Diagnostic Potential Research Articles

Liquid biomarkers in prostate cancer: recent advancements and future directions.

Traditional diagnostic approaches of prostate cancer like PSA are limited by high false-positive rates and insufficient capture of tumour heterogeneity, necessitating the development of more precise tools. This review examines the latest advancements in liquid biomarkers for prostate cancer, focusing on their potential to refine diagnostic accuracy and monitor disease progression. Liquid biomarkers have gained prominence because of their minimally invasive nature and ability to reflect the molecular characteristics of prostate cancer. Circulating tumour cells provide insight into tumour cell dissemination and are indicative of aggressive disease phenotypes, with single-cell analyses revealing genomic instability and treatment resistance. Circulating tumour DNA offers real-time tumour genomic information, aiding in treatment decision-making in advanced prostate cancer, where it has been associated with clinical progression. MicroRNAs act as oncogenes or tumour suppressors and exhibit diagnostic and prognostic potential; however, their clinical utility is constrained by the lack of consistent validation. Extracellular vesicles contain tumour-derived biomolecules, with specific proteins demonstrating prognostic relevance. Applications of these markers to urinary testing have been demonstrated. Liquid biomarkers show potential in refining prostate cancer management. Future research should aim to integrate these biomarkers into a cohesive framework in line with precision medicine principles.

Quantum sensing of microRNAs with nitrogen-vacancy centers in diamond

Label-free detection of nucleic acids such as microRNAs holds great potential for early diagnostics of various types of cancers. Measuring intrinsic biomolecular charge using methods based on field effect has been a promising way to accomplish label-free detection. However, the charges of biomolecules are screened by counter ions in solutions over a short distance (Debye length), thereby limiting the sensitivity of these methods. Here, we measure the intrinsic magnetic noise of paramagnetic counter ions, such as Mn2+, interacting with microRNAs using nitrogen-vacancy (NV) centers in diamond. All-atom molecular dynamics simulations show that microRNA interacts with the diamond surface resulting in excess accumulation of Mn ions and stronger magnetic noise. We confirm this prediction by observing an increase in spin relaxation contrast of the NV centers, indicating higher Mn2+ local concentration. This opens new possibilities for next-generation quantum sensing of charged biomolecules, overcoming limitations due to the Debye screening.

Diagnostic Accuracy of Conjunctival Rt-Pcr in Sars-Cov-2: A Systematic Review and Diagnostic Accuracy Meta-Analysis

ABSTRACT Purpose To study the positivity rate of conjunctival realtime polymerase chain reaction (RT-PCR) testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Design Systematic review and diagnostic accuracy meta-analysis. Methods MEDLINE and EMBASE were queried using medical subject headings terms. Diagnostic accuracy meta-analyses and forest plots were obtained using the RevMan software. Results After deduplication, appraisal of abstract titles and full-text analysis of 1441 articles, 42 articles with 3351 COVID-19 patients were included in this review. Of these, 412 conjunctival swabs/Schirmer paper strips tested positive for SARS-CoV-2 by RT-PCR. The pooled sensitivity of the RT-PCR tests across the 24 studies with laboratory-confirmed COVID-19 patients was 10.3%. Conclusions Only 1 in 10 RT-PCR tests performed on conjunctival swabs were positive for SARS-CoV-2. Although this suggests that SARS-CoV-2 is likely present and detectable in the conjunctiva, this detection method has low diagnostic potential.

Diagnostic Ultrasound in the Evaluation of Stiff Shoulder: Association of Axillary Recess Thickness with Standard Clinical Measures.

Stiff shoulder, including primary and secondary types, poses diagnostic challenges due to vague definitions and criteria. This study evaluates the diagnostic potential of ultrasound-measured axillary recess (AR) thickness in shoulder stiffness. In this cross-sectional study, 35 patients with unilateral shoulder stiffness were assessed. AR thickness was measured using high-resolution ultrasound. Parameters like passive range of motion (PROM), Numerical Rating Scale (NRS), and Constant-Murley (CM) score were evaluated to find correlations with AR thickness. The average age was 50.7 years, and mean BMI was 22.7. AR thickness in stiff shoulders (average 3.19 mm) was significantly higher than in unaffected shoulders (average 1.93 mm, p < 0.001). A cutoff of 3.0 mm for AR thickness yielded 73.3% sensitivity and 84.6% specificity for primary stiffness; 2.6 mm cutoff resulted in 57.9% sensitivity and 88.2% specificity for secondary stiffness. Significant correlations were found between AR thickness and PROM, especially in shoulder external rotation and extension. AR thickness measured by ultrasound might serve as a valuable diagnostic and evaluation parameter in shoulder stiffness.

