Alzheimer's disease (AD), the most common neurodegenerative disorder, is pathologically defined by amyloid-β plaques and tau tangles. Current diagnostic tools like CSF analysis and PET imaging are invasive or costly, limiting routine use. This study proposes a novel, label-free approach using Fourier-transform infrared (FTIR) spectroscopy to identify disease-specific biochemical signatures in plasma-derived small extracellular vesicles (sEVs) from 30  AD patients and 20 age-matched controls. sEVs were validated by ultracentrifugation, TEM, nanoparticle tracking (mean size: 98.7 ± 12.4 nm in AD vs. 102.3 ± 14.1 nm in controls), and Western blot for CD9, CD81, and TSG101. FTIR analysis revealed significant alterations in AD sEVs: consistent increase in lipid peroxidation (based on 3015 cm−1, 1745 cm−1 bands), 19.8 % change in β-sheet content, and 22.4 % enhancement in phosphate vibrations (1072 cm−1). Key spectral ratios showed excellent diagnostic accuracy, with the lipid peroxidation index (AUC = 0.998) and protein disorder index (AUC = 0.978). This rapid, cost-effective, and non-invasive method enables simultaneous assessment of lipid, protein, and glycan changes in AD. With broader validation, FTIR-based profiling of plasma sEVs could offer a transformative tool for early AD diagnosis and monitoring.

Small extracellular vesicles (sEVs) can provide information about the pathophysiology of the cells; therefore, sEVs have attracted considerable interest as possible diagnostic biomarkers. A key challenge lies in the necessity for simple and cost-effective sEV isolation methods to achieve high purity and yield suitable for research and clinical applications. We are introducing a comprehensive study on isolating sEVs using a novel cocktail strategy that integrates chemical precipitation and ultrafiltration with a two-step filtering process to ensure a highly pure and homogeneous population and further compared with PEG-based precipitation, ultra-centrifugation, and size-exclusion-chromatography columns. The isolated sEVs from each protocol are quantified for size and yield using nanoparticle tracking analysis, morphologically characterized through transmission electron microscopy, and validated by quantifying the expression profiles of sEV surface biomarkers. Furthermore, the study explores the applicability of our method for downstream multi-omics analyses. The results highlight the efficacy of the proposed protocol, demonstrating the ease and efficiency of isolating sEVs from different biofluids with minimal laboratory requirements and confirming the compatibility with multi-omics analyses. These findings position our method as particularly valuable for translational research, offering a promising avenue for advancing the study and application of sEVs in diagnostic and therapeutic research.

Gastrointestinal neuroendocrine tumors (GI NETs) remain diagnostically challenging due to limitations of current methods. This study pioneers the application of Fourier-transform infrared (FTIR) spectroscopy for GI NET detection through plasma lipid profiling. Analyzing 22 patients and 8 controls, we identified specific biomarker ratios (I3015/I2929 and I3015/I1650) reflecting tumor-associated oxidative stress and membrane alterations. Multivariate analysis revealed excellent diagnostic accuracy (94–96.1% sensitivity, 100% specificity) superior to conventional biomarkers, with PCA showing clear group separation (96.5% variance). The FTIR approach demonstrated significant advantages: rapid analysis (< 5 min), minimal sample requirements (4 μL), and low cost, addressing critical clinical needs. Spectral changes correlated with known lipid metabolism dysregulation in NETs, particularly increased unsaturated fatty acids (3015 cm−1) and altered acyl chain packing (2929 cm−1). These findings establish FTIR as a practical, label-free alternative to invasive diagnostics, with potential for both early detection and treatment monitoring. The identified lipid signatures not only provide robust diagnostic markers but also suggest new therapeutic targets for NET management. This cost-effective technology could transform clinical practice by enabling routine screening and personalized treatment strategies. Future studies should validate these results in larger cohorts and explore correlations with tumor grade and treatment response.

Background: Alzheimer’s disease (AD) is a neurodegenerative disease characterized by Aβ plaques and neurofibrillary tangles. Chronic inflammation and synaptic dysfunction lead to disease progression and cognitive decline. Small extracellular vesicles (sEVs) are implicated in AD progression by facilitating the spread of pathological proteins and inflammatory cytokines. This study investigates synaptic dysfunction and neuroinflammation protein markers in plasma-derived sEVs (PsEVs), their association with Amyloid-β and tau pathologies, and their correlation with AD progression.

