The search for a unique Raman signature of amyloid-beta plaques in human brain tissue from Alzheimer's disease patients

Gamma oscillation modulation for cognitive impairment: A systematic review

BackgroundGamma oscillation modulation has emerged as a potential non-invasive treatment to counteract cognitive impairment in Alzheimer's disease (AD) and mild cognitive impairment (MCI). Non-invasive brain stimulation techniques like transcranial alternating current stimulation (tACS), gamma sensory stimulation (GSS), and transcranial magnetic stimulation (TMS) show promise in supporting specific cognitive functions.ObjectiveTo review and evaluate the efficacy of gamma oscillation modulation techniques in benefiting cognitive functions among individuals with AD and MCI.MethodsA systematic review was conducted, analyzing studies from 2015 to 2023 across databases such as PubMed, Web of Science, and Scopus. Inclusion criteria focused on studies involving tACS, GSS, or TMS applied to older adults with MCI or AD. A total of 438 articles were screened, of which 10 met the eligibility criteria.ResultsFindings suggest that gamma tACS, especially targeting the precuneus and dorsolateral prefrontal cortex, benefits episodic memory and cognitive performance. GSS also showed potential in supporting memory and attention, while TMS exhibited inconsistent but promising results when applied to the angular gyrus. However, heterogeneity in study designs and small sample sizes limit the generalizability of these outcomes.ConclusionsGamma oscillation modulation offers potential cognitive benefits for patients with AD and MCI, particularly in memory support. Further studies with larger samples and well-designed protocols are needed to confirm its therapeutic efficacy and optimize intervention parameters.

Machine Learning Interpretation of Optical Spectroscopy Using Peak-Sensitive Logistic Regression

Optical spectroscopy, a noninvasive molecular sensing technique, offers valuable insights into material characterization, molecule identification, and biosample analysis. Despite the informativeness of high-dimensional optical spectra, their interpretation remains a challenge. Machine learning methods have gained prominence in spectral analyses, efficiently unveiling analyte compositions. However, these methods still face challenges in interpretability, particularly in generating clear feature importance maps that highlight the spectral features specific to each class of data. These limitations arise from feature noise, model complexity, and the lack of optimization for spectroscopy. In this work, we introduce a machine learning algorithm─logistic regression with peak-sensitive elastic-net regularization (PSE-LR)─tailored for spectral analysis. PSE-LR enables classification and interpretability by producing a peak-sensitive feature importance map, achieving an F1-score of 0.93 and a feature sensitivity of 1.0. Its performance is compared with other methods, including k-nearest neighbors (KNN), elastic-net logistic regression (E-LR), support vector machine (SVM), principal component analysis followed by linear discriminant analysis (PCA-LDA), XGBoost, and neural network (NN). Applying PSE-LR to Raman and photoluminescence (PL) spectra, we detected the receptor-binding domain (RBD) of SARS-CoV-2 spike protein in ultralow concentrations, identified neuroprotective solution (NPS) in brain samples, recognized WS2 monolayer and WSe2/WS2 heterobilayer, analyzed Alzheimer's disease (AD) brains, and suggested potential disease biomarkers. Our findings demonstrate PSE-LR's utility in detecting subtle spectral features and generating interpretable feature importance maps. It is beneficial for the spectral characterization of materials, molecules, and biosamples and applicable to other spectroscopic methods. This work also facilitates the development of nanodevices such as nanosensors and miniaturized spectrometers based on nanomaterials.

Label-free Aβ plaque detection in Alzheimer's disease brain tissue using infrared microscopy and neural networks

We present a novel method for the label-free detection of amyloid-beta (Aβ) plaques, the key hallmark of Alzheimer's disease, in human brain tissue sections. Conventionally, immunohistochemistry (IHC) is employed for the characterization of Aβ plaques, hindering subsequent analysis. Here, a semi-supervised convolutional neural network (CNN) is trained to detect Aβ plaques in quantum cascade laser infrared (QCL-IR) microscopy images. Laser microdissection (LMD) is then used to precisely extract plaques from snap-frozen, unstained tissue sections. Mass spectrometry-based proteomics reveals a loss of soluble proteins in IHC stained samples. Our method prevents this loss and provides a novel tool that expands the scope of molecular analysis methods to chemically native plaques. Insight into soluble plaque components will complement our understanding of plaques and their role in Alzheimer's disease.