Exosome-transported circ_0061407 and circ_0008103 play a tumour-repressive role and show diagnostic value in non-small-cell lung cancer

BackgroundCircular RNAs (circRNAs), one of the major contents of exosomes, have been shown to participate in the occurrence and progression of cancers. The role and the diagnostic potential of exosome-transported circRNAs in non-small-cell lung cancer (NSCLC) remain largely unknown.MethodsThe NSCLC-associated exosomal circ_0061407 and circ_0008103 were screened by circRNA microarray. The role of circ_0061407 and circ_0008103 in NSCLC was examined in vitro and in vivo. The encapsulation of the two circRNAs into exosomes and the transport to recipient cells were observed by confocal microscopy. The effects of exosome-transported circ_0061407 and circ_0008103 on recipient cells were investigated using a co-culture device. Bioinformatics analyses were performed to predict the mechanisms by which circ_0061407 and circ_0008103 affected NSCLC. The quantitative polymerase chain reaction was used to quantify the exosome-containing circ_0061407 and circ_0008103 in the serum samples of healthy, pneumonia, benign lung tumours, and NSCLC. The diagnostic efficacy was evaluated using receiver operating characteristic curves.ResultsThe levels of circ_0061407 and circ_0008103 within exosomes were down-regulated in the serum of patients with NSCLC. The up-regulation of circ_0061407 and circ_0008103 inhibited the proliferation, migration/invasion, cloning formation of NSCLC cells in vitro and inhibited lung tumour growth in vivo. Circ_0061407 and circ_0008103 were observed to be packaged in exosomes and transported to recipient cells, where they inhibited the proliferation, migration/invasion, and cloning formation abilities of the recipient cells. Moreover, circ_0061407 and circ_0008103 might be involved in the progression of NSCLC by interacting with microRNAs and proteins. Additionally, lower serum exosomal circ_0061407 and circ_0008103 levels were associated with advanced pathological staging and distant metastasis.ConclusionsThis study identified two novel exosome-transported circRNAs (circ_0061407 and circ_0008103) associated with NSCLC. These findings may provide additional insights into the development of NSCLC and potential diagnostic biomarkers for NSCLC.

Multidimensional biomarker approach integrating tumor markers, inflammatory indicators, and disease activity indicators may improve prediction of rheumatoid arthritis-associated interstitial lung disease.

Rheumatoid arthritis (RA) often leads to interstitial lung disease (ILD), significantly affecting patient outcomes. This study explored the diagnostic accuracy of a multi-biomarker approach to offer a more efficient and accessible diagnostic strategy for RA-associated ILD (RA-ILD). Patients diagnosed with RA, with or without ILD, at Beijing Tiantan Hospital from October 2019 to October 2023 were analyzed. A total of 125 RA patients were included, with 76 diagnosed with RA-ILD. The study focused on three categories of indicators: tumor markers, inflammatory indicators, and disease activity measures. The heatmap correlation analysis was employed to analyze the correlation among these indicators. Logistic regression was used to determine odds ratios (OR) for indicators linked to RA-ILD risk. Receiver-operating characteristic (ROC) curve analysis was employed to evaluate the diagnostic potential of these indicators for RA-ILD. The results of logistic regression analysis showed that tumor markers (carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 125 (CA125), and cytokeratin 19 fragment (CYFRA21-1)), as well as inflammatory indicators (neutrophil, neutrophil-to-lymphocyte ratio (NLR), platelet, C-reactive protein (CRP)) and disease activity measures (disease activity score-28-CRP (DAS28-CRP), rheumatoid factor (RF), and anti-cyclic peptide containing citrulline (anti-CCP)), were significantly associated with RA-ILD. The correlation coefficients among these indicators were relatively low. Notably, the combination indicator 4, which integrated the aforementioned three categories of biomarkers, demonstrated improved diagnostic accuracy with an AUC of 0.857. The study demonstrated that combining tumor markers, inflammatory indicators, and disease activity measures significantly enhanced the prediction of RA-ILD. Key Points • Multidimensional strategy: Integrated tumor markers, inflammatory indicators, and disease activity measures to enhance early detection of rheumatoid arthritis-associated interstitial lung disease (RA-ILD). • Diagnostic accuracy: Employed heatmap correlation and logistic regression, identifying significant associations and improving diagnostic accuracy with a multidimensional biomarker combination. • Superior performance: The combined multidimensional biomarker strategy demonstrated higher diagnostic precision compared to individual or dual-category indicators. • Clinical relevance: Offers a promising, accessible approach for early detection of RA-ILD in clinical settings, potentially improving patient outcomes.

