White matter hyperintensity on MRI and plasma Aß42/40 ratio additively increase the risk of cognitive impairment in hypertensive adults.

INTRODUCTION: Dementia often involves comorbid Alzheimer's and vascular pathology, but their combined impact warrants additional study. METHODS: We analyzed the Systolic Blood Pressure Intervention Trial and categorized white matter hyperintensity (WMH) volume into highest versus lowest/mid tertile and the amyloid beta (Aß)42/40 ratio into lowest versus mid/highest ratio tertile. Using these binary variables, we created four exposure categories: (1) combined low risk, (2) Aß risk, (3) WMH risk, and (4) combined high risk. RESULTS: In the cohort of 467 participants (mean age 69.7 ± 7.1, 41.8% female, 31.9% nonwhite or Hispanic) during 4.8 years of follow-up and across the four exposure categories the rates of cognitive impairment were 5.3%, 7.8%, 11.8%, and 22.6%. Compared to the combined low-risk category, the adjusted hazard ratio for cognitive impairment was 4.12 (95% confidence interval, 1.71 to 9.94) in the combined high-risk category. DISCUSSION: This study emphasizes the potential impact of therapeutic approaches to dementia prevention that target both vascular and amyloid pathology. HIGHLIGHTS: White matter hyperintensity (WMH) and plasma amyloid (Aß42/40) are additive risk factors for the development of cognitive impairment in the SPRINT MIND trial. Individuals in the high-risk categories of both WMH and Aß42/40 had a near fivefold increase in risk of cognitive impairment during 4.8 years of follow-up on average. These findings suggest that treatment strategies targeting both vascular health and amyloid burden warrant further research.

Comparison of Lung Tissue-Derived Extracellular Vesicles Using Multiple Dissociation Methods for Profiling Protein Biomarkers.

Extracellular vesicles (EVs) operate as chemical messengers that facilitate intercellular communication. Emerging evidence has demonstrated that lung tissue-derived EVs play pivotal roles in pulmonary physiological processes and have potential as biomarkers and therapeutics for lung diseases. Multiple methods have been proposed for the isolation of lung tissue-derived EVs. However, the effects of different tissue pre-treatments on lung EV isolation and subsequent disease biomarker discovery have not yet been comprehensively investigated. In this study, we compared the physical characteristics, recovery yields, and protein compositions of EVs isolated from lung tissues using three methods based on different tissue dissociation principles. Methodologically, the beneficial roles of blood perfusion and gentle meshing were emphasized based on their impact on EV yield and purity. These results demonstrate that different methods enrich distinct subpopulations of EVs that exhibit significant differences in their protein cargo and surface properties. These disparities directly affect the diagnostic detection of marker proteins related to lung diseases, including lung tumors, asthma, and pulmonary fibrosis. Collectively, these findings highlight the variations in EV characteristics resulting from the applied approaches and offer compelling suggestions for guiding researchers in selecting a suitable isolation method based on downstream functional studies and clinical applications.

Comparative profiling of whole-cell and exosome samples reveals protein signatures that stratify breast cancer subtypes.

Identifying novel breast cancer biomarkers will improve patient stratification, enhance therapeutic outcomes, and help develop non-invasive diagnostics. We compared the proteomic profiles of whole-cell and exosomal samples of representative breast cancer cell subtypes to evaluate the potential of extracellular vesicles as non-invasive disease biomarkers in liquid biopsies. Overall, differentially-expressed proteins in whole-cell and exosome samples (which included markers for invasion, metastasis, angiogenesis, and drug resistance) effectively discriminated subtypes; furthermore, our results confirmed that the proteomic profile of exosomes reflects breast cancer cell-of-origin, which underscores their potential as disease biomarkers. Our study will contribute to identifying biomarkers that support breast cancer patient stratification and developing novel therapeutic strategies. We include an open, interactive web tool to explore the data as a molecular resource that can explain the role of these protein signatures in breast cancer classification.

The ADNI PET Core at 20.

