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Abstract This study evaluated the positive predictive value (PPV) of artificial intelligence (AI) in detecting pneumothorax on chest radiographs (CXRs) and its affecting factors. Patients determined to have pneumothorax on CXR by a commercial AI software from March to December 2021 were included retrospectively. The PPV was evaluated according to the true-positive (TP) and false-positive (FP) diagnosis determined by radiologists. To know the factors that might influence the results, logistic regression with generalized estimating equation was used. Among a total of 87,658 CXRs, 308 CXRs with 331 pneumothoraces from 283 patients were finally included. The overall PPV of AI about pneumothorax was 41.1% (TF:FP = 136:195). The PA view (odds ratio [OR], 29.837; 95% confidence interval [CI], 15.062–59.107), high abnormality score (OR, 1.081; 95% CI, 1.066–1.097), large amount of pneumothorax (OR, 1.005; 95% CI, 1.003–1.007), presence of ipsilateral atelectasis (OR, 3.508; 95% CI, 1.509–8.156) and a small amount of ipsilateral pleural effusion (OR, 5.277; 95% CI, 2.55–10.919) had significant effects on the increasing PPV. Therefore, PPV for pneumothorax diagnosis using AI can vary based on patients’ factors, image-acquisition protocols, and the presence of concurrent lesions on CXR.

Abstract This study aimed to develop a new simple and effective prognostic model using artificial intelligence (AI)-based chest radiograph (CXR) results to predict the outcomes of pneumonia. Patients aged > 18 years, admitted the treatment of pneumonia between March 2020 and August 2021 were included. We developed prognostic models, including an AI-based consolidation score in addition to the conventional CURB-65 (confusion, urea, respiratory rate, blood pressure, and age ≥ 65) and pneumonia severity index (PSI) for predicting pneumonia outcomes, defined as 30-day mortality during admission. A total of 489 patients, including 310 and 179 patients in training and test sets, were included. In the training set, the AI-based consolidation score on CXR was a significant variable for predicting the outcome (hazard ratio 1.016, 95% confidence interval [CI] 1.001–1.031). The model that combined CURB-65, initial O2 requirement, intubation, and the AI-based consolidation score showed a significantly high C-index of 0.692 (95% CI 0.628–0.757) compared to other models. In the test set, this model also demonstrated a significantly high C-index of 0.726 (95% CI 0.644–0.809) compared to the conventional CURB-65 and PSI (p

Abstract Objectives This study aimed to investigate arterial stiffness index, physical activity, and food and nutrient intake in middle-aged adults over 40 years when the incidence of cardiovascular disease begins to increase. Methods This study included 106 subjects (48 males and 58 females) aged between 40 and 64 years. The arterial stiffness index (brachial-ankle pulse wave velocity [baPWV], and ankle-brachial index [ABI]) were measured using a blood pressure pulse wave testing device. Physical activity was assessed using the Korean version of the Global Physical Activity Questionnaire, and food and nutrient intake was calculated using the Food Frequency Questionnaire. Results The mean age of the subjects was 54.4 years. Although the ABI of the subjects was within the normal range, they were divided into tertiles to compare physical activity and food and nutrient intake. In males, the time spent on moderate to vigorous physical activity (MVPA) was significantly higher in T3 (600.6 min/week) than in T1 (304.4 min/week). In females, the time spent in sedentary behavior was significantly lower in T3 (294.5 min/week) than in T1 (472.1 min/week). In addition, the frequency of fish consumption was significantly higher in T3 (1.27 frequency/day) than in T1 (0.64 frequency/day) in females. Polyunsaturated fatty acid (PUFA) and ω-3 fatty acid intake, adjusted for energy intake, were significantly positively correlated with ABI (r = 0.200 and r = 0.218, respectively). Conclusions High MVPA (in males), low sedentary behavior (in females), and PUFA and ω-3 fatty acid intake through fish consumption may be associated with low peripheral artery stiffness. Therefore, arteriosclerosis can be prevented through physical activity and proper dietary therapy.

Extracting knowledge from texts is crucial for enriching everyday knowledge. Constructing a knowledge extraction environment requires comprehensive processes, such as data generation, data processing, and model and framework design. However, these processes require significant effort in low-resource environments where shared data are not published. Currently, there is no environment that can design an entire knowledge extraction framework and perform step-by-step experiments even with unlimited resources. Thus, this study proposes a method for building a cost-effective knowledge extraction environment. In particular, we present a low-cost, high-quality method for annotating a corpus for knowledge extraction, in which data sharing is unavailable. The dataset collected using this method improves the performance of knowledge-extraction system models. Specifically, the co-reference resolution and relation extraction performance were improved by 10% and 18.9%, respectively. Additionally, the entire knowledge extraction system was evaluated using sequential multitask learning, and the performance was improved by 5% as each trained model was introduced.

Purpose: To evaluate artificial intelligence-based computer-aided diagnosis (AI-CAD) for screening mammography, we analyzed the diagnostic performance of radiologists by providing and withholding AI-CAD results alternatively every month. Methods: This retrospective study was approved by the institutional review board with a waiver for informed consent. Between August 2020 and May 2022, 1819 consecutive women (mean age 50.8 ± 9.4 years) with 2061 screening mammography and ultrasound performed on the same day in a single institution were included. Radiologists interpreted screening mammography in clinical practice with AI-CAD results being provided or withheld alternatively by month. The AI-CAD results were retrospectively obtained for analysis even when withheld from radiologists. The diagnostic performances of radiologists and stand-alone AI-CAD were compared and the performances of radiologists with and without AI-CAD assistance were also compared by cancer detection rate, recall rate, sensitivity, specificity, accuracy and area under the receiver-operating-characteristics curve (AUC). Results: Twenty-nine breast cancer patients and 1790 women without cancers were included. Diagnostic performances of the radiologists did not significantly differ with and without AI-CAD assistance. Radiologists with AI-CAD assistance showed the same sensitivity (76.5%) and similar specificity (92.3% vs 93.8%), AUC (0.844 vs 0.851), and recall rates (8.8% vs. 7.4%) compared to standalone AI-CAD. Radiologists without AI-CAD assistance showed lower specificity (91.9% vs 94.6%) and accuracy (91.5% vs 94.1%) and higher recall rates (8.6% vs 5.9%, all p

IntroductionMetabolic dysfunction-associated steatotic liver disease (MASLD) presents a growing health concern in pediatric populations due to its association with obesity and metabolic syndrome. Bioelectrical impedance analysis (BIA) offers a non-invasive and potentially effective alternative for identifying MASLD risk in youth with overweight or obesity. Therefore, this study aimed to assess the utility of BIA for screening for MASLD in the youth.MethodThis retrospective, cross-sectional study included 206 children and adolescents aged

Abstract Mammography is currently the most commonly used modality for breast cancer screening. However, its sensitivity is relatively low in women with dense breasts. Dense breast tissues show a relatively high rate of interval cancers and are at high risk for developing breast cancer. As a supplemental screening tool, ultrasonography is a widely adopted imaging modality to standard mammography, especially for dense breasts. Lately, automated breast ultrasound imaging has gained attention due to its advantages over hand-held ultrasound imaging. However, automated breast ultrasound imaging requires considerable time and effort for reading because of the lengthy data. Hence, developing a computer-aided nodule detection system for automated breast ultrasound is invaluable and impactful practically. This study proposes a three-dimensional breast nodule detection system based on a simple two-dimensional deep-learning model exploiting automated breast ultrasound. Additionally, we provide several postprocessing steps to reduce false positives. In our experiments using the in-house automated breast ultrasound datasets, a sensitivity of $$93.65\%$$ 93.65 % with 8.6 false positives is achieved on unseen test data at best.

