Thresholding Computing with Heterogeneous Integration of Memristive Kernel with Metal-Oxide-Semiconductor Capacitor for Temporal Data Analysis.

Precise event detection within time-series data is increasingly critical, particularly in noisy environments. Reservoir computing, a robust computing method widely utilized with memristive devices, is efficient in processing temporal signals. However, it typically lacks intrinsic thresholding mechanisms essential for precise event detection. This study introduces a new approach by integrating two Pt/HfO2/TiN (PHT) memristors and one Ni/HfO2/n-Si (NHS) metal-oxide-semiconductor capacitor (2M1MOS) to implement a tunable thresholding function. The current-voltage nonlinearity of memristors combined with the capacitance-voltage nonlinearity of the capacitor forms the basis of the 2M1MOS kernel system. The proposed kernel hardware effectively records feature-specified information of the input signal onto the memristors through capacitive thresholding. In electrocardiogram analysis, the memristive response exhibited a more than ten-fold difference between arrhythmia and normal beats. In isolated spoken digit classification, the kernel achieved an error rate of only 0.7% by tuning thresholds for various time-specific conditions. The kernel is also applied to biometric authentication by extracting personal features using various threshold times, presenting more complex and multifaceted uses of heartbeats and voice data as bio-indicators. These demonstrations highlight the potential of thresholding computing in a memristive framework with heterogeneous integration.

Association between single-person household wage workers in South Korea and insomnia symptoms: the 6th Korean Working Conditions Survey (KWCS).

BACKGROUND: The rise in single-person households is a global phenomenon with well-documented implications for both physical and mental well-being. However, there remains a scarcity of studies focusing specifically on the health impacts of single-person households on workers. This study aims to address this gap by comparing insomnia symptoms between single- and multi-person household workers, shedding light on the health implications of household composition. METHODS: This study utilized data from the Sixth Korean Working Conditions Survey. Insomnia symptoms were categorized into normal sleep and insomnia symptom groups utilizing the 3-item Minimal Insomnia Symptom Scale. Multiple logistic regression analysis was employed to examine the association between single-person household wage workers and insomnia symptoms. RESULTS: In comparison to wage workers from multi-person households, those from single-person households exhibited heightened risks of reporting insomnia symptoms. In the fully adjusted model, the odds ratios for symptoms of insomnia among single-person household wage workers was 1.173 (95% confidence interval: 1.020-1.349). CONCLUSIONS: This study underscores that single-person household wage workers in Korea face an elevated risk of insomnia symptoms compared to their counterparts in multi-person households.

The impact of pulmonary tuberculosis on SARS-CoV-2 infection: a nationwide cohort study.

Background: The interaction between COVID-19 and tuberculosis (TB) is not yet fully understood, and large-scale research on the mortality outcome of such dual infection has been limited. This study aimed to investigate the impact of PTB on mortality among patients with COVID-19 within a Korean population by conducting an extensive analysis of a nationwide large dataset. Method: We investigated the mortality and disease severity among COVID-19 patients who had PTB in South Korea. This study analyzed 462,444 out of 566,494 COVID-19 patients identified between January 2020 and December 2021. Result: A total of 203 COVID-19 with PTB patients and 812 matched COVID-19 without PTB were analyzed using 1:4 propensity score matching. COVID-19 patients with PTB exhibited higher in-hospital mortality (odds ratio (OR) 3.02, 95% confidence interval (CI) 1.45-6.27, p-value = 0.003) and were at increased risk of requiring conventional oxygen therapy (OR 1.57, 95% CI 1.10-2.25, p-value = 0.013) as well as high flow nasal cannula (HFNC) or noninvasive ventilation (NIV) oxygen therapy (OR 1.91, 95 CI 1.10-3.32, p-value = 0.022) compared to those without PTB. Compared to matched COVID-19 without PTB, co-infected patients showed increased mortality rates across various timeframes, including during hospitalization, and at 30 day and 90 day intervals. In-hospital mortality rates were particularly elevated among women, individuals with malignancy, and those with lower incomes. Furthermore, the increased in-hospital mortality among PTB patients persisted irrespective of the timing of TB diagnosis or vaccination status against COVID-19. Conclusion: We suggest that physicians be aware of the risk of mortality and severity among COVID-19 patients with PTB; coinfection with COVID-19 is a critical situation that remains to be further explored and needs more attention in countries with an intermediate to high PTB burden.

Combustion visualization analysis of alternative fuels in the pulverized coal injection raceway through laminar flow reactor.

