Background/Aims: Previous studies have revealed that glucagon-like peptide-1 receptor agonist (GLP-1RA) and thiazolidinedione (TZD) can improve nonalcoholic fatty liver disease (NAFLD) or nonalcoholic steatohepatitis (NASH). However, comprehensive research comparing the effects of GLP-1RA and TZD is limited. Thus, this study aimed to compare the effects of GLP-1RA and TZD on NAFLD or NASH through a network meta-analysis.Methods: The PubMed, Embase, Web of Science, and Scopus databases were searched for randomized controlled trials (RCTs) that explored the efficacy of GLP-1RAs or TZDs in adult patients with NAFLD or NASH. The outcomes were liver biopsy-based (NAFLD activity score [NAS], fibrosis stage, and NASH resolution), noninvasive technique-based (liver fat content on proton magnetic resonance spectroscopy [1H-MRS] and controlled attenuation parameter [CAP]), biological, and anthropometric indicators. A random effects model was used to calculate the mean difference (MD) and relative risk with 95% confidence interval (CI).Results: Twenty-five RCTs with 2,237 overweight or obese patients were included. GLP-1RA was significantly superior in reducing liver fat content evaluated using 1H-MRS (MD –2.42, 95% CI –3.84 to –1.00), body mass index (MD –1.60, 95% CI –2.41 to –0.80), and waist circumference (MD –4.89, 95% CI –8.17 to –1.61) than TZD. In liver biopsy-based evaluation and liver fat content assessment using CAP, GLP-1RA tended to surpass TZD, albeit not significantly. Sensitivity analysis showed consistent results with the main results.Conclusions: Compared with TZD, GLP-1RA had better effects on liver fat content, body mass index, and waist circumference in overweight or obese patients with NAFLD or NASH.

Garlic-related misinformation is prevalent whenever a virus outbreak occurs. With the outbreak of COVID-19, garlic-related misinformation is spreading through social media, including Twitter. Bidirectional Encoder Representations from Transformers (BERT) can be used to classify misinformation from a vast number of tweets. This study aimed to apply the BERT model for classifying misinformation on garlic and COVID-19 on Twitter, using 5929 original tweets mentioning garlic and COVID-19 (4151 for fine-tuning, 1778 for test). Tweets were manually labeled as ‘misinformation’ and ‘other.’ We fine-tuned five BERT models (BERT_BASE, BERT_LARGE, BERTweet-base, BERTweet-COVID-19, and BERTweet-large) using a general COVID-19 rumor dataset or a garlic-specific dataset. Accuracy and F1 score were calculated to evaluate the performance of the models. The BERT models fine-tuned with the COVID-19 rumor dataset showed poor performance, with maximum accuracy of 0.647. BERT models fine-tuned with the garlic-specific dataset showed better performance. BERTweet models achieved accuracy of 0.897–0.911, while BERT_BASE and BERT_LARGE achieved accuracy of 0.887–0.897. BERTweet-large showed the best performance with maximum accuracy of 0.911 and an F1 score of 0.894. Thus, BERT models showed good performance in classifying misinformation. The results of our study will help detect misinformation related to garlic and COVID-19 on Twitter.

Lee SW, et al. Allergy Asthma Immunol Res. 2023 Mar;15(2):231-245. https://doi.org/10.4168/aair.2023.15.2.231

Purpose: Asthma can cause a systemic inflammatory response, and anemia of chronic disease (ACD) is known to be caused by other disorders with a chronic inflammatory state. However, it is unclear whether the incidence of anemia is increased in patients with asthma. The objective of this study was to compare the incidence of anemia in patients with asthma and healthy adults. Patients and Methods: This retrospective cohort study included patients newly diagnosed with asthma at Seoul National University Hospital from 2010 to 2017. Patients with comorbidities before the first visit (index date) that may increase anemia risk were excluded. Cox regression models adjusting for patient age, sex, and obesity were used to compare anemia hazard ratios (HRs) between asthma patients (n=1354) and healthy adults (n=1731). Results: This study included 3085 patients. During 5-y follow-up, anemia occurred in 203 (15.0%) patients with asthma and 79 (4.6%) healthy adults. Compared with healthy adults, the HR for anemia after adjusting for age, sex, and obesity was 4.06 (95% CI: 2.70– 6.09) in patients with asthma. In patients aged 18– 64.9 y, the adjusted HR of anemia was 3.27 (95% CI: 2.12– 5.04) in patients with asthma, compared to healthy patients. In patients > 65 y, this adjusted HR was 5.56 (95% CI: 1.31– 23.67). Conclusion: The risk of anemia was increased in patients with asthma after adjusting for sex, age, and obesity and excluding comorbidities that can cause anemia. These results suggest the need for regular monitoring for anemia in patients with asthma.