Methods: A total of 90 [AD = 35, mild cognitive impairment (MCI) = 25, and healthy age-matched controls (AMC) = 30] participants were recruited. PsEVs were isolated using a chemical precipitation method, and their morphology was characterized by transmission electron microscopy. Using nanoparticle tracking analysis, the size and concentration of PsEVs were determined. Antibody-based validation of PsEVs was done using CD63, CD81, TSG101, and L1CAM antibodies. Synaptic dysfunction and neuroinflammation were evaluated with synaptophysin, TNF-α, IL-1β, and GFAP antibodies. AD-specific markers, amyloid-β (1–42), and p-Tau were examined within PsEVs using Western blot and ELISA.

Results: Our findings reveal higher concentrations of PsEVs in AD and MCI compared to AMC (p < 0.0001). Amyloid-β (1–42) expression within PsEVs is significantly elevated in MCI and AD compared to AMC. We could also differentiate between the amyloid-β (1–42) expression in AD and MCI. Similarly, PsEVs-derived p-Tau exhibited elevated expression in MCI compared with AMC, which is further increased in AD. Synaptophysin exhibited downregulated expression in PsEVs from MCI to AD (p = 0.047) compared to AMC, whereas IL-1β, TNF-α, and GFAP showed increased expression in MCI and AD compared to AMC. The correlation between the neuropsychological tests and PsEVs-derived proteins (which included markers for synaptic integrity, neuroinflammation, and disease pathology) was also performed in our study. The increased number of PsEVs correlates with disease pathological markers, synaptic dysfunction, and neuroinflammation.

Conclusions: Elevated PsEVs, upregulated amyloid-β (1–42), and p-Tau expression show high diagnostic accuracy in AD. The downregulated synaptophysin expression and upregulated neuroinflammatory markers in AD and MCI patients suggest potential synaptic degeneration and neuroinflammation. These findings support the potential of PsEV-associated biomarkers for AD diagnosis and highlight synaptic dysfunction and neuroinflammation in disease progression.

The survival rate over a five-year period for rare pancreatic neuroendocrine tumors (PanNET) is notably lower compared to other neuroendocrine tumors due to late-stage detection, which is a consequence of the absence of suitable diagnostic markers; therefore, there exists a critical need for an early-stage biomarker-specific to PanNETs. This study introduces a novel approach, investigating the impact of small extracellular vesicles (sEV) in PanNET growth and metastasis. As proof of concept, this study shows a correlation between sEV concentration in controls and PanNET. Notably, higher sEV concentrations were observed in PanNETs than in controls (p < 0.0001) with a sensitivity of 100%. Further, apparent differences were observed in the sEV concentrations between controls and grades 1 PanNET (p = 0.005). The expression of sEV markers was confirmed using CD63, TSG101, CD9, Flotillin-1, and GAD65 antibodies. Additionally, the expression of cancer marker BIRC2/cIAP1 (p = 0.002) and autophagy marker Beclin-1 (p = 0.02) were observed in plasma-derived sEVs and PanNET tissue. This study represents the first to indicate the increased secretion of sEV in PanNET patients&apos; blood plasma, proposing potential function of sEV as a new biomarker for early-stage PanNET detection.

Breast cancer, a leading cause of female mortality due to delayed detection owing to asymptomatic nature and limited early diagnostic tools, was investigated using a multi-modal approach. Plasma-derived small EVs from breast cancer patients (BrCa, n = 74) and healthy controls (HC, n = 30) were analyzed. Small EVs (n = 104), isolated through chemical precipitation, underwent characterization via transmission electron microscopy (TEM) and nanoparticle tracking analysis (NTA). Validation involved antibody-based tests (TSG101, CD9, CD81, CD63). Infrared spectra of small EVs were obtained, revealing significant differences in lipid acyl chains, particularly in the C–H stretching of CH3. The study focused on the lipid region (3050–2900 cm−1), identifying peaks (3015 cm−1, 2960 cm−1, 2929 cm−1) as distinctive lipid characteristics. Spectroscopic lipid-to-lipid ratios [(I3015/I2929), (I2960/I2929)] emerged as prominent breast cancer markers. Exploration of protein, nucleic acid, and carbohydrate ratios indicated variations in alpha helices, asymmetric C–H stretching vibrations, and C–O stretching at 1033 cm−1. Principal component analysis (PCA) successfully differentiated BrCa and HC small EVs, and heatmap analysis and receiver operating characteristic (ROC) curve evaluations underscored the discriminatory power of lipid ratios. Notably, (I2960/I2929) exhibited 100% sensitivity and specificity, highlighting its potential as a robust BrCa sEV marker for breast cancer detection.

