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Ensuring the quality of medicinal herbs in the herbal market is crucial. However, the genetic and physical similarities among medicinal materials have led to issues of mixing and counterfeit distribution, posing significant challenges to quality assurance. Recent advancements in deep learning technology, widely applied in the field of computer vision, have demonstrated the potential to classify images quickly and accurately, even those that can only be distinguished by experts. This study aimed to develop a classification model based on deep learning technology to distinguish RGB images of seeds from Ziziphus jujuba Mill. var. spinosa, Ziziphus mauritiana Lam., and Hovenia dulcis Thunb. Using three advanced convolutional neural network (CNN) architectures—ResNet-50, Inception-v3, and DenseNet-121—all models demonstrated a classification performance above 98% on the test set, with classification times as low as 23 ms. These results validate that the models and methods developed in this study can effectively distinguish Z. jujuba seeds from morphologically similar species. Furthermore, the strong performance and speed of these models make them suitable for practical use in quality inspection settings.

Triple-negative breast cancer (TNBC) is a highly aggressive type of breast cancer and has a poor prognosis. As standardized TNBC treatment regimens cause drug resistance and tumor recurrence, the development of new TNBC treatment strategies is urgently required. Bufotalin is a bufadienolide isolated from the skin and parotid venom glands of the toad Bufo gargarizan, and has several pharmacological properties, including antiviral, anti-inflammatory, and anticancer activities. However, the anticancer effect and underlying molecular mechanisms of action of bufotalin in TNBC have not been fully studied. In the current study, we investigated the effects of bufotalin on the growth and metastasis of MDA-MB-231 and HCC1937 TNBC cells. Bufotalin potently inhibited the proliferation of both TNBC cell lines by promoting cell cycle arrest and caspase-mediated apoptosis. Furthermore, bufotalin effectively suppressed the migration and invasion of both TNBC cell lines by regulating the expression of key epithelial-mesenchymal transition (EMT) biomarkers, matrix metalloproteinases (MMPs), and integrin α6. Notably, the anticancer effect of bufotalin in TNBC cells was associated with the downregulation of the signal transducer and activator of the transcription 3 (STAT3) signaling pathway. Collectively, our results suggest that the natural compound bufotalin may exert antiproliferative and antimetastatic activities in TNBC cells by modulating the apoptotic pathway and the STAT3/EMT axis.

Abstract Background Commercial vehicle accidents are the leading cause of occupational fatalities and an increased risk of traffic accidents is associated with excessive fatigue, other health problems as well as poor sleep during work. This study explores individual and occupational factors associated with different levels of daytime sleepiness and identifies their association with driving risk among occupational drivers working at construction sites. Methods This cross-sectional and correlational study adopted a self-reported questionnaire of Korean construction drivers (N = 492). The data were collected from October 2018 to February 2019 using a battery of six validated instruments about participants’ sociodemographic, health-related, and occupational characteristics. One-way ANOVA and multinomial logistic regression were conducted using IBM SPSS WIN/VER 25.0, with a two-tailed alpha of .05. Results Based on the Epworth Sleepiness Scale, “moderate” (31.7%) and “severe” (10.2%) daytime sleepiness groups were identified. There were significant differences in break time, driving fatigue, depressive symptom, subjective sleep quality, physical and mental health, and driving risk among the three groups (all p-values < .001). Driving fatigue (Adjusted Odds Ratio [aOR] = 1.08, 1.17), depressive symptoms (aOR = 0.91, 0.98), subjective sleep quality (aOR = 1.18 in moderate only), and driving over the speed limit (aOR = 1.43, 2.25) were significant factors for determining “moderate” and “severe” daytime sleepiness groups, respectively. Conclusion A significant number of construction drivers experience excessive daytime sleepiness; thus it is important to reduce the negative impact of driving fatigue and other factors on daytime sleepiness. Our study findings suggest that occupational health care providers should pay attention to development and implementation of health management interventions to reduce driving fatigue that incorporate the drivers’ physical, mental, and occupational factors. Professional organizations need to establish internal regulations and public policies to promote health and safety among occupational drivers who specifically work at construction sites.

In this paper, we propose a multi-position cluster-based weighted position estimation method that minimizes the influence of multipath (MP)/non-line-of-sight (NLOS) signals using a global navigation satellite system (GNSS) receiver. The proposed method is suitable for positioning passenger cars, particularly in urban driving environments. Density-based spatial clustering of applications with noise (DBSCAN)-based clustering is performed by generating multi-position data through a subset of observable satellites and analyzing the density characteristics of position data generated by line-of-sight (LOS) satellite signals from the generated multi-position data. To estimate the optimal position through clustered data, we propose a method by constructing a weighted model through Doppler-based velocity measurements, which is robust to MP delay signals compared to code-based pseudorange measurements. In addition, to prevent unnecessary clustering points from having weights, the predicted range is selected based on the nonholonomic constraint of the vehicle. The proposed algorithm was quantitatively validated by selecting a region in an actual urban environment where the MP/NLOS error could occur significantly. It was confirmed that the accuracy of vehicle position was improved by approximately 24% by the proposed method compared to existing positioning solutions.

