Effects of Immersive Technology-based Education for Undergraduate Nursing Students: A Systematic Review and Meta-Analysis using the GRADE approach.

BACKGROUND: The adoption of immersive technology in simulation-based nursing education has grown significantly, offering a solution to resource limitations and enabling safe access to clinical environments. Despite its advantages, there are still diverse reports regarding the effectiveness of immersive technology. It is crucial to verify the effectiveness of immersive technology in nursing education to inform future educational programs. OBJECTIVE: This systematic review aimed to identify the contents of immersive technology-based education for undergraduate nursing students and evaluate the effectiveness of immersive technology compared to traditional teaching methods. METHODS: A literature search was performed using four databases: PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase, and Web of Science, with the latest search completed on January 19, 2023. The inclusion criteria were as follows: participants were undergraduate nursing students; studies were published in Korean or English; designs included randomized controlled trials (RCTs) or non-randomized studies; and interventions involved virtual reality (VR), augmented reality (AR), mixed reality (MR), or extended reality (XR). Quality assessment was conducted using Version 2 of the Cochrane risk of bias tool (RoB 2) for RCTs and the Risk of Bias Assessment Tool for Non-Randomized Studies (RoBANS). The main outcomes of the included studies were classified according to the New World Kirkpatrick Model (NWKM), ranging from Level 1 (Reaction) to Level 4 (Results). Meta-analysis was conducted using RevMan 5.4 software, and subgroup analysis was conducted due to heterogeneity of the results of meta-analysis. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach was adopted for assessing certainty and synthesizing results of the relevant literature. RESULTS: A total of 23 studies were included, with participants numbers ranging from 33 to 289. Nineteen studies adopted VR to simulate various nursing scenarios, including disaster training, resuscitation, health assessments, and home healthcare. Four studies utilized AR technologies. Fifteen studies involved virtual patients in their scenarios. Based on NWKM, the main outcome variables were classified as Level 1 (usability and satisfaction), Level 2 (knowledge, motivation, confidence, performance, attitude, and self-efficacy), and Level 3 (clinical reasoning). Level 4 outcomes were not found in selected studies. Results of the subgroup analysis of meta-analysis showed that immersive technology-based nursing education was more effective than traditional education on knowledge attainment (standard mean difference (SMD)=0.59, 95% confidence interval (CI)=0.28-0.90, P<.001, I2=49%). Additionally, there were significant difference differences between the experimental groups and the control groups in confidence (SMD=0.70, 95% CI= 0.05-1.35, P=.03, I2=82%), and self-efficacy (SMD=0.86, 95% CI= 0.42-1.30; P<.001, I2=63%). CONCLUSIONS: These findings support the effectiveness of immersive technology-based education for undergraduate nursing students, despite heterogeneity in methods and interventions. We suggest that long-term cohort studies should be conducted to evaluate the effects of immersive technology-based nursing education on the NWKM Level 4.

Artificial Intelligence-Based Evaluation of Carotid Artery Compressibility via Point-of-Care Ultrasound in Determining the Return of Spontaneous Circulation During Cardiopulmonary Resuscitation.

AIM: This study introduces RealCAC-Net, an artificial intelligence (AI) system, to quantify carotid artery compressibility (CAC) and determine the return of spontaneous circulation (ROSC) during cardiopulmonary resuscitation . METHODS: A prospective study based on data from a South Korean emergency department from 2022 to 2023 investigated carotid artery compressibility in adult patients with cardiac arrest using a novel AI model, RealCAC-Net. The data comprised 11,958 training images from 161 cases and 15,080 test images from 134 cases. RealCAC-Net processes images in three steps: TransUNet-based segmentation, the carotid artery compressibility measurement algorithm for improved segmentation and CAC calculation, and CAC-based classification from 0 (indicating a circular shape) to 1 (indicating high compression). The accuracy of the ROSC classification model was tested using metrics such as the dice similarity coefficient, intersection-over-union, precision, recall, and F1 score. RESULTS: RealCAC-Net, which applied the carotid artery compressibility measurement algorithm, performed better than the baseline model in cross-validation, with an average dice similarity coefficient of 0.90, an intersection-over-union of 0.84, and a classification accuracy of 0.96. The test set achieved a classification accuracy of 0.96 and an F1 score of 0.97, demonstrating its efficacy in accurately identifying ROSC in cardiac arrest situations. CONCLUSIONS: RealCAC-Net enabled precise CAC quantification for ROSC determination during cardiopulmonary resuscitation. Future research should integrate this AI-enhanced ultrasound approach to revolutionize emergency care.