Abstract This study evaluated how often clinically significant lung nodules were detected unexpectedly on chest radiographs (CXR) by artificial intelligence (AI)—based detection software, and whether co-existing findings can aid in differential diagnosis of lung nodules. Patients (> 18 years old) with AI-detected lung nodules at their first visit from March 2021 to February 2022, except for those in the pulmonology or thoracic surgery departments, were retrospectively included. Three radiologists categorized nodules into malignancy, active inflammation, post-inflammatory sequelae, or “other” groups. Characteristics of the nodule and abnormality scores of co-existing lung lesions were compared. Approximately 1% of patients (152/14,563) had unexpected lung nodules. Among 73 patients with follow-up exams, 69.9% had true positive nodules. Increased abnormality scores for nodules were significantly associated with malignancy (odds ratio [OR] 1.076, P = 0.001). Increased abnormality scores for consolidation (OR 1.033, P = 0.040) and pleural effusion (OR 1.025, P = 0.041) were significantly correlated with active inflammation–type nodules. Abnormality scores for fibrosis (OR 1.036, P = 0.013) and nodules (OR 0.940, P = 0.001) were significantly associated with post-inflammatory sequelae categorization. AI-based lesion-detection software of CXRs in daily practice can help identify clinically significant incidental lung nodules, and referring accompanying lung lesions may help classify the nodule.

The study determined the effect of incorporating Momordica charantia leaf powder (MCLP) into corn-starch 3D food-printing ink as a functional ingredient. The effects of the particle size (75, 131, and 200 μm) and quantity of MCLP on 3D printing performance, structural, textural, and rheological properties of corn starch gel were evaluated with different concentrations (5, 10, and 15 % (w/w)) of corn starch. The viscoelastic properties of food inks were determined considering their behavior during extrusion and self-recovery after printing. Scanning electron microscope was used to characterize the microstructure. Based on the results, a high starch content (15 %) with 5 % MCLP was more favorable for 3D food printing. In addition, 3D printing performance, textural and rheological properties of formulated ink was mainly governed by the particle size of MCLP. The food ink with a 5 % mass fraction of 200 μm MCLP had the highest printing precision and the best masticatory properties.

Abstract Mounting evidence suggests that probiotics are beneficial for treating Alzheimer’s disease (AD). However, the mechanisms by which specific probiotics modify AD pathophysiology are not clearly understood. In this study, we investigated whether Lactobacillus paracasei-derived extracellular vesicles (Lpc-EV) can directly act on neuronal cells to modify amyloid-beta (Aβ)-induced transcriptional changes and Aβ pathology in the brains of Tg-APP/PS1 mice. Lpc-EV treatment in HT22 neuronal cells counteracts Aβ-induced downregulation of Brain-derived neurotrophic factor (Bdnf), Neurotrophin 3 (Nt3), Nt4/5, and TrkB receptor, and reverses Aβ-induced altered expression of diverse nuclear factors, including the downregulation of Methyl-CpG binding protein 2 (Mecp2) and Sirtuin 1 (Sirt1). Systematic siRNA-mediated knockdown experiments indicate that the upregulation of Bdnf, Nt3, Nt4/5, and TrkB by Lpc-EV is mediated via multiple epigenetic factors whose activation converges on Mecp2 and Sirt1. In addition, Lpc-EV reverses Aβ-induced downregulation of the Aβ-degrading proteases Matrix metalloproteinase 2 (Mmp-2), Mmp-9, and Neprilysin (Nep), whose upregulation is also controlled by MeCP2 and Sirt1. Lpc-EV treatment restores the downregulated expression of Bdnf, Nt4/5, TrkB, Mmp-2, Mmp-9, and Nep; induces the upregulation of MeCP2 and Sirt1 in the hippocampus; alleviates Aβ accumulation and neuroinflammatory responses in the brain; and mitigates cognitive decline in Tg-APP/PS1 mice. These results suggest that Lpc-EV cargo contains a neuroactive component that upregulates the expression of neurotrophic factors and Aβ-degrading proteases (Mmp-2, Mmp-9, and Nep) through the upregulation of MeCP2 and Sirt1, and ameliorates Aβ pathology and cognitive deficits in Tg-APP/PS1 mice.

Abstract Whether the utilization of artificial intelligence (AI) during the interpretation of chest radiographs (CXRs) would affect the radiologists’ workload is of particular interest. Therefore, this prospective observational study aimed to observe how AI affected the reading times of radiologists in the daily interpretation of CXRs. Radiologists who agreed to have the reading times of their CXR interpretations collected from September to December 2021 were recruited. Reading time was defined as the duration in seconds from opening CXRs to transcribing the image by the same radiologist. As commercial AI software was integrated for all CXRs, the radiologists could refer to AI results for 2 months (AI-aided period). During the other 2 months, the radiologists were automatically blinded to the AI results (AI-unaided period). A total of 11 radiologists participated, and 18,680 CXRs were included. Total reading times were significantly shortened with AI use, compared to no use (13.3 s vs. 14.8 s, p

Purpose: To evaluate the stand-alone diagnostic performances of AI-CAD and outcomes of AI-CAD detected abnormalities when applied to the mammographic interpretation workflow. Methods: From January 2016 to December 2017, 6499 screening mammograms of 5228 women were collected from a single screening facility. Historic reads of three radiologists were used as radiologist interpretation. A commercially-available AI-CAD was used for analysis. One radiologist not involved in interpretation had retrospectively reviewed the abnormality features and assessed the significance (negligible vs. need recall) of the AI-CAD marks. Ground truth in terms of cancer, benign or absence of abnormality was confirmed according to histopathologic diagnosis or negative results on the next-round screen. Results: Of the 6499 mammograms, 6282 (96.7%) were in the negative, 189 (2.9%) were in the benign, and 28 (0.4%) were in the cancer group. AI-CAD detected 5 (17.9%, 5 of 28) of the 9 cancers that were intially interpreted as negative. Of the 648 AI-CAD recalls, 89.0% (577 of 648) were marks seen on examinations in the negative group, and 267 (41.2%) of the AI-CAD marks were considered to be negligible. Stand-alone AI-CAD has significantly higher recall rates (10.0% vs. 3.4%, P

Purpose This study evaluated how artificial intelligence-based computer-assisted diagnosis (AI-CAD) for breast ultrasonography (US) influences diagnostic performance and agreement between radiologists with varying experience levels in different workflows. Methods Images of 492 breast lesions (200 malignant and 292 benign masses) in 472 women taken from April 2017 to June 2018 were included. Six radiologists (three inexperienced [

