Effects of a choral program combining wind instrument performance and breathing training on respiratory function, stress, and quality of life in adolescents: A randomized controlled trial.

BACKGROUND: Choral activities are correlated with various health and wellbeing parameters. However, an intervention combining a music program using wind instruments and choral activities has not yet been investigated. Thus, this study aimed to assess the effects of a 12-week intervention combining a wind instrument performance program and a choral program on stress factors, quality of life, and respiratory function in adolescents located in a metropolitan city with exposure to air pollution. METHOD: This randomized controlled trial consisted of 50 adolescents, and the subjects were randomly assigned to a combination wind instrument and choral training group, a choral training group, and a control group. Following a 12-week intervention program, respiratory function, stress factors, and quality of life were compared between the three groups. RESULTS: Regarding respiratory function, with the exception of maximal inspiratory pressure, all measured variables exhibited an interaction to indicate a variation in the pattern of change(p<0.05). Furthermore, regarding stress factors and quality of life, all measured variables exhibited an interaction to indicate a variation in the pattern of change(p<0.05). As a result of the post-hoc analysis, significant differences were found in all variables in experimental group 1 compared to other groups (p<0.05). CONCLUSION: The results showed that the 12-week intervention combining a wind instrument performance program and a choral program had positive effects in improving the respiratory function, stress factors, and quality of life in adolescents. This study findings are expected to support future studies aimed at promoting overall health including respiratory function and psychological factors through various music-based programs.

Enhanced multi-class pathology lesion detection in gastric neoplasms using deep learning-based approach and validation.

This study developed a new convolutional neural network model to detect and classify gastric lesions as malignant, premalignant, and benign. We used 10,181 white-light endoscopy images from 2606 patients in an 8:1:1 ratio. Lesions were categorized as early gastric cancer (EGC), advanced gastric cancer (AGC), gastric dysplasia, benign gastric ulcer (BGU), benign polyp, and benign erosion. We assessed the lesion detection and classification model using six-class, cancer versus non-cancer, and neoplasm versus non-neoplasm categories, as well as T-stage estimation in cancer lesions (T1, T2-T4). The lesion detection rate was 95.22% (219/230 patients) on a per-patient basis: 100% for EGC, 97.22% for AGC, 96.49% for dysplasia, 75.00% for BGU, 97.22% for benign polyps, and 80.49% for benign erosion. The six-class category exhibited an accuracy of 73.43%, sensitivity of 80.90%, specificity of 83.32%, positive predictive value (PPV) of 73.68%, and negative predictive value (NPV) of 88.53%. The sensitivity and NPV were 78.62% and 88.57% for the cancer versus non-cancer category, and 83.26% and 89.80% for the neoplasm versus non-neoplasm category, respectively. The T stage estimation model achieved an accuracy of 85.17%, sensitivity of 88.68%, specificity of 79.81%, PPV of 87.04%, and NPV of 82.18%. The novel CNN-based model remarkably detected and classified malignant, premalignant, and benign gastric lesions and accurately estimated gastric cancer T-stages.

Towards optimal design of patient isolation units in emergency rooms to prevent airborne virus transmission: From computational fluid dynamics to data-driven modeling.

BACKGROUND: Patient isolation units (PIUs) can be an effective method for effective infection control. Computational fluid dynamics (CFD) is commonly used for PIU design; however, optimizing this design requires extensive computational resources. Our study aims to provide data-driven models to determine the PIU settings, thereby promoting a more rapid design process. METHOD: Using CFD simulations, we evaluated various PIU parameters and room conditions to assess the impact of PIU installation on ventilation and isolation. We investigated particle dispersion from coughing subjects and airflow patterns. Machine-learning models were trained using CFD simulation data to estimate the performance and identify significant parameters. RESULTS: Physical isolation alone was insufficient to prevent the dispersion of smaller particles. However, a properly installed fan filter unit (FFU) generally enhanced the effectiveness of physical isolation. Ventilation and isolation performance under various conditions were predicted with a mean absolute percentage error of within 13%. The position of the FFU was found to be the most important factor affecting the PIU performance. CONCLUSION: Data-driven modeling based on CFD simulations can expedite the PIU design process by offering predictive capabilities and clarifying important performance factors. Reducing the time required to design a PIU is critical when a rapid response is required.

