Biomarkers in medicine最新文献

Aims: Hepatocellular carcinoma (HCC) represents a major global health burden. Tumor-associated autoantibodies (TAAs) represent promising biomarkers for cancer detection. This study aims to evaluate the diagnostic value of autoantibody panels in HCC.

Patients and methods: Candidate antigens were identified via multi-omics screening (Gene Expression Omnibus (GEO), Gene Expression Profiling Interactive Analysis (GEPIA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), Human Protein Atlas (HPA)) and validated by enzyme-linked immunosorbent assay (ELISA) in 280 HCC patients and 280 controls. Diagnostic models were constructed using eight machines learning algorithms.

Results: A total of 10 TAAs were identified, with AUCs ranging from 0.610 to 0.729. Logistic regression (LR) was identified as the optimal model. The LR model predicted that the positive rate of early HCC (62.39%) was significantly higher than that of AFP (47.71%). Notably, this model demonstrated superior predictive capability for AFP-negative HCC (AUC = 0.751). Combining the LR model with AFP for diagnosis achieved a positive rate of 96.36%, significantly higher than the 64.78% positive rate obtained with AFP alone.

Conclusion: This novel serum autoantibody panel serves as a valuable diagnostic biomarker. Its combination with AFP significantly reduces missed diagnoses, offering a promising strategy to optimize HCC screening.

Background: Preterm infants: VD-thyroid interplay and impact on brain development.

Methods: A retrospective cohort study design was employed, selecting 94 PI admitted to the NICU from January to August 2024 as the study subjects. Serum 25(OH)D levels and TF indicators (STSH, FT3, FT4) were measured, and brain structural abnormalities were evaluated using cranial ultrasound and MRI.

Results: The STSH level in the VD sufficient group (SG) was visibly lower as against the deficient group (DG) (p = 0.03), and FT3 and FT4 levels in the SG were visibly higher as against the DG (0.06, 0.01), although the correlation analysis was not statistically meaningful (p > 0.05). In the subjects with brain structural abnormalities, thyroid dysfunction was visibly present. Perinatal brain injury was positively correlated with STSH (r = 0.42) and negatively correlated with FT4 (-0.45); the subjects with intracranial hemorrhage suggested the strongest correlations (STSH: 0.51, FT4: -0.52) (all p < 0.001).

Conclusion: Thyroid dysfunction in PI is visibly associated with neurodevelopmental impairments, but there is no clear correlation between VD levels and TF. It is recommended to enhance TF monitoring for high-risk PI and optimize clinical management strategies.

Aims: Advanced rehabilitation technologies are progressively integrated into stroke rehabilitation. However, their capacity to elicit neurological benefits via neuroplasticity biomarkers, particularly brain-derived neurotrophic factor (BDNF), and their association with functional recovery remain poorly understood. This review aimed to systematically evaluate the effectiveness of technology-assisted rehabilitation on blood-based biomarkers in stroke patients, discuss their potential link to functional recovery, and quantitatively analyze BDNF through meta-analysis.

Methods: We conducted a systematic review and a meta-analysis of studies published from January 2010 to July 2025. A comprehensive search was performed using PubMed, Scopus, and Cochrane Library. Screening was conducted using Rayyan software, and analysis was performed using SPSS Statistics.

Results: Fifteen studies were included in the systematic review, with eight eligibles for meta-analysis. The serum BDNF subgroup presented a trend toward higher levels in the technology-assisted group (SMD = 0.44; 95% CI: -0.12 to 1.01; p = 0.13), while the plasma subgroup showed a significant decrease (SMD = -0.17; 95% CI: -1.24 to -0.18; p = 0.01).

Conclusions: Technology-assisted rehabilitation may influence neural repair biomarkers, suggesting a potential role in stroke recovery. However, inconsistencies across studies, particularly short intervention durations and heterogeneous study designs, indicate the need for high-quality and longitudinal investigations.

Background: Previous studies on extensive-stage small cell lung cancer (ES-SCLC) have primarily focused on serum tumor markers (STM) measurements at a single time point, overlooking the prognostic value of sequential STM monitoring.

Methods: We conducted a retrospective cohort study of 253 patients with ES-SCLC and applied latent class growth mixed modeling to define trajectory groups for neuron-specific enolase (NSE), carcinoembryonic antigen (CEA), and cytokeratin 19 fragment (CYFRA21-1).

Results: Overall survival (OS) and adjusted hazard ratios (HRs) (95% confidence intervals [CIs]) for mortality in the persistent-rising vs. low-stable groups were 1.19 (0.73 - 1.95), 1.58 (1.07 - 2.33), and 2.34 (1.11 - 4.92) for NSE, CEA, and CYFRA21-1, respectively. Persistent elevations of CEA (p = 0.021) and CYFRA21-1 (p = 0.026) were independent OS prognostic factors. For progression-free survival (PFS), adjusted HRs (95% CIs) were 2.27 (1.38 - 3.74), 1.22 (0.83 - 1.80), and 0.99 (0.48 - 2.05) for NSE, CEA, and CYFRA21-1, respectively, with NSE (p < 0.001) independently predicting PFS. Combined subgroups (three-low, one-high, and two-high) demonstrated significant OS and PFS stratification (p < 0.001).