Abstract Qualitative analysis of fundus photographs enables straightforward pattern recognition of advanced pathologic myopia. However, it has limitations in defining the classification of the degree or extent of early disease, such that it may be biased by subjective interpretation. In this study, we used the fovea, optic disc, and deepest point of the eye (DPE) as the three major markers (i.e., key indicators) of the posterior globe to quantify the relative tomographic elevation of the posterior sclera (TEPS). Using this quantitative index from eyes of 860 myopic patients, support vector machine based machine learning classifier predicted pathologic myopia an AUROC of 0.828, with 77.5% sensitivity and 88.07% specificity. Axial length and choroidal thickness, the existing quantitative indicator of pathologic myopia only reached an AUROC of 0.758, with 75.0% sensitivity and 76.61% specificity. When all six indices were applied (four TEPS, AxL, and SCT), the discriminative ability of the SVM model was excellent, demonstrating an AUROC of 0.868, with 80.0% sensitivity and 93.58% specificity. Our model provides an accurate modality for identification of patients with pathologic myopia and may help prioritize these patients for further treatment.

Abstract Background Limited data are available on the impact of a specialized extracorporeal membrane oxygenation (ECMO) team on clinical outcomes in patients with acute myocardial infarction (AMI) complicated by cardiogenic shock (CS). This study evaluated whether specialized ECMO team is associated with improved in-hospital mortality in AMI patients undergoing veno-arterial (VA) ECMO. Methods A total of 255 AMI patients who underwent VA-ECMO were included. In January 2014, a multidisciplinary ECMO team was founded at our institution. Eligible patients were classified into a pre-ECMO team group (n = 131) and a post-ECMO team group (n = 124). The primary outcome was in-hospital mortality. Results In-hospital mortality (pre-ECMO team vs. post-ECMO team, 54.2% vs. 33.9%; p = 0.002) and cardiac intensive care unit mortality (pre-ECMO team vs. post-ECMO team, 51.9% vs. 30.6%; p = 0.001) were significantly lower after the implementation of a multidisciplinary ECMO team. On multivariable logistic regression model, implementation of the multidisciplinary ECMO team was associated with reduction of in-hospital mortality [odds ratio: 0.37, 95% confidence interval (CI) 0.20–0.67; p = 0.001]. Incidence of all-cause mortality [58.3% vs. 35.2%; hazard ratio (HR): 0.49, 95% CI 0.34–0.72; p

Objective The increased use of smartphones has led to several problems, including excessive smartphone use and the decreased self-ability to control smartphone use. To prevent these problems, the MindsCare app was developed as a method of self-management and intervention based on an evaluation of smartphone usage. We designed the MindsCare app to manage smartphone usage and prevent problematic smartphone use by providing personalized interventions. Methods We recruited 342 Korean participants over the age of 20 and asked them to use MindsCare for 13 weeks. Subsequently, we evaluated the changes in average smartphone usage time and the usability of the app. We designed a usability evaluation questionnaire based on the Technology Acceptance Model and conducted factor and reliability analyses on the participants’ responses. In the eighth week of the study, participants responded to a survey on the usability of the app. We ultimately collected data from 190 participants. Results The average score for the usability of the system was 3.61 on a five-point Likert scale, and approximately 58% of the participants responded positively to the evaluation items. In addition, our analysis of MindsCare data revealed a significant reduction in average smartphone use time in the eighth week compared to the baseline (t = 3.47, p = 0.001). Structural equation model analysis revealed that effort expectancy and performance expectancy had a positive relation with behavior intention for the app. Conclusions Through this study, we confirmed the MindsCare app's smartphone usage time reduction effect and proved its good usability. As a result, MindsCare may contribute to achieving users’ goals of reducing problematic smartphone use.

A substantial percentage of international students are placed on academic probation each year. This study explored the challenges and resilience characteristics of Chinese international students placed on academic probation in their first year of college. Semi-structured interviews were conducted with nine probationary Chinese international students, and the data were analyzed using a thematic analysis approach. The results indicated that challenges with daily routine, reduced adult supervision, inadequate academic preparation, and limited participation in the application process were the main factors that contributed to their academic probation. Proactivity, independence, and flexible thinking were important resilience characteristics that may have helped students cope positively with stresses relating to academic probation. Targeted institutional support could be strengthened. Implications, limitations, and suggestions for future research are also discussed.