Abstract Artificial intelligence (AI) applied to pediatric chest radiographs are yet scarce. This study evaluated whether AI-based software developed for adult chest radiographs can be used for pediatric chest radiographs. Pediatric patients (≤ 18 years old) who underwent chest radiographs from March to May 2021 were included retrospectively. An AI-based lesion detection software assessed the presence of nodules, consolidation, fibrosis, atelectasis, cardiomegaly, pleural effusion, pneumothorax, and pneumoperitoneum. Using the pediatric radiologist’s results as standard reference, we assessed the diagnostic performance of the software. For the total 2273 chest radiographs, the AI-based software showed a sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of 67.2%, 91.1%, 57.7%, 93.9%, and 87.5%, respectively. Age was a significant factor for incorrect results (odds radio 0.821, 95% confidence interval 0.791–0.851). When we excluded cardiomegaly and children 2 years old or younger, sensitivity, specificity, PPV, NPV and accuracy significantly increased (86.4%, 97.9%, 79.7%, 98.7% and 96.9%, respectively, all p

Abstract Background Papillary thyroid carcinoma (PTC), the most common endocrine cancer, accounts for 80–85% of all malignant thyroid tumors. This study focused on identifying targets that affect the multifocality of PTC. In a previous study, we determined 158 mRNAs related to multifocality in BRAF-mutated PTC using The Cancer Genome Atlas. Methods We used multi-omics data (miRNAs and mRNAs) to identify the regulatory mechanisms of the investigated mRNAs. miRNA inhibitors were used to determine the relationship between mRNAs and miRNAs. We analyzed the target protein levels in patient sera using ELISA and immunohistochemical staining of patients’ tissues. Results We identified 44 miRNAs that showed a negative correlation with mRNA expression. Using in vitro experiments, we identified four miRNAs that inhibit TEK and/or AXIN2 among the target mRNAs. We also showed that the downregulation of TEK and AXIN2 decreased the proliferation and migration of BRAF ( +) PTC cells. To evaluate the diagnostic ability of multifocal PTC, we examined serum TEK or AXIN2 in unifocal and multifocal PTC patients using ELISA, and showed that the serum TEK in multifocal PTC patients was higher than that in the unifocal PTC patients. The immunohistochemical study showed higher TEK and AXIN2 expression in multifocal PTC than unifocal PTC. Conclusions Both TEK and AXIN2 play a potential role in the multifocality of PTC, and serum TEK may be a diagnostic marker for multifocal PTC.

PurposeDetection of early lung cancer using chest radiograph remains challenging. We aimed to highlight the benefit of using artificial intelligence (AI) in chest radiograph with regard to its role in the unexpected detection of resectable early lung cancer.Materials and methodsPatients with pathologically proven resectable lung cancer from March 2020 to February 2022 were retrospectively analyzed. Among them, we included patients with incidentally detected resectable lung cancer. Because commercially available AI-based lesion detection software was integrated for all chest radiographs in our hospital, we reviewed the clinical process of detecting lung cancer using AI in chest radiographs.ResultsAmong the 75 patients with pathologically proven resectable lung cancer, 13 (17.3%) had incidentally discovered lung cancer with a median size of 2.6 cm. Eight patients underwent chest radiograph for the evaluation of extrapulmonary diseases, while five underwent radiograph in preparation of an operation or procedure concerning other body parts. All lesions were detected as nodules by the AI-based software, and the median abnormality score for the nodules was 78%. Eight patients (61.5%) consulted a pulmonologist promptly on the same day when the chest radiograph was taken and before they received the radiologist's official report. Total and invasive sizes of the part-solid nodules were 2.3-3.3 cm and 0.75-2.2 cm, respectively.ConclusionThis study demonstrates actual cases of unexpectedly detected resectable early lung cancer using AI-based lesion detection software. Our results suggest that AI is beneficial for incidental detection of early lung cancer in chest radiographs.

Purpose To assess experience with and perceptions of clinical application of artificial intelligence (AI) to chest radiographs among doctors in a single hospital. Materials and methods A hospital-wide online survey of the use of commercially available AI-based lesion detection software for chest radiographs was conducted with all clinicians and radiologists at our hospital in this prospective study. In our hospital, version 2 of the abovementioned software was utilized from March 2020 to February 2021 and could detect three types of lesions. Version 3 was utilized for chest radiographs by detecting nine types of lesions from March 2021. The participants of this survey answered questions on their own experience using AI-based software in daily practice. The questionnaires were composed of single choice, multiple choices, and scale bar questions. Answers were analyzed according to the clinicians and radiologists using paired t-test and the Wilcoxon rank-sum test. Results One hundred twenty-three doctors answered the survey, and 74% completed all questions. The proportion of individuals who utilized AI was higher among radiologists than clinicians (82.5% vs. 45.9%, p = 0.008). AI was perceived as being the most useful in the emergency room, and pneumothorax was considered the most valuable finding. Approximately 21% of clinicians and 16% of radiologists changed their own reading results after referring to AI, and trust levels for AI were 64.9% and 66.5%, respectively. Participants thought AI helped reduce reading times and reading requests. They answered that AI helped increase diagnostic accuracy and were more positive about AI after actual usage. Conclusion Actual adaptation of AI for daily chest radiographs received overall positive feedback from clinicians and radiologists in this hospital-wide survey. Participating doctors preferred to use AI and regarded it more favorably after actual working with the AI-based software in daily clinical practice.

Objective: To identify the clinical and sonographic risk factors for aggressive behavior of Medullary Thyroid Carcinomas (MTCs). Material and methods: This is a retrospective analysis. The informed consents were waived. Totally, 127 patients were selected from the database. Two radiologists were invited to review the clinical records and ultrasonic images and scored all the cases according to ACR TI-RADS, retrospectively. Kappa test was used to evaluate the consistency between the two reviewers. Logistic regression analysis was carried to identify the risk factors for aggressive behaviors of MTCs. Comparison of survival proportions between different groups were calculated by Kaplan–Meier method and log-rank test. Results: Female patients with MTCs were more commonly seen than male (1.7:1), male sex was a risk factor for both metastasis (OR: 4.471, P = 0.001) and perithyroidal invasion (OR = 4.674, P = 0.004). Consistency between the two reviewers were quite high (K value, 0.797–0.988). On sonograms, typical MTCs manifest as hypoechoic (96.9%) solid nodules (94.5%). Sex of patients (P = 0.001), margin (P = 0.003) and focality (P = 0.01) of the nodule were independent risk factors for metastasis, whereas sex of the patients (P = 0.004) and margin (P = 0.000) were independent risk factors for perithyroidal invasion. By Kaplan–Meier analysis, survival proportions different between groups with/without perithyroidal extension (P = 0.000) but not between groups with/without metastasis (P = 0.473). Conclusion: High frequency ultrasound and TI-RADS were effective methods for preoperative diagnosis of MTC. Sex of the patients and margin of the nodule are common risk factors for both metastasis and perithyroidal invasion. Focality of the tumor is another independent risk factor for metastasis.