Polypropylene microplastics triggered mouse kidney lipidome reprogramming combined with ROS stress as revealed by lipidomics and Raman biospectra

Microplastics intrigue kidney toxicity such as mitochondrial dysfunction and inflammation promotion. However, as an organ relying heavily on fatty acid oxidation, how microplastics influence kidney lipidomes remain unclear. Hence, we performed Raman spectra and multidimensional mass spectrometry-based shotgun lipidomics to decode kidney lipidomics landscape under polypropylene microplastics exposure. Kidney functions and cellular redox homeostasis were remarkably disturbed as revealed by levels of biochemical renal function markers, malonaldehyde, hydrogen peroxide and antioxidants. Ultrastructure alterations including the foot process fusion implied the kidney injury associated with lipidomic changes. Raman spectra successfully further confirmed the cellular change of reactive oxygen species and lipid disorders. Lipidomics showed that polypropylene microplastics caused abnormal lipidome and irregular exchange by remodeling triglycerides and phospholipids. Genes involved in lipid metabolism such as Fads1 and Elovl5 exhibited highly diversified expression profiles responding to polypropylene microplastics stress and possessed significant correlations with ROS indicators. These results explained ultrastructure alterations and aggravation of kidney injuries. Our work revealed polypropylene microplastics inducing lipidomic detriment in mouse kidney by Raman spectra and lipidomics firstly, elucidating the significances of lipidomic remodeling coupled with ROS stress in the kidney damages. The findings provided reliable evidence on the health risks of polypropylene microplastics in kidney.

Effects of Pretreatment With Coenzyme Q10 (CoQ10) and High-Intensity Interval Training (HIIT) on FNDC5, Irisin, and BDNF Levels, and Amyloid-Beta (Aβ) Plaque Formation in the Hippocampus of Aβ-Induced Alzheimer's Disease Rats

AIMS

Physical exercise has been shown to protect against cognitive decline in Alzheimer's disease (AD), likely through the upregulation of brain-derived neurotrophic factor (BDNF). Recent studies have reported that exercise activates the FNDC5/irisin pathway in the hippocampus of mice, triggering a neuroprotective gene program that includes BDNF. This study aimed to investigate the effects of 8 weeks of pretreatment with coenzyme Q10 (CoQ10) and high-intensity interval training (HIIT), both individually and in combination, on FNDC5, irisin, BDNF, and amyloid-beta (Aβ) plaque formation in the hippocampus of Aβ-related AD rats.

METHODS

In this study, 72 male Wistar rats were randomly assigned to one of the following groups: control, sham, HIIT (low intensity: 3 min running at 50%-60% VO2max; high intensity: 4 min running at 85%-90% VO2max), Q10 (50 mg/kg, orally administered), Q10 + HIIT, AD, AD + HIIT, AD + Q10, and AD + Q10 + HIIT.

RESULTS

Aβ injection resulted in a trend toward decreased levels of FNDC5, irisin, and BDNF, alongside increased Aβ plaque formation in the hippocampus of Aβ-induced AD rats. However, pretreatment with CoQ10, HIIT, or their combination significantly restored hippocampal levels of FNDC5, irisin, and BDNF, while also inhibiting Aβ plaque accumulation in these rats.

CONCLUSION

Pretreatment with CoQ10 and HIIT improved the Aβ-induced reduction in BDNF levels probably through the FNDC5/irisin pathway and preventing Aβ plaque formation.

Identification of tauopathy-associated lipid signatures in Alzheimer's disease mouse brain using label-free chemical imaging

There is cumulative evidence that lipid metabolism plays a key role in the pathogenesis of various neurodegenerative disorders including Alzheimer's disease (AD). Visualising lipid content in a non-destructive label-free manner can aid in elucidating the AD phenotypes towards a better understanding of the disease. In this study, we combined multiple optical molecular-specific methods, Fourier transform infrared (FTIR) spectroscopic imaging, synchrotron radiation-infrared (SR-IR) microscopy, Raman and stimulated Raman scattering (SRS) microscopy, and optical-photothermal infrared (O-PTIR) microscopy with multivariate data analysis, to investigate the biochemistry of brain hippocampus in situ using a mouse model of tauopathy (rTg4510). We observed a significant difference in the morphology and lipid content between transgenic (TG) and wild type (WT) samples. Immunohistochemical staining revealed some degree of microglia co-localisation with elevated lipids in the brain. These results provide new evidence of tauopathy-related dysfunction in a preclinical study at a subcellular level.

