Lung cancer (LC) is the most frequently diagnosed cancer and is the leading cause of cancer-associated death. Serum markers that exhibit high sensitivity and specificity for LC may assist in the diagnosis and prognosis of LC. The banked serum samples from 599 individuals, including 201 healthy controls, 124 patients with benign lung diseases, and 274 LC cases, were used. The serum concentrations of biomarkers were determined by electrochemiluminescence immunoassay and chemiluminescence immunoassay. The results showed that the serum human epididymis secretory protein 4 (HE4) levels in the LC group were significantly higher than in the healthy and benign lung disease groups. The serum levels of HE4, NSE, and CYFRA21-1 were significantly higher in patients with LC compared to those in the benign lung disease group. The area under the area under the curve (AUC) of HE4 for discriminating LC from healthy controls was 0.851 (95% CI, 0.818-0.884) and 0.739 (95% CI, 0.695-0.783), 0.747 (95% CI, 0.704-0.790), 0.626 (95% CI, 0.577-0.676), and 0.700 (95% CI, 0.653-0.747) for NSE, CYFRA21-1, SCC, and ProGRP, respectively. The AUC value of the combination of serum HE4 combined with NSE, CYFRA21-1, SCC, and proGRP for cancer diagnosis was 0.896 (95% CI, 0.868-0.923). In early LC, the AUC value of HE4 for discriminating early LC from healthy controls was 0.802 (95% CI, 0.758-0.845), 0.728 (95% CI, 0.679-0.778), 0.699 (95% CI, 0.646-0.752), 0.605 (95% CI, 0.548-0.662), and 0.685 (95% CI, 0.630-0.739) for NSE, CYFRA21-1, SCC, and ProGRP, respectively. The AUC value of the combination of serum HE4 with NSE, CYFRA21-1, SCC, and proGRP for early LC was 0.867 (95% CI, 0.831-0.903). Serum HE4 is a promising LC biomarker, particularly for early-stage LC. Measuring serum HE4 levels may improve the diagnostic efficiency of LC.

Objective: To investigate the clinical value of fucosylated GP73 (Fuc-GP73) levels for differential diagnosis of hepatocellular carcinoma from other liver diseases. Methods: Serum specimens were collected from 50 patients with hepatocellular carcinoma, 60 patients with other digestive system diseases (ODSD), and 40 normal controls. Lectin affinity chromatography column combining with the enzyme-linked immunosorbent assay (ELISA) using the ELISA index was utilized to measure the level of Fuc-GP73. By receiver operating characteristic (ROC) curve analysis its sensitivity and specificity were used to evaluate the diagnostic significance of Fuc-GP73 in hepatocellular carcinoma. Results: The median serum Fuc-GP73 level of hepatocellular carcinoma (20.4 μg/L) was much higher than that of ODSD patients (1.8 μg/L) and the normal controls group (0.3 μg/L), significantly (P <0.01). There was no significant correlation between serum Fuc-GP73 level and sex, age, and tumor size in the hepatocellular carcinoma group (P > 0.05); however, it was related to tumor, node, metastasis stage and lymph node metastasis (P <0.05). The area under the ROC curve (AUC) of Fuc-GP73 to detect hepatocellular carcinoma alone was 0.885; with the prespecified specificity of 95%, the sensitivity and the cutoff value were 82% and 3.1 μg/L. In addition, the combined test of Fuc-GP73 with other biomarkers can improve the clinical diagnostic efficiency; the AUC can reach to 0.983; and with the prespecified specificity of 95% its sensitivity increased to 94%. Conclusion: Fuc-GP73 can act as a superior glycobiomarker for the differential diagnosis of hepatocellular carcinoma; its combined detection with other biomarkers can improve diagnostic accuracy.

