People-Oriented Culture and its association with burnout, depressive symptoms, and sleep problems during COVID-19 pandemic among EMS providers in Korea.

OBJECTIVE: This study examined how perceived people-oriented culture (POC) was associated with burnout, depressive symptoms, and sleep problems during the COVID-19 pandemic among emergency medical service (EMS) providers in Korea. METHODS: We conducted a cross-sectional survey among 693 EMS providers in 2021. RESULTS: Overall, 60% reported burnout and around 25% had depressive symptoms. Prevalence of poor sleep quality, unrestful sleep, and sleep disturbance were 46.5%, 58.2%, and 52.2%, respectively. Compared to high POC group, higher prevalence of depressive symptoms was observed among medium (PR: 1.57, 95% CI: 1.06, 2.32) and low (PR: 2.70, 95% CI: 1.92, 3.79) POC group. Similar trends were observed in the analysis of burnout and sleep problems. CONCLUSIONS: Our findings underscore that low POC could play a critical role in worsening burnout, depressive symptoms, and sleep problems among EMS providers.

Ethnic discrimination, asking for fair treatment, and poor self-rated health: a gender stratified analysis of 13,443 Korean Chinese waged workers in South Korea.

BACKGROUND: In South Korea, Korean Chinese workers experience ethnic discrimination although they share physical similarities and ethnic heritage with native-born Koreans. This study aimed to examine whether perceived ethnic discrimination is associated with poor self-rated health and whether the association differs by gender among Korean Chinese waged workers in South Korea. METHODS: We conducted a pooled cross-sectional analysis using data of 13,443 Korean Chinese waged workers from the Survey on Immigrants' Living Conditions and Labor Force conducted in 2018, 2020, and 2022. Based on perceived ethnic discrimination, asking for fair treatment, and subsequent situational improvement, respondents were classified into the following four groups: "Not experienced," "Experienced, not asked for fair treatment," "Experienced, asked for fair treatment, not improved," and "Experienced, asked for fair treatment, improved." Poor self-rated health was assessed using a single question "How is your current overall health?" We applied logistic regression to examine the association between perceived ethnic discrimination and poor self-rated health, with gender-stratified analyses. RESULTS: We found an association between ethnic discrimination and poor self-rated health among Korean Chinese waged workers. In the gender-stratified analysis, the "Experienced, not asked for fair treatment" group was more likely to report poor self-rated health compared to the "Not experienced" group, regardless of gender. However, gender differences were observed in the group stratified by situational improvements. For male workers, no statistically significant association was found in the "Experienced, asked for fair treatment, improved" group with poor self-rated health (odd ratios: 0.87, 95% confidence intervals: 0.30-2.53). Conversely, among female workers, a statistically significant association was observed (odd ratios: 2.63, 95% confidence intervals: 1.29-5.38). CONCLUSIONS: This study is the first to find an association between perceived ethnic discrimination and poor self-rated health, along with gender differences in the association between situational improvements after asking for fair treatment and poor self-rated health among Korean Chinese waged workers in South Korea.

Identifying Candidate Polyphenols Beneficial for Oxidative Liver Injury through Multiscale Network Analysis.

Oxidative stress, a driver of liver pathology, remains a challenge in clinical management, necessitating innovative approaches. In this research, we delved into the therapeutic potential of polyphenols for oxidative liver injury using a multiscale network analysis framework. From the Phenol-Explorer database, we curated a list of polyphenols along with their corresponding PubChem IDs. Verified target information was then collated from multiple databases. We subsequently measured the propagative effects of these compounds and prioritized a ranking based on their correlation scores for oxidative liver injury. This result underwent evaluation to discern its effectiveness in differentiating between known and unknown polyphenols, demonstrating superior performance over chance level in distinguishing these compounds. We found that lariciresinol and isopimpinellin yielded high correlation scores in relation to oxidative liver injury without reported evidence. By analyzing the impact on a multiscale network, we found that lariciresinol and isopimpinellin were predicted to offer beneficial effects on the disease by directly acting on targets such as CASP3, NR1I2, and CYP3A4 or by modulating biological functions related to the apoptotic process and oxidative stress. This study not only corroborates the efficacy of identified polyphenols in liver health but also opens avenues for future investigations into their mechanistic actions.

Change in employment status and its causal effect on suicidal ideation and depressive symptoms: A marginal structural model with machine learning algorithms.