Raman spectroscopy in the study of amyloid formation and phase separation

Neurodegenerative diseases, such as Alzheimer's and Parkinson's, share a common pathological feature of amyloid structure accumulation. However, the structure-function relationship between these well-ordered, β-sheet-rich, filamentous protein deposits and disease etiology remains to be defined. Recently, an emerging hypothesis has linked phase separation, a process involved in the formation of protein condensates, to amyloid formation, suggesting that liquid protein droplets serve as loci for amyloid initiation. To elucidate how these processes contribute to disease progression, tools that can directly report on protein secondary structural changes are needed. Here, we review recent studies that have demonstrated Raman spectroscopy as a powerful vibrational technique for interrogating amyloid structures; one that offers sensitivity from the global secondary structural level to specific residues. This probe-free technique is further enhanced via coupling to a microscope, which affords structural data with spatial resolution, known as Raman spectral imaging (RSI). In vitro and in cellulo applications of RSI are discussed, highlighting studies of protein droplet aging, cellular internalization of fibrils, and Raman imaging of intracellular water. Collectively, utilization of the myriad Raman spectroscopic methods will contribute to a deeper understanding of protein conformational dynamics in the complex cellular milieu and offer potential clinical diagnostic capabilities for protein misfolding and aggregation processes in disease states.

Advancements in Neurosurgical Intraoperative Histology

Despite their relatively low incidence globally, central nervous system (CNS) tumors remain amongst the most lethal cancers, with only a few other malignancies surpassing them in 5-year mortality rates. Treatment decisions for brain tumors heavily rely on histopathological analysis, particularly intraoperatively, to guide surgical interventions and optimize patient outcomes. Frozen sectioning has emerged as a vital intraoperative technique, allowing for highly accurate, rapid analysis of tissue samples, although it poses challenges regarding interpretive errors and tissue distortion. Raman histology, based on Raman spectroscopy, has shown great promise in providing label-free, molecular information for accurate intraoperative diagnosis, aiding in tumor resection and the identification of neurodegenerative disease. Techniques including Stimulated Raman Scattering (SRS), Coherent Anti-Stokes Raman Scattering (CARS), Surface-Enhanced Raman Scattering (SERS), and Tip-Enhanced Raman Scattering (TERS) have profoundly enhanced the speed and resolution of Raman imaging. Similarly, Confocal Laser Endomicroscopy (CLE) allows for real-time imaging and the rapid intraoperative histologic evaluation of specimens. While CLE is primarily utilized in gastrointestinal procedures, its application in neurosurgery is promising, particularly in the context of gliomas and meningiomas. This review focuses on discussing the immense progress in intraoperative histology within neurosurgery and provides insight into the impact of these advancements on enhancing patient outcomes.

Colocalization of β-Sheets and Carotenoids in Aβ Plaques Revealed with Multimodal Spatially Resolved Vibrational Spectroscopy

The aggregation of amyloid β(Aβ) peptides is at the heart of Alzheimer's disease development and progression. As a result, amyloid aggregates have been studied extensively in vitro, and detailed structural information on fibrillar amyloid aggregates is available. However, forwarding these structural models to amyloid plaques in the human brain is still a major challenge. The chemistry of amyloid plaques, particularly in terms of the protein secondary structure and associated chemical moieties, remains poorly understood. In this report, we use Raman microspectroscopy to identify the presence of carotenoids in amyloid plaques and demonstrate that the abundance of carotenoids is correlated with the overall protein secondary structure of plaques, specifically to the population of β-sheets. While the association of carotenoids with plaques has been previously identified, their correlation with the β structure has never been identified. To further validate these findings, we have used optical photothermal infrared (O-PTIR) spectroscopy, which is a spatially resolved technique that yields complementary infrared contrast to Raman. O-PTIR unequivocally demonstrates the presence of elevated β-sheets in carotenoid-containing plaques and the lack of β structure in noncarotenoid plaques. Our findings underscore the potential link between anti-inflammatory species as carotenoids to specific secondary structural motifs within Aβ plaques and highlight the possible role of chemically distinct plaques in neuroinflammation, which can uncover new mechanistic insights and lead to new therapeutic strategies for AD.

A review: Exploring the metabolic and structural characterisation of beta pleated amyloid fibril in human tissue using Raman spectrometry and SAXS

