Stabilization of liquid instabilities with ionized gas jets.

Impinging gas jets can induce depressions in liquid surfaces, a phenomenon familiar to anyone who has observed the cavity produced by blowing air through a straw directly above a cup of juice. A dimple-like stable cavity on a liquid surface forms owing to the balance of forces among the gas jet impingement, gravity and surface tension1,2. With increasing gas jet speed, the cavity becomes unstable and shows oscillatory motion, bubbling (Rayleigh instability) and splashing (Kelvin-Helmholtz instability)3,4. However, despite its scientific and practical importance-particularly in regard to reducing cavity instability growth in certain gas-blown systems-little attention has been given to the hydrodynamic stability of a cavity in such gas-liquid systems so far. Here we demonstrate the stabilization of such instabilities by weakly ionized gas for the case of a gas jet impinging on water, based on shadowgraph experiments and computational two-phase fluid and plasma modelling. We focus on the interfacial dynamics relevant to electrohydrodynamic (EHD) gas flow, so-called electric wind, which is induced by the momentum transfer from accelerated charged particles to neutral gas under an electric field. A weakly ionized gas jet consisting of periodic pulsed ionization waves5, called plasma bullets, exerts more force via electrohydrodynamic flow on the water surface than a neutral gas jet alone, resulting in cavity expansion without destabilization. Furthermore, both the bidirectional electrohydrodynamic gas flow and electric field parallel to the gas-water interface produced by plasma interacting 'in the cavity' render the surface more stable. This case study demonstrates the dynamics of liquids subjected to a plasma-induced force, offering insights into physical processes and revealing an interdependence between weakly ionized gases and deformable dielectric matter, including plasma-liquid systems.

Knockdown of TWIST1 enhances arsenic trioxide- and ionizing radiation-induced cell death in lung cancer cells by promoting mitochondrial dysfunction.

TWIST1 is implicated in the process of epithelial mesenchymal transition, metastasis, stemness, and drug resistance in cancer cells, and therefore is a potential target for cancer therapy. In the present study, we found that knockdown of TWIST1 by small interfering RNA (siRNA) enhanced arsenic trioxide (ATO)- and ionizing radiation (IR)-induced cell death in non-small-cell lung cancer cells. Interestingly, intracellular reactive oxygen species levels were increased in cells treated with TWIST1 siRNA and further increased by co-treatment with ATO or IR. Pretreatment of lung cancer cells with the antioxidant N-acetyl-cysteine markedly suppressed the cell death induced by combined treatment with TWIST1 siRNA and ATO or IR. Moreover, treatment of cells with TWIST1 siRNA induced mitochondrial membrane depolarization and significantly increased mitochondrial fragmentation (fission) and upregulated the fission-related proteins FIS1 and DRP1. Collectively, our results demonstrate that siRNA-mediated TWIST1 knockdown induces mitochondrial dysfunction and enhances IR- and ATO-induced cell death in lung cancer cells.

Design and performance evaluation of a distributed OFDMA-based MAC protocol for MANETs.

In this paper, we propose a distributed MAC protocol for OFDMA-based wireless mobile ad hoc multihop networks, in which the resource reservation and data transmission procedures are operated in a distributed manner. A frame format is designed considering the characteristics of OFDMA that each node can transmit or receive data to or from multiple nodes simultaneously. Under this frame structure, we propose a distributed resource management method including network state estimation and resource reservation processes. We categorize five types of logical errors according to their root causes and show that two of the logical errors are inevitable while three of them are avoided under the proposed distributed MAC protocol. In addition, we provide a systematic method to determine the advertisement period of each node by presenting a clear relation between the accuracy of estimated network states and the signaling overhead. We evaluate the performance of the proposed protocol in respect of the reservation success rate and the success rate of data transmission. Since our method focuses on avoiding logical errors, it could be easily placed on top of the other resource allocation methods focusing on the physical layer issues of the resource management problem and interworked with them.

Innovative food-upcycling solutions: Comparative analysis of edible films from kimchi-extracted cellulose, sorbitol, and citric acid for food packaging applications.