OBJECTIVE: This study aimed to assess the causal effect of a change in employment status on suicidal ideation and depressive symptoms by applying marginal structural models (MSM) with machine-learning (ML) algorithms. METHODS: We analyzed data from the 8-15th waves (2013-2020) of the Korean Welfare Panel Study, a nationally representative longitudinal dataset. Our analysis included 13 294 observations from 3621 participants who had standard employment at baseline (2013-2019). Based on employment status at follow-up year (2014-2020), respondents were classified into two groups: (i) maintained standard employment (reference group), (ii) changed to non-standard employment. Suicidal ideation during the past year and depressive symptoms during the past week were assessed through self-report questionnaire. To apply the ML algorithms to the MSM, we conducted eight ML algorithms to build the propensity score indicating a change in employment status. Then, we applied the MSM to examine the causal effect by using inverse probability weights calculated based on the propensity score from ML algorithms. RESULTS: The random forest algorithm performed best among all algorithms, showing the highest area under the curve 0.702, 95% confidence interval (CI) 0.686-0.718. In the MSM with the random forest algorithm, workers who changed from standard to non-standard employment were 2.07 times more likely to report suicidal ideation compared to those who maintained standard employment (95% CI 1.16-3.70). A similar trend was observed in the analysis of depressive symptoms. CONCLUSIONS: This study found that a change in employment status could lead to a higher risk of suicidal ideation and depressive symptoms.

Optimal bilayer composites for temperature-tracking wireless electronics.

Modern silicone-based epidermal electronics engineered for body temperature sensing represent a pivotal development in the quest for advancing preventive medicine and enhancing post-surgical monitoring. While these compact and highly flexible electronics empower real-time monitoring in dynamic environments, a noteworthy limitation is the challenge in regulating the infiltration or obstruction of heat from the external environment into the surface layers of these electronics. The study presents a cost-effective temperature sensing solution by embedding wireless electronics in a multi-layered elastomeric composite to meet the dual needs of enhanced thermal insulation for encapsulation in contact with air and improved thermal conductivity for the substrate in contact with the skin. The encapsulating composite benefits from the inclusion of hollow silica microspheres, which reduce the thermal conductivity by 40%, while non-spherical aluminum nitride enhances the thermal conductivity of the substrate by 370%. The addition of particles to the respective composites inevitably leads to an increase in modulus. Two composite elements are engineered to coexist while maintaining a matching low modulus of 3.4 MPa and a stretchability exceeding 30%, all without compromising the optimized thermal properties. Consecutive thermal, electrical, and mechanical characterization confirms the sensor's capacity for precise body temperature monitoring during a single day's lifespan, while also assessing the influence of behavioral factors on body temperature.

Photonic control of ligand nanospacing in self-assembly regulates stem cell fate.

Extracellular matrix (ECM) undergoes dynamic inflation that dynamically changes ligand nanospacing but has not been explored. Here we utilize ECM-mimicking photocontrolled supramolecular ligand-tunable Azo+ self-assembly composed of azobenzene derivatives (Azo+) stacked via cation-π interactions and stabilized with RGD ligand-bearing poly(acrylic acid). Near-infrared-upconverted-ultraviolet light induces cis-Azo+-mediated inflation that suppresses cation-π interactions, thereby inflating liganded self-assembly. This inflation increases nanospacing of "closely nanospaced" ligands from 1.8 nm to 2.6 nm and the surface area of liganded self-assembly that facilitate stem cell adhesion, mechanosensing, and differentiation both in vitro and in vivo, including the release of loaded molecules by destabilizing water bridges and hydrogen bonds between the Azo+ molecules and loaded molecules. Conversely, visible light induces trans-Azo+ formation that facilitates cation-π interactions, thereby deflating self-assembly with "closely nanospaced" ligands that inhibits stem cell adhesion, mechanosensing, and differentiation. In stark contrast, when ligand nanospacing increases from 8.7 nm to 12.2 nm via the inflation of self-assembly, the surface area of "distantly nanospaced" ligands increases, thereby suppressing stem cell adhesion, mechanosensing, and differentiation. Long-term in vivo stability of self-assembly via real-time tracking and upconversion are verified. This tuning of ligand nanospacing can unravel dynamic ligand-cell interactions for stem cell-regulated tissue regeneration.