Background: This study aimed to predict pathologic complete response (pCR) in neoadjuvant chemotherapy for ER+HER2- locally advanced breast cancer (LABC), a subtype with limited treatment response. Methods: We included 265 ER+HER2- LABC patients (2010–2020) with pre-treatment MRI, neoadjuvant chemotherapy, and confirmed pathology. Using data from January 2016, we divided them into training and validation cohorts. Volumes of interest (VOI) for the tumoral and peritumoral regions were segmented on preoperative MRI from three sequences: T1-weighted early and delayed contrast-enhanced sequences and T2-weighted fat-suppressed sequence (T2FS). We constructed seven machine learning models using tumoral, peritumoral, and combined texture features within and across the sequences, and evaluated their pCR prediction performance using AUC values. Results: The best single sequence model was SVM using a 1 mm tumor-to-peritumor VOI in the early contrast-enhanced phase (AUC = 0.9447). Among the combinations, the top-performing model was K-Nearest Neighbor, using 1 mm tumor-to-peritumor VOI in the early contrast-enhanced phase and 3 mm peritumoral VOI in T2FS (AUC = 0.9631). Conclusions: We suggest that a combined machine learning model that integrates tumoral and peritumoral radiomic features across different MRI sequences can provide a more accurate pretreatment pCR prediction for neoadjuvant chemotherapy in ER+HER2- LABC.

The prediction of corticosteroid responses in coronavirus disease 2019 (COVID-19) patients is crucial in clinical practice, and exploring the role of artificial intelligence (AI)-assisted analysis of chest radiographs (CXR) is warranted. This retrospective case–control study involving mild-to-moderate COVID-19 patients treated with corticosteroids was conducted from 4 September 2021, to 30 August 2022. The primary endpoint of the study was corticosteroid responsiveness, defined as the advancement of two or more of the eight-categories-ordinal scale. Serial abnormality scores for consolidation and pleural effusion on CXR were obtained using a commercial AI-based software based on days from the onset of symptoms. Amongst the 258 participants included in the analysis, 147 (57%) were male. Multivariable logistic regression analysis revealed that high pleural effusion score at 6–9 days from onset of symptoms (adjusted odds ratio of (aOR): 1.022, 95% confidence interval (CI): 1.003–1.042, p = 0.020) and consolidation scores up to 9 days from onset of symptoms (0–2 days: aOR: 1.025, 95% CI: 1.006–1.045, p = 0.010; 3–5 days: aOR: 1.03 95% CI: 1.011–1.051, p = 0.002; 6–9 days: aOR; 1.052, 95% CI: 1.015–1.089, p = 0.005) were associated with an unfavorable corticosteroid response. AI-generated scores could help intervene in the use of corticosteroids in COVID-19 patients who would not benefit from them.

The proteasome is a multi-catalytic protease complex that is involved in protein quality control via three proteolytic activities (i.e., caspase-, trypsin-, and chymotrypsin-like activities). Most cellular proteins are selectively degraded by the proteasome via ubiquitination. Moreover, the ubiquitin–proteasome system is a critical process for maintaining protein homeostasis. Here, we briefly summarize the structure of the proteasome, its regulatory mechanisms, proteins that regulate proteasome activity, and alterations to proteasome activity found in diverse diseases, chemoresistant cells, and cancer stem cells. Finally, we describe potential therapeutic modalities that use the ubiquitin–proteasome system.

This review summarizes the potential use of citrus peels in the food industry. The present work is an overview of different compounds extracted from various species of citrus peel and the functional properties of different compounds, along with their potential applications as valuable ingredients in food-based products. Citrus peel is a valuable natural source of diverse bioactive compounds, including polyphenols, pectins, proteins, pigments, dietary fibers, and essential oils. These bioactive compounds exhibit many biological activities, including antioxidant, antimicrobial, anticancer, anti-inflammatory, and antidiabetic activities. Thus, citrus peel can be considered as a promising source of functional foods. It can also be utilized as a food-coloring, flavoring, and thickening agent. Thus, waste generated in the citrus processing industry in the form of citrus peel exhibits potential economic benefits by reentering the food processing line as a food additive while providing sustainable and innovative solutions to food waste utilization.

This study aimed to investigate the clinical implications and prognostic value of artificial intelligence (AI)-based results for chest radiographs (CXR) in coronavirus disease 2019 (COVID-19) patients. Patients who were admitted due to COVID-19 from September 2021 to March 2022 were retrospectively included. A commercial AI-based software was used to assess CXR data for consolidation and pleural effusion scores. Clinical data, including laboratory results, were analyzed for possible prognostic factors. Total O2 supply period, the last SpO2 result, and deterioration were evaluated as prognostic indicators of treatment outcome. Generalized linear mixed model and regression tests were used to examine the prognostic value of CXR results. Among a total of 228 patients (mean 59.9 ± 18.8 years old), consolidation scores had a significant association with erythrocyte sedimentation rate and C-reactive protein changes, and initial consolidation scores were associated with the last SpO2 result (estimate −0.018, p = 0.024). All consolidation scores during admission showed significant association with the total O2 supply period and the last SpO2 result. Early changing degree of consolidation score showed an association with deterioration (odds ratio 1.017, 95% confidence interval 1.005–1.03). In conclusion, AI-based CXR results for consolidation have potential prognostic value for predicting treatment outcomes in COVID-19 patients.

Atopic dermatitis (AD) is a long-lasting inflammatory skin disease that contributes to the global health burden and impacts 10–20% of the world’s population. In this study, we determined the anti-AD effect of a by-product of silkworm (Bombyx mori) larval powder, strain Yeonnokjam (SLPY), as a sustainable, natural source for the development of therapeutic agents for AD. HaCaT cells were used to assess the in vitro anti-inflammatory activity of SLPY, and a 1-chloro-2,4-dinitrobenzene (DNCB)-induced mouse model was used to study the in vivo anti-AD effects. SLPY treatment downregulated the expression of the inflammatory cytokines TNF-α, IL1β, IL-8, and Cox-2 in stimulated HaCaT cells. Similarly, the topical application of SLPY in DNCB-treated mice downregulated the expression of inflammatory cytokines and proteins while ameliorating the clinical features of AD. Further, SLPY treatment inhibited the nuclear translocation of NF-κb p65, thereby supporting the efficacy of SLPY in the treatment of AD.

Purpose The purpose of this study was to evaluate the predictive performance of ultrasonography (US)-based radiomics for axillary lymph node metastasis and to compare it with that of a clinicopathologic model. Methods A total of 496 patients (mean age, 52.5±10.9 years) who underwent breast cancer surgery between January 2014 and December 2014 were included in this study. Among them, 306 patients who underwent surgery between January 2014 and August 2014 were enrolled as a training cohort, and 190 patients who underwent surgery between September 2014 and December 2014 were enrolled as a validation cohort. To predict axillary lymph node metastasis in breast cancer, we developed a preoperative clinicopathologic model using multivariable logistic regression and constructed a radiomics model using 23 radiomic features selected via least absolute shrinkage and selection operator regression. Results In the training cohort, the areas under the curve (AUC) were 0.760, 0.812, and 0.858 for the clinicopathologic, radiomics, and combined models, respectively. In the validation cohort, the AUCs were 0.708, 0.831, and 0.810, respectively. The combined model showed significantly better diagnostic performance than the clinicopathologic model. Conclusion A radiomics model based on the US features of primary breast cancers showed additional value when combined with a clinicopathologic model to predict axillary lymph node metastasis.

