A confounder controlled machine learning approach: Group analysis and classification of schizophrenia and Alzheimer's disease using resting-state functional network connectivity.

Resting-state functional magnetic resonance imaging (rs-fMRI) has increasingly been used to study both Alzheimer's disease (AD) and schizophrenia (SZ). While most rs-fMRI studies being conducted in AD and SZ compare patients to healthy controls, it is also of interest to directly compare AD and SZ patients with each other to identify potential biomarkers shared between the disorders. However, comparing patient groups collected in different studies can be challenging due to potential confounds, such as differences in the patient's age, scan protocols, etc. In this study, we compared and contrasted resting-state functional network connectivity (rs-FNC) of 162 patients with AD and late mild cognitive impairment (LMCI), 181 schizophrenia patients, and 315 cognitively normal (CN) subjects. We used confounder-controlled rs-FNC and applied machine learning algorithms (including support vector machine, logistic regression, random forest, and k-nearest neighbor) and deep learning models (i.e., fully-connected neural networks) to classify subjects in binary and three-class categories according to their diagnosis labels (e.g., AD, SZ, and CN). Our statistical analysis revealed that FNC between the following network pairs is stronger in AD compared to SZ: subcortical-cerebellum, subcortical-cognitive control, cognitive control-cerebellum, and visual-sensory motor networks. On the other hand, FNC is stronger in SZ than AD for the following network pairs: subcortical-visual, subcortical-auditory, subcortical-sensory motor, cerebellum-visual, sensory motor-cognitive control, and within the cerebellum networks. Furthermore, we observed that while AD and SZ disorders each have unique FNC abnormalities, they also share some common functional abnormalities that can be due to similar neurobiological mechanisms or genetic factors contributing to these disorders' development. Moreover, we achieved an accuracy of 85% in classifying subjects into AD and SZ where default mode, visual, and subcortical networks contributed the most to the classification and accuracy of 68% in classifying subjects into AD, SZ, and CN with the subcortical domain appearing as the most contributing features to the three-way classification. Finally, our findings indicated that for all classification tasks, except AD vs. SZ, males are more predictable than females.

Computerized decision support is an effective approach to select memory clinic patients for amyloid-PET.

BACKGROUND: The use of amyloid-PET in dementia workup is upcoming. At the same time, amyloid-PET is costly and limitedly available. While the appropriate use criteria (AUC) aim for optimal use of amyloid-PET, their limited sensitivity hinders the translation to clinical practice. Therefore, there is a need for tools that guide selection of patients for whom amyloid-PET has the most clinical utility. We aimed to develop a computerized decision support approach to select patients for amyloid-PET. METHODS: We included 286 subjects (135 controls, 108 Alzheimer's disease dementia, 33 frontotemporal lobe dementia, and 10 vascular dementia) from the Amsterdam Dementia Cohort, with available neuropsychology, APOE, MRI and [18F]florbetaben amyloid-PET. In our computerized decision support approach, using supervised machine learning based on the DSI classifier, we first classified the subjects using only neuropsychology, APOE, and quantified MRI. Then, for subjects with uncertain classification (probability of correct class (PCC) < 0.75) we enriched classification by adding (hypothetical) amyloid positive (AD-like) and negative (normal) PET visual read results and assessed whether the diagnosis became more certain in at least one scenario (PPC≥0.75). If this was the case, the actual visual read result was used in the final classification. We compared the proportion of PET scans and patients diagnosed with sufficient certainty in the computerized approach with three scenarios: 1) without amyloid-PET, 2) amyloid-PET according to the AUC, and 3) amyloid-PET for all patients. RESULTS: The computerized approach advised PET in n = 60(21%) patients, leading to a diagnosis with sufficient certainty in n = 188(66%) patients. This approach was more efficient than the other three scenarios: 1) without amyloid-PET, diagnostic classification was obtained in n = 155(54%), 2) applying the AUC resulted in amyloid-PET in n = 113(40%) and diagnostic classification in n = 156(55%), and 3) performing amyloid-PET in all resulted in diagnostic classification in n = 154(54%). CONCLUSION: Our computerized data-driven approach selected 21% of memory clinic patients for amyloid-PET, without compromising diagnostic performance. Our work contributes to a cost-effective implementation and could support clinicians in making a balanced decision in ordering additional amyloid PET during the dementia workup.

Unravelling the complex interplay of cuproptosis, lncRNAs, and immune infiltration in Alzheimer's disease: a step towards novel therapeutic targets.