In this study, kimchi-extracted cellulose was utilized to fabricate edible films using a hot synthetic approach, followed by solvent casting, and employing sorbitol and citric acid as the plasticizer and crosslinker, respectively. The chemical, optical, physical, and thermal properties of these films were explored to provide a comparative assessment of their suitability for various packaging applications. Chemical analyses confirmed that the kimchi-extracted cellulose comprised cellulose Iß and amorphous cellulose and did not contain any impurities. Optical analyses revealed that kimchi-extracted cellulose-containing films exhibited better-dispersed surfaces than films fabricated from commercial cellulose. Physical property analyses indicated their hydrophilic characteristics with contact angles <20°. In the thermal analysis, similar Tg results confirmed the comparable thermal stability between films containing commercial microcrystalline cellulose-containing films and kimchi-extracted cellulose-containing films. Edible films produced from kimchi-extracted cellulose through food-upcycling approaches are therefore promising for applications as packaging materials.

Preparation of food active packaging materials based on calcium hydroxide and modified porous medium for reducing carbon dioxide and kimchi odor.

Carbon dioxide and kimchi odor compounds, formed during fermentation, negatively affect the long-distance distribution of commercial kimchi. To address these issues, in this study, we modified different porous media (activated carbon, bleaching earth, diatomite, and zeolite) using sodium bicarbonate and silver (Ag) ions. Functional sheets were prepared using linear low-density polyethylene, calcium hydroxide, a porous medium, and a blowing agent. Various prepared porous media and sheets were effective in removing acetic acid, sulfur compounds (allyl methyl sulfide, dimethyl disulfide, allyl methyl disulfide, and diallyl disulfide), and carbon dioxide. Porous media with micropores exhibited a sulfur compound removal efficiency of 43.5%-99.4%, while no effect was observed on acetic acid removal. However, porous media with mesopores showed an acetic acid removal efficiency of 42.3%-90.7%, with no reduction in sulfur compounds removal. The impregnation of porous materials with sodium bicarbonate significantly (p < 0.05) enhanced the acetic acid removal activity. Ag modification improved the sulfur compound removal of the mesoporous bleaching earth and diatomite statistically (p < 0.05). Additionally, the incorporation of sodium bicarbonate-impregnated mesoporous media significantly improved carbon dioxide removal, reducing concentrations from 25.97% to 14.27% with respect to the control group. Our functional food packaging materials can solve the current issues in kimchi distribution by removing carbon dioxide and kimchi odor without affecting its quality. PRACTICAL APPLICATION: Food active packaging materials containing calcium hydroxide and modified porous medium are effective in removing carbon dioxide and kimchi odor (acetic acid and sulfur compounds). The removal of carbon dioxide and kimchi odor, which adversely affect the distribution and sale of commercial kimchi, can help solve the current issues with kimchi distribution without affecting its quality.

Prediction of final pathology depending on preoperative myometrial invasion and grade assessment in low-risk endometrial cancer patients: A Korean Gynecologic Oncology Group ancillary study.

OBJECTIVES: Fertility-sparing treatment (FST) might be considered an option for reproductive patients with low-risk endometrial cancer (EC). On the other hand, the matching rates between preoperative assessment and postoperative pathology in low-risk EC patients are not high enough. We aimed to predict the postoperative pathology depending on preoperative myometrial invasion (MI) and grade in low-risk EC patients to help extend the current criteria for FST. METHODS/MATERIALS: This ancillary study (KGOG 2015S) of Korean Gynecologic Oncology Group 2015, a prospective, multicenter study included patients with no MI or MI <1/2 on preoperative MRI and endometrioid adenocarcinoma and grade 1 or 2 on endometrial biopsy. Among the eligible patients, Groups 1-4 were defined with no MI and grade 1, no MI and grade 2, MI <1/2 and grade 1, and MI <1/2 and grade 2, respectively. New prediction models using machine learning were developed. RESULTS: Among 251 eligible patients, Groups 1-4 included 106, 41, 74, and 30 patients, respectively. The new prediction models showed superior prediction values to those from conventional analysis. In the new prediction models, the best NPV, sensitivity, and AUC of preoperative each group to predict postoperative each group were as follows: 87.2%, 71.6%, and 0.732 (Group 1); 97.6%, 78.6%, and 0.656 (Group 2); 71.3%, 78.6% and 0.588 (Group 3); 91.8%, 64.9%, and 0.676% (Group 4). CONCLUSIONS: In low-risk EC patients, the prediction of postoperative pathology was ineffective, but the new prediction models provided a better prediction.

Development of a calcium hydroxide-dye kimchi ripening indicator and its application in kimchi packaging.