Role of Stigma in Moderating the Effects of Loneliness on Mental Health Problems Among Patients With COVID-19 in South Korea.

OBJECTIVE: This study examined the factors affecting depression, anxiety, and suicidal ideation among patients with coronavirus disease-2019 (COVID-19) during the early phase of COVID-19 in South Korea and investigated the role of stigma in moderating the effects of loneliness on mental health problems among these patients. METHODS: Conducted as part of the COVID-19 Mental Health Panel Survey over 12 weeks in 2021, this survey enrolled participants aged 15-79 years, applying standardized weights for ratio correction, and collected 640 completed questionnaires. Demographic characteristics were analyzed using descriptive statistics. Suicidal ideation, anxiety, and depression post-COVID-19 were examined using t-tests and logistic regression. The PROCESS macro explored stigma's moderating effects on loneliness and mental health outcomes. RESULTS: Results showed that 7.9% and 10.0% of the enrolled participants were at risk for anxiety and depression, respectively, with 3% contemplating suicide post-COVID-19. Stigma positively impacted depression and anxiety, acting as a significant moderator for loneliness, and mental health, with a stronger effect for higher stigma perception. Unemployment and college education elevated mental health risks in COVID-19 cases. Low health satisfaction and poor sleep were linked to suicidal ideation, while fatigue and COVID-19 stigma increased depression and anxiety risks. Loneliness was significantly associated with suicidal ideation, depression, and anxiety. CONCLUSION: Unemployment, college education, low health satisfaction, and poor sleep were linked to suicidal ideation. Fatigue and COVID-19 stigma raised depression/anxiety risks. Loneliness correlated with suicidal thoughts, depression, and anxiety. Stigma moderated the link between loneliness and mental health issues.

Pixel-Wise Interstitial Lung Disease Interval Change Analysis: A Quantitative Evaluation Method for Chest Radiographs Using Weakly Supervised Learning.

Interstitial lung disease (ILD) is characterized by progressive pathological changes that require timely and accurate diagnosis. The early detection and progression assessment of ILD are important for effective management. This study introduces a novel quantitative evaluation method utilizing chest radiographs to analyze pixel-wise changes in ILD. Using a weakly supervised learning framework, the approach incorporates the contrastive unpaired translation model and a newly developed ILD extent scoring algorithm for more precise and objective quantification of disease changes than conventional visual assessments. The ILD extent score calculated through this method demonstrated a classification accuracy of 92.98% between ILD and normal classes. Additionally, using an ILD follow-up dataset for interval change analysis, this method assessed disease progression with an accuracy of 85.29%. These findings validate the reliability of the ILD extent score as a tool for ILD monitoring. The results of this study suggest that the proposed quantitative method may improve the monitoring and management of ILD.

Prevalence, Correlates, and Comorbidities Among Young Adults Who Screened Positive for ADHD in South Korea During the COVID-19 Pandemic.

OBJECTIVE: This study examined the prevalence, associated factors, and psychiatric comorbidities of adult ADHD during the COVID-19 pandemic by analyzing nationally representative data. METHODS: Among the 5,511 respondents of the 2021 National Mental Health Survey, South Korea, 2,764 (18-49 years) were selected. The Korean versions of the Adult ADHD Self-Report Scale, Composite International Diagnostic Interview, and Structured Clinical Interview for Internet Gaming Disorder were used as diagnostic assessments. RESULTS: The 6-month prevalence of positive screens for adult ADHD was 3.1%. In individuals aged 18 to 29 years exhibiting adult ADHD symptoms, high prevalence rates of alcohol use, depression, and Internet gaming disorders were observed in the last 12 months. Adults who screened positive for ADHD reported significantly lower life satisfaction and resilience, and higher loneliness and social isolation (vs. non-ADHD group). CONCLUSION: Adult ADHD symptoms significantly influenced mental well-being, highlighting the need for an appropriate treatment/prevention system, particularly for individuals aged 18 to 29 years.

Improvement effect of gemigliptin on salivary gland dysfunction in exogenous methylglyoxal-injected rats.