BACKGROUND: Cuproptosis, a type of cell death involving copper ion accumulation and oxidative stress, has been implicated in the development of Alzheimer's disease (AD). AIM: This study aimed to explore the potential mechanisms and roles of cuproptosis-related genes (CRGs), long non-coding RNAs (lncRNAs), and immune cells in the development of cuproptosis in AD. SUBJECTS AND METHODS: Gene expression profiles of AD were acquired from the Gene Expression Omnibus (GEO) database, and differential analysis was conducted to identify CRGs. Random Forest (RF) modelling was employed to select the most crucial CRGs, which were subsequently validated in the test set. A nomogram model was created to predict AD risk and categorise AD subtypes based on the identified CRGs. A lncRNA-related ceRNA network was built, and immune cell infiltration analysis was conducted. RESULTS: Twelve differentially expressed CRGs were identified in the AD dataset. The RF model pinpointed the five most critical CRGs, which were validated in the test set with an AUC of 0.90. A lncRNA-related ceRNA network was developed, and immune cell infiltration analysis revealed high levels of M1 macrophages and mast cells, along with low levels of memory B cells in AD samples. Correlation analysis unveiled associations between CRGs, lncRNAs, and differentially infiltrating immune cells. CONCLUSION: This research offers insights into the potential mechanisms and roles of CRGs, lncRNAs, and immune cells in the development of cuproptosis in AD. The identified CRGs and lncRNAs may serve as potential therapeutic targets for AD, and the nomogram model may assist in early AD diagnosis and subtyping.

Locus coeruleus integrity is related to an exploitation-based decision-making bias in older adulthood.

Optimal decision-making balances exploration for new information against exploitation of known rewards, a process mediated by the locus coeruleus and its norepinephrine projections. We predicted that an exploitation-bias that emerges in older adulthood would be associated with lower microstructural integrity of the locus coeruleus. Leveraging in vivo histological methods from quantitative MRI-magnetic transfer saturation-we provide evidence that older age is associated with lower locus coeruleus integrity. Critically, we demonstrate that an exploitation bias in older adulthood, assessed with a foraging task, is sensitive and specific to lower locus coeruleus integrity. Because the locus coeruleus is uniquely vulnerable to Alzheimer's disease pathology, our findings suggest that aging, and a presymptomatic trajectory of Alzheimer's related decline, may fundamentally alter decision-making abilities in later life.

Transcriptomic Analysis of Lipid Metabolism Genes in Alzheimer's Disease: Highlighting Pathological Outcomes and Compartmentalized Immune Status.

The dysregulation of lipid metabolism has been strongly associated with Alzheimer's disease (AD) and has intricate connections with various aspects of disease progression, such as amyloidogenesis, bioenergetic deficit, oxidative stress, neuroinflammation, and myelin degeneration. Here, a comprehensive bioinformatic assessment was conducted on lipid metabolism genes in the brains and peripheral blood of AD-derived transcriptome datasets, characterizing the correlation between differentially expressed genes (DEGs) of lipid metabolism and disease pathologies, as well as immune cell preferences. Through the application of weighted gene co-expression network analysis (WGCNA), modules eigengenes related to lipid metabolism were pinpointed, and the examination of their molecular functions within biological processes, molecular pathways, and their associations with pathological phenotypes and molecular networks has been characterized. Analysis of biological networks indicates notable discrepancies in the expression patterns of the DEGs between neuronal and immune cells, as well as variations in cell type enrichments within both brain tissue and peripheral blood. Additionally, drugs targeting the DEGs from central and peripheral and a diagnostic model for hub genes from the blood were retrieved and assessed, some of which were shown to be useful for therapeutic and diagnostic. These results revealed the distinctive pattern of transcriptionally abnormal lipid metabolism in central, peripheral, and immune cell activation, providing valuable insight into lipid metabolism for diagnosing and guiding more effective treatment for AD.

Diabetes-related clinical and microstructural white matter changes in patients with Alzheimer's disease.