Intelligent packaging that provides real-time information on food quality is useful for consumers. We developed a kimchi ripening indicator that can determine the ripeness of kimchi inside packaging and evaluated its applicability and limitations. The indicator was made using calcium hydroxide, which captures CO2, and four pH-sensitive dyes (cresol red, bromothymol blue, bromocresol purple, and methyl red). Fourier-transform infrared spectra of the prepared powders showed shapes similar to that of calcium hydroxide, and the dyes were evenly distributed on the calcium hydroxide surfaces. When the developed indicators were evaluated for kimchi packaging application, the indicator made from synthesized calcium hydroxide and bromothymol blue was the most reliable and clearly reflected useful kimchi ripening information. The indicator developed in this study is judged to be practically usable at temperatures of 4-15 °C. However, its usefulness is limited in that the seller cannot change the packaging capacity or kimchi capacity.

Machine learning approaches that use clinical, laboratory, and electrocardiogram data enhance the prediction of obstructive coronary artery disease.

Pretest probability (PTP) for assessing obstructive coronary artery disease (ObCAD) was updated to reduce overestimation. However, standard laboratory findings and electrocardiogram (ECG) raw data as first-line tests have not been evaluated for integration into the PTP estimation. Therefore, this study developed an ensemble model by adopting machine learning (ML) and deep learning (DL) algorithms with clinical, laboratory, and ECG data for the assessment of ObCAD. Data were extracted from the electronic medical records of patients with suspected ObCAD who underwent coronary angiography. With the ML algorithm, 27 clinical and laboratory data were included to identify ObCAD, whereas ECG waveform data were utilized with the DL algorithm. The ensemble method combined the clinical-laboratory and ECG models. We included 7907 patients between 2008 and 2020. The clinical and laboratory model showed an area under the curve (AUC) of 0.747; the ECG model had an AUC of 0.685. The ensemble model demonstrated the highest AUC of 0.767. The sensitivity, specificity, and F1 score of the ensemble model ObCAD were 0.761, 0.625, and 0.696, respectively. It demonstrated good performance and superior prediction over traditional PTP models. This may facilitate personalized decisions for ObCAD assessment and reduce PTP overestimation.

Machine learning model for predicting ciprofloxacin resistance and presence of ESBL in patients with UTI in the ED.

Increasing antimicrobial resistance in uropathogens is a clinical challenge to emergency physicians as antibiotics should be selected before an infecting pathogen or its antibiotic resistance profile is confirmed. We created a predictive model for antibiotic resistance of uropathogens, using machine learning (ML) algorithms. This single-center retrospective study evaluated patients diagnosed with urinary tract infection (UTI) in the emergency department (ED) between January 2020 and June 2021. Thirty-nine variables were used to train the model to predict resistance to ciprofloxacin and the presence of urinary pathogens' extended-spectrum beta-lactamases. The model was built with Gradient-Boosted Decision Tree (GBDT) with performance evaluation. Also, we visualized feature importance using SHapely Additive exPlanations. After two-step customization of threshold adjustment and feature selection, the final model was compared with that of the original prescribers in the emergency department (ED) according to the ineffectiveness of the antibiotic selected. The probability of using ineffective antibiotics in the ED was significantly lowered by 20% in our GBDT model through customization of the decision threshold. Moreover, we could narrow the number of predictors down to twenty and five variables with high importance while maintaining similar model performance. An ML model is potentially useful for predicting antibiotic resistance improving the effectiveness of empirical antimicrobial treatment in patients with UTI in the ED. The model could be a point-of-care decision support tool to guide clinicians toward individualized antibiotic prescriptions.

Convolutional neural network-based respiration analysis of electrical activities of the diaphragm.

The electrical activity of the diaphragm (Edi) is considered a new respiratory vital sign for monitoring breathing patterns and efforts during ventilator care. However, the Edi signal contains irregular noise from complex causes, which makes reliable breathing analysis difficult. Deep learning was implemented to accurately detect the Edi signal peaks and analyze actual neural breathing in premature infants. Edi signals were collected from 17 premature infants born before gestational age less than 32 weeks, who received ventilatory support with a non-invasive neurally adjusted ventilatory assist. First, a local maximal detection method that over-detects candidate Edi peaks was used. Subsequently, a convolutional neural network-based deep learning was implemented to classify candidates into final Edi peaks. Our approach showed superior performance in all aspects of respiratory Edi peak detection and neural breathing analysis compared with the currently used recording technique in the ventilator. The method obtained a f1-score of 0.956 for the Edi peak detection performance and [Formula: see text] value of 0.823 for respiratory rates based on the number of Edi peaks. The proposed technique can achieve a more reliable analysis of Edi signals, including evaluation of the respiration rate in premature infants.