Gochujang, a traditional Korean fermented food, protects through suppressed inflammatory pathways and histological structure disruption in dextran sodium sulfate (DSS)-induced colitis mice.

The mechanisms underlying chronic inflammatory diseases remain unclear. Therefore, researchers have explored the mechanisms underlying colitis using diverse materials. Recently, there has been an increasing interest in fermented products and bioconversion materials, their potential efficacy is being actively studied. Gochujang, a traditional Korean fermented product, is crafted by blending fermented Meju powder, gochu (Korean chili) powder, glutinous rice, and salt. In our study, we explored the effectiveness of Gochujang (500 mg/kg; Cheongju and Hongcheon, Korea) in dextran sulfate sodium (DSS)-induced colitis mice model. Gochujang was orally administered for 2 weeks, followed by the induction of colitis using 3% DSS in the previous week. During our investigation, Gochujang variants (TCG22-25, Cheongju and TCG22-48, Hongcheon) did not exhibit significant inhibition of weight reduction (p = 0.061) but notably (p = 0.001) suppressed the reduction in large intestine length in DSS-induced colitis mice. In the serum from colitis mice, TCG22-48 demonstrated reduced levels of the inflammatory cytokines interleukin (IL)-6 (p = 0.001) and tumor necrosis factor (TNF)-α (p = 0.001). Additionally, it inhibited the phosphorylation of Erk (p = 0.028), p38, and NF-κB (p = 0.001) the inflammatory mechanism. In our study, TCG22-25 demonstrated a reduction in the IL-6 level (p = 0.001) in serum and inhibited the phosphorylation of p38 and NF-κB (p = 0.001). Histological analysis revealed a significant (p = 0.001) reduction in the pathological score of the large intestine from TCG22-25 and TCG22-48. In conclusion, the intake of Gochujang demonstrates potent anti-inflammatory effects, mitigating colitis by preventing the large intestine length reduction of animals with colitis, lowering serum levels of TNF-α and IL-6 cytokines, and inhibiting histological disruption and inflammatory mechanism phosphorylation.

Validity Study for Clinical Use of Hand-Held Spirometer in Patients with Chronic Obstructive Pulmonary Disease.

A spirometer is a medical device frequently used clinically for the diagnosis and prediction of lung disease. This study aimed to investigate the clinical usefulness of a hand-held spirometer (The Spirokit), compared with conventional spirometry in patients with chronic obstructive pulmonary disease (COPD). This study was conducted from February 2022 to October 2022. Measurements from 80 patients with COPD (male: 53, female: 27) were obtained using The Spirokit and PC-based pulmonary function test equipment, and the resulting values were compared and analyzed. For the concurrent validity comparison of The Spirokit, the intra-class correlation (ICC 2, 1), coefficients of variation (CVME), 95% limits of agreement (95% LOA), and Cohen's Kappa Index were analyzed. The Spirokit showed high agreement (ICC: 0.929-0.989; 95% LOA: -0.525 to 2.559; and CVME: 0.05-0.08) with the PC-based pulmonary function tester. Using the Cohen's kappa coefficients, the device showed high sensitivity, specificity, and accuracy scores of Pa: 0.90, Pc: 0.52, and K: 0.79, respectively, indicating considerable agreement. The Spirokit, a portable pulmonary function test device, is a piece of equipment with high validity and portability, with high potential for replacing PC-based pulmonary function test equipment.

A multimodal virtual vision platform as a next-generation vision system for a surgical robot.

Robot-assisted surgery platforms are utilized globally thanks to their stereoscopic vision systems and enhanced functional assistance. However, the necessity of ergonomic improvement for their use by surgeons has been increased. In surgical robots, issues with chronic fatigue exist owing to the fixed posture of the conventional stereo viewer (SV) vision system. A head-mounted display was adopted to alleviate the inconvenience, and a virtual vision platform (VVP) is proposed in this study. The VVP can provide various critical data, including medical images, vital signs, and patient records, in three-dimensional virtual reality space so that users can access medical information simultaneously. An availability of the VVP was investigated based on various user evaluations by surgeons and novices, who executed the given tasks and answered questionnaires. The performances of the SV and VVP were not significantly different; however, the craniovertebral angle of the VVP was 16.35° higher on average than that of the SV. Survey results regarding the VVP were positive; participants indicated that the optimal number of displays was six, preferring the 2 × 3 array. Reflecting the tendencies, the VVP can be a neoconceptual candidate to be customized for medical use, which opens a new prospect in a next-generation surgical robot.