Diagnostic accuracy of high resolution computed tomography (HRCT) of chest in diagnosing sputum smear positive and sputum smear negative pulmonary tuberculosis (PTB).

Objective: To assess the diagnostic accuracy of high resolution computed tomography (HRCT) of chest in diagnosing sputum smear positive and negative pulmonary tuberculosis (PTB). Study Design: Cross-sectional study. Setting: Tertiary Care Hospital, Kharian Cantt. Period: Oct 2021 to April 2022. Methods: The retrospective reviews of medical records of patients undergone HRCT chest and sputum for AFB smear and culture due to pulmonary tuberculosis (PTB) suspicion were included. The HRCT and AFB findings for sample size of 220 was compared. SPSS was used to stratify outcomes on basis of sputum smear results. Diagnostic accuracy of HRCT chest was calculated by taking AFB as gold standard. The AFB findings and HRCT outcomes were compared through correlation analysis and paired t-test with p value &lt; 0.05 considered as significant. Results: The sensitivity was found to be 86.23% with specificity of 86.48%, positive predictive value of 86.23%, negative predictive value of 86.48% and diagnostic accuracy of 86.36% for HRCT for diagnosing pulmonary tuberculosis (PTB). Conclusion: HRCT chest affirms high diagnostic potential for pulmonary tuberculosis (PTB) and should be used as a routine diagnostic tool for the disease.

Whole-body magnetic resonance neurography in patients with chronic inflammatory demyelinating polyneuropathy.

Whole-body magnetic resonance neurography (MRN) is an imaging modality that shows peripheral nerve signal change in patients with chronic inflammatory demyelinating polyneuropathy (CIDP). We aimed to explore the diagnostic potential of whole-body MRN and its potential as a monitoring tool after immunotherapy in treatment-naïve CIDP patients. Whole-body MRN using coronal 3-dimensional short tau inversion recovery (STIR) sampling perfection with application-optimized contrasts by using different flip angle evolution (SPACE) techniques was performed in patients being investigated for CIDP and in healthy controls. Baseline clinical neuropathy scales and electrophysiologic parameters were collected, and MRN findings were compared before and after CIDP treatment. We found highly concordant symmetrical thickening and increased T2 signal intensities in the brachial/lumbosacral plexus, femoral, or sciatic nerves in five of the eight patients with a final diagnosis of CIDP and none of the healthy controls. There were no treatment-related imaging changes in five patients with CIDP who completed a follow-up study. Diffuse, symmetrical thickening, and increased T2 signal in root, plexus, and peripheral nerves were found in two patients ultimately excluded due to a diagnosis of polyneuropathy, organomegaly, endocrinopathy, monoclonal gammopathy, skin changes (POEMS) syndrome in addition to signal changes in the muscles, bony lesions, organomegaly, and lymphadenopathy. Whole-body MRN imaging shows promise in detecting abnormalities in proximal nerve segments in patients with CIDP. Future studies evaluating the role of MRN in assessing treatment response should consider follow-up scans after treatment durations of more than 4 months.

Abstract PO3-07-01: Multiscale Computational Analysis of Patient-Matched Multi-Modal Imaging of Breast Tissue Microenvironment

