Triple-negative breast cancer (TNBC) has a higher risk of death within 5 years of being diagnosed than the other forms of breast cancer. It is the second leading cause of death due to cancer among women. Currently, however, no diagnostic blood-based biomarker exists to identify the early stages of TNBC. To address this point, we utilized a human protein microarray system to identify serum autoantibodies that showed different expression patterns between TNBC and normal serum samples, and identified five autoantibodies showing TNBC-specific expression. Among them, we selected the thioredoxin-like 2 (TXNL2) autoantibody and evaluated its diagnostic relevance by dot blot analysis with the recombinant TXNL2 protein. We demonstrated that the TXNL2 autoantibody showed 2- to 6-fold higher expression in TNBC samples than in normal samples suggesting that serum TXNL2 autoantibodies are potential biomarkers for TNBC.
Autoantibodies ; Biomarkers ; Breast Neoplasms ; Cause of Death ; Female ; Humans ; Protein Array Analysis ; Triple Negative Breast Neoplasms*

OBJECTIVE: The aim of this study was to compare the accuracy of Bolton analysis obtained from digital models scanned with the Ortho Insight three-dimensional (3D) laser scanner system to those obtained from cone-beam computed tomography (CBCT) images and traditional plaster models. METHODS: CBCT scans and plaster models were obtained from 50 patients. Plaster models were scanned using the Ortho Insight 3D laser scanner; Bolton ratios were calculated with its software. CBCT scans were imported and analyzed using AVIZO software. Plaster models were measured with a digital caliper. Data were analyzed with descriptive statistics and the intraclass correlation coefficient (ICC). RESULTS: Anterior and overall Bolton ratios obtained by the three different modalities exhibited excellent agreement (> 0.970). The mean differences between the scanned digital models and physical models and between the CBCT images and scanned digital models for overall Bolton ratios were 0.41 +/- 0.305% and 0.45 +/- 0.456%, respectively; for anterior Bolton ratios, 0.59 +/- 0.520% and 1.01 +/- 0.780%, respectively. ICC results showed that intraexaminer error reliability was generally excellent (> 0.858 for all three diagnostic modalities), with < 1.45% discrepancy in the Bolton analysis. CONCLUSIONS: Laser scanned digital models are highly accurate compared to physical models and CBCT scans for assessing the spatial relationships of dental arches for orthodontic diagnosis.
Cone-Beam Computed Tomography ; Dental Arch ; Diagnosis ; Humans

BACKGROUND: Diet pattern of regular and three meals per day is commonly recommended. Studies investigated the health effect of gorging pattern of diet using meal frequency and meal skipping, but the health effect of meal calorie variation between three regular meals has never been investigated. In this study, maximum meal calorie variation was defined as subtraction calorie for a meal with minimum energy intake from calories for a meal with maximum energy intake between three meals and examined the effect of maximum meal calorie variation between three regular meals a day on cardiovascular risk factors. METHODS: A total of 4,680 healthy subjects aged 20-87 years who underwent medical screening examination, at one tertiary hospital health screening center and completed 24-hour dietary recall was included. Serum cholesterol subfractions, fasting glucose and blood pressure were measured. RESULTS: Maximum meal calorie variation was significantly related to serum concentration of total cholesterol (beta = 1.77; 95% confidence interval [CI], 0.36 to 3.18) and low density lipoprotein-cholesterol (LDL-C) (beta = 1.64; 95% CI, 0.37 to 2.91), body mass index (beta = 0.24; 95% CI, 0.12 to 0.37) and waist circumference (beta = 0.66; 95% CI, 0.34 to 0.98) after adjustment for potential confounders. CONCLUSION: This study suggests the notion that concentration of total cholesterol and LDL-C and obesity indices are related to maximum meal calorie variation between three meals, independently of energy intake and other confounding factors in free-living population.
Aged ; Blood Pressure ; Body Mass Index ; Cholesterol ; Diet ; Energy Intake ; Fasting ; Glucose ; Humans ; Mass Screening ; Meals ; Obesity ; Risk Factors ; Tertiary Care Centers ; Waist Circumference