Biomarkers in medicine最新文献

Aims: Cancer screening is essential for reducing GC-associated deaths. Nonetheless, implementing population-based screening strategies poses challenges. In this study, a comprehensive receiver operating characteristic (ROC) analysis was conducted on 2565 microRNAs (miRNAs) from 6997 samples to identify a classifier for GC screening.

Method: First, batch effects were corrected across the five Gene Expression Omnibus Series (GSE) datasets. Second, a predictive model was established using the incidence method. Finally, this model was validated using randomly selected datasets, all datasets after batch effect removal, and each of the datasets separately.

Results: Six miRNAs, namely miR-1290, miR-5100, miR-1343-3p, miR-8073, miR-4706, and miR-4787-3p were identified, with an area under the ROC curve (AUC) of 0.990 ± 0.002, 0.993 ± 0.002, 0.996 ± 0.004, 0.978 ± 0.010, 0.957 ± 0.015, and 0.969 ± 0.015, respectively. The miRNA set obtained by combining the six miRNAs yielded an AUC of 0.997 ± 0.001, which was higher than that of the six individual miRNAs (p < 0.001). Validation across the total dataset and five GSE datasets (GSE106817, GSE112264, GSE113486, GSE113740, and GSE164174) yielded AUCs of 0.997, 0.999, 1.000, 1.000, 0.996, and 0.994, respectively.

Conclusion: The novel miRNA set comprising miR-1290, miR-5100, miR-1343-3p, miR-8073, miR-4706, and miR-4787-3p holds promise as a diagnostic classifier for GC screening.

Objective: Colorectal cancer (CRC) is a major contributor to global cancer mortality. Reliable biomarkers like c-Jun and Interleukin-8 (IL-8) may improve prognosis and therapy. Considering the possible ethnic differences in CRC biomarkers, this study is the first to examine a distinct Southeast Asian cohort (Indonesia).

Methods: A retrospective study analyzed 98 CRC patients using immunohistochemistry to evaluate c-Jun and IL-8 expression. Paraffin-embedded tissues were assessed for correlations with clinicopathological features. Statistical analyses were performed with p < 0.05 considered significant.

Results: c-Jun expression was significantly higher in mucinous or serrated histology (median 1.80, range 0.90-2.30) compared to adenocarcinoma, NOS (median 1.60, range 0.70-2.50) (p = 0.04). Meanwhile, IL-8 expression showed no significant differences across all clinicopathological factors. Neither biomarkers showed significant association with most clinicopathological factors, including age, sex, tumor size, location, stage, grade, invasion, or metastasis.

Conclusions: c-Jun and IL-8 expression showed limited prognostic relevance for most clinicopathological features of CRC. However, elevated c-Jun expression may indicate its particular involvement in distinct CRC subtype pathogenesis.

Aim: The study of human sweat and its metabolite profile can reveal important metabolic processes. Metabolites produced during respiratory infections, such as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), create unique odor signatures. This study aims to identify a distinct signature of SARS-CoV-2 infection through the analysis of sweat metabolites.

Material and methods: Sweat samples were collected from the axillae of individuals during the Delta and Omicron pandemic waves. Samples represent symptomatic (ventilator; n = 49), asymptomatic (home quarantine; n = 46) patients, and healthy individuals (n = 50) from Pune district, Maharashtra. Sweat metabolites were extracted under acidic conditions and analyzed using gas chromatography-mass spectrometry (GC-MS) with the NIST library and a hit threshold of 80%. The identified compounds were assessed for their origins and metabolic roles.

Results: Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) revealed distinct clustering of the groups. We report six compounds-6-ethyl-2-methyl decane, tetradecane, styrene, 2-ethyl-1-hexanol, 2-methyl heptane, and 1-ethoxy pentane-specifically in infected individuals.

Conclusion: Alkanes and their derivatives were significantly abundant in the symptomatic cohort and linked to inflammatory lung conditions as compared to healthy controls, thus affirming the presence of a distinct sweat metabolite profile in SARS-CoV-2 symptomatic individuals.