 : The Alzheimer's Disease Neuroimaging Initiative (ADNI) PET Core has evolved over time, beginning with positron emission tomography (PET) imaging of a subsample of participants with [18F]fluorodeoxyglucose (FDG)-PET, adding tracers for measurement of ß-amyloid, followed by tau tracers. This review examines the evolution of the ADNI PET Core, the novel aspects of PET imaging in each stage of ADNI, and gives an accounting of PET images available in the ADNI database. The ADNI PET Core has been and continues to be a rich resource that provides quantitative PET data and preprocessed PET images to the scientific community, allowing interrogation of both basic and clinically relevant questions. By standardizing methods across different PET scanners and multiple PET tracers, the Core has demonstrated the feasibility of large-scale, multi-center PET studies. Data managed and disseminated by the PET Core has been critical to defining pathophysiological models of Alzheimer's disease (AD) and helped to drive methods used in modern therapeutic trials. HIGHLIGHTS: The ADNI PET Core began with FDG-PET and now includes three amyloid and three tau PET ligands. The PET Core has standardized acquisition and analysis of multitracer PET images. The ADNI PET Core helped to develop methods that have facilitated clinical trials in AD.

Process, advances, and perspectives of graphene oxide-SELEX for the development of aptamer molecular probes: A comprehensive review.

BACKGROUND: Aptamers are screened via the systematic evolution of ligands by exponential enrichment (SELEX) and are widely used in molecular diagnostics and targeted therapies. The development of efficient and convenient SELEX technology has facilitated rapid access to high-performance aptamers, thereby advancing the aptamer industry. Graphene oxide (GO) serves as an immobilization matrix for libraries in GO-SELEX, making it suitable for screening aptamers against diverse targets. RESULTS: This review summarizes the detailed steps involved in GO-SELEX, including monitoring methods, various sublibrary acquisition methods, and practical applications from its inception to the present day. In addition, the potential of GO-SELEX in the development of broad-spectrum aptamers is explored, and its current limitations for future development are emphasized. This review effectively promotes the application of the GO-SELEX technique by providing valuable insights and assisting researchers interested in conducting related studies. SIGNIFICANCE AND NOVELTY: To date, no review on the topic of GO-SELEX has been published, making it challenging for researchers to initiate studies in this area. We believe that this review will broaden the SELEX options available to researchers, ensuring that they can meet the growing demand for molecular probes in the scientific domain.

The role of the Alzheimer's Disease Neuroimaging Initiative in establishing the Dominantly Inherited Alzheimer Network.

The Dominantly Inherited Alzheimer Network (DIAN) initially was funded by the National Institute on Aging (NIA) in 2008 and thus was able to adopt and incorporate the protocols developed by the Alzheimer's Disease Neuroimaging Initiative (ADNI) that had been established by the NIA in 2004. The use of ADNI protocols for DIAN neuroimaging studies and assays of biological fluids for Alzheimer disease (AD) biomarkers permitted examination of the hypothesis that autosomal dominant AD (ADAD), studied by DIAN, and "sporadic" late-onset AD (LOAD), studied by ADNI, shared the same pathobiological construct. In a collaborative effort, the longitudinal DIAN and ADNI databases were compared and the findings supported the conclusion that ADAD and LOAD share a similar pathophysiology. The importance of the DIAN study thus is amplified by its relevance to LOAD, as characterized by the "parent" ADNI program.

An Overview of the ADReSS-M Signal Processing Grand Challenge on Multilingual Alzheimer's Dementia Recognition Through Spontaneous Speech.

The ADReSS-M Signal Processing Grand Challenge was held at the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023. The challenge targeted difficult automatic prediction problems of great societal and medical relevance, namely, the detection of Alzheimer's Dementia (AD) and the estimation of cognitive test scoress. Participants were invited to create models for the assessment of cognitive function based on spontaneous speech data. Most of these models employed signal processing and machine learning methods. The ADReSS-M challenge was designed to assess the extent to which predictive models built based on speech in one language generalise to another language. The language data compiled and made available for ADReSS-M comprised English, for model training, and Greek, for model testing and validation. To the best of our knowledge no previous shared research task investigated acoustic features of the speech signal or linguistic characteristics in the context of multilingual AD detection. This paper describes the context of the ADReSS-M challenge, its data sets, its predictive tasks, the evaluation methodology we employed, our baseline models and results, and the top five submissions. The paper concludes with a summary discussion of the ADReSS-M results, and our critical assessment of the future outlook in this field.

