Sepsis remains a leading global health challenge, with delayed recognition and limited diagnostic accuracy of current tools contributing to high morbidity and mortality. Conventional clinical scores (SOFA/qSOFA), standard biomarkers (CRP, PCT), and blood cultures suffer from delayed responsiveness, insufficient specificity, or slow turnaround, underscoring the urgent need for more reliable early diagnostic strategies. Presepsin, a soluble CD14 subtype generated during pathogen recognition by innate immune cells, has emerged as a promising biomarker with potential to reflect infection status earlier and more specifically than traditional markers. This systematic review and meta-analysis quantitatively evaluated the diagnostic accuracy of presepsin across diverse populations. PubMed, EMBASE, Web of Science, and Cochrane Library were searched for studies published between 2015 and 2025. Forty-seven studies involving 7,087 participants were included. Pooled sensitivity, specificity, diagnostic odds ratio (DOR), area under the curve (AUC), and likelihood ratios (PLR/NLR) with 95% confidence intervals (CI) were calculated using random-effects models. Heterogeneity was assessed with I² statistics, meta-regression, and subgroup analyses. Study quality was evaluated using QUADAS-2. Presepsin demonstrated excellent overall diagnostic performance: pooled sensitivity 0.84 (95% CI: 0.81–0.88), specificity 0.86 (95% CI: 0.80–0.90), DOR 32.23 (95% CI: 20.11–51.66), and AUC 0.91 (95% CI: 0.88–0.93). Subgroup analyses confirmed robust performance across settings and populations, with particularly high accuracy in neonates (sensitivity 0.90, specificity 0.92, AUC 0.96), followed by children (sensitivity 0.84, specificity 0.81, AUC 0.88, NLR 0.20) and adults (sensitivity 0.81, specificity 0.82, AUC 0.87). Meta-regression identified year of publication, geographic region, specimen type, population, and diagnostic criteria as key contributors to heterogeneity, but sensitivity analyses confirmed result stability. No significant publication bias was observed (p = 0.33). In conclusion, presepsin is a valuable and highly promising biomarker for sepsis diagnosis, showing favorable diagnostic accuracy across populations, with strongest utility in neonates. Its application in pediatric and adult patients warrants further validation through large, prospective, multi-center studies.

Glioma is one of the most prevalent primary intracranial tumors, and biomarker testing offers a non-invasive modality with high diagnostic efficiency. The aim of this meta-analysis is to evaluate the diagnostic effectiveness of exosomes as biomarkers for glioma. We included 16 studies on exosomes as biomarkers for gliomas. The pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) for 25 biomarkers across these 16 studies were as follows: 82% (95% CI: 0.77-0.86), 91% (95% CI: 0.86-0.94), 9.10 (95% CI: 5.64-14.68), 0.20 (95% CI: 0.16-0.25), 45.94 (95% CI: 25.40-83.09), and 0.92 (95% CI: 0.89-0.94), respectively. Meta-regression indicated that biomarker analysis, biomarker type, and sample size may be sources of heterogeneity. Subgroup analysis suggested that ultracentrifugation (UC) was a better method for extracting exosomes. miRNA and other RNA groups (sncRNA, lncRNA, circRNA) provided higher SEN (0.88 vs. 0.84 vs. 0.78) compared to proteins. This study demonstrates the superior diagnostic efficacy of exosomes as biomarkers for gliomas, with high accuracy in diagnosing gliomas.

Background: This meta-analysis evaluates the diagnostic accuracy of machine learning-derived FFRCT (ML-FFRCT) for CAD, using invasive coronary angiography-derived fractional flow reserve (ICA-FFR) as the gold standard to provide evidence for clinical translation. Methods: We systematically searched PubMed and Embase for relevant studies. Study quality was assessed using QUADAS-2 in RevMan 5.3. Diagnostic performance was evaluated by pooling sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the curve (AUC) using Stata 14.0. Meta-regression and subgroup analyses were conducted based on the publication year, country, study design, sample source, and sample size. Results: The pooled SEN was 0.84 (95% CI: 0.79–0.87) and SPE was 0.83 (95% CI: 0.77–0.88). The PLR and NLR were 4.95 (95% CI: 3.58–6.84) and 0.20 (95% CI: 0.15–0.26), respectively. The DOR was 25.15 (95% CI: 14.87–42.52) and the AUC was 0.90 (95% CI: 0.87–0.93), indicating high diagnostic accuracy. Deeks’ funnel plot revealed no significant publication bias. Conclusions: ML-FFRCT demonstrates high SEN and SPE in diagnosing CAD. These findings support its potential as a promising noninvasive tool for CAD assessment.

Background and Purpose : Glioblastoma remains a therapeutic challenge with a poor prognosis despite multimodal treatments. Reporter-based magnetic resonance imaging (MRI) offers a promising approach for tumor visualization, but its efficacy depends on sufficient reporter gene expression. This study aimed to develop a chimeric element-regulated ferritin heavy chain 1 (FTH1) reporter system to enhance MRI-based glioma detection while enabling targeted therapy via transferrin receptor (TfR)-mediated drug delivery. Methods: Using gene cloning techniques, we constructed a chimeric FTH1 expression system comprising tumor-specific PEG3 promoter (transcriptional control), bFGF-2 5′UTR (translational enhancement), and WPRE (mRNA stabilization). Lentiviral vectors delivered constructs to U251 glioblastoma cells and xenografts. FTH1/TfR expression was validated by Western blot and immunofluorescence. Iron accumulation was assessed via Prussian blue staining and TEM. MRI evaluated T2 signal changes. Transferrin-modified doxorubicin liposomes (Tf-LPD) were characterized for size and drug loading and tested for cellular uptake and cytotoxicity in vitro. In vivo therapeutic efficacy was assessed in nude mouse models through tumor volume measurement, MR imaging, and histopathology. Results: The chimeric system increased FTH1 expression significantly over PEG3-only controls (p < 0.01), with an increase of nearly 1.5-fold compared to the negative and blank groups and approximately a two-fold increase relative to the single promoter group, with corresponding TfR upregulation. Enhanced iron accumulation reduced T2 relaxation times significantly (p < 0.01), improving MR contrast. Tf-LPD (115 nm, 70% encapsulation) showed TfR-dependent uptake, inducing obvious apoptosis in high-TfR cells compared with that in controls. In vivo, Tf-LPD reduced tumor growth markedly in chimeric-system xenografts versus controls, with concurrent MR signal attenuation. Conclusions: The chimeric regulatory strategy overcomes limitations of single-element systems, demonstrating significant potential for integrated glioma theranostics. Its modular design may be adaptable to other reporter genes and malignancies.