Background: Hashimoto thyroiditis (HT) is suspected to correlate with papillary thyroid carcinoma (PTC) development. While some HT cases exhibit histologic features of immunoglobulin G4 (IgG4)-related disease, the relationship of HT with PTC progression remains unestablished. Methods: This cross-sectional study included 426 adult patients with PTC (≥1 cm) undergoing thyroidectomy at an academic thyroid center. HT was identified based on its typical histologic features. IgG4 and IgG immunohistochemistry were performed. Wholeslide images of immunostained slides were digitalized. Positive plasma cells per 2 mm2 were counted using QuPath and a pre-trained deep learning model. The primary outcome was tumor structural recurrence post-surgery. Results: Among the 426 PTC patients, 79 were diagnosed with HT. With a 40% IgG4 positive/IgG plasma cell ratio as the threshold for diagnosing IgG4-related disease, a cutoff value of >150 IgG4 positive plasma cells per 2 mm2 was established. According to this criterion, 53% (43/79) of HT patients were classified as IgG4-related. The IgG4-related HT subgroup presented a more advanced cancer stage than the IgG4-non-related HT group (P=0.038). The median observation period was 109 months (range, 6 to 142). Initial assessment revealed 43 recurrence cases. Recurrence-free survival periods showed significant (P=0.023) differences, with patients with IgG4 non-related HT showing the longest period, followed by patients without HT and those with IgG4-related HT. Conclusion This study effectively stratified recurrence risk in PTC patients based on HT status and IgG4-related subtypes. These findings may contribute to better-informed treatment decisions and patient care strategies.

This study aims to conduct the comparative analysis of the radiation dose according to before and after the calibration of the ionization chamber used for measuring radiation dose in the MDCT, as well as of CTDIW according to temperature and pressure correction factors in the CT room. A comparative analysis was conducted based on the measured MDCT (GE light speed plus 4 slice, USA) data using head and body CT dosimetric phantom, and Model 2026C electrometer (RADICAL 2026C, USA) calibrated on March 21, 2007. As a result, the CTDIW value which reflected calibration factors, as well as correction factors of temperature and pressure, was found to be the range of 0.479~3.162 mGy in effective radiation dose than the uncorrected values. Also, under the routine abdomen routine CT image acquisition conditions used in reference hospitals, patient effective dose was measured to indicate the difference of the maximum of 0.7 mSv between before and after the application of such factors. These results imply that the calibration of the ion chamber, and the correction of temperature and pressure of the CT room are crucial in measuring and calculating patient effective dose. Thus, to measure patient radiation dose accurately, the detailed information should be made available regarding not only the temperature and pressure of the CT room, but also the humidity and recombination factor, characteristics of X-ray beam quality, exposure conditions, scan region, and so forth.
Abdomen ; Calibration ; Head ; Humans ; Humidity ; Light ; Recombination, Genetic

Background: Studies in experimental models of allergic asthma have shown that mesenchymal stem cells (MSCs) have therapeutic potential for T-helper 2 (TH2) cell-mediated inflammation. However, the mechanisms underlying these therapeutic effects are not fully understood and their safety has not been confirmed. Methods: Using a mouse model of experimental allergic asthma, we investigated the efficacy of human adipose-derived mesenchymal stem cells (hADSCs) or human bone marrow-derived mesenchymal stem cells (hBMSCs) according to treatment frequency and timing. Results: Ovalbumin (OVA)-sensitized and -challenged mice exhibited airway hyperresponsiveness (AHR), airway inflammation, and significant increases in TH2 cytokine levels. Both double and single human mesenchymal stem cell (hMSC) treatments significantly decreased AHR and bronchoalveolar lavage fluid counts. In addition, single treatment with hMSCs showed significant attenuation of allergic airway inflammation. However, double treatment with hMSCs during OVA -sensitization and -challenge further increased inflammatory cell infiltration, and TH2 cytokine levels. Conclusion The results of treatment with hADSCs or hBMSCs suppresses AHR and airway inflammation. However, double hMSC treatment significantly induces eosinophilic airway inflammation and lung histological changes. Therefore, double hMSC treatment is ineffective against asthma and single injection frequency appears to be more important for the treatment of asthma. These results suggest that hMSC therapy can be used for treatment of asthma patients but that it should be used carefully.

Background and Objectives: Paroxysmal atrial fibrillation (AF) is a major potential cause of embolic stroke of undetermined source (ESUS). However, identifying AF remains challenging because it occurs sporadically. Deep learning could be used to identify hidden AF based on the sinus rhythm (SR) electrocardiogram (ECG). We combined known AF risk factors and developed a deep learning algorithm (DLA) for predicting AF to optimize diagnostic performance in ESUS patients. Methods: A DLA was developed to identify AF using SR 12-lead ECG with the database consisting of AF patients and non-AF patients. The accuracy of the DLA was validated in 221 ESUS patients who underwent insertable cardiac monitor (ICM) insertion to identify AF. Results: A total of 44,085 ECGs from 12,666 patient were used for developing the DLA. The internal validation of the DLA revealed 0.862 (95% confidence interval, 0.850–0.873) area under the curve (AUC) in the receiver operating curve analysis. In external validation data from 221 ESUS patients, the diagnostic accuracy of DLA and AUC were 0.811 and 0.827, respectively, and DLA outperformed conventional predictive models, including CHARGE-AF,C2HEST, and HATCH. The combined model, comprising atrial ectopic burden, left atrial diameter and the DLA, showed excellent performance in AF prediction with AUC of 0.906. Conclusions The DLA accurately identified paroxysmal AF using 12-lead SR ECG in patients with ESUS and outperformed the conventional models. The DLA model along with the traditional AF risk factors could be a useful tool to identify paroxysmal AF in ESUS patients.

Background/Aims: H2 receptor antagonists (H2RA) have been used to treat gastritis by inhibiting gastric acid. Proton pump inhibitors (PPIs) are more potent acid suppressants than H2RA.However, the efficacy and safety of low-dose PPI for treating gastritis remain unclear. The aim was to investigate the efficacy and safety of low-dose PPI for treating gastritis. Methods: A double-blind, noninferiority, multicenter, phase 3 clinical trial randomly assigned 476 patients with endoscopic erosive gastritis to a group using esomeprazole 10 mg (DW1903) daily and a group using famotidine 20 mg (DW1903R1) daily for 2 weeks. The full-analysis set included 319 patients (DW1903, n=159; DW1903R1, n=160) and the per-protocol set included 298 patients (DW1903, n=147; DW1903R1, n=151). The primary endpoint (erosion improvement rate) and secondary endpoint (erosion and edema cure rates, improvement rates of hemorrhage, erythema, and symptoms) were assessed after the treatment. Adverse events were compared. Results: According to the full-analysis set, the erosion improvement rates in the DW1903 and DW1903R1 groups were 59.8% and 58.8%, respectively. According to the per-protocol analysis, the erosion improvement rates in the DW1903 and DW1903R1 groups were 61.9% and 59.6%, respectively. Secondary endpoints were not significantly different between two groups except that the hemorrhagic improvement rate was higher in DW1903 with statistical tendency. The number of adverse events were not statistically different. Conclusions DW1903 of a low-dose PPI was not inferior to DW1903R1 of H2RA. Thus, lowdose PPI can be a novel option for treating gastritis (ClinicalTrials.gov Identifier: NCT05163756).