The Clinical Usability Evaluation of an Attachable Video Laryngoscope in the Simulated Tracheal Intubation Scenario: A Manikin Study.

The aim of this study was to assess the usefulness of an attachable video laryngoscope (AVL) by attaching a camera and a monitor to a conventional Macintosh laryngoscope (CML). Normal and tongue edema airway scenarios were simulated using a manikin. Twenty physicians performed tracheal intubations using CML, AVL, Pentax Airwayscope® (AWS), and McGrath MAC® (MAC) in each scenario. Ten physicians who had clinical experience in using tracheal intubation were designated as the skilled group, and another ten physicians who were affiliated with other departments and had little clinical experience using tracheal intubation were designated as the unskilled group. The time required for intubation and the success rate were recorded. The degree of difficulty of use and glottic view assessment were scored by participants. All 20 participants successfully completed the study. There was no difference in tracheal intubation success rate and intubation time in the normal airway scenario in both skilled and unskilled groups. In the experienced group, AWS had the highest success rate (100%) in the tongue edema airway scenario, followed by AVL (60%), MAC (60%), and CML (10%) (p = 0.001). The time required to intubate using AWS was significantly shorter than that with AVL (10.2 s vs. 19.2 s) or MAC (10.2 s vs. 20.4 s, p = 0.007). The difficulty of using AVL was significantly lower than that of CML (7.8 vs. 2.8; p < 0.001). For the experienced group, AVL was interpreted as being inferior to AWS but better than MAC. Similarly, in the unskilled group, AVL had a similar success rate and tracheal intubation time as MAC in the tongue edema scenario, but this was not statistically significant. The difficulty of using AVL was significantly lower than that of CML (8.8 vs. 3.3; p < 0.001). AVL may be an alternative for VL.

Reliability and Agreement Assessment of Sarcopenia Diagnosis through Comparison of Bioelectrical Impedance Analysis and Dual-Energy X-ray Absorptiometry.

A unified diagnostic criterion has yet to be established for sarcopenia. Therefore, we analyzed the reliability and validity of sarcopenia diagnosis using bioelectrical impedance analysis (BIA) compared with the gold standard, dual-energy X-ray absorptiometry (DEXA), and evaluated the predictive accuracy of BIA for diagnosis. The clinical trial, involving a total of 239 participants, was conducted between December 2018 and September 2019 on healthy volunteers without significant medical histories. The participants underwent health assessments, followed by sequential DEXA and BIA measurements. In both the low and normal appendicular skeletal muscle (ASM) groups, there were significant differences in the right arm, left arm, right leg, left leg, ASM, and ASM index (ASMI) between DEXA and BIA across all age groups (p < 0.05). BIA tended to overestimate compared to DEXA, but ASMI values for males and females were consistent with the criteria for sarcopenia. Bland-Altman analysis showed that each segment in both the low and normal ASM groups fell within the limits of agreement (LOA). The diagnosis of sarcopenia using BIA was significantly different from that using DEXA. However, it exhibited a significantly high correlation, fell within the LOA, and demonstrated high predictive accuracy. BIA can be considered an effective tool for diagnosing sarcopenia.

Solibacillus palustris sp. nov., isolated from wetland soil of ecology park.

A Gram-staining-positive, motile, aerobic and rod-shaped bacterium, designated strain MA9T was isolated from wetland soil of ecology park, in Seoul, Republic of Korea. This bacterium was characterized to determine its taxonomic position by using the polyphasic approach. Strain MA9T grew at 10-37 °C and at pH 6.0-9.5 on TSB. Menaquinone MK-7 was the predominant respiratory quinone and iso-C15 : 0, iso-C16 : 0 and C16 : 1 ω7c alcohol were the major fatty acids. The main polar lipids were phosphatidylethanolamine (PE), phosphatidylserine (PS), diphosphatidylglycerol (DPG) and phosphatidylglycerol (PG). The peptidoglycan type of the cell wall was A4α l-Lys-d-Glu. Based on 16S rRNA gene sequencing, strain MA9T clustered with species of the genus Solibacillus and appeared closely related to S. silvestris DSM 12223T (97.8 % sequence similarity), S. cecembensis DSM 21993T (97.6 %), S. isronensis DSM 21046T (97.6 %) and S. kalamii DSM 101595T (96.6 %). The G+C content of the genomic DNA was 37.0 mol%. Digital DNA-DNA hybridization between strain MA9T and type strains of S. silvestris, S. isronensis, S. cecembensis and S. kalamii resulted in values below 70 %. Strain MA9T could be differentiated genotypically and phenotypically from the recognized species of the genus Solibacillus. The isolate therefore represents a novel species, for which the name Solibacillus palustris sp. nov. is proposed, with the type strain MA9T (=KACC 22212T = LMG 32188T).