Amyloidosis is a deleterious condition caused by abnormal amyloid fibril build-up in living tissues. To date, 42 proteins that are linked to amyloid fibrils have been discovered. Amyloid fibril structure variation can affect the severity, progression rate, or clinical symptoms of amyloidosis. Since amyloid fibril build-up is the primary pathological basis for various neurodegenerative illnesses, characterization of these deadly proteins, particularly utilising optical techniques have been a focus. Spectroscopy techniques provide significant non-invasive platforms for the investigation of the structure and conformation of amyloid fibrils, offering a wide spectrum of analyses ranging from nanometric to micrometric size scales. Even though this area of study has been intensively explored, there still remain aspects of amyloid fibrillization that are not fully known, a matter hindering progress in treating and curing amyloidosis. This review aims to provide recent updates and comprehensive information on optical techniques for metabolic and proteomic characterization of β-pleated amyloid fibrils found in human tissue with thorough literature analysis of publications. Raman spectroscopy and SAXS are well established experimental methods for study of structural properties of biomaterials. With suitable models, they offer extended information for valid proteomic analysis under physiologically relevant conditions. This review points to evidence that despite limitations, these techniques are able to provide for the necessary output and proteomics indication in order to extrapolate the aetiology of amyloid fibrils for reliable diagnostic purposes. Our metabolic database may also contribute to elucidating the nature and function of the amyloid proteome in development and clearance of amyloid diseases.

Non-Perturbative Identification and Subtyping of Amyloidosis in Human Kidney Tissue with Raman Spectroscopy and Machine Learning

Amyloids are proteins with characteristic beta-sheet secondary structures that display fibrillary ultrastructural configurations. They can result in pathologic lesions when deposited in human organs. Various types of amyloid protein can be routinely identified in human tissue specimens by special stains, immunolabeling, and electron microscopy, and, for certain forms of amyloidosis, mass spectrometry is required. In this study, we applied Raman spectroscopy to identify immunoglobulin light chain and amyloid A amyloidosis in human renal tissue biopsies and compared the results with a normal kidney biopsy as a control case. Raman spectra of amyloid fibrils within unstained, frozen, human kidney tissue demonstrated changes in conformation of protein secondary structures. By using t-distributed stochastic neighbor embedding (t-SNE) and density-based spatial clustering of applications with noise (DBSCAN), Raman spectroscopic data were accurately classified with respect to each amyloid type and deposition site. To the best of our knowledge, this is the first time Raman spectroscopy has been used for amyloid characterization of ex vivo human kidney tissue samples. Our approach, using Raman spectroscopy with machine learning algorithms, shows the potential for the identification of amyloid in pathologic lesions.

Anti-LINGO-1 antibody protects neurons and synapses in the medial prefrontal cortex of APP/PS1 transgenic mice

The medial prefrontal cortex (mPFC), one of the most vulnerable brain regions in Alzheimer's disease (AD), plays a critical role in cognition. Leucine-rich repeat and immunoglobulin-like domain-containing nogo receptor-interacting protein-1 (LINGO-1) negatively affects nerve growth in the central nervous system; however, its role in the pathological damage to the mPFC remains to be studied in AD. In this study, an anti-LINGO-1 antibody was administered to 10-month-old APP/PS1 mice, and behavioral tests, stereological methods, immunohistochemistry and immunofluorescence were used to answer this question. Our results revealed that LINGO-1 was highly expressed in the neurons of the mPFC of AD mice, and the anti-LINGO-1 antibody improved prefrontal cortex-related function and reduced the protein level of LINGO-1, atrophy of the volume, Aβ deposition and massive losses of synapses and neurons in the mPFC of AD mice. Antagonizing LINGO-1 could effectively alleviate the pathological damage in the mPFC of AD mice, which might be an important structural basis for improving prefrontal cortex-related function. Abnormal expression of LINGO-1 in the mPFC may be one of the key targets of AD, and the effect initiated by the anti-LINGO-1 antibody may provide an important basis in the search for drugs for the prevention and treatment of AD.

Raman Spectroscopy on Brain Disorders: Transition from Fundamental Research to Clinical Applications

Brain disorders such as brain tumors and neurodegenerative diseases (NDs) are accompanied by chemical alterations in the tissues. Early diagnosis of these diseases will provide key benefits for patients and opportunities for preventive treatments. To detect these sophisticated diseases, various imaging modalities have been developed such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). However, they provide inadequate molecule-specific information. In comparison, Raman spectroscopy (RS) is an analytical tool that provides rich information about molecular fingerprints. It is also inexpensive and rapid compared to CT, MRI, and PET. While intrinsic RS suffers from low yield, in recent years, through the adoption of Raman enhancement technologies and advanced data analysis approaches, RS has undergone significant advancements in its ability to probe biological tissues, including the brain. This review discusses recent clinical and biomedical applications of RS and related techniques applicable to brain tumors and NDs.