Mediating effect of vascular calcification in galectin-3-related mortality in hemodialysis patients.

Galectin-3 levels have been studied as a potential biomarker for predicting cardiovascular (CV) risk and mortality in hemodialysis (HD) patients. Recently, a close relationship between galectin-3 and vascular calcification (VC) has been reported. Here, we investigated the role of VC as a mediating factor in the association between galectin-3 and mortality. Serum galectin-3 and baseline aortic arch calcification (AoAC) score were measured in 477 incident HD patients. Mortality data were obtained at a median follow-up of 40 months. Causal mediation analysis was performed to examine the effect of vascular risk factors on galectin-3-related mortality. The prevalence of AoAC in HD patients was 57% (n = 272), and elevated galectin-3 levels were associated with a significantly increased risk of AoAC. When the galectin-3 level was divided by the median level of 37 ng/mL, a higher galectin group increased the risk of all-cause mortality by 1.71-fold (95% CI 1.02-2.92, p = 0.048), even after adjustment for multiple CV risk factors. Mediation analysis showed that both the direct effect of the galectin-3 on mortality (ß = 0.0368, bootstrapped 95% CI [0.0113-0.0622]) and the indirect effects were significant. AoAC score and high-sensitivity CRP levels significantly mediated the association between galectin-3 and mortality (total indirect effects: ß = 0.0188, bootstrapped 95% CI [0.0066-0.0352]). This study suggests that the association between high galectin-3 and mortality may be partially mediated by higher VC and inflammatory state in HD patients.

Female workers with long working hours are more likely to have depressive symptoms when having family-to-work conflict.

PURPOSE: Workers' health can be influenced by risk factors from their family environments as well as their work environments. This paper sought to examine how the association between long working hours and depressive symptoms differs based on the level of FWC after being stratified by worker's gender. METHODS: We used the dataset of 20,384 full-time wage workers from the sixth Korean Working Conditions Survey (2020). Long working hours were defined as working 52 h or more per week. FWC was measured using a 2-item questionnaire, and depressive symptoms were measured using the WHO-5 well-being index. Applying modified Poisson regression, we evaluated how the association between long working hours and depressive symptoms differs by the level of FWC male and female workers separately. RESULTS: In the analysis of the female workers, long working hours were associated with depressive symptoms in the high FWC group (PR 1.35, 95% CI 1.17, 1.55) after adjusting for potential confounders whereas no association was observed in the low FWC group. Among the male workers, a statistically significant association was observed in both high FWC (PR 1.22, 95% CI 1.07, 1.38) and low FWC (PR 1.28, 95% CI 1.12, 1.47) groups. CONCLUSION: FWC may act as a workplace stressor that potentially amplifies the health impact of long working hours among female workers.

Necking Reduction at Low Temperature in Aspect Ratio Etching of SiO2 at CF4/H2/Ar Plasma.

This study investigated the effect of temperature on the aspect-ratio etching of SiO2 in CF4/H2/Ar plasma using patterned samples of a 200 nm trench in a low-temperature reactive-ion etching system. Lower temperatures resulted in higher etch rates and aspect ratios for SiO2. However, the plasma property was constant with the chuck temperature, indicated by the line intensity ratio from optical emission spectroscopy monitoring of the plasma. The variables obtained from the characterization of the etched profile for the 200 nm trench after etching were analyzed as a function of temperature. A reduction in the necking ratio affected the etch rate and aspect ratio of SiO2. The etching mechanism of the aspect ratio etching of SiO2 was discussed based on the results of the surface composition at necking via energy-dispersive X-ray spectroscopy with temperature. The results suggested that the neutral species reaching the etch front of SiO2 had a low sticking coefficient. The bowing ratio decreased with lowering temperature, indicating the presence of directional ions during etching. Therefore, a lower temperature for the aspect ratio etching of SiO2 could achieve a faster etch rate and a higher aspect ratio of SiO2 via the reduction of necking than higher temperatures.

Utilizing Gate-Controlled Supercurrent for All-Metallic Tunable Superconducting Microwave Resonators.