ESMSec: Prediction of Secreted Proteins in Human Body Fluids Using Protein Language Models and Attention.

The secreted proteins of human body fluid have the potential to be used as biomarkers for diseases. These biomarkers can be used for early diagnosis and risk prediction of diseases, so the study of secreted proteins of human body fluid has great application value. In recent years, the deep-learning-based transformer language model has transferred from the field of natural language processing (NLP) to the field of proteomics, leading to the development of protein language models (PLMs) for protein sequence representation. Here, we propose a deep learning framework called ESM Predict Secreted Proteins (ESMSec) to predict three types of proteins secreted in human body fluid. The ESMSec is based on the ESM2 model and attention architecture. Specifically, the protein sequence data are firstly put into the ESM2 model to extract the feature information from the last hidden layer, and all the input proteins are encoded into a fixed 1000 × 480 matrix. Secondly, multi-head attention with a fully connected neural network is employed as the classifier to perform binary classification according to whether they are secreted into each body fluid. Our experiment utilized three human body fluids that are important and ubiquitous markers. Experimental results show that ESMSec achieved average accuracy of 0.8486, 0.8358, and 0.8325 on the testing datasets for plasma, cerebrospinal fluid (CSF), and seminal fluid, which on average outperform the state-of-the-art (SOTA) methods. The outstanding performance results of ESMSec demonstrate that the ESM can improve the prediction performance of the model and has great potential to screen the secretion information of human body fluid proteins.

Developing portable and controllable fluorescence capillary imprinted sensor for visual detection Crohn's disease biomarkers.

Simultaneous detection of multiple biomarker levels is essential to improve the accuracy of early diagnosis. Introducing capillary will simplify procedure, less time, and reduce reagent consumption for point-of-care testing of biomarkers. Here, we developed a portable and controllable smartphone-integrated fluorescence capillary imprinted sensing platform for the accuracy visual detection of Crohn's disease biomarkers (lysozyme, Fe3+) using single-excitation/double-signal detection. A novel controllable capillary coating strategy was developed by static gas-driven coating method for synthesis uniform fluorescence capillary imprinted sensor (Si-CD/g-CdTe@MIP capillary sensor). When Fe3+ and lysozyme were added, the fluorescence intensity of Si-CD/g-CdTe@MIP capillary sensor was quenched at 426 nm and enhanced at 546 nm, respectively. This Si-CD/g-CdTe@MIP capillary sensor has high sensitivity and selectivity for quantification lysozyme and Fe3+ simultaneously with the detection limit of 0.098 nM and 0.20 nM, respectively. In addition, the smartphone-integrated Si-CD/g-CdTe@MIP capillary sensor was applied for the intelligent detection of lysozyme and Fe3+, in which the detection limit was calculated as 0.32 nM and 0.65 nM. The smartphone-integrated visual Si-CD/g-CdTe@MIP capillary sensor realized ultrasensitive microanalysis (18 µL/time) of biomarkers in health man and Crohn 's patients, providing a novel strategy for early diagnosis of Crohn 's disease.

Association of glial fibrillary acid protein, Alzheimer's disease pathology and cognitive decline.

