Impact of Diabetes on Oncologic Outcome of Colorectal Cancer Patients: Colon vs. Rectal Cancer

Background: To evaluate the impact of diabetes on outcomes in colorectal cancer patients and to examine whether this association varies by the location of tumor (colon vs. rectum). Patients and methods This study includes 4,131 stage I-III colorectal cancer patients, treated between 1995 and 2007 (12.5% diabetic, 53% colon, 47% rectal) in South Korea. Cox proportional hazards modeling was used to determine the prognostic influence of DM on survival endpoints. Results: Colorectal cancer patients with DM had significantly worse disease-free survival (DFS) [hazard ratio (HR) 1.17, 95% confidence interval (CI): 1.00–1.37] compared with patients without DM. When considering colon and rectal cancer independently, DM was significantly associated with worse overall survival (OS) (HR: 1.46, 95% CI: 1.11–1.92), DFS (HR: 1.45, 95% CI: 1.15–1.84) and recurrence-free survival (RFS) (HR: 1.32, 95% CI: 0.98–1.76) in colon cancer patients. No association for OS, DFS or RFS was observed in rectal cancer patients. There was significant interaction of location of tumor (colon vs. rectal cancer) with DM on OS (P = 0.009) and DFS (P = 0.007). Conclusions: This study suggests that DM negatively impacts survival outcomes of patients with colon cancer but not rectal cancer

Comparison of Oral Sulfate Solution and Polyethylene Glycol Plus Ascorbic Acid on the Efficacy of Bowel Preparation

Background/Aims The quality of bowel preparation is one of the quality indicators for colonoscopy. The aim of this study was to compare the efficacy of oral sulfate solution (OSS) and polyethylene glycol plus ascorbic acid (PEG-AA) for bowel preparation. Methods The study involved 167 patients who underwent diagnostic colonoscopies. Inadequate bowel preparation was defined as any score of ≤1 in each colon section based on the Boston Bowel Preparation Scale. Multivariate logistic regression was used to compare the efficacy of OSS and PEG-AA. Subgroup analyses were performed based on patient characteristics. Results Overall, 106 (63.5%) patients received OSS, and 61 (36.5%) patients received PEG-AA. The rate of inadequate bowel preparation was 12.3% in patients receiving OSS and 32.8% in patients receiving PEG-AA (p=0.001). OSS (odds ratio [OR] = 0.26; p=0.003) and morning examination (OR=0.11; p=0.038) were significantly associated with efficient bowel preparation. The efficacy of OSS compared with PEG-AA was only significant in patients ≥50 years of age vs. <50 years of age (OR=0.13; p=0.001 vs. OR=0.96; p=0.959) and female vs. male patients (OR=0.06; p=0.002 vs. OR=0.58; p=0.339). Conclusions OSS was significantly more efficient for bowel preparation than PEG-AA, especially in patients ≥50 years of age and female patients. Morning examination led to a good quality of bowel preparation, irrespective of the preparation regimen

Prevalence of Human Papilloma Virus Infections and Cervical Cytological Abnormalities among Korean Women with Systemic Lupus Erythematosus

We performed a multicenter cross-sectional study of 134 sexually active systemic lupus erythematosus (SLE) patients to investigate the prevalence of and risk factors for high risk human papilloma virus (HPV) infection and cervical cytological abnormalities among Korean women with SLE. In this multicenter cross-sectional study, HPV testing and routine cervical cytologic examination was performed. HPV was typed using a hybrid method or the polymerase chain reaction. Data on 4,595 healthy women were used for comparison. SLE patients had greater prevalence of high-risk HPV infection (24.6% vs. 7.9%, P<0.001, odds ratio 3.8, 95% confidence interval 2.5-5.7) and of abnormal cervical cytology (16.4 vs. 2.8%, P<0.001, OR 4.4, 95% CI 2.5-7.8) compared with controls. SLE itself was identified as independent risk factors for high risk HPV infection among Korean women (OR 3.8, 95% CI 2.5-5.7) along with ≥2 sexual partners (OR 8.5, 95% CI 1.2-61.6), and Pap smear abnormalities (OR 97.3, 95% CI 6.5-1,456.7). High-risk HPV infection and cervical cytological abnormalities were more common among Korean women with SLE than controls. SLE itself may be a risk factor for HPV infection among Korean women, suggesting the importance of close monitoring of HPV infections and abnormal Pap smears in SLE patients