Improvement of osseointegration efficacy of titanium implant through plasma surface treatment.

A novel plasma treatment source for generating cylindrical plasma on the surface of titanium dental implants is developed herein. Using the titanium implant as an electrode and the packaging wall as a dielectric barrier, a dielectric barrier discharge (DBD) plasma was generated, allowing the implant to remain sterile. Numerical and experimental investigations were conducted to determine the optimal discharge conditions for eliminating hydrocarbon impurities, which are known to degrade the bioactivity of the implant. XPS measurement confirmed that plasma treatment reduced the amount of carbon impurities on the implant surface by approximately 60%. Additionally, in vitro experiments demonstrated that the surface treatment significantly improved cell adhesion, proliferation, and differentiation. Collectively, we proposed a plasma treatment source for dental implants that successfully removes carbon impurities and facilitate the osseointegration of SLA implants.

Deodorization films based on polyphenol compound-rich natural deodorants and polycaprolactone for removing volatile sulfur compounds from kimchi.

As natural polyphenols have been known to have the deodorizing activity, the deodorizing properties and mechanisms of action of polyphenols, the main constituents of green tea extract (GTE), black tea extract (BTE), and grape seed extract (GSE), against volatile sulfur compounds (VSCs) in kimchi were investigated. Six VSCs were targeted and detected to be in high abundance in kimchi. The deodorizing activity (%) toward VSCs was found to be in the following order: GSE (58.4 to 91.8) >GTE (37.6 to 73.8) >BTE (28.4 to 60.3). This was attributed to the high phenolic (892.6 ± 10.5 mg GAE/g) and flavonoid (666.5 ± 23.9 mg CE/g) contents in GSE, that is, polymeric proanthocyanidins (85.97%). Particularly, the hydroxyl groups in the polyphenols showed deodorizing activity against VSCs via a sulfur-capture reaction. For packaging applications, deodorization films based on GSE and polycaprolactone were developed, and the GSE/polycaprolactone 20% films exhibited strong deodorizing effects (54.9 to 99.8%) against kimchi VSCs.

Early detection of diabetic retinopathy based on deep learning and ultra-wide-field fundus images.

Visually impaired and blind people due to diabetic retinopathy were 2.6 million in 2015 and estimated to be 3.2 million in 2020 globally. Though the incidence of diabetic retinopathy is expected to decrease for high-income countries, detection and treatment of it in the early stages are crucial for low-income and middle-income countries. Due to the recent advancement of deep learning technologies, researchers showed that automated screening and grading of diabetic retinopathy are efficient in saving time and workforce. However, most automatic systems utilize conventional fundus photography, despite ultra-wide-field fundus photography provides up to 82% of the retinal surface. In this study, we present a diabetic retinopathy detection system based on ultra-wide-field fundus photography and deep learning. In experiments, we show that the use of early treatment diabetic retinopathy study 7-standard field image extracted from ultra-wide-field fundus photography outperforms that of the optic disc and macula centered image in a statistical sense.

Changes in the physical properties of frozen cooked rice depending on thermal insulation levels of packaging during freeze-thaw.

Frozen cooked rice, a common commercially available product, has become the food of convenience in different parts of the world. Frozen foods that are well made in factories often experience quality deterioration due to temperature fluctuation during distribution. This study aimed to evaluate the impact of repeated freeze-thaw, which may occur during distribution, on the physical quality of frozen cooked rice. Additionally, the effect of the thermal insulation levels of the packaging on the quality change of frozen cooked rice as a result of repeated freeze-thaw was analyzed. The repeated freeze-thaw treatment of frozen cooked rice resulted in moisture loss, microstructure destruction, increase in hardness, increase in adhesiveness, decrease in the L* -value, increase in the a* -value, increase in the b* -value, and increase in the ΔE-value. In particular, the quality of frozen cooked rice quickly deteriorated in samples stored in packaging with low thermal insulation. On the contrary, the higher the thermal insulation of the packaging, the longer the changes in the physical properties of the frozen cooked rice were delayed. The findings of the present study show that the deterioration of quality induced by the repeated freeze-thaw treatment of frozen cooked rice could be suppressed by thermal insulated packaging. PRACTICAL APPLICATION: The present study indicates that thermal insulated packaging can be used for industrial packaging of frozen cooked rice, as it delays the quality deteriorating effects of repeated freeze-thaw. This can help maintain the quality of frozen cooked rice and improve consumer satisfaction despite temperature fluctuations during distribution.