The symptom of hyposalivation associated with hypofunction of the salivary glands is a common feature of diabetes. Inadequate saliva production can cause tissue damage in the mouth, making it susceptible to infections and leading to oral health diseases. Previous studies have highlighted the harmful effects of methylglyoxal (MGO) and MGO-derived advanced glycation end products (AGEs) in diabetes. In this study, we investigated the protective effects of gemigliptin, a dipeptidyl peptidase-4 (DPP-4) inhibitor, against MGO-induced salivary gland dysfunction. MGO treatment of immortalized human salivary gland acinar cells induced apoptosis via reactive oxygen species (ROS)-mediated pathways, but this effect was mitigated by gemigliptin. In vivo experiments involved the simultaneous administration of MGO (17.25 mg/kg) with aminoguanidine (100 mg/kg) and gemigliptin (10 and 100 mg/kg) daily to rats for two weeks. Gemigliptin increased the saliva volume and amylase levels in MGO-injected rats. Gemigliptin reduced the DPP-4 activity in both the salivary glands and serum of MGO-injected rats. Furthermore, gemigliptin exerted anti-glycation effects by reducing the accumulation of AGEs in the saliva, salivary glands, and serum and suppressing the expression of the receptor for AGEs. These actions protected the salivary gland cells from ROS-mediated apoptosis. Overall, gemigliptin protected the salivary gland cells from ROS-mediated cell death, reduced the accumulation of amylase and mucins in the salivary glands, and enhanced the salivary function by upregulating aquaporin 5 expression, and it exerted protective effects against MGO-induced salivary gland dysfunction by enhancing the anti-glycation, antioxidant, and salivary secretion activities. Our findings suggest gemigliptin as a potential therapeutic for patients with salivary gland dysfunction caused by the complications of diabetes.

Maternal nanoplastic ingestion induces an increase in offspring body weight through altered lipid species and microbiota.

The rapidly increasing prevalence of obesity and overweight, especially in children and adolescents, has become a serious societal issue. Although various genetic and environmental risk factors for pediatric obesity and overweight have been identified, the problem has not been solved. In this study, we examined whether environmental nanoplastic (NP) pollutants can act as environmental obesogens using mouse models exposed to NPs derived from polystyrene and polypropylene, which are abundant in the environment. We found abnormal weight gain in the progeny until 6 weeks of age following the oral administration of NPs to the mother during gestation and lactation. Through a series of experiments involving multi-omic analyses, we have demonstrated that NP-induced weight gain is caused by alterations in the lipid composition (lysophosphatidylcholine/phosphatidylcholine ratio) of maternal breast milk and he gut microbiota distribution of the progeny. These data indicate that environmental NPs can act as obesogens in childhood.

Fc-fused IL-7 provides broad antiviral effects against respiratory virus infections through IL-17A-producing pulmonary innate-like T cells.

Repeated pandemics caused by the influenza virus and severe acute respiratory syndrome coronavirus (SARS-CoV) have resulted in serious problems in global public health, emphasizing the need for broad-spectrum antiviral therapeutics against respiratory virus infections. Here, we show the protective effects of long-acting recombinant human interleukin-7 fused with hybrid Fc (rhIL-7-hyFc) against major respiratory viruses, including influenza virus, SARS-CoV-2, and respiratory syncytial virus. Administration of rhIL-7-hyFc in a therapeutic or prophylactic regimen induces substantial antiviral effects. During an influenza A virus (IAV) infection, rhIL-7-hyFc treatment increases pulmonary T cells composed of blood-derived interferon γ (IFNγ)+ conventional T cells and locally expanded IL-17A+ innate-like T cells. Single-cell RNA transcriptomics reveals that rhIL-7-hyFc upregulates antiviral genes in pulmonary T cells and induces clonal expansion of type 17 innate-like T cells. rhIL-7-hyFc-mediated disease prevention is dependent on IL-17A in both IAV- and SARS-CoV-2-infected mice. Collectively, we suggest that rhIL-7-hyFc can be used as a broadly active therapeutic for future respiratory virus pandemic.

APP-C31: An Intracellular Promoter of Both Metal-Free and Metal-Bound Amyloid-ß40 Aggregation and Toxicity in Alzheimer's Disease.