Identification of Gluconacetobacter xylinus LYP25 and application to bacterial cellulose production in biomass hydrolysate with acetic acid.

Bacterial cellulose (BC) is a remarkable biomacromolecule with potential applications in food, biomedical, and other industries. However, the low economic feasibility of BC production processes hinders its industrialization. In our previous work, we obtained candidate strains with improved BC production through random mutations in Gluconacetobacter. In this study, the molecular identification of LYP25 strain with significantly improved productivity, the development of chestnut pericarp (CP) hydrolysate medium, and its application in BC fermentation were performed for cost-effective BC production process. As a result, the mutant strain was identified as Gluconacetobacter xylinus. The CP hydrolysate (CPH) medium contained 30 g/L glucose with 0.4 g/L acetic acid, whereas other candidates known to inhibit fermentation were not detected. Although acetic acid is generally known as a fermentation inhibitor, it improves the BC production by G. xylinus when present within about 5 g/L in the medium. Fermentation of G. xylinus LYP25 in CPH medium resulted in 17.3 g/L BC, a 33 % improvement in production compared to the control medium, and BC from the experimental and control groups had similar physicochemical properties. Finally, the overall process of BC production from biomass was evaluated and our proposed platform showed the highest yield (17.9 g BC/100 g biomass).

Enhanced Enzymatic Synthesis of Puerarin Palmitate with Different Acyl Donors for Lipid Solubility Improvement.

Puerarin is a flavonoid known as a natural antioxidant found in the root of Pueraria robata. Its antioxidant, anticancer, and anti-inflammatory effects have attracted attention as a potential functional ingredient in various bioindustries. However, puerarin has limited bioavailability owing to its low lipid solubility and stability. Acylation is proposed as a synthesis method to overcome this limitation. In this study, lipase-catalyzed acylation of puerarin and various acyl donors was performed, and the enzymatic synthetic condition was optimized. Under the condition (20 g/L of Novozym 435, palmitic anhydride, 1:15, 40 °C, tetrahydrofuran (THF)), the synthesis of puerarin ester achieved a significantly high conversion (98.97%) within a short time (3 h). The molecule of the synthesized puerarin palmitate was identified by various analyses such as liquid chromatography-mass spectrometry (LC-MS), Fourier-transform infrared spectroscopy (FT-IR), and carbon-13 nuclear magnetic resonance (13C NMR). The lipid solubility and the radical scavenging activity were also evaluated. Puerarin palmitate showed a slight decrease in antioxidant activity, but lipid solubility was significantly improved, improving bioavailability. The high conversion achieved for puerarin esters in this study will provide the foundation for industrial applications.

Efficient Recovery Strategy of Luteolin from Agricultural Waste Peanut Shells and Activity Evaluation of Its Functional Biomolecules.

Peanut shells (PSs) generated from agricultural waste contain valuable compounds with bioactive properties such as anti-aging, antimicrobial, and antioxidant properties, making it desirable to recycle them as a sustainable resource. The aim of this study is to design an effective luteolin recovery process as the first step of an integrated biorefinery utilizing PSs as raw material. The major extraction variables and their ranges for luteolin recovery from PSs were determined (0-60 °C, 1-5 h, 0-100% MeOH concentration) and a predictive model was derived through a response surface methodology (RSM). Based on the predictive model, the equation determined for the maximal extraction of luteolin at 1 h was as follows: y = -1.8475x + 159.57, and the significant range of variables was as follows: 33.8 °C ≤ temperature (x) ≤ 48.5 °C and 70.0% ≤ MeOH concentration (y) ≤ 97.5%, respectively. High antioxidant and elastase inhibitory activities of PS extracts were confirmed, and these results support their potential to be used as functional materials. In addition, 39.2% of the solid residue after extraction was carbohydrate, which has potential as a carbon source for fermentation. This study provides a useful direction on an integrated biorefinery approach for sustainable agricultural waste valorization.