Hybridizing a microwave mode with a quantum state requires precise frequency matching of a superconducting microwave resonator and the corresponding quantum object. However, fabrication always brings imperfections in geometry and material properties, causing deviations from the desired operating frequencies. An effective and universal strategy for their resonant coupling is to tune the frequency of a resonator, as quantum states like phonons are hardly tunable. Here, we demonstrate gate-tunable, titanium-nitride (TiN)-based superconducting resonators by implementing a nanowire inductor whose kinetic inductance is tuned via the gate-controlled supercurrent (GCS) effect. We investigate their responses for different gate biases and observe 4% (∼150 MHz) frequency tuning with decreasing internal quality factors. We also perform temperature-controlled experiments to support phonon-related mechanisms in the GCS effect and the resonance tuning. The GCS effect-based method proposed in this study provides an effective route for locally tunable resonators that can be employed in various hybrid quantum devices.

Accuracy of zirconia crown manufactured using stereolithography and digital light processing.

OBJECTIVES: The aim of this study is to evaluate the accuracy of zirconia crowns fabricated using stereolithography (SLA) and digital light processing (DLP) and to compare their accuracy with those fabricated using the subtractive manufacturing (SM) method. METHODS: A typodont model with a prepared maxillary first molar was scanned, and the anatomical contour crown was designed using dental computer-aided-design (CAD) software. The designed file in standard tessellation language (STL) format was used to fabricate 10 crowns per group. The crowns were manufactured using a dental milling machine (Datron D5; MLC group), SLA (CERAMAKER 900; SLAC group), and DLP (ZIPRO; DLPC group) printers. The fabricated crowns were scanned using a dental laboratory scanner and saved in three parts: the external, intaglio, and marginal surfaces. For accuracy assessment, these parts were superimposed to the reference file. Root mean square (RMS) values were evaluated using three-dimensional analysis software (Geomagic Control X). Statistical significance was evaluated using a nonparametric Kruskal-Wallis test (α = 0.05) and a post-hoc Mann-Whitney U test with Bonferroni correction (α = 0.016). RESULTS: Trueness evaluation revealed the lowest RMS value in all areas in the MLC group, followed by that in the DLPC group. The precision evaluation revealed the lowest RMS value in all areas in the MLC group. Statistically significant differences were observed among the groups in the external, intaglio, and marginal surface (P < 0.05). CONCLUSIONS: Although the restorations fabricated using SM revealed higher accuracy, the crowns manufactured using SLA and DLP methods were considered clinically acceptable. CLINICAL SIGNIFICANCE: In the production of zirconia crowns, subtractive manufacturing continues to demonstrate significantly higher accuracy compared to additive manufacturing. However, crowns fabricated using the additive manufacturing method also demonstrated high accuracy.

Machine Learning-Based Measurement of Regional and Global Spinal Parameters Using the Concept of Incidence Angle of Inflection Points.

This study delves into the application of convolutional neural networks (CNNs) in evaluating spinal sagittal alignment, introducing the innovative concept of incidence angles of inflection points (IAIPs) as intuitive parameters to capture the interplay between pelvic and spinal alignment. Pioneering the fusion of IAIPs with machine learning for sagittal alignment analysis, this research scrutinized whole-spine lateral radiographs from hundreds of patients who visited a single institution, utilizing high-quality images for parameter assessments. Noteworthy findings revealed robust success rates for certain parameters, including pelvic and C2 incidence angles, but comparatively lower rates for sacral slope and L1 incidence. The proposed CNN-based machine learning method demonstrated remarkable efficiency, achieving an impressive 80 percent detection rate for various spinal angles, such as lumbar lordosis and thoracic kyphosis, with a precise error threshold of 3.5°. Further bolstering the study's credibility, measurements derived from the novel formula closely aligned with those directly extracted from the CNN model. In conclusion, this research underscores the utility of the CNN-based deep learning algorithm in delivering precise measurements of spinal sagittal parameters, and highlights the potential for integrating machine learning with the IAIP concept for comprehensive data accumulation in the domain of sagittal spinal alignment analysis, thus advancing our understanding of spinal health.

Usefulness of a drill stopper to prevent iatrogenic soft tissue injury in orthopedic surgery.

