Snake fang-inspired stamping patch for transdermal delivery of liquid formulations

A flexible microneedle patch that can transdermally deliver liquid-phase therapeutics would enable direct use of existing, approved drugs and vaccines, which are mostly in liquid form, without the need for additional drug solidification, efficacy verification, and subsequent approval. Specialized dissolving or coated microneedle patches that deliver reformulated, solidified therapeutics have made considerable advances; however, microneedles that can deliver liquid drugs and vaccines still remain elusive because of technical limitations. Here, we present a snake fang-inspired microneedle patch that can administer existing liquid formulations to patients in an ultrafast manner (< 15 s). Rear-fanged snakes have an intriguing molar with a groove on the surface, which enables rapid and efficient infusion of venom or saliva into prey. Liquid delivery is based on surface tension and capillary action. The microneedle patch uses multiple open groove architectures that emulate the grooved fangs of rear-fanged snakes: Similar to snake fangs, the microneedles can rapidly and efficiently deliver diverse liquid-phase drugs and vaccines in seconds under capillary action with only gentle thumb pressure, without requiring a complex pumping system. Hydrodynamic simulations show that the snake fang-inspired open groove architectures enable rapid capillary force-driven delivery of liquid formulations with varied surface tensions and viscosities. We demonstrate that administration of ovalbumin and influenza virus with the snake fang-inspired microneedle patch induces robust antibody production and protective immune response in guinea pigs and mice

Enhanced Ex Vivo Expansion of Human Adipose Tissue-Derived Mesenchymal Stromal Cells by Fibroblast Growth Factor-2 and Dexamethasone

In the present study, we investigated the ex vivo expansion of human adipose tissue-derived mesenchymal stromal cells (ATSCs) to identify factors that promoted efficient expansion while preserving stem cell potential. We examined several growth factors and steroids, and found that the combination of a low concentration of fibroblast growth factor-2 (FGF-2) (1 ng/mL) and dexamethasone (DEX) or betamethasone (BET) enhanced the proliferation of ATSCs by approximately 30-60% as compared to control. Enhanced proliferation under these conditions was confirmed using ATSCs isolated from three independent donors. ATSCs that were expanded in the presence of FGF-2 and DEX for 5 days were capable of differentiating into either osteoblastic or adipogenic cells, and the cells were positive for the mesenchymal stem cell markers such as CD29, CD44, CD90, CD105, and CD146, suggesting that the stem cell potential of the ATSCs was preserved. Analysis of signaling pathway revealed that tyrosine phosphorylation of Src kinase was dramatically increased in response to FGF-2 and DEX, suggesting the involvement of Src-dependent pathways in the stimulatory mechanism of proliferation of ATSCs by FGF-2 and DEX. Moreover, Src family kinase inhibitors (SU6656 and Src kinase inhibitor I) substantially reduced the FGF-2 and DEX-induced proliferation of ATSCs. SU6656 also inhibited the osteogenic and adipogenic differentiation of ATSCs. The results of the current study demonstrate that FGF-2 in combination with DEX stimulates the proliferation and osteoblastic and adipogenic differentiation of ATSCs through a Src-dependent mechanism, and that FGF-2 and DEX promote the efficient ex vivo expansion of ATSCs.This work was supported by a grant from the Ministry of Health and Welfare [0405-BO01-0204-0006] and by a Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (MOST); Grant Numbers: M10646020001-06N4602-00110 and No. R01-2006-000-10756-0).1

Acupuncture for the Treatment of Dry Eye: A Multicenter Randomised Controlled Trial with Active Comparison Intervention (Artificial Teardrops)

To evaluate the effects of acupuncture compared to a control group using artificial tears.multicenter randomised controlled trial (three local research hospitals of South Korea).150 patients with moderate to severe dry eye.Participants were randomly allocated into four weeks of acupuncture treatment (bilateral BL2, GB14, TE 23, Ex1, ST1, GB20, LI4, LI11 and single GV23) or to the artificial tears group (sodium carboxymethylcellulose).The ocular surface disease index (OSDI), tear film break-up time (TFBUT), Schirmer Ι test, visual analogue scale (VAS) for self-assessment of ocular discomfort, general assessment (by both acupuncture practitioners and participants) and quality of life (QOL) through the Measure Yourself Medical Outcome Profile-2 (MYMOP-2).There was no statistically significant difference between two groups for the improvement of dry eye symptoms as measured by OSDI (MD -16.11, 95% CI [-20.91, -11.32] with acupuncture and -15.37, 95% CI [-19.57, -11.16] with artificial tears; P = 0.419), VAS (acupuncture: -23.84 [-29.59, -18.09]; artificial tears: -22.2 [-27.24, -17.16], P = 0.530) or quality of life (acupuncture: -1.32 [-1.65, -0.99]; artificial tears: -0.96 [-1.32, -0.6], P = 0.42) immediately after treatment. However, compared with artificial tears group, the OSDI (acupuncture: -16.15 [-21.38, -10.92]; artificial tears: -10.76 [-15.25, -6.27], P = 0.030) and VAS (acupuncture: -23.88 [-30.9, -16.86]; artificial tears: -14.71 [-20.86, -8.55], P = 0.018) were significantly improved in the acupuncture group at 8 weeks after the end of acupuncture treatment. TFBUT measurements increased significantly in the acupuncture group after treatment.Acupuncture may have benefits on the mid-term outcomes related to dry eye syndrome compared with artificial tears.ClinicalTrials.gov NCT01105221