Currently, the steelmaking process uses a pulverized coal injection (PCI) system that serves as the heat source and reductant for ironmaking (blast furnace and FINEX) where system uses expensive high-grade coal and high operating costs. Hydrogen steelmaking is currently being developed to achieve carbon-free operation. To achieve a soft-landing during this phase of rapid change, the use of biomass and inexpensive, thermal coal, and coke dust is necessary. Research on their combustion characteristics is necessary to apply these alternative fuels to PCI. Therefore, this study analyzed the combustion characteristics of ignition delay, devolatilization, and char combustion using a laminar flow reactor visualization equipment that simulates blast furnace (BF) and FINEX PCI tuyere, using flame image data processing. The ignition time were generally longer in BF than in FINEX, and the char combustion length and time also showed the same trend due to the high oxygen rate which indicate under 2 ms on ignition delay, under 16 ms on char combustion. Also, the volatile cloud was qualitatively shown in the image to be highest in thermal coal and biomass with high volatile matter. Based on the correlation and theoretical calculation with proximate analysis and the results, ignition delay time had a combined effect of volatile matter and moisture except coke dust, and char combustion time affected unburned carbon. The combustion chemical characteristics were discussed with chemical percolation devolatilization (CPD) model parameter. Through SEM image and BET analysis, the surface area has been increased more than 10 times after combustion. Consequently, the biomass and high moisture thermal coal could cofired within 10 % and coke dust could be cofired within 9 %, respectively.

Spatiotemporally modulated full-polarized light emission for multiplexed optical encryption.

Spatiotemporal control of full freedoms of polarized light emission is crucial in multiplexed optical computing, encryption and communication. Although recent advancements have been made in active emission or passive conversion of polarized light through solution-processed nanomaterials or metasurfaces, these design paths usually encounter limitations, such as small polarization degrees, low light utilization efficiency, limited polarization states, and lack of spatiotemporal control. Here, we addressed these challenges by integrating the spatiotemporal modulation of the LED device, the precise control and efficient polarization emission through nanomaterial assembly, and the programmable patterning/positioning using 3D printing. We achieved an extremely high degree of polarization for both linearly and circularly polarized emission from ultrathin inorganic nanowires and quantum nanorods thanks to the shear-force-induced alignment effect during the protruding of printing filaments. Real-time polarization modulation covering the entire Poincaré sphere can be conveniently obtained through the programming of the on-off state of each LED pixel. Further, the output polarization states can be encoded by an ordered chiral plasmonic film. Our device provides an excellent platform for multiplexing spatiotemporal polarization information, enabling visible light communication with an exceptionally elevated level of physical layer security and multifunctional encrypted displays that can encode both 2D and 3D information.

Histopathological correlations of CT-based radiomics imaging biomarkers in native kidney biopsy.

BACKGROUND: Kidney biopsy is the standard of care for the diagnosis of various kidney diseases. In particular, chronic histopathologic lesions, such as interstitial fibrosis and tubular atrophy, can provide prognostic information regarding chronic kidney disease progression. In this study, we aimed to evaluate historadiological correlations between CT-based radiomic features and chronic histologic changes in native kidney biopsies and to construct and validate a radiomics-based prediction model for chronicity grade. METHODS: We included patients aged ≥ 18 years who underwent kidney biopsy and abdominal CT scan within a week before kidney biopsy. Left kidneys were three-dimensionally segmented using a deep learning model based on the 3D Swin UNEt Transformers architecture. We additionally defined isovolumic cortical regions of interest near the lower pole of the left kidneys. Shape, first-order, and high-order texture features were extracted after resampling and kernel normalization. Correlations and diagnostic metrics between extracted features and chronic histologic lesions were examined. A machine learning-based radiomic prediction model for moderate chronicity was developed and compared according to the segmented regions of interest (ROI). RESULTS: Overall, moderate correlations with statistical significance (P < 0.05) were found between chronic histopathologic grade and top-ranked radiomic features. Total parenchymal features were more strongly correlated than cortical ROI features, and texture features were more highly ranked. However, conventional imaging markers, including kidney length, were poorly correlated. Top-ranked individual radiomic features had areas under receiver operating characteristic curves (AUCs) of 0.65 to 0.74. Developed radiomics models for moderate-to-severe chronicity achieved AUCs of 0.89 (95% confidence interval [CI] 0.75-0.99) and 0.74 (95% CI 0.52-0.93) for total parenchymal and cortical ROI features, respectively. CONCLUSION: Significant historadiological correlations were identified between CT-based radiomic features and chronic histologic changes in native kidney biopsies. Our findings underscore the potential of CT-based radiomic features and their prediction model for the non-invasive assessment of kidney fibrosis.