Objective: To evaluate the predictive value of peripheral blood inflammatory biomarkers - Systemic Immune-Inflammation Index (SII), Neutrophil-to-Lymphocyte Ratio (NLR), and Platelet-to-Lymphocyte Ratio (PLR) - for recurrence risk of intrauterine adhesion (IUA) following hysteroscopic adhesiolysis.

Methods: This retrospective study included 170 patients who underwent hysteroscopic adhesiolysis for IUA between October 2022 and October 2024. Within a 6-month follow-up based on their recurrence status, the patients were categorized into recurrence (R-IUA, n = 60) and non-recurrence (Non-IUA, n = 110) groups. SII, NLR, and PLR levels were assessed preoperatively, 24 hours postoperatively, and on postoperative day 7. Dynamic changes (δSII, δNLR, δPLR) were calculated. ROC curves assessed predictive performance, and logistic regression identified independent risk factors, which were incorporated into a nomogram model.

Results: The R-IUA group had significantly higher levels of SII and NLR at all time points, with δSII showing the strongest predictive accuracy (AUC > 0.85). Multivariate analysis identified δSII, δNLR, amenorrhea, curettage history, and lack of intrauterine stent as independent predictors. The nomogram incorporating these factors achieved an AUC of 0.89.

Conclusion: Dynamic inflammatory biomarkers, especially δSII and δNLR, are effective predictors of IUA recurrence and may guide individualized postoperative management.

Aims: This study aimed to evaluate serum levels of killer cell lectin-like receptor B1 (KLRB1, CD161) as a biomarker for distinguishing between viral and bacterial causes in patients with community-acquired pneumonia (CAP).

Materials & methods: A total of 120 individuals were enrolled between November 2024 and January 2025: 46 with viral pneumonia, 44 with bacterial pneumonia, and 30 healthy controls. Serum KLRB1 levels were measured using ELISA. Microbiological cultures, PCR testing, and serology were used to classify pneumonia etiology. Additional laboratory and radiological data were collected.

Results: Streptococcus pneumoniae and Influenza A H1N1 were the most common agents for bacterial and viral pneumonia, respectively. KLRB1, CRP, and leukocyte levels were significantly higher in bacterial cases than viral ones (p < 0.001). KLRB1 levels were also significantly higher in healthy controls compared to both pneumonia groups. ROC analysis showed a KLRB1 cutoff of 5.11 ng/mL yielded 97% sensitivity and 85% specificity in distinguishing bacterial from viral pneumonia.

Conclusions: Serum KLRB1 may serve as a valuable biomarker to differentiate between viral and bacterial CAP, supporting early diagnosis and optimized treatment decisions.

Introduction: Galectin-3 (Gal-3) is a biomarker associated with myocardial fibrosis, a key factor in the dysfunction of the functionally single ventricle (FSV) in patients after the Fontan procedure. This study aimed to evaluate the relationship between serum Gal-3 levels and echocardiographic and cardiopulmonary exercise parameters in this population.

Methods: Thirty-seven patients (23 males, 14 females) with Fontan circulation were included. All underwent speckle-tracking echocardiography (STE), cardiopulmonary exercise testing (CPET), and serum Gal-3 measurement using ELISA. Correlations between Gal-3 and clinical, echocardiographic, and CPET parameters were analyzed.

Results: Gal-3 levels correlated positively with patient age and time since Fontan completion (p < 0.05). No significant associations were found between Gal-3 and ejection fraction, global longitudinal strain (GLS), or free wall strain. However, Gal-3 showed a significant correlation with the transmural strain gradient (p < 0.05). No association was observed between Gal-3 and CPET parameters, including peak VO₂.

Conclusions: Galectin-3 may reflect fibrotic remodeling of the FSV, as suggested by its correlation with the transmural strain gradient. The absence of a relationship with exercise capacity highlights the complexity of Fontan-related dysfunction. Gal-3 shows promise as a noninvasive biomarker of myocardial fibrosis in this unique patient group.

Aims: This study aims to validate the potential of miR-93-3p, which is aberrantly expressed in acute ischemic stroke (AIS) patients, as a key biomarker for diagnosing AIS and predicting subsequent cognitive impairment.