Intracellular C-terminal cleavage of the amyloid precursor protein (APP) is elevated in the brains of Alzheimer's disease (AD) patients and produces a peptide labeled APP-C31 that is suspected to be involved in the pathology of AD. But details about the role of APP-C31 in the development of the disease are not known. Here, this work reports that APP-C31 directly interacts with the N-terminal and self-recognition regions of amyloid-ß40 (Aß40 ) to form transient adducts, which facilitates the aggregation of both metal-free and metal-bound Aß40 peptides and aggravates their toxicity. Specifically, APP-C31 increases the perinuclear and intranuclear generation of large Aß40 deposits and, consequently, damages the nucleus leading to apoptosis. The Aß40 -induced degeneration of neurites and inflammation are also intensified by APP-C31 in human neurons and murine brains. This study demonstrates a new function of APP-C31 as an intracellular promoter of Aß40 amyloidogenesis in both metal-free and metal-present environments, and may offer an interesting alternative target for developing treatments for AD that have not been considered thus far.

Automated precision localization of peripherally inserted central catheter tip through model-agnostic multi-stage networks.

BACKGROUND: Peripherally inserted central catheters (PICCs) have been widely used as one of the representative central venous lines (CVCs) due to their long-term intravascular access with low infectivity. However, PICCs have a fatal drawback of a high frequency of tip mispositions, increasing the risk of puncture, embolism, and complications such as cardiac arrhythmias. To automatically and precisely detect it, various attempts have been made by using the latest deep learning (DL) technologies. However, even with these approaches, it is still practically difficult to determine the tip location because the multiple fragments phenomenon (MFP) occurs in the process of predicting and extracting the PICC line required before predicting the tip. OBJECTIVE: This study aimed to develop a system generally applied to existing models and to restore the PICC line more exactly by removing the MFs of the model output, thereby precisely localizing the actual tip position for detecting its misposition. METHODS: To achieve this, we proposed a multi-stage DL-based framework post-processing the PICC line extraction result of the existing technology. Our method consists of the following three stages: 1. Existing PICC line segmentation network for a baseline, 2. Patch-based PICC line refinement network, 3. PICC line reconnection network. The proposed second and third-stage models address MFs caused by the sparseness of the PICC line and the line disconnection due to confusion with anatomical structures respectively, thereby enhancing tip detection. RESULTS: To verify the objective performance of the proposed MFCN, internal validation and external validation were conducted. For internal validation, learning (130 samples) and verification (150 samples) were performed with 280 data, including PICC among Chest X-ray (CXR) images taken at our institution. External validation was conducted using a public dataset called the Royal Australian and New Zealand College of Radiologists (RANZCR), and training (130 samples) and validation (150 samples) were performed with 280 data of CXR images, including PICC, which has the same number as that for internal validation. The performance was compared by root mean squared error (RMSE) and the ratio of single fragment images (RatioSFI) (i.e., the rate at which model predicts PICC as multiple sub-lines) according to whether or not MFCN is applied to seven conventional models (i.e., FCDN, UNET, AUNET, TUNET, FCDN-HT, UNET-ELL, and UNET-RPN). In internal validation, when MFCN was applied to the existing single model, MFP was improved by an average of 45 %. The RMSE improved over 63% from an average of 27.54 mm (17.16 to 35.80 mm) to 9.77 mm (9.11 to 10.98 mm). In external validation, when MFCN was applied, the MFP incidence rate decreased by an average of 32% and the RMSE decreased by an average of 65%. Therefore, by applying the proposed MFCN, we observed the consistent detection performance improvement of PICC tip location compared to the existing model. CONCLUSION: In this study, we applied the proposed technique to the existing technique and demonstrated that it provides high tip detection performance, proving its high versatility and superiority. Therefore, we believe, in countries and regions where radiologists are scarce, that the proposed DL approach will be able to effectively detect PICC misposition on behalf of radiologists.

Double Emulsion-Mediated Delivery of Polyphenol Mixture Alleviates Atopic Dermatitis.

Although the polyphenols have been studied to alleviate inflammation, there are still challenges to delivering the polyphenols with stabilized formulation due to their low water solubility and susceptibility to oxidation. Herein, the transdermal delivery system of polyphenol mixture (PM), including quercetin (Q), phloretin (P), and ellagic acid (E), is developed using double emulsion for applying to atopic dermatitis (AD). Through the in vitro anti-degranulation assay, the optimal molar ratio of each polyphenol (Q:P:E = 5:1:1) is obtained, and the PM shows at most a 43.6% reduction of degranulation of immune cells, which is the primary factor of AD. Moreover, the water-in-oil-in-water double emulsion (W/O/W) enhances the PM's stability and has a higher anti-degranulation effect than the oil-in-water emulsion (O/W). In the in vivo 1-chloro-2,4-dinitrobenzene (DNCB)-induced mice AD model, PM reduces more AD symptoms than every single polyphenol. The PM-encapsulated W/O/W (PM_W/O/W) shows the most effectiveness in AD by decreasing dermatitis score, i.e., skin/ear thickness, mast cells, and serum IgE level. Finally, this suggests that the findings on the optimal ratio of PM and double emulsion-based delivery would be beneficial in treating AD and can be applied to other allergic diseases.