Preeminently Robust Neural PPG Denoiser

Photoplethysmography (PPG) is a simple and cost-efficient technique that effectively measures cardiovascular response by detecting blood volume changes in a noninvasive manner. A practical challenge in the use of PPGs in real-world applications is noise reduction. PPG signals are likely to be compromised by various types of noise, such as scattering or motion artifacts, and removing such compounding noises using a monotonous method is not easy. To this end, this paper proposes a neural PPG denoiser that can robustly remove multiple types of noise from a PPG signal. By casting the noise reduction problem into a signal restoration approach, we aim to achieve a solid performance in the reduction of different noise types using a single neural denoiser built upon transformer-based deep generative models. Using this proposed method, we conducted the experiments on the noise reduction of a PPG signal synthetically contaminated with five types of noise. Following this, we performed a comparative study using six different noise reduction algorithms, each of which is known to be the best model for each noise. Evaluation results of the peak signal-to-noise ratio (PSNR) show that the neural PPG denoiser is superior in three out of five noise types to the performance of conventional noise reduction algorithms. The salt-and-pepper noise type showed the best performance, with the PSNR of the neural PPG denoiser being 36.6080, and the PSNRs of the other methods were 19.8160 and 32.8234. The Poisson noise type performed the worst, showing a PSNR of 33.0090; the PSNRs of other methods were 35.1822 and 33.4795, respectively. Thereafter, an experiment to recover a signal synthesized with two or more of the five noise types was conducted. When the number of mixed noises was two, three, four, and five, the PSNRs were 29.2759, 27.8759, 26.5608, and 25.9402, respectively. Finally, an experiment to recover motion artifacts was also conducted. The synthesized motion artifact signal was created by synthesizing only a certain ratio of the total signal length. As a result of the motion artifact signal restoration, the PSNRs were 25.2872, 22.8240, 21.2901, and 19.9577 at 30%, 50%, 70%, and 90% motion artifact ratios, respectively. In the three experiments conducted, the neural PPG denoiser showed that various types of noise were effectively removed. This proposal contributes to the universal denoising of continuous PPG signals and can be further expanded to denoise continuous signals in the general domain

Factor Structure of the Korean Version of the Occupational Socialization of Beginning Physical Education Teachers Scale in the Context of the COVID-19 Pandemic and Its Relationship with Health Perception Education

This study aimed to explore the factor structure of the Korean version of the occupational socialization of beginning physical education teachers scale, in the context of the COVID-19 pandemic, and to verify its relationship with health perception education. In October 2021, 257 Korean beginning physical education teachers were enrolled in this study. Data were analyzed using frequency analysis, exploratory factor analysis, confirmatory factor analysis, descriptive statistics, reliability analysis, and multiple regression analysis. Regarding the findings, first, the occupational socialization of beginning physical education teachers scale showed a six-factor structure: role recognition, past physical education class experience, pre-service teacher education, organizational atmosphere, fellow physical education teachers, and sports facility. Second, occupational socialization of beginning physical education teachers showed a partial positive effect on health perception education. These results suggest that the Korean Metropolitan and Provincial Offices of Education and Korean schools should develop various methods to support and ensure the occupational socialization of beginning physical education teachers. Such efforts may enable these new professionals to effectively adapt to their schools, teaching roles, and provide effective health education to students under the difficult context of the COVID-19 pandemic, wherein normal educational activities are hindered

Predictive modelling of student dropout risk: Practical insights from a South Korean distance university

Distance education supports lifelong learning and empowers individuals in rapidly changing societal conditions, yet it encounters high dropout rates due to a range of individual and societal obstacles. This study addresses the challenge of creating a practical prediction model by analyzing extensive real-world time-point data from a well-established online university in Seoul. Covering 144,540 instances from 2018 to 2022, the study integrates diverse datasets to compare the accuracy of models based on longitudinal, semester-wise, and gender-specific datasets. The demographic, academic, and online metrics identified significant dropout indicators, including age (particularly when binned), residential area, specific occupations, GPA, and LMS log metrics, using a stepwise backward elimination process. The study revealed that, despite societal changes, recent data from the last four semesters can be effectively used for stable prediction training. Gender-based analysis showed different factors influencing dropout risk for males and females. The Light Gradient Boosting Machine (LGBM) algorithm excelled in prediction accuracy, with the ROC-AUC metric affirming its superiority. However, logistic regression also showed its competitive performance and offered in-depth interpretation. In South Korea's distinct educational setting, merging advanced algorithms like LGBM with the interpretive strength of logistic regression is key for effective student support strategies