High-Performance Plasma Biomarker Panel for Alzheimer's Disease Screening Using a Femtomolar-Level Label-Free Biosensing System

Multi-Biomarker Profiling for Precision Diagnosis of Lung Cancer

Multi-biomarker analysis can enhance the accuracy of the single-biomarker analysis by reducing the errors caused by genetic and environmental differences. For this reason, multi-biomarker analysis shows higher accuracy in early and precision diagnosis. However, conventional analysis methods have limitations for multi-biomarker analysis because of their long pre-processing times, inconsistent results, and large sample requirements. To solve these, a fast and accurate precision diagnostic method is introduced for lung cancer by multi-biomarker profiling using a single drop of blood. For this, surface-enhanced Raman spectroscopic immunoassay (SERSIA) is employed for the accurate, quick, and reliable quantification of biomarkers. Then, it is checked the statistical relation of the multi-biomarkers to differentiate between healthy controls and lung cancer patients. This approach has proven effective; with 20 µL of blood serum, lung cancer is diagnosed with 92% accuracy. It also accurately identifies the type and stage of cancer with 87% and 85%, respectively. These results show the importance of multi-biomarker analysis in overcoming the challenges posed by single-biomarker diagnostics. Furthermore, it markedly improves multi-biomarker-based analysis methods, illustrating its important impact on clinical diagnostics.

Diagnosis and therapy of Alzheimer's disease: Light-driven heterogeneous redox processes

Light-driven heterogeneous processes are promising approaches for diagnosing and treating Alzheimer's disease (AD) by regulating its relevant biomolecules. The molecular understanding of the heterogeneous interface environment and its interaction with target biomolecules is important. This review critically appraises the advances in AD early diagnosis and therapy employing heterogeneous light-driven redox processes, encompassing photoelectrochemical (PEC) biosensing, photodynamic therapy, photothermal therapy, PEC therapy, and photoacoustic therapy. The design strategies for heterogeneous interfaces based on target biomolecules and applications are also compiled. Finally, the remaining challenges and future perspectives are discussed. The present review may promote the fundamental understanding of AD diagnosis and therapy and facilitate interdisciplinary studies at the junction of nanotechnology and bioscience.

Gut microbiota metabolites: potential therapeutic targets for Alzheimer's disease?

Background

Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive decline in cognitive function, which significantly increases pain and social burden. However, few therapeutic interventions are effective in preventing or mitigating the progression of AD. An increasing number of recent studies support the hypothesis that the gut microbiome and its metabolites may be associated with upstream regulators of AD pathology.

Methods

In this review, we comprehensively explore the potential mechanisms and currently available interventions targeting the microbiome for the improvement of AD. Our discussion is structured around modern research advancements in AD, the bidirectional communication between the gut and brain, the multi-target regulatory effects of microbial metabolites on AD, and therapeutic strategies aimed at modulating gut microbiota to manage AD.

Results

The gut microbiota plays a crucial role in the pathogenesis of AD through continuous bidirectional communication via the microbiota-gut-brain axis. Among these, microbial metabolites such as lipids, amino acids, bile acids and neurotransmitters, especially sphingolipids and phospholipids, may serve as central components of the gut-brain axis, regulating AD-related pathogenic mechanisms including β-amyloid metabolism, Tau protein phosphorylation, and neuroinflammation. Additionally, interventions such as probiotic administration, fecal microbiota transplantation, and antibiotic use have also provided evidence supporting the association between gut microbiota and AD. At the same time, we propose an innovative strategy for treating AD: a healthy lifestyle combined with targeted probiotics and other potential therapeutic interventions, aiming to restore intestinal ecology and microbiota balance.

Conclusion

Despite previous efforts, the molecular mechanisms by which gut microbes act on AD have yet to be fully described. However, intestinal microorganisms may become an essential target for connecting the gut-brain axis and improving the symptoms of AD. At the same time, it requires joint exploration by multiple centers and multiple disciplines.

Which neuroimaging and fluid biomarkers method is better in theranostic of Alzheimer's disease? An umbrella review

Biomarkers are measured to evaluate physiological and pathological processes as well as responses to a therapeutic intervention. Biomarkers can be classified as diagnostic, prognostic, predictor, clinical, and therapeutic. In Alzheimer's disease (AD), multiple biomarkers have been reported so far. Nevertheless, finding a specific biomarker in AD remains a major challenge. Three databases, including PubMed, Web of Science, and Scopus were selected with the keywords of Alzheimer's disease, neuroimaging, biomarker, and blood. The results were finalized with 49 potential CSF/blood and 35 neuroimaging biomarkers. To distinguish normal from AD patients, amyloid-beta42 (Aβ42), plasma glial fibrillary acidic protein (GFAP), and neurofilament light (NFL) as potential biomarkers in cerebrospinal fluid (CSF) as well as the serum could be detected. Nevertheless, most of the biomarkers fairly change in the CSF during AD, listed as kallikrein 6, virus-like particles (VLP-1), galectin-3 (Gal-3), and synaptotagmin-1 (Syt-1). From the neuroimaging aspect, atrophy is an accepted biomarker for the neuropathologic progression of AD. In addition, Magnetic resonance spectroscopy (MRS), diffusion weighted imaging (DWI), diffusion tensor imaging (DTI), tractography (DTT), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI), can be used to detect AD. Using neuroimaging and CSF/blood biomarkers, in combination with artificial intelligence, it is possible to obtain information on prognosis and follow-up on the different stages of AD. Hence physicians could select the suitable therapy to attenuate disease symptoms and follow up on the efficiency of the prescribed drug.