3D printing of monolithic gravity-assisted step-emulsification device for scalable production of high viscosity emulsion droplets.

Microfluidic technology widely used in generating monodisperse emulsion droplets often suffers from complexity, scalability, applicability to practical fluids, as well as operation instability due to its susceptibility to flow perturbations, low clearance, and depletion of surfactants. Herein, we present a monolithic 3D-printed step-emulsification device (3D-PSD) for scalable and robust production of high viscosity emulsion droplets up to 208.16 mPa s, which cannot be fully addressed using conventional step-emulsification devices. By utilizing stereo-lithography (SLA), 24 triangular nozzles with a pair of 3D void flow distributors are integrated within the 3D-PSD to ensure uniform flow distribution followed by monodisperse droplet formation. The outlets positioned vertically downward enables gravity-assisted clearing to prevent droplet accumulation and thereby maintain size monodispersity. Deposition of silica nanoparticles (SiNP) within the device was also shown to alter the surface wettability from hydrophobic to hydrophilic, enabling the production of both water-in-oil (W/O) as well as oil-in-water (O/W) emulsion droplets, operated at a maximum production rate of up to 50 mL h-1. The utility of the device is further verified through continuous production of biodegradable polycaprolactone (PCL) microparticles using O/W emulsion as templates. We envision that the 3D-PSD presented in this work marks a significant leap in high-throughput production of high viscosity emulsion droplets as well as the particle analogs.

Ionic Liquid-Based Extraction of Fulvic-like Substances from Wood Sawdust: Reproducing Unique Biological Activities of Fulvic Acids Using Renewable Natural Sources.

Fulvic acids (FAs) have been commercially used in cosmetics and agronomy due to their unique biological activities, such as plant stimulation and anti-inflammatory effects. However, the extraction sources of FAs, such as peat, are currently limited. Consequently, new extraction methods using renewable resources need to be developed, while reproducing the biological functions. Here, ionic liquids (ILs) effectively extracted fulvic-like substances (FLSs) from wood sawdust. The overall molecular weight distributions of FLSs were similar to those of commercial FAs, and key organic groups (e.g., aromatic, phenolic, and methoxy groups) were also found to be shared between commercial FAs and FLSs. Detailed compositional analysis revealed by high-resolution mass spectrometry showed that the extracts contain both lignin-like and lipid-like molecules, while commercial FAs are biased toward lignin-like and carbohydrate-like molecules. FLSs generally showed better and similar performance in radical scavenging activity against ABTS+· and H2O2. Fibroblast proliferation and lettuce growth enhancements were also observed with the extract containing 1-ethyl-3-methylimidazolium acetate and triethylammonium hydrogen sulfate, respectively, which performed better than commercial FAs. Immunofluorescence staining of in vitro human follicle dermal papilla cells supports that coexpression of hair growth-related proteins can be accelerated with FLSs, and this effect was further evidenced by in vivo mouse model experiments. Finally, the reusability of ILs in the extraction process was confirmed by analyzing the structural features of FLSs from each recycling. Our findings indicate that ILs are useful for obtaining biologically functional fulvic analogs from renewable plant sources.

Analyses of Osteogenesis Imperfecta in South Korea Using the Nationwide Health Insurance Service Claim Data: A Propensity Score-Matched Study.

Osteogenesis imperfecta (OI) is the most common inherited form of bone fragility and includes a heterogeneous group of genetic disorders that most commonly result from defects associated with type I collagen. Although genetic analyses have been developed, nationwide research on the incidence and associated fractures in OI is lacking. This study aimed to investigate the patterns of OI prevalence, incidence, fracture rate, etc. in South Korea using National Health Insurance Service (NHIS) claims data. We found 1596 patients newly diagnosed with OI between March 2002 and February 2020. We evaluated the incidence, prevalence, and history of fractures, fracture site, prescription of anti-osteoporosis drugs, etc. To compare medical costs, fracture rates, and scoliosis rates, we created a control group comprising patients without OI using 1:1 propensity score matching. The prevalence of OI increased slightly each year, with an annual incidence of 20.20 per 100,000 live births. Mean fracture frequency in OI patients was 17 (2-32) times per patient and the most frequent fracture site was the lower leg. A total of 21.4% patients were prescribed anti-osteoporosis drugs, and the most popular drug was pamidronate. After 1:1 propensity score matching, in terms of scoliosis, OI patients had a 3.91 times higher prevalence of scoliosis than in healthy patients which was statistically significant. The sum of medical care expenses for patients with OI was 3.5 times higher than that for patients without OI. We identified nationwide trends in OI occurrence, fractures, and medication use. This study also highlighted the real-world data of scoliosis and medical costs compared to the control group.

