forms of α-syn in cerebrospinal fluid, blood, saliva, and skin. Digital biomarkers and artificial intelligence offer new means for early diagnosis and longitudinal follow-up of degenerative brain diseases.

Identification of diffusion, kurtosis, and propagator MRI markers of Alzheimer’s disease pathology in post-mortem human tissue

Abstract Alzheimer’s disease (AD) is an irreversible degenerative brain disease affecting 6.7 million Americans and while the hallmark AD pathologies of plaques and tangles follow a stereotyped progression during the course of the disease, clinical markers for early diagnosis are lacking and approximately 20% of all AD cases are ultimately misdiagnosed. Conventional clinical MRI is capable of reporting severe brain atrophy, but fails to recognize earlier biomarkers associated with more subtle cellular and molecular changes. Microstructural Magnetic Resonance Imaging (MRI) techniques are promising to address this challenge and may sensitively detect and distinguish tissue degeneration, tauopathies, and beta amyloid plaques to improve accuracy of diagnosis and enable early detection. The objective of this study was to identify and compare the most promising microstructural markers of AD pathology over a range of diffusion and relaxometry-based MRI techniques from conventional to advanced. To accomplish this, we performed MRI microscopy of post-mortem human temporal lobe specimens (n = 14) at high resolution and image quality and evaluated the relative influence of metrics across multiple microstructural MRI frameworks using principal component analysis (PCA). We performed additional correlation analysis between metrics identified by PCA and clinical neuropathology scores of Braak stage and plaque and tangle load. Hippocampal diffusion and restriction metrics contributed most to the first principal component, and the correlation with Braak score was positive for diffusivity and negative for restriction metrics. Additionally, the MAP-MRI propagator anisotropy (PA) metric of microscale anisotropy was strongly and negatively correlated with AD pathology while the conventional fractional anisotropy (FA) metric showed little or no correspondence and there was not a strong association between FA and PA by PCA. Entorhinal cortex findings were minimal except for reported increases in restriction due to plaque content. Taken together, our findings suggest that microstructural MRI metrics of restriction and diffusion are most prominent and may reflect degenerative processes in AD brain tissue and that microscale anisotropy may be more advantageous than conventional FA for the detection of subtle and earlier cellular changes in AD.

On propagation in networks, promising models beyond network diffusion to describe degenerative brain diseases and traumatic brain injuries.

Introduction: Connections among neurons form one of the most amazing and effective network in nature. At higher level, also the functional structures of the brain is organized as a network. It is therefore natural to use modern techniques of network analysis to describe the structures of networks in the brain. Many studies have been conducted in this area, showing that the structure of the neuronal network is complex, with a small-world topology, modularity and the presence of hubs. Other studies have been conducted to investigate the dynamical processes occurring in brain networks, analyzing local and large-scale network dynamics. Recently, network diffusion dynamics have been proposed as a model for the progression of brain degenerative diseases and for traumatic brain injuries. Methods: In this paper, the dynamics of network diffusion is re-examined and reaction-diffusion models on networks is introduced in order to better describe the degenerative dynamics in the brain. Results: Numerical simulations of the dynamics of injuries in the brain connectome are presented. Different choices of reaction term and initial condition provide very different phenomenologies, showing how network propagation models are highly flexible. Discussion: The uniqueness of this research lies in the fact that it is the first time that reaction-diffusion dynamics have been applied to the connectome to model the evolution of neurodegenerative diseases or traumatic brain injury. In addition, the generality of these models allows the introduction of non-constant diffusion and different reaction terms with non-constant parameters, allowing a more precise definition of the pathology to be studied.

Nasal turbinate lymphatic obstruction: a proposed new paradigm in the etiology of essential hypertension.

Hypertension affects an estimated 1.3 billion people worldwide and is considered the number one contributor to mortality via stroke, heart failure, renal failure, and dementia. Although the physiologic mechanisms leading to the development of essential hypertension are poorly understood, the regulation of cerebral perfusion has been proposed as a primary cause. This article proposes a novel etiology for essential hypertension. Our hypothesis developed from a review of nuclear medicine scans, where the authors observed a significantly abnormal increase in nasal turbinate vasodilation in hypertensive patients using quantitative region of interest analysis. The authors propose that nasal turbinate vasodilation and resultant blood pooling obstruct the flow of cerebrospinal fluid passing through nasal turbinate lymphatics, thereby increasing intracranial pressure. The authors discuss the glymphatic/lymphatic clearance system which is impaired with age, and at which time hypertension also develops. The increased intracranial pressure leads to compensatory hypertension via Cushing's mechanism, i.e., the selfish brain hypothesis. The nasal turbinate vasodilation, due to increased parasympathetic activity, occurs simultaneously along with the well-established increased sympathetic activity of the cardiovascular system. The increased parasympathetic activity is likely due to an autonomic imbalance secondary to the increase in worldwide consumption of processed food. This hypothesis explains the rapid worldwide rise in essential hypertension in the last 50 years and offers a novel mechanism and a new paradigm for the etiology of essential hypertension. This new paradigm offers compelling evidence for the modulation of parasympathetic nervous system activity as a novel treatment strategy, specifically targeting nasal turbinate regulation, to treat diseases such as hypertension, idiopathic intracranial hypertension, and degenerative brain diseases. The proposed mechanism of essential hypertension presented in this paper is a working hypothesis and confirmatory studies will be needed.

Fine semantic segmentation of hands for human functional pattern recognition in IADLs using deep learning

AbstractBackgroundAlzheimer’s Disease (AD) is an irreversible degenerative brain disease and the most common cause of dementia, in the elderly population (age 65 and above) although people younger may develop the disease (Clemmensen, 2020). AD is characterized by impairment in behavior and cognition which eventually obstruct the Instrumental Activities of Daily Living (IADL) (Kumar, 2022). Researchers have predicted functional capacity by assessing IADL as they are strongly associated with cognitive impairment. With the availability of big data and public repositories of multimedia data such as images and videos, artificial intelligence algorithms have been used in classifying and making informed decisions that could help in disease prediction and monitoring. In the context of early diagnosis of Alzheimer, researchers have worked with machine learning techniques applied to neuroimaging for AD classification (Lama, 2021). Researchers and practitioners often use Activity of Daily Living to monitor independent‐living senior citizens’ self‐care ability, wellness status, and disease progression (Zhu, 2021). Automating the assessments of IADL will ease the evaluation of functional and cognitive function and strengthen the prediction of AD.MethodOur work approaches the timely detection and diagnosis of AD by exploring the deficiency in hand dexterity and visuospatial skills while performing IADL using egocentric videos. Therefore, in this work, we propose a fine semantic segmentation of hands, optimizing the predictions at the level of the relationship between pixels in a deep learning method. We trained the optimized RefineNet‐Pix convolutional neural network, obtaining a higher accuracy in the segmentation of semantic maps of hands.ResultsWith the optimization of RefineNet‐Pix we obtained an accuracy higher than 87.9% (Urooj, 2018) in the semantic segmentation of hands. By integrating the RefineNet‐Pix results to the base model for human functional pattern recognition, we obtain an accuracy higher than 74% with respect to the base model (Yemisi, 2022).ConclusionThe optimized RefineNet‐Pix model segments pixel‐wise the hand regions in egocentric videos, providing hand motion information that can be used to classify impairment based on human functional patterns. Optimization of these models is a way forward in building a technological device for the support of Alzheimer’s diagnosis.

Fine semantic segmentation of hands for human functional pattern recognition in IADLs using deep learning

AbstractBackgroundAlzheimer’s Disease (AD) is an irreversible degenerative brain disease and the most common cause of dementia, in the elderly population (age 65 and above) although people younger may develop the disease (Clemmensen, 2020). AD is characterized by impairment in behavior and cognition which eventually obstruct the Instrumental Activities of Daily Living (IADL) (Kumar, 2022). Researchers have predicted functional capacity by assessing IADL as they are strongly associated with cognitive impairment. With the availability of big data and public repositories of multimedia data such as images and videos, artificial intelligence algorithms have been used in classifying and making informed decisions that could help in disease prediction and monitoring. In the context of early diagnosis of Alzheimer, researchers have worked with machine learning techniques applied to neuroimaging for AD classification (Lama, 2021). Researchers and practitioners often use Activity of Daily Living to monitor independent‐living senior citizens’ self‐care ability, wellness status, and disease progression (Zhu, 2021). Automating the assessments of IADL will ease the evaluation of functional and cognitive function and strengthen the prediction of AD.MethodOur work approaches the timely detection and diagnosis of AD by exploring the deficiency in hand dexterity and visuospatial skills while performing IADL using egocentric videos. Therefore, in this work, we propose a fine semantic segmentation of hands, optimizing the predictions at the level of the relationship between pixels in a deep learning method. We trained the optimized RefineNet‐Pix convolutional neural network, obtaining a higher accuracy in the segmentation of semantic maps of hands.ResultWith the optimization of RefineNet‐Pix we obtained an accuracy higher than 87.9% (Urooj, 2018) in the semantic segmentation of hands. By integrating the RefineNet‐Pix results to the base model for human functional pattern recognition, we obtain an accuracy higher than 74% with respect to the base model (Yemisi, 2022).ConclusionThe optimized RefineNet‐Pix model segments pixel‐wise the hand regions in egocentric videos, providing hand motion information that can be used to classify impairment based on human functional patterns. Optimization of these models is a way forward in building a technological device for the support of Alzheimer’s diagnosis.

Closing the sex/gender gap in dementia: homing in on the vasculature (biomarkers)

AbstractAs we move toward precision medicine approaches, we cannot continue to pursue a one model fits all. Sex differences in brain aging and degeneration have been reported across the spectrum of research methodologies from human epidemiological studies and drug trials to model systems of degenerative brain disease. Blood proteomic biomarkers combined with clinical data can provide useful multi‐modal disease models in humans to uncover important biological associations with relevance to human disease. Small vessel disease in aging or AD is prevalent in the aging populations and represents a common and important risk factor for cognitive impairment. Dysregulated angiogenesis is emerging as a relevant pathology in SVD‐related vascular cognitive impairment with potential for therapeutic modulation. Recent work by our group and others is suggesting that the association of plasma markers of angiogenesis with clinical outcomes is sex dimorphic. Results demonstrate several age and sex‐dependent associations between groups of markers that capture both beneficial and pathological aspects of angiogenesis in aging. Much remains to be uncovered regarding underlying mechanisms, interactions with neurodegenerative pathologies, and ideal windows for sex‐informed therapeutic interventions on angiogenesis. However, the emerging body of work on sex differences regarding angiogenesis in aging, AD and other neurodegenerative disorders, represents a critical first step toward demonstrating the relevance of sex/gender to therapeutically oriented studies of vascular pathologies in dementia‐causing diseases.

In pursuit of degenerative brain disease diagnosis: Dementia biomarkers detected by DNA aptamer-attached portable graphene biosensor.

Dementia is a brain disease which results in irreversible and progressive loss of cognition and motor activity. Despite global efforts, there is no simple and reliable diagnosis or treatment option. Current diagnosis involves indirect testing of commonly inaccessible biofluids and low-resolution brain imaging. We have developed a portable, wireless readout-based Graphene field-effect transistor (GFET) biosensor platform that can detect viruses, proteins, and small molecules with single-molecule sensitivity and specificity. We report the detection of three important amyloids, namely, Amyloid beta (Aβ), Tau (τ), and α-Synuclein (αS) using DNA aptamer nanoprobes. These amyloids were isolated, purified, and characterized from the autopsied brain tissues of Alzheimer's Disease (AD) and Parkinson's Disease (PD) patients. The limit of detection (LoD) of the sensor is 10 fM, 1-10 pM, 10-100 fM for Aβ, τ, and αS, respectively. Synthetic as well as autopsied brain-derived amyloids showed a statistically significant sensor response with respect to derived thresholds, confirming the ability to define diseased vs. nondiseased states. The detection of each amyloid was specific to their aptamers; Aβ, τ, and αS peptides when tested, respectively, with aptamers nonspecific to them showed statistically insignificant cross-reactivity. Thus, the aptamer-based GFET biosensor has high sensitivity and precision across a range of epidemiologically significant AD and PD variants. This portable diagnostic system would allow at-home and POC testing for neurodegenerative diseases globally.

Get your head out of the game: framing of sportswomen and concussions

ABSTRACT One of the major sports stories to garner headlines in the past few years has been the effects of concussions on football players. None has elicited more headlines than a Boston University study released in June 2017 that diagnosed 117 out of 202 former football players Chronic Traumatic Encephalopathy (CTE), the degenerative brain disease which is caused by repeated head trauma and concussions. Recent studies, however, show that sportswomen may suffer from more concussions. In various longitudinal studies across multiple platforms, scholars have found that media coverage of sportswomen has declined. It stands to reason that reporting of health issues affecting them would mirror these results as well. This study employed a framing analysis of how many stories appeared in online national newspapers and sports sites about sportswomen and concussions in 2017 and after the FIFA Women’s World Cup in 2019. The lack of reporting demonstrates journalism’s continuing role in upholding a patriarchal system and perpetuating hegemonic masculinity in society.

Pearls & Oy-sters: Familial Verbal Auditory Agnosia Due to C9orf72 Repeat Expansion.

Chromosome 9 open reading frame 72 (C9orf72) gene pathogenic variants have been typically associated with frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS), but recent studies suggest their involvement in other disorders. This report describes a family with an autosomal dominant pattern of inheritance of progressive verbal auditory agnosia due to GGGGCC repeat expansion in C9orf72. A 60-year-old right-handed male truck driver presented with slowly progressive poor speech perception for 8 years, which became most troublesome when receiving verbal orders over the phone. He had difficulty recognizing single-syllable spoken words beyond his hearing loss but had no problem understanding complex written language. He had a heterozygous pathogenic variant carrying 160 hexanucleotide repeats in the C9orf72 gene. His family history included his deceased mother with similar symptoms that had progressed over 30 years, as well as his older brother and youngest sister who experienced speech perception difficulty beginning in their early fifties. His asymptomatic younger brother had a heterozygous 2 repeat in the C9orf72 gene, while his symptomatic youngest sister had a heterozygous 159 repeat. The patient and his sister exhibited more pronounced cortical thinning in the frontotemporoparietal areas. The discrepancy observed between the distribution of atrophy and the presentation of symptoms in patients with C9orf72 pathogenic repeat expansion may be attributable to the slow progression of their clinical course over time. The variable symptom presentation of C9orf72 pathogenic repeat expansion highlights the importance of considering this pathogenic variant as a potential cause of autosomal dominant degenerative brain diseases beyond FTD and ALS.

Applications and Considerations for Microfluidic Systems To Model the Blood-Brain Barrier.

In a myriad of developmental and degenerative brain diseases, characteristic pathological biomarkers are often associated with cerebral blood flow and vasculature. However, the relationship between vascular dysfunction and markers of brain disease is not well-defined. Additionally, it is difficult to deliver effective therapeutics to the brain due to the highly regulated blood-brain barrier (BBB) at the microvasculature interface of the brain. This Review first covers the need for modeling the BBB and the challenges of modeling the BBB. In vitro models of the BBB enable the study of the relationship between vascular dysfunction, BBB function, and disease progression and can serve as a platform to screen therapeutics. In particular, microfluidic-based in vitro BBB models are useful for studying brain vasculature as they support cell culture within the presence of continuous perfusion, which mirrors the in vivo flow and associated stress conditions in the brain. Early microfluidic models of the BBB created the most simplistic models possible that still displayed some functional aspects of the in vivo BBB. Therefore, this Review also discusses the emerging unique ways in which microfluidics in tandem with recent advancements in cell culture, biomaterials, and in vitro modeling can be used to develop more complex and physiologically relevant models of the BBB. Finally, we discuss the current and future state-of-the-art application of microfluidic BBB models for drug development and disease modeling, and the ongoing areas of needed innovation in this field.

Aberrant accumulation of age- and disease-associated factors following neural probe implantation in a mouse model of Alzheimer’s disease

Objective. Electrical stimulation has had a profound impact on our current understanding of nervous system physiology and provided viable clinical options for addressing neurological dysfunction within the brain. Unfortunately, the brain’s immune suppression of indwelling microelectrodes currently presents a major roadblock in the long-term application of neural recording and stimulating devices. In some ways, brain trauma induced by penetrating microelectrodes produces similar neuropathology as debilitating brain diseases, such as Alzheimer’s disease (AD), while also suffering from end-stage neuron loss and tissue degeneration. The goal of the present study was to understand whether there may be any parallel mechanisms at play between brain injury from chronic microelectrode implantation and those of neurodegenerative disorder. Approach. We used two-photon microscopy to visualize the accumulation, if any, of age- and disease-associated factors around chronically implanted electrodes in both young and aged mouse models of AD. Main results. We determined that electrode injury leads to aberrant accumulation of lipofuscin, an age-related pigment, in wild-type and AD mice alike. Furthermore, we reveal that chronic microelectrode implantation reduces the growth of pre-existing Alzheimer’s plaques while simultaneously elevating amyloid burden at the electrode-tissue interface. Lastly, we uncover novel spatial and temporal patterns of glial reactivity, axonal and myelin pathology, and neurodegeneration related to neurodegenerative disease around chronically implanted microelectrodes. Significance. This study offers multiple novel perspectives on the possible neurodegenerative mechanisms afflicting chronic brain implants, spurring new potential avenues of neuroscience investigation and design of more targeted therapies for improving neural device biocompatibility and treatment of degenerative brain disease.

Alzheimer's Disease: Insights from Large-Scale Brain Dynamics Models.

Alzheimer's disease (AD) is a degenerative brain disease, and the condition is difficult to assess. In the past, numerous brain dynamics models have made remarkable contributions to neuroscience and the brain from the microcosmic to the macroscopic scale. Recently, large-scale brain dynamics models have been developed based on dual-driven multimodal neuroimaging data and neurodynamics theory. These models bridge the gap between anatomical structure and functional dynamics and have played an important role in assisting the understanding of the brain mechanism. Large-scale brain dynamics have been widely used to explain how macroscale neuroimaging biomarkers emerge from potential neuronal population level disturbances associated with AD. In this review, we describe this emerging approach to studying AD that utilizes a biophysically large-scale brain dynamics model. In particular, we focus on the application of the model to AD and discuss important directions for the future development and analysis of AD models. This will facilitate the development of virtual brain models in the field of AD diagnosis and treatment and add new opportunities for advancing clinical neuroscience.

Development of novel salicylic acid–donepezil–rivastigmine hybrids as multifunctional agents for the treatment of Alzheimer’s disease

Alzheimer’s disease (AD) is a chronic, progressive brain degenerative disease that is common in the elderly. So far, there is no effective treatment. The multi-target-directed ligands (MTDLs) strategy has been recognised as the most promising approach due to the complexity of the pathogenesis of AD. Herein, novel salicylic acid–donepezil–rivastigmine hybrids were designed and synthesised. The bioactivity results exhibited that 5a was a reversible and selective eqBChE inhibitor (IC50 = 0.53 μM), and the docking provided the possible mechanism. Compound 5a also displayed potential anti-inflammatory effects and significant neuroprotective effect. Moreover, 5a exhibited favourable stabilities in artificial gastrointestinal solution and plasma. Finally, 5a demonstrated potential cognitive improvement in scopolamine-induced cognitive dysfunction. Hence, 5a was a potential multifunctional lead compound against AD.

Label free impedance based acetylcholinesterase enzymatic biosensors for the detection of acetylcholine

Realtime monitoring of neurotransmitters is of great interest for understanding their fundamental role in a wide range of biological processes in the central and peripheral nervous system, as well as their role, in several degenerative brain diseases. The measurement of acetylcholine in the brain is particularly challenging due to the complex environment of the brain and the low concentration and short lifetime of acetylcholine. In this paper, we demonstrated a novel, label-free biosensor for the detection of Ach using a single enzyme, acetylcholinesterase (ACHE), and electrochemical impedance spectroscopy (EIS). Acetylcholinesterase was covalently immobilized onto the surface of gold microelectrodes through an amine-reactive crosslinker dithiobis(succinimidyl propionate) (DSP). Passivation of the gold electrode with SuperBlock eliminated or reduced any non-specific response to other major interfering neurotransmitter molecules such as dopamine (DA), norepinephrine (NE) and epinephrine (EH). The sensors were able to detect acetylcholine over a wide concentration range (5.5–550 μM) in sample volumes as small as 300 μL by applying a 10 mV AC voltage at a frequency of 500 Hz. The sensors showed a linear relationship between Ach concentration and ΔZmod(R2 = 0.99) in PBS. The sensor responded to acetylcholine not only when evaluated in a simple buffer (PBS buffer) but in several more complex environments such as rat brain slurry and rat whole blood. The sensor remained responsive to acetylcholine after being implanted ex vivo in rat brain tissue. These results bode well for the future application of these novel sensors for real time in vivo monitoring of acetylcholine.

Big tau aggregation disrupts microtubule tyrosination and causes myocardial diastolic dysfunction: from discovery to therapy.

Amyloid plaques and neurofibrillary tangles, the molecular lesions that characterize Alzheimer's disease (AD) and other forms of dementia, are emerging as determinants of proteinopathies 'beyond the brain'. This study aims to establish tau's putative pathophysiological mechanistic roles and potential future therapeutic targeting of tau in heart failure (HF). A mouse model of tauopathy and human myocardial and brain tissue from patients with HF, AD, and controls was employed in this study. Tau protein expression was examined together with its distribution, and in vitro tau-related pathophysiological mechanisms were identified using a variety of biochemical, imaging, and functional approaches. A novel tau-targeting immunotherapy was tested to explore tau-targeted therapeutic potential in HF. Tau is expressed in normal and diseased human hearts, in contradistinction to the current oft-cited observation that tau is expressed specifically in the brain. Notably, the main cardiac isoform is high-molecular-weight (HMW) tau (also known as big tau), and hyperphosphorylated tau segregates in aggregates in HF and AD hearts. As previously described for amyloid-beta, the tauopathy phenotype in human myocardium is of diastolic dysfunction. Perturbation in the tubulin code, specifically a loss of tyrosinated microtubules, emerged as a potential mechanism of myocardial tauopathy. Monoclonal anti-tau antibody therapy improved myocardial function and clearance of toxic aggregates in mice, supporting tau as a potential target for novel HF immunotherapy. The study presents new mechanistic evidence and potential treatment for the brain-heart tauopathy axis in myocardial and brain degenerative diseases and ageing.