Biomarkers最新文献

Background and objective: Waterpipe smoking (WPS) has increased globally and may lead to various metabolic disorders. However, its long-term effects and cessation impact on metabolic biomarkers and omentin-1 remain unclear. This study aims to evaluate the impact of WPS and its cessation on metabolic biomarkers and omentin-1 levels and explore their correlations.

Materials and methods: 90 individuals were categorized into three groups (non-smokers, waterpipe smokers and cessation of waterpipe smokers). FBS and lipid profiles including TC, TG and HDL were measured using the Cobas 6000 c501 system, while FI was analyzed with the Cobas 6000 c601 system. Omentin-1 concentrations were determined using the enzyme-linked immunosorbent assay (ELISA) with a human omentin ELISA kit.

Results: FI, HOMA-IR and lipid profiles were significantly elevated in WPS and cessation groups. Omentin-1 and DBP levels significantly decreased in both groups compared to non-smokers. Increased WPS duration leads to reduced BMI, WC and DBP, while cessation duration decreases FBS and SBP. A negative association was identified among omentin-1 with FBS and O₂.

Conclusion: WPS and its cessation adversely affect metabolic health, reducing omentin-1 levels and increasing the risk of metabolic disorders. Over time, cessation improves specific biochemical markers, highlighting the need for public health awareness.

Blood biomarkers can provide objective insight into a player's physiological state of recovery. Individualised approaches to biomarker monitoring may be of higher potential value in assessing player health and recovery compared to population-based reference ranges. We aimed to explore the application of individualised adaptive reference ranges (IARR) in English Premier League (EPL) soccer players using a POC biomarker for C-Reactive Protein (CRP) as a marker of inflammation. Using historical data collected from players' CRP values during the 2019-2020 season, we evaluated the effectiveness of static and IARR in identifying abnormal values and reported sensitivity and specificity at a 5% significance level. Our analysis confirmed that monitoring with IARR is more effective in identifying true abnormalities compared to population-based static reference ranges, particularly when the intra-individual variability is considerably lower than inter-individual variability. The application of IARR for blood monitoring data could assist the practitioner in identifying periods where a player may require performance (e.g. workload management and recovery practices) or medical support from the multi-disciplinary team. However, IARR serve more as an early warning system than a diagnostic tool. Thus, significant care is needed to prevent misuse and misinterpretation when implementing this strategy in real-world settings.

Preterm prelabor rupture of the fetal membranes (PPROM) increases the risk of neonatal mortality and morbidity. The etiology behind the condition is multifactorial but believed to result from an overactivation of inflammatory pathways. This systematic review aimed to synthesize the literature behind first-trimester biomarkers associated with PPROM and compare it to literature within the same area for preterm birth.A search strategy was performed in PubMed, Embase, and CINAHL from 1993-2024 resulting in 14,889 articles screened by two independent authors and presented according to PRISMA guidelines. The biomarkers from the included articles were categorized into four medical headings: The immune system, metabolism and endocrinology, hematology, and reproduction. Biomarkers associated with PPROM were primarily related to the immune system.C-reactive protein (CRP) and white blood cells (WBC) were often investigated for an association with PPROM but displayed divergent results of varying quality. Decreased concentrations of placental growth factor (PlGF) were associated with PPROM and spontaneous preterm birth, potentially highlighting a shared etiology, making soluble fms-like tyrosine kinase-1 (sFlt-1) interesting to investigate as well. Most biomarkers were examined in single studies, providing limited data to make significant conclusions about each biomarker. This review encourages further investigation of CRP, WBC, PlGF, and sFlt-1.

Background: The role of systemic inflammation in the development and progression of cardiovascular diseases has been attractive, but its association with incident dilated cardiomyopathy (DCM) is rarely investigated. This study aimed to systematically investigate the association between various inflammatory markers and DCM incidence.

Methods: The data were derived from the UK Biobank database. Systemic inflammation markers in this study encompassed peripheral immune cell counts and their ratios and the low-grade inflammation score (INFLA-score). The Cox proportional hazards regression, restricted cubic splines model, and segmented regression were adopted to assess the association between systemic inflammation markers and DCM incidence. Additionally, the subgroup Cox analysis stratified across sex was also performed.

Results: A total of 351,148 participants were enrolled in this study, and 377 subjects developed DCM during a mean follow-up of 12.21 years. The positive association between C-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR), and CRP-to-lymphocyte ratio (CLR) and DCM incident risk was found (CRP: HR = 1.190, P = 0.001; NLR: HR = 1.315, P = 0.033; CLR: HR = 1.206, P < 0.001), while the lymphocyte-to-monocyte ratio (LMR) was negatively associated with DCM incident risk (HR = 0.756; P = 0.033). Furthermore, the increased risk of DCM incidence was significantly and nonlinearly correlated with the reduction of platelet count (HR = 0.543; P = 0.002). In the subgroup analysis, sex-specific inflammation markers related to DCM development were noticed.

Conclusions: The study has underlined that multiple inflammation markers were significantly associated with the risk of incident DCM, which would provide evidence for the aetiological study of DCM.

Background: Lung cancer is the cancer with the highest morbidity and mortality in the world. With the increasing diagnosis rate of patients with early-stage lung cancer, surgery treatment becomes an option for more patients. However, there is a lack of effective indicators to assess the risk of recurrence after lung cancer surgery.

Methods: We collected levels of serum autoantibodies and evaluated their roles as biomarkers especially for postoperative recurrence of lung cancer. In vitro experiments including antibody-dependent cellular cytotoxicity (ADCC), antibody-dependent cellular phagocytosis (ADCP) and complement-dependent cytotoxicity (CDC) were performed to explore the functions of serum autoantibodies.