Projection mapping system for laser speckle contrast image: feasibility study for clinical application.

Significance: Laser speckle contrast images (LSCIs) have been utilized to monitor blood flow perfusion. However, they have conventionally been observed on monitor screens, resulting in potential spatial mismatching between the imaging region of interest (IROI) and monitor screen. Aim: This study proposes a projection mapping (PM) system for LSCIs (PMS_LSCI) that projects LSCIs to directly observe the blood flow perfusion in the IROI. Approach: The PMS_LSCI consists of a camera, imaging optics, a laser projector, and graphic user interface software. The spatial matching in the regions of interest was performed by adjusting the software screen of the LSCI in the IROI and evaluated by conducting in-vitro and in-vivo studies. An additional in-vivo study was performed to investigate the feasibility of real-time PM of the LSCI. Results: The spatial mismatching in the regions of interest was ranged from 2.74% to 6.47% depending on the surface curvature. The PMS_LSCI could enable real-time PM of LSCI at four different blood flow states depending on blood pressure. Conclusions: The PMS_LSCI projects the LSCI in the IROI by interacting with a projector instead of the monitor screen. The PMS_LSCI presented clinical feasibility in the in-vitro and in-vivo studies.

Application of Machine Learning Algorithm in Predicting Axillary Lymph Node Metastasis from Breast Cancer on Preoperative Chest CT.

Axillary lymph node (ALN) status is one of the most critical prognostic factors in patients with breast cancer. However, ALN evaluation with contrast-enhanced CT (CECT) has been challenging. Machine learning (ML) is known to show excellent performance in image recognition tasks. The purpose of our study was to evaluate the performance of the ML algorithm for predicting ALN metastasis by combining preoperative CECT features of both ALN and primary tumor. This was a retrospective single-institutional study of a total of 266 patients with breast cancer who underwent preoperative chest CECT. Random forest (RF), extreme gradient boosting (XGBoost), and neural network (NN) algorithms were used. Statistical analysis and recursive feature elimination (RFE) were adopted as feature selection for ML. The best ML-based ALN prediction model for breast cancer was NN with RFE, which achieved an AUROC of 0.76 ± 0.11 and an accuracy of 0.74 ± 0.12. By comparing NN with RFE model performance with and without ALN features from CECT, NN with RFE model with ALN features showed better performance at all performance evaluations, which indicated the effect of ALN features. Through our study, we were able to demonstrate that the ML algorithm could effectively predict the final diagnosis of ALN metastases from CECT images of the primary tumor and ALN. This suggests that ML has the potential to differentiate between benign and malignant ALNs.

The Effects of Sargassum horneri Extract and Fucoidan on Tear Hyposecretion and Ocular Surface Injury in Rats with Dry Eye Diseases.

Hyperosmotic stress caused by tear hyposection is a leading cause of dry eye disease. We investigated the prevention of dry eye disease in corneal epithelial cells and in rats that were induced to develop dry eye disease via unilateral excision of their exorbital lacrimal gland using Sargassum horneri extract (AB_SH) and its bioactive component fucoidan. Oral administration of AB_SH (250 mg/kg and 500 mg/kg) and fucoidan (100 mg/kg) was conducted for 7 days. In order to measure tear secretion, phenol red thread tear tests were performed along with corneal irregularity measurements. The apoptotic injury in the cornea and the lacrimal gland was evaluated using TUNEL staining. AB_SH and fucoidan were shown to suppress apoptosis and the expression of apoptosis-related proteins in human corneal epithelial cells under hyperosmotic conditions. Oral administration of AB_SH and fucoidan attenuated tear hyposecretion and corneal irregularity in the lacrimal gland-excised rats. In addition, AB_SH and fucoidan also reduced apoptosis in the cornea and lacrimal gland. This study suggests that S. horneri extract and fucoidan can effectively ameliorate dry eye disease by suppressing the apoptosis of ocular tissues.