In-Materia Annealing and Combinatorial Optimization Based on Vertical Memristive Array.

Due to its area and energy efficiency, a memristive crossbar array (CBA) has been extensively studied for various combinatorial optimization applications, from network problems to circuit design. However, conventional approaches include heavily burdening software fine-tuning for the annealing process. Instead, this study introduces the "in-materia annealing" method, where the inter-layer interference of vertically stacked memristive CBA is utilized as an annealing method. When mapping combinatorial optimization problems into the configuration layer of the CBA, exponentially decaying annealing profiles are generated in nearby noise layers. Moreover, in-materia annealing profiles can be controlled by changing compliance current, read voltage, and read pulse width. Therefore, the annealing profiles can be arbitrarily controlled and generated individually for each cell, providing rich noise sources to solve the problem efficiently. Consequently, the experimental and simulation of Max-Cut and weighted Max-Cut problems achieve notable results with the minimum software burden.

High-Dimensional Physical Reservoir with Back-End-of-Line-Compatible Tin Monoxide Thin-Film Transistor.

This work demonstrates a physical reservoir using a back-end-of-line compatible thin-film transistor (TFT) with tin monoxide (SnO) as the channel material for neuromorphic computing. The electron trapping and time-dependent detrapping at the channel interface induce the SnO·TFT to exhibit fading memory and nonlinearity characteristics, the critical assets for physical reservoir computing. The three-terminal configuration of the TFT allows the generation of higher-dimensional reservoir states by simultaneously adjusting the bias conditions of the gate and drain terminals, surpassing the performances of typical two-terminal-based reservoirs such as memristors. The high-dimensional SnO TFT reservoir performs exceptionally in two benchmark tests, achieving a 94.1% accuracy in Modified National Institute of Standards and Technology handwritten number recognition and a normalized root-mean-square error of 0.089 in Mackey-Glass time-series prediction. Furthermore, it is suitable for vertical integration because its fabrication temperature is <250 °C, providing the benefit of achieving a high integration density.

Research reviews on myosin head interactions with F-actin.

The sliding filament theory and the cross-bridge model have been fundamental in understanding muscle contraction. While the cross-bridge model explains the interaction between a single myosin head and actin filament, the native myosin molecule consists of two heads. This review explores the possibility and mechanism of two-headed binding in myosin II to the actin. Recent studies using electron tomography and resonance energy transfer have provided evidence in support of the occurrence of two-headed binding. The flexibility of the regulatory light chain (RLC) appears to play a significant role in enabling this binding mode. However, high-resolution structures of the RLCs in the two-headed bound state have not yet been reported. Resolving these structures, possibly through sub-tomogram averaging or single-particle analysis, would provide definitive proof of the conformational flexibility of RLCs and their role in facilitating two-headed binding. Further investigations are also required to address questions such as the predominance of two-headed versus single-headed binding and the influence of the state of each of the heads on the other. An understanding of the mechanism of two-headed binding is crucial for developing a comprehensive model of the cross-bridge cycle of the native myosin molecule.

Heterogeneous density-based clustering with a dual-functional memristive array.

In the big data era, the requirement for data clustering methods that can handle massive and heterogeneous datasets with varying distributions increases. This study proposes a clustering algorithm for data sets with heterogeneous density using a dual-mode memristor crossbar array for data clustering. The array consists of a Ta/HfO2/RuO2 memristor operating in analog or digital modes, controlled by the reset voltage. The digital mode shows low dispersion and a high resistance ratio, and the analog mode enables precise conductance tuning. The local outlier factor is introduced to handle a heterogeneous density, and the required Euclidean and K-distances within the given dataset are calculated in the analog mode in parallel. In the digital mode, clustering is performed based on the connectivity among data points after excluding the detected outliers. The proposed algorithm boasts linear time complexity for the entire process. Extensive evaluations of synthetic datasets demonstrate significant improvement over representative density-based algorithms, and the datasets with heterogeneous density are clustered feasibly. Finally, the proposed algorithm is used to cluster the single-molecule localization microscopy data, demonstrating the feasibility of the suggested method for real-world problems.

Memristive Crossbar Array-Based Probabilistic Graph Modeling.