A predictive model to analyze the factors affecting the presence of serious chest injury in the occupants on motor vehicle crashes: Logistic regression approach.

OBJECTIVE: Chest injuries that occur in motor vehicle crashes (MVCs) include rib fractures, pneumothorax, hemothorax, and hemothorax depending on the injury mechanism. Many risk factors are associated with serious chest injuries from MVCs. The Korean In-Depth Accident Study database was analyzed to identify risk factors associated with motor vehicle occupants' serious chest injury. METHODS: Among 3,697 patients who visited the emergency room in regional emergency medical centers after MVCs between 2011 and 2018, we analyzed data from 1,226 patients with chest injuries. Vehicle damage was assessed using the Collision Deformation Classification (CDC) code and images of the damaged vehicle, and trauma scores were used to determine injury severity. Serious chest injury was defined as an Abbreviated Injury Scale (AIS) score for the chest code was more than 3. The patients were divided into two groups: serious chest injury patients with MAIS ≥ 3 and those with non-serious chest injury with MAIS < 3. A predictive model to analyze the factors affecting the presence of serious chest injury in the occupants on MVCs was constructed by a logistic regression analysis. RESULTS: Among the 1,226 patients with chest injuries, 484 (39.5%) had serious chest injuries. Patients in the serious group were older than those in the non-serious group (p=.001). In analyses based on vehicle type, the proportion of light truck occupants was higher in the serious group than in the non-serious group (p=.026). The rate of seatbelt use was lower in the serious group than in the non-serious group (p=.008). The median crush extent (seventh column of the CDC code) was higher in the serious group than in the non-serious group (p<.001). Emergency room data showed that the rates of intensive care unit (ICU) admission and death were higher among patients with serious injuries (p<.001). Similarly, the general ward/ICU admission data showed that the transfer and death rates were higher in patients with serious injuries (p<.001). The median ISS was higher in the serious group than in the non-serious group (p<.001). A predictive model was derived based on sex, age, vehicle type, seating row, belt status, collision type, and crush extent. This predictive model had an explanatory power of 67.2% for serious chest injuries. The model was estimated for external validation using the confusion matrix by applying the predictive model to the 2019 and 2020 data of the same structure as the data at the time of model development in the KIDAS database. CONCLUSIONS: Although this study had a major limitation in that the explanatory power of the predictive model was weak due to the small number of samples and many exclusion conditions, it was meaningful in that it suggested a model that could predict serious chest injuries in motor vehicle occupants (MVOs) based on actual accident investigation data in Korea. Future studies should yield more meaningful results, for example, if the chest compression depth value is derived through the reconstruction of MVCs using accurate collision speed values, and better models can be developed to predict the relationship between these values and the occurrence of serious chest injury.

Risk factors affecting severe thoracic injuries in motor vehicle collisions based on age group and collision directions.

OBJECTIVE: This study aimed to investigate the effect of age and collision direction on the severity of thoracic injuries based on a real-world crash database. METHODS: This was a retrospective, observational study. We used the Korean In-Depth Accident Study (KIDAS) database, which was collected from crash injury patients who visited emergency medical centers between January 2011 and February 2022 in Korea. Among the 4520 patients enrolled in the database, we selected 1908 adult patients with abbreviated injury scale (AIS) scores between 0 and 6 in the thoracic region. We classified patients with an AIS score of 3 or higher into the severe injury group. RESULTS: The incidence rate of severe thoracic injuries due to motor vehicle accidents was 16.4%. Between the severe and non-severe thoracic injury groups, there were significant differences in sex, age, collision direction, crash object, seatbelt use, and delta-V parameters. Among the age groups, over 55 years occupants had a higher risk in the thoracic regions than those under 54 years occupants. The risk of severe thoracic injury was highest in near-side collisions in all collision directions. Far-side and rear-end collisions showed a lower risk than frontal collisions. Occupants with unfastened seatbelts were at greater risk. CONCLUSIONS: The risk of severe thoracic injury is high in near-side collisions among elderly occupants. However, the risk of injury for elderly occupants increases in a super-aging society. To reduce thoracic injury, safety features made for elderly occupants in near-side collisions are required.