Raman Spectroscopy Techniques for the Investigation and Diagnosis of Alzheimer's Disease

Alzheimer's disease (AD) is the most common neurodegenerative disorder, resulting in memory loss, cognitive decline, bodily function impairment, and finally death. The growing number of people suffering from AD increasingly urges the development of effective early diagnosis and monitoring techniques. Here, we review the most recent developments in the field of Raman-based techniques, which have shown a significant potential in identifying AD by detecting specific biomarkers in biological fluids, as well as in providing fundamental insights into key molecules involved in the disease progression or in the analysis of histological specimens of patients with AD. These techniques comprise spontaneous and resonant Raman spectroscopies, exploit plasmon- or fiber- enhanced effects, such as surface-, tip- or fiber- enhanced Raman spectroscopies, or involve non-linear techniques like coherent Raman scattering. The scientific efforts employed up to now as well as the rapid technological advancements in optical detection instruments (spectrometers, lasers, substrates for analysis, etc.) and the diffusion of advanced data processing methods suggest a leading role of Raman techniques in the perspective of a preclinical or clinical detection of AD.

Neurotrophic factor-secreting cells restored endogenous hippocampal neurogenesis through the Wnt/β-catenin signaling pathway in AD model mice

Background

Impairment in neurogenesis correlates with memory and  cognitive dysfunction in AD patients. In the recent decade, therapies with stem cell bases are growing and proved to be efficient. This study is a preliminary attempt to explore the impact of NTF-SCs on hippocampal neurogenesis mediated by the Wnt/β-catenin signaling cascade in AD-like mouse brain parenchyma.

Methods

The BALB/c mice were divided into four groups: Control, AD +Vehicle, AD+ TF-SCs-CM and AD+NTF-SCs (n = 10). For AD induction, 100 µM Aβ_1-42 was injected into lateral ventricles. The AD-like model was confirmed via passive avoidance test and Thioflavin-S staining 21 days following Aβ injection. Next, NTF-SCs were differentiated from ADMSCs, and both NTF-SCs and supernatant (NTF-SCs-CM) were injected into the hippocampus after AD confirmation. Endogenous neural stem cells (NSCs) proliferation capacity was assessed after 50 mg/kbW BrdU injection for 4 days using immunofluorescence (IF) staining. The percent of BrdU/Nestin and BrdU/NeuN positive NSCs were calculated. Real-time RT-PCR was used to detect genes related to the Wnt/β-catenin signaling cascade. The spatial learning and memory alternation was evaluated using the Morris water maze (MWM).

Results

Data showed the reduction in escape latency over 5 days in the AD mice compared to the control group. The administration of NTF-SCs and NTF-SCs-CM increased this value compared to the AD-Vehicle group. Both NTF-SCs and NTF-SCs-CM were the potential to reduce the cumulative distance to the platform in AD mice compared to the AD-Vehicle group. The time spent in target quadrants was ameliorated following NTF-SCs and NTF-SCs-CM transplantation followed by an improved MWM performance. IF imaging revealed the increase in BrdU/Nestin⁺ and BrdU/NeuN⁺ in AD mice that received NTF-SCs and NTF-SCs-CM, indicating enhanced neurogenesis. Based on real-time PCR analysis, the expression of PI3K, Akt, MAPK, ERK, Wnt, and β-catenin was upregulated and coincided with the suppression of GSK-3β after injection of NTF-SCs-CM and NTF-SCs. In this study, NTF-SCs had superior effects in AD mice that received NTF-SCs compared to NTF-SCs-CM.

Conclusions

The activation of Wnt/β-catenin pathway via NTF-SCs can be touted as a possible therapeutic approach to restore neurogenesis in AD mice.

In Situ Identification of Unknown Crystals in Acute Kidney Injury Using Raman Spectroscopy

Raman spectroscopy is a well-established and powerful tool for in situ biomolecular evaluation. Type 2 crystal nephropathies are characterized by the deposition of crystalline materials in the tubular lumen, resulting in rapid onset of acute kidney injury without specific symptoms. Timely crystal identification is essential for its diagnosis, mechanism exploration and therapy, but remains challenging. This study aims to develop a Raman spectroscopy-based method to assist pathological diagnosis of type 2 crystal nephropathies. Unknown crystals in renal tissue slides from a victim suffered extensive burn injury were detected by Raman spectroscopy, and the inclusion of crystals was determined by comparing Raman data with established database. Multiple crystals were scanned to verify the reproducibility of crystal in situ. Raman data of 20 random crystals were obtained, and the distribution and uniformity of substances in crystals were investigated by Raman imaging. A mouse model was established to mimic the crystal nephropathy to verify the availability of Raman spectroscopy in frozen biopsy. All crystals on the human slides were identified to be calcium oxalate dihydrate, and the distribution and content of calcium oxalate dihydrate on a single crystal were uneven. Raman spectroscopy was further validated to be available in identification of calcium oxalate dihydrate crystals in the biopsy specimens. Here, a Raman spectroscopy-based method for in situ identification of unknown crystals in both paraffin-embedded tissues and biopsy specimens was established, providing an effective and promising method to analyze unknown crystals in tissues and assist the precise pathological diagnosis in both clinical and forensic medicine.

