Background: Manual data extraction of colonoscopy quality indicators is time and labor intensive. Natural language processing (NLP), a computer-based linguistics technique, can automate the extraction of important clinical information, such as adverse events, from unstructured free-text reports. NLP information extraction can facilitate the optimization of clinical work by helping to improve quality control and patient management. Objective: We developed an NLP pipeline to analyze free-text colonoscopy and pathology reports and evaluated its ability to automatically assess adenoma detection rate (ADR), sessile serrated lesion detection rate (SDR), and postcolonoscopy surveillance intervals. Methods: The NLP tool for extracting colonoscopy quality indicators was developed using a data set of 2000 screening colonoscopy reports from a single health care system, with an associated 1425 pathology reports. The NLP system was then tested on a data set of 1000 colonoscopy reports and its performance was compared with that of 5 human annotators. Additionally, data from 54,562 colonoscopies performed between 2010 and 2019 were analyzed using the NLP pipeline. Results: The NLP pipeline achieved an overall accuracy of 0.99-1.00 for identifying polyp subtypes, 0.99-1.00 for identifying the anatomical location of polyps, and 0.98 for counting the number of neoplastic polyps. The NLP pipeline achieved performance similar to clinical experts for assessing ADR, SDR, and surveillance intervals. NLP analysis of a 10-year colonoscopy data set identified great individual variance in colonoscopy quality indicators among 25 endoscopists. Conclusions: The NLP pipeline could accurately extract information from colonoscopy and pathology reports and demonstrated clinical efficacy for assessing ADR, SDR, and surveillance intervals in these reports. Implementation of the system enabled automated analysis and feedback on quality indicators, which could motivate endoscopists to improve the quality of their performance and improve clinical decision-making in colorectal cancer screening programs.

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of liver disease associated with various metabolic disorders. Metabolic dysfunction-associated fatty liver disease (MAFLD) emphasizes metabolic dysfunction in NAFLD. Although the relationship between NAFLD and colorectal adenomas has been suggested, the effect of MAFLD on colorectal adenoma has yet to be investigated. In this study, we examined the relationship between NAFLD/MAFLD and colorectal adenoma in comparison with other metabolic factors. Methods: Examinees who underwent colonoscopy and abdominal ultrasonography on the same day from January 2012 to December 2012 were included. NAFLD was diagnosed according to the findings of ultrasonography. The Fibrosis-4 (FIB-4) index was used as a surrogate marker for advanced hepatic fibrosis. A logistic regression model was used to analyze the risk of NAFLD/MAFLD for colorectal adenoma. Results: The prevalence of NAFLD and MAFLD was 37.5% and 32.8%, respectively. In the multivariate analysis, male sex, older age, diabetes, and smoking increased the risk of colorectal adenoma. NAFLD and MAFLD were the most important risk factors for colorectal adenoma only in females [adjusted odds ratio (OR) 1.43 and 95% confidence interval (CI) 1.01–2.03, and OR 1.55, 95% CI 1.09–2.20, respectively]. NAFLD and MAFLD with an advanced fibrosis index were significantly associated with an increased risk of colorectal adenoma. (NAFLD: OR 1.38, 95% CI, 1.04–1.83, p = 0.027; MAFLD: OR 1.45, 95% CI, 1.13–1.96, p = 0.004, respectively). Conclusion: NAFLD and MAFLD were significantly associated with a higher risk of colorectal adenomas, especially in females. NAFLD and MAFLD with advanced fibrosis were associated with an increased risk of colorectal adenoma. Colonoscopic examinations may be emphasized for patients with NAFLD/MAFLD, for women, or patients with the presence of hepatic fibrosis.

In a preliminary study we found that incubating raw ginseng in oil facilitated autolysis and extensive metabolism of ginseng, releasing flavor and lipophilic compounds into the oil so that it could be used as an ingredient for high value-added foods, while the residue could be utilized for making ginseng extract. Here, we report the effect of oil (grapeseed oil [GSO]) extract of ginseng (OEG) on body weight gain and lipid metabolism in a mouse model. OEG, but not GSO, inhibited porcine pancreatic lipase. Plasma triglyceride (TG) levels were lower in male ICR mice at 1, 2, 3, and 4 hours after oral administration of the lipid emulsion plus OEG (1 g/kg of body weight) than in the group administered only the lipid emulsion or lipid emulsion plus GSO. Next, male C57BL/6J mice were fed a standard diet, a high fat (HF) diet containing 30% lard, or diets including 30% OEG or GSO based on the standard diet for 14 weeks. Consumption of OEG-containing diet significantly lowered the body weight gain, feed efficiency, visceral fat accumulation, plasma TG, and hepatic and white epididymal adipocyte sizes, as well as expression of peroxisome proliferator-activated receptor γ (PPARγ) in liver and adipose tissue. In conclusion, dietary OEG improved obesity-related parameters in blood, liver, and adipose tissue in a mouse model and suppressed obesity induced by HF diet, possibly by regulating lipid metabolism by modulating PPARγ protein expression.

Background: To date, a 10-year follow-up study on complementary and alternative medical treatment of lumbar intervertebral disc herniation (LDH) has never been conducted. Therefore, we aimed to perform a prospective 10-year follow-up study on the integrated treatment of LDH in Korea.