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.

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.

Single-cell analysis of human PBMCs in healthy and type 2 diabetes populations: dysregulated immune networks in type 2 diabetes unveiled through single-cell profiling.

Abnormalities in glucose metabolism that precede the onset of type 2 diabetes (T2D) activate immune cells, leading to elevated inflammatory factors and chronic inflammation. However, no single-cell RNA sequencing (scRNA-seq) studies have characterized the properties and networks of individual immune cells in T2D. Here, we analyzed peripheral blood mononuclear cells (PBMCs) from non-diabetes and T2D patients by scRNA-seq. We found that CD14 monocytes in T2D patients were in a pro-inflammatory state and intermediate monocytes expressed more MHC class II genes. In T2D patients, cytotoxic CD4 T cells, effector memory CD8 T cells, and γδ T cells have increased cytotoxicity and clonal expansion. B cells were characterized by increased differentiation into intermediate B cells, plasma cells, and isotype class switching with increased expression of soluble antibody genes. These results suggest that monocytes, T cells, and B cells could interact to induce chronic inflammation in T2D patients with pro-inflammatory characteristics.

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.

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.

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.

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.

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.

Angularly offset multiline dispersive optical phased array enabling large field of view and plateau envelope.

We propose and demonstrate an angularly offset multiline (AOML) dispersive silicon nitride optical phased array (OPA) that enables efficient line beam scanning with an expanded field of view (FOV) and plateau envelope. The suggested AOML OPA incorporates multiline OPA units, which were seamlessly integrated with a 45° angular offset through a thermo-optic switch based on a multimode interference coupler, resulting in a wide FOV that combines three consecutive scanning ranges. Simultaneously, a periodic diffraction envelope rendered by the multiline OPA units contributes to reduced peak intensity fluctuation of the main lobe across the large FOV. An expedient polishing enabling the angled facet was diligently accomplished through the implementation of oblique polishing techniques applied to the 90° angle of the chip. For each dispersive OPA unit, we engineered an array of delay lines with progressively adjustable delay lengths, enabling a passive wavelength-tunable beam scanning. Experimental validation of the proposed OPA revealed efficient beam scanning, achieved by wavelength tuning from 1530 to 1600 nm and seamless switching between multiline OPAs, yielding an FOV of 152° with a main lobe intensity fluctuation of 2.8 dB. The measured efficiency of dispersive scanning was estimated at 0.97°/nm, as intended.

Individualized predictions for clinical milestone in amyotrophic lateral sclerosis: A multialgorithmic approach.

Objective: The phenotypic heterogeneity and complex disease trajectory complicate the ability to predict specific clinical milestone for individual patients with amyotrophic lateral sclerosis (ALS). Here we developed individualized prediction models to estimate the time to the loss of autonomy in swallowing function. Methods: Utilizing the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database, we built three models of distinct time-to-event prediction algorithms: accelerated failure time (AFT), cox proportional hazard (COX) and random survival forest (RSF) for an individualized risk assessment of the swallowing milestone. The target variable was defined as the time to a decline in the ALSFRS-R swallowing item score to 1 or below, indicating a need for supplementary tube feeding. Results: Internal cross-validation revealed the median concordance index (C-index) of 0.851 (IQR, 0.842-0.859) for AFT, 0.850 (0.841-0.859) for COX and 0.846 (0.839-0.854) for RSF, and all models demonstrated good distributional calibration with predicted and observed event probabilities closely matched across different time intervals. For external validation with a registry dataset with characteristics different from PRO-ACT, the discriminative power was replicated with comparable C-indices for all models, whereas the calibration revealed a left-skewed distribution suggesting a bias towards overestimation of event probabilities in real-world data. While all models were effective at stratifying patients, the results of RSF model, unlike AFT and COX, did not match well with the KM curves of the corresponding risk groups, supporting the importance of nuanced understanding of data structure and algorithmic properties. Conclusion: Our models are implemented into a web application which could be applied to individualized counselling, management and clinical trial design for gastrostomy intervention. Further studies for model optimization will advance personalized care in patients with ALS.

The Association between Family History of Lung Cancer and Development of Lung Cancer: Analysis from the KoGES Data in Korea.