Cancer is a cause of high deaths worldwide and also a huge burden for the health system. Cancer cells have unique properties such as a high rate of proliferation, self-renewal, metastasis, and treatment resistance, therefore, the development of novel diagnoses of cancers is a tedious task. Exosomes are secreted by virtually all cell types and have the ability to carry a multitude of biomolecules crucial for intercellular communication, hence, contributing a crucial part in the onset and spread of cancer. These exosomal components can be utilized in the development of markers for diagnostic and prognostic purposes for various cancers. This review emphasized primarily the following topics: exosomes structure and functions, isolation and characterization strategies of exosomes, the role of exosomal contents in cancer with a focus in particular on noncoding RNA and protein, exosomes, and the cancer microenvironment interactions, cancer stem cells, and tumor diagnosis and prognosis based on exosomes.

Pancreatic Neuroendocrine tumors (PanNET) are challenging to diagnose and often detected at advanced stages due to a lack of specific and sensitive biomarkers. This study utilized proteomics as a valuable approach for cancer biomarker discovery; therefore, mass spectrometry-based proteomic profiling was conducted on plasma samples from 12 subjects (3 controls; 5 Grade I, 4 Grade II PanNET patients) to identify potential proteins capable of effectively distinguishing PanNET from healthy controls. Data are available via ProteomeXchange with the identifier PXD045045. 13.2% of proteins were uniquely identified in PanNET, while 60% were commonly expressed in PanNET and controls. 17 proteins exhibiting significant differential expression between PanNET and controls were identified with downstream analysis. Further, 5 proteins (C1QA, COMP, HSP90B1, ITGA2B, and FN1) were selected by pathway analysis and were validated using Western blot analysis. Significant downregulation of C1QA (p = 0.001: within groups, 0.03: control vs. grade I, 0.0013: grade I vs. grade II) and COMP (p = 0.011: within groups, 0.019: control vs grade I) were observed in PanNET Grade I & II than in controls. Subsequently, ELISA on 38 samples revealed significant downregulation of C1QA and COMP with increasing disease severity. This study shows the potential of C1QA and COMP in the early detection of PanNET, highlighting their role in the search for early-stage (Grade-I and Grade-II) diagnostic markers and therapeutic targets for PanNET.

Background: Parkinson's disease (PD) is an increasingly common neurodegenerative condition, which causes movement dysfunction and a broad range of non-motor symptoms. There is no molecular or biochemical diagnosis test for PD. The miRNAs are a class of small non-coding RNAs and are extensively studied owing to their altered expression in pathological states and facile harvesting and analysis techniques.

Methods: A total of 48 samples (16 each of PD, aged-matched, and young controls) were recruited. The small extracellular vesicles (sEVs) were isolated and validated using Western blot, transmission electron microscope, and nanoparticle tracking analysis. Small RNA isolation, library preparation, and small RNA sequencing followed by differential expression and targeted prediction of miRNA were performed. The real-time PCR was performed with the targeted miRNA on PD, age-matched, and young healthy control of plasma and plasma-derived sEVs to demonstrate their potential as a diagnostic biomarker.

Results: In RNA sequencing, we identified 14.89% upregulated (fold change 1.11 to 11.04, p < 0.05) and 16.54% downregulated (fold change −1.04 to −7.28, p < 0.05) miRNAs in PD and controls. Four differentially expressed miRNAs (miR-23b-3p, miR-29a-3p, miR-19b-3p, and miR-150-3p) were selected. The expression of miR-23b-3p was “upregulated” (p = 0.002) in plasma, whereas “downregulated” (p = 0.0284) in plasma-derived sEVs in PD than age-matched controls. The ROC analysis of miR-23b-3p revealed better AUC values in plasma (AUC = 0.8086, p = 0.0029) and plasma-derived sEVs (AUC = 0.7278, p = 0.0483) of PD and age-matched controls.

Conclusion: We observed an opposite expression profile of miR-23b-3p in PD and age-matched healthy control in plasma and plasma-derived sEV fractions, where the expression of miR-23b-3p is increased in PD plasma while decreased in plasma-derived sEV fractions. We further observed the different miR-23b-3p expression profiles in young and age-matched healthy control.