Objective: This study introduces a novel technique utilizing a drill stopper to limit drill penetration depth and to prevent iatrogenic injuries, specifically neurovascular damage, in orthopedic surgeries. Orthopedic surgeries frequently involve the use of drills, which are essential tools for various procedures. However, improper handling of drills can lead to iatrogenic soft tissue injuries, causing severe consequences such as permanent disability or life-threatening complications. To address this issue, we propose the use of a drill stopper as a safeguard to prevent excessive drill penetration and reduce the risk of soft tissue damage during surgery. Materials and Methods: The study involved 32 orthopedic surgeons, half of whom were experienced and the other half inexperienced. Synthetic femur bone models (Synbone) were used for drilling exercises, employing four configurations: a sharp drill bit without a stopper (SF, Sharp Free), a sharp drill bit with a stopper (SS, Sharp Stopper), a blunt drill bit without a stopper (BF, Blunt Free), and a blunt drill bit with a stopper (BS, Blunt Stopper). Each participant conducted three trials for each configuration, and the penetration depth was measured after each trial. Results: For experienced surgeons, the average penetration depths were 3.83 (±1.826)mm for SF, 11.02 (±3.461)mm for BF, 2.88 (±0.334)mm for SS, and 2.75 (±0.601)mm for BS. In contrast, inexperienced surgeons had average depths of 8.52 (±4.608)mm for SF, 18.75 (±4.305)mm for BF, 2.96 (±0.683)mm for SS, and 2.83 (±0.724)mm for BS. Conclusion: The use of a drill stopper was highly effective in controlling drill penetration depth and preventing iatrogenic injuries during orthopedic surgeries. We recommend its incorporation, particularly when using a blunt drill bit or when an inexperienced surgeon operates in an anatomically unfamiliar area. Using the drill stopper, the risk of severe injuries from excessive drill penetration can be minimized, leading to improved patient safety and better surgical outcomes.

Lack of compensation for COVID-19-related overtime work and its association with burnout among EMS providers in Korea.

OBJECTIVES: This study examined the association between lack of compensation for COVID-19-related overtime work (LCCOW) and burnout among emergency medical service (EMS) providers in Seoul, Korea. METHODS: We conducted a cross-sectional survey of 693 EMS providers in Seoul, Korea. Participants were classified into 3 groups according to their experience of coronavirus disease 2019 (COVID-19)-related overtime work and LCCOW: (1) "did not experience," (2) "experienced and was compensated," and (3) "experienced and was not compensated." Burnout was measured using the Korean version of the Copenhagen Burnout Inventory, which has 3 subdomains: personal burnout (PB), work-related burnout (WRB), and citizen-related burnout (CRB). Multiple linear regression was applied to examine whether LCCOW was associated with burnout after adjusting for potential confounders. RESULTS: In total, 74.2% of participants experienced COVID-19-related overtime work, and 14.6% of those who worked overtime experienced LCCOW. COVID-19-related overtime work showed a statistically non-significant association with burnout. However, the association differed by LCCOW. Compared to the "did not experience" group, the "experienced and was not compensated" group was associated with PB (ß=10.519; 95% confidence interval [CI], 3.455 to 17.584), WRB (ß=10.339; 95% CI, 3.398 to 17.280), and CRB (ß=12.290; 95% CI, 6.900 to 17.680), whereas no association was observed for the "experienced and was compensated" group. Furthermore, an analysis restricted to EMS providers who worked overtime due to COVID-19 showed that LCCOW was associated with PB (ß=7.970; 95% CI, 1.064 to 14.876), WRB (ß=7.276; 95% CI, 0.270 to 14.283), and CRB (ß=10.000; 95% CI, 3.435 to 16.565). CONCLUSIONS: This study suggests that LCCOW could be critical in worsening burnout among EMS providers who worked overtime due to COVID-19.

A Study on the Interoperability Technology of Digital Identification Based on WACI Protocol with Multiparty Distributed Signature.

In digital identity authentication, credentials are typically stored in a digital wallet and authenticated through a single key-based signature and public key verification. However, ensuring compatibility between systems and credentials can be challenging and the existing architecture can create a single point of failure, which can hinder system stability and prevent data interchange. To address this problem, we propose a multiparty distributed signature structure using FROST, a Schnorr signature-based threshold signature algorithm, applied to the WACI protocol framework for credential interaction. This approach eliminates a single point of failure and secures the signer's anonymity. Additionally, by following standard interoperability protocol procedures, we can ensure interoperability during the exchange of digital wallets and credentials. This paper presents a method that combines a multiparty distributed signature algorithm and an interoperability protocol, and discusses the implementation results.

Efficacy of a Novel Pleiotropic MMP-Inhibitor, CMC2.24, in a Long-Term Diabetes Rat Model with Severe Hyperglycemia-Induced Oral Bone Loss.