Electrochemical monitoring sensors of water pollution systems

Analytical techniques as strong, precise, and expensive are necessary for monitoring food and water safety for contaminants, microorganisms, and allergies that might be harmful if used. Sudan dyes are commonly utilized as an ingredient in food dye substances and a variety of industrial items. These colors are classified as three carcinogens and are linked to liver and bladder cancers. They are not authorized for human consumption by the International Agency for Research on Cancer (IARC) and are not permitted to be used by the Food Standards Agency or the European Union. This article describes electrochemical dye analysis beside the numerous electrochemical sensors utilized to identify these dyes as a food colorant and water. As a result, the qualities, chemistry, and toxicity of dyes as food colorants and industrial goods in Sudan have been investigated in this study. Sudan dyes have been thoroughly studied, and many electrochemical sensors have been developed to define and monitor these dyes in food colorants. As a result, current electrochemical sensors have been found to be neither mass-production nor cost-effective. Mostly, the synthesis of high-performance materials needs high knowledge, and the production of electrode surfaces is remained difficult due to labor-intensive and time-consuming activities.

Rapid Biomarker Screening of Alzheimer's Disease by Interpretable Machine Learning and Graphene-Assisted Raman Spectroscopy

The study of Alzheimer's disease (AD), the most common cause of dementia, faces challenges in terms of understanding the cause, monitoring the pathogenesis, and developing early diagnoses and effective treatments. Rapid and accurate identification of AD biomarkers in the brain is critical to providing key insights into AD and facilitating the development of early diagnosis methods. In this work, we developed a platform that enables a rapid screening of AD biomarkers by employing graphene-assisted Raman spectroscopy and machine learning interpretation in AD transgenic animal brains. Specifically, we collected Raman spectra on slices of mouse brains with and without AD and used machine learning to classify AD and non-AD spectra. By contacting monolayer graphene with the brain slices, the accuracy was increased from 77% to 98% in machine learning classification. Further, using a linear support vector machine (SVM), we identified a spectral feature importance map that reveals the importance of each Raman wavenumber in classifying AD and non-AD spectra. Based on this spectral feature importance map, we identified AD biomarkers including Aβ and tau proteins and other potential biomarkers, such as triolein, phosphatidylcholine, and actin, which have been confirmed by other biochemical studies. Our Raman-machine learning integrated method with interpretability will facilitate the study of AD and can be extended to other tissues and biofluids and for various other diseases.

Challenges in Experimental Methods

Experimental studies of amyloids encounter many challenges. There are many methods available for studying proteins, which can be applied to amyloids: from basic staining techniques, allowing visualization of fibers, to complex methods, e.g., AFM-IR used to their detailed biochemical and structural characterization in nanoscale. Which method is appropriate depends on the goal of an experiment: verification of aggregational properties of a peptide, distinguishing oligomers from mature fibers, or kinetic studies. Insolubility, rapid aggregation, and the need of using a high-purity peptide may be a limiting factor in studies involving amyloids. Moreover, the results obtained by various experimental methods often differ significantly, which may lead to misclassification of amyloid peptides. Due to ambiguity of experimental results, laborious and time-consuming analysis, bioinformatical methods become more widely used for amyloids.

Label-Free Infrared Spectroscopic Imaging Reveals Heterogeneity of β-Sheet Aggregates in Alzheimer's Disease

The aggregation of the amyloid beta (Aβ) protein into plaques is a pathological feature of Alzheimer's disease (AD). While amyloid aggregates have been extensively studied in vitro, their structural aspects and associated chemistry in the brain are not fully understood. In this report, we demonstrate, using infrared spectroscopic imaging, that Aβ plaques exhibit significant heterogeneities in terms of their secondary structure and phospholipid content. We show that the capabilities of discrete frequency infrared imaging (DFIR) are ideally suited for characterization of amyloid deposits in brain tissues and employ DFIR to identify nonplaque β-sheet aggregates distributed throughout brain tissues. We further demonstrate that phospholipid-rich β-sheet deposits exist outside of plaques in all diseased tissues, indicating their potential clinical significance. This is the very first application of DFIR toward a characterization of protein aggregates in an AD brain and provides a rapid, label-free approach that allows us to uncover β-sheet heterogeneities in the AD, which may be significant for targeted therapeutic strategies in the future.

