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Graphene oxide-quenching-based fluorescence in situ hybridization (G-FISH) to detect RNA in tissue: Simple and fast tissue RNA diagnostics
摘要： FISH-based RNA detection in paraffin-embedded tissue can be challenging, with complicated procedures producing uncertain results and poor image quality. Here, we developed a robust RNA detection method based on graphene oxide (GO) quenching and recovery of fluorescence in situ hybridization (G-FISH) in formalin-fixed paraffin-embedded (FFPE) tissues. Using a fluorophore-labeled peptide nucleic acid (PNA) attached to GO, the endogenous long noncoding RNA BC1, the constitutive protein β-actin mRNA, and miR-124a and miR-21 could be detected in the cytoplasm of a normal mouse brain, primary cultured hippocampal neurons, an Alzheimer’s disease model mouse brain, and glioblastoma multiforme tumor tissues, respectively. Coding and non-coding RNAs, either long or short, could be detected in deparaffinized FFPE or frozen tissues, as well as in clear lipid-exchanged anatomically rigid imaging/immunostaining-compatible tissue hydrogel (CLARITY)-transparent brain tissues. The fluorescence recovered by G-FISH correlated highly with the amount of miR-21, as measured by quantitative real time RT-PCR. We propose G-FISH as a simple, fast, inexpensive, and sensitive method for RNA detection, with a very low background, which could be applied to a variety of research or diagnostic purposes.
关键词： glioblastoma multiforme tumor,tissue RNA diagnostics,Graphene oxide-quenching-based fluorescence in situ hybridization (G-FISH),Alzheimer’s disease,formalin-fixed paraffin-embedded (FFPE) tissue
更新于2025-09-23 15:23:52
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Estimating $c$-level partial correlation graphs with application to brain imaging
摘要： Alzheimer’s disease (AD) is a chronic neurodegenerative disease that changes the functional connectivity of the brain. The alteration of the strong connections between different brain regions is of particular interest to researchers. In this article, we use partial correlations to model the brain connectivity network and propose a data-driven procedure to recover a c-level partial correlation graph based on PET data, which is the graph of the absolute partial correlations larger than a pre-speci?ed constant c. The proposed procedure is adaptive to the “large p, small n” scenario commonly seen in whole brain studies, and it incorporates the variation of the estimated partial correlations, which results in higher power compared to the existing methods. A case study on the FDG-PET images from AD and normal control (NC) subjects discovers new brain regions, Sup Frontal and Mid Frontal in the frontal lobe, which have different brain functional connectivity between AD and NC.
关键词： Partial correlation,High dimensionality,Alzheimer’s Disease,Brain connectivity
更新于2025-09-23 15:23:52
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Usefulness of peripapillary nerve fiber layer thickness assessed by optical coherence tomography as a biomarker for Alzheimer’s disease
摘要： The use of optical coherence tomography (OCT) has been suggested as a potential biomarker for Alzheimer’s Disease based on previously reported thinning of the retinal nerve fiber layer (RNFL) in Alzheimer’s disease’s (AD) and Mild Cognitive Impairment (MCI). However, other studies have not shown such results. 930 individuals (414 cognitively healthy individuals, 192 probable amnestic MCI and 324 probable AD) attending a memory clinic were consecutively included and underwent spectral domain OCT (Maestro, Topcon) examinations to assess differences in peripapillary RNFL thickness, using a design of high ecological validity. Adjustment by age, education, sex and OCT image quality was performed. We found a non-significant decrease in mean RNFL thickness as follows: control group: 100,20 ± 14,60 μm, MCI group: 98,54 ± 14,43 μm and AD group: 96,61 ± 15,27 μm. The multivariate adjusted analysis revealed no significant differences in mean overall (p = 0.352), temporal (p = 0,119), nasal (p = 0,151), superior (p = 0,435) or inferior (p = 0,825) quadrants between AD, MCI and control groups. These results do not support the usefulness of peripapillary RNFL analysis as a marker of cognitive impairment or in discriminating between cognitive groups. The analysis of other OCT measurements in other retinal areas and layers as biomarkers for AD should be tested further.
关键词： retinal nerve fiber layer,optical coherence tomography,Alzheimer’s Disease,cognitive impairment,biomarker
更新于2025-09-23 15:21:21
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Noninvasive In Situ Ratiometric Imaging of Biometals Based on Self-Assembled Peptide Nanoribbon
摘要： Development of probes for accurate sensing and imaging of biometals in situ is still a growing interest owing to their crucial roles in cellular metabolism, neurotransmission, and apoptosis. Among them, Zn2+ and Cu2+ are two important cooperative biometals closely related to Alzheimer’s disease (AD). Herein, we developed a multifunctional probe based on self-assembling peptide nanoribbon for ratiometric sensing of Zn2+, Cu2+, or Zn2+ and Cu2+ simultaneously. Uniform peptide nanoribbon (AQZ@NR) was rationally designed by coassembling a Zn2+-specific ligand AQZ-modified peptide (AQZKL-7) with peptide KL-7. The nanoribbon further combined with Cu2+-sensitive near-infrared quantum dots (NIR QDs) and Alexa Fluor 633 as an inner reference molecule, which was endowed with the capability for ratiometric Zn2+ and Cu2+ imaging at the same time. The peptide-based probe exhibited good specificity to Zn2+ and Cu2+ without interference from other ions. Importantly, the nanoprobe was successfully applied for noninvasive Zn2+ and Cu2+ monitoring in both living cells and zebrafish via multicolor fluorescence imaging. This gives insights into the dynamic Zn2+ and Cu2+ distribution in an intracellular and in vivo mode, as well as understanding the neurotoxicity of high concentration of Zn2+ and Cu2+. Therefore, the self-assembled nanoprobe shows great promise in multiplexed detection of many other biometals and biomolecules, which will benefit the diagnosis and treatment of AD in clinical applications.