Abstract We aimed to predict molecular subtypes of breast cancer using radiomics signatures extracted from synthetic mammography reconstructed from digital breast tomosynthesis (DBT). A total of 365 patients with invasive breast cancer with three different molecular subtypes (luminal A + B, luminal; HER2-positive, HER2; triple-negative, TN) were assigned to the training set and temporally independent validation cohort. A total of 129 radiomics features were extracted from synthetic mammograms. The radiomics signature was built using the elastic-net approach. Clinical features included patient age, lesion size and image features assessed by radiologists. In the validation cohort, the radiomics signature yielded an AUC of 0.838, 0.556, and 0.645 for the TN, HER2 and luminal subtypes, respectively. In a multivariate analysis, the radiomics signature was the only independent predictor of the molecular subtype. The combination of the radiomics signature and clinical features showed significantly higher AUC values than clinical features only for distinguishing the TN subtype. In conclusion, the radiomics signature showed high performance for distinguishing TN breast cancer. Radiomics signatures may serve as biomarkers for TN breast cancer and may help to determine the direction of treatment for these patients.

Abstract The American Joint Committee on Cancer (AJCC) 8th TNM staging system of differentiated thyroid cancer defines gross strap muscle invasion as T3b stage. However, the impact of strap muscle invasion on disease-specific survival (DSS) remains controversial. To elucidate the survival impact of strap muscle invasion of any degree in thyroid cancers, the Surveillance, Epidemiology, and End Results (SEER) database (1973–2018) was queried for thyroid cancer only patients on July 2019 (n = 19,914). The Cox proportional hazard analysis with multivariable adjustment revealed that strap muscle invasion was not a significant factor for DSS in tumors equal to or smaller than 40 mm (hazard ratio (HR) = 1.620 [confidence interval (CI) 0.917 – 2.860]; p = 0.097). The competing risk analysis with multivariable adjustment showed that strap muscle invasion did not significantly impact DSS regardless of tumor size or cause of death (cancer-caused death (Subdistribution HR (SDHR) = 1.567 [CI 0.984 – 2.495]; p = 0.059); deaths to other causes (SDHR = 1.155 [CI 0.842 – 1.585]; p = 0.370). A “modified” staging schema discarding strap muscle invasion as a T stage criterion showed better 10-year DSS distinction between T stages. The modified staging schema may better reflect cancer-caused death risk and may prevent potential overstaging.

Purpose To investigate the correlation between magnetic resonance (MR) image-based radiomics features and the genomic features of breast cancer by focusing on biomolecular intrinsic subtypes and gene expression profiles based on risk scores. Materials and Methods We used the publicly available datasets from the Cancer Genome Atlas and the Cancer Imaging Archive to extract the radiomics features of 122 breast cancers on MR images. Furthermore, PAM50 intrinsic subtypes were classified and their risk scores were determined from gene expression profiles. The relationship between radiomics features and biomolecular characteristics was analyzed. A penalized generalized regression analysis was performed to build prediction models. Results The PAM50 subtype demonstrated a statistically significant association with the maximum 2D diameter (p = 0.0189), degree of correlation (p = 0.0386), and inverse difference moment normalized (p = 0.0337). Among risk score systems, GGI and GENE70 shared 8 correlated radiomic features (p = 0.0008–0.0492) that were statistically significant. Although the maximum 2D diameter was most significantly correlated to both score systems (p = 0.0139, and p = 0.0008), the overall degree of correlation of the prediction models was weak with the highest correlation coefficient of GENE70 being 0.2171. Conclusion Maximum 2D diameter, degree of correlation, and inverse difference moment normalized demonstrated significant relationships with the PAM50 intrinsic subtypes along with gene expression profile-based risk scores such as GENE70, despite weak correlations.

Purpose To evaluate the optimal measurement location, cut-off value, and diagnostic performance of S-Shearwave in differential diagnosis of breast masses seen on ultrasonography (US). Materials and Methods During the study period, 225 breast masses in 197 women were included. S-Shearwave measurements were made by applying a square region-of-interest automatically generated by the US machine. Shearwave elasticity was measured three times at four different locations of the mass, and the highest shearwave elasticity was used for calculating the optimal cut-off value. Diagnostic performance was evaluated by using the area under the receiving operator characteristic curve (AUC). Results Of the 225 breast masses, 156 (69.3%) were benign and 69 (30.7%) were malignant. Mean S-Shearwave values were significantly higher for malignant masses (108.0 ± 70.0 kPa vs. 43.4 ± 38.3 kPa; p < 0.001). No significant differences were seen among AUC values at different measurement locations. With a cut-off value of 41.9 kPa, S-Shearwave showed 85.7% sensitivity, 63.9% specificity, 70.7% accuracy, and positive and negative predictive values of 51.7% and 90.8%, respectively. The AUCs for US and S-Shearwave did not show significant differences (p = 0.179). Conclusion S-Shearwave shows comparable diagnostic performance to that of grayscale US that can be applied for differential diagnosis of breast masses seen on US.

Purpose The objective of this study was to evaluate the diagnostic value and threshold levels of cytokeratin fragment 21-1 (CYFRA 21-1) in fine-needle aspiration (FNA) washouts for detection of lymph node (LN) recurrence in postoperative breast cancer patients. Materials and Methods FNA cytological assessments and CYFRA 21-1 measurement in FNA washouts were performed for 64 axillary LNs suspicious for recurrence in 64 post-operative breast cancer patients. Final diagnosis was made on the basis of FNA cytology and follow-up data over at least 2 years. The concentration of CYFRA 21-1 was compared between recurrent LNs and benign LNs. Diagnostic performance and cut-off value were evaluated using a receiver operating characteristic curve. Results Regardless of the non-diagnostic results, the median concentration of CYFRA 21-1 in recurrent LNs was significantly higher than that in benign LNs (p < 0.001). The optimal diagnostic cut-off value was 1.6 ng/mL. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of CYFRA 21-1 for LN recurrence were 90.9%, 100%, 100%, 98.1%, and 98.4%, respectively. Conclusion Measurement of CYFRA 21-1 concentration from ultrasound-guided FNA biopsy aspirates showed excellent diagnostic performance with a cut-off value of 1.6 ng/mL. These results indicate that measurement of CYFRA 21-1 concentration in FNA washouts is useful for the diagnosis of axillary LN recurrence in post-operative breast cancer patients.

Purpose The purpose of this study was to compare the visibility of breast tissue markers in cases of breast cancer on ultrasonography (US) after neoadjuvant chemotherapy (NAC) and to analyze whether the type of marker affected the choice of localization method after NAC. Methods We included 153 tissue markers inserted within breast cancers that showed pathologically complete response (pCR) after NAC from January 2012 to April 2017. One of three types of markers (a surgical clip, Cormark, or UltraClip) was inserted. Medical records and imaging findings were retrospectively reviewed. We compared the visibility of the different types of tissue markers on US after NAC, and also compared the imaging modalities used in the preoperative localization. The chi-square test, Fisher exact test, and multiple logistic regression were used for analysis. Results Of the 153 tissue markers, 56 were surgical clips, 61 Cormark, and 36 UltraClip. After NAC, residual lesions were not seen on US in 42 cases (27.5%). In multivariate analysis, the visibility of the surgical clips and Cormark markers was better than that of the UltraClip markers (odds ratio [OR], 5.467; 95% confidence interal [CI], 1.717 to 17.410; P=0.004 and OR, 3.045; 95% CI, 1.074 to 8.628; P=0.036, respectively). Among the 131 cases where localization targeting the marker was required, the proportion of US-guided localizations was significantly higher when a surgical clip was used than when an UltraClip marker was used (OR, 5.566; 95% CI, 1.610 to 19.246; P=0.007) in the multivariate analysis. Conclusion The type of breast tissue marker affected its visibility on US in cases with pCR after NAC, which in turn affected the localization methodology.