Micro-Raman spectroscopy of lipid halo and dense-core amyloid plaques: aging process characterization in the Alzheimer's disease APPswePS1ΔE9 mouse model

The deposition of amyloid plaques is considered one of the main microscopic features of Alzheimer's disease (AD). Since plaque formation can precede extensive neurodegeneration and it is the main clinical manifestation of AD, it constitutes a relevant target for new treatment and diagnostic approaches. Micro-Raman spectroscopy, a label-free technique, is an accurate method for amyloid plaque identification and characterization. Here, we present a high spatial resolution micro-Raman hyperspectral study in transgenic APPswePS1ΔE9 mouse brains, showing details of AD tissue biochemical and histological changes without staining. First we used stimulated micro-Raman scattering to identify the lipid-rich halo surrounding the amyloid plaque, and then proceeded with spontaneous (conventional) micro-Raman spectral mapping, which shows a cholesterol and sphingomyelin lipid-rich halo structure around dense-core amyloid plaques. The detailed images of this lipid halo relate morphologically well with dystrophic neurites surrounding plaques. Principal Component Analysis (PCA) of the micro-Raman hyperspectral data indicates the feasibility of the optical biomarkers of AD progression with the potential for discriminating transgenic groups of young adult mice (6-month-old) from older ones (12-month-old). Frequency-specific PCA suggests that plaque-related neurodegeneration is the predominant change captured by Raman spectroscopy, and the main differences are highlighted by vibrational modes associated with cholesterol located majorly in the lipid halo.

Spatial organization of protein aggregates on red blood cells as physical biomarkers of Alzheimer's disease pathology

Quantifying physical differences of protein aggregates implicated in Alzheimer’s disease (AD), in blood, could provide crucial information on disease stages. Here, red blood cells (RBCs) from 50 patients with neurocognitive complaints and 16 healthy individuals were profiled using an atomic force microscope (AFM). AFM measurements revealed patient age– and stage of neurocognitive disorder–dependent differences in size, shape, morphology, assembly, and prevalence of protein aggregates on RBCs, referred to as physical biomarkers. Crystals composed of fibrils were exclusively detected on RBCs for AD patients aged above 80 years. Fibril prevalence was negatively correlated with the cerebrospinal fluid (CSF) β-amyloid (Aβ) 42/40 ratio and was observed to be higher in the Aβ-positive patient category. Using a cutoff of ≥40% fibril prevalence, the CSF Aβ status was classified with 88% accuracy (sensitivity 100%, specificity 73%). The merits and challenges in integrating physical biomarkers in AD diagnosis are discussed.

The Progress of Label-Free Optical Imaging in Alzheimer's Disease Screening and Diagnosis

As the major neurodegenerative disease of dementia, Alzheimer's disease (AD) has caused an enormous social and economic burden on society. Currently, AD has neither clear pathogenesis nor effective treatments. Positron emission tomography (PET) and magnetic resonance imaging (MRI) have been verified as potential tools for diagnosing and monitoring Alzheimer's disease. However, the high costs, low spatial resolution, and long acquisition time limit their broad clinical utilization. The gold standard of AD diagnosis routinely used in research is imaging AD biomarkers with dyes or other reagents, which are unsuitable for in vivo studies owing to their potential toxicity and prolonged and costly process of the U.S. Food and Drug Administration (FDA) approval for human use. Furthermore, these exogenous reagents might bring unwarranted interference to mechanistic studies, causing unreliable results. Several label-free optical imaging techniques, such as infrared spectroscopic imaging (IRSI), Raman spectroscopic imaging (RSI), optical coherence tomography (OCT), autofluorescence imaging (AFI), optical harmonic generation imaging (OHGI), etc., have been developed to circumvent this issue and made it possible to offer an accurate and detailed analysis of AD biomarkers. In this review, we present the emerging label-free optical imaging techniques and their applications in AD, along with their potential and challenges in AD diagnosis.

Label-free Raman spectroscopy: A potential tool for early diagnosis of diabetic keratopathy

Diabetes has become a major public health problem worldwide, and the incidence of diabetes has been increasing progressively. Diabetes is prone to cause various complications, among which diabetic keratopathy (DK) emphasizes the significant impact on the cornea. The current diagnosis of DK lacks biochemical markers that can be used for early and non-invasive screening and detection. In contrast, in this study, Raman spectroscopy, which demonstrates non-destructive, label-free features, especially the unique advantage of providing molecular fingerprint information for target substances, were utilized to interrogate the intrinsic information of the corneal tissues from normal and diabetic mouse models, respectively. Visually, the Raman spectral response derived from the biochemical components and biochemical differences between the two groups were compared. Moreover, multivariate analysis methods such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were carried out for advanced statistical analysis. PCA yields a diagnostic results of 57.4% sensitivity, 89.2% specificity, 74.8% accuracy between the diabetic group and control group; Moreover, PLS-DA was employed to enhance the diagnostic ability, showing 76.1% sensitivity, 86.1% specificity, and 87.6% accuracy between the diabetic group and control group. Our proof-of-concept results show the potential of Raman spectroscopy-based techniques to help explore the underlying pathogenesis of DK disease and thus be further expanded for potential applications in the early screening of diabetic diseases.