Comprehensive analyses of the association between a family history of lung cancer and lung cancer risk are limited, especially in the Korean population. We used baseline data from the Korean Genome and Epidemiology Study, conducted between 2001 and 2013. This study enrolled 198,980 individuals. Lung cancer diagnoses and family histories were determined using questionnaires. Multivariable logistic regression analysis was performed to evaluate the effect of family history on the risk of lung cancer. Of 198,980 individuals, 6296 (3.2%) and 140 (0.1%) had a family history of lung cancer and lung cancer, respectively. Individuals with a family history of lung cancer in first-degree relatives (FDRs) had a higher risk of lung cancer development than those without (adjusted odds ratio [aOR] = 2.28, 95% confidence interval [CI] = 1.11-4.66). This was more pronounced in young individuals (<60 years) who had affected relatives diagnosed with lung cancer before the age of 60 years (aOR = 3.77, 95% CI = 1.19-11.88). In subgroup analyses, this association was more evident in women, never smokers, and young individuals. A family history of lung cancer, especially in FDRs, is a significant risk factor for lung cancer development in Korea.

The impact of sexual reproduction-induced vertical migration on the complexity of harmful algal blooms in Heterosigma akashiwo.

Vertical migration behaviour, which is integral to marine energy circulation, is a prevalent trait among marine organisms. However, the behaviour of phytoplankton, particularly beyond diel vertical migration (DVM), remain underexplored compared to groups like zooplankton. Through the lens of the harmful alga Heterosigma akashiwo, which exhibits unique vertical migrations and fluctuating red tide patterns, this study aimed to explore the ecological intricacies and diverse benefits of phytoplankton vertical migration behaviours. During the bloom period of H. akashiwo, we unexpectedly observed a dense concentration of cells at bottom layer during daytime. This phase coincided with the emergence of cells related to this species' sexual reproduction. Laboratory experiments further showed an elevated frequency of sexual reproduction in the cell populations that migrated to deeper depths compared to those at the surface. This finding implies a connection between dense bottom accumulation (BA) and the life cycle transitions of the species. This BA phase persisted for two days, after which the populations returned to their standard DVM behaviour, providing insight into the unique fluctuating red tide patterns of H. akashiwo. Our study suggests that phytoplankton vertical migrations are not strictly dictated by DVM, revealing diverse vertical migration behaviours that may contribute to the complexity of harmful algal bloom patterns.

Generation of an induced pluripotent stem cell line from a patient with arrhythmogenic right ventricular cardiomyopathy harboring a TMEM43 splice-site variant.

Arrhythmogenic cardiomyopathy (ACM) is a cardiomyopathy that is predominantly inherited and characterized by cardiac arrhythmias and structural abnormalities. TMEM43 (transmembrane protein 43) is one of the well-known genetic culprits behind ACM. In this study, we successfully generated an induced pluripotent stem cell (iPSC) line, YCMi010-A, derived from a male patient diagnosed with ACM. Although these iPSCs harbored a heterozygous intronic splice variant, TMEM43 c.443-2A > G, they still displayed normal cellular morphology and were confirmed to express pluripotency markers. YCMi010-A iPSC line is a promising model for investigating the pathomechanisms associated with ACM and exploring potential therapeutic strategies.

Moiré superlattices in twisted two-dimensional halide perovskites.

Moiré superlattices have emerged as a new platform for studying strongly correlated quantum phenomena, but these systems have been largely limited to van der Waals layer two-dimensional materials. Here we introduce moiré superlattices leveraging ultrathin, ligand-free halide perovskites, facilitated by ionic interactions. Square moiré superlattices with varying periodic lengths are clearly visualized through high-resolution transmission electron microscopy. Twist-angle-dependent transient photoluminescence microscopy and electrical characterizations indicate the emergence of localized bright excitons and trapped charge carriers near a twist angle of ~10°. The localized excitons are accompanied by enhanced exciton emission, attributed to an increased oscillator strength by a theoretically predicted flat band. This research showcases the promise of two-dimensional perovskites as unique room-temperature moiré materials.

Characteristics of Severe Asthma in the Elderly: Observations From the Korean Severe Asthma Registry (KoSAR).