Internet of medical things-based real-time digital health service for precision medicine: Empirical studies using MEDBIZ platform.

The aim of this study was to introduce the implemented MEDBIZ platform based on the internet of medical things (IoMT) supporting real-time digital health services for precision medicine. In addition, we demonstrated four empirical studies of the digital health ecosystem that could provide real-time healthcare services based on IoMT using real-world data from in-hospital and out-hospital patients. Implemented MEDBIZ platform based on the IoMT devices and big data to provide digital healthcare services to the enterprise and users. The big data platform is consisting of four main components: IoMT, core, analytics, and services. Among the implemented MEDBIZ platform, we performed four clinical trials that designed monitoring services related to chronic obstructive pulmonary disease, metabolic syndrome, arrhythmia, and diabetes mellitus. Of the four empirical studies on monitoring services, two had been completed and the rest were still in progress. In the metabolic syndrome monitoring service, two studies were reported. One was reported that intervention components, especially wearable devices and mobile apps, made systolic blood pressure, diastolic blood pressure, waist circumference, and glycosylated hemoglobin decrease after 6 months. Another one was presented that increasing high-density lipoprotein cholesterol and triglyceride levels were prevented in participants with the pre-metabolic syndrome. Also, self-care using healthcare devices might help prevent and manage metabolic syndrome. In the arrhythmia monitoring service, during the real-time monitoring of vital signs remotely at the monitoring center, 318 (15.9%) general hikers found abnormal signals, and 296 (93.1%) people were recommended for treatment. We demonstrated the implemented MEDBIZ platform based on IoMT supporting digital healthcare services by acquiring real-world data for getting real-world evidence. And then through this platform, we were developing software as a medical device, digital therapeutics, and digital healthcare services, and contributing to the development of the digital health ecosystem.

Improved production of bacterial cellulose using Gluconacetobacter sp. LYP25, a strain developed in UVC mutagenesis with limited viability conditions.

Bacterial cellulose (BC), a natural polymer synthesized by bacteria, has received considerable attention owing to its impressive physicomechanical properties. However, the low productivity of BC-producing strains poses a challenge to industrializing this material and making it economically viable. In the present study, UV-induced random mutagenesis of Gluconacetobacter xylinus ATCC 53524 was performed to improve BC production. Sixty mutants were obtained from the following mutagenesis procedure: the correlation between UVC fluence and cell death was investigated, and a limited viability condition was determined as a UVC dose to kill 99.99 %. Compared to the control strain, BC production by the mutant strains LYP25 and LYP23 improved 46.4 % and 44.9 %, respectively. Fermentation profiling using the selected strains showed that LYP25 was superior in glucose consumption and BC production, 13.8 % and 41.0 %, respectively, compared to the control strain. Finally, the physicochemical properties of LYP25-derived BC were similar to those of the control strain; thus, the mutant strain is expected to be a promising producer of BC in the bio-industry based on improved productivity.

Machine learning-based injury severity prediction of level 1 trauma center enrolled patients associated with car-to-car crashes in Korea.

Injury prediction models enables to improve trauma outcomes for motor vehicle occupants in accurate decision-making and early transport to appropriate trauma centers. This study aims to investigate the injury severity prediction (ISP) capability in machine-learning analytics based on five-different regional Level 1 trauma center enrolled patients in Korea. We study car crash-related injury data of 1417 patients enrolled in the Korea In-Depth Accident Study database from January 2011 to April 2021. Severe injury classification was defined using an Injury Severity Score of 15 or greater. A planar crash was considered by excluding rollovers to compromise an accurate prediction. Furthermore, dissimilarities of the collision partner component based on vehicle segmentation were assumed for crash incompatibility. To handle class-imbalanced clinical datasets, we used four data-sampling techniques (i.e., class-weighting, resampling, synthetic minority oversampling, and adaptive synthetic sampling). Machine-learning analytics based on logistic regression, extreme gradient boosting (XGBoost), and a multilayer perceptron model were used for the evaluations. Each model was executed using five-fold cross-validation to solve overfitting consistent with the hyperparameters tuned to improve model performance. The area under the receiver operating characteristic curve of 0.896. Additionally, the present ISP model showed an under-triage rate of 6.1%. The Delta-V, age, and Principal ~ were significant predictors. The results demonstrated that the data-balanced XGBoost model achieved a reliable performance on injury severity classification of emergency department patients. This finding considers ISP model selection, which affected prediction performance based on overall predictor variables.