Abstract Introduction: Mammographic breast density is a strong quantitative cancer risk factor, but its link to underlying tissue and cellular level changes are weakly understood. Understanding the complex restructuring changes in the breast tumor microenvironment and its impact on breast density is integral to improving risk assessment and treatment strategies. A novel approach was developed to stratify mammographic dense breast tissue into areas of active dense tissue and passive dense tissue. Active dense tissue is structurally reorganizing and links to cancer dynamics, whereas passive dense mammographic tissue remains organized.1,2 A complementary wavelet-based analysis technique to measure the multiscale anisotropy of collagen fibers from Second-Harmonic Generation (SHG) imaging demonstrated clinical cancer diagnostic potential in mouse carcinoma and human pancreatic cancer.3,4 This tool is now leveraged for a multi-modal study in which patient-matched H&amp;E tissue biopsies are imaged using both bright-field microscopy and SHG imaging to compare with the patient’s corresponding mammograms. Stratifying the mammographic density into active and passive dense areas, a correlation between biopsy tissue anisotropy and mammographic density subtypes can be calculated to help understand how tumor microenvironment changes affect a patient’s mammographic breast tissue composition. Methods: SHG and brightfield-imaged biopsy slides from 10 patients (five malignant, five benign) collected from Maine Medical Center (Maine, US) were analyzed using the 2D Wavelet Transform Modulus Maxima (WTMM) Anisotropy Method generating a large-scale and a small-scale anisotropy factor as well as a scale-combined anisotropy calculated from their large- and small-scale anisotropy separation. A multi-modal anisotropy score was calculated by adding the imaged area’s H&amp;E combined anisotropy score with its respective SHG combined anisotropy score. This analysis was done on eight randomly selected ductal areas for each imaging modality on a slide and correlated with the measured areas of density subtypes from the whole mammographic view. Linear regression was used for determining correlation between H&amp;E and SHG anisotropy factors as well as with active and passive mammographic density subtype measurements. Results: The malignant patients’ small-scale H&amp;E anisotropy factor positively correlated with their small scale SHG anisotropy factor (R2=0.571). No correlation was found for the benign patients (R2=0.011). The strongest correlations were found between benign patients’ mammographic passive (positive correlation) and active (negative correlation) dense tissues vs the H&amp;E anisotropy scale-combined factor (R2=0.858 and R2=0.961, respectively). The largest malignant patient correlation was a negative relationship between SHG anisotropy scale-combined factor and overall mammographic density (inclusive of both active and passive dense tissue) (R2=0.891). The multi-modal anisotropy score correlated with overall mammographic density for both benign (positive correlation, R2=0.698) and malignant patients (negative correlation, R2=0.773). Combining the multi-modal anisotropy factor from SHG and H&amp;E with the active dense tissue measurement using K-Means clustering, 5/5 malignant and 4/5 benign patients were correctly classified. Conclusion: Density in mammograms correlates with underlying quantitative changes in a patient’s tissue and collagen anisotropy. Combining both H&amp;E and SHG analysis on tissue biopsy with active and passive density metrics from computational mammography leads to the best predictive potential than any one method on their own.

SIT1 identifies circulating hypoactive T cells with elevated cytotoxic molecule secretion in systemic lupus erythematosus patients.

This study aims to elucidate the expression and functionality of SIT1 in circulating CD8/CD4 + T cells in humans and to delineate its significance in systemic lupus erythematosus (SLE) patients. We employed multiparametric flow cytometry to investigate the expression of SIT1 in circulating CD8/CD4 + T cells and their respective subsets, comparing healthy controls (HCs) with SLE patients. Furthermore, we assessed the levels of granzyme B, perforin, IL-17, and IFN-γ in SIT1-related CD8/CD4 + T cells from both HCs and SLE patients, both before and after PMA stimulation. Clinically, we conducted receiver operating characteristic curve analysis and correlation analysis to evaluate the clinical relevance of SIT1-related CD8/CD4 + T cells in SLE patients. SIT1 exhibited higher expression in CD4 + T cells, with SIT1 - T cells demonstrating elevated levels of granzyme B, perforin, and IFN-γ compared to SIT1 + T cells. PMA-stimulated T cells exhibited reduced SIT1 expression compared to unstimulated T cells. SLE patients displayed increased SIT1 + proportions in CD8 + T cells and decreased SIT1 + CD4 + T cell numbers. Additionally, SIT1 + cells in SLE patients exhibited significantly higher levels of granzyme B and perforin compared to HCs. SIT1 + cells demonstrated significant associations with clinical indicators in SLE patients, with indicators related to SIT1 proving valuable in the diagnosis of SLE patients. SIT1 is inversely correlated with T cell activation. In SLE patients, SIT1 expression is altered in T cells concomitant with an augmented secretion of cytotoxic molecules. This upregulation may contribute to the pathogenesis of SLE and enhance its diagnostic potential.