Purpose: CMC2.24, a novel 4-(phenylaminocarbonyl)-chemically-modified-curcumin, is a pleiotropic MMP-Inhibitor of various inflammatory/collagenolytic diseases including periodontitis. This compound has demonstrated efficacy in host modulation therapy along with improved resolution of inflammation in various study models. The objective of current study is to determine the efficacy of CMC2.24 in reducing the severity of diabetes, and its long-term role as an MMP-inhibitor, in a rat model. Methods: Twenty-one adult male Sprague-Dawley rats were randomly distributed into three groups: Normal (N), Diabetic (D) and Diabetic+CMC2.24 (D+2.24). All three groups were orally administered vehicle: carboxymethylcellulose alone (N, D), or CMC2.24 (D+2.24; 30mg/kg/day). Blood was collected at 2-months and 4-months' time-point. At completion, gingival tissue and peritoneal washes were collected/analyzed, and jaws examined for alveolar bone loss by micro-CT. Additionally, sodium hypochlorite(NaClO)-activation of human-recombinant (rh) MMP-9 and its inhibition by treatment with 10µM CMC2.24, Doxycycline, and Curcumin were evaluated. Results: CMC2.24 significantly reduced the levels of lower-molecular-weight active-MMP-9 in plasma. Similar trend of reduced active-MMP-9 was also observed in cell-free peritoneal and pooled gingival extracts. Thus, treatment substantially decreased conversion of pro- to actively destructive proteinase. Normalization of the pro-inflammatory cytokine (IL-1ß, resolvin-RvD1), and diabetes-induced osteoporosis was observed in presence of CMCM2.24. CMC2.24 also exhibited significant anti-oxidant activity by inhibiting the activation of MMP-9 to a lower-molecular-weight (82kDa) pathologically active form. All these systemic and local effects were observed in the absence of reduction in severity of hyperglycemia. Conclusion: CMC2.24 reduced activation of pathologic active-MMP-9, normalized diabetic osteoporosis, and promoted resolution of inflammation but had no effect on the hyperglycemia in diabetic rats. This study also highlights the role of MMP-9 as an early/sensitive biomarker in the absence of change in any other biochemical parameter. CMC2.24 also inhibited significant activation of pro-MMP-9 by NaOCl (oxidant) adding to known mechanisms by which this compound treats collagenolytic/inflammatory diseases including periodontitis.

AI-based analysis of 3D position and orientation of red blood cells using a digital in-line holographic microscopy.

The morphological and mechanical characteristics of red blood cells (RBCs) largely vary depending on the occurrence of hematologic disorders. Variations in the rheological properties of RBCs affect the dynamic motions of RBCs, especially their rotational behavior. However, conventional techniques for measuring the orientation of biconcave-shaped RBCs still have some technical limitations, including complicated optical setups, complex post data processing, and low throughput. In this study, we propose a novel image-based technique for measuring 3D position and orientation of normal RBCs using digital in-line holographic microscopy (DIHM) and artificial intelligence (AI). Formaldehyde-fixed RBCs are immobilized in coagulated polydimethylsiloxane (PDMS). Holographic images of RBCs positioned at various out-of-plane angles are acquired by precisely manipulating the PDMS-trapped RBC sample attached to a 4-axis optical stage. With the aid of deep learning algorithms for data augmentation and regression analysis, the out-of-plane angle of RBCs is directly predicted from the captured holographic images. The 3D position and in-plane angle of RBCs are acquired by employing numerical reconstruction and ellipse detection methods. Combining these digital image processing techniques, the 3D positional and orientational information of each RBC recorded in a single holographic image is measured within 23.5 and 3.07 s, respectively. The proposed AI-based DIHM technique that can extract the 3D position, orientation, and morphology of individual RBCs would be utilized to analyze the dynamic translational and rotational motions of abnormal RBCs with hematologic disorders in shear flows through further research.

Compound-level identification of sasang constitution type-specific personalized herbal medicine using data science approach.