AIM: Although there exists substantial epidemiological evidence indicating an elevated risk of dementia in individuals with diabetes, our understanding of the neuropathological underpinnings of the association between Type-2 diabetes mellitus (T2DM) and Alzheimer's disease (AD) remains unclear. This study aims to unveil the microstructural brain changes associated with T2DM in AD and identify the clinical variables contributing to these changes. METHODS: In this retrospective study involving 64 patients with AD, 31 individuals had concurrent T2DM. The study involved a comparative analysis of diffusion tensor imaging (DTI) images and clinical features between patients with and without T2DM. The FSL FMRIB software library was used for comprehensive preprocessing and tractography analysis of DTI data. After eddy current correction, the "bedpost" model was utilized to model diffusion parameters. Linear regression analysis with a stepwise method was used to predict the clinical variables that could lead to microstructural white matter changes. RESULTS: We observed a significant impairment in the left superior longitudinal fasciculus (SLF) among patients with AD who also had T2DM. This impairment in patients with AD and T2DM was associated with an elevation in creatine levels. CONCLUSION: The white matter microstructure in the left SLF appears to be sensitive to the impairment of kidney function associated with T2DM in patients with AD. The emergence of AD in association with T2DM may be driven by mechanisms distinct from the typical AD pathology. Compromised renal function in AD could potentially contribute to impaired white matter integrity.

Comparative studies of hair shaft components between healthy and diseased donors.

Globally, the rapid aging of the population is predicted to become even more severe in the second half of the 21st century. Thus, it is expected to establish a growing expectation for innovative, non-invasive health indicators and diagnostic methods to support disease prevention, care, and health promotion efforts. In this study, we aimed to establish a new health index and disease diagnosis method by analyzing the minerals and free amino acid components contained in hair shaft. We first evaluated the range of these components in healthy humans and then conducted a comparative analysis of these components in subjects with diabetes, hypertension, androgenetic alopecia, major depressive disorder, Alzheimer's disease, and stroke. In the statistical analysis, we first used a student's t test to compare the hair components of healthy people and those of patients with various diseases. However, many minerals and free amino acids showed significant differences in all diseases, because the sample size of the healthy group was very large compared to the sample size of the disease group. Therefore, we attempted a comparative analysis based on effect size, which is not affected by differences in sample size. As a result, we were able to narrow down the minerals and free amino acids for all diseases compared to t test analysis. For diabetes, the t test narrowed down the minerals to 15, whereas the effect size measurement narrowed it down to 3 (Cr, Mn, and Hg). For free amino acids, the t test narrowed it down to 15 minerals. By measuring the effect size, we were able to narrow it down to 7 (Gly, His, Lys, Pro, Ser, Thr, and Val). It is also possible to narrow down the minerals and free amino acids in other diseases, and to identify potential health indicators and disease-related components by using effect size.

Towards early diagnosis of Alzheimer's disease: advances in immune-related blood biomarkers and computational approaches.

Alzheimer's disease has an increasing prevalence in the population world-wide, yet current diagnostic methods based on recommended biomarkers are only available in specialized clinics. Due to these circumstances, Alzheimer's disease is usually diagnosed late, which contrasts with the currently available treatment options that are only effective for patients at an early stage. Blood-based biomarkers could fill in the gap of easily accessible and low-cost methods for early diagnosis of the disease. In particular, immune-based blood-biomarkers might be a promising option, given the recently discovered cross-talk of immune cells of the central nervous system with those in the peripheral immune system. Here, we give a background on recent advances in research on brain-immune system cross-talk in Alzheimer's disease and review machine learning approaches, which can combine multiple biomarkers with further information (e.g. age, sex, APOE genotype) into predictive models supporting an earlier diagnosis. In addition, mechanistic modeling approaches, such as agent-based modeling open the possibility to model and analyze cell dynamics over time. This review aims to provide an overview of the current state of immune-system related blood-based biomarkers and their potential for the early diagnosis of Alzheimer's disease.

Interrelationship of Sleep Disturbances and Cognitive Status on Mortality.

Sleep disturbances may promote the development and advancement of Alzheimer's disease. Our purpose was to determine if sleep disturbances were associated with earlier mortality while accounting for cognition. The National Alzheimer's Coordinating Center database was used to evaluate mortality risk conferred by sleep, and the Montreal Cognitive Assessment score determined cognitive status. Demographics, sleep disturbances, cognitive status, and comorbid/other neuropsychiatric conditions were examined as predictors of survival time via Cox regression. The sample (N = 31,110) had a median age [interquartile range] of 72 [66, 79] years, MoCA score of 23 [16, 26], and survival time of 106.0 months [104.0,108.0]; 10,278 (33%) died during follow-up; 21% (n = 6461) experienced sleep disturbances. Sleep disturbances impacted survival time depending on cognition, with the greatest effect in transition from normal to cognitive impairment (P < .001). Findings support that sleep disturbances negatively impact survival time, and the impact of sleep disturbances on survival time is interrelated with cognition.

Mitigating cognitive deficits with teriflunomide: unraveling PI3K-modulated behavioral outcomes in mice.