Ishige okamurae Celluclast extract ameliorates non-alcoholic fatty liver in high-fructose diet-fed mice by modulation of lipid metabolism and gut microbiota composition.

Recently, a new mechanism has revealed that gut microbiota plays a pivotal role in metabolizing fructose to acetate that facilitates hepatic lipogenesis. Therefore, our study investigated the role of microbiome on abnormal lipid synthesis in the presence of fructose and identified attenuating effects of Ishige okamurae Celluclast extract (IOCE) against fructose-induced fatty liver. The results indicated that oral administration of IOCE (150 and 300 mg/kg/day for 12 weeks) significantly reduced both gut microbiota-mediated and -non-mediated hepatic lipogenesis simultaneously triggered by fructose metabolism. IOCE reduced hepatic triglyceride accumulation and expression levels of key enzymes for glucolipid metabolism. In addition, IOCE regulated fatty acid synthesis, ß-oxidation, and improved hepatic inflammation. Furthermore, IOCE inhibited direct fructose-to-acetate conversion and altered the compositions of gut microbiota. These findings suggest that IOCE might serve as a potential prebiotic dietary supplement by ameliorating fatty liver through dual regulation of classical lipogenic pathway and gut microbiota.

Estimating the Volume of Nodules and Masses on Serial Chest Radiography Using a Deep-Learning-Based Automatic Detection Algorithm: A Preliminary Study.

BACKGROUND: The purpose of this study was to assess the volume of the pulmonary nodules and masses on serial chest X-rays (CXRs) from deep-learning-based automatic detection algorithm (DLAD)-based parameters. METHODS: In a retrospective single-institutional study, 72 patients, who obtained serial CXRs (n = 147) for pulmonary nodules or masses with corresponding chest CT images as the reference standards, were included. A pre-trained DLAD based on a convolutional neural network was developed to detect and localize nodules using 13,710 radiographs and to calculate a localization map and the derived parameters (e.g., the area and mean probability value of pulmonary nodules) for each CXR, including serial follow-ups. For validation, reference 3D CT volumes were measured semi-automatically. Volume prediction models for pulmonary nodules were established through univariable or multivariable, and linear or non-linear regression analyses with the parameters. A polynomial regression analysis was performed as a method of a non-linear regression model. RESULTS: Of the 147 CXRs and 208 nodules of 72 patients, the mean volume of nodules or masses was measured as 9.37 ± 11.69 cm3 (mean ± standard deviation). The area and CT volume demonstrated a linear correlation of moderate strength (i.e., R = 0.58, RMSE: 9449.9 mm3 m3 in a linear regression analysis). The area and mean probability values exhibited a strong linear correlation (R = 0.73). The volume prediction performance based on a multivariable regression model was best with a mean probability and unit-adjusted area (i.e. , RMSE: 7975.6 mm3, the smallest among the other variable parameters). CONCLUSIONS: The prediction model with the area and the mean probability based on the DLAD showed a rather accurate quantitative estimation of pulmonary nodule or mass volume and the change in serial CXRs.

How Three Self-Secreted Biofilm Exopolysaccharides of Pseudomonas aeruginosa, Psl, Pel, and Alginate, Can Each Be Exploited for Antibiotic Adjuvant Effects in Cystic Fibrosis Lung Infection.

In cystic fibrosis (CF), pulmonary infection with Pseudomonas aeruginosa is a cause of increased morbidity and mortality, especially in patients for whom infection becomes chronic and there is reliance on long-term suppressive therapies. Current antimicrobials, though varied mechanistically and by mode of delivery, are inadequate not only due to their failure to eradicate infection but also because they do not halt the progression of lung function decline over time. One of the reasons for this failure is thought to be the biofilm mode of growth of P. aeruginosa, wherein self-secreted exopolysaccharides (EPSs) provide physical protection against antibiotics and an array of niches with resulting metabolic and phenotypic heterogeneity. The three biofilm-associated EPSs secreted by P. aeruginosa (alginate, Psl, and Pel) are each under investigation and are being exploited in ways that potentiate antibiotics. In this review, we describe the development and structure of P. aeruginosa biofilms before examining each EPS as a potential therapeutic target for combating pulmonary infection with P. aeruginosa in CF, with a particular focus on the current evidence for these emerging therapies and barriers to bringing these therapies into clinic.

Fabrication of Assembled FeS2 Nanosheet and Application for High-Performance Supercapacitor Electrodes.