IntroductionExposure to the fine particulate matter PM2.5 is strongly associated with atherosclerotic diseases, creating considerable public concern. Nevertheless, the mechanisms have not been fully elucidated. We exposed atherosclerosis-prone apoE-deficient mice to PM2.5 to begin investigating these mechanisms.Material and methodsThirty-two 8-week-old male apoE–/– mice were divided to two groups fed with high-fat diet: a control group instilled with 0.9% saline, and an experimental group instilled with PM2.5 (30 mg/kg/day) for 8 weeks. We measured PM2.5 in whole blood by the ICP-MS method, and lipids and inflammatory factors by standard methods. The whole descending arteries were stained with oil red O; Aortic roots were stained with Movat, Sirius Red and immunohistochemical stains for pathological analysis; Brachiocephalic arteries for scanning electron microscopy, the descending arteries for Q-PCR. Echocardiography was used to evaluate cardiac function.ResultsIn PM2.5 group, we observed elevated heavy metal components, consistent with higher amounts of platelets in total blood. The PM2.5 group also had elevated serum inflammatory factor levels. Finally, the PM2.5 group showed larger atherosclerotic plaques (p = 0.0231), higher numbers of lesion macrophages (p = 0.0183), greater injury to endothelial layers with greater adherence of platelets and leukocytes, elevated inflammatory factor levels, the NAD(P)H oxidase subunits p22phox and p47phox (p = 0.0079 and p = 0.0294), the M1/M2 associated markers IL-6, TNF-α (p = 0.0291, p = 0.0286), iNOS, IL-12 (p = 0.0122 and p = 0.0280) and arginase-1, and CD206 (p = 0.0216 and p = 0.0317).ConclusionsPM2.5 exposure activated circulating leukocytes, platelets and associated inflammatory factors, contributing to the progression of atherosclerosis in apoE–/– mice.

Purpose Periostin is a secreted extracellular matrix protein that is strongly associated with triglyceride metabolism, chronic inflammation, and insulin resistance. Growing evidence suggests that there is a link between periostin and ovarian function. Our aim was to ascertain whether circulating periostin levels are altered in women with polycystic ovary syndrome (PCOS) and to further explore the relationship between periostin and glucose metabolism disorder in PCOS patients. Methods In total, 50 women with PCOS and 30 age-matched controls without PCOS were recruited for this cross-sectional study. Periostin levels were measured using ELISA as well. Results Circulating periostin levels were significantly elevated in PCOS women compared with controls [4206.75(222.00, 4815.25) vs. 430.75(142. 13, 730.86) ng/ml, P=0. 005]. Spearman’s correlation analysis showed that serum periostin levels had a positive correlation with body mass index (BMI), uric acid, homeostasis model assessment of insulin resistance (HOMA-IR), high-sensitive C reactive protein (hs-CRP), and a negative correlation with insulin sensitivity index (ISI). Logistic regression models revealed that PCOS was correlated with waist to hip ratio (WHR), fasting blood glucose (FBG), and periostin levels. In addition, multivariate linear regression analyses showed that FBG, HOMA-IR, and the lipid accumulation index (LAP) were independent factors influencing serum periostin levels. Conclusion PCOS is associated with elevated levels of periostin.

Objective We aimed to examine the association between bone morphogenetic protein-9 (BMP-9) and type 2 diabetes mellitus (T2DM) in conjunction with non-alcoholic fatty liver disease (NAFLD) and insulin resistance (IR) and to identify evidence supporting the potential role of BMP-9 in the clinical prevention and treatment of T2DM in conjunction with NAFLD. Methods One hundred and twenty subjects were included in this study. We sorted all of the subjects into four groups of equal size (n=30 each). A trained expert assessed the height, weight, systolic blood pressure (SBP), and diastolic blood pressure (DBP) of the subjects and computed the body mass index (BMI). All subjects had their fasting blood glucose (FBG), fasting insulin (FINS), serum BMP-9, and biochemical indices assessed. Results Significant variations were observed in BMI, SBP, DBP, ALT, TC, TG, HDL-C, LDL-C, ApoB, FBG, FINS, HOMA-IR, and serum BMP-9 among the four groups (P<0.05). The level of serum BMP-9 was positively correlated with HDL-C, while the level of serum BMP-9 was negatively correlated with BMI, SBP, DBP, ALT, TC, TG, LDL-C, FBG, FINS, and HOMA-IR. Multiple stepwise regression analyses revealed that FINS, LDL-C, HDL-C, and BMI were independent factors impacting serum BMP-9 levels (P<0.05). Logistic regression analyses revealed that BMP-9 was a protective factor for T2DM paired with NAFLD, while HOMA-IR was a risk factor. Conclusion Serum BMP-9 levels are significantly lower in the T2DM+NAFLD group when compared to other groups, and BMP-9 is an independent risk factor for T2DM paired with NAFLD.