BACKGROUND: Alzheimer's disease is a leading neurological disorder that gradually impairs memory and cognitive abilities, ultimately leading to the inability to perform even basic daily tasks. Teriflunomide is known to preserve neuronal activity and protect mitochondria in the brain slices exposed to oxidative stress. The current research was undertaken to investigate the teriflunomide's cognitive rescuing abilities against scopolamine-induced comorbid cognitive impairment and its influence on phosphatidylinositol-3-kinase (PI3K) inhibition-mediated behavior alteration in mice. METHODS: Swiss albino mice were divided into 7 groups; vehicle control, scopolamine, donepezil + scopolamine, teriflunomide (10 mg/kg) + scopolamine; teriflunomide (20 mg/kg) + scopolamine, LY294002 and LY294002 + teriflunomide (20 mg/kg). Mice underwent a nine-day protocol, receiving scopolamine injections (2 mg/kg) for the final three days to induce cognitive impairment. Donepezil, teriflunomide, and LY294002 treatments were given continuously for 9 days. MWM, Y-maze, OFT and rota-rod tests were conducted on days 7 and 9. On the last day, blood samples were collected for serum TNF-α analysis, after which the mice were sacrificed, and brain samples were harvested for oxidative stress analysis. RESULTS: Scopolamine administration for three consecutive days increased the time required to reach the platform in the MWM test, whereas, reduced the percentage of spontaneous alternations in the Y-maze, number of square crossing in OFT and retention time in the rota-rod test. In biochemical analysis, scopolamine downregulated the brain GSH level, whereas it upregulated the brain TBARS and serum TNF-α levels. Teriflunomide treatment effectively mitigated all the behavioral and biochemical alterations induced by scopolamine. Furthermore, LY294002 administration reduced the memory function and GSH level, whereas, uplifted the serum TNF-α levels. Teriflunomide abrogated the memory-impairing, GSH-lowering, and TNF-α-increasing effects of LY294002. CONCLUSION: Our results delineate that the improvement in memory, locomotion, and motor coordination might be attributed to the oxidative and inflammatory stress inhibitory potential of teriflunomide. Moreover, PI3K inhibition-induced memory impairment might be attributed to reduced GSH levels and increased TNF-α levels.

A new and unified method for regression analysis of interval-censored failure time data under semiparametric transformation models with missing covariates.

This paper discusses regression analysis of interval-censored failure time data arising from semiparametric transformation models in the presence of missing covariates. Although some methods have been developed for the problem, they either apply only to limited situations or may have some computational issues. Corresponding to these, we propose a new and unified two-step inference procedure that can be easily implemented using the existing or standard software. The proposed method makes use of a set of working models to extract partial information from incomplete observations and yields a consistent estimator of regression parameters assuming missing at random. An extensive simulation study is conducted and indicates that it performs well in practical situations. Finally, we apply the proposed approach to an Alzheimer's Disease study that motivated this study.

Electropositive Citric Acid-Polyethyleneimine Carbon Dots Carrying the PINK1 Gene Regulate ATP-Related Metabolic Dysfunction in APP/PS1-N2a Cells.

(1) Background: Alzheimer's disease (AD) is characterized by ß-amyloid (Aß) peptide accumulation and mitochondrial dysfunction during the early stage of disease. PINK1 regulates the balance between mitochondrial homeostasis and bioenergy supply and demand via the PINK1/Parkin pathway, Na+/Ca2+ exchange, and other pathways. (2) Methods: In this study, we synthesized positively charged carbon dots (CA-PEI CDs) using citric acid (CA) and polyethyleneimine (PEI) and used them as vectors to express PINK1 genes in the APP/PS1-N2a cell line to determine mitochondrial function, electron transport chain (ETC) activity, and ATP-related metabolomics. (3) Results: Our findings showed that the CA-PEI CDs exhibit the characteristics of photoluminescence, low toxicity, and concentrated DNA. They are ideal biological carriers for gene delivery. PINK1 overexpression significantly increased the mitochondrial membrane potential in APP/PS1-N2a cells and reduced reactive-oxygen-species generation and Aß1-40 and Aß1-42 levels. An increase in the activity of NADH ubiquinone oxidoreductase (complex I, CI) and cytochrome C oxidase (complex IV, CIV) induces the oxidative phosphorylation of mitochondria, increasing ATP generation. (4) Conclusions: These findings indicate that the PINK gene can alleviate AD by increasing bioenergetic metabolism, reducing Aß1-40 and Aß1-42, and increasing ATP production.