Results: Our study demonstrated that serum autoantibody-positive patients with early-stage lung cancer had a longer postoperative progression period. The levels of serum autoantibodies in patients with lung cancer were higher than that in patients with benign lung diseases. But all the serum autoantibodies had no difference between patients with stage I and II. In addition, the results of in vitro experiments indicated that serum autoantibodies can mediate immune responses and enhance anti-tumour effects.

Conclusion: This study proposed effective biomarkers for prognosis in lung cancer patients after surgery which is critical to reduce the recurrence.

Introduction: Elevated fluoride (F^-) exposure during childhood produces dental fluorosis (DF). Nails have been used for monitoring systemic F^- in relation to DF. The aim of this study was to evaluate F^- levels in toenails in association with DF severity in Mexican schoolchildren.

Materials and methods: 120 schoolchildren from nonendemic areas (NEAs) and endemic F^- areas (EAs) were screened for DF via the Thylstrup and Fejerskov index (TFI). Toenails were collected to quantify systemic F^-. The associations between the biomarker, DF severity, tap water intake, sex, and age were analyzed.

Results: The mean F^- in toenails in the NEAs and EAs were 0.63 ± 0.43 and 2.72 ± 1.38 mg/kg, respectively (p < 0.001). A positive correlation was observed between the biomarker and DF severity (r_s = 0.755, p < 0.001). Tap water consumption and the biomarker were associated with DF severity (p < 0.001). Within TFI7-8 the mean F^- level was higher in those ages 10-11 than in those ages 8-9 (p < 0.05).

Conclusion: Systemic F^- levels in toenails are associated with DF severity in Mexican schoolchildren from both the NEAs and the EAs, which reflects the ability of the biomarker to accurately record the exposure to the compound in relation to clinical damage.

Background: Lung cancer is a primary global health concern, responsible for a considerable portion of cancer-related fatalities worldwide. Understanding its molecular complexities is crucial for identifying potential targets for treatment. The goal is to slow disease progression and intervene early to prevent the development of advanced lung cancer cases. Hence, there's an urgent need for new biomarkers that can detect lung cancer in its early stages.

Methods: The study conducted RNA-Seq analysis of lung cancer samples from the publicly available SRA database (NCBI SRP009408), including both control and tumour samples. The genes with differential expression between tumour and healthy tissues were identified using R and Bioconductor. Machine learning (ML) techniques, Random Forest, Lasso, XGBoost, Gradient Boosting and Elastic Net were employed to pinpoint significant genes followed by classifiers, Multilayer Perceptron (MLP), Support Vector Machines (SVM) and k-Nearest Neighbours (k-NN). Gene ontology and pathway analyses were performed on the significant differentially expressed genes (DEGs). The top genes from DEG and machine learning analyses were combined for protein-protein interaction (PPI) analysis, identifying 10 hub genes essential for lung cancer progression.

Results: The integrated analysis of ML and DEGs revealed the significance of specific genes in lung cancer samples, identified the top 5 upregulated genes (COL11A1, TOP2A, SULF1, DIO2, MIR196A2) and the top 5 downregulated genes (PDK4, FOSB, FLYWCH1, CYB5D2, MIR328), along with their associated genes implicated in pathways or co-expression networks were identified. Among the various algorithms employed, Random Forest and XGBoost proved effective in identifying common genes, underscoring their potential significance in lung cancer pathogenesis. The MLP exhibited the highest accuracy in classifying samples using all genes. Additionally, the protein-protein interaction (PPI) analysis identified 10 hub genes that are pivotal in lung cancer pathogenesis: COL1A1, SOX2, SPP1, THBS2, POSTN, COL5A1, COL11A1, TIMP1, TOP2A and PKP1.

Conclusion: The study contributes to the early prediction of lung cancer by identifying potential biomarkers that could enhance early diagnosis and pave the way for practical clinical applications in the future. Integrating DEGs and machine learning-derived significant genes for PPI analysis offers a robust approach to uncovering critical molecular targets for lung cancer treatment.

Background: Growing evidence indicates that noncombustible products could be a tobacco harm reduction tool for smokers who do not quit. The Tobacco Heating System (THS) emits substantially lower levels of harmful cigarette smoke constituents, and previous randomized clinical studies showed improved levels of biomarkers of potential harm (BoPH) linked to smoking-related disease.

Methods: In this cross-sectional study of healthy participants (n = 982) who (i) smoked cigarettes, (ii) had voluntarily switched from smoking to THS use, or (iii) formerly smoked, blood and urine samples were assayed for nine BoPH. The co-primary endpoints were carboxyhemoglobin, total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol, white blood cells, and 8-epi-prostaglandin-F_2α. The key secondary endpoints were high-density lipoprotein cholesterol, soluble intercellular adhesion molecule-1, 11-dehydrothromboxane B₂, central vascular augmentation index, and forced expiratory volume in 1 s (%predicted post-bronchodilator).

Results: THS users showed significant favorable differences in all nine BoPH compared to current smokers. Results in THS users were similar to those in former smokers.

Conclusion: Compared to current smokers, healthy participants who voluntarily switched from smoking to THS use for ≥2 years in the real world had favorable differences in BoPH related to oxygen delivery, genotoxicity, inflammation, oxidative stress, lipid metabolism, endothelial function, platelet activation, and cardiovascular and respiratory function. Clinicaltrials.gov Identifier: NCT05385055.