Increasing evidence shows that neuroinflammation is a possible modulator of tau spread effects on cognitive impairment in Alzheimer's disease. In this context, plasma levels of the glial fibrillary acidic protein (GFAP) have been suggested to have a robust association with Alzheimer's disease pathophysiology. This study aims to assess the correlation between plasma GFAP and Alzheimer's disease pathology, and their synergistic effect on cognitive performance and decline. A cohort of 122 memory clinic subjects with amyloid and tau positron emission tomography, MRI scans, plasma GFAP, and Mini-Mental State Examination (MMSE) was included in the study. A subsample of 94 subjects had a follow-up MMSE score at least one year after baseline. Regional and voxel-based correlations between Alzheimer's disease biomarkers and plasma GFAP were assessed. Mediation analyses were performed to evaluate the effects of plasma GFAP on the association between amyloid and tau PET, and tau PET and cognitive impairment and decline. GFAP was associated with increased tau PET ligand uptake in the lateral temporal and inferior temporal lobes in a strong left-sided pattern independently of age, gender, education, amyloid, and APOE status (ß=0.001, p < 0.01). The annual rate of MMSE change was significantly and independently correlated with both GFAP (ß=0.006, p < 0.01) and global tau SUVR (ß=4.33, p < 0.01), but not with amyloid burden. Partial mediation effects of GFAP were found on the association between amyloid and tau pathology (13.7%), and between tau pathology and cognitive decline (17.4%), but not on global cognition at baseline. Neuroinflammation measured by circulating GFAP is independently associated with tau Alzheimer's disease pathology and with cognitive decline, suggesting neuroinflammation as a potential target for future disease-modifying trials targeting tau pathology. Peretti et al. show that a circulatory marker of neuroinflammation-glial fibrillary acidic protein-is associated with tau pathology in lateral temporal and frontal regions in patients with Alzheimer's disease, independent of amyloid load. Neuroinflammation appears to modulate the association between amyloid and tau biomarkers.

Fast, sensitive LC-MS resolution of α -hydroxy acid biomarkers via SPP-teicoplanin and an alternative UV detection approach.

Enantioseparation of α -hydroxy acids is essential since specific enantiomers of these compounds can be used as disease biomarkers for diagnosis and prognosis of cancer, brain diseases, kidney diseases, diabetes, etc., as well as in the food industry to ensure quality. HPLC methods were developed for the enantioselective separation of 11 α -hydroxy acids using a superficially porous particle-based teicoplanin (TeicoShell) chiral stationary phase. The retention behaviors observed for the hydroxy acids were HILIC, reversed phase, and ion-exclusion. While both mass spectrometry and UV spectroscopy detection methods could be used, specific mobile phases containing ammonium formate and potassium dihydrogen phosphate, respectively, were necessary with each approach. The LC-MS mode was approximately two orders of magnitude more sensitive than UV detection. Mobile phase acidity and ionic strength significantly affected enantioresolution and enantioselectivity. Interestingly, higher ionic strength resulted in increased retention and enantioresolution. It was noticed that for formate-containing mobile phases, using acetonitrile as the organic modifier usually resulted in greater enantioresolution compared to methanol. However, sometimes using acetonitrile with high ammonium formate concentrations led to lengthy retention times which could be avoided by using methanol as the organic modifier. Additionally, the enantiomeric purities of single enantiomer standards were determined and it was shown that almost all standards contained some levels of enantiomeric impurities.

A Panorama of Extracellular Vesicle Applications: From Biomarker Detection to Therapeutics.

Extracellular vesicles (EVs) secreted by all cell types are involved in the cell-to-cell transfer of regulatory factors that influence cell and tissue phenotypes in normal and diseased tissues. EVs are thus a rich source of biomarker targets for assays that analyze blood and urinary EVs for disease diagnosis. Sensitive biomarker detection in EVs derived from specific cell populations is a key major hurdle when analyzing complex biological samples, but innovative approaches surveyed in this Perspective can streamline EV isolation and enhance the sensitivity of EV detection procedures required for clinical application of EV-based diagnostics and therapeutics, including nanotechnology and microfluidics, to achieve EV characterizations. Finally, this Perspective also outlines opportunities and challenges remaining for clinical translation of EV-based assays.

Urine biomarkers for Alzheimer's disease: A new opportunity for wastewater-based epidemiology?

While Alzheimer's disease (AD) diagnosis, management, and care have become priorities for healthcare providers and researcher's worldwide due to rapid population aging, epidemiologic surveillance efforts are currently limited by costly, invasive diagnostic procedures, particularly in low to middle income countries (LMIC). In recent years, wastewater-based epidemiology (WBE) has emerged as a promising tool for public health assessment through detection and quantification of specific biomarkers in wastewater, but applications for non-infectious diseases such as AD remain limited. This early review seeks to summarize AD-related biomarkers and urine and other peripheral biofluids and discuss their potential integration to WBE platforms to guide the first prospective efforts in the field. Promising results have been reported in clinical settings, indicating the potential of amyloid ß, tau, neural thread protein, long non-coding RNAs, oxidative stress markers and other dysregulated metabolites for AD diagnosis, but questions regarding their concentration and stability in wastewater and the correlation between clinical levels and sewage circulation must be addressed in future studies before comprehensive WBE systems can be developed.