Preventive Effectiveness of Thoracic Side Airbags in Side-Impact Crashes Based on Korea In-Depth Accident Study (KIDAS) Database.

Studies on the effectiveness of thoracic side airbags (tSABs) in preventing thoracic injuries is limited and conflicting. This retrospective observational study aims to evaluate the effectiveness of tSABs in side-impact crashes based on data for motor vehicle occupants (MVOs) who visited an emergency department in Korea. The data were obtained from the Korean In-Depth Accident Study (KIDAS) database for patients treated at Wonju Severance Christian Hospital between January 2011 and April 2020. Of the 3899 patients with road traffic injuries, data for 490 patients were used. The overall frequency of tSAB deployment in side-impact crashes was found to be 8.1%. In the multivariate analysis, elderly age, near-side impact, colliding with fixed objects, non-oblique force, and higher crush extent were found to be factors associated with higher thoracic injuries (Abbreviated Injury Scale ≥ 2). MVOs in crashes with tSAB deployment were at an increased risk of injury compared with MVOs in crashes with no deployment, but no statistical difference was observed [adjusted odds ratios (AORs): 1.65 (0.73-3.73)]. Further, the incidence of lung injury and rib fractures increased with tSAB activation (p < 0.05). These results demonstrate the limited capability of tSABs in preventing thoracic injuries in motor vehicle crashes.

Comparative Study on the Outcome of Trauma Patients Transferred by Doctor Helicopters and Ground Ambulance in South Korea.

OBJECTIVE: The purpose of this study was to analyze the cost-effectiveness of helicopter emergency medical services (HEMS) for its economic operations in South Korea. METHODS: This study targeted trauma patients that were transported by either HEMS or ground emergency medical services (GEMS) from the scene of an accident to a regional emergency medical center. From this patient population, severe trauma patients (injury severity score ISS ≥ 16 points) with a distance travelled from the scene of the injury to the hospital that was 30 km or longer and with analyzable outcome data were extracted and included in this study. Cost-effectiveness was analyzed from survival and efficiency based on medical costs incurred from the pre-hospital setting to hospital discharge. This study included a total of 34 HEMS and 105 GEMS patients with an Injury Severity Score (ISS) ≥ 16 points from a pool of 357 potential patients. RESULTS: The survival-to-discharge rate of HEMS was 29 of 34 patients (85.3%) and was significantly higher than that of GEMS, where only 66 of 105 patients (62.8%) survived to discharge (P = 0.024). The expected and the actual mortality was higher in HEMS than it was in GEMS. Statistical significant difference in cost was found between the 2 groups (P = 0.002). CONCLUSIONS: The results of the present study indicate the increased discharge rate, survival rate and reduced in hospital mortality of HEMS with reduced admission time. This result association leads to reasonable cost effectiveness and efficient estimates overall.

Microbial Production of Bacterial Cellulose Using Chestnut Shell Hydrolysates by Gluconacetobacter xylinus ATCC 53524.

Bacterial cellulose (BC) is gaining attention as a carbon-neutral alternative to plant cellulose, and as a means to prevent deforestation and achieve a carbon-neutral society. However, the high cost of fermentation media for BC production is a barrier to its industrialization. In this study, chestnut shell (CS) hydrolysates were used as a carbon source for the BC-producing bacteria strain, Gluconacetobacter xylinus ATCC 53524. To evaluate the suitability of the CS hydrolysates, major inhibitors in the hydrolysates were analyzed, and BC production was profiled during fermentation. CS hydrolysates (40 g glucose/l) contained 1.9 g/l acetic acid when applied directly to the main medium. As a result, the BC concentration at 96 h using the control group and CS hydrolysates was 12.5 g/l and 16.7 g/l, respectively (1.3-fold improved). In addition, the surface morphology of BC derived from CS hydrolysates revealed more densely packed nanofibrils than the control group. In the microbial BC production using CS, the hydrolysate had no inhibitory effect during fermentation, suggesting it is a suitable feedstock for a sustainable and eco-friendly biorefinery. To the best of our knowledge, this is the first study to valorize CS by utilizing it in BC production.