Materials & methods: The level of miR-93-3p was measured using quantitative real-time polymerase chain reaction (qRT-PCR). Receiver operating characteristic (ROC) curves were employed to assess the diagnostic value of miR-93-3p in AIS patients and its predictive value for post-stroke cognitive impairment (PSCI) risk after AIS. Additionally, SH-SY5Y cells subjected to oxygen-glucose deprivation (OGD) were used to explore how miR-93-3p regulates cell viability, inflammation, and oxidative stress. The target genes of miR-93-3p were predicted by integrating the TarBase, TargetScan, and miRDB databases, followed by GO and KEGG pathway enrichment analysis of the candidate genes.

Results: miR-93-3p levels were higher in AIS patients, with a more pronounced increase in those with PSCI (p < 0.001). ROC curve analysis confirmed that miR-93-3p has strong diagnostic value for differentiating AIS patients from healthy controls. Moreover, miR-93-3p levels can independently predict PSCI occurrence. The levels of C-reactive protein and homocysteine were positively correlated with the level of miR-93-3p. In miR-93-3p-silenced SH-SY5Y cells, OGD-induced cell damage were reversed. The secretion of inflammatory factors and malondialdehyde (MDA) was reduced, while the intracellular levels of superoxide dismutase (SOD) and glutathione peroxidase (GSH-PX) were increased. The predicted targets of miR-93-3p were significantly enriched in key pathways implicated in stroke pathophysiology, including ubiquitin-mediated proteolysis, cellular response to decreased oxygen levels, and the Notch signaling pathway.

Conclusions: In conclusion, miR-93-3p may serve as a biomarker for AIS diagnosis and PSCI prediction.

Aims: This meta-analysis evaluates the diagnostic and prognostic performance of severe pneumonia through a comprehensive meta-analysis.

Patients and methods: A systematic literature search was conducted across PubMed, Embase, Cochrane Library, Web of Science, and Scopus. Studies were included if they focused on severe pneumonia patients, assessed relevant inflammatory markers, and provided sufficient data for meta-analysis.

Results: The diagnostic meta-analysis found a sensitivity of 0.72 (95% CI: 0.64-0.79) and a specificity of 0.75 (95% CI: 0.70-0.80). Area under the summary receiver operating characteristic curve was 0.80 (95% CI: 0.76-0.83). However, these pooled estimates showed high heterogeneity (I² > 80%), indicating substantial variation across studies and requiring cautious interpretation. Subgroup analyses revealed that procalcitonin (PCT) had the highest specificity. For predicting short-term mortality, a preliminary analysis of five studies (n = 463) showed a pooled sensitivity of 0.72 (95% CI: 0.64-0.79) and a specificity of 0.65 (95% CI: 0.59-0.70), suggesting a potential prognostic signal that needs validation in larger, prospective cohorts.

Conclusions: Inflammatory markers are valuable auxiliary tools to support clinical judgment in assessing severity and predicting outcomes in patients with severe pneumonia. They offer moderate accuracy in distinguishing severe from non-severe cases and in predicting short-term mortality.

Background: Cardiovascular disease (CVD) remains the leading cause of premature mortality worldwide. Among its manifestations, ischemia with non-obstructive coronary arteries (INOCA) and myocardial infarction with non-obstructive coronary arteries (MINOCA) are increasingly recognized and associated with major adverse cardiovascular events. While biomarkers are established tools for diagnosing and predicting outcomes in CVD, their role in INOCA and MINOCA remains unclear. This review summarizes current evidence on cardiovascular biomarkers and their clinical relevance in the context of INOCA and MINOCA.

Methods: A systematic review of original studies was conducted using Ovid-MedLine and Embase databases. Eligible studies included adult patients diagnosed with INOCA or MINOCA, with measurements of specific serum biomarkers.

Results: Of 1,493 records identified, 53 were included in the quantitative analysis, encompassing 10 biomarkers. Among inflammatory markers, only C-reactive protein was significantly higher in INOCA patients compared to healthy controls. Metabolic, coagulation and endothelial biomarkers showed no differences. Limited data in the MINOCA population precluded comprehensive biomarker analysis.

Conclusion: Elevated biomarkers of inflammation in INOCA suggest underlying mechanisms such as oxidative stress, cytokine activation, and immune-mediated microvascular dysfunction. Their diagnostic and prognostic potential in INOCA remains promising but requires further validation in clinical studies.