Platycodin D induces apoptosis via regulating MAPK pathway and promotes autophagy in colon cancer cell.

Platycodin D (PD) is the main component of triterpene saponins found in Platycodi radix. In this study, we observed a decrease in cell viability, an increase in apoptotic bodies, and an increase in the rate of apoptosis. Also, we observed an increase in cleaved PARP and Bax, a decrease in Bcl-2, and p-ERK, and an increase in p-p38 and p-JNK. Furthermore, a change in cell viability and the expression of p-p38, Bax, and Bcl-2 using the p38 inhibitor revealed a decrease in p-p38 and Bax and an increase in Bcl-2 in the inhibitor treatment group. In addition, we observed an increase in vacuole formation through morphological changes and an increase in acidic vesicular organelles (AVOs). We also observed an increase in the expression of beclin 1, LC 3-I, and -II. There was no significant decrease in cell viability in the group treated with 3-MA, but a decrease in cell viability was noted in the group treated with HCQ. HCQ treatment resulted in an increase in Bax and a decrease in Bcl-2. These findings reveal that in HT-29 colon cancer cells, PD induces apoptosis through the MAPK pathway, thereby exerting anticancer effects. Moreover, autophagy caused by PD inhibits apoptosis by protecting the cells.

Density clustering-based automatic anatomical section recognition in colonoscopy video using deep learning.

Recognizing anatomical sections during colonoscopy is crucial for diagnosing colonic diseases and generating accurate reports. While recent studies have endeavored to identify anatomical regions of the colon using deep learning, the deformable anatomical characteristics of the colon pose challenges for establishing a reliable localization system. This study presents a system utilizing 100 colonoscopy videos, combining density clustering and deep learning. Cascaded CNN models are employed to estimate the appendix orifice (AO), flexures, and "outside of the body," sequentially. Subsequently, DBSCAN algorithm is applied to identify anatomical sections. Clustering-based analysis integrates clinical knowledge and context based on the anatomical section within the model. We address challenges posed by colonoscopy images through non-informative removal preprocessing. The image data is labeled by clinicians, and the system deduces section correspondence stochastically. The model categorizes the colon into three sections: right (cecum and ascending colon), middle (transverse colon), and left (descending colon, sigmoid colon, rectum). We estimated the appearance time of anatomical boundaries with an average error of 6.31 s for AO, 9.79 s for HF, 27.69 s for SF, and 3.26 s for outside of the body. The proposed method can facilitate future advancements towards AI-based automatic reporting, offering time-saving efficacy and standardization.

Automated deep learning model for estimating intraoperative blood loss using gauze images.

The intraoperative estimated blood loss (EBL), an essential parameter for perioperative management, has been evaluated by manually weighing blood in gauze and suction bottles, a process both time-consuming and labor-intensive. As the novel EBL prediction platform, we developed an automated deep learning EBL prediction model, utilizing the patch-wise crumpled state (P-W CS) of gauze images with texture analysis. The proposed algorithm was developed using animal data obtained from a porcine experiment and validated on human intraoperative data prospectively collected from 102 laparoscopic gastric cancer surgeries. The EBL prediction model involves gauze area detection and subsequent EBL regression based on the detected areas, with each stage optimized through comparative model performance evaluations. The selected gauze detection model demonstrated a sensitivity of 96.5% and a specificity of 98.0%. Based on this detection model, the performance of EBL regression stage models was compared. Comparative evaluations revealed that our P-W CS-based model outperforms others, including one reliant on convolutional neural networks and another analyzing the gauze's overall crumpled state. The P-W CS-based model achieved a mean absolute error (MAE) of 0.25 g and a mean absolute percentage error (MAPE) of 7.26% in EBL regression. Additionally, per-patient assessment yielded an MAE of 0.58 g, indicating errors < 1 g/patient. In conclusion, our algorithm provides an objective standard and streamlined approach for EBL estimation during surgery without the need for perioperative approximation and additional tasks by humans. The robust performance of the model across varied surgical conditions emphasizes its clinical potential for real-world application.