WGCNA and Machine Learning Analysis Identified SAMD9 and IFIT3 as Primary Sjögren’s Syndrome Key Genes

Current treatments for primary Sjögren's Syndrome (pSS) are with limited effect, partially due to the heterogeneity and uncleared mechanism. We got GSE40568 (Japan) and GSE40611 (USA), and analyzed them with WGCNA to find key Differentially expressed genes (DEGs) between pSS and healthy salivary glands (SG). Key pSS genes (KPGs) were further selected through 3 machine-learning methods. The expression of KPGs was validated via two other GEO datasets (GSE127952 and GSE154926). Infiltrated immune cells, ceRNA network, and potential compounds were explored. Our study identified 376 DEGs from the pSS patients, with 186 genes located in the "plum2" module, showing the strongest correlation with clinical characteristics. SAMD9 and IFIT3 emerged as KPGs with excellent diagnostic potential. SAMD9 demonstrated close association with immune cell infiltration. We constructed a lncRNA-miRNA-mRNA network comprising 2 KPGs, 12 miRNAs, 124 lncRNAs, and potential therapeutic targets. In the investigation of pSS public datasets, our study revealed two potential critical mediators in the pathological process of pSS salivary glands, namely SAMD9 and IFIT3. Furthermore, we put forth a hypothesis regarding the ceRNA network and made predictions regarding potential therapeutic drugs targeting these two genes.

Combined Serum CTRP7 and CTRP15 Levels as a Novel Biomarker for Insulin Resistance and Type 2 Diabetes Mellitus

AimsThis study aimed to examine the alterations in the serum CTRP7 and CTRP15 concentrations in patients newly diagnosed with type 2 diabetes mellitus (T2DM) and to assess the diagnostic potential of the log10 (CTRP7+CTRP15) for insulin resistance (IR) and T2DM. MethodsSerum CTRP7, CTRP15, and adiponectin levels were measured using an enzyme-linked immunosorbent assay (ELISA). Bioinformatics analysis was conducted to investigate CTRP7 and CTRP15-related genes and metabolic signaling pathways. ResultsLog10 (CTRP7+CTRP15) levels were notably elevated in the impaired glucose tolerance (IGT) and T2DM cohorts compared with those in the normal control (NGT) cohort. Log10(CTRP7+CTRP15) exhibited positive correlations with HOMA-IR, area under the glucose curve (AUCg), HbA1c%, triglyceride (TG), visceral adiposity index (VAI), body mass index (BMI), and free fatty acid (FFA), levels but negative correlations with adiponectin. Multivariate stepwise regression analysis revealed that HOMA-IR, BMI, HbA1c and FFA levels were independent factors affecting the log10 (CTRP7+CTRP15). Logistic regression analysis revealed that log10 (CTRP7+CTRP15) was independently associated with T2DM and significantly associated with increased risk. Receiver operating characteristic (ROC) curve analysis indicated that the predictive value of log10 (CTRP7+CTRP15) for T2DM and IR was superior to that of CTRP7 or CTRP15 alone. Intervention studies demonstrated that insulin, FFAs and acute exercise contribute to the elevation of serum CTRP7 levels, while hyperglycemia inhibited CTRP7 secretion. Short-term changes in blood glucose, insulin, FFA and acute exercise had minimal effects on serum CTRP15 levels. Bioinformatics analysis revealed that CTRP7 and CTRP15 interact with multiple metabolism-related genes and are enriched in glucose and lipid metabolism-related pathways. ConclusionLog10 (CTRP7+CTRP15) may serve as a valuable diagnostic marker for the management of metabolic-related diseases, particularly T2DM and IR.

Gut microbiome composition and metabolic activity in women with diverticulitis

The etiopathogenesis of diverticulitis, among the most common gastrointestinal diagnoses, remains largely unknown. By leveraging stool collected within a large prospective cohort, we performed shotgun metagenomic sequencing and untargeted metabolomics profiling among 121 women diagnosed with diverticulitis requiring antibiotics or hospitalizations (cases), matched to 121 women without diverticulitis (controls) according to age and race. Overall microbial community structure and metabolomic profiles differed in diverticulitis cases compared to controls, including enrichment of pro-inflammatory Ruminococcus gnavus, 1,7-dimethyluric acid, and histidine-related metabolites, and depletion of butyrate-producing bacteria and anti-inflammatory ceramides. Through integrated multi-omic analysis, we detected covarying microbial and metabolic features, such as Bilophila wadsworthia and bile acids, specific to diverticulitis. Additionally, we observed that microbial composition modulated the protective association between a prudent fiber-rich diet and diverticulitis. Our findings offer insights into the perturbations in inflammation-related microbial and metabolic signatures associated with diverticulitis, supporting the potential of microbial-based diagnostics and therapeutic targets.