Cerebrospinal fluid protein biomarkers in Parkinson's disease.

Proteomic profiling is an effective way to identify biomarkers for Parkinson's disease (PD). Cerebrospinal fluid (CSF) has direct connectivity with the brain and could be a source of finding biomarkers and their clinical implications. Comparative proteomic profiling has shown that a group of differentially displayed proteins exist. The studies performed using conventional and classical tools also supported the occurrence of these proteins. Many studies have highlighted the potential of CSF proteomic profiling for biomarker identification and their clinical applications. Some of these proteins are useful for disease diagnosis and prediction. Proteomic profiling of CSF also has immense potential to distinguish PD from similar neurodegenerative disorders. A few protein biomarkers help in fundamental knowledge generation and clinical interpretation. However, the specific biomarker of PD is not yet known. The use of proteomic approaches in clinical settings is also rare. A large-scale, multi-centric, multi-population and multi-continental study using multiple proteomic tools is warranted. Such a study can provide valuable, comprehensive and reliable information for a better understanding of PD and the development of specific biomarkers. The current article sheds light on the role of CSF proteomic profiling in identifying biomarkers of PD and their clinical implications. The article also explains the achievements, obstacles and hopes for future directions of this approach.

Changes in glial cell activation and extracellular vesicles production precede the onset of disease symptoms in transgenic hSOD1G93A pigs.

SOD1 gene is associated with progressive motor neuron degeneration in the familiar forms of amyotrophic lateral sclerosis. Although studies on mutant human SOD1 transgenic rodent models have provided important insights into disease pathogenesis, they have not led to the discovery of early biomarkers or effective therapies in human disease. The recent generation of a transgenic swine model expressing the human pathological hSOD1G93A gene, which recapitulates the course of human disease, represents an interesting tool for the identification of early disease mechanisms and diagnostic biomarkers. Here, we analyze the activation state of CNS cells in transgenic pigs during the disease course and investigate whether changes in neuronal and glial cell activation state can be reflected by the amount of extracellular vesicles they release in biological fluids. To assess the activation state of neural cells, we performed a biochemical characterization of neurons and glial cells in the spinal cords of hSOD1G93A pigs during the disease course. Quantification of EVs of CNS cell origin was performed in cerebrospinal fluid and plasma of transgenic pigs at different disease stages by Western blot and peptide microarray analyses. We report an early activation of oligodendrocytes in hSOD1G93A transgenic tissue followed by astrocyte and microglia activation, especially in animals with motor symptoms. At late asymptomatic stage, EV production from astrocytes and microglia is increased in the cerebrospinal fluid, but not in the plasma, of transgenic pigs reflecting donor cell activation in the spinal cord. Estimation of EV production by biochemical analyses is corroborated by direct quantification of neuron- and microglia-derived EVs in the cerebrospinal fluid by a Membrane Sensing Peptide enabled on-chip analysis that provides fast results and low sample consumption. Collectively, our data indicate that alteration in astrocytic EV production precedes the onset of disease symptoms in the hSODG93A swine model, mirroring donor cell activation in the spinal cord, and suggest that EV measurements from the cells first activated in the ALS pig model, i.e. OPCs, may further improve early disease detection.

The impact of tau deposition and hypometabolism on cognitive impairment and longitudinal cognitive decline.