Effective Prevention and Management Tools for Metabolic Syndrome Based on Digital Health-Based Lifestyle Interventions Using Healthcare Devices.

Digital health-based lifestyle interventions (e.g., mobile applications, short messaging service, wearable devices, social media, and interactive websites) are widely used to manage metabolic syndrome (MetS). This study aimed to confirm the utility of self-care for prevention or management of MetS. We recruited 106 participants with one or more MetS risk factors from December 2019 to September 2020. Participants were provided five healthcare devices and applications. Characteristics were compared at baseline and follow-up to examine changes in risk factors, engagement, persistence, and physical activity (analyzed through device use frequency and lifestyle interventions performed). Participants with 1-2 MetS risk factors showed statistically significant reductions in waist circumference (WC) and blood pressure (BP). Participants with ≥3 MetS risk factors showed statistically significant reductions in risk factors including weight, body mass index, WC, BP, and fasting blood sugar (FBS). The prevention and improvement groups used more healthcare devices than the other groups. Smartwatch was the most frequently used device (5 times/week), and physical activity logged more than 7000 steps/week. WC, BP, and FBS of the improvement group were reduced by more than 40%. Based on engagement, persistence, and physical activity, digital health-based lifestyle interventions could be helpful for MetS prevention and management.

Improved Productivity of Astaxanthin from Photosensitive Haematococcus pluvialis Using Phototaxis Technology.

Haematococcus pluvialis is a microalgae actively studied for the production of natural astaxanthin, which is a powerful antioxidant for human application. However, it is economically disadvantageous for commercialization owing to the low productivity of astaxanthin. This study reports an effective screening strategy using the negative phototaxis of the H. pluvialis to attain the mutants having high astaxanthin production. A polydimethylsiloxane (PDMS)-based microfluidic device irradiated with a specific light was developed to efficiently figure out the phototactic response of H. pluvialis. The partial photosynthesis deficient (PP) mutant (negative control) showed a 0.78-fold decreased cellular response to blue light compared to the wild type, demonstrating the positive relationship between the photosynthetic efficiency and the phototaxis. Based on this relationship, the Haematococcus mutants showing photosensitivity to blue light were selected from the 10,000 random mutant libraries. The M1 strain attained from the phototaxis-based screening showed 1.17-fold improved growth rate and 1.26-fold increases in astaxanthin production (55.12 ± 4.12 mg g-1) in the 100 L photo-bioreactor compared to the wild type. This study provides an effective selection tool for industrial application of the H. pluvialis with improved astaxanthin productivity.

The Effect of a Mobile and Wearable Device Intervention on Increased Physical Activity to Prevent Metabolic Syndrome: Observational Study.