Development and validation of an artificial intelligence algorithm for detecting vocal cords in video laryngoscopy.

Airway procedures in life-threatening situations are vital for saving lives. Video laryngoscopy (VL) is commonly performed during endotracheal intubation (ETI) in the emergency department. Artificial intelligence (AI) is widely used in the medical field, particularly to detect anatomical structures. This study aimed to develop an AI algorithm that detects vocal cords from VL images acquired during emergent situations. This retrospective study used VL images acquired in the emergency department to facilitate the ETI. The vocal cord image was labeled with a ground-truth bounding box. The dataset was divided into training and validation datasets. The algorithm was developed from a training dataset using the YOLOv4 model. The performance of the algorithm was evaluated using a test set. The test set was further divided into specific environments during the ETI for clinical subgroup analysis. In total, 20,161 images from 84 patients were used in this study. A total of 10,287, 5766, and 4108 images were used for the model training, validation, and test sets, respectively. The developed algorithm achieved F1 score 0.906, sensitivity 0.963, and specificity 0.842 in the validation set. The performance in the test set was F1 score 0.808, sensitivity 0.823, and specificity 0.804. We developed and validated an AI algorithm to detect vocal cords in VL. This algorithm demonstrated a high performance. The algorithm can be used to determine the vocal cord to ensure safe ETI.

Mask R-CNN based multiclass segmentation model for endotracheal intubation using video laryngoscope.

Objective: Endotracheal intubation (ETI) is critical to secure the airway in emergent situations. Although artificial intelligence algorithms are frequently used to analyze medical images, their application to evaluating intraoral structures based on images captured during emergent ETI remains limited. The aim of this study is to develop an artificial intelligence model for segmenting structures in the oral cavity using video laryngoscope (VL) images. Methods: From 54 VL videos, clinicians manually labeled images that include motion blur, foggy vision, blood, mucus, and vomitus. Anatomical structures of interest included the tongue, epiglottis, vocal cord, and corniculate cartilage. EfficientNet-B5 with DeepLabv3+, EffecientNet-B5 with U-Net, and Configured Mask R-Convolution Neural Network (CNN) were used; EffecientNet-B5 was pretrained on ImageNet. Dice similarity coefficient (DSC) was used to measure the segmentation performance of the model. Accuracy, recall, specificity, and F1 score were used to evaluate the model's performance in targeting the structure from the value of the intersection over union between the ground truth and prediction mask. Results: The DSC of tongue, epiglottis, vocal cord, and corniculate cartilage obtained from the EfficientNet-B5 with DeepLabv3+, EfficientNet-B5 with U-Net, and Configured Mask R-CNN model were 0.3351/0.7675/0.766/0.6539, 0.0/0.7581/0.7395/0.6906, and 0.1167/0.7677/0.7207/0.57, respectively. Furthermore, the processing speeds (frames per second) of the three models stood at 3, 24, and 32, respectively. Conclusions: The algorithm developed in this study can assist medical providers performing ETI in emergent situations.

Protaetia brevitarsis Extract Attenuates RANKL-Induced Osteoclastogenesis by Inhibiting the JNK/NF-κB/PLCγ2 Signaling Pathway.

Protaetia brevitarsis (PB)-derived bioactive substances have been used as food and medicine in many Asian countries because of their antioxidant, antidiabetic, anti-cancer, and hepatoprotective properties. However, the effect of PB extracts (PBE) on osteoclast differentiation is unclear. In this study, we investigated the effect of PBE on RANKL-induced osteoclastogenesis in mouse bone marrow-derived macrophages (BMMs). To investigate the cytotoxicity of PBE, the viability of BMMs was confirmed via MTT assay. Tartrate-resistant acid phosphatase (TRAP) staining and pit assays were performed to confirm the inhibitory effect of PBE on osteoclast differentiation and bone resorption. The expression levels of osteoclast differentiation-related genes and proteins were evaluated using quantitative real-time PCR and Western blotting. PBE attenuated osteoclastogenesis in BMMs in TRAP and pit assays without cytotoxicity. The expression levels of osteoclast marker genes and proteins induced by RANKL were decreased after PBE treatment. PBE suppressed osteoclastogenesis by inhibiting the RANKL-induced activated JNK/NF-κB/PLCγ2 signaling pathway and the expression of NFATc1 and c-Fos. Collectively, these results suggest that PBE could be a potential therapeutic strategy or functional product for osteoclast-related bone disease.