PURPOSE: Few studies have compared the clinical characteristics of severe asthma (SA) in elderly patients compared to that in nonelderly patients. METHODS: We analyzed data from the Korean SA Registry, a nationwide, real-world observational study of SA in Korea. The baseline clinical characteristics, disease control status, and medication use of the patients were compared between elderly (≥ 65 years) and nonelderly groups. RESULTS: Of the 864 patients with SA, 260 (30.1%) were in the elderly group. The elderly group had lower atopy rate, but had higher prevalence of chronic obstructive pulmonary disease (COPD), hypertension, and osteoporosis than did the nonelderly group. The elderly group had a lower rate of type 2 inflammation and lower levels of forced expiratory volume in 1 second (FEV1) (% predicted) and FEV1/forced vital capacity ratio than did the nonelderly group (P < 0.05 for all). However, asthma symptom scores and the frequency of asthma exacerbation were not significantly different between the 2 groups. Of controller medications, biologics were less frequently used in the elderly group (P < 0.05 for all). CONCLUSIONS: SA in the elderly is characterized by lower lung function, less type 2-low airway inflammation, and comorbidity with COPD. These findings are being taken into consideration in the management of elderly patients with SA in real-world clinical practice.

The Impact of Bronchiectasis on the Clinical Characteristics of Non-Severe Asthma.

Current literature primarily delves into the relationship between bronchiectasis and severe asthma, and only a few studies have evaluated the impact of bronchiectasis in patients with non-severe asthma. Therefore, this study investigated the clinical impact of bronchiectasis in patients with non-severe asthma. A prospective observational study of 140 non-severe asthmatic patients with (bronchiectasis group) and without bronchiectasis (control group) was conducted between September 2012 and February 2022. The bronchiectasis and control groups were compared in terms of demographics, lung function, asthma control test (ACT) results, exacerbation history, and respiratory medications. Among 140 non-severe asthmatic subjects, approximately 15.7% (n = 22) had bronchiectasis. The most common type of bronchiectasis was cylindrical type (90.7%). The left lingular division was the most frequently involved lung lobe (20.4%). There were no significant differences in the demographics (age, sex, body mass index, smoking history, and comorbidities) or ACT results between the 2 groups. The bronchiectasis group used inhaled corticosteroids/long-acting ß2-agonists (P = 0.074) and mucolytics (P < 0.001) more frequently than the control group. Compared to the control group, the bronchiectasis group had lower forced expiratory volume in 1 second (FEV1) (L) (1.9 ± 0.7 L vs. 2.3 ± 0.9 L, P = 0.039) and FEV1%predicted (67.2 ± 22.2%predicted vs. 77.1 ± 20.0%predicted, P = 0.038). The rate of hospital admission to a general ward in the preceding year was significantly higher in the bronchiectasis group compared to those of the control group (23.8% vs. 3.5%, P = 0.005) with an adjusted odds ratio of 6.308 (95% confidence interval, 1.401-28.392). Patients with non-severe asthma and bronchiectasis had lower lung function and more frequent exacerbations requiring hospitalization than those without bronchiectasis. More attention is needed for asthmatic patients with bronchiectasis, even if the asthma is not severe.

Human-Unrecognizable Differential Private Noised Image Generation Method.

Differential privacy has emerged as a practical technique for privacy-preserving deep learning. However, recent studies on privacy attacks have demonstrated vulnerabilities in the existing differential privacy implementations for deep models. While encryption-based methods offer robust security, their computational overheads are often prohibitive. To address these challenges, we propose a novel differential privacy-based image generation method. Our approach employs two distinct noise types: one makes the image unrecognizable to humans, preserving privacy during transmission, while the other maintains features essential for machine learning analysis. This allows the deep learning service to provide accurate results, without compromising data privacy. We demonstrate the feasibility of our method on the CIFAR100 dataset, which offers a realistic complexity for evaluation.

Implementation of Bayesian networks and Bayesian inference using a Cu0.1Te0.9/HfO2/Pt threshold switching memristor.

Bayesian networks and Bayesian inference, which forecast uncertain causal relationships within a stochastic framework, are used in various artificial intelligence applications. However, implementing hardware circuits for the Bayesian inference has shortcomings regarding device performance and circuit complexity. This work proposed a Bayesian network and inference circuit using a Cu0.1Te0.9/HfO2/Pt volatile memristor, a probabilistic bit neuron that can control the probability of being 'true' or 'false.' Nodal probabilities within the network are feasibly sampled with low errors, even with the device's cycle-to-cycle variations. Furthermore, Bayesian inference of all conditional probabilities within the network is implemented with low power (<186 nW) and energy consumption (441.4 fJ), and a normalized mean squared error of ∼7.5 × 10-4 through division feedback logic with a variational learning rate to suppress the inherent variation of the memristor. The suggested memristor-based Bayesian network shows the potential to replace the conventional complementary metal oxide semiconductor-based Bayesian estimation method with power efficiency using a stochastic computing method.