Atopic dermatitis (AD) is a widely researched chronic inflammatory skin disease with a complex etiology. The increased prevalence of AD necessitates exploration of natural sources as potential therapeutic agents with limited side effects. In the current study, a 1-chloro-2,4-dinitrobenzene (DNCB)-induced AD mouse model was used to examine the anti-AD effects of Tenebrio molitor trypsin hydrolysate (TMTH) and its underlying molecular mechanism. DNCB-treated mice were treated with TMTH (1 and 10 mg/kg), and prednisolone (3 mg/kg) was used as the positive control. Serum and skin tissue samples were collected for subsequent analyses. The expression levels of proteins linked to the myeloid differentiation primary response 88 (MyD88)-dependent mitogen-activated protein kinase (MAPK) signaling pathway and serum IgE levels were estimated via Western blotting technique and ELISA (enzyme-linked immunosorbent assay), respectively. Inflammatory cell infiltration and thickening of the dorsal skin were measured using toluidine blue and hematoxylin and eosin staining, respectively. Oral administration of TMTH significantly reduced mast cell infiltration and dermal and epidermal thickness. Moreover, TMTH treatment reduced serum IgE levels. Western blotting confirmed that TMTH treatment suppressed the MyD88-dependent MAPK signaling pathway. Therefore, TMTH substantially inhibited AD-like skin lesion formation via immunomodulation, showing considerable potential for AD treatment.

Endoplasmic reticulum (ER) stress activates the unfolded protein response (UPR) signaling via the accumulation of unfolded and misfolded proteins. ER stress leads to the production of reactive oxygen species (ROS), which are necessary to maintain redox homeostasis in the ER. Although peroxiredoxin 1 (Prx1) is an antioxidant enzyme that regulates intracellular ROS levels, the link between Prx1 and ER stress remains unclear. In this study, we investigated the role of Prx1 in X-box binding protein 1 (XBP-1) activation, the C/EBP homologous protein (CHOP) pathway, and apoptosis in response to ER stress. We observed that Prx1 overexpression inhibited the nuclear localization of XBP-1 and the expression of XBP-1 target genes and CHOP after thapsigargin (Tg) treatment to induce ER stress. In addition, Prx1 inhibited apoptosis and ROS production during ER stress. The ROS scavenger inhibited ER stress-induced apoptosis but did not affect XBP-1 activation and CHOP expression. Therefore, the biological role of Prx1 in ER stress may have important implications for ER stress-related diseases.

Purpose The purpose of this study is to analyze medical audit of screening digital mammography at a tertiary hospital and to review changes of medical audit according to newly revised standard. Materials and Methods We analyzed 7764 asymptomatic women who underwent screening mammogram at our hospital from January, 2013 to December, 2014. The family or past history of breast, gynecologic and other cancers was reviewed retrospectively. Analysis 1 defined category 3 as positive result and analysis 2 defined category 3 as negative. Results The overall cancer detection rate was 4.6 per 1000 cases. The cancer detection rate in patients with non-gynecological and non-thyroid cancer (n = 391, 51.2) was the highest compared to patients with family history of breast cancer (n = 691, 1.4), or gynecological cancer (n = 311, 12.9). In analysis 1, positive predictive value 1 decreased 1.3% (6.0% vs. 7.3%) and recall rate increased 1.3% (7.3% vs. 6.0%) compared with analysis 2. The results were appropriate for newly revised target. Conclusion The results of screening digital mammography in the tertiary medical institution showed excellent results even if category 3 was regarded as positive. In addition, screening tests for secondary cancer are needed in the tertiary hospital.

This paper designs an adaptive sliding mode speed controller (ASMSC) that can compensate for parameter uncertainty of an interior permanent magnet synchronous motor (IPMSM) drive. Unlike the previous control systems, the proposed ASMSC guarantees a precise speed tracking capability in the presence of severe parameter variations without accurate knowledge on the motor parameter values and uncertainty bounds. In particular, the proposed adaptive switching gain tuning (ASGT) term can effectively solve the excessive input energy consumption problem due to an unnecessarily overestimated switching gain. Next, the convergence and stability analysis are proven through a Lyapunov function. The feasibility of the proposed approach is verified via experimental results using a prototype IPMSM test bed with a TI TMS320F28335 digital signal processor. In this paper, the proposed SMSC is investigated with two control terms: without an ASGT term and with an ASGT term. In addition, the conventional proportional-integral speed controller and conventional linear matrix inequalities based sliding mode speed controller are chosen for the performance comparison. Finally, the proposed ASMSC can assure more robust and faster speed performances against the parameter uncertainty under three dynamic load conditions.

Oat (Avena sativa) bran, a by-product during oat grain processing, is a excellent source of fibre, vitamins and phytochemicals. The health benefits of dietary fibre have long been established. In the present study, the antioxidant and hepatoprotective effects of oat bran extracts were investigated. The extracts showed strong 1,1-diphenyl-2-picryl-hydrazyl (DPPH), 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS), hydroxyl, superoxide radicals scavenging and reducing power activities in vitro. In addition, the extracts (50 mg/kg mouse) significantly reduced the levels of malondialdehyde and hepatic damage marker enzymes (aspartate transaminase and alanine transaminase), proinflammatory cytokines as well as elevated SOD, CAT, and GPx enzymes expressions in LPS-treated (1 mg/kg body weight) BALB/c mice. Therefore, the present study strongly suggests that both oat bran extracts could be excellent raw materials for manufacturing functional food due to its protective effect on hepatic liver damage and excellent antioxidant activity.

This study aimed to evaluate the effects of cinnamamides on atopic dermatitis (AD) and the mechanisms underlying these effects. To this end, the actions of two cinnamamides, (E)-3-(4-hydroxyphenyl)-N-phenylethyl acrylamide (NCT) and N-trans-coumaroyltyramine (NCPA), were determined on AD by orally administering them to mice. Oral administration of the cinnamamides ameliorated the increase in epidermal and dermal thickness as well as mast cell infiltration. Cinnamamides suppressed serum immunoglobulin (Ig) levels and expression of T-helper (Th)1/Th2 cytokines. Moreover, cinnamamides suppressed interleukin (IL)-4, which plays a crucial role in preparing naïve clusters of differentiation (CD)4+ T cells, and decreased the cervical lymph node size and weight. Interestingly, in almost all cases, NCPA exhibited higher anti-AD activity compared to NCT. These results strongly indicate that NCPA may have potential as an anti-AD agent, and further mechanistic comparative studies of NCT and NCPA are required to determine the cause of differences in biological activity.

Silicon-based electrodes are widely recognized as promising anodes for high-energy-density lithium-ion batteries (LIBs). Silicon is a representative anode material for next-generation LIBs due to its advantages of being an abundant resource and having a high theoretical capacity and a low electrochemical reduction potential. However, its huge volume change during the charge–discharge process and low electrical conductivity can be critical problems in its utilization as a practical anode material. In this study, we solved the problem of the large volume expansion of silicon anodes by using the carbon coating method with a low-cost phenolic resin that can be used to obtain high-performance LIBs. The surrounding carbon layers on the silicon surface were well made from a phenolic resin via a solvent-assisted wet coating process followed by carbonization. Consequently, the electrochemical performance of the carbon-coated silicon anode achieved a high specific capacity (3092 mA h g−1) and excellent capacity retention (~100% capacity retention after 50 cycles and even 64% capacity retention after 100 cycles at 0.05 C). This work provides a simple but effective strategy for the improvement of silicon-based anodes for high-performance LIBs.