BackgroundAlcohol use disorder (AUD) is a chronic disease with a higher recurrence rate than that of other mental illnesses. Moreover, it requires continuous outpatient treatment for the patient to maintain abstinence. However, with a low probability of these patients to continue outpatient treatment, predicting and managing patients who might discontinue treatment becomes necessary. Accordingly, we developed a machine learning (ML) algorithm to predict which the risk of patients dropping out of outpatient treatment schemes.MethodsA total of 839 patients were selected out of 2,206 patients admitted for AUD in three hospitals under the Catholic Central Medical Center in Korea. We implemented six ML models-logistic regression, support vector machine, k-nearest neighbor, random forest, neural network, and AdaBoost-and compared the prediction performances thereof.ResultsAmong the six models, AdaBoost was selected as the final model for recommended use owing to its area under the receiver operating characteristic curve (AUROC) of 0.72. The four variables affecting the prediction based on feature importance were the length of hospitalization, age, residential area, and diabetes.ConclusionAn ML algorithm was developed herein to predict the risk of patients with AUD in Korea discontinuing outpatient treatment. By testing and validating various machine learning models, we determined the best performing model, AdaBoost, as the final model for recommended use. Using this model, clinicians can manage patients with high risks of discontinuing treatment and establish patient-specific treatment strategies. Therefore, our model can potentially enable patients with AUD to successfully complete their treatments by identifying them before they can drop out.

There is conflicting evidence for the clinical benefit of statin therapy in patients with vasospastic angina (VSA). We investigated the association of statin therapy with clinical outcomes in relatively large populations with clinically suspected VSA from a nationwide population-based database. Data were collected from the Health Insurance Review and Assessment database records of 4,099 patients that were in an intensive care unit with VSA between January 1, 2008 and May 31, 2015. We divided the patients into a statin group (n = 1,795) and a non-statin group (n = 2,304). The primary outcome was a composite of cardiac arrest and acute myocardial infarction (AMI). The median follow-up duration was 3.8 years (interquartile range: 2.2 to 5.8 years). Cardiac arrest or AMI occurred in 120 patients (5.2%) in the statin group, and 97 patients (5.4%) in the non-statin group (P = 0.976). With inverse probability of treatment weighting, there was no significant difference in the rate of cardiac arrest or AMI between the two groups (adjusted hazard ratio [HR], 0.99; 95% confidence interval [CI], 0.76-1.30; P = 0.937), or even between the non-statin group and high-intensity statin group (adjusted HR, 1.08; 95% CI, 0.69-1.70; P = 0.75). The beneficial association of statin use with the primary outcome was consistently lacking across the various comorbidity types. Statin therapy was not associated with reduced cardiac arrest or AMI in patients with VSA, regardless of statin intensity. Prospective, randomized trials will be needed to confirm our findings.

BackgroundThis study compared the preventive effects of ramosetron and ondansetron on postoperative nausea and vomiting (PONV) in highly susceptible patients undergoing abdominal hysterectomy.MethodsIn a prospective, randomized, double-blinded study, a total of 120 highly susceptible women (nonsmokers, those receiving opioid-based IV patient-controlled analgesia [PCA]) undergoing abdominal hysterectomy were included in the study. Patients were divided into 2 groups and each group received either 0.3 mg of ramosetron or 4 mg of ondansetron, IV. All patients received fentanyl-based IV PCA during the 48 h postoperative periods. The incidences of PONV and side effects of 5-HT3 antagonists (headache and dizziness) were assessed at 3 intervals (

BackgroundPreoxygenation with tidal volume breathing for 3 min is commonly used technique. An end tidal expiratory oxygen concentration greater than 90% is considerd to be adequate for preoxygenation. The aim of this study was to check the effects of preoxygenation on elderly patients through the comparison with young patients during the 3 min tidal volume breathing technique.MethodsSixty patients from ASA class I or II who were scheduled for elective orthopedic general surgery were divided into an elderly (>65 yr) group and a control (25-65 yr) group. Patients were instructed in the technique of preoxygenation. Preoxygenation was accomplished with an appropriately sized face mask connected to an anesthesia machine with 100% oxygen during 3 min with patients in both groups. Expired O2, CO2 concentration and oxygen saturation were recorded simultaneously for 3 min.ResultsThe elderly group showed significantly lower end tidal oxygen concentration than the control group from 50 sec to the end of study (180 sec) with the 3 min tidal volume breathing technique (P < 0.05). In 180 sec, the control group had over 90% (91.5%) end tidal oxygen concentration, but in the elderly group end tidal oxygen concentration could not reach 90% (86.2%). In oxygen saturation, the elderly group showed a significantly lower level until 40 sec from the start of study, and then two groups showed a similar levels of oxygen saturation until the end of study.ConclusionsEnd tidal oxygen concentration did not reach 90% in 180 sec in the elderly group during preoxygenation with the 3 min tidal volume breathing technique.