Euonymus alatus (Thunb.) Siebold leaf extract enhanced immunostimulatory effects in a cyclophosphamide-induced immunosuppressed rat model.

Background: Euonymus alatus (Thunb.) Siebold (EA) is a medicinal plant used in some Asian countries to treat various diseases, including cancer, hyperglycemia, diabetes, urticaria, dysmenorrhea, and arthritis. Owing to the wide range of pharmacological applications of EA, various roles of EA are being studied. Objective: We evaluated the immune-enhancing effect of EA treatment in a cyclophosphamide (Cy)-induced immunosuppressed rat model. Design: We analyzed the immune enhancement effect of EA on macrophages by western blotting. In addition, cell viability and natural killer (NK) cell activity were analyzed in splenocytes following EA treatment. For in vivo studies, analysis of weekly body weight, spleen weight, immune cell count, cytokine levels, and spleen histological findings was performed following EA administration in Cy-induced immunocompromised rats. Results: EA significantly increased cell viability and phospho-nuclear factor-kappa B and phospho-extracellular signal-regulated kinase protein levels in the macrophages. EA significantly increased NK cell activity in splenocytes compared with the control group. In Cy-induced immunosuppressed rats, EA administration increased spleen tissue weight and the contents of leukocytes, lymphocytes, granulocytes, intermediate cells, and plasma cytokines (tumor necrosis factor-α and interferon-γ). In addition, improvement in the damaged spleen tissue was observed. Conclusions: These findings confirm that EA exerts an immune-enhancing effect, thereby suggesting its potential as an immunostimulatory agent or functional food.

Evaluating diagnostic content of AI-generated chest radiography: A multi-center visual Turing test.

BACKGROUND: Accurate interpretation of chest radiographs requires years of medical training, and many countries face a shortage of medical professionals to meet such requirements. Recent advancements in artificial intelligence (AI) have aided diagnoses; however, their performance is often limited due to data imbalance. The aim of this study was to augment imbalanced medical data using generative adversarial networks (GANs) and evaluate the clinical quality of the generated images via a multi-center visual Turing test. METHODS: Using six chest radiograph datasets, (MIMIC, CheXPert, CXR8, JSRT, VBD, and OpenI), starGAN v2 generated chest radiographs with specific pathologies. Five board-certified radiologists from three university hospitals, each with at least five years of clinical experience, evaluated the image quality through a visual Turing test. Further evaluations were performed to investigate whether GAN augmentation enhanced the convolutional neural network (CNN) classifier performances. RESULTS: In terms of identifying GAN images as artificial, there was no significant difference in the sensitivity between radiologists and random guessing (result of radiologists: 147/275 (53.5%) vs result of random guessing: 137.5/275, (50%); p = .284). GAN augmentation enhanced CNN classifier performance by 11.7%. CONCLUSION: Radiologists effectively classified chest pathologies with synthesized radiographs, suggesting that the images contained adequate clinical information. Furthermore, GAN augmentation enhanced CNN performance, providing a bypass to overcome data imbalance in medical AI training. CNN based methods rely on the amount and quality of training data; the present study showed that GAN augmentation could effectively augment training data for medical AI.

Effects of a Senior Musical Program on the Physical Function and Cognitive Abilities of Older Women in the Community.

BACKGROUND: We aimed to investigate the effects of a community-based senior musical program on the cognitive and physical functions in older women. METHOD: Older women aged ≥65 years participating in a program at a community welfare center were randomized to experimental (n = 17) or control (n = 17) groups. The control group participated in singing and yoga classes offered at the welfare center, while the experimental group participated in a senior musical program consisting of vocal training, dancing, and breathing training. The effects of the 12-week program (120 min/session, two sessions/week) and the intergroup differences in outcomes were compared using the cognitive impairment screening test (CIST), pulmonary function test (PFT), respiratory muscle pressure test (RPT), and static and dynamic balance tests. RESULT: The experimental group showed significant post-intervention changes in CIST scores, cardiorespiratory parameters, and static and dynamic balance (p < 0.05), but the control group only showed significant changes in some respiratory and balance parameters (p < 0.05). In comparison with the control group, the experimental group showed significantly greater post-intervention changes in the CIST score, PFT and RPT parameters, static balance, and Y-balance anterior (p < 0.05). CONCLUSIONS: The senior musical program enhanced older women's cognitive, respiratory, and physical functions and promoted a sense of accomplishment and self-satisfaction.