Women with Fibromyalgia Have Lower Levels of Calcium, Magnesium, Iron and Manganese in Hair Mineral Analysis

Little is known about hair mineral status in fibromyalgia patients. This study evaluated the characteristics of hair minerals in female patients with fibromyalgia compared with a healthy reference group. Forty-four female patients diagnosed with fibromyalgia according to the American College of Rheumatology criteria were enrolled as the case group. Ageand body mass index-matched data were obtained from 122 control subjects enrolled during visit for a regular health check-up. Hair minerals were analyzed and compared between the two groups. The mean age was 43.7 yr. General characteristics were not different between the two groups. Fibromyalgia patients showed a significantly lower level of calcium (775 µg/g vs 1,093 µg/g), magnesium (52 µg/g vs 72 µg/g), iron (5.9 µg/g vs 7.1 µg/g), copper (28.3 µg/g vs 40.2 µg/g) and manganese (140 ng/g vs 190 ng/g). Calcium, magnesium, iron, and manganese were loaded in the same factor using factor analysis; the mean of this factor was significantly lower in fibromyalgia group in multivariate analysis with adjustment for potential confounders. In conclusion, the concentrations of calcium, magnesium, iron, and manganese in the hair of female patients with fibromyalgia are lower than of controls, even after adjustment of potential confounders

Federated learning for thyroid ultrasound image analysis to protect personal information: Validation study in a real health care environment

Background: Federated learning is a decentralized approach to machine learning; it is a training strategy that overcomes medical data privacy regulations and generalizes deep learning algorithms. Federated learning mitigates many systemic privacy risks by sharing only the model and parameters for training, without the need to export existing medical data sets. In this study, we performed ultrasound image analysis using federated learning to predict whether thyroid nodules were benign or malignant. Objective: The goal of this study was to evaluate whether the performance of federated learning was comparable with that of conventional deep learning. Methods: A total of 8457 (5375 malignant, 3082 benign) ultrasound images were collected from 6 institutions and used for federated learning and conventional deep learning. Five deep learning networks (VGG19, ResNet50, ResNext50, SE-ResNet50, and SE-ResNext50) were used. Using stratified random sampling, we selected 20% (1075 malignant, 616 benign) of the total images for internal validation. For external validation, we used 100 ultrasound images (50 malignant, 50 benign) from another institution Results: For internal validation, the area under the receiver operating characteristic (AUROC) curve for federated learning was between 78.88% and 87.56%, and the AUROC for conventional deep learning was between 82.61% and 91.57%. For external validation, the AUROC for federated learning was between 75.20% and 86.72%, and the AUROC curve for conventional deep learning was between 73.04% and 91.04%. Conclusions: We demonstrated that the performance of federated learning using decentralized data was comparable to that of conventional deep learning using pooled data. Federated learning might be potentially useful for analyzing medical images while protecting patients personal information. © 2021 JMIR Medical Informatics. All rights reserved.1

Bioinformatics services for analyzing massive genomic datasets

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating down-stream analysis of genome data. Bio-Express web service is freely available at https://www. bioexpress.re.kr/. ?? 2020, Korea Genome Organization

Study of Ga2\text{}_{2}O3\text{}_{3} Nanobelts Synthesized by the Thermal Annealing of GaN Powders

We synthesized the uniform monoclinic gallium oxide (Ga$\text{}_{2}$O$\text{}_{3}$) nanobelts by a simple thermal annealing of GaN powders. The as-syn-thesized nanobelts were rectangular in cross-sectional shape with width ranging from 100 to 700 nm. The length direction of the nanobelt was along [010]. Photoluminescence measurement under excitation at 325 nm showed that the Ga$\text{}_{ }$2O$\text{}_{3}$ nanobelts had a blue emission at around 454 nm