Modern graph datasets with structural complexity and uncertainties due to incomplete information or data variability require advanced modeling techniques beyond conventional graph models. This study introduces a memristive crossbar array (CBA)-based probabilistic graph model (C-PGM) utilizing Cu0.3Te0.7/HfO2/Pt memristors, which exhibit probabilistic switching, self-rectifying, and memory characteristics. C-PGM addresses the complexities and uncertainties inherent in structural graph data across various domains, leveraging the probabilistic nature of memristors. C-PGM relies on the device-to-device variation across multiple memristive CBAs, overcoming the limitations of previous approaches that rely on sequential operations, which are slower and have a reliability concern due to repeated switching. This new approach enables the fast processing and massive implementation of probabilistic units at the expense of chip area. In this study, the hardware-based C-PGM feasibly expresses small-scale probabilistic graphs and shows minimal error in aggregate probability calculations. The probability calculation capabilities of C-PGM are applied to steady-state estimation and the PageRank algorithm, which is implemented on a simulated large-scale C-PGM. The C-PGM-based steady-state estimation and PageRank algorithm demonstrate comparable accuracy to conventional methods while significantly reducing computational costs.

Insights into Actin Isoform-Specific Interactions with Myosin via Computational Analysis.

Actin, which plays a crucial role in cellular structure and function, interacts with various binding proteins, notably myosin. In mammals, actin is composed of six isoforms that exhibit high levels of sequence conservation and structural similarity overall. As a result, the selection of actin isoforms was considered unimportant in structural studies of their binding with myosin. However, recent high-resolution structural research discovered subtle structural differences in the N-terminus of actin isoforms, suggesting the possibility that each actin isoform may engage in specific interactions with myosin isoforms. In this study, we aimed to explore this possibility, particularly by understanding the influence of different actin isoforms on the interaction with myosin 7A. First, we compared the reported actomyosin structures utilizing the same type of actin isoforms as the high-resolution filamentous skeletal α-actin (3.5 Å) structure elucidated using cryo-EM. Through this comparison, we confirmed that the diversity of myosin isoforms leads to differences in interaction with the actin N-terminus, and that loop 2 of the myosin actin-binding sites directly interacts with the actin N-terminus. Subsequently, with the aid of multiple sequence alignment, we observed significant variations in the length of loop 2 across different myosin isoforms. We predicted that these length differences in loop 2 would likely result in structural variations that would affect the interaction with the actin N-terminus. For myosin 7A, loop 2 was found to be very short, and protein complex predictions using skeletal α-actin confirmed an interaction between loop 2 and the actin N-terminus. The prediction indicated that the positively charged residues present in loop 2 electrostatically interact with the acidic patch residues D24 and D25 of actin subdomain 1, whereas interaction with the actin N-terminus beyond this was not observed. Additionally, analyses of the actomyosin-7A prediction models generated using various actin isoforms consistently yielded the same results regardless of the type of actin isoform employed. The results of this study suggest that the subtle structural differences in the N-terminus of actin isoforms are unlikely to influence the binding structure with short loop 2 myosin 7A. Our findings are expected to provide a deeper understanding for future high-resolution structural binding studies of actin and myosin.

Chronic periodontitis and risk of lung cancer: a nationwide cohort study.

Background: The impact of long-term chronic periodontal conditions on the risk of lung cancer could not be accurately evaluated. Our aim was to provide more evidence on the connection between chronic periodontitis (CP) and lung cancer using a nationwide dataset. Methods: This study used data from the Korean National Health Insurance Service National Sample Cohort. We enrolled 72,658 individuals with CP (CP cohort) between 2005 and 2019 and 1:1 age- and sex-matched controls without CP (non-CP cohort). Results: During the median follow-up period of 5.1 (interquartile range, 2.8-8.0) years, 0.56% (n = 405/72,658) of the CP cohort and 0.29% (n = 212/72,658) of the matched non-CP cohort developed lung cancer, with incidence rates of 8.3 and 4.5 per 10,000 person-years. The risk of incident lung cancer was significantly higher in the CP cohort than in the matched non-CP cohort (adjusted hazard ratio = 2.27, 95% confidence interval = 1.94-2.65). The risk of incident lung cancer was 2.45-fold and 2.10-fold higher in mild and moderate-to-severe CP cohorts than in the matched non-CP control. The risk of incident lung cancer was especially higher in the 40-59 age group, females, and never-smokers than their counterparts. Conclusion: We demonstrate that the risk of incident lung cancer is higher in individuals with CP than in those without. The risk of lung cancer was especially high in individuals with more severe CP, females, never-smokers, and obese populations.