Chrysin Induces Apoptosis via the MAPK Pathway and Regulates ERK/mTOR-Mediated Autophagy in MC-3 Cells.

Chrysin is a flavonoid found abundantly in substances, such as honey and phytochemicals, and is known to exhibit anticancer effects against various cancer cells. Nevertheless, the anticancer effect of chrysin against oral cancer has not yet been verified. Furthermore, the mechanism underlying autophagy is yet to be clearly elucidated. Thus, this study investigated chrysin-mediated apoptosis and autophagy in human mucoepidermoid carcinoma (MC-3) cells. The change in MC-3 cell viability was examined using a 3-(4,5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide cell viability assay, as well as 40,6-diamidino-2-phenylindole, annexin V, and propidium iodide staining. Western blotting was used to analyze the proteins related to apoptosis and the mitogen-activated protein kinase (MAPK) pathway. In addition, the presence or absence of autophagy and changes in the expression of related proteins were investigated using acridine orange staining and Western blot. The results suggested that chrysin induced apoptosis and autophagy in MC-3 oral cancer cells via the MAPK/extracellular signal-regulated kinase pathway. Moreover, the induced autophagy exerted a cytoprotective effect against apoptosis. Thus, the further reduced cell viability due to autophagy as well as apoptosis induction highlight therapeutic potential of chrysin for oral cancer.

Field evaluation of the safety and immunogenicity of a classical swine fever virus E2 subunit vaccine in breeding and nursery animals on Jeju Island, South Korea.

Purpose: Classical swine fever (CSF) reemerged on CSF-free Jeju Island where vaccination is not practiced by the unintentional injection of a live attenuated vaccine (modified live attenuated vaccines-low-virulence Miyagi [MLV-LOM]) in 2014. Since the Jeju provincial authority is considering adopting a voluntary immunization policy using a CSF-E2 subunit vaccine to combat LOM-derived CSF endemic, this study aimed to evaluate in Jeju herds. Materials and Methods: Two vaccination trials using the Bayovac CSF-E2 vaccine licensed for use in South Korea assessed the safety and humoral immunity of the CSF-E2 vaccine in breeding (trial 1) and nursery animals (trial 2) under farm application conditions. Results: Neither local nor systemic (including reproductive) adverse effects were objectively observed in pregnant sows and young piglets following a respective vaccination regime at pregnancy or weaning, respectively. Trial 1 showed that sows immunized with the CSF-E2 vaccine possessed high and consistent E2-specific and neutralizing antibody levels. The CSF-E2 vaccine-immunized pregnant sows subsequently conferred appropriate and steady passive immunity to their offspring. In trial 2, a double immunization scheme of the CSF-E2 vaccine in piglets at 40 and 60 days of age could elicit a consistent and long-lasting adequate antibody response. Additionally, the two trials detected no Erns-specific antibody responses, indicating that CSF-E2 vaccine can differentiate infected from vaccinated animals (DIVA). Conclusion: Our trial data collectively provide invaluable information on applying the CSF-E2 subunit vaccine to circumvent the possible drawbacks associated with the MLV-LOM concerning the safety, efficacy, and DIVA, in the LOM-endemic field farms and contribute to advanced CSF eradication on Jeju Island.

Myricetin induces apoptosis through the MAPK pathway and regulates JNK­mediated autophagy in SK­BR­3 cells.