Protection of Si Nanowires against Aß Toxicity by the Inhibition of Aß Aggregation.

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by the accumulation of amyloid beta (Aß) plaques in the brain. Aß1-42 is the main component of Aß plaque, which is toxic to neuronal cells. Si nanowires (Si NWs) have the advantages of small particle size, high specific surface area, and good biocompatibility, and have potential application prospects in suppressing Aß aggregation. In this study, we employed the vapor-liquid-solid (VLS) growth mechanism to grow Si NWs using Au nanoparticles as catalysts in a plasma-enhanced chemical vapor deposition (PECVD) system. Subsequently, these Si NWs were transferred to a phosphoric acid buffer solution (PBS). We found that Si NWs significantly reduced cell death in PC12 cells (rat adrenal pheochromocytoma cells) induced by Aß1-42 oligomers via double staining with 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and fluorescein diacetate/propyl iodide (FDA/PI). Most importantly, pre-incubated Si NWs largely prevented Aß1-42 oligomer-induced PC12 cell death, suggesting that Si NWs exerts an anti-Aß neuroprotective effect by inhibiting Aß aggregation. The analysis of Fourier Transform Infrared (FTIR) results demonstrates that Si NWs reduce the toxicity of fibrils and oligomers by intervening in the formation of ß-sheet structures, thereby protecting the viability of nerve cells. Our findings suggest that Si NWs may be a potential therapeutic agent for AD by protecting neuronal cells from the toxicity of Aß1-42.

Effects of SPI1-mediated transcriptome remodeling on Alzheimer's disease-related phenotypes in mouse models of Aß amyloidosis.

SPI1 was recently reported as a genetic risk factor for Alzheimer's disease (AD) in large-scale genome-wide association studies. However, it is unknown whether SPI1 should be downregulated or increased to have therapeutic benefits. To investigate the effect of modulating SPI1 levels on AD pathogenesis, we performed extensive biochemical, histological, and transcriptomic analyses using both Spi1-knockdown and Spi1-overexpression mouse models. Here, we show that the knockdown of Spi1 expression significantly exacerbates insoluble amyloid-ß (Aß) levels, amyloid plaque deposition, and gliosis. Conversely, overexpression of Spi1 significantly ameliorates these phenotypes and dystrophic neurites. Further mechanistic studies using targeted and single-cell transcriptomics approaches demonstrate that altered Spi1 expression modulates several pathways, such as immune response pathways and complement system. Our data suggest that transcriptional reprogramming by targeting transcription factors, like Spi1, might hold promise as a therapeutic strategy. This approach could potentially expand the current landscape of druggable targets for AD.

Teamwork and Nurse Care Coordination in Home Healthcare.

Home healthcare agencies provide interdisciplinary care to millions of individuals annually. Care is typically led by registered nurses who often determine additional disciplines need to be included in the plan of care. We found that, although persons living with dementia represent about 30% of the home healthcare population, data from our home healthcare system showed that over a 1-year period with 36,443 home care episodes, only 29.6% had one or more social worker visits. Recognizing Alzheimer's disease-related dementia as a terminal condition and shifting toward a palliative care approach can be a challenge in home healthcare where care is focused on restorative care or rehabilitative goals with a primary focus on improvement in condition. The goal of this article is to present insights into nurse-led care coordination and teamwork and provide implications for practice.

A mathematical model on the propagation of tau pathology in neurodegenerative diseases.

A system of partial differential equations is developed to study the spreading of tau pathology in the brain for Alzheimer's and other neurodegenerative diseases. Two cases are considered with one assuming intracellular diffusion through synaptic activities or the nanotubes that connect the adjacent cells. The other, in addition to intracellular spreading, takes into account of the secretion of the tau species which are able to diffuse, move with the interstitial fluid flow and subsequently taken up by the surrounding cells providing an alternative pathway for disease spreading. Cross membrane transport of the tau species are considered enabling us to examine the role of extracellular clearance of tau protein on the disease status. Bifurcation analysis is carried out for the steady states of the spatially homogeneous system yielding the results that fast cross-membrane transport combined with effective extracellular clearance is key to maintain the brain's healthy status. Numerical simulations of the first case exhibit solutions of travelling wave form describing the gradual outward spreading of the pathology; whereas the second case shows faster spreading with the buildup of neurofibrillary tangles quickly elevated throughout. Our investigation thus indicates that the gradual progression of the intracellular spreading case is more consistent with the clinical observations of the development of Alzheimer's disease.