Conclusion: Dynamic monitoring of NSE, CEA, and CYFRA21-1 provides a valuable approach for prognostic prediction in patients with ES-SCLC.

Aims: Obstructive sleep apnea (OSA) is characterized by diverse biological and clinical disturbances, yet no study has systematically examined scientific developments related to its objective assessment measures. This study aimed to map the development, research hotspots, and emerging trends related to biological and clinical assessment indicators in OSA.

Materials and methods: Publications indexed in the Web of Science Core Collection and Scopus from 2000 to 2025 were reviewed. A total of 1,793 articles were analyzed using VOSviewer, CiteSpace, the R bibliometrix package, and Python. The analysis assessed publication and citation trends, country contributions, keyword co-occurrence, and thematic evolution to map global research patterns in OSA assessment.

Results: The number of publications increased steadily over time, reflecting growing research interest in multidimensional assessment approaches. Research themes have evolved from general inflammatory and metabolic markers toward more mechanistic and clinically oriented indicators, including oxidative stress pathways, circulating biomarkers, and cerebrovascular or cognitive related measures.

Conclusions: Current research increasingly emphasizes integrated biological and clinical assessment frameworks for better characterization of OSA. Future studies should focus on validation, methodological standardization, and the integration of multiple assessment domains to facilitate clinical translation.

Aims: Acute ischemic stroke (AIS) is a leading cause of mortality and morbidity, yet largely preventable. An urgent clinical need exists for new biomarkers that enable early, noninvasive, and accurate diagnosis, even before the incident occurs. This study aims to determine the valency of serum sclerostin (SOST), receptor activator of nuclear factor-kappa B ligand (RANKL), oxidized low-density lipoproteins (OxLDL), and phoenixin-14 in AIS.

Patients and methods: A case-control study was conducted in the emergency department (ED) of a tertiary care hospital between June 2024 and September 2024, including 48 patients with AIS and 40 healthy individuals. The enzyme-linked immunosorbent assay was used to determine the levels of SOST, OxLDL, RANKL, and phoenixin-14. Diagnostic accuracy and independent associations with AIS were examined.

Results: Biomarker levels were significantly higher in AIS group. SOST was the best, with an area under the curve of 0.809. A one-unit increase in SOST and OxLDL levels increased the probability of stroke by 1.418 and 1.006 times, respectively.

Conclusions: SOST, OxLDL, RANKL, and phoenixin-14 May be complementary markers that warrant further validation, even though the results show an association rather than a causal relationship, suggesting they might be useful for differentiating AIS from healthy controls.

Purpose: This meta-analysis aimed to evaluate the pan-cancer prognostic value of the neutrophil-to-lymphocyte ratio (NLR) for risk stratification in patients with cancer.

Methods: We systematically searched Embase, PubMed, Google Scholar, and the Cochrane Library. The analysis included prospective studies, randomized controlled trials (RCTs), and post-hoc RCT analyses reporting multivariate-adjusted associations between the NLR and survival outcomes.

Results: Elevated NLR was significantly associated with worse overall survival (HR 1.61, 95% CI 1.44-1.80) and progression-free survival (HR 1.42, 1.27-1.59). Subgroup analyses by cancer type showed consistent associations in lung (OS-HR 2.29, 1.56-3.37; PFS-HR 1.73, 1.13-2.65), colorectal (OS-HR 1.88, 1.49-2.36; PFS-HR 1.43, 1.12-1.82), gastric (OS-HR 1.65, 1.46-1.87; PFS-HR 1.88, 1.14-3.11), and breast cancers (OS-HR 1.53, 1.27-1.83; PFS-HR 1.45, 1.29-1.64). Analysis by treatment modality revealed differential prognostic effects, including for chemotherapy (OS-HR 1.48, 1.34-1.65; PFS-HR 1.34, 1.14-1.57), immunotherapy (OS-HR 3.07, 1.65-5.71; PFS-HR 1.94, 1.12-3.36), surgery (OS-HR 1.90, 1.44-2.52), and targeted therapy plus chemotherapy (OS-HR 1.56, 1.28-1.90; PFS-HR 1.46, 1.22-1.76).

Conclusion: An elevated NLR is associated with inferior clinical outcomes across multiple cancers, with the magnitude of its prognostic impact varying by treatment modality.

Objective: Major depressive disorder (MDD) is the most common mood disorder affecting human health. The complex pathogenesis of MDD remains poorly understood, and the heterogeneity associated with the various subtypes limits our understanding of the pathophysiological mechanisms. Antidepressants are the main treatment for depressive symptoms, with selective serotonin reuptake inhibitors (SSRIs) most commonly used; however, predictors of SSRI response and their pharmacological mechanisms remain unclear. In this study, we aimed to identify the biomarkers that can predict treatment response and efficacy of SSRIs.

Methods: We compared serum protein levels between patients receiving SSRIs treatment and those who achieved remission through SSRI treatment to identify predictive biomarkers for SSRI treatment effect using a liquid chromatography-mass spectrometer.

Results: Sexhormone-binding globulin(SHBG) level was high in patients who achieved remission after SSRItreatment and was substantially different from that in patients with depression who received treatment without remission.

Conclusion: SHBG may serve as a predictive biomarker of SSRI treatment response and may help elucidate the molecular mechanisms of SSRI therapy in MDD, including the interplay between sex-hormone regulation and immune - inflammatory pathways.