To overcome the low-energy-density limitation of supercapacitors, we aimed to achieve a material with a high specific capacitance by manipulating the nanostructure of FeS2, which comprises the most abundant and affordable elements. In this study, nanosheet-assembled FeS2 (NSA-FeS2) was fabricated using a novel method. Sub-micron droplets of sulfur particles stabilized with polyvinylpyrrolidone were formed in silicone oil medium, and Fe(CO)5 was absorbed and reacted on the surface to form core-shell particles, ES/[Fe], with a sulfur core and an iron-containing outer shell. The high temperature treatment of ES/[Fe] produced NSA-FeS2, in which pyrite FeS2 nanosheets grew and were partially interconnected. In a three-electrode system, the as-prepared NSA-FeS2 and NSA-FeS2/polyaniline (PANI) composites exhibited specific capacitances of 763 and 976 Fg-1, respectively, at a current density of 0.5 Ag-1, with corresponding capacitance retentions of 93 and 96% after 3000 charge-discharge cycles. The capacitance retention of the NSA-FeS2/PANI composites was 49% when the current density was increased from 0.5 to 5 Ag-1. Notably, the obtained specific capacitances exhibited the highest values in pure FeS2 and FeS2-based composites, indicating the significant potential for the utilization of iron sulfide in pseudocapacitive electrode materials.

Association between dental amalgam restoration and urine mercury concentrations among young women: a cross-sectional study.

BACKGROUND: The association between dental amalgam fillings and urine mercury concentrations was investigated in this study to assess the health risks associated with dental amalgams. METHODS: This cross-sectional study included 99 women in their 20s who visited the dental clinic in Daegu, Korea. The 99 participants were composed of 68 subjects who had dental amalgam fillings (exposure group) and 31 subjects who did not have dental amalgam fillings (nonexposure group). Oral examinations were conducted by a single dental hygienist, sociodemographic features were investigated as confounding variables, and urine mercury concentrations were measured using an automatic mercury analyzer. RESULTS: The mean±standard deviation of the urine mercury concentrations of the exposure and nonexposure groups were 1.50±1.78 µg/g creatinine and 0.53±0.63 µg/g creatinine, respectively. The exposure group showed significantly higher levels than the nonexposure group (p<0.01). The urine mercury concentration significantly increased with an increase in the number of teeth filled with amalgam, cavity surfaces involved, and number of defective amalgam fillings, and according to the latest exposure time (p<0.001). In the multiple regression analysis of amalgam-related factors and urine mercury concentrations after correction for confounding factors, the urine mercury concentration in the group with six or more amalgam-filled teeth, 11 or more cavity surfaces, and two or more defective amalgams was significantly higher than that in the nonexposure group (p<0.001). CONCLUSION: According to this study, exposure to dental amalgams was confirmed to significantly affect urine mercury concentrations.

Prevalence of Mental Disorders and Associated Factors in Korean Adults: National Mental Health Survey of Korea 2021.

OBJECTIVE: Mental health is a global concern and needs to be studied more closely. We aimed to estimate the prevalence of mental disorders and their associated factors among the general population in Korea. METHODS: The National Mental Health Survey of Korea 2021 was conducted between June 19 and August 31, 2021 and included 13,530 households; 5,511 participants completed the interview (response rate: 40.7%). The lifetime and 12-month diagnosis rates of mental disorders were made using the Korean version of the Composite International Diagnostic Interview 2.1. Factors associated with alcohol use disorder (AUD), nicotine use disorder, depressive disorder, and anxiety disorder were analyzed, and mental health service utilization rates were estimated. RESULTS: The lifetime prevalence of mental disorders was 27.8%. The 12-month prevalence rates of alcohol use, nicotine use, depressive, and anxiety disorders were 2.6%, 2.7%, 1.7%, and 3.1%, respectively. The risk factors associated with 12-month diagnosis rates were as follows: AUD: sex and age; nicotine use disorder: sex; depressive disorder: marital status and job status; anxiety disorder: sex, marital status, and job status. The 12-month treatment and service utilization rates for 12-month AUD, nicotine use disorder, depressive disorder, and anxiety disorder were 2.6%, 1.1%, 28.2%, and 9.1%, respectively. CONCLUSION: Approximately 25% of adults in the general population were diagnosed with mental disorders during their lifetime. The treatment rates were substantially low. Future studies on this topic and efforts to increase the mental health treatment rate at a national level are needed.