Objective This study compared fatty acid compositions and antioxidant activities of high-preference cuts (loin, tenderloin, and rib) and low-preference cuts (brisket, topside, and shank) of Hanwoo (Bos taurus coreanae) cows to obtain potentially useful information for promoting the consumption of various low-preference cuts. Methods Individual 500 g samples of fresh beef were collected from each of the six cuts from 10 Hanwoo cows (quality grade 1) and immediately freeze-dried. The dried samples were evaluated for fatty acid composition, free radical scavenging activities (hydroxyl, alkyl, and 2, 2′-diphenyl-1-picrylhydrazyl [DPPH] radical), and antioxidative enzyme activities (glutathione peroxidase [GPx], glutathione-S-transferase [GST], and superoxide dismutase [SOD]). Results The percentages of total polyunsaturated fatty acids were significantly higher in low-preference cuts than in high-preference cuts (p

Purpose The aim of this study was to investigate the associations of Bethesda categories III, V, and VI with the clinical and pathological features of thyroid nodules surgically confirmed as conventional papillary thyroid carcinomas (PTCs). Methods We analyzed 1,990 consecutive patients diagnosed with conventional PTC at surgery with preoperative Bethesda categories III, V, or VI. We determined the odds ratio (ORs) of the clinical and pathological variables associated with categories III and V, using category VI as the reference. Results Category III and V PTCs had a smaller pathological tumor size (OR, 0.934 and OR, 0.969, respectively) and less frequently had central lymph node metastasis (OR, 0.487 and OR, 0.780, respectively) than category VI PTCs. Category III PTCs less frequently showed suspicious ultrasonographic features (OR, 0.296) than category VI PTCs, and category V PTCs less frequently had gross extrathyroidal extension, with borderline significance (OR, 0.643; P=0.059). Conclusion Conventional PTCs with a preoperative Bethesda category of III or V may less frequently exhibit poor prognostic factors than those with malignant cytology.

Background Obstructive airway disease patients with increased variability of airflow and incompletely reversible airflow obstruction are often categorized as having asthma–chronic obstructive pulmonary disease (COPD) overlap syndrome (ACOS). ACOS is heterogeneous with two sub-phenotypes: asthma-ACOS and COPD-ACOS. The objective of this study was to determine the difference in risk of exacerbation between the two sub-phenotypes of ACOS. Methods A total of 223 patients exhibiting incompletely reversible airflow obstruction with increased variability (spirometrically defined ACOS) were enrolled. These patients were divided into asthma-ACOS and COPD-ACOS according to their physician's diagnosis and smoking history of 10 pack-years. Within-group comparisons were made for asthma-ACOS versus COPD-ACOS and light smokers versus heavy smokers. Results Compared to patients with COPD-ACOS, patients with asthma-ACOS experienced exacerbation more often despite their younger age, history of light smoking, and better lung function. While the light-smoking group showed better lung function, they made unscheduled outpatient clinic visits more frequently. On multivariate analysis, asthma-ACOS and poor inhaler compliance were significantly associated with more than two unscheduled clinic visits during the previous year. Conclusion Spirometrically defined ACOS includes heterogeneous subgroups with different clinical features. Phenotyping of ACOS by physician's diagnosis could be significant in predicting future risk of exacerbation.

High expression of glucose transporter family members, which augment glucose uptake and glycolytic flux, has been shown to play a pivotal role in the proliferation and survival of tumor cells, contributing to the energy supply, biosynthesis and homeostasis of cancer cells. Among the many members, solute carrier family 2 member 1 (SLC2A1) encodes a glucose transporter, GLUT1, that is critical in the metabolism of glucose, which is an energy source for cell growth that contributes to cancer progression and development. The aim of this study was to analyze the survival and genetic changes/immune profiles in patients with gastric cancer with high SLC2A1 expression and to provide treatment for improving prognosis. This study investigated the clinicopathologic parameters, the proportion of immune cells and gene sets affecting SLC2A1 expression in 279 and 415 patients with gastric cancer from the Eulji Hospital cohort and The Cancer Genome Atlas, respectively. We assessed the response to conventional chemotherapy drugs, including fluorouracil, a compound of fluoropyrimidine S-1, oxaliplatin, and all-trans-retinoic acid (ATRA), in gastric cancer cell lines with high SLC2A1 expression. High SLC2A1 expression was associated with poor prognosis, cancer cell proliferation, decreased immune cells, including CD8 T cells and B cells, and a low prognostic nutrition index, representing body nutrition-related status. In pathway network analysis, SLC2A1 was indirectly linked to the retinoic signaling pathway and negatively regulated immune cells/receptors. In the drug response analysis, the drug ATRA inhibited gastric cancer cell lines with high SLC2A1 expression. Treatment involving the use of SLC2A1 could contribute to better clinical management/research for patients with gastric cancer.

To explore the inhibitory mechanism of heat-killed Enterococcus faecalis, EF-2001 on hepatic lipid deposition, a diet-induced obese (DIO) animal model was established by high-fat diet (HFD). The DIO C57BL/6 mice were divided into four groups: the normal group without HFD (ND, n = 8), obesity group (HFD, n = 8), experimental group (HFD + EF-2001, 200 mg/kg, n = 8), and positive control group (HFD + Orlistat, 60 mg/kg, n = 8). After 4 weeks, liver and adipose tissue were fixed in 10% paraformaldehyde, followed by embedding in paraffin for tissue sectioning. The differences in body mass, body fat ratio, fatty cell area, and lipid profiling of the liver (TC, LDL, and HDL) were also determined. Moreover, Western blot was performed to analyze the expression of lipid accumulation-related proteins, including AMPK, PPARγ, SREBP-1, ACC, and FAS. Compared with the HFD group, the HFD + EF-2001 group exhibited decreased fat mass, liver index, adipocyte area, TC, and LDL, and an increased level of HDL. The results of liver hematoxylin and eosin (H&E), and oil red O staining showed that the mice in each intervention group were improved on hepatic lipid accumulation, and the mice in the HFD + EF-2001 group were the most similar to those in the normal group when compared with the HFD group. From the Western blot results, we proved that EF-2001 activated the AMPK signaling pathway. EF-2001 significantly upregulated the expressions of p-AMPK and p-ACC and downregulated PPARγ, SREBP-1, and FAS in murine liver. Taken together, these results suggest that EF-2001 decrease lipid accumulation in the DIO model mice through the AMPK pathway and ameliorate liver damage by HFD.