BackgroundRocuronium-induced withdrawal movements can be harmful to patients during the induction period. Remifentanil has been reported to reduce these movements effectively. In this study, we determined the EC50 of remifentanil for the prevention of rocuronium induced withdrawal movements in male, female, old and child group.MethodsWe included patients scheduled for general anesthesia and assigned them into 4 groups depending on their age and gender: male group (20-60 yr), female group (20-60 yr), old group (>65 yr) and child group (6-12 yr). Remifentanil was administered by target controlled infusion. Propofol 2 mg/kg was then administered after equilibration between the effect and plasma concentration of remifentanil was reached. After loss of consciousness, rocuronium 0.6 mg/kg was administered. Patient's response to the rocuronium was graded using a 4 point scale in a blinded manner. The EC50 of remifentanil for preventing rocuronium induced withdrawal movements was determined using Dixon's up-and -down method.ResultsThe EC50 of remifentanil for preventing rocuronium induced withdrawal movements was 1.8 ± 0.5 ng/ml [95% confidence interval 1.3-2.2] in the male group, 2.3 ± 1.0 ng/ml [1.3-3.2] in the female group, 0.5 ± 0.4 ng/ml [0.2-0.8] in the old group and 2.8 ± 0.8 ng/ml [2.1-3.5] in the child group.ConclusionsThe EC50 of remifentanil for preventing rocuronium induced withdrawal movements was lowest in the elderly and higher in children than male adult patients. No difference in the EC50 of remifentanil was seen between male and female adult patients.

To investigate the appropriateness of the current vancomycin dosing strategy in adult patients with extracorporeal membrane oxygenation (ECMO), between March 2013 and November 2013, patients who were treated with vancomycin while on ECMO were enrolled. Control group consisted of 60 patients on vancomycin without ECMO, stayed in medical intensive care unit during the same study period and with the same exclusion criteria. Early trough levels were obtained within the fourth dosing, and maintenance levels were measured at steady state. A total of 20 patients were included in the analysis in ECMO group. Sixteen patients received an initial intravenous dose of 1.0 g vancomycin followed by 1.0 g every 12 hours. The non-steady state trough level of vancomycin after starting administration was subtherapeutic in 19 patients (95.00%) in ECMO group as compared with 40 patients (66.67%) in the control group (p = 0.013). Vancomycin clearance was 1.27±0.51 mL/min/kg, vancomycin clearance/creatinine clearance ratio was 0.90 ± 0.37, and elimination rate constant was 0.12 ± 0.04 h-1. Vancomycin dosingfrequency and total daily dose were significantly increased after clinical pharmacokinetic services of the pharmacist based on calculated pharmacokinetic parameters (from 2.10 ± 0.72 to 2.90 ± 0.97 times/day, p = 0.002 and from 32.54 ± 8.43 to 42.24 ± 14.62mg/kg, p = 0.014) in ECMO group in contrast with those (from 2.11 ± 0.69 to 2.37 ± 0.86 times/day, p = 0.071 and from 33.91 ± 11.85 to 31.61 ± 17.50 mg/kg, p = 0.350) in the control group.Although the elimination rate for vancomycin was similar with population parameter of non ECMO patients, the current dosing strategy of our institution for vancomycinin our ICU was not sufficient to achieve the target trough in the initial period in most patients receiving ECMO.

Purpose: To determine whether food texture affects chewing side preference (CSP) and to investigate the relationship between CSP and masticatory factors, such as occlusal contact area, bite force, and masticatory performance. Materials and Methods: Forty-seven adults (20 women and 27 men; mean age: 24 years) participated in this study. Three types of food (chewing gum, beef jerky, and peanuts) were provided to assess CSP. Occlusal contact area was measured at various ranges of interocclusal distance, and the bite force was measured. Masticatory performance was assessed according to the median particle size. Asymmetry indices of each measurement were calculated and analyzed using Pearson correlation coefficient (a = .05). Results: The CSP for beef jerky and peanuts were significantly correlated with each other, whereas the CSP for chewing gum was not correlated with other food. The proportion of participants who chewed equally on both sides was higher for chewing gum than for beef jerky. There was a significant correlation between the CSP for beef jerky and occlusal contact area, especially at interocclusal distance ranges of 0 to 89 µm and 0 to 109 µm (r = 0.41). Bite force and masticatory performance were not significantly correlated with CSP. Conclusions: Food texture seemed to affect CSP, and masticatory laterality was greater for tough foods. Moreover, CSP for tough food was closely related to the occlusal contact area at an interocclusal distance level of about 0.1 mm. [ABSTRACT FROM AUTHOR]