Multimodal, label-free fluorescence and Raman imaging of amyloid deposits in snap-frozen Alzheimer's disease human brain tissue

Alzheimer's disease (AD) neuropathology is characterized by hyperphosphorylated tau containing neurofibrillary tangles and amyloid-beta (Aβ) plaques. Normally these hallmarks are studied by (immuno-) histological techniques requiring chemical pretreatment and indirect labelling. Label-free imaging enables one to visualize normal tissue and pathology in its native form. Therefore, these techniques could contribute to a better understanding of the disease. Here, we present a comprehensive study of high-resolution fluorescence imaging (before and after staining) and spectroscopic modalities (Raman mapping under pre-resonance conditions and stimulated Raman scattering (SRS)) of amyloid deposits in snap-frozen AD human brain tissue. We performed fluorescence and spectroscopic imaging and subsequent thioflavin-S staining of the same tissue slices to provide direct confirmation of plaque location and correlation of spectroscopic biomarkers with plaque morphology; differences were observed between cored and fibrillar plaques. The SRS results showed a protein peak shift towards the β-sheet structure in cored amyloid deposits. In the Raman maps recorded with 532 nm excitation we identified the presence of carotenoids as a unique marker to differentiate between a cored amyloid plaque area versus a non-plaque area without prior knowledge of their location. The observed presence of carotenoids suggests a distinct neuroinflammatory response to misfolded protein accumulations.

Biochemical Characterization of Mouse Retina of an Alzheimer's Disease Model by Raman Spectroscopy

The presence of biomarkers characteristic for Alzheimer’s disease in the retina is a controversial topic. Raman spectroscopy offers information on the biochemical composition of tissues. Thus, it could give valuable insight into the diagnostic value of retinal analysis. Within the present study, retinas of a double transgenic mouse model, that expresses a chimeric mouse/human amyloid precursor protein and a mutant form of human presenilin 1, and corresponding control group were subjected to ex vivo Raman imaging. The Raman data recorded on cross sections of whole eyes highlight the layered structure of the retina in a label-free manner. Based on the Raman information obtained from en face mounted retina samples, a discrimination between healthy and Alzheimer’s disease retinal tissue can be done with an accuracy of 85.9%. For this a partial least squares-linear discriminant analysis was applied. Therefore, although no macromolecular changes in form of, i.e., amyloid beta plaques, can be noticed based on Raman spectroscopy, subtle biochemical changes happening in the retina could lead to Alzheimer’s disease identification.

A label-free reusable aptasensor for Alzheimer's disease

To early effectively detect amyloid-beta (Aβ) oligomers, a label-free reusable aptasensor was designed. This aptasensor based on a luminescent nanoscale lanthanum-based metal-organic framework (L-MOF)-armored single-stranded DNA antibody (MOF-armored-anti-DNA antibody) as signal tags and aptamer bound to magnetic beads (Apt-MB) as capture probe. The reusable aptasensor combines signal tag and capture probe with antigen-antibody interaction. When the reusable aptasensor is formed, the strong fluorescence intensity of L-MOF will "turn off" by photo-induced electron transfer from excited states to an unfilled d shell of iron cations on the nanoparticle surface. Upon the presence of Aβ oligomers in serum samples, they can be especially distinguished with the Aβ oligomers aptamer in capture probes and then signal tags are released into the solution for developing the fluorescence aptasensor under excitation/emission 365 nm/430 nm. Meanwhile, the aptamer was recovered from the complex of Aβ oligomers/Apt-MB by heat treatment. When the temperature returns to room temperature, the recovered aptamer in the capture probe can once again bound to the MOF-armored-anti-DNA antibody for reuse. The label-free reusable aptasensor system detection has high sensitivity and selectivity toward Aβ oligomers (LOD = 0.4 pg/mL) and an excellent linear range (0.001-100 ng/mL). This strategy is a fruitful step for the development of reusable aptasensor and may turn on new avenues for the applications of Aβ oligomer detection in clinical diagnosis.Graphical abstract.