INTRODUCTION: Tau and neurodegeneration strongly correlate with cognitive impairment, as compared to amyloid. However, their contribution in explaining cognition and predicting cognitive decline in memory clinics remains unclarified. METHODS: We included 94 participants with Mini-Mental State Examination (MMSE), tau positron emission tomography (PET), amyloid PET, fluorodeoxyglucose (FDG) PET, and MRI scans from Geneva Memory Center. Linear regression and mediation analyses tested the independent and combined association between biomarkers, cognitive performance, and decline. Linear mixed-effects and Cox proportional hazards models assessed biomarkers' prognostic values. RESULTS: Metabolism had the strongest association with cognition (r = 0.712; p < 0.001), followed by tau (r = -0.682; p < 0.001). Neocortical tau showed the strongest association with cognitive decline (r = -0.677; p < 0.001). Metabolism mediated the association between tau and cognition and marginally mediated the one with decline. Tau positivity represented the strongest risk factor for decline (hazard ratio = 32). DISCUSSION: Tau and neurodegeneration synergistically contribute to global cognitive impairment while tau drives decline. The tau PET superior prognostic value supports its implementation in memory clinics. HIGHLIGHTS: Hypometabolism has the strongest association with concurrent cognitive impairment. Neocortical tau pathology is the main determinant of cognitive decline over time. FDG-PET has a superior value compared to MRI as a measure of neurodegeneration. The prognostic value of tau-PET exceeded all other neuroimaging modalities.

Menopausal vasomotor symptoms and plasma Alzheimer disease biomarkers.

BACKGROUND: Identifying risk factors for Alzheimer disease in women is important as women compose two-thirds of individuals with Alzheimer disease. Previous work links vasomotor symptoms, the cardinal menopausal symptom, with poor memory performance and alterations in brain structure, function, and connectivity. These associations are evident when vasomotor symptoms are monitored objectively with ambulatory skin conductance monitors. OBJECTIVE: This study aimed to determine whether vasomotor symptoms are associated with Alzheimer disease biomarkers. STUDY DESIGN: Between 2017 and 2020, the MsBrain study enrolled 274 community-dwelling women aged 45 to 67 years who had a uterus and at least 1 ovary and were late perimenopausal or postmenopausal status. The key exclusion criteria included neurologic disorder, surgical menopause, and recent use of hormonal or nonhormonal vasomotor symptom treatment. Women underwent 24 hours of ambulatory skin conductance monitoring to assess vasomotor symptoms. Plasma concentrations of Alzheimer disease biomarkers, including amyloid ß 42-to-amyloid ß 40 ratio, phosphorylated tau (181 and 231), glial fibrillary acidic protein, and neurofilament light, were measured using a single-molecule array (Simoa) technology. Associations between vasomotor symptoms and Alzheimer disease biomarkers were assessed via linear regression models adjusted for age, race and ethnicity, education, body mass index, and apolipoprotein E4 status. Additional models adjusted for estradiol and sleep. RESULTS: A total of 248 (mean age, 59.06 years; 81% White; 99% postmenopausal status) of enrolled MsBrain participants contributed data. Objectively assessed vasomotor symptoms occurring during sleep were associated with significantly lower amyloid ß 42/amyloid ß 40, (beta, -.0010 [standard error, .0004]; P=.018; multivariable), suggestive of greater brain amyloid ß pathology. The findings remained significant after additional adjustments for estradiol and sleep. CONCLUSION: Nighttime vasomotor symptoms may be a marker of women at risk of Alzheimer disease. It is yet unknown if these associations are causal.

Montreal Cognitive Assessment in Mild Cognitive Impairment: Relationship with Cerebrospinal Fluid Biomarkers and Conversion to Dementia.

BACKGROUND: Mild cognitive impairment (MCI) is considered a prodromal state of dementia. Abnormal values of cerebrospinal fluid Alzheimer's disease biomarkers (CSF-AD-b) have been associated with a higher risk of conversion to dementia (due to Alzheimer's disease), but studies evaluating the ability of Montreal Cognitive Assessment (MoCA) in this task are lacking. OBJECTIVE: This study aims to investigate the relationship between MoCA and CSF-AD-b, as well as the ability of those tools to predict conversion to dementia. METHODS: Taking advantage of our MCI cohort with biological characterization on longitudinal follow-up (180 patients followed for 62.6 months during which 41.3% converted), we computed MoCA and MMSE z-scores, using Portuguese normative data. The performance in MoCA z-score was correlated with CSF-AD-b and the relative time to conversion and risk according to baseline characteristics were analyzed using Kaplan-Meier analysis and Cox regression models. RESULTS: MoCA z-scores were correlated with Aß42 (p = 0.026), t-tau (p = 0.033), and p-tau (p = 0.01). Impaired MMSE (p < 0.001) and MoCA z-scores (p = 0.019), decreased Aß42 (p < 0.001) and increased t-tau (p < 0.001) and p-tau (p < 0.001) were associated with shorter estimated time of conversion. Aß42 (p < 0.001) and MMSE z-scores (p = 0.029) were independent predictors of conversion. For those with at least 9 years of education, MoCA z-score (p = 0.004) (but not MMSE) was an independent predictor of conversion as well as Aß42. CONCLUSIONS: This study confirms the role of CSF-AD-b, namely Aß42, in predicting conversion from MCI to dementia and suggests the utility of MoCA in predicting conversion in highly educated subjects, supporting its use in the evaluation of MCI patients.