Challenge for Diagnostic Assessment of Deep Learning Algorithm for Metastases Classification in Sentinel Lymph Nodes on Frozen Tissue Section Digital Slides in Women with Breast Cancer.

PURPOSE: Assessing the status of metastasis in sentinel lymph nodes (SLNs) by pathologists is an essential task for the accurate staging of breast cancer. However, histopathological evaluation of SLNs by a pathologist is not easy and is a tedious and time-consuming task. The purpose of this study is to review a challenge competition (HeLP 2018) to develop automated solutions for the classification of metastases in hematoxylin and eosin-stained frozen tissue sections of SLNs in breast cancer patients. MATERIALS AND METHODS: A total of 297 digital slides were obtained from frozen SLN sections, which include post-neoadjuvant cases (n = 144, 48.5%) in Asan Medical Center, South Korea. The slides were divided into training, development, and validation sets. All of the imaging datasets have been manually segmented by expert pathologists. A total of 10 participants were allowed to use the Kakao challenge platform for six weeks with two P40 GPUs. The algorithms were assessed in terms of the AUC (area under receiver operating characteristic curve). RESULTS: The top three teams showed 0.986, 0.985, and 0.945 AUCs for the development set and 0.805, 0.776, and 0.765 AUCs for the validation set. Micrometastatic tumors, neoadjuvant systemic therapy, invasive lobular carcinoma, and histologic grade 3 were associated with lower diagnostic accuracy. CONCLUSION: In a challenge competition, accurate deep learning algorithms have been developed, which can be helpful in making frozen diagnosis of intraoperative SLN biopsy. Whether this approach has clinical utility will require evaluation in a clinical setting.

Influence of Packaging Oxygen Transmission Rate on Physical Characteristics of Frozen Cooked Rice Under Various Freezing Conditions.

The influence of packaging oxygen transmission rate (OTR; 0, 3,000, 5,000, 7,000, and 20,000 [mL/m2 ]/day) on cooked rice quality factors, including freezing rate and time, moisture content, color parameters, texture characteristics, and morphology, were evaluated. Cooked rice was frozen at -20 and -80 °C using packaging with different OTRs for 14 days. Freezing rates in packaging with lower OTRs (0, 3,000, and 5,000 [mL/m2 ]/day) were higher than those in packaging with higher OTRs. The moisture content of cooked rice was the highest in OTR 5,000 packaging under all experimental conditions. Lightness (L* ) and total color difference (ΔE) values were the highest in OTR 20,000 packaging, whereas ΔE values were the lowest in OTR 5,000 packaging. Hardness and cohesiveness of frozen cooked rice gradually increased from OTR 0 to 5,000 but decreased from OTR 5,000 to 20,000. Morphology was distinct in all conditions and at all OTRs. Thus, we confirmed that the OTR of packaging influences the physical characteristics of frozen cooked rice. Therefore, packaging OTR should be considered when seeking to improve the quality of frozen cooked rice. PRACTICAL APPLICATION: Packaging oxygen transmission rate (OTR) influenced quality characteristics of frozen cooked rice under various freezing conditions. Cooked rice frozen in packaging with lower OTRs (0, 3,000, and 5,000 [mL/m2 ]/day) showed higher freezing rates, higher moisture content, shorter freezing times, smaller ice crystal formation, homogeneous pore distribution, and lower total color differences (ΔE) than did cooked rice frozen in packaging with higher OTRs (7,000 and 20,000 [mL/m2 ]/day). Packaging OTR influences frozen cooked rice quality characteristics, and should therefore be carefully considered when designing rice products.

Effect of pasteurization on delayed kimchi ripening and regression analysis for shelf life estimation of kimchi.