BACKGROUND: Research on whether wearable devices and app-based interventions can effectively prevent metabolic syndrome (MetS) by increasing physical activity (PA) among middle-aged people living in the rural areas of South Korea remains insufficient. OBJECTIVE: The aim of this study was to determine whether mobile and wearable device interventions can improve health indicators, including PA, in MetS risk groups in rural South Korea. METHODS: In this clinical trial, performed from December 2019 to June 2020, participants were asked to use a wearable device (GalaxyWatch Active1) alone (standard intervention) or the wearable device and mobile app (Yonsei Health Korea) (enhanced intervention). Clinical measures and International Physical Activity Questionnaire (IPAQ) scores were evaluated initially and after 6 months. The number of steps was monitored through the website. The primary outcome was the difference in PA and clinical measures between the enhanced intervention and standard intervention groups. The secondary outcome was the decrease in MetS factors related to the change in PA. RESULTS: A total of 267 participants were randomly selected, 221 of whom completed the 6-month study. Among the 221 participants, 113 were allocated to the enhanced intervention group and 108 were allocated to the standard intervention group. After 6 months, the body weight and BMI for the enhanced intervention group decreased by 0.6 (SD 1.87) and 0.21 (SD 0.76), respectively (P<.001). In both groups, systolic blood pressure, diastolic blood pressure, waist circumference, and glycated hemoglobin A1c (HbA1c) decreased (P<.001). The total PA was approximately 2.8 times lower in the standard intervention group (mean 44.47, SD 224.85) than in the enhanced intervention group (mean 124.36, SD 570.0). Moreover, the enhanced intervention group achieved the recommended level of moderate to vigorous physical activity (MVPA), whereas the standard intervention group did not (188 minutes/week vs 118 minutes/week). Additionally, the number of participants in the enhanced intervention group (n=113) that reached 10,000 daily steps or more after the intervention increased from 9 (8.0%) to 26 (23.1%) (P=.002), whereas this number did not increase significantly in the standard intervention group (n=108), from 8 (7.4%) to 16 (14.8%) (P=.72). The number of participants without any MetS factors increased by 12 (11%) and 8 (7%) in the enhanced and standard intervention group, respectively. CONCLUSIONS: PA monitoring and an intervention using wearable devices were effective in preventing MetS in a rural population in Korea. Blood pressure, waist circumference, and HbA1c were improved in both intervention groups, which were effective in reducing MetS factors. However, only the participants in the enhanced intervention group continuously increased their MVPA and step counts above the recommended level to prevent MetS. Body weight and BMI were further improved, and a higher number of participants with zero MetS factors was attained from the enhanced intervention. TRIAL REGISTRATION: Clinical Research Information Service KCT0005783; https://cris.nih.go.kr/cris/search/detailSearch.do/16123.

Enhanced Production of Bacterial Cellulose from Miscanthus as Sustainable Feedstock through Statistical Optimization of Culture Conditions.

Biorefineries are attracting attention as an alternative to the petroleum industry to reduce carbon emissions and achieve sustainable development. In particular, because forests play an important role in potentially reducing greenhouse gas emissions to net zero, alternatives to cellulose produced by plants are required. Bacterial cellulose (BC) can prevent deforestation and has a high potential for use as a biomaterial in various industries such as food, cosmetics, and pharmaceuticals. This study aimed to improve BC production from lignocellulose, a sustainable feedstock, and to optimize the culture conditions for Gluconacetobacter xylinus using Miscanthus hydrolysates as a medium. The productivity of BC was improved using statistical optimization of the major culture parameters which were as follows: temperature, 29 °C; initial pH, 5.1; and sodium alginate concentration, 0.09% (w/v). The predicted and actual values of BC production in the optimal conditions were 14.07 g/L and 14.88 g/L, respectively, confirming that our prediction model was statistically significant. Additionally, BC production using Miscanthus hydrolysates was 1.12-fold higher than in the control group (commercial glucose). Our result indicate that lignocellulose can be used in the BC production processes in the near future.

Energy-efficient glucose recovery from chestnut shell by optimization of NaOH pretreatment at room temperature and application to bioethanol production.

Biofuel policies are currently being implemented globally to reduce greenhouse gas emissions. The recent European regulation, Renewable Energy Directive (RED) II, states that renewable resources should be used as raw materials. In this study, chestnut shell (CNS), a food processing residue, was utilized as a feedstock for bioethanol production. Statistical optimization was performed to improve biomass-to-glucose conversion (BtG) from the CNS. In order to design an energy-efficient process, the pretreatment was fixed at room temperature in the numerical optimization. The optimal conditions derived from the predicted model are as follows: temperature of 25 °C, reaction time of 2.8 h, and NaOH concentration of 1.9% (w/w). Under optimal conditions, both predicted and experimental BtG were 31.0%, while BtG was approximately 3.3-fold improved compared to the control group (without pretreatment). The recovered glucose was utilized for bioethanol fermentation by Saccharomyces cerevisiae K35 and the ethanol yield was achieved to be 98%. Finally, according to the mass balance based on 1000 g CNS, glucose of 310 g can be recovered by the pretreatment; the bioethanol production was approximately 155 g. This strategy suggests a direction to utilize CNS as a potential feedstock for biorefinery through the design of an economical and energy-efficient pretreatment process by lowering the reaction temperature to room temperature.