Myricetin, a flavonoid found in fruits and vegetables, is known to have antioxidant and anticancer effects. However, the anticancer effects of myricetin on SK­BR­3 human breast cancer cells have not been elucidated. In the present study, the anticancer effects of myricetin were confirmed in human breast cancer SK­BR­3 cells. As the concentration of myricetin increased, the cell viability decreased. DAPI (4',6­diamidino­2­phenylindole) and Annexin V/PI staining also revealed a significant increase in apoptotic bodies and apoptosis. Western blot analysis was performed to confirm the myricetin­induced expression of apoptosis­related proteins. The levels of cleaved PARP and Bax proteins were increased, and that of Bcl­2 was decreased. The levels of proteins in the mitogen­activated protein kinase (MAPK) pathway were examined to confirm the mechanism of myricetin­induced apoptosis, and it was found that the expression levels of phosphorylated c­Jun N­terminal kinase (p­JNK) and phosphorylated mitogen­activated protein kinases (p­p38) were increased, whereas that of phosphorylated extracellular­regulated kinase (p­ERK) was decreased. It was also demonstrated that myricetin induced autophagy by promoting autophagy­related proteins such as microtubule­associated protein 1A/1B­light chain 3 (LC 3) and beclin 1. In addition, 3­methyladenine (3­MA) was used to evaluate the association between cell viability and autophagy in cells treated with myricetin. The results showed that simultaneous treatment with 3­MA and myricetin promoted the apoptosis of breast cancer cells. Furthermore, treatment with a JNK inhibitor reduced cell viability, promoted Bax expression, and reduced the expression of p­JNK, Bcl­2, and LC 3­II/I. These results suggest that myricetin induces apoptosis via the MAPK pathway and regulates JNK­mediated autophagy in SK­BR­3 cells. In conclusion, myricetin shows potential as a natural anticancer agent in SK­BR­3 cells.

Colonoscopic image synthesis with generative adversarial network for enhanced detection of sessile serrated lesions using convolutional neural network.

Computer-aided detection (CADe) systems have been actively researched for polyp detection in colonoscopy. To be an effective system, it is important to detect additional polyps that may be easily missed by endoscopists. Sessile serrated lesions (SSLs) are a precursor to colorectal cancer with a relatively higher miss rate, owing to their flat and subtle morphology. Colonoscopy CADe systems could help endoscopists; however, the current systems exhibit a very low performance for detecting SSLs. We propose a polyp detection system that reflects the morphological characteristics of SSLs to detect unrecognized or easily missed polyps. To develop a well-trained system with imbalanced polyp data, a generative adversarial network (GAN) was used to synthesize high-resolution whole endoscopic images, including SSL. Quantitative and qualitative evaluations on GAN-synthesized images ensure that synthetic images are realistic and include SSL endoscopic features. Moreover, traditional augmentation methods were used to compare the efficacy of the GAN augmentation method. The CADe system augmented with GAN synthesized images showed a 17.5% improvement in sensitivity on SSLs. Consequently, we verified the potential of the GAN to synthesize high-resolution images with endoscopic features and the proposed system was found to be effective in detecting easily missed polyps during a colonoscopy.

Anti-Biofilm Effects of Torilis japonica Ethanol Extracts against Staphylococcus aureus.

The spread of antibiotic-resistant strains of Staphylococcus aureus, a gram-positive opportunistic pathogen, has increased due to the frequent use of antibiotics. Inhibition of the quorum-sensing systems of biofilm-producing strains using plant extracts represents an efficient approach for controlling infections. Torilis japonica is a medicinal herb showing various bioactivities; however, no studies have reported the anti-biofilm effects of T. japonica extracts against drug-resistant S. aureus. In this study, we evaluated the inhibitory effects of T. japonica ethanol extract (TJE) on biofilm production in methicillin-sensitive S. aureus (MSSA) KCTC 1927, methicillin-resistant S. aureus (MRSA) KCCM 40510, and MRSA KCCM 40511. Biofilm assays showed that TJE could inhibit biofilm formation in all strains. Furthermore, the hemolysis of sheep blood was found to be reduced when the strains were treated with TJE. The mRNA expression of agrA, sarA, icaA, hla, and RNAIII was evaluated using reverse transcription-polymerase chain reaction to determine the effect of TJE on the regulation of genes encoding quorum sensing-related virulence factors in MSSA and MRSA. The expression of hla reduced in a concentration-dependent manner upon treatment with TJE. Moreover, the expression levels of other genes were significantly reduced compared to those in the control group. In conclusion, TJE can suppress biofilm formation and virulence factor-related gene expression in MSSA and MRSA strains. The extract may therefore be used to develop treatments for infections caused by antibiotic-resistant S. aureus.