Lead optimization based design, synthesis, and pharmacological evaluation of quinazoline derivatives as multi-targeting agents for Alzheimer's disease treatment.

The complexity and multifaceted nature of Alzheimer's disease (AD) have driven us to further explore quinazoline scaffolds as multi-targeting agents for AD treatment. The lead optimization strategy was utilized in designing of new series of derivatives (AK-1 to AK-14) followed by synthesis, characterization, and pharmacological evaluation against human cholinesterase's (hChE) and ß-secretase (hBACE-1) enzymes. Amongst them, compounds AK-1, AK-2, and AK-3 showed good and significant inhibitory activity against both hAChE and hBACE-1 enzymes with favorable permeation across the blood-brain barrier. The most active compound AK-2 revealed significant propidium iodide (PI) displacement from the AChE-PAS region and was non-neurotoxic against SH-SY5Y cell lines. The lead molecule (AK-2) also showed Aß aggregation inhibition in a self- and AChE-induced Aß aggregation, Thioflavin-T assay. Further, compound AK-2 significantly ameliorated Aß-induced cognitive deficits in the Aß-induced Morris water maze rat model and demonstrated a significant rescue in eye phenotype in the Aꞵ-phenotypic drosophila model of AD. Ex-vivo immunohistochemistry (IHC) analysis on hippocampal rat brains showed reduced Aß and BACE-1 protein levels. Compound AK-2 suggested good oral absorption via pharmacokinetic studies and displayed a good and stable ligand-protein interaction in in-silico molecular modeling analysis. Thus, the compound AK-2 can be regarded as a lead molecule and should be investigated further for the treatment of AD.

Estradiol improves behavior in FAD transgenic mice that express APOE3 but not APOE4 after ovariectomy.

Increasing evidence suggests that female individuals have a higher Alzheimer's disease (AD) risk associated with post-menopausal loss of circulating estradiol (E2). However, clinical data are conflicting on whether E2 lowers AD risk. One potential contributing factor is APOE. The greatest genetic risk factor for AD is APOE4, a factor that is pronounced in female individuals post-menopause. Clinical data suggests that APOE impacts the response of AD patients to E2 replacement therapy. However, whether APOE4 prevents, is neutral, or promotes any positive effects of E2 is unclear. Therefore, our goal was to determine whether APOE modulates the impact of E2 on behavior and AD pathology in vivo. To that end, mice that express human APOE3 (E3FAD) or APOE4 (E4FAD) and overproduce Aß42 were ovariectomized at either 4 months (early) or 8 months (late) and treated with vehicle or E2 for 4 months. In E3FAD mice, we found that E2 mitigated the detrimental effect of ovariectomy on memory, with no effect on Aß in the early paradigm and only improved learning in the late paradigm. Although E2 lowered Aß in E4FAD mice in the early paradigm, there was no impact on learning or memory, possibly due to higher Aß pathology compared to E3FAD mice. In the late paradigm, there was no effect on learning/memory and Aß pathology in E4FAD mice. Collectively, these data support the idea that, in the presence of Aß pathology, APOE impacts the response to E2 supplementation post-menopause.

Nucleic acid aptamer-based electrochemical sensor for the detection of serum P-tau231 and the instant screening test of Alzheimer's disease.

The instant screening of patients with a tendency towards developing Alzheimer's disease (AD) is significant for providing preventive measures and treatment. However, the current imaging-based technology cannot meet the requirements in the early stage. Developing biosensor-based liquid biopsy technology could be overcoming this bottleneck problem. Herein, we developed a simple, low-cost, and sensitive electrochemical aptamer biosensor for detecting phosphorylated tau protein threonine 231 (P-tau231), the earliest and one of the most efficacious abnormally elevated biomarkers of AD. Gold nanoparticles (AuNPs) were electrochemically synthesized on a glassy carbon electrode as the transducer, exhibiting excellent conductivity, and were applied to amplify the electrochemical signal. A nucleic acid aptamer was designed as the receptor to capture the P-tau231 protein, specifically through the formation of an aptamer-antigen complex. The proposed biosensor showed excellent sensitivity in detecting P-tau 231, with a broad linear detection range from 10 to 107 pg/mL and a limit of detection (LOD) of 2.31 pg/mL. The recoveries of the biosensor in human serum ranged from 97.59 to 103.26%, demonstrating that the biosensor could be used in complex practical samples. In addition, the results showed that the developed biosensor has good repeatability, reproducibility, and stability, which provides a novel method for the early screening of AD.