Comparison of Metabarcoding and Microscopy Methodologies to Analyze Diatom Communities in Five Estuaries Along the Southern Coast of the Korean Peninsula.

The study of microalgal communities is critical for understanding aquatic ecosystems. These communities primarily comprise diatoms (Heterokontophyta), with two methods commonly used to study them: Microscopy and metabarcoding. However, these two methods often deliver different results; thus, their suitability for analyzing diatom communities is frequently debated and evaluated. This study used these two methods to analyze the diatom communities in identical water samples and compare the results. The taxonomy of the species constituting the diatom communities was confirmed, and both methods showed that species belonging to the orders Bacillariales and Naviculales (class Bacillariophyceae) are the most diverse. In the lower taxonomic levels (family, genus, and species), microscopy tended to show a bias toward detecting diatom species (Nitzschia frustulum, Nitzschia inconspicua, Nitzschia intermedia, Navicula gregaria, Navicula perminuta, Navicula recens, Navicula sp.) belonging to the Bacillariaceae and Naviculaceae families. The results of the two methods differed in identifying diatom species in the communities and analyzing their structural characteristics. These results are consistent with the fact that diatoms belonging to the genera Nitzschia and Navicula are abundant in the communities; furthermore, only the Illumina MiSeq data showed the abundance of the Melosira and Entomoneis genera. The results obtained from microscopy were superior to those of Illumina MiSeq regarding species-level identification. Based on the results obtained via microscopy and Illumina MiSeq, it was revealed that neither method is perfect and that each has clear strengths and weaknesses. Therefore, to analyze diatom communities effectively and accurately, these two methods should be combined.

Memristors with Tunable Volatility for Reconfigurable Neuromorphic Computing.

Neuromorphic computing promises an energy-efficient alternative to traditional digital processors in handling data-heavy tasks, primarily driven by the development of both volatile (neuronal) and nonvolatile (synaptic) resistive switches or memristors. However, despite their energy efficiency, memristor-based technologies presently lack functional tunability, thus limiting their competitiveness with arbitrarily programmable (general purpose) digital computers. This work introduces a two-terminal bilayer memristor, which can be tuned among neuronal, synaptic, and hybrid behaviors. The varying behaviors are accessed via facile control over the filament formed within the memristor, enabled by the interplay between the two active ionic species (oxygen vacancies and metal cations). This solution is unlike single-species ion migration employed in most other memristors, which makes their behavior difficult to control. By reconfiguring a single crossbar array of hybrid memristors, two different applications that usually require distinct types of devices are demonstrated - reprogrammable heterogeneous reservoir computing and arbitrary non-Euclidean graph networks. Thus, this work outlines a potential path toward functionally reconfigurable postdigital computers.

Study on Awareness of Suicide and Suicide Prevention Among Community Youth.

Objectives: South Korea has the highest suicide rate among Organisation for Economic Co-operation and Development countries; there is an increasing trend in suicide attempts among middle and high school students. Various factors contribute to the risk of suicide among adolescents, and the perception of suicide prevention has emerged as a significant factor. This study aimed to investigate the association between emotional and behavioral difficulties among middle and high school students and their perceptions of suicide prevention and to explore differences in suicide perception according to age. Methods: A survey was conducted among community middle and high school students, including 530 participants, between 2020 and 2021. Emotional and behavioral difficulties were assessed using the Strengths and Difficulties Questionnaire-Korean version, and participants were asked to complete a questionnaire on the importance and possibility of suicide prevention. A correlation test and analysis of variance were used to examine the relationships between the variables, and suicide awareness was compared according to age. Results: The participants who displayed higher strength or lower difficulty were more likely to respond positively to suicide prevention measures. They also exhibited high strength and low difficulty levels, thus agreeing with the importance of suicide prevention. Regarding age-related perceptions of suicide, adults aged 20-29 years reported the lowest probability of suicide prevention. Conclusion: Suicide perceptions influence the incidence of suicide. Therefore, active societal engagement through suicide prevention campaigns and related education is essential to improve such perceptions. Continuous attention and support are required to address this issue.

Does COVID-19 vaccination increase the risk of interstitial lung disease at a population level?

This study showed a significantly lower incidence of ILD among COVID-19 vaccinated individuals compared to unvaccinated, suggesting that the risk of COVID-19 vaccine-related ILD is not as high as previously reported https://bit.ly/3TWzzxP.