Introduction: Sasang Constitutional Medicine (SCM) is a type of traditional Korean medicine where patients are classified as one of four Sasang constitution types (Sasang type) and medications consisting of medicinal herbs are prescribed according to the Sasang type. Despite the importance of personalized medicine, the operation mechanism is largely unknown. To gain a better understanding, we investigated the compound information that composes Sasang type-specific personalized herbal medicines on both multivariate and univariate levels. Methods: Five machine learning classifiers including extremely randomized trees (ERT) were trained to investigate whether the Sasang type can be explained by compound information at the multivariate level. Hierarchical clustering was conducted to determine whether compounds are processed distributedly or specifically. Taxonomic and biosynthetic analyses were conducted on these compounds. A univariate level statistical test was conducted to provide more robust Sasang type-specific compound information. Results: Using the trained ERT classifier, sixty important compounds were extracted. The sixty compounds were clustered into three groups, corresponding to each Sasang type-prominent compounds, suggesting that most compounds have specific preference for the Sasang type. Structural and biosynthetic characteristics of these Sasang type-prominent compounds were determined based on taxonomy and pathway analyses. Fourteen compounds showed statistically significant relevance with the Sasang type. Additionally, we predicted the Sasang type of unknown herbs, which were confirmed by their biological effects in functional assays. Conclusion: This study investigated the personalized herbal medicines of the SCM using compound information. This study provided information on the chemical characteristics of the compounds that are essential for classifying the Sasang type of medicinal herbs, as well as predictions regarding the Sasang type of the commonly used but unidentified medicinal herbs.

3D printable conductive composite inks for the fabrication of biocompatible electrodes in tissue engineering application.

Native tissues are affected by the microenvironment surrounding the tissue, including electrical activities. External electrical stimulation, which is used in replicating electrical activities and regulating cell behavior, is mainly applied in neural and cardiac tissues due to their electrophysiological properties. The in vitro cell culture platform with electrodes provides precise control of the stimulation property and eases the observation of the effects on the cells. The frequently used electrodes are metal or carbon rods, but their risk of damaging tissue and their mechanical properties that are largely different from those of native tissues hinder further applications. Biocompatible polymer reinforced with conductive fillers emerges as a potential solution to fabricate the complex structure of the platform and electrode. Conductive polymer can be used as an ink in the extrusion-based printing method, thus enabling the fabrication of volumetric structures. The filler simultaneously alters the electrical and rheological properties of the ink; therefore, the amount of additional compound should be precisely determined regarding printability and conductivity. This review provides an overview on the rheology and conductivity change relative to the concentration of conductive fillers and the applications of printed electrodes. Next, we discuss the future potential use of a cell culture platform with electrodes from in vitro and in vivo perspectives.

Accelerated settling velocity of airborne particulate matter on hairy plant leaves.

Phytoremediation has emerged as an ecofriendly technique to reduce hazardous particulate matter (PM) in the air. Although previous studies have conducted statistical analyses to reveal PM removal capabilities of various plant species according to their leaf characteristics, the underlying physical mechanism of PM adsorption of plants remains unclear. Conventional methodologies for measuring PM accumulation usually require long-term field tests and provide limited understanding on PM removal effects of individual leaf traits of various plants. In this study, we propose a novel methodology which can compare the electrostatic interactions between PMs and plant leaves according to their trichome structures by using digital in-line holographic microscopy (DIHM). Surface characteristics of Perilla frutescens and Capsicum annuum leaves are measured to examine electrostatic effects according to the morphological features of trichomes. 3D settling motions of PMs near the microstructures of trichomes of the two plant species are compared in detail. To validate the PM removal effect of the hairy microstructures, a polydimethylsiloxane (PDMS) replica model of a P. frutescens leaf is fabricated to demonstrate accelerated settling velocities of PMs near trichome-like microstructures. The size and electric charge distributions of PMs with irregular shapes are analyzed using DIHM. Numerical simulation of the PM deposition near a trichome-like structure is conducted to verify the empirical results. As a result, the settling velocities of PMs on P. frutescens leaves and a PDMS replica sample are 12.11 ± 1.88% and 34.06 ± 4.19% faster than those on C. annuum leaves and a flat PDMS sample, respectively. These findings indicate that the curved microstructures of hairy trichomes of plant leaves increase the ability to capture PMs by enhancing the electric field intensity just near trichomes. Compared with conventional methods, the proposed methodology can quantitatively evaluate the settling velocity of PMs on various plant leaves according to the morphological structure and density of trichomes within a short period of time. The present research findings would be widely utilized in the selection of suitable air-purifying plants for sustainable removal of harmful air pollutants in urban and indoor environments.