Summary: Background: Mammography is the current standard for breast cancer screening. This study aimed to develop an artificial intelligence (AI) algorithm for diagnosis of breast cancer in mammography, and explore whether it could benefit radiologists by improving accuracy of diagnosis. Methods: In this retrospective study, an AI algorithm was developed and validated with 170 230 mammography examinations collected from five institutions in South Korea, the USA, and the UK, including 36 468 cancer positive confirmed by biopsy, 59 544 benign confirmed by biopsy (8827 mammograms) or follow-up imaging (50 717 mammograms), and 74 218 normal. For the multicentre, observer-blinded, reader study, 320 mammograms (160 cancer positive, 64 benign, 96 normal) were independently obtained from two institutions. 14 radiologists participated as readers and assessed each mammogram in terms of likelihood of malignancy (LOM), location of malignancy, and necessity to recall the patient, first without and then with assistance of the AI algorithm. The performance of AI and radiologists was evaluated in terms of LOM-based area under the receiver operating characteristic curve (AUROC) and recall-based sensitivity and specificity. Findings: The AI standalone performance was AUROC 0·959 (95% CI 0·952–0·966) overall, and 0·970 (0·963–0·978) in the South Korea dataset, 0·953 (0·938–0·968) in the USA dataset, and 0·938 (0·918–0·958) in the UK dataset. In the reader study, the performance level of AI was 0·940 (0·915–0·965), significantly higher than that of the radiologists without AI assistance (0·810, 95% CI 0·770–0·850; p

PURPOSE:Preoperative neck ultrasound (US) for lateral cervical lymph nodes is recommended for all patients undergoing thyroidectomy for thyroid malignancy, but it is operator dependent. We aimed to develop a radiomics signature using US images of the primary tumor to preoperatively predict lateral lymph node metastasis (LNM) in patients with conventional papillary thyroid carcinoma (cPTC). METHODS:Four hundred consecutive cPTC patients from January 2004 to February 2006 were enrolled as the training cohort, and 368 consecutive cPTC patients from March 2006 to February 2007 served as the validation cohort. A radiomics signature, which consisted of 14 selected features, was generated by the least absolute shrinkage and selection operator (LASSO) regression model in the training cohort. The discriminating performance of the radiomics signature was assessed in the validation cohort with the area under the receiver operating characteristic curve (AUC). RESULTS:The radiomics signature was significantly associated with lateral cervical lymph node status (p < 0.001). The AUC of its performance in discriminating metastatic and non-metastatic lateral cervical lymph nodes was 0.710 (95% CI: 0.649-0.770) in the training cohort and was 0.621 (95% CI: 0.560-0.682) in the validation cohort. CONCLUSIONS:The present study showed that US radiomic features of the primary tumor were associated with lateral cervical lymph node status. Although their discriminatory performance was slightly lower in the validation cohort, our study shows that US radiomic features of the primary tumor alone have the potential to predict lateral LNM.

PURPOSE:To evaluate whether if ultrasonography (US)-based radiomics enables prediction of the presence of BRAFV600E mutations among patients diagnosed as papillary thyroid carcninoma (PTC). METHODS:From December 2015 to May 2017, 527 patients who had been treated surgically for PTC were included (training: 387, validation: 140). All patients had BRAFV600E mutation analysis performed on surgical specimen. Feature extraction was performed using preoperative US images of the 527 patients (mean size of PTC: 16.4mm±7.9, range, 10-85 mm). A Radiomics Score was generated by using the least absolute shrinkage and selection operator (LASSO) regression model. Univariable/multivariable logistic regression analysis was performed to evaluate the factors including Radiomics Score in predicting BRAFV600E mutation. Subgroup analysis including conventional PTC

Rheumatoid arthritis (RA) is a chronic inflammatory polyarthritis characterized by progressive joint destruction. IL-17-producing CD4+ T (Th17) cells play pivotal roles in RA development and progression. Retinoic acid receptor-related orphan receptor alpha (RORα) is a negative regulator of inflammatory responses, whereas RORγt, another member of the ROR family, is a Th17 lineage-specific transcription factor. Here, we investigated the immunoregulatory potential of RORα in collagen-induced arthritis (CIA) mice, an experimental model of RA. Cholesterol sulfate (CS) or SR1078, a ligand of RORα, inhibited RORγt expression and Th17 differentiation in vitro. In addition, fortification of RORα in T cells inhibited the expression levels of glycolysis-associated genes. We found that RORα overexpression in CIA mice attenuated the clinical and histological severities of inflammatory arthritis. The anti-arthritic effect of RORα was associated with suppressed Th17 differentiation and attenuated mTOR-STAT3 signaling in T cells. Furthermore, altered RORα activity could directly affect osteoclastogenesis implicated in progressive bone destruction in human RA. Our findings defined a critical role of RORα in the pathogenesis of RA. These data suggest that RORα may have novel therapeutic uses in the treatment of RA.

Carvacrol (2-methyl-5-(1-methylethyl)-phenol) compound derived from oils of Thymus vulgaris is a natural member of monoterpene phenol. It has been shown that carvacrol exhibit anti-microbial, anti-inflammatory, anti-oxidant activities. However, no studies have reported its anti-melanogenesis effect. Therefore, the objective of this study was to investigate the anti-melanogenic potential of carvacrol. Results of this study confirmed that carvacrol could regulate protein expression levels of microphthalmia-associated transcription factor [MITF, a protein closely related to transcription of cAMP response element-binding protein (CREB)] and various enzymes involved in melanin synthesis. Moreover, this study provided evidence that carvacrol could regulate the degradation of MITF protein by extracellularly responsive kinases (ERK) phosphorylation. Carvacrol strongly inhibited the synthesis of CREB protein, tyrosinase-related protein 1 (TRP-1), and tyrosinase known to be important enzymes involved in melanogenesis. These results indicate that carvacrol can inhibit melanin synthase by decreasing enzyme expression levels important for melanin synthesis.

Purpose: This study identifies the effects of the educational leadership of nursing unit managers on team effectiveness and the mediating effects of organizational communication satisfaction; it highlights the importance of educational leadership and organizational communication and provides the data needed to enhance the education capacity of managers. Methods: The participants were 216 nurses working at unit with nursing unit managers of staff nurses at a tertiary hospital located in Cheongju city, South Korea, and nurses who had worked for more than 6 months at the same unit. This study was conducted using questionnaires on educational leadership, team effectiveness, and organizational communication satisfaction. Data analysis was performed with a t test, analysis of variance, Scheffé test, Pearson's correlation coefficient, and simple and multiple regression analyses using SPSS, version 23.0. Mediation analysis was tested using Baron and Kenny's regression analysis and a Sobel test. Results: The mean score for the educational leadership of nursing unit managers was 3.74 (±0.68); for organizational communication satisfaction, 3.14 (±0.51); and for team effectiveness, 3.52 (±0.49). Educational leadership was significantly positively correlated with team effectiveness and organizational communication satisfaction. Organizational communication satisfaction demonstrated a complete mediating effect on the relationship between educational leadership and team effectiveness (β = .61, p

Ultrasound (US)-guided breast biopsy has become the main method for diagnosing breast pathology, and it has a high diagnostic accuracy, approaching that of open surgical biopsy. However, methods for confirming adequate lesion retrieval after US-guided biopsy are relatively limited and false-negative results are unavoidable. Determining imaging-pathology concordance after US-guided biopsy is essential for validating the biopsy result and providing appropriate management. In this review article, we briefly present the results of US-guided breast biopsy; describe general aspects to consider when establishing imaging-pathology concordance; and review the various categories of imaging-pathology correlations and corresponding management strategies.