Signal Amplification Strategy Design in Nanozyme-Based Biosensors for Highly Sensitive Detection of Trace Biomarkers.

Nanozymes show great promise in enhancing disease biomarker sensing by leveraging their physicochemical properties and enzymatic activities. These qualities facilitate signal amplification and matrix effects reduction, thus boosting biomarker sensing performance. In this review, recent studies from the last five years, concentrating on disease biomarker detection improvement through nanozyme-based biosensing are examined. This enhancement primarily involves the modulations of the size, morphology, doping, modification, electromagnetic mechanisms, electron conduction efficiency, and surface plasmon resonance effects of nanozymes for increased sensitivity. In addition, a comprehensive description of the synthesis and tuning strategies employed for nanozymes has been provided. This includes a detailed elucidation of their catalytic mechanisms in alignment with the fundamental principles of enhanced sensing technology, accompanied by the presentation of quantitatively analyzed results. Moreover, the diverse applications of nanozymes in strip sensing, colorimetric sensing, electrochemical sensing, and surface-enhanced Raman scattering have been outlined. Additionally, the limitations, challenges, and corresponding recommendations concerning the application of nanozymes in biosensing have been summarized. Furthermore, insights have been offered into the future development and outlook of nanozymes for biosensing. This review aims to serve not only as a reference for enhancing the sensitivity of nanozyme-based biosensors but also as a catalyst for exploring nanozyme properties and their broader applications in biosensing.

Serum matrix metalloproteinase-9 (MMP9) and amyloid-beta protein precursor (APP) as potential biomarkers in children with Fragile-X syndrome: A cross sectional study.

INTRODUCTION: Fragile-X syndrome(FXS) is a neurological disease caused by abnormal repeats in the 5'untranslated region of the FMR1 gene leading to a defective fragile-X-messenger-ribonucleoprotein-1 (FMRP). Although relatively common in children, it is usually under-diagnosed especially in developing countries where genetic screening is not routinely practiced. So far, FXS lacks a laboratory biomarker that can be used for screening, severity scoring or therapeutic monitoring of potential new treatments. METHODS: 110 subjects were recruited; 80 male children with suspected FXS and 30 matched healthy children. We evaluated the clinical utility of serum matrix metalloproteinase-9(MMP9) and amyloid-beta protein precursor(APP) as potential biomarkers for FXS. RESULTS: Out of 80 suspected children, 14 had full mutation, 8 had the premutation and 58 children had normal genotypes. No statistically-significant difference was detected between children with different genotypes concerning age of onset(P = 0.658), main clinical presentation(P = 0.388), clinical severity-score(P = 0.799), patient's disease-course(P = 0.719) and intellectual disability(P = 0.351). Both MMP9 and APP showed a statistically significant difference when comparing different genotype subgroups(P = 0.019 and < 0.001, respectively). Clinically, MMP9 levels were highest in children presenting with language defects, while APP was highest in children with neurodevelopmental delay. In receiver operating curve analysis, comparing full and premutation with the normal genotype group, MMP9 has an area-under-the-curve of 0.701(95 % CI 0.557-0.845), while APP was marginally better at 0.763(95 % CI 0.620-0.906). When combined together, elevated MMP9 or APP had excellent sensitivity > 95 % for picking-up FXS cases in the clinical setting. CONCLUSIONS: Screening for circulating biomarkers in the absence of FXS genetic diagnosis is justified. Our study is the first to evaluate both MMP9 and APP in FXS suspected children in a clinical setting and to assess their correlation with disease presentation and severity.