关键词： fluorescence imaging,biometals,ratiometric imaging,peptide nanoribbon,Cu2+,Zn2+,self-assembly,Alzheimer’s disease
更新于2025-09-23 15:21:01
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Au nano-urchins enabled localized surface plasmon resonance sensing of beta amyloid fibrillation
摘要： Early stage detection of neurodegenerative diseases such as Alzheimer’s disease (AD) is of utmost importance, as it has become one of the leading causes of death of millions of people. The gradual intellectual decline in AD patients is an outcome of fibrillation of amyloid beta 1-42 (Aβ1-42) peptides in brain. In this paper, we present localized surface plasmon resonance (LSPR) based sensing of Aβ1-42 fibrillation using Au nano-urchins. Strongly localized field confinement at the spiky nanostructures of nano-urchin surfaces enables them to detect very low concentrations of Aβ1-42. In addition, the LSPR peak of Au nano-urchins, which is very sensitive to ambient conditions, shows significant responses at different fibrillation stages of Aβ1-42. Reduction in LSPR peak intensity with increase in the fibrillation is chosen as the sensing parameter here. This paper in this context provides LSPR based highly sensitive, label-free and real-time sensing of Aβ1-42 fibrillation that is highly advantageous compared to the existing techniques which require binding additives or fluorescent biomarkers.
关键词： Au nano-urchins,localized surface plasmon resonance,biosensing,amyloid beta,Alzheimer’s disease
更新于2025-09-23 15:19:57
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Sparse Feature Learning with Label Information for Alzheimer’s Disease Classification Based on Magnetic Resonance Imaging
摘要： Biomedical signal processing data have been used for automatic diagnosis and classification of brain disease, which is an important part of research in smart city. How to select discriminant features from these data is the key that will affect subsequent automatic diagnosis and classification performance. However, in previous manifold regularized sparse regression models, the local neighborhood structure was constructed directly in the traditional Euclidean distance without fully utilizing the label information of the subjects, which leads to the selection of less discriminative features. In this paper, we propose a novel manifold regularized sparse regression model for learning discriminative features. Specifically, we first adopt l2,1-norm regularization to jointly select a relevant feature subset among the samples. Then, to select more discriminative features, a novel manifold regularization term is constructed via the relative distance adjusted by the label information, which can simultaneously maintain the compactness of intra-class samples and the separability of inter-class samples. The proposed feature learning method is further carried out for both the binary classification and the multi-class classification. Experimental results on Alzheimer’s Disease Neuroimaging Initiative database demonstrate the effectiveness of the proposed method, which can be utilized for the diagnosis of Alzheimer’s disease and mild cognitive impairment.
关键词： feature learning,Alzheimer's disease,manifold regularization,sparse regression
更新于2025-09-19 17:15:36
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[IEEE 2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO) - Kiev (2018.4.24-2018.4.26)] 2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO) - Florbetapir Image Analysis for Alzheimer's Disease Diagnosis
摘要： Over decades Alzheimer’s disease (AD) remains without decent cure, and only disease-modifying methods are available. This paper is devoted to the analysis of amyloid-PET images with florbetapir (18F-AV-45) tracer to detect the presence of AD or Mild Cognitive Impairment (MCI). The first part of the article dedicated to image processing pipeline, specifically, spacial normalisation and feature extraction. The second part is devoted to the development of the multiclass classifier with deep learning methods. In particular, deep neural network was developed to distinguish three stages: health control (HC), MCI and AD. After tuning and training a neural network, the final specificity of 78% and sensitivity of 90% has been achieved.