Pasteurization-mediated delayed kimchi ripening and regression analysis for shelf life estimation were investigated. Various initial kimchi microbial communities were simplified to lactic acid bacteria Leuconostoc sp. and Lactobacillus sp. over time, with concomitant pH decrease from 6.39 to 4.34 and acidity increase from 0.06% to 0.35%. Other quality characteristics (organic acid, carbon dioxide, and microbial population) also changed, exhibiting high intercorrelation. Pasteurization decreased the initial bacterial counts from 5.20 to 1.92 log CFU/g, thereby delaying the change in quality characteristics (pH, acidity, organic acid, microbial population, carbon dioxide, and microbial community); however, the texture did not differ significantly (p < 0.05). In addition, the regression equation for the relationship between acidity and carbon dioxide levels suggested that shelf life could be estimated in conjunction with the ideal gas equation. In conclusion, pasteurization and regression analysis for kimchi shelf life estimation may enable the maintenance of quality and effective management during the distribution process.

Nucleus Segmentation Using Gaussian Mixture based Shape Models.

We identify cells in microscopy images with stained nuclei, using the following process: Candidate seeds for nuclei are identified as extrema in a Laplacian-of-Gaussian space, and weak candidates are eliminated from clusters obtained by ellipse fitting; a region of interest for each nucleus is then defined by combining local and global thresholding; and these regions are repeatedly merged and split by modeling the shape of a nucleus and measuring the roughness of the shared boundaries connected nuclei. This method showed superior abilities to detect the nucleus regions and to split the boundaries of connected nuclei. Our experiments show higher scores in comparison with five other techniques in terms of eight evaluation metrics.

Optimization of green extraction methods for cinnamic acid and cinnamaldehyde from Cinnamon (Cinnamomum cassia) by response surface methodology.

The major compounds of cinnamon are cinnamic acid and cinnamaldehyde, for which the conditions of microwave-assisted extraction (MAE), ultrasound-assisted extraction (UAE), and reflux extraction (RE) were optimized using response surface methodology for comparing their efficiencies in terms of extraction yield, consumption of time and energy, and CO2 emission. The results indicated MAE superiority to UAE and RE owing to the highest yield of target compounds (total yield: 0.89%, cinnamic acid: 6.48 mg/100 mL, and cinnamaldehyde: 244.45 mg/100 mL) at optimum MAE conditions: 59% ethanol, 147.5 W microwave power and 3.4 min of extraction time. RE resulted in comparable yields with the highest consumption of time, energy, and solvent, and least CO2 emission. Therefore, it is concluded that MAE is the most efficient method for green extraction of cinnamic acid and cinnamaldehyde from cinnamon powder compared to UAE and RE.

Development of a Sulfite-Based Oxygen Scavenger and its Application in Kimchi Packaging to Prevent Oxygen-mediated Deterioration of Kimchi Quality.

A sulfite-based oxygen scavenger (SOS) was developed with sodium metabisulfite and applied to kimchi packaging in an attempt to prevent oxygen-mediated kimchi quality degradation. The results of the oxygen- scavenging capacity test showed that the SOS had a competitive oxygen- scavenging performance in comparison with commercial oxygen scavengers. The kimchi was packaged with and without the SOS and stored over 12 weeks at 0 and 10 °C for an SOS application test. The kimchi treated with the SOS showed a significantly lower (P < 0.05) headspace oxygen and carbon dioxide concentration and pressure inside the packages than the control. The pH and titratable acidity values indicated that the SOS did not retard the kimchi fermentation process. The Hunter L, a, and b values in the kimchi packaged with the SOS were significantly higher (P < 0.05) than those in the control. After 12 weeks of storage, the total aerobic bacteria counts were reduced by 1.32 and 2.97 log CFU/g, lactic acid bacteria counts were reduced by 2.22 and 4.42 log CFU/g, and total yeasts and molds counts were reduced by 1.76 and 3.04 log CFU/g at 0 and 10 °C, respectively, by the SOS compared to those in the control. These results demonstrated that the developed SOS inhibited oxygen-mediated deterioration of the kimchi, but did not affect the kimchi fermentation. Therefore, our SOS can be used as an active food-packaging technology for kimchi quality preservation. PRACTICAL APPLICATION: A newly designed sulfite-based oxygen scavenger was applied in kimchi packaging, and it showed remarkable preventive effects on the kimchi quality deterioration caused by oxygen. Accordingly, it can be used as an active food-packaging technology to maintain kimchi quality during the storage period. Moreover, it can also be effectively utilized in the packaging of other high-moisture foods such as meat, fish, fruits, vegetables, and dairy products.