CNS Germ Cell Tumors: Molecular Advances, Significance in Risk Stratification and Future Directions

Central Nervous System Germ Cell Tumors (CNS GCTs) represent a subtype of intracranial malignant tumors characterized by highly heterogeneous histology. Current diagnostic methods in clinical practice have notable limitations, and treatment strategies struggle to achieve personalized therapy based on patient risk stratification. Advances in molecular genetics, biology, epigenetics, and understanding of the tumor microenvironment suggest the diagnostic potential of associated molecular alterations, aiding risk subgroup identification at diagnosis. Furthermore, they suggest the existence of novel therapeutic approaches targeting chromosomal alterations, mutated genes and altered signaling pathways, methylation changes, microRNAs, and immune checkpoints. Moving forward, further research is imperative to explore the pathogenesis of CNS GCTs and unravel the intricate interactions among various molecular alterations. Additionally, these findings require validation in clinical cohorts to assess their role in the diagnosis, risk stratification, and treatment of patients.

Cellulose Nanofibrils of High Immunoaffinity for Efficient Enrichment of Small Extracellular Vesicles.

Extracellular vesicles (EVs), crucial in facilitating the transport of diverse molecular cargoes for intercellular communication, have shown great potential in diagnostics, therapeutics, and drug delivery. The challenge of developing effective preparation methods for EVs is heightened by their intrinsic heterogeneity and complexity. Here, a novel strategy for high EV enrichment is developed by utilizing EV-affinitive-modified cellulose nanofibrils. Specifically, modified cellulose with rich carboxyl groups has outstanding dispersing properties, able to be dispersed into cellulose nanofibrils in solution. These cellulose nanofibrils are utilized as scaffolds for the immobilization of EV-affinitive antibody of CD63 by chemical conjugation. The CD63-modified nanofibrils demonstrate a superior EV capture efficiency of 86.4% compared with other reported methods. The high performance of this system is further validated by the efficient capture of EVs from biological blood plasma, allowing the detection of bioactive markers from EV-derived miRNAs and proteins. The authors envision that these modified cellulose nanofibrils of enhanced capability on EV enrichment will open new avenues in various biomedical applications.

Optimization of protocols for blood-derived extracellular vesicles for studies in liver diseases

Aim: Extracellular vesicles (EVs) have gained significant attention for their diagnostic and therapeutic potential in various diseases, including liver disorders. This study focuses on optimizing the isolation and characterization of small EVs from plasma and serum samples in patients with liver diseases, aiming to advance our understanding and potential clinical applications of EVs. Methods: Blood samples were collected from patients with end-stage liver disease (ESLD) enlisted in the TransplantLines Cohort and Biobank Study, and healthy donors. We employed differential ultracentrifugation (DUC) to evaluate three distinct protocols: a 3-step DUC, a washing step omitted [samples without washing (WW)], and a contaminant-depleted plasma (CDP) protocol. RNA isolation methodologies were compared, involving the use of TRI-reagent or the commercial AllPrep DNA/RNA kit. Further insights into EV composition were obtained through proteomic analyses, comparing samples subjected to traditional cell lysis (L) with those processed without lysis (NL). Results: We successfully isolated EVs from both plasma and serum samples as confirmed by the presence of specific EV markers, including CD9, CD63, CD81, and tumor susceptibility gene 101 (TSG-101). While some contaminants remained, such as albumin and lipoproteins, the protocol selected to continue EVs analysis was the 3-step protocol. Transmission electron microscopy (TEM) and nanotracking analysis (NTA) further confirmed EVs presence. RNA extraction was achieved using TRI-reagent, but not with the commercial kit highlighting the importance of selecting an appropriate method for RNA isolation. Finally, proteomics analysis showed that lysed samples were significantly more enriched in proteins compared to non-lysed samples, although protein variability was still present in both groups. Conclusions: Optimizing EV isolation techniques is essential for harnessing their potential in liver disease diagnosis and therapy. Further refinement of purification methods, a deep characterization of our cohort and understanding the variability and cargo within EVs will be crucial for future biomarker discovery and therapeutic applications in liver-related diseases.

