Biomarkers in medicine最新文献

Aims: To explore hepatic steatosis and fibrosis related biomarkers in patients with metabolic dysfunction-associated steatotic liver disease (MASLD).

Patients and methods: Total 158 patients with MASLD were tested with Fibroscan to measure hepatic steatosis value (CAP value) and liver fibrosis value (E value), and divided into mild group (31 cases), moderate (49 cases), and severe fatty liver group (78 cases) according to CAP value; no fibrosis group (106 cases), early fibrosis group (38 cases), and advanced fibrosis and cirrhosis group (14 cases) according to E value.

Results: E value was negatively correlated with CHOL and LDL, and CAP value was positively correlated with LDL. TG, CHOL and LDL levels in severe fatty liver group were significantly higher than those in mild fatty liver group; TG and LDL levels in moderate fatty liver group were higher than those in mild fatty liver group. TG level in early fibrosis group was significantly higher than that in advanced fibrosis and cirrhosis group.

Conclusion: With the aggravation of hyperlipidemia, hepatic steatosis increases; with the aggravation of liver fibrosis, TG level decreases. Lipid metabolism worsens with the degree of steatosis. LDL is related to the severity of hepatic steatosis and fibrosis.

Purpose: In-stent restenosis (ISR) after vertebral artery stenting (VAS) affects 20-35% of patients, yet current risk stratification lacks sensitivity for early intervention. We propose the first combined biomarker model integrating endothelin-1 (ET-1) and fibroblast growth factor 23 (FGF23) to address this gap.

Methods: A prospective cohort study was conducted involving 148 patients who underwent VAS between 2020 and 2024. Blood samples were collected preoperatively to measure ET-1 and FGF23 levels. ISR was defined as a stenosis of at least 50% on follow-up imaging. Statistical analyses included multivariable logistic regression and receiver operating characteristic (ROC) curve evaluations to assess the biomarkers' performance.

Results: ISR occurred in 34 patients (23%). Both ET-1 and FGF23 levels were significantly higher in the ISR group. Multivariate analysis identified ET-1, FGF23, stent length, and LDL-C levels as independent predictors of ISR. The combined model using both biomarkers demonstrated superior discriminative performance (AUC = 0.96) compared to individual markers (AUC = 0.73 for ET-1 and AUC = 0.77 for FGF23). The model achieved sensitivity and specificity of 92.3% and 89.7%, respectively.

Conclusion: The combined assessment of serum ET-1 and FGF23 exhibits a synergistic predictive role for ISR after VAS. The ET-1/FGF23 model enables personalized risk stratification, guiding targeted therapies to reduce recurrent ischemic events and healthcare costs.

Objective: This study aims to evaluate the predictive value of the CALLY index in cancer prognosis via systematic review and meta-analysis.

Methods: PubMed, Web of Science, Embase, and Cochrane were searched up to November 2024. Study quality was evaluated using the Newcastle-Ottawa Scale (NOS), and meta-analysis was performed with STATA 17.0.

Results: Among 21 cohort studies,the findings indicated that, regarding overall survival (OS), a low CALLY index was correlated with a 113% elevated likelihood of all-cause mortality compared to those with a higher CALLY index (risk ratio [RR] = 0.47, 95% confidence intervals [95%CI]: 0.42-0.53). An 85% elevated risk of disease-free survival (DFS) and relapse-free survival (RFS) was observed in individuals with a low CALLY index (pooled RR = 0.54, 95%CI: 0.46-0.63). Moreover, a lower CALLY index was correlated with a significantly greater tumor burden (standardized mean difference (SMD) = -0.64, 95%CI: -0.76-0.52). The stage-specific analysis demonstrated that a low CALLY index significantly increased the risk of cancer progression by 54% in individuals at stage II (RR = 0.65, 95%CI: 0.43-0.98) and by 67% in individuals at stage III (RR = 0.60, 95%CI: 0.43-0.86).

Conclusion: The CALLY index independently predicts adverse cancer outcomes.

Background: Periostin (POSTN) is a matricellular protein involved in kidney fibrosis and inflammation but also linked to tumor progression and regulation of the local microenvironment.

Aims: This study aimed to evaluate the association between serum POSTN, transgelin (TAGLN) and highly sensitive interleukin 6 (hsIL-6) and de novo malignancy occurrence post kidney transplant (KTx).

Methods: Serum concentrations of POSTN, TAGLN, and hsIL-6 were measured in 127 KTRs and compared with 32 healthy controls. Patients were followed for a median (IQR) of 29 (25-32) months.

Results: Log-transformed serum POSTN concentrations were lower in the KTx group (mean [SD]: 6.80[0.53] vs. 7.06[0.33] pmol/l), whereas transgelin (4.62[0.34] vs. 4.30[0.29] ng/mL) and hsIL-6 (1.51[0.50] vs. 0.99[0.37] pg/mL) were elevated (p < 0.001 for all). Final model showed satisfactory discrimination (AUC 0.83; 95% CI 0.74-0.91). Patients in the moderate POSTN zone were characterized higher odds of malignancy (OR 4.40; 95% CI 1.21-16.91, p = 0.011). Higher POSTN levels were independently associated with time post-KTx (β = 0.20; p < 0.001). Lower TAGLN levels were observed in older patients (β = -0.005; p = 0.011), those with CV disease (β = -0.200; p = 0.008) and among smokers (β = -0.19; p = 0.026).

Conclusions: In patients post-KTx, elevated serum POSTN is an independent predictor of new-onset malignancy. Further prospective evaluation is warranted.

Objective: This study evaluated the prognostic significance of miR-21 and miR-486 expression in patients undergoing clock-guided minimally invasive surgery for pulmonary nodules.

Methods: In this prospective cohort study, intraoperative tissues from 138 lung cancer patients were analyzed. MiRNA expression was quantified via RT-qPCR, and patients were stratified into high- and low-expression groups using ROC-determined cutoffs. Postoperative outcomes, including residual nodule characteristics and survival, were monitored.

Results: At 6 months postoperatively, the high-expression group demonstrated significantly larger residual nodules (1.06 vs. 0.73 cm, p < 0.001), higher density (p = 0.003), and elevated metabolic activity (p = 0.014). This group also experienced shorter median overall survival (OS) (17.4 vs. 21.6 months, p = 0.003) and progression-free survival (PFS) (11.5 vs. 16.6 months, p = 0.012). In multivariable analysis, both miR-21 (HR = 1.75, p = 0.023) and miR-486 (HR = 1.68, p = 0.031) remained independent predictors of poor OS after adjusting for clinical covariates.

Conclusion: Elevated miR-21 and miR-486 expression predicts aggressive tumor behavior and poor survival after precise nodule resection, highlighting their potential as biomarkers for postoperative risk stratification.

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.

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.

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.