关键词： Deep learning,Florbetapir,PET imaging,Alzheimer's disease,Amyloid Imaging
更新于2025-09-19 17:15:36
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Femtomolar sensing of Alzheimer's tau proteins by water oxidation-coupled photoelectrochemical platform
摘要： Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder. A key pathogenic event of AD is the formation of intracellular neurofibrillary tangles that are mainly composed of tau proteins. Here, we report on ultrasensitive detection of total tau (t-tau) proteins using an artificial electron donor-free, BiVO4-based photoelectrochemical (PEC) analysis. The platform was constructed by incorporating molybdenum (Mo) dopant and iron oxyhydroxide (FeOOH) ad-layer into the BiVO4 photoelectrode and employing a signal amplifier formed by horseradish peroxidase (HRP)-triggered oxidation of 3,3′-diaminobenzidine (DAB). Despite the absence of additional electron suppliers, the FeOOH/Mo:BiVO4 conjugated with the Tau5 antibody produced strong current signals at 0 V (vs. Ag/AgCl, 3M NaCl) under the illumination of a white light-emitting diode. The Mo extrinsic dopants increased the charge carrier density of BiVO4-Tau5 by 1.57 times, and the FeOOH co-catalyst promoted the interfacial water oxidation reaction of Mo:BiVO4-Tau5 by suppressing charge recombination. The introduction of HRP-labeled Tau46 capture antibodies to the FeOOH/Mo:BiVO4-Tau5 platform produced insoluble precipitation on the transducer by accelerating the oxidation of DAB, which amplified the photocurrent signal of FeOOH/Mo:BiVO4-Tau5 by 2.07-fold. Consequently, the water oxidation-coupled, FeOOH/Mo:BiVO4-based PEC sensing platform accurately and selectively recognized t-tau proteins down to femtomolar concentrations; the limit of detection and limit of quantification were determined to be 1.59 fM and 4.11 fM, respectively.
关键词： Alzheimer’s disease,water oxidation,Femtomolar sensitivity,tau proteins,BiVO4
更新于2025-09-19 17:13:59
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[IEEE 2019 Joint Conference of the IEEE International Frequency Control Symposium anEuropean Frequency and Time Forum (EFTF/IFC) - Orlando, FL, USA (2019.4.14-2019.4.18)] 2019 Joint Conference of the IEEE International Frequency Control Symposium and European Frequency and Time Forum (EFTF/IFC) - Phase Noise Directely Measurement of Optical Second Harmonic Generation in MgO:PPLN Waveguide based on the 120-degree Phase Difference Interferometer
摘要： We examine whether modeling of the causal dynamic relationships between frontal and occipital electroencephalogram (EEG) time-series recordings reveal reliable differentiating characteristics of Alzheimer’s patients versus control subjects in a manner that may assist clinical diagnosis of Alzheimer’s disease (AD). The proposed modeling approach utilizes the concept of principal dynamic modes (PDMs) and their associated nonlinear functions (ANF) and hypothesizes that the ANFs of some PDMs for the AD patients will be distinct from their counterparts in control subjects. To this purpose, global PDMs are extracted from 1-min EEG signals of 17 AD patients and 24 control subjects at rest using Volterra models estimated via Laguerre expansions, whereby the O1 or O2 recording is viewed as the input signal and the F3 or F4 recording as the output signal. Subsequent singular value decomposition of the estimated Volterra kernels yields the global PDMs that represent an ef?cient basis of functions for the representation of the EEG dynamics in all subjects. The respective ANFs are computed for each subject and characterize the speci?c dynamics of each subject. For comparison, signal features traditionally used in the analysis of EEG signals in AD are computed as benchmark. The results indicate that the ANFs of two speci?c PDMs, corresponding to the delta–theta and alpha bands, can delineate the two groups well.
关键词： assistive diagnosis,Alzheimer’s disease,nonlinear modeling,EEG signal processing
更新于2025-09-19 17:13:59
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Assessing Neural Compensation with Visuospatial Working Memory Load using Near-Infrared Imaging
摘要： Alzheimer’s disease is characterized by the progressive deterioration of cognitive abilities particularly working memory while mild cognitive impairment (MCI) represents its prodrome. It is generally believed that neural compensation is intact in MCI but absent in Alzheimer’s disease. This study investigated the effects of increasing task load as a means to induce neural compensation through a novel visual working memory (VSWM) task using functional near-infrared spectroscopy (fNIRS). The bilateral prefrontal cortex (PFC) was explored due to its relevance in VSWM and neural compensation. A total of 31 healthy controls (HC), 12 patients with MCI and 18 patients with mild Alzheimers disease (mAD) were recruited. Although all groups showed sensitivity in terms of behavioral performance (i.e. score) towards increasing task load (level 1 to 3), only in MCI load effect on cortical response (as measured by fNIRS) was significant. At lower task load, bilateral PFC activation did not differ between MCI and HC. Neural compensation in the form of hyperactivation was only noticeable in MCI with a moderate task load. Lack of hyperactivation in mAD, coupled with significantly poorer task performance across task loads, suggested the inability to compensate due to a greater degree of neurodegeneration. Our findings provided an insight into the interaction of cognitive load theory and neural compensatory mechanisms. The experiment results demonstrated the feasibility of inducing neural compensation with the proposed VSWM task at the right amount of cognitive load. This may provide a promising avenue to develop an effective cognitive training and rehabilitation for dementia population.
关键词： mild cognitive impairment,visuospatial working memory,normal aging,functional near-infrared spectroscopy,neural compensation,mild Alzheimer’s disease
更新于2025-09-12 10:27:22