Evaluating the Diagnostic Potential of Combined Salivary and Skin Biomarkers in Parkinson’s Disease

Oligomeric alpha-synuclein (α-syn) in saliva and phosphorylated α-syn deposits in the skin have emerged as promising diagnostic biomarkers for Parkinson’s disease (PD). This study aimed to assess and compare the diagnostic value of these biomarkers in discriminating between 38 PD patients and 24 healthy subjects (HSs) using easily accessible biological samples. Additionally, the study sought to determine the diagnostic potential of combining these biomarkers and to explore their correlations with clinical features. Salivary oligomeric α-syn levels were quantified using competitive ELISA, while skin biopsies were analyzed through immunofluorescence to detect phosphorylated α-syn at Ser129 (p-S129). Both biomarkers individually were accurate in discriminating PD patients from HSs, with a modest agreement between them. The combined positivity of salivary α-syn oligomers and skin p-S129 aggregates differentiated PD patients from HSs with an excellent discriminative ability with an AUC of 0.9095. The modest agreement observed between salivary and skin biomarkers individually suggests that they may reflect different aspects of PD pathology, thus providing complementary information when combined. This study’s results highlight the potential of utilizing a multimodal biomarker approach to enhance diagnostic accuracy in PD.

Quantitative hepatitis B core antibody and quantitative hepatitis B surface antigen: Novel viral biomarkers for chronic hepatitis B management.

The management of hepatitis B virus (HBV) infection now involves regular and appropriate monitoring of viral activity, disease progression, and treatment response. Traditional HBV infection biomarkers are limited in their ability to predict clinical outcomes or therapeutic effectiveness. Quantitation of HBV core antibodies (qAnti-HBc) is a novel non-invasive biomarker that may help with a variety of diagnostic issues. It was shown to correlate strongly with infection stages, hepatic inflammation and fibrosis, chronic infection exacerbations, and the presence of occult infection. Furthermore, qAnti-HBc levels were shown to be predictive of spontaneous or treatment-induced HBeAg and HBsAg seroclearance, relapse after medication termination, re-infection following liver transplantation, and viral reactivation in the presence of immunosuppression. qAnti-HBc, on the other hand, cannot be relied on as a single diagnostic test to address all problems, and its diagnostic and prognostic potential may be greatly increased when paired with qHBsAg. Commercial qAnti-HBc diagnostic kits are currently not widely available. Because many methodologies are only semi-quantitative, comparing data from various studies and defining universal cut-off values remains difficult. This review focuses on the clinical utility of qAnti-HBc and qHBsAg in chronic hepatitis B management.

Utility of Relative ADC in Discriminating the Benign and Malign Liver Masses: Diagnostic Potential in Comparison to ADC

Utility of Relative ADC in Discriminating the Benign and Malign Liver Masses: Diagnostic Potential in Comparison to ADC

Comprehensive analysis and prediction model of mitophagy and ferroptosis in primary immune thrombocytopenia.

Primary immune thrombocytopenia (ITP) is linked to specific pathogenic mechanisms, yet its relationship with mitophagy and ferroptosis is poorly understood. This study aimed to identify new biomarkers and explore the role of mitophagy and ferroptosis in ITP pathogenesis. Techniques such as differential analysis, Mfuzz expression pattern clustering, machine learning, gene set enrichment analysis, single-cell RNA sequencing (scRNA-seq) and immune infiltration analysis were employed to investigate the molecular pathways of pivotal genes. Two-sample Mendelian randomization (TSMR) assessed the causal effects in ITP. Key genes identified in the training set included GABARAPL1, S100A8, LIN28A, and GDF9, which demonstrated diagnostic potential in validation sets. Functional analysis indicated these genes' involvement in ubiquitin phosphorylation, PPAR signalling pathway and T-cell differentiation. Immune infiltration analysis revealed increased macrophage presence in ITP, related to the critical genes. scRNA-seq indicated reduced GABARAPL1 expression in ITP bone marrow macrophages. TSMR linked S100A8 with ITP diagnosis, presenting an OR of 0.856 (95% CI = 0.736-0.997, p = 0.045). The study pinpointed four central genes, GABARAPL1, S100A8, LIN28A, and GDF9, tied to mitophagy and ferroptosis in ITP. It posits that diminished GABARAPL1 expression may disrupts ubiquitin phosphorylation and PPAR signalling, impairing mitophagy and